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Cutting costs for cancer pts with comorbidities
Photo courtesy of the CDC
Patients with incurable cancer and multiple comorbidities who consulted with a palliative care team within 2 days of hospitalization had significant savings in hospital costs, according to a new study.
The study also showed that the higher number of comorbidities a patient had, the greater the reduction in direct hospital costs with early palliative care as opposed to standard care.
Previous studies have shown a link between palliative care and lower costs, but this is the first to examine whether the effect of palliative care consultation varies by the number of co-existing chronic conditions.
“We already know that coordinated, patient-centered palliative care improves care quality, enhances survival, and reduces costs for persons with cancer,” said R. Sean Morrison, MD, of the Icahn School of Medicine at Mount Sinai in New York, New York.
“Our latest research now shows the strong association between cost and the number of co-occurring conditions. Among patients with advanced cancer and other serious illnesses, aggressive treatments are often inconsistent with patients’ wishes and are associated with worse quality of life compared to other treatments. It is imperative that policymakers act to expand access to palliative care.”
Dr Morrison and his colleagues described their research in Health Affairs.
The study included 906 patients with advanced cancer and multiple comorbidities who were treated at 6 hospitals. One hundred and ninety-three patients were seen by a palliative care team within 2 days of hospitalization, while the remaining 713 patients received usual care.
Patients from the palliative care group had significantly lower total direct hospital costs if they had multimorbidity. For patients with a comorbidity score of 0–1, the estimated mean treatment effect was not significant.
However, patients with a comorbidity score of 2–3 had a 22% reduction in costs, or a reduction of $2321. Patients with a score of 4 or higher had a cost reduction of 32%, or $3515.
“The fact that we found greater cost savings for cancer patients with more comorbidities than for those with fewer comorbidities raises the question of whether similar results would be observed in patients with other serious illnesses and multimorbidity,” said Peter May, of Trinity College Dublin in Ireland.
“Future research is also needed to determine when in the course of illness palliative care is most cost-effective.” 
Photo courtesy of the CDC
Patients with incurable cancer and multiple comorbidities who consulted with a palliative care team within 2 days of hospitalization had significant savings in hospital costs, according to a new study.
The study also showed that the higher number of comorbidities a patient had, the greater the reduction in direct hospital costs with early palliative care as opposed to standard care.
Previous studies have shown a link between palliative care and lower costs, but this is the first to examine whether the effect of palliative care consultation varies by the number of co-existing chronic conditions.
“We already know that coordinated, patient-centered palliative care improves care quality, enhances survival, and reduces costs for persons with cancer,” said R. Sean Morrison, MD, of the Icahn School of Medicine at Mount Sinai in New York, New York.
“Our latest research now shows the strong association between cost and the number of co-occurring conditions. Among patients with advanced cancer and other serious illnesses, aggressive treatments are often inconsistent with patients’ wishes and are associated with worse quality of life compared to other treatments. It is imperative that policymakers act to expand access to palliative care.”
Dr Morrison and his colleagues described their research in Health Affairs.
The study included 906 patients with advanced cancer and multiple comorbidities who were treated at 6 hospitals. One hundred and ninety-three patients were seen by a palliative care team within 2 days of hospitalization, while the remaining 713 patients received usual care.
Patients from the palliative care group had significantly lower total direct hospital costs if they had multimorbidity. For patients with a comorbidity score of 0–1, the estimated mean treatment effect was not significant.
However, patients with a comorbidity score of 2–3 had a 22% reduction in costs, or a reduction of $2321. Patients with a score of 4 or higher had a cost reduction of 32%, or $3515.
“The fact that we found greater cost savings for cancer patients with more comorbidities than for those with fewer comorbidities raises the question of whether similar results would be observed in patients with other serious illnesses and multimorbidity,” said Peter May, of Trinity College Dublin in Ireland.
“Future research is also needed to determine when in the course of illness palliative care is most cost-effective.”
Photo courtesy of the CDC
Patients with incurable cancer and multiple comorbidities who consulted with a palliative care team within 2 days of hospitalization had significant savings in hospital costs, according to a new study.
The study also showed that the higher number of comorbidities a patient had, the greater the reduction in direct hospital costs with early palliative care as opposed to standard care.
Previous studies have shown a link between palliative care and lower costs, but this is the first to examine whether the effect of palliative care consultation varies by the number of co-existing chronic conditions.
“We already know that coordinated, patient-centered palliative care improves care quality, enhances survival, and reduces costs for persons with cancer,” said R. Sean Morrison, MD, of the Icahn School of Medicine at Mount Sinai in New York, New York.
“Our latest research now shows the strong association between cost and the number of co-occurring conditions. Among patients with advanced cancer and other serious illnesses, aggressive treatments are often inconsistent with patients’ wishes and are associated with worse quality of life compared to other treatments. It is imperative that policymakers act to expand access to palliative care.”
Dr Morrison and his colleagues described their research in Health Affairs.
The study included 906 patients with advanced cancer and multiple comorbidities who were treated at 6 hospitals. One hundred and ninety-three patients were seen by a palliative care team within 2 days of hospitalization, while the remaining 713 patients received usual care.
Patients from the palliative care group had significantly lower total direct hospital costs if they had multimorbidity. For patients with a comorbidity score of 0–1, the estimated mean treatment effect was not significant.
However, patients with a comorbidity score of 2–3 had a 22% reduction in costs, or a reduction of $2321. Patients with a score of 4 or higher had a cost reduction of 32%, or $3515.
“The fact that we found greater cost savings for cancer patients with more comorbidities than for those with fewer comorbidities raises the question of whether similar results would be observed in patients with other serious illnesses and multimorbidity,” said Peter May, of Trinity College Dublin in Ireland.
“Future research is also needed to determine when in the course of illness palliative care is most cost-effective.”
A Perfect Storm: The current climate in breast cancer
This is the first installment of a five-part monthly series that will discuss the pathologic, genomic, and clinical factors that contribute to the racial survival disparity in breast cancer. The series, which is adapted from an article that originally appeared in CA: A Cancer Journal for Clinicians,1 a journal of the American Cancer Society, will also review exciting and innovative interventions to close this survival gap. This month’s column reviews the scope of this important health care issue.
The National Cancer Institute’s (NCI) Surveillance, Epidemiology, and End Results Program (SEER) has estimated that 231,840 new cases of female breast cancer will be diagnosed in 2015, representing 14% of all new cancer cases among women. The NCI also has estimated 40,290 deaths from breast cancer, representing 6.8% of all cancer deaths among women.2 Breast cancer is the second leading cause of cancer death among women after lung cancer. It is well known that there has historically been a significant racial divide in breast cancer incidence (rate of new occurrences of breast cancer) and mortality (death) rates. Caucasian women were more likely to be diagnosed with breast cancer, but African American women were more likely to die from it.
However, in a recently released study by DeSantis et al. this incidence trend no longer holds, and in 2012 there was a convergence of breast cancer incidence rates at 135 cases per 100,000 women for both Caucasian and African American women.3 In addition, this recent analysis revealed that the mortality disparity between African American and Caucasian women has continued to increase, with a death rate 42% higher in African American than in Caucasian women in 2012. While overall improvements in therapy have led to a decrease in breast cancer death rates in the United States since 1990, the decreases in death rates began earlier and have been larger in proportionate terms for Caucasians than for African Americans.4,5 According to SEER data from 1975 to 2011, Caucasian women had a 23% increase in breast cancer incidence and a 34% decrease in mortality, whereas African American women experienced a 35% increase in incidence and a 2% increase in mortality.6
Beyond national statistics and on a more-local level, several studies have explored regional variations in breast cancer mortality by race. One such study analyzed mortality data from the National Center for Health Statistics from 1975 to 2004.5 The researchers discovered that trends in breast cancer death rates varied widely by region. While breast cancer death rates in Caucasian women decreased in all 50 states, among African American women in 37 states analyzed, breast cancer death rates increased in 2 states, were level in 24 states, and decreased in only 11 states. Many of the states in which African American breast cancer death rates were level or rising were in the South and Midwest.
There are also differences in age and stage at diagnosis between African American and Caucasian women. Although the overall incidence of breast cancer has been historically higher in Caucasians, the incidence profile changes when the data are looked at by age. Among African American women with breast cancer, 33% are diagnosed at an age younger than 50 years, compared with 21.9% among Caucasian women.7
In women younger than 35 years, the incidence of breast cancer in African Americans is 1.4-2.0 times that of Caucasians.8 In addition, African American women present with more advanced-stage disease. Again, using the SEER program and examining data from 2005-2011, 62% of Caucasians had localized disease (cancer confined to the breast and potentially curable) versus 53% of African Americans. In all, 5% of Caucasians had distant disease (cancer outside the breast and treatable but not curable), compared with 9% of African Americans.9 A recent study in JAMA of 373,563 women with breast cancer during 2004-2011 found that African American women were less likely to be diagnosed with stage I breast cancer than were non-Hispanic white women across all age groups (non-Hispanic white women, 50.8%; African American women, 37.0%).10
The researchers examined further those women with small breast cancers (breast tumors ≤ 2 cm) and the percentages of nodal metastases (cancer in the lymph nodes) and distant metastases (cancer outside the breast) by race/ethnicity. The authors found that an African American woman with a small-sized breast tumor was more likely to present with lymph node metastases and distant metastases. Significantly, African American women were also more likely to die of breast cancer with small-sized tumors than were non-Hispanic white women.
These differences in age and stage highlight important differences in tumor biology, genomics, and patterns of care that contribute to the disparity in breast cancer survival between Caucasian and African American women. The February installment of this column will explore tumor biology – the first element in the perfect storm.
Other installments of this column can be found in the Related Content box.
1. Daly B, Olopade OI: A perfect storm: How tumor biology, genomics, and health care delivery patterns collide to create a racial survival disparity in breast cancer and proposed interventions for change. CA Cancer J Clin. 65:221-38, 2015.
2. National Cancer Institute. Surveillance, Epidemiology, and End Results (SEER) Program Stat fact sheets: Breast cancer. Surveillance, Epidemiology, and End Results Program. http://seer.cancer.gov/statfacts/html/breast.html. Accessed Nov. 20, 2015.
3. DeSantis C, Fedewa S, Goding Sauer A, et al., Breast cancer statistics, 2015: Convergence of incidence rates between black and white women. CA: A Cancer Journal for Clinicians. doi: 10.3322/caac.21320
4. DeLancey JO, Thun MJ, Jemal A, et al.: Recent trends in Black-White disparities in cancer mortality. Cancer Epidemiol Biomarkers Prev. 17:2908-12, 2008.
5. DeSantis C, Jemal A, Ward E, et al.: Temporal trends in breast cancer mortality by state and race. Cancer Causes Control. 19:537-45, 2008.
6. Howlander N NA, Krapcho M, et al. eds.: SEER Cancer Statistics Review, 1975-2011, 2014.
7. Clarke CA, West DW, Edwards BK, et al.: Existing data on breast cancer in African-American women: what we know and what we need to know. Cancer. 97:211-21, 2003.
8. Marie Swanson G, Haslam SZ, Azzouz F: Breast cancer among young African-American women: a summary of data and literature and of issues discussed during the Summit Meeting on Breast Cancer Among African American Women, Washington, DC, September 8-10, 2000. Cancer. 97:273-9, 2003.
9. National Cancer Institute. SEER Cancer Statistics Review, 1975-2012. http://seer.cancer.gov/csr/1975_2012/results_single/sect_04_table.13.pdf. Accessed, Nov. 20, 2015.
10. Iqbal J, Ginsburg O, Rochon PA, et al: Differences in breast cancer stage at diagnosis and cancer-specific survival by race and ethnicity in the United States. JAMA 313:165-73, 2015.
Bobby Daly, MD, MBA, is the chief fellow in the section of hematology/oncology at the University of Chicago Medicine. His clinical focus is breast and thoracic oncology, and his research focus is health services. Specifically, Dr. Daly researches disparities in oncology care delivery, oncology health care utilization, aggressive end-of-life oncology care, and oncology payment models. He received his MD and MBA from Harvard Medical School and Harvard Business School, both in Boston, and a BA in Economics and History from Stanford (Calif.) University. He was the recipient of the Dean’s Award at Harvard Medical and Business Schools.
Olufunmilayo Olopade, MD, FACP, OON, is the Walter L. Palmer Distinguished Service Professor of Medicine and Human Genetics, and director, Center for Global Health at the University of Chicago. She is adopting emerging high throughput genomic and informatics strategies to identify genetic and nongenetic risk factors for breast cancer in order to implement precision health care in diverse populations. This innovative approach has the potential to improve the quality of care and reduce costs while saving more lives.
Disclosures: Dr. Olopade serves on the Medical Advisory Board for CancerIQ. Dr. Daly serves as a director of Quadrant Holdings Corporation and receives compensation from this entity. Frontline Medical Communications is a subsidiary of Quadrant Holdings Corporation.
Published in conjunction with Susan G. Komen®.
This is the first installment of a five-part monthly series that will discuss the pathologic, genomic, and clinical factors that contribute to the racial survival disparity in breast cancer. The series, which is adapted from an article that originally appeared in CA: A Cancer Journal for Clinicians,1 a journal of the American Cancer Society, will also review exciting and innovative interventions to close this survival gap. This month’s column reviews the scope of this important health care issue.
The National Cancer Institute’s (NCI) Surveillance, Epidemiology, and End Results Program (SEER) has estimated that 231,840 new cases of female breast cancer will be diagnosed in 2015, representing 14% of all new cancer cases among women. The NCI also has estimated 40,290 deaths from breast cancer, representing 6.8% of all cancer deaths among women.2 Breast cancer is the second leading cause of cancer death among women after lung cancer. It is well known that there has historically been a significant racial divide in breast cancer incidence (rate of new occurrences of breast cancer) and mortality (death) rates. Caucasian women were more likely to be diagnosed with breast cancer, but African American women were more likely to die from it.
However, in a recently released study by DeSantis et al. this incidence trend no longer holds, and in 2012 there was a convergence of breast cancer incidence rates at 135 cases per 100,000 women for both Caucasian and African American women.3 In addition, this recent analysis revealed that the mortality disparity between African American and Caucasian women has continued to increase, with a death rate 42% higher in African American than in Caucasian women in 2012. While overall improvements in therapy have led to a decrease in breast cancer death rates in the United States since 1990, the decreases in death rates began earlier and have been larger in proportionate terms for Caucasians than for African Americans.4,5 According to SEER data from 1975 to 2011, Caucasian women had a 23% increase in breast cancer incidence and a 34% decrease in mortality, whereas African American women experienced a 35% increase in incidence and a 2% increase in mortality.6
Beyond national statistics and on a more-local level, several studies have explored regional variations in breast cancer mortality by race. One such study analyzed mortality data from the National Center for Health Statistics from 1975 to 2004.5 The researchers discovered that trends in breast cancer death rates varied widely by region. While breast cancer death rates in Caucasian women decreased in all 50 states, among African American women in 37 states analyzed, breast cancer death rates increased in 2 states, were level in 24 states, and decreased in only 11 states. Many of the states in which African American breast cancer death rates were level or rising were in the South and Midwest.
There are also differences in age and stage at diagnosis between African American and Caucasian women. Although the overall incidence of breast cancer has been historically higher in Caucasians, the incidence profile changes when the data are looked at by age. Among African American women with breast cancer, 33% are diagnosed at an age younger than 50 years, compared with 21.9% among Caucasian women.7
In women younger than 35 years, the incidence of breast cancer in African Americans is 1.4-2.0 times that of Caucasians.8 In addition, African American women present with more advanced-stage disease. Again, using the SEER program and examining data from 2005-2011, 62% of Caucasians had localized disease (cancer confined to the breast and potentially curable) versus 53% of African Americans. In all, 5% of Caucasians had distant disease (cancer outside the breast and treatable but not curable), compared with 9% of African Americans.9 A recent study in JAMA of 373,563 women with breast cancer during 2004-2011 found that African American women were less likely to be diagnosed with stage I breast cancer than were non-Hispanic white women across all age groups (non-Hispanic white women, 50.8%; African American women, 37.0%).10
The researchers examined further those women with small breast cancers (breast tumors ≤ 2 cm) and the percentages of nodal metastases (cancer in the lymph nodes) and distant metastases (cancer outside the breast) by race/ethnicity. The authors found that an African American woman with a small-sized breast tumor was more likely to present with lymph node metastases and distant metastases. Significantly, African American women were also more likely to die of breast cancer with small-sized tumors than were non-Hispanic white women.
These differences in age and stage highlight important differences in tumor biology, genomics, and patterns of care that contribute to the disparity in breast cancer survival between Caucasian and African American women. The February installment of this column will explore tumor biology – the first element in the perfect storm.
Other installments of this column can be found in the Related Content box.
1. Daly B, Olopade OI: A perfect storm: How tumor biology, genomics, and health care delivery patterns collide to create a racial survival disparity in breast cancer and proposed interventions for change. CA Cancer J Clin. 65:221-38, 2015.
2. National Cancer Institute. Surveillance, Epidemiology, and End Results (SEER) Program Stat fact sheets: Breast cancer. Surveillance, Epidemiology, and End Results Program. http://seer.cancer.gov/statfacts/html/breast.html. Accessed Nov. 20, 2015.
3. DeSantis C, Fedewa S, Goding Sauer A, et al., Breast cancer statistics, 2015: Convergence of incidence rates between black and white women. CA: A Cancer Journal for Clinicians. doi: 10.3322/caac.21320
4. DeLancey JO, Thun MJ, Jemal A, et al.: Recent trends in Black-White disparities in cancer mortality. Cancer Epidemiol Biomarkers Prev. 17:2908-12, 2008.
5. DeSantis C, Jemal A, Ward E, et al.: Temporal trends in breast cancer mortality by state and race. Cancer Causes Control. 19:537-45, 2008.
6. Howlander N NA, Krapcho M, et al. eds.: SEER Cancer Statistics Review, 1975-2011, 2014.
7. Clarke CA, West DW, Edwards BK, et al.: Existing data on breast cancer in African-American women: what we know and what we need to know. Cancer. 97:211-21, 2003.
8. Marie Swanson G, Haslam SZ, Azzouz F: Breast cancer among young African-American women: a summary of data and literature and of issues discussed during the Summit Meeting on Breast Cancer Among African American Women, Washington, DC, September 8-10, 2000. Cancer. 97:273-9, 2003.
9. National Cancer Institute. SEER Cancer Statistics Review, 1975-2012. http://seer.cancer.gov/csr/1975_2012/results_single/sect_04_table.13.pdf. Accessed, Nov. 20, 2015.
10. Iqbal J, Ginsburg O, Rochon PA, et al: Differences in breast cancer stage at diagnosis and cancer-specific survival by race and ethnicity in the United States. JAMA 313:165-73, 2015.
Bobby Daly, MD, MBA, is the chief fellow in the section of hematology/oncology at the University of Chicago Medicine. His clinical focus is breast and thoracic oncology, and his research focus is health services. Specifically, Dr. Daly researches disparities in oncology care delivery, oncology health care utilization, aggressive end-of-life oncology care, and oncology payment models. He received his MD and MBA from Harvard Medical School and Harvard Business School, both in Boston, and a BA in Economics and History from Stanford (Calif.) University. He was the recipient of the Dean’s Award at Harvard Medical and Business Schools.
Olufunmilayo Olopade, MD, FACP, OON, is the Walter L. Palmer Distinguished Service Professor of Medicine and Human Genetics, and director, Center for Global Health at the University of Chicago. She is adopting emerging high throughput genomic and informatics strategies to identify genetic and nongenetic risk factors for breast cancer in order to implement precision health care in diverse populations. This innovative approach has the potential to improve the quality of care and reduce costs while saving more lives.
Disclosures: Dr. Olopade serves on the Medical Advisory Board for CancerIQ. Dr. Daly serves as a director of Quadrant Holdings Corporation and receives compensation from this entity. Frontline Medical Communications is a subsidiary of Quadrant Holdings Corporation.
Published in conjunction with Susan G. Komen®.
This is the first installment of a five-part monthly series that will discuss the pathologic, genomic, and clinical factors that contribute to the racial survival disparity in breast cancer. The series, which is adapted from an article that originally appeared in CA: A Cancer Journal for Clinicians,1 a journal of the American Cancer Society, will also review exciting and innovative interventions to close this survival gap. This month’s column reviews the scope of this important health care issue.
The National Cancer Institute’s (NCI) Surveillance, Epidemiology, and End Results Program (SEER) has estimated that 231,840 new cases of female breast cancer will be diagnosed in 2015, representing 14% of all new cancer cases among women. The NCI also has estimated 40,290 deaths from breast cancer, representing 6.8% of all cancer deaths among women.2 Breast cancer is the second leading cause of cancer death among women after lung cancer. It is well known that there has historically been a significant racial divide in breast cancer incidence (rate of new occurrences of breast cancer) and mortality (death) rates. Caucasian women were more likely to be diagnosed with breast cancer, but African American women were more likely to die from it.
However, in a recently released study by DeSantis et al. this incidence trend no longer holds, and in 2012 there was a convergence of breast cancer incidence rates at 135 cases per 100,000 women for both Caucasian and African American women.3 In addition, this recent analysis revealed that the mortality disparity between African American and Caucasian women has continued to increase, with a death rate 42% higher in African American than in Caucasian women in 2012. While overall improvements in therapy have led to a decrease in breast cancer death rates in the United States since 1990, the decreases in death rates began earlier and have been larger in proportionate terms for Caucasians than for African Americans.4,5 According to SEER data from 1975 to 2011, Caucasian women had a 23% increase in breast cancer incidence and a 34% decrease in mortality, whereas African American women experienced a 35% increase in incidence and a 2% increase in mortality.6
Beyond national statistics and on a more-local level, several studies have explored regional variations in breast cancer mortality by race. One such study analyzed mortality data from the National Center for Health Statistics from 1975 to 2004.5 The researchers discovered that trends in breast cancer death rates varied widely by region. While breast cancer death rates in Caucasian women decreased in all 50 states, among African American women in 37 states analyzed, breast cancer death rates increased in 2 states, were level in 24 states, and decreased in only 11 states. Many of the states in which African American breast cancer death rates were level or rising were in the South and Midwest.
There are also differences in age and stage at diagnosis between African American and Caucasian women. Although the overall incidence of breast cancer has been historically higher in Caucasians, the incidence profile changes when the data are looked at by age. Among African American women with breast cancer, 33% are diagnosed at an age younger than 50 years, compared with 21.9% among Caucasian women.7
In women younger than 35 years, the incidence of breast cancer in African Americans is 1.4-2.0 times that of Caucasians.8 In addition, African American women present with more advanced-stage disease. Again, using the SEER program and examining data from 2005-2011, 62% of Caucasians had localized disease (cancer confined to the breast and potentially curable) versus 53% of African Americans. In all, 5% of Caucasians had distant disease (cancer outside the breast and treatable but not curable), compared with 9% of African Americans.9 A recent study in JAMA of 373,563 women with breast cancer during 2004-2011 found that African American women were less likely to be diagnosed with stage I breast cancer than were non-Hispanic white women across all age groups (non-Hispanic white women, 50.8%; African American women, 37.0%).10
The researchers examined further those women with small breast cancers (breast tumors ≤ 2 cm) and the percentages of nodal metastases (cancer in the lymph nodes) and distant metastases (cancer outside the breast) by race/ethnicity. The authors found that an African American woman with a small-sized breast tumor was more likely to present with lymph node metastases and distant metastases. Significantly, African American women were also more likely to die of breast cancer with small-sized tumors than were non-Hispanic white women.
These differences in age and stage highlight important differences in tumor biology, genomics, and patterns of care that contribute to the disparity in breast cancer survival between Caucasian and African American women. The February installment of this column will explore tumor biology – the first element in the perfect storm.
Other installments of this column can be found in the Related Content box.
1. Daly B, Olopade OI: A perfect storm: How tumor biology, genomics, and health care delivery patterns collide to create a racial survival disparity in breast cancer and proposed interventions for change. CA Cancer J Clin. 65:221-38, 2015.
2. National Cancer Institute. Surveillance, Epidemiology, and End Results (SEER) Program Stat fact sheets: Breast cancer. Surveillance, Epidemiology, and End Results Program. http://seer.cancer.gov/statfacts/html/breast.html. Accessed Nov. 20, 2015.
3. DeSantis C, Fedewa S, Goding Sauer A, et al., Breast cancer statistics, 2015: Convergence of incidence rates between black and white women. CA: A Cancer Journal for Clinicians. doi: 10.3322/caac.21320
4. DeLancey JO, Thun MJ, Jemal A, et al.: Recent trends in Black-White disparities in cancer mortality. Cancer Epidemiol Biomarkers Prev. 17:2908-12, 2008.
5. DeSantis C, Jemal A, Ward E, et al.: Temporal trends in breast cancer mortality by state and race. Cancer Causes Control. 19:537-45, 2008.
6. Howlander N NA, Krapcho M, et al. eds.: SEER Cancer Statistics Review, 1975-2011, 2014.
7. Clarke CA, West DW, Edwards BK, et al.: Existing data on breast cancer in African-American women: what we know and what we need to know. Cancer. 97:211-21, 2003.
8. Marie Swanson G, Haslam SZ, Azzouz F: Breast cancer among young African-American women: a summary of data and literature and of issues discussed during the Summit Meeting on Breast Cancer Among African American Women, Washington, DC, September 8-10, 2000. Cancer. 97:273-9, 2003.
9. National Cancer Institute. SEER Cancer Statistics Review, 1975-2012. http://seer.cancer.gov/csr/1975_2012/results_single/sect_04_table.13.pdf. Accessed, Nov. 20, 2015.
10. Iqbal J, Ginsburg O, Rochon PA, et al: Differences in breast cancer stage at diagnosis and cancer-specific survival by race and ethnicity in the United States. JAMA 313:165-73, 2015.
Bobby Daly, MD, MBA, is the chief fellow in the section of hematology/oncology at the University of Chicago Medicine. His clinical focus is breast and thoracic oncology, and his research focus is health services. Specifically, Dr. Daly researches disparities in oncology care delivery, oncology health care utilization, aggressive end-of-life oncology care, and oncology payment models. He received his MD and MBA from Harvard Medical School and Harvard Business School, both in Boston, and a BA in Economics and History from Stanford (Calif.) University. He was the recipient of the Dean’s Award at Harvard Medical and Business Schools.
Olufunmilayo Olopade, MD, FACP, OON, is the Walter L. Palmer Distinguished Service Professor of Medicine and Human Genetics, and director, Center for Global Health at the University of Chicago. She is adopting emerging high throughput genomic and informatics strategies to identify genetic and nongenetic risk factors for breast cancer in order to implement precision health care in diverse populations. This innovative approach has the potential to improve the quality of care and reduce costs while saving more lives.
Disclosures: Dr. Olopade serves on the Medical Advisory Board for CancerIQ. Dr. Daly serves as a director of Quadrant Holdings Corporation and receives compensation from this entity. Frontline Medical Communications is a subsidiary of Quadrant Holdings Corporation.
Published in conjunction with Susan G. Komen®.
Pure Intrathoracic Scapular Dislocation
Scapular dislocation, which is also termed locked scapula or scapulothoracic dislocation, is an unusual condition that can be described as extrathoracic or intrathoracic dislocation, depending on the penetration of scapula into the thoracic cavity.
There have been 3 reported cases of intrathoracic scapular dislocations in the literature,1-3all associated with a preexisting condition (eg, sternoclavicular separation, prior rib fracture, thoracotomy for a lung transplant procedure, or surgical resection of superior ribs during breast or pulmonary tumor excisions). Three published cases of intrathoracic scapular impaction involve comminuted scapular fractures with intrathoracic impaction of the inferior fragment through intercostal space.4-6
Here we report an intrathoracic scapular dislocation that was not associated with fracture of the scapula or predisposing factors. To our knowledge, this is the first case of pure intrathoracic dislocation. The possibility of intrathoracic scapular dislocation should be considered as part of the differential diagnosis even in patients with a negative anamnesis for predisposing factors, such as lung or chest surgery. The patient provided written informed consent for print and electronic publication of this case report.
Case Report
A 29-year-old woman presented to the emergency department after a motor vehicle accident. She had tenderness over the left shoulder and left elbow with decreased range of motion; however, motor and sensory examination of the wrist and fingers were normal. No distal neurovascular deficit was noted.
Physical examination revealed pain on pelvic compression. We observed an asymmetrical appearance between shoulders; the left shoulder was superior when compared with the right side (Figure 1). Palpation of the scapula aggravated the pain. The inferior angle of the left scapula was not palpable, and the medial border was palpated through the intercostal space between the third and fourth ribs.
Initial radiographs showed additional left olecranon and bilateral ramus pubis fractures. A chest radiograph showed nondisplaced fractures of the second and third ribs without any obvious hemothorax or pneumothorax. No other pathology involving the chest, such as resection of the ribs or congenital anomaly, was observed. The patient reported no history of thoracic trauma or lung surgery. There were no fractures of the scapula, humerus, or clavicles. Thoracic computed tomography was performed, and 3-dimensional (3D) reconstruction showed that the inferior angle of scapula penetrated into the thoracic cavity through the third intercostal space (Figure 2).
Given the intrathoracic scapular dislocation diagnosis, closed reduction under sedation was planned. The patient was placed in the supine position, and reduction was performed by applying pressure on the shoulder anteriorly. This maneuver increased deformity. At the same time, another physician pulled the spine of the scapula superiorly, releasing the scapula out of the thoracic cavity. When the arm was slightly lowered to neutral position, scapular deformity was no longer present (Figure 3). A shoulder sling was applied, and the patient was hospitalized for surgical fixation of pelvic and olecranon fractures. The arm was immobilized in a sling for 1 week, and shoulder exercises were started immediately afterward.
At 1-month follow-up, full shoulder range of motion was achieved, although rehabilitation for the elbow continued. Final follow-up examination at 4 months revealed no difference between shoulders, and no recurrence occurred.
Discussion
Intrathoracic scapular dislocation is a rare injury. There are only a few cases reported in the literature, and most of them are well associated with a predisposing factor. Nettrour and colleagues1 described the first intrathoracic scapular dislocation, which occurred 6 weeks after sternoclavicular separation and fracture of a rib. In the case reports of Ward and colleagues2 and Fowler and colleagues,3 the predisposing factor was resection of the ribs due to pancoast tumor and breast carcinoma, respectively. The mechanism of these dislocations depends on a weak area over the thoracic cage, creating a fulcrum point for levering the scapula into the thoracic cavity.
There are other cases of scapular dislocations that are accompanied by a comminuted fracture of scapula; a review of the literature revealed 3 cases.4-6 In our opinion, fracture of the inferior pole of the scapula leads to injury of the soft tissues and also results in intrathoracic impaction by creating a weak area over the thoracic cavity. This mechanism can be referred to as penetration.
Our case is singular because it is the first case that is not associated with fracture of the scapula or predisposing factors. Consequently, we report the first pure intrathoracic scapular dislocation in the literature. It is important to suspect intrathoracic scapular dislocation in the case of deformity (Figure 1), even in the absence of any predisposing factors or scapular fracture.
Although plain radiographs may not be elucidative, 3D reconstruction of computed tomography (Figure 2) reveals the pathology and plays an important role in guiding treatment.
In the treatment of our patient, relying on the unique dislocation mechanism without any fracture of the scapula or ribs, we started early active shoulder movement after 1 week of immobilization in a shoulder sling, which prevented recurrence of dislocation. In addition to presenting the first pure intrathoracic scapular dislocation, this case demonstrated satisfactory clinical results with short-term immobilization and early rehabilitation.
Conclusion
Contrary to the literature, the possibility of intrathoracic scapular dislocation should be considered in the differential diagnosis even in patients with a negative anamnesis for predisposing factors, such as lung or chest surgery, and when no fractures are detected. Shoulder or thorax computed tomography, especially 3D reconstructions, are helpful in diagnosing the condition and in guiding treatment. Closed reduction under sedation followed by early rehabilitation is an appropriate treatment method, which resulted in a full return of function in 1 month in our patient.
1. Nettrour LF, Krufky EL, Mueller RE, Raycroft JF. Locked scapula: intrathoracic dislocation of the inferior angle. A case report. J Bone Joint Surg Am. 1972;54(2):413-416.
2. Ward WG, Weaver JP, Garrett WE Jr. Locked scapula: A case report. J Bone Joint Surg Am. 1989;71(10):1558-1159.
3. Fowler TT, Taylor BC, Fankhauser RA. Recurrent low-energy intrathoracic dislocation of the scapula. Am J Orthop. 2013;42(1):E1-E4.
4. Blue JM, Anglen JO, Helikson MA. Fracture of the scapula with intrathoracic penetration. A case report. J Bone Joint Surg Am. 1997;79(7):1076-1078.
5. Schwartzbach CC, Seoudi H, Ross AE, Hendershot K, Robinson L, Malekzadeh A. Fracture of the scapula with intrathoracic penetration in a skeletally mature patient. A case report. J Bone Joint Surg Am. 2006;88(12):2735-2738.
6. Porte AN, Wirtzfeld DA, Mann C. Intrathoracic scapular impaction: an unusual complication of scapular fractures. Can J Surg. 2009;52(3):E62-E63.
Scapular dislocation, which is also termed locked scapula or scapulothoracic dislocation, is an unusual condition that can be described as extrathoracic or intrathoracic dislocation, depending on the penetration of scapula into the thoracic cavity.
There have been 3 reported cases of intrathoracic scapular dislocations in the literature,1-3all associated with a preexisting condition (eg, sternoclavicular separation, prior rib fracture, thoracotomy for a lung transplant procedure, or surgical resection of superior ribs during breast or pulmonary tumor excisions). Three published cases of intrathoracic scapular impaction involve comminuted scapular fractures with intrathoracic impaction of the inferior fragment through intercostal space.4-6
Here we report an intrathoracic scapular dislocation that was not associated with fracture of the scapula or predisposing factors. To our knowledge, this is the first case of pure intrathoracic dislocation. The possibility of intrathoracic scapular dislocation should be considered as part of the differential diagnosis even in patients with a negative anamnesis for predisposing factors, such as lung or chest surgery. The patient provided written informed consent for print and electronic publication of this case report.
Case Report
A 29-year-old woman presented to the emergency department after a motor vehicle accident. She had tenderness over the left shoulder and left elbow with decreased range of motion; however, motor and sensory examination of the wrist and fingers were normal. No distal neurovascular deficit was noted.
Physical examination revealed pain on pelvic compression. We observed an asymmetrical appearance between shoulders; the left shoulder was superior when compared with the right side (Figure 1). Palpation of the scapula aggravated the pain. The inferior angle of the left scapula was not palpable, and the medial border was palpated through the intercostal space between the third and fourth ribs.
Initial radiographs showed additional left olecranon and bilateral ramus pubis fractures. A chest radiograph showed nondisplaced fractures of the second and third ribs without any obvious hemothorax or pneumothorax. No other pathology involving the chest, such as resection of the ribs or congenital anomaly, was observed. The patient reported no history of thoracic trauma or lung surgery. There were no fractures of the scapula, humerus, or clavicles. Thoracic computed tomography was performed, and 3-dimensional (3D) reconstruction showed that the inferior angle of scapula penetrated into the thoracic cavity through the third intercostal space (Figure 2).
Given the intrathoracic scapular dislocation diagnosis, closed reduction under sedation was planned. The patient was placed in the supine position, and reduction was performed by applying pressure on the shoulder anteriorly. This maneuver increased deformity. At the same time, another physician pulled the spine of the scapula superiorly, releasing the scapula out of the thoracic cavity. When the arm was slightly lowered to neutral position, scapular deformity was no longer present (Figure 3). A shoulder sling was applied, and the patient was hospitalized for surgical fixation of pelvic and olecranon fractures. The arm was immobilized in a sling for 1 week, and shoulder exercises were started immediately afterward.
At 1-month follow-up, full shoulder range of motion was achieved, although rehabilitation for the elbow continued. Final follow-up examination at 4 months revealed no difference between shoulders, and no recurrence occurred.
Discussion
Intrathoracic scapular dislocation is a rare injury. There are only a few cases reported in the literature, and most of them are well associated with a predisposing factor. Nettrour and colleagues1 described the first intrathoracic scapular dislocation, which occurred 6 weeks after sternoclavicular separation and fracture of a rib. In the case reports of Ward and colleagues2 and Fowler and colleagues,3 the predisposing factor was resection of the ribs due to pancoast tumor and breast carcinoma, respectively. The mechanism of these dislocations depends on a weak area over the thoracic cage, creating a fulcrum point for levering the scapula into the thoracic cavity.
There are other cases of scapular dislocations that are accompanied by a comminuted fracture of scapula; a review of the literature revealed 3 cases.4-6 In our opinion, fracture of the inferior pole of the scapula leads to injury of the soft tissues and also results in intrathoracic impaction by creating a weak area over the thoracic cavity. This mechanism can be referred to as penetration.
Our case is singular because it is the first case that is not associated with fracture of the scapula or predisposing factors. Consequently, we report the first pure intrathoracic scapular dislocation in the literature. It is important to suspect intrathoracic scapular dislocation in the case of deformity (Figure 1), even in the absence of any predisposing factors or scapular fracture.
Although plain radiographs may not be elucidative, 3D reconstruction of computed tomography (Figure 2) reveals the pathology and plays an important role in guiding treatment.
In the treatment of our patient, relying on the unique dislocation mechanism without any fracture of the scapula or ribs, we started early active shoulder movement after 1 week of immobilization in a shoulder sling, which prevented recurrence of dislocation. In addition to presenting the first pure intrathoracic scapular dislocation, this case demonstrated satisfactory clinical results with short-term immobilization and early rehabilitation.
Conclusion
Contrary to the literature, the possibility of intrathoracic scapular dislocation should be considered in the differential diagnosis even in patients with a negative anamnesis for predisposing factors, such as lung or chest surgery, and when no fractures are detected. Shoulder or thorax computed tomography, especially 3D reconstructions, are helpful in diagnosing the condition and in guiding treatment. Closed reduction under sedation followed by early rehabilitation is an appropriate treatment method, which resulted in a full return of function in 1 month in our patient.
Scapular dislocation, which is also termed locked scapula or scapulothoracic dislocation, is an unusual condition that can be described as extrathoracic or intrathoracic dislocation, depending on the penetration of scapula into the thoracic cavity.
There have been 3 reported cases of intrathoracic scapular dislocations in the literature,1-3all associated with a preexisting condition (eg, sternoclavicular separation, prior rib fracture, thoracotomy for a lung transplant procedure, or surgical resection of superior ribs during breast or pulmonary tumor excisions). Three published cases of intrathoracic scapular impaction involve comminuted scapular fractures with intrathoracic impaction of the inferior fragment through intercostal space.4-6
Here we report an intrathoracic scapular dislocation that was not associated with fracture of the scapula or predisposing factors. To our knowledge, this is the first case of pure intrathoracic dislocation. The possibility of intrathoracic scapular dislocation should be considered as part of the differential diagnosis even in patients with a negative anamnesis for predisposing factors, such as lung or chest surgery. The patient provided written informed consent for print and electronic publication of this case report.
Case Report
A 29-year-old woman presented to the emergency department after a motor vehicle accident. She had tenderness over the left shoulder and left elbow with decreased range of motion; however, motor and sensory examination of the wrist and fingers were normal. No distal neurovascular deficit was noted.
Physical examination revealed pain on pelvic compression. We observed an asymmetrical appearance between shoulders; the left shoulder was superior when compared with the right side (Figure 1). Palpation of the scapula aggravated the pain. The inferior angle of the left scapula was not palpable, and the medial border was palpated through the intercostal space between the third and fourth ribs.
Initial radiographs showed additional left olecranon and bilateral ramus pubis fractures. A chest radiograph showed nondisplaced fractures of the second and third ribs without any obvious hemothorax or pneumothorax. No other pathology involving the chest, such as resection of the ribs or congenital anomaly, was observed. The patient reported no history of thoracic trauma or lung surgery. There were no fractures of the scapula, humerus, or clavicles. Thoracic computed tomography was performed, and 3-dimensional (3D) reconstruction showed that the inferior angle of scapula penetrated into the thoracic cavity through the third intercostal space (Figure 2).
Given the intrathoracic scapular dislocation diagnosis, closed reduction under sedation was planned. The patient was placed in the supine position, and reduction was performed by applying pressure on the shoulder anteriorly. This maneuver increased deformity. At the same time, another physician pulled the spine of the scapula superiorly, releasing the scapula out of the thoracic cavity. When the arm was slightly lowered to neutral position, scapular deformity was no longer present (Figure 3). A shoulder sling was applied, and the patient was hospitalized for surgical fixation of pelvic and olecranon fractures. The arm was immobilized in a sling for 1 week, and shoulder exercises were started immediately afterward.
At 1-month follow-up, full shoulder range of motion was achieved, although rehabilitation for the elbow continued. Final follow-up examination at 4 months revealed no difference between shoulders, and no recurrence occurred.
Discussion
Intrathoracic scapular dislocation is a rare injury. There are only a few cases reported in the literature, and most of them are well associated with a predisposing factor. Nettrour and colleagues1 described the first intrathoracic scapular dislocation, which occurred 6 weeks after sternoclavicular separation and fracture of a rib. In the case reports of Ward and colleagues2 and Fowler and colleagues,3 the predisposing factor was resection of the ribs due to pancoast tumor and breast carcinoma, respectively. The mechanism of these dislocations depends on a weak area over the thoracic cage, creating a fulcrum point for levering the scapula into the thoracic cavity.
There are other cases of scapular dislocations that are accompanied by a comminuted fracture of scapula; a review of the literature revealed 3 cases.4-6 In our opinion, fracture of the inferior pole of the scapula leads to injury of the soft tissues and also results in intrathoracic impaction by creating a weak area over the thoracic cavity. This mechanism can be referred to as penetration.
Our case is singular because it is the first case that is not associated with fracture of the scapula or predisposing factors. Consequently, we report the first pure intrathoracic scapular dislocation in the literature. It is important to suspect intrathoracic scapular dislocation in the case of deformity (Figure 1), even in the absence of any predisposing factors or scapular fracture.
Although plain radiographs may not be elucidative, 3D reconstruction of computed tomography (Figure 2) reveals the pathology and plays an important role in guiding treatment.
In the treatment of our patient, relying on the unique dislocation mechanism without any fracture of the scapula or ribs, we started early active shoulder movement after 1 week of immobilization in a shoulder sling, which prevented recurrence of dislocation. In addition to presenting the first pure intrathoracic scapular dislocation, this case demonstrated satisfactory clinical results with short-term immobilization and early rehabilitation.
Conclusion
Contrary to the literature, the possibility of intrathoracic scapular dislocation should be considered in the differential diagnosis even in patients with a negative anamnesis for predisposing factors, such as lung or chest surgery, and when no fractures are detected. Shoulder or thorax computed tomography, especially 3D reconstructions, are helpful in diagnosing the condition and in guiding treatment. Closed reduction under sedation followed by early rehabilitation is an appropriate treatment method, which resulted in a full return of function in 1 month in our patient.
1. Nettrour LF, Krufky EL, Mueller RE, Raycroft JF. Locked scapula: intrathoracic dislocation of the inferior angle. A case report. J Bone Joint Surg Am. 1972;54(2):413-416.
2. Ward WG, Weaver JP, Garrett WE Jr. Locked scapula: A case report. J Bone Joint Surg Am. 1989;71(10):1558-1159.
3. Fowler TT, Taylor BC, Fankhauser RA. Recurrent low-energy intrathoracic dislocation of the scapula. Am J Orthop. 2013;42(1):E1-E4.
4. Blue JM, Anglen JO, Helikson MA. Fracture of the scapula with intrathoracic penetration. A case report. J Bone Joint Surg Am. 1997;79(7):1076-1078.
5. Schwartzbach CC, Seoudi H, Ross AE, Hendershot K, Robinson L, Malekzadeh A. Fracture of the scapula with intrathoracic penetration in a skeletally mature patient. A case report. J Bone Joint Surg Am. 2006;88(12):2735-2738.
6. Porte AN, Wirtzfeld DA, Mann C. Intrathoracic scapular impaction: an unusual complication of scapular fractures. Can J Surg. 2009;52(3):E62-E63.
1. Nettrour LF, Krufky EL, Mueller RE, Raycroft JF. Locked scapula: intrathoracic dislocation of the inferior angle. A case report. J Bone Joint Surg Am. 1972;54(2):413-416.
2. Ward WG, Weaver JP, Garrett WE Jr. Locked scapula: A case report. J Bone Joint Surg Am. 1989;71(10):1558-1159.
3. Fowler TT, Taylor BC, Fankhauser RA. Recurrent low-energy intrathoracic dislocation of the scapula. Am J Orthop. 2013;42(1):E1-E4.
4. Blue JM, Anglen JO, Helikson MA. Fracture of the scapula with intrathoracic penetration. A case report. J Bone Joint Surg Am. 1997;79(7):1076-1078.
5. Schwartzbach CC, Seoudi H, Ross AE, Hendershot K, Robinson L, Malekzadeh A. Fracture of the scapula with intrathoracic penetration in a skeletally mature patient. A case report. J Bone Joint Surg Am. 2006;88(12):2735-2738.
6. Porte AN, Wirtzfeld DA, Mann C. Intrathoracic scapular impaction: an unusual complication of scapular fractures. Can J Surg. 2009;52(3):E62-E63.
Web Page Content and Quality Assessed for Shoulder Replacement
The Internet is becoming a primary source for obtaining medical information. This growing trend may have serious implications for the medical field. As patients increasingly regard the Internet as an essential tool for obtaining health-related information, questions have been raised regarding the quality of medical information available on the Internet.1 Studies have shown that health-related sites often present inaccurate, inconsistent, and outdated information that may have a negative impact on health care decisions made by patients.2
According to the US Census Bureau, 71.7% of American households report having access to the Internet.3 Of those who have access to Internet, approximately 72% have sought health information online over the last year.4 Among people older than age 65 years living in the United States, there has been a growing trend toward using the Internet, from 14% in 2000 to almost 60% in 2013, according to the Pew Research Internet Project.5 Most medical websites are viewed for information on diseases and treatment options.6 Since most patients want to be informed about treatment options, as well as risks and benefits for each treatment, access to credible information is essential for proper decision-making.7
To assess the quality of information on the Internet, we used DISCERN, a standardized questionnaire to aid consumers in judging Internet content.8 The DISCERN instrument, available at www.discern.org.uk, was designed by an expert group in the United Kingdom. First, an expert panel developed and tested the instrument, and then health care providers and self-help group members tested it further.8,9 The questionnaire had been found to have good interrater reliability, regardless of use by health professionals or consumers.8-10
More than 53,000 shoulder arthroplasties are performed in the United States annually, and the number is growing, with the main goal of pain relief from glenohumeral degenerative joint disease.11,12 The Internet has become a quasi–second opinion for patients trying to participate in their care. Given the prevalence of shoulder-related surgeries, it is critical to analyze and become familiar with the quality of information that patients read online in order to direct them to nonbiased, all-inclusive websites. In this study, we provide a summary assessment and comparison of the quality of online information pertaining to shoulder replacement, using medical (total shoulder replacement) and nontechnical (shoulder replacement) search terms.
Methods
Websites were identified using 3 search engines (Google, Yahoo, and Bing) and 2 search terms, shoulder replacement (SR) and total shoulder arthroplasty (TSA), on January 17, 2014. These 3 search engines were used because 77% of health care–related information online searches begin through a search engine (Google, Bing, Yahoo); only 13% begin at a health care–specialized website.4 These search terms were used after consulting with orthopedic residents and attending physicians in a focus group regarding the terminology used with patients. The first 30 websites in each search engine were identified consecutively and evaluated for category and quality of information using the DISCERN instrument.
A total of 180 websites (90 per search term) were reviewed. Each website was evaluated independently by 3 medical students. In the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flow diagram, we recorded how websites were identified, screened, and included (Figure 1).13 Websites that were duplicated within each search term and those that were inaccessible were used to determine the total number of noncommercial versus commercial websites, but were excluded from the final analysis. The first part of the analysis involved determining the type of website (eg, commercial vs noncommercial) based upon the html endings. All .com endings were classified as commercial websites; noncommercial included .gov, .org, .edu, and .net endings. Next, each website was categorized based on the target audience. Websites were grouped into health professional–oriented information, patient-oriented, advertisement, or “other.” These classifications were based on those described in previous works.14,15 The “other” category included images, YouTube videos, another search engine, and open forums, which were also excluded from the final analysis because they were not easily evaluable with the DISCERN instrument. Websites were considered health professional–oriented if they included journal articles, scholarly articles, and/or rehabilitation protocols. Patient-directed websites clearly stated the information was directed to patients or provided a general overview. Advertisement included sites that displayed ads or products for sale. Websites were evaluated for quality using the DISCERN instrument (Figure 2).
DISCERN has 3 subdivision scores: the reliable score (composed of the first 8 questions), the treatment options (the next 7 questions), and 1 final question that addresses the overall quality of the website and is rated independently of the first 15 questions. DISCERN uses 2 scales, a binary scale anchored on both extremes with the number 1 equaling complete absence of the criteria being measured, and the number 5 at the upper extreme, representing completeness of the quality being assessed. In between 1 and 5 is a partial ordinal scale measuring from 2 to 4, which indicates the information is present to some extent but not complete. The ordinal scale allows ranking of the criteria being assessed. Summarizing values from each of the 2 scales poses some concern: the scale is not a true binary scale because of the ordinal scale of the middle numbers (2-4), and as such, is not amenable to being an interval scale to calculate arithmetic means. To summarize the values from the 2 scales, we calculated the harmonic mean, the arithmetic mean, the geometric mean, and the median. The means were empirically compared with the median, and we used the harmonic mean to summarize scale values because it was the best approximation of the medians.
Results
A total of 90 websites were assessed with the search term total shoulder arthroplasty and another 90 with shoulder replacement. When 37 duplicate websites for TSA and 52 for SR were eliminated, 53 (59%) and 38 (42%) unique websites were evaluated for each search term, respectively (Figure 1). (These unique websites are included in the Appendix.) Between the 2 search terms, 20 websites were duplicated. Figure 3 shows the distribution of websites by category. Total shoulder arthroplasty provided the highest percentage of health professional–oriented information; SR had the greatest percentage of patient-oriented information. Both TSA and SR had nearly the same number of advertisements and websites labeled “other.” The percentage of noncommercial websites from each search engine is represented in Figure 4. For SR, Google had 40% (12/30) noncommercial websites compared with Yahoo at 53% (16/30) and Bing at 46% (14/30). Total shoulder arthroplasty had 43% (13/30) noncommercial websites on Google, 27% (8/30) on Yahoo, and 40% (12/30) on Bing. In total, SR had more noncommercial websites, 47% (42/90), compared with 37% (33/90) for TSA.
The mean of all 3 raters for reliablity (DISCERN questions 1-8) and treatment options (DISCERN questions 9-15) is represented in the Table. For both search terms, we found that websites identified as health professional–oriented had the highest reliable mean scores, followed by patient-oriented, and advertisement at the lowest (SR: P = .054; TSA: P = .134). For SR, treatment mean scores demonstrated similar results with health professional–oriented websites receiving the highest, followed by patient-oriented and advertisement (P = .005). However, the treatment mean scores for TSA differed with patient-oriented websites receiving higher scores than health professional–oriented websites, but this was not statistically significant (P= .407). Regarding search terms, there were no significant differences between mean reliable and treatment scores across all categories.
The average overall DISCERN score for TSA websites was 2.5 (range, 1-5), compared with 2.3 (range, 1-5) for SR websites. The overall reliable score (DISCERN questions 1-8) for TSA websites was 2.6 and 2.5 for SR websites (P < .001). For TSA websites, 38% (20/53) were classified as good, having an overall DISCERN score ≥3, versus 26% (10/38) of SR websites. The overall DISCERN score for health professional–oriented websites was 2.7, patient-oriented websites received a score of 2.6, and advertisements had the lowest score at 2.4.
Discussion
Both patients and health professionals obtain information on health care subjects through the Internet, which has become the primary resource for patients.15,16 However, there are no strict regulations of the content being written. This creates a challenge for the typical user to find credible and evidence-based information, which is important because misleading information could cause undue anxiety, among other effects.17,18 The aims of this study were to determine the quality of Internet information for shoulder replacement surgeries using the medical terminology total shoulder arthroplasty (TSA) and the nontechnical term shoulder replacement (SR), and to compare the results.
After analyzing the types of websites returned for both total shoulder arthroplasty and shoulder replacement (Figure 4), it was interesting to find that using nonmedical terminology as the search term provided more noncommercial websites compared with total shoulder arthroplasty. Furthermore, Yahoo provided the highest yield of noncommercial websites at 16, with Bing at 14, when using SR as the search term. We believe the increase in noncommercial websites returned for SR was greater than for TSA because SR yielded more patient-oriented websites, which usually had html endings of .edu and .org, as shown in Figure 3 (48% of SR websites offered patient-oriented information).
Although there were more noncommercial websites for SR, the majority of the DISCERN values between the 2 search terms did not differ significantly. This is a direct result of the number of sites (20) that were duplicated across both search terms. However as seen in the Table, TSA had similar reliable mean scores for advertisements and patient-oriented websites but a slightly higher reliable score for health professional–oriented websites. We correlated this with the increased number of health professional–oriented websites returned when using TSA as the search term (Figure 3). The health professional–oriented websites explained their aims and cited their sources more consistently than did patient-oriented sites and advertisements, resulting in higher reliable scores. Although patient-oriented websites frequently lacked citations, they provided information about multiple treatment options, which were more relevant to consumers. This resulted in nearly equivalent reliable scores. Treatment means for advertisements in both SR and TSA were similar. However, treatment means for professional-oriented websites in TSA were lower than those for SR because health professional–oriented websites often were only moderately relevant to consumers, with their focus usually on 1 treatment option or on rehabilitation protocols. Although the DISCERN scores were similar between the search terms, total shoulder arthroplasty provided more websites (20) classified as good—overall DISCERN score, ≥3—than SR did (10). Advertisement websites had similar overall DISCERN scores, which we anticipated because most of the advertisements were duplicated across the search terms.
Using the 2 search terms, academic websites and commercial websites, such as WebMD, consistently received higher reliable and overall DISCERN scores. Advertisement websites, which need to deliver a clear message, frequently scored high on explicitly stating their aims and relevance to consumers, but focused on their products without discussing the benefits of other treatment options. This is significant because Internet search engines, such as Google, offer sponsor links for which organizations pay to appear at the top of the search results. This creates the potential for consumers to receive biased information because most individuals only visit the top 10 websites generated by a search engine.19
We concluded that the quality of online information relating to SR and TSA was highly variable and frequently of moderate-to-poor quality, with most overall DISCERN scores <3. The quality of information found online for this study using the DISCERN instrument is consistent with those studies using DISCERN to evaluate other medical conditions (eg, bunions, chronic pain, general anesthesia, and anterior cruciate ligament reconstruction).2,9,15,19 These studies also concluded that online information varies tremendously in quality and completeness.
This study has several limitations. Websites were searched at a single time point and, because Internet resources are frequently updated, the results of this study could vary. Furthermore, although Google, Yahoo, and Bing are 3 of the most popular search engines, these are not the only resources patients use when searching the Internet for health-related information. Other search engines, such as Pubmed.gov and MSN.com, could provide additional websites for Internet users. Lastly, although DISCERN is validated to address the quality of information available online, it does not evaluate the accuracy of the information.8 Our use of DISCERN involves 2 scales, a binary yes/no (ratings, 1 and 5) and an ordinal scale (ratings, 2-4). As such, a single mean summary statistic cannot be calculated.
Conclusion
The information available on the Internet pertaining to TSA and SR is highly variable and provides mostly moderate-to-poor quality information based on the DISCERN instrument. Many websites failed to describe the benefits and the risks of different treatment options, including nonoperative management. Health care professionals should be aware that patients often refer to the Internet as a primary resource for obtaining medical information. It is important to direct patients to websites that provide accurate information, because patients who educate themselves about their conditions and actively participate in decision-making may have improved health outcomes.20-22 Overall, academic websites and commercial websites, such as WebMD and OrthoInfo, generally had higher DISCERN scores when using either search term. Of major concern is the potential for misleading advertisements or incorrect information that can negatively affect health outcomes. This study found that using nonmedical terminology (SR) provided more noncommercial and patient-oriented websites, especially through Yahoo. This study highlights the need for more comprehensive online information pertaining to shoulder replacement that can better serve as a resource for Internet users.
1. Eysenbach G, Powell J, Kuss O, Sa ER. Empirical studies assessing the quality of health information for consumers on the world wide web: a systematic review. JAMA. 2002;287(20):2691-2700.
2. Bruce-Brand RA, Baker JF, Byrne DP, Hogan NA, McCarthy T. Assessment of the quality and content of information on anterior cruciate ligament reconstruction on the internet. Arthroscopy. 2013;29(6):1095-1100.
3. Computer and internet use in the United States: population characteristics. US Census Bureau website. http://www.census.gov/hhes/computer/. Accessed December 11, 2015.
4. Fox S, Duggan M. Health online 2013. Pew Research Center website. http://pewinternet.org/Reports/2013/Health-online.aspx. Published January 15, 2013. Accessed November 24, 2015.
5. Smith A. Older adults and technology use. Pew Research Center website. http://www.pewinternet.org/2014/04/03/older-adults-and-technology-use. Published April 3, 2014. Accessed November 24, 2015.
6. Shuyler KS, Knight KM. What are patients seeking when they turn to the internet? Qualitative content analysis of questions asked by visitors to an orthopaedics web site. J Med Internet Res. 2003;5(4):e24.
7. Meredith P, Emberton M, Wood C, Smith J. Comparison of patients’ needs for information on prostate surgery with printed materials provided by surgeons. Qual Health Care. 1995;4(1):18-23.
8. Charnock D, Shepperd S, Needham G, Gann R. DISCERN: An instrument for judging the quality of written consumer health information on treatment choices. J Epidemiol Community Health. 1999;53(2):105-111.
9. Kaicker J, Debono VB, Dang W, Buckley N, Thabane L. Assessment of the quality and variability of health information on chronic pain websites using the DISCERN instrument. BMC Med. 2010;8(1):59.
10. Griffiths KM, Christensen H. Website quality indicators for consumers. J Med Internet Res. 2005;7(5):e55.
11. Wiater JM. Shoulder joint replacement. American Academy of Orthopedic Surgeons website. http://orthoinfo.aaos.org/topic.cfm?topic=A00094. Updated December 2011. Accessed November 24, 2015.
12. Kim SH, Wise BL, Zhang Y, Szabo RM. Increasing incidence of shoulder arthroplasty in the united states. J Bone Joint Surg Am. 2011;93(24):2249-2254.
13. Liberati A, Altman DG, Tetzlaff J, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. Ann Intern Med. 2009;151(4):W65-W94.
14. Nason GJ, Baker JF, Byrne DP, Noel J, Moore D, Kiely PJ. Scoliosis-specific information on the internet: has the “information highway” led to better information provision? Spine. 2012;37(21):E1364-E1369.
15. Starman JS, Gettys FK, Capo JA, Fleischli JE, Norton HJ, Karunakar MA. Quality and content of internet-based information for ten common orthopaedic sports medicine diagnoses. J Bone Joint Surg Am. 2010;92(7):1612-1618.
16. Bernstein J, Ahn J, Veillette C. The future of orthopaedic information management. J Bone Joint Surg Am. 2012;94(13):e95.
17. Berland GK, Elliott MN, Morales LS, et al. Health information on the Internet: accessibility, quality, and readability in English and Spanish. JAMA. 2001;285(20):2612-2621.
18. Fallowfield LJ, Hall A, Maguire GP, Baum M. Psychological outcomes of different treatment policies in women with early breast cancer outside a clinical trial. BMJ. 1990;301(6752):575-580.
19. Chong YM, Fraval A, Chandrananth J, Plunkett V, Tran P. Assessment of the quality of web-based information on bunions. Foot Ankle Int. 2013;34(8):1134-1139.
20. Brody DS, Miller SM, Lerman CE, Smith DG, Caputo GC. Patient perception of involvement in medical care. J Gen Intern Med. 1989;4(6):506-511.
21. Greenfield S, Kaplan S, Ware JE Jr. Expanding patient involvement in care. Effects on patient outcomes. Ann Intern Med. 1985;102(4):520-528.
22. Kaplan SH, Greenfield S, Ware JE Jr. Assessing the effects of physician-patient interactions on the outcomes of chronic disease. Med Care. 1989;27(3 suppl):S110-S127.
The Internet is becoming a primary source for obtaining medical information. This growing trend may have serious implications for the medical field. As patients increasingly regard the Internet as an essential tool for obtaining health-related information, questions have been raised regarding the quality of medical information available on the Internet.1 Studies have shown that health-related sites often present inaccurate, inconsistent, and outdated information that may have a negative impact on health care decisions made by patients.2
According to the US Census Bureau, 71.7% of American households report having access to the Internet.3 Of those who have access to Internet, approximately 72% have sought health information online over the last year.4 Among people older than age 65 years living in the United States, there has been a growing trend toward using the Internet, from 14% in 2000 to almost 60% in 2013, according to the Pew Research Internet Project.5 Most medical websites are viewed for information on diseases and treatment options.6 Since most patients want to be informed about treatment options, as well as risks and benefits for each treatment, access to credible information is essential for proper decision-making.7
To assess the quality of information on the Internet, we used DISCERN, a standardized questionnaire to aid consumers in judging Internet content.8 The DISCERN instrument, available at www.discern.org.uk, was designed by an expert group in the United Kingdom. First, an expert panel developed and tested the instrument, and then health care providers and self-help group members tested it further.8,9 The questionnaire had been found to have good interrater reliability, regardless of use by health professionals or consumers.8-10
More than 53,000 shoulder arthroplasties are performed in the United States annually, and the number is growing, with the main goal of pain relief from glenohumeral degenerative joint disease.11,12 The Internet has become a quasi–second opinion for patients trying to participate in their care. Given the prevalence of shoulder-related surgeries, it is critical to analyze and become familiar with the quality of information that patients read online in order to direct them to nonbiased, all-inclusive websites. In this study, we provide a summary assessment and comparison of the quality of online information pertaining to shoulder replacement, using medical (total shoulder replacement) and nontechnical (shoulder replacement) search terms.
Methods
Websites were identified using 3 search engines (Google, Yahoo, and Bing) and 2 search terms, shoulder replacement (SR) and total shoulder arthroplasty (TSA), on January 17, 2014. These 3 search engines were used because 77% of health care–related information online searches begin through a search engine (Google, Bing, Yahoo); only 13% begin at a health care–specialized website.4 These search terms were used after consulting with orthopedic residents and attending physicians in a focus group regarding the terminology used with patients. The first 30 websites in each search engine were identified consecutively and evaluated for category and quality of information using the DISCERN instrument.
A total of 180 websites (90 per search term) were reviewed. Each website was evaluated independently by 3 medical students. In the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flow diagram, we recorded how websites were identified, screened, and included (Figure 1).13 Websites that were duplicated within each search term and those that were inaccessible were used to determine the total number of noncommercial versus commercial websites, but were excluded from the final analysis. The first part of the analysis involved determining the type of website (eg, commercial vs noncommercial) based upon the html endings. All .com endings were classified as commercial websites; noncommercial included .gov, .org, .edu, and .net endings. Next, each website was categorized based on the target audience. Websites were grouped into health professional–oriented information, patient-oriented, advertisement, or “other.” These classifications were based on those described in previous works.14,15 The “other” category included images, YouTube videos, another search engine, and open forums, which were also excluded from the final analysis because they were not easily evaluable with the DISCERN instrument. Websites were considered health professional–oriented if they included journal articles, scholarly articles, and/or rehabilitation protocols. Patient-directed websites clearly stated the information was directed to patients or provided a general overview. Advertisement included sites that displayed ads or products for sale. Websites were evaluated for quality using the DISCERN instrument (Figure 2).
DISCERN has 3 subdivision scores: the reliable score (composed of the first 8 questions), the treatment options (the next 7 questions), and 1 final question that addresses the overall quality of the website and is rated independently of the first 15 questions. DISCERN uses 2 scales, a binary scale anchored on both extremes with the number 1 equaling complete absence of the criteria being measured, and the number 5 at the upper extreme, representing completeness of the quality being assessed. In between 1 and 5 is a partial ordinal scale measuring from 2 to 4, which indicates the information is present to some extent but not complete. The ordinal scale allows ranking of the criteria being assessed. Summarizing values from each of the 2 scales poses some concern: the scale is not a true binary scale because of the ordinal scale of the middle numbers (2-4), and as such, is not amenable to being an interval scale to calculate arithmetic means. To summarize the values from the 2 scales, we calculated the harmonic mean, the arithmetic mean, the geometric mean, and the median. The means were empirically compared with the median, and we used the harmonic mean to summarize scale values because it was the best approximation of the medians.
Results
A total of 90 websites were assessed with the search term total shoulder arthroplasty and another 90 with shoulder replacement. When 37 duplicate websites for TSA and 52 for SR were eliminated, 53 (59%) and 38 (42%) unique websites were evaluated for each search term, respectively (Figure 1). (These unique websites are included in the Appendix.) Between the 2 search terms, 20 websites were duplicated. Figure 3 shows the distribution of websites by category. Total shoulder arthroplasty provided the highest percentage of health professional–oriented information; SR had the greatest percentage of patient-oriented information. Both TSA and SR had nearly the same number of advertisements and websites labeled “other.” The percentage of noncommercial websites from each search engine is represented in Figure 4. For SR, Google had 40% (12/30) noncommercial websites compared with Yahoo at 53% (16/30) and Bing at 46% (14/30). Total shoulder arthroplasty had 43% (13/30) noncommercial websites on Google, 27% (8/30) on Yahoo, and 40% (12/30) on Bing. In total, SR had more noncommercial websites, 47% (42/90), compared with 37% (33/90) for TSA.
The mean of all 3 raters for reliablity (DISCERN questions 1-8) and treatment options (DISCERN questions 9-15) is represented in the Table. For both search terms, we found that websites identified as health professional–oriented had the highest reliable mean scores, followed by patient-oriented, and advertisement at the lowest (SR: P = .054; TSA: P = .134). For SR, treatment mean scores demonstrated similar results with health professional–oriented websites receiving the highest, followed by patient-oriented and advertisement (P = .005). However, the treatment mean scores for TSA differed with patient-oriented websites receiving higher scores than health professional–oriented websites, but this was not statistically significant (P= .407). Regarding search terms, there were no significant differences between mean reliable and treatment scores across all categories.
The average overall DISCERN score for TSA websites was 2.5 (range, 1-5), compared with 2.3 (range, 1-5) for SR websites. The overall reliable score (DISCERN questions 1-8) for TSA websites was 2.6 and 2.5 for SR websites (P < .001). For TSA websites, 38% (20/53) were classified as good, having an overall DISCERN score ≥3, versus 26% (10/38) of SR websites. The overall DISCERN score for health professional–oriented websites was 2.7, patient-oriented websites received a score of 2.6, and advertisements had the lowest score at 2.4.
Discussion
Both patients and health professionals obtain information on health care subjects through the Internet, which has become the primary resource for patients.15,16 However, there are no strict regulations of the content being written. This creates a challenge for the typical user to find credible and evidence-based information, which is important because misleading information could cause undue anxiety, among other effects.17,18 The aims of this study were to determine the quality of Internet information for shoulder replacement surgeries using the medical terminology total shoulder arthroplasty (TSA) and the nontechnical term shoulder replacement (SR), and to compare the results.
After analyzing the types of websites returned for both total shoulder arthroplasty and shoulder replacement (Figure 4), it was interesting to find that using nonmedical terminology as the search term provided more noncommercial websites compared with total shoulder arthroplasty. Furthermore, Yahoo provided the highest yield of noncommercial websites at 16, with Bing at 14, when using SR as the search term. We believe the increase in noncommercial websites returned for SR was greater than for TSA because SR yielded more patient-oriented websites, which usually had html endings of .edu and .org, as shown in Figure 3 (48% of SR websites offered patient-oriented information).
Although there were more noncommercial websites for SR, the majority of the DISCERN values between the 2 search terms did not differ significantly. This is a direct result of the number of sites (20) that were duplicated across both search terms. However as seen in the Table, TSA had similar reliable mean scores for advertisements and patient-oriented websites but a slightly higher reliable score for health professional–oriented websites. We correlated this with the increased number of health professional–oriented websites returned when using TSA as the search term (Figure 3). The health professional–oriented websites explained their aims and cited their sources more consistently than did patient-oriented sites and advertisements, resulting in higher reliable scores. Although patient-oriented websites frequently lacked citations, they provided information about multiple treatment options, which were more relevant to consumers. This resulted in nearly equivalent reliable scores. Treatment means for advertisements in both SR and TSA were similar. However, treatment means for professional-oriented websites in TSA were lower than those for SR because health professional–oriented websites often were only moderately relevant to consumers, with their focus usually on 1 treatment option or on rehabilitation protocols. Although the DISCERN scores were similar between the search terms, total shoulder arthroplasty provided more websites (20) classified as good—overall DISCERN score, ≥3—than SR did (10). Advertisement websites had similar overall DISCERN scores, which we anticipated because most of the advertisements were duplicated across the search terms.
Using the 2 search terms, academic websites and commercial websites, such as WebMD, consistently received higher reliable and overall DISCERN scores. Advertisement websites, which need to deliver a clear message, frequently scored high on explicitly stating their aims and relevance to consumers, but focused on their products without discussing the benefits of other treatment options. This is significant because Internet search engines, such as Google, offer sponsor links for which organizations pay to appear at the top of the search results. This creates the potential for consumers to receive biased information because most individuals only visit the top 10 websites generated by a search engine.19
We concluded that the quality of online information relating to SR and TSA was highly variable and frequently of moderate-to-poor quality, with most overall DISCERN scores <3. The quality of information found online for this study using the DISCERN instrument is consistent with those studies using DISCERN to evaluate other medical conditions (eg, bunions, chronic pain, general anesthesia, and anterior cruciate ligament reconstruction).2,9,15,19 These studies also concluded that online information varies tremendously in quality and completeness.
This study has several limitations. Websites were searched at a single time point and, because Internet resources are frequently updated, the results of this study could vary. Furthermore, although Google, Yahoo, and Bing are 3 of the most popular search engines, these are not the only resources patients use when searching the Internet for health-related information. Other search engines, such as Pubmed.gov and MSN.com, could provide additional websites for Internet users. Lastly, although DISCERN is validated to address the quality of information available online, it does not evaluate the accuracy of the information.8 Our use of DISCERN involves 2 scales, a binary yes/no (ratings, 1 and 5) and an ordinal scale (ratings, 2-4). As such, a single mean summary statistic cannot be calculated.
Conclusion
The information available on the Internet pertaining to TSA and SR is highly variable and provides mostly moderate-to-poor quality information based on the DISCERN instrument. Many websites failed to describe the benefits and the risks of different treatment options, including nonoperative management. Health care professionals should be aware that patients often refer to the Internet as a primary resource for obtaining medical information. It is important to direct patients to websites that provide accurate information, because patients who educate themselves about their conditions and actively participate in decision-making may have improved health outcomes.20-22 Overall, academic websites and commercial websites, such as WebMD and OrthoInfo, generally had higher DISCERN scores when using either search term. Of major concern is the potential for misleading advertisements or incorrect information that can negatively affect health outcomes. This study found that using nonmedical terminology (SR) provided more noncommercial and patient-oriented websites, especially through Yahoo. This study highlights the need for more comprehensive online information pertaining to shoulder replacement that can better serve as a resource for Internet users.
The Internet is becoming a primary source for obtaining medical information. This growing trend may have serious implications for the medical field. As patients increasingly regard the Internet as an essential tool for obtaining health-related information, questions have been raised regarding the quality of medical information available on the Internet.1 Studies have shown that health-related sites often present inaccurate, inconsistent, and outdated information that may have a negative impact on health care decisions made by patients.2
According to the US Census Bureau, 71.7% of American households report having access to the Internet.3 Of those who have access to Internet, approximately 72% have sought health information online over the last year.4 Among people older than age 65 years living in the United States, there has been a growing trend toward using the Internet, from 14% in 2000 to almost 60% in 2013, according to the Pew Research Internet Project.5 Most medical websites are viewed for information on diseases and treatment options.6 Since most patients want to be informed about treatment options, as well as risks and benefits for each treatment, access to credible information is essential for proper decision-making.7
To assess the quality of information on the Internet, we used DISCERN, a standardized questionnaire to aid consumers in judging Internet content.8 The DISCERN instrument, available at www.discern.org.uk, was designed by an expert group in the United Kingdom. First, an expert panel developed and tested the instrument, and then health care providers and self-help group members tested it further.8,9 The questionnaire had been found to have good interrater reliability, regardless of use by health professionals or consumers.8-10
More than 53,000 shoulder arthroplasties are performed in the United States annually, and the number is growing, with the main goal of pain relief from glenohumeral degenerative joint disease.11,12 The Internet has become a quasi–second opinion for patients trying to participate in their care. Given the prevalence of shoulder-related surgeries, it is critical to analyze and become familiar with the quality of information that patients read online in order to direct them to nonbiased, all-inclusive websites. In this study, we provide a summary assessment and comparison of the quality of online information pertaining to shoulder replacement, using medical (total shoulder replacement) and nontechnical (shoulder replacement) search terms.
Methods
Websites were identified using 3 search engines (Google, Yahoo, and Bing) and 2 search terms, shoulder replacement (SR) and total shoulder arthroplasty (TSA), on January 17, 2014. These 3 search engines were used because 77% of health care–related information online searches begin through a search engine (Google, Bing, Yahoo); only 13% begin at a health care–specialized website.4 These search terms were used after consulting with orthopedic residents and attending physicians in a focus group regarding the terminology used with patients. The first 30 websites in each search engine were identified consecutively and evaluated for category and quality of information using the DISCERN instrument.
A total of 180 websites (90 per search term) were reviewed. Each website was evaluated independently by 3 medical students. In the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flow diagram, we recorded how websites were identified, screened, and included (Figure 1).13 Websites that were duplicated within each search term and those that were inaccessible were used to determine the total number of noncommercial versus commercial websites, but were excluded from the final analysis. The first part of the analysis involved determining the type of website (eg, commercial vs noncommercial) based upon the html endings. All .com endings were classified as commercial websites; noncommercial included .gov, .org, .edu, and .net endings. Next, each website was categorized based on the target audience. Websites were grouped into health professional–oriented information, patient-oriented, advertisement, or “other.” These classifications were based on those described in previous works.14,15 The “other” category included images, YouTube videos, another search engine, and open forums, which were also excluded from the final analysis because they were not easily evaluable with the DISCERN instrument. Websites were considered health professional–oriented if they included journal articles, scholarly articles, and/or rehabilitation protocols. Patient-directed websites clearly stated the information was directed to patients or provided a general overview. Advertisement included sites that displayed ads or products for sale. Websites were evaluated for quality using the DISCERN instrument (Figure 2).
DISCERN has 3 subdivision scores: the reliable score (composed of the first 8 questions), the treatment options (the next 7 questions), and 1 final question that addresses the overall quality of the website and is rated independently of the first 15 questions. DISCERN uses 2 scales, a binary scale anchored on both extremes with the number 1 equaling complete absence of the criteria being measured, and the number 5 at the upper extreme, representing completeness of the quality being assessed. In between 1 and 5 is a partial ordinal scale measuring from 2 to 4, which indicates the information is present to some extent but not complete. The ordinal scale allows ranking of the criteria being assessed. Summarizing values from each of the 2 scales poses some concern: the scale is not a true binary scale because of the ordinal scale of the middle numbers (2-4), and as such, is not amenable to being an interval scale to calculate arithmetic means. To summarize the values from the 2 scales, we calculated the harmonic mean, the arithmetic mean, the geometric mean, and the median. The means were empirically compared with the median, and we used the harmonic mean to summarize scale values because it was the best approximation of the medians.
Results
A total of 90 websites were assessed with the search term total shoulder arthroplasty and another 90 with shoulder replacement. When 37 duplicate websites for TSA and 52 for SR were eliminated, 53 (59%) and 38 (42%) unique websites were evaluated for each search term, respectively (Figure 1). (These unique websites are included in the Appendix.) Between the 2 search terms, 20 websites were duplicated. Figure 3 shows the distribution of websites by category. Total shoulder arthroplasty provided the highest percentage of health professional–oriented information; SR had the greatest percentage of patient-oriented information. Both TSA and SR had nearly the same number of advertisements and websites labeled “other.” The percentage of noncommercial websites from each search engine is represented in Figure 4. For SR, Google had 40% (12/30) noncommercial websites compared with Yahoo at 53% (16/30) and Bing at 46% (14/30). Total shoulder arthroplasty had 43% (13/30) noncommercial websites on Google, 27% (8/30) on Yahoo, and 40% (12/30) on Bing. In total, SR had more noncommercial websites, 47% (42/90), compared with 37% (33/90) for TSA.
The mean of all 3 raters for reliablity (DISCERN questions 1-8) and treatment options (DISCERN questions 9-15) is represented in the Table. For both search terms, we found that websites identified as health professional–oriented had the highest reliable mean scores, followed by patient-oriented, and advertisement at the lowest (SR: P = .054; TSA: P = .134). For SR, treatment mean scores demonstrated similar results with health professional–oriented websites receiving the highest, followed by patient-oriented and advertisement (P = .005). However, the treatment mean scores for TSA differed with patient-oriented websites receiving higher scores than health professional–oriented websites, but this was not statistically significant (P= .407). Regarding search terms, there were no significant differences between mean reliable and treatment scores across all categories.
The average overall DISCERN score for TSA websites was 2.5 (range, 1-5), compared with 2.3 (range, 1-5) for SR websites. The overall reliable score (DISCERN questions 1-8) for TSA websites was 2.6 and 2.5 for SR websites (P < .001). For TSA websites, 38% (20/53) were classified as good, having an overall DISCERN score ≥3, versus 26% (10/38) of SR websites. The overall DISCERN score for health professional–oriented websites was 2.7, patient-oriented websites received a score of 2.6, and advertisements had the lowest score at 2.4.
Discussion
Both patients and health professionals obtain information on health care subjects through the Internet, which has become the primary resource for patients.15,16 However, there are no strict regulations of the content being written. This creates a challenge for the typical user to find credible and evidence-based information, which is important because misleading information could cause undue anxiety, among other effects.17,18 The aims of this study were to determine the quality of Internet information for shoulder replacement surgeries using the medical terminology total shoulder arthroplasty (TSA) and the nontechnical term shoulder replacement (SR), and to compare the results.
After analyzing the types of websites returned for both total shoulder arthroplasty and shoulder replacement (Figure 4), it was interesting to find that using nonmedical terminology as the search term provided more noncommercial websites compared with total shoulder arthroplasty. Furthermore, Yahoo provided the highest yield of noncommercial websites at 16, with Bing at 14, when using SR as the search term. We believe the increase in noncommercial websites returned for SR was greater than for TSA because SR yielded more patient-oriented websites, which usually had html endings of .edu and .org, as shown in Figure 3 (48% of SR websites offered patient-oriented information).
Although there were more noncommercial websites for SR, the majority of the DISCERN values between the 2 search terms did not differ significantly. This is a direct result of the number of sites (20) that were duplicated across both search terms. However as seen in the Table, TSA had similar reliable mean scores for advertisements and patient-oriented websites but a slightly higher reliable score for health professional–oriented websites. We correlated this with the increased number of health professional–oriented websites returned when using TSA as the search term (Figure 3). The health professional–oriented websites explained their aims and cited their sources more consistently than did patient-oriented sites and advertisements, resulting in higher reliable scores. Although patient-oriented websites frequently lacked citations, they provided information about multiple treatment options, which were more relevant to consumers. This resulted in nearly equivalent reliable scores. Treatment means for advertisements in both SR and TSA were similar. However, treatment means for professional-oriented websites in TSA were lower than those for SR because health professional–oriented websites often were only moderately relevant to consumers, with their focus usually on 1 treatment option or on rehabilitation protocols. Although the DISCERN scores were similar between the search terms, total shoulder arthroplasty provided more websites (20) classified as good—overall DISCERN score, ≥3—than SR did (10). Advertisement websites had similar overall DISCERN scores, which we anticipated because most of the advertisements were duplicated across the search terms.
Using the 2 search terms, academic websites and commercial websites, such as WebMD, consistently received higher reliable and overall DISCERN scores. Advertisement websites, which need to deliver a clear message, frequently scored high on explicitly stating their aims and relevance to consumers, but focused on their products without discussing the benefits of other treatment options. This is significant because Internet search engines, such as Google, offer sponsor links for which organizations pay to appear at the top of the search results. This creates the potential for consumers to receive biased information because most individuals only visit the top 10 websites generated by a search engine.19
We concluded that the quality of online information relating to SR and TSA was highly variable and frequently of moderate-to-poor quality, with most overall DISCERN scores <3. The quality of information found online for this study using the DISCERN instrument is consistent with those studies using DISCERN to evaluate other medical conditions (eg, bunions, chronic pain, general anesthesia, and anterior cruciate ligament reconstruction).2,9,15,19 These studies also concluded that online information varies tremendously in quality and completeness.
This study has several limitations. Websites were searched at a single time point and, because Internet resources are frequently updated, the results of this study could vary. Furthermore, although Google, Yahoo, and Bing are 3 of the most popular search engines, these are not the only resources patients use when searching the Internet for health-related information. Other search engines, such as Pubmed.gov and MSN.com, could provide additional websites for Internet users. Lastly, although DISCERN is validated to address the quality of information available online, it does not evaluate the accuracy of the information.8 Our use of DISCERN involves 2 scales, a binary yes/no (ratings, 1 and 5) and an ordinal scale (ratings, 2-4). As such, a single mean summary statistic cannot be calculated.
Conclusion
The information available on the Internet pertaining to TSA and SR is highly variable and provides mostly moderate-to-poor quality information based on the DISCERN instrument. Many websites failed to describe the benefits and the risks of different treatment options, including nonoperative management. Health care professionals should be aware that patients often refer to the Internet as a primary resource for obtaining medical information. It is important to direct patients to websites that provide accurate information, because patients who educate themselves about their conditions and actively participate in decision-making may have improved health outcomes.20-22 Overall, academic websites and commercial websites, such as WebMD and OrthoInfo, generally had higher DISCERN scores when using either search term. Of major concern is the potential for misleading advertisements or incorrect information that can negatively affect health outcomes. This study found that using nonmedical terminology (SR) provided more noncommercial and patient-oriented websites, especially through Yahoo. This study highlights the need for more comprehensive online information pertaining to shoulder replacement that can better serve as a resource for Internet users.
1. Eysenbach G, Powell J, Kuss O, Sa ER. Empirical studies assessing the quality of health information for consumers on the world wide web: a systematic review. JAMA. 2002;287(20):2691-2700.
2. Bruce-Brand RA, Baker JF, Byrne DP, Hogan NA, McCarthy T. Assessment of the quality and content of information on anterior cruciate ligament reconstruction on the internet. Arthroscopy. 2013;29(6):1095-1100.
3. Computer and internet use in the United States: population characteristics. US Census Bureau website. http://www.census.gov/hhes/computer/. Accessed December 11, 2015.
4. Fox S, Duggan M. Health online 2013. Pew Research Center website. http://pewinternet.org/Reports/2013/Health-online.aspx. Published January 15, 2013. Accessed November 24, 2015.
5. Smith A. Older adults and technology use. Pew Research Center website. http://www.pewinternet.org/2014/04/03/older-adults-and-technology-use. Published April 3, 2014. Accessed November 24, 2015.
6. Shuyler KS, Knight KM. What are patients seeking when they turn to the internet? Qualitative content analysis of questions asked by visitors to an orthopaedics web site. J Med Internet Res. 2003;5(4):e24.
7. Meredith P, Emberton M, Wood C, Smith J. Comparison of patients’ needs for information on prostate surgery with printed materials provided by surgeons. Qual Health Care. 1995;4(1):18-23.
8. Charnock D, Shepperd S, Needham G, Gann R. DISCERN: An instrument for judging the quality of written consumer health information on treatment choices. J Epidemiol Community Health. 1999;53(2):105-111.
9. Kaicker J, Debono VB, Dang W, Buckley N, Thabane L. Assessment of the quality and variability of health information on chronic pain websites using the DISCERN instrument. BMC Med. 2010;8(1):59.
10. Griffiths KM, Christensen H. Website quality indicators for consumers. J Med Internet Res. 2005;7(5):e55.
11. Wiater JM. Shoulder joint replacement. American Academy of Orthopedic Surgeons website. http://orthoinfo.aaos.org/topic.cfm?topic=A00094. Updated December 2011. Accessed November 24, 2015.
12. Kim SH, Wise BL, Zhang Y, Szabo RM. Increasing incidence of shoulder arthroplasty in the united states. J Bone Joint Surg Am. 2011;93(24):2249-2254.
13. Liberati A, Altman DG, Tetzlaff J, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. Ann Intern Med. 2009;151(4):W65-W94.
14. Nason GJ, Baker JF, Byrne DP, Noel J, Moore D, Kiely PJ. Scoliosis-specific information on the internet: has the “information highway” led to better information provision? Spine. 2012;37(21):E1364-E1369.
15. Starman JS, Gettys FK, Capo JA, Fleischli JE, Norton HJ, Karunakar MA. Quality and content of internet-based information for ten common orthopaedic sports medicine diagnoses. J Bone Joint Surg Am. 2010;92(7):1612-1618.
16. Bernstein J, Ahn J, Veillette C. The future of orthopaedic information management. J Bone Joint Surg Am. 2012;94(13):e95.
17. Berland GK, Elliott MN, Morales LS, et al. Health information on the Internet: accessibility, quality, and readability in English and Spanish. JAMA. 2001;285(20):2612-2621.
18. Fallowfield LJ, Hall A, Maguire GP, Baum M. Psychological outcomes of different treatment policies in women with early breast cancer outside a clinical trial. BMJ. 1990;301(6752):575-580.
19. Chong YM, Fraval A, Chandrananth J, Plunkett V, Tran P. Assessment of the quality of web-based information on bunions. Foot Ankle Int. 2013;34(8):1134-1139.
20. Brody DS, Miller SM, Lerman CE, Smith DG, Caputo GC. Patient perception of involvement in medical care. J Gen Intern Med. 1989;4(6):506-511.
21. Greenfield S, Kaplan S, Ware JE Jr. Expanding patient involvement in care. Effects on patient outcomes. Ann Intern Med. 1985;102(4):520-528.
22. Kaplan SH, Greenfield S, Ware JE Jr. Assessing the effects of physician-patient interactions on the outcomes of chronic disease. Med Care. 1989;27(3 suppl):S110-S127.
1. Eysenbach G, Powell J, Kuss O, Sa ER. Empirical studies assessing the quality of health information for consumers on the world wide web: a systematic review. JAMA. 2002;287(20):2691-2700.
2. Bruce-Brand RA, Baker JF, Byrne DP, Hogan NA, McCarthy T. Assessment of the quality and content of information on anterior cruciate ligament reconstruction on the internet. Arthroscopy. 2013;29(6):1095-1100.
3. Computer and internet use in the United States: population characteristics. US Census Bureau website. http://www.census.gov/hhes/computer/. Accessed December 11, 2015.
4. Fox S, Duggan M. Health online 2013. Pew Research Center website. http://pewinternet.org/Reports/2013/Health-online.aspx. Published January 15, 2013. Accessed November 24, 2015.
5. Smith A. Older adults and technology use. Pew Research Center website. http://www.pewinternet.org/2014/04/03/older-adults-and-technology-use. Published April 3, 2014. Accessed November 24, 2015.
6. Shuyler KS, Knight KM. What are patients seeking when they turn to the internet? Qualitative content analysis of questions asked by visitors to an orthopaedics web site. J Med Internet Res. 2003;5(4):e24.
7. Meredith P, Emberton M, Wood C, Smith J. Comparison of patients’ needs for information on prostate surgery with printed materials provided by surgeons. Qual Health Care. 1995;4(1):18-23.
8. Charnock D, Shepperd S, Needham G, Gann R. DISCERN: An instrument for judging the quality of written consumer health information on treatment choices. J Epidemiol Community Health. 1999;53(2):105-111.
9. Kaicker J, Debono VB, Dang W, Buckley N, Thabane L. Assessment of the quality and variability of health information on chronic pain websites using the DISCERN instrument. BMC Med. 2010;8(1):59.
10. Griffiths KM, Christensen H. Website quality indicators for consumers. J Med Internet Res. 2005;7(5):e55.
11. Wiater JM. Shoulder joint replacement. American Academy of Orthopedic Surgeons website. http://orthoinfo.aaos.org/topic.cfm?topic=A00094. Updated December 2011. Accessed November 24, 2015.
12. Kim SH, Wise BL, Zhang Y, Szabo RM. Increasing incidence of shoulder arthroplasty in the united states. J Bone Joint Surg Am. 2011;93(24):2249-2254.
13. Liberati A, Altman DG, Tetzlaff J, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. Ann Intern Med. 2009;151(4):W65-W94.
14. Nason GJ, Baker JF, Byrne DP, Noel J, Moore D, Kiely PJ. Scoliosis-specific information on the internet: has the “information highway” led to better information provision? Spine. 2012;37(21):E1364-E1369.
15. Starman JS, Gettys FK, Capo JA, Fleischli JE, Norton HJ, Karunakar MA. Quality and content of internet-based information for ten common orthopaedic sports medicine diagnoses. J Bone Joint Surg Am. 2010;92(7):1612-1618.
16. Bernstein J, Ahn J, Veillette C. The future of orthopaedic information management. J Bone Joint Surg Am. 2012;94(13):e95.
17. Berland GK, Elliott MN, Morales LS, et al. Health information on the Internet: accessibility, quality, and readability in English and Spanish. JAMA. 2001;285(20):2612-2621.
18. Fallowfield LJ, Hall A, Maguire GP, Baum M. Psychological outcomes of different treatment policies in women with early breast cancer outside a clinical trial. BMJ. 1990;301(6752):575-580.
19. Chong YM, Fraval A, Chandrananth J, Plunkett V, Tran P. Assessment of the quality of web-based information on bunions. Foot Ankle Int. 2013;34(8):1134-1139.
20. Brody DS, Miller SM, Lerman CE, Smith DG, Caputo GC. Patient perception of involvement in medical care. J Gen Intern Med. 1989;4(6):506-511.
21. Greenfield S, Kaplan S, Ware JE Jr. Expanding patient involvement in care. Effects on patient outcomes. Ann Intern Med. 1985;102(4):520-528.
22. Kaplan SH, Greenfield S, Ware JE Jr. Assessing the effects of physician-patient interactions on the outcomes of chronic disease. Med Care. 1989;27(3 suppl):S110-S127.
Incidence, Risk Factors, and Outcome Trends of Acute Kidney Injury in Elective Total Hip and Knee Arthroplasty
Degenerative arthritis is a widespread chronic condition with an incidence of almost 43 million and annual health care costs of $60 billion in the United States alone.1 Although many cases can be managed symptomatically with medical therapy and intra-articular injections,2 many patients experience disease progression resulting in decreased ambulatory ability and work productivity. For these patients, elective hip and knee arthroplasties can drastically improve quality of life and functionality.3,4 Over the past decade, there has been a marked increase in the number of primary and revision total hip and knee arthroplasties performed in the United States. By 2030, the demand for primary total hip arthroplasties will grow an estimated 174%, to 572,000 procedures. Likewise, the demand for primary total knee arthroplasties is projected to grow by 673%, to 3.48 million procedures.5 However, though better surgical techniques and technology have led to improved functional outcomes, there is still substantial risk for complications in the perioperative period, especially in the geriatric population, in which substantial comorbidities are common.6-9
Acute kidney injury (AKI) is a common public health problem in hospitalized patients and in patients undergoing procedures. More than one-third of all AKI cases occur in surgical settings.10,11 Over the past decade, both community-acquired and in-hospital AKIs rapidly increased in incidence in all major clinical settings.12-14 Patients with AKI have high rates of adverse outcomes during hospitalization and discharge.11,15 Sequelae of AKIs include worsening chronic kidney disease (CKD) and progression to end-stage renal disease, necessitating either long-term dialysis or transplantation.12 This in turn leads to exacerbated disability, diminished quality of life, and disproportionate burden on health care resources.
Much of our knowledge about postoperative AKI has been derived from cardiovascular, thoracic, and abdominal surgery settings. However, there is a paucity of data on epidemiology and trends for either AKI or associated outcomes in patients undergoing major orthopedic surgery. The few studies to date either were single-center or had inadequate sample sizes for appropriately powered analysis of the risk factors and outcomes related to AKI.16
In the study reported here, we analyzed a large cohort of patients from a nationwide multicenter database to determine the incidence of and risk factors for AKI. We also examined the mortality and adverse discharges associated with AKI after major joint surgery. Lastly, we assessed temporal trends in both incidence and outcomes of AKI, including the death risk attributable to AKI.
Methods
Database
We extracted our study cohort from the Nationwide Inpatient Sample (NIS) and the National Inpatient Sample of Healthcare Cost and Utilization Project (HCUP) compiled by the Agency for Healthcare Research and Quality.17 NIS, the largest inpatient care database in the United States, stores data from almost 8 million stays in about 1000 hospitals across the country each year. Its participating hospital pool consists of about 20% of US community hospitals, resulting in a sampling frame comprising about 90% of all hospital discharges in the United States. This allows for calculation of precise, weighted nationwide estimates. Data elements within NIS are drawn from hospital discharge abstracts that indicate all procedures performed. NIS also stores information on patient characteristics, length of stay (LOS), discharge disposition, postoperative morbidity, and observed in-hospital mortality. However, it stores no information on long-term follow-up or complications after discharge.
Data Analysis
For the period 2002–2012, we queried the NIS database for hip and knee arthroplasties with primary diagnosis codes for osteoarthritis and secondary codes for AKI. We excluded patients under age 18 years and patients with diagnosis codes for hip and knee fracture/necrosis, inflammatory/infectious arthritis, or bone neoplasms (Table 1). We then extracted baseline characteristics of the study population. Patient-level characteristics included age, sex, race, quartile classification of median household income according to postal (ZIP) code, and primary payer (Medicare/Medicaid, private insurance, self-pay, no charge). Hospital-level characteristics included hospital location (urban, rural), hospital bed size (small, medium, large), region (Northeast, Midwest/North Central, South, West), and teaching status. We defined illness severity and likelihood of death using Deyo’s modification of the Charlson Comorbidity Index (CCI), which draws on principal and secondary ICD-9-CM (International Classification of Diseases, Ninth Revision-Clinical Modification) diagnosis codes, procedure codes, and patient demographics to estimate a patient’s mortality risk. This method reliably predicts mortality and readmission in the orthopedic population.18,19 We assessed the effect of AKI on 4 outcomes, including in-hospital mortality, discharge disposition, LOS, and cost of stay. Discharge disposition was grouped by either (a) home or short-term facility or (b) adverse discharge. Home or short-term facility covered routine, short-term hospital, against medical advice, home intravenous provider, another rehabilitation facility, another institution for outpatient services, institution for outpatient services, discharged alive, and destination unknown; adverse discharge covered skilled nursing facility, intermediate care, hospice home, hospice medical facility, long-term care hospital, and certified nursing facility. This dichotomization of discharge disposition is often used in studies of NIS data.20
Statistical Analyses
We compared the baseline characteristics of hospitalized patients with and without AKI. To test for significance, we used the χ2 test for categorical variables, the Student t test for normally distributed continuous variables, the Wilcoxon rank sum test for non-normally distributed continuous variables, and the Cochran-Armitage test for trends in AKI incidence. We used survey logistic regression models to calculate adjusted odds ratios (ORs) with 95% confidence intervals (95% CIs) in order to estimate the predictors of AKI and the impact of AKI on hospital outcomes. We constructed final models after adjusting for confounders, testing for potential interactions, and ensuring no multicolinearity between covariates. Last, we computed the risk proportion of death attributable to AKI, indicating the proportion of deaths that could potentially be avoided if AKI and its complications were abrogated.21
We performed all statistical analyses with SAS Version 9.3 (SAS Institute) using designated weight values to produce weighted national estimates. The threshold for statistical significance was set at P < .01 (with ORs and 95% CIs that excluded 1).
Results
AKI Incidence, Risk Factors, and Trends
We identified 7,235,251 patients who underwent elective hip or knee arthroplasty for osteoarthritis between 2002 and 2012—an estimate consistent with data from the Centers for Disease Control and Prevention.22 Of that total, 94,367 (1.3%) had AKI. The proportion of discharges diagnosed with AKI increased rapidly over the decade, from 0.5% in 2002 to 1.8% to 1.9% in the period 2010–2012. This upward trend was highly significant (Ptrend < .001) (Figure 1). Patients with AKI (vs patients without AKI) were more likely to be older (mean age, 70 vs 66 years; P < .001), male (50.8% vs 38.4%; P < .001), and black (10.07% vs 5.15%; P<. 001). They were also found to have a significantly higher comorbidity score (mean CCI, 2.8 vs 1.5; P < .001) and higher proportions of comorbidities, including hypertension, CKD, atrial fibrillation, diabetes mellitus (DM), congestive heart failure, chronic liver disease, and hepatitis C virus infection. In addition, AKI was associated with perioperative myocardial infarction (MI), sepsis, cardiac catheterization, and blood transfusion. Regarding socioeconomic characteristics, patients with AKI were more likely to have Medicare/Medicaid insurance (72.26% vs 58.06%; P < .001) and to belong to the extremes of income categories (Table 2).
Using multivariable logistic regression, we found that increased age (1.11 increase in adjusted OR for every year older; 95% CI, 1.09-1.14; P < .001), male sex (adjusted OR, 1.65; 95% CI, 1.60-1.71; P < .001), and black race (adjusted OR, 1.57; 95% CI, 1.45-1.69; P < .001) were significantly associated with postoperative AKI. Regarding comorbidities, baseline CKD (adjusted OR, 8.64; 95% CI, 8.14-9.18; P < .001) and congestive heart failure (adjusted OR, 2.74; 95% CI, 2.57-2.92; P< .0001) were most significantly associated with AKI. Perioperative events, including sepsis (adjusted OR, 35.64; 95% CI, 30.28-41.96; P < .0001), MI (adjusted OR, 6.14; 95% CI, 5.17-7.28; P < .0001), and blood transfusion (adjusted OR, 2.28; 95% CI, 2.15-2.42; P < .0001), were also strongly associated with postoperative AKI. Last, compared with urban hospitals and small hospital bed size, rural hospitals (adjusted OR, 0.70; 95% CI, 0.60-0.81; P< .001) and large bed size (adjusted OR, 0.82; 95% CI, 0.70-0.93; P = .003) were associated with lower probability of developing AKI (Table 3).
Figure 2 elucidates the frequency of AKI based on a combination of key preoperative comorbid conditions and postoperative complications—demonstrating that the proportion of AKI cases associated with other postoperative complications is significantly higher in the CKD and concomitant DM/CKD patient populations. Patients hospitalized with CKD exhibited higher rates of AKI in cases involving blood transfusion (20.9% vs 1.8%; P < .001), acute MI (48.9% vs 13.8%; P < .001), and sepsis (74.7% vs 36.3%;P< .001) relative to patients without CKD. Similarly, patients with concomitant DM/CKD exhibited higher rates of AKI in cases involving blood transfusion (23% vs 1.9%; P< .001), acute MI (51.1% vs 12.1%; P< .001), and sepsis (75% vs 38.2%; P < .001) relative to patients without either condition. However, patients hospitalized with DM alone exhibited only marginally higher rates of AKI in cases involving blood transfusion (4.7% vs 2%; P < .01) and acute MI (19.2% vs 16.7%; P< .01) and a lower rate in cases involving sepsis (38.2% vs 41.7%; P < .01) relative to patients without DM. These data suggest that CKD is the most significant clinically relevant risk factor for AKI and that CKD may synergize with DM to raise the risk for AKI.
Outcomes
We then analyzed the impact of AKI on hospital outcomes, including in-hospital mortality, discharge disposition, LOS, and cost of care. Mortality was significantly higher in patients with AKI than in patients without it (2.08% vs 0.06%; P < .001). Even after adjusting for confounders (eg, demographics, comorbidity burden, perioperative sepsis, hospital-level characteristics), AKI was still associated with strikingly higher odds of in-hospital death (adjusted OR, 11.32; 95% CI, 9.34-13.74; P < .001). However, analysis of temporal trends indicated that the odds for adjusted mortality associated with AKI decreased from 18.09 to 9.45 (Ptrend = .01) over the period 2002–2012 (Figure 3). This decrease in odds of death was countered by an increase in incidence of AKI, resulting in a stable attributable risk proportion (97.9% in 2002 to 97.3% in 2012; Ptrend = .90) (Table 4). Regarding discharge disposition, patients with AKI were much less likely to be discharged home (41.35% vs 62.59%; P < .001) and more likely to be discharged to long-term care (56.37% vs 37.03%; P< .001). After adjustment for confounders, AKI was associated with significantly increased odds of adverse discharge (adjusted OR, 2.24; 95% CI, 2.12-2.36; P< .001). Analysis of temporal trends revealed no appreciable decrease in the adjusted odds of adverse discharge between 2002 (adjusted OR, 1.87; 95% CI, 1.37-2.55; P < .001) and 2012 (adjusted OR, 1.93; 95% CI, 1.76-2.11; P < .001) (Figure 4, Table 5). Last, both mean LOS (5 days vs 3 days; P < .001) and mean cost of hospitalization (US $22,269 vs $15,757; P < .001) were significantly higher in patients with AKI.
Discussion
In this study, we found that the incidence of AKI among hospitalized patients increased 4-fold between 2002 and 2012. Moreover, we identified numerous patient-specific, hospital-specific, perioperative risk factors for AKI. Most important, we found that AKI was associated with a strikingly higher risk of in-hospital death, and surviving patients were more likely to experience adverse discharge. Although the adjusted mortality rate associated with AKI decreased over that decade, the attributable risk proportion remained stable.
Few studies have addressed this significant public health concern. In one recent study in Australia, Kimmel and colleagues16 identified risk factors for AKI but lacked data on AKI outcomes. In a study of complications and mortality occurring after orthopedic surgery, Belmont and colleagues22 categorized complications as either local or systemic but did not examine renal complications. Only 2 other major studies have been conducted on renal outcomes associated with major joint surgery, and both were limited to patients with acute hip fractures. The first included acute fracture surgery patients and omitted elective joint surgery patients, and it evaluated admission renal function but not postoperative AKI.22 The second study had a sample size of only 170 patients.23 Thus, the literature leaves us with a crucial knowledge gap in renal outcomes and their postoperative impact in elective arthroplasties.
The present study filled this information gap by examining the incidence, risk factors, outcomes, and temporal trends of AKI after elective hip and knee arthroplasties. The increasing incidence of AKI in this surgical setting is similar to that of AKI in other surgical settings (cardiac and noncardiac).21 Although our analysis was limited by lack of perioperative management data, patients undergoing elective joint arthroplasty can experience kidney dysfunction for several reasons, including volume depletion, postoperative sepsis, and influence of medications, such as nonsteroidal anti-inflammatory drugs (NSAIDs), especially in older patients with more comorbidities and a higher burden of CKD. Each of these factors can cause renal dysfunction in patients having orthopedic procedures.24 Moreover, NSAID use among elective joint arthroplasty patients is likely higher because of an emphasis on multimodal analgesia, as recent randomized controlled trials have demonstrated the efficacy of NSAID use in controlling pain without increasing bleeding.25-27 Our results also demonstrated that the absolute incidence of AKI after orthopedic surgery is relatively low. One possible explanation for this phenomenon is that the definitions used were based on ICD-9-CM codes that underestimate the true incidence of AKI.
Consistent with other studies, we found that certain key preoperative comorbid conditions and postoperative events were associated with higher AKI risk. We stratified the rate of AKI associated with each postoperative event (sepsis, acute MI, cardiac catheterization, need for transfusion) by DM/CKD comorbidity. CKD was associated with significantly higher AKI risk across all postoperative complications. This information may provide clinicians with bedside information that can be used to determine which patients may be at higher or lower risk for AKI.
Our analysis of patient outcomes revealed that, though AKI was relatively uncommon, it increased the risk for death during hospitalization more than 10-fold between 2002 and 2012. Although the adjusted OR of in-hospital mortality decreased over the decade studied, the concurrent increase in AKI incidence caused the attributable risk of death associated with AKI to essentially remain the same. This observation is consistent with recent reports from cardiac surgery settings.21 These data together suggest that ameliorating occurrences of AKI would decrease mortality and increase quality of care for patients undergoing elective joint surgeries.
We also examined the effect of AKI on resource use by studying LOS, costs, and risk for adverse discharge. Much as in other surgical settings, AKI increased both LOS and overall hospitalization costs. More important, AKI was associated with increased adverse discharge (discharge to long-term care or nursing homes). Although exact reasons are unclear, we can speculate that postoperative renal dysfunction precludes early rehabilitation, impeding desired functional outcome and disposition.28,29 Given the projected increases in primary and revision hip and knee arthroplasties,5 these data predict that the impact of AKI on health outcomes will increase alarmingly in coming years.
There are limitations to our study. First, it was based on administrative data and lacked patient-level and laboratory data. As reported, the sensitivity of AKI codes remains moderate,30 so the true burden may be higher than indicated here. As the definition of AKI was based on administrative coding, we also could not estimate severity, though previous studies have found that administrative codes typically capture a more severe form of disease.31 Another limitation is that, because the data were deidentified, we could not delineate the risk for recurrent AKI in repeated surgical procedures, though this cohort unlikely was large enough to qualitatively affect our results. The third limitation is that, though we used CCI to adjust for the comorbidity burden, we were unable to account for other unmeasured confounders associated with increased AKI incidence, such as specific medication use. In addition, given the lack of patient-level data, we could not analyze the specific factors responsible for AKI in the perioperative period. Nevertheless, the strengths of a nationally representative sample, such as large sample size and generalizability, outweigh these limitations.
Conclusion
AKI is potentially an important quality indicator of elective joint surgery, and reducing its incidence is therefore essential for quality improvement. Given that hip and knee arthroplasties are projected to increase exponentially, as is the burden of comorbid conditions in this population, postoperative AKI will continue to have an incremental impact on health and health care resources. Thus, a carefully planned approach of interdisciplinary perioperative care is warranted to reduce both the risk and the consequences of this devastating condition.
1. Reginster JY. The prevalence and burden of arthritis. Rheumatology. 2002;41(supp 1):3-6.
2. Kullenberg B, Runesson R, Tuvhag R, Olsson C, Resch S. Intraarticular corticosteroid injection: pain relief in osteoarthritis of the hip? J Rheumatol. 2004;31(11):2265-2268.
3. Kawasaki M, Hasegawa Y, Sakano S, Torii Y, Warashina H. Quality of life after several treatments for osteoarthritis of the hip. J Orthop Sci. 2003;8(1):32-35.
4. Ethgen O, Bruyère O, Richy F, Dardennes C, Reginster JY. Health-related quality of life in total hip and total knee arthroplasty. A qualitative and systematic review of the literature. J Bone Joint Surg Am. 2004;86(5):963-974.
5. Kurtz S, Ong K, Lau E, Mowat F, Halpern M. Projections of primary and revision hip and knee arthroplasty in the United States from 2005 to 2030. J Bone Joint Surg Am. 2007;89(4):780-785.
6. Matlock D, Earnest M, Epstein A. Utilization of elective hip and knee arthroplasty by age and payer. Clin Orthop Relat Res. 2008;466(4):914-919.
7. Parvizi J, Holiday AD, Ereth MH, Lewallen DG. The Frank Stinchfield Award. Sudden death during primary hip arthroplasty. Clin Orthop Relat Res. 1999;(369):39-48.
8. Parvizi J, Mui A, Purtill JJ, Sharkey PF, Hozack WJ, Rothman RH. Total joint arthroplasty: when do fatal or near-fatal complications occur? J Bone Joint Surg Am. 2007;89(1):27-32.
9. Parvizi J, Sullivan TA, Trousdale RT, Lewallen DG. Thirty-day mortality after total knee arthroplasty. J Bone Joint Surg Am. 2001;83(8):1157-1161.
10. Uchino S, Kellum JA, Bellomo R, et al; Beginning and Ending Supportive Therapy for the Kidney (BEST Kidney) Investigators. Acute renal failure in critically ill patients: a multinational, multicenter study. JAMA. 2005;294(7):813-818.
11. Thakar CV. Perioperative acute kidney injury. Adv Chronic Kidney Dis. 2013;20(1):67-75.
12. Hsu CY, Chertow GM, McCulloch CE, Fan D, Ordoñez JD, Go AS. Nonrecovery of kidney function and death after acute on chronic renal failure. Clin J Am Soc Nephrol. 2009;4(5):891-898.
13. Rewa O, Bagshaw SM. Acute kidney injury—epidemiology, outcomes and economics. Nat Rev Nephrol. 2014;10(4):193-207.
14. Thakar CV, Worley S, Arrigain S, Yared JP, Paganini EP. Influence of renal dysfunction on mortality after cardiac surgery: modifying effect of preoperative renal function. Kidney Int. 2005;67(3):1112-1119.
15. Zeng X, McMahon GM, Brunelli SM, Bates DW, Waikar SS. Incidence, outcomes, and comparisons across definitions of AKI in hospitalized individuals. Clin J Am Soc Nephrol. 2014;9(1):12-20.
16. Kimmel LA, Wilson S, Janardan JD, Liew SM, Walker RG. Incidence of acute kidney injury following total joint arthroplasty: a retrospective review by RIFLE criteria. Clin Kidney J. 2014;7(6):546-551.
17. Agency for Healthcare Research and Quality. Healthcare Cost and Utilization Project (HCUP) databases, 2002–2012. Rockville, MD: Agency for Healthcare Research and Quality.
18. Bjorgul K, Novicoff WM, Saleh KJ. Evaluating comorbidities in total hip and knee arthroplasty: available instruments. J Orthop Traumatol. 2010;11(4):203-209.
19. Voskuijl T, Hageman M, Ring D. Higher Charlson Comorbidity Index Scores are associated with readmission after orthopaedic surgery. Clin Orthop Relat Res. 2014;472(5):1638-1644.
20. Chertow GM, Burdick E, Honour M, Bonventre JV, Bates DW. Acute kidney injury, mortality, length of stay, and costs in hospitalized patients. J Am Soc Nephrol. 2005;16(11):3365-3370.
21. Lenihan CR, Montez-Rath ME, Mora Mangano CT, Chertow GM, Winkelmayer WC. Trends in acute kidney injury, associated use of dialysis, and mortality after cardiac surgery, 1999 to 2008. Ann Thorac Surg. 2013;95(1):20-28.
22. Belmont PJ Jr, Goodman GP, Waterman BR, Bader JO, Schoenfeld AJ. Thirty-day postoperative complications and mortality following total knee arthroplasty: incidence and risk factors among a national sample of 15,321 patients. J Bone Joint Surg Am. 2014;96(1):20-26.
23. Bennet SJ, Berry OM, Goddard J, Keating JF. Acute renal dysfunction following hip fracture. Injury. 2010;41(4):335-338.
24. Kateros K, Doulgerakis C, Galanakos SP, Sakellariou VI, Papadakis SA, Macheras GA. Analysis of kidney dysfunction in orthopaedic patients. BMC Nephrol. 2012;13:101.
25. Huang YM, Wang CM, Wang CT, Lin WP, Horng LC, Jiang CC. Perioperative celecoxib administration for pain management after total knee arthroplasty—a randomized, controlled study. BMC Musculoskelet Disord. 2008;9:77.
26. Kelley TC, Adams MJ, Mulliken BD, Dalury DF. Efficacy of multimodal perioperative analgesia protocol with periarticular medication injection in total knee arthroplasty: a randomized, double-blinded study. J Arthroplasty. 2013;28(8):1274-1277.
27. Lamplot JD, Wagner ER, Manning DW. Multimodal pain management in total knee arthroplasty: a prospective randomized controlled trial. J Arthroplasty. 2014;29(2):329-334.
28. Munin MC, Rudy TE, Glynn NW, Crossett LS, Rubash HE. Early inpatient rehabilitation after elective hip and knee arthroplasty. JAMA. 1998;279(11):847-852.
29. Pua YH, Ong PH. Association of early ambulation with length of stay and costs in total knee arthroplasty: retrospective cohort study. Am J Phys Med Rehabil. 2014;93(11):962-970.
30. Waikar SS, Wald R, Chertow GM, et al. Validity of International Classification of Diseases, Ninth Revision, Clinical Modification codes for acute renal failure. J Am Soc Nephrol. 2006;17(6):1688-1694.
31. Grams ME, Waikar SS, MacMahon B, Whelton S, Ballew SH, Coresh J. Performance and limitations of administrative data in the identification of AKI. Clin J Am Soc Nephrol. 2014;9(4):682-689.
Degenerative arthritis is a widespread chronic condition with an incidence of almost 43 million and annual health care costs of $60 billion in the United States alone.1 Although many cases can be managed symptomatically with medical therapy and intra-articular injections,2 many patients experience disease progression resulting in decreased ambulatory ability and work productivity. For these patients, elective hip and knee arthroplasties can drastically improve quality of life and functionality.3,4 Over the past decade, there has been a marked increase in the number of primary and revision total hip and knee arthroplasties performed in the United States. By 2030, the demand for primary total hip arthroplasties will grow an estimated 174%, to 572,000 procedures. Likewise, the demand for primary total knee arthroplasties is projected to grow by 673%, to 3.48 million procedures.5 However, though better surgical techniques and technology have led to improved functional outcomes, there is still substantial risk for complications in the perioperative period, especially in the geriatric population, in which substantial comorbidities are common.6-9
Acute kidney injury (AKI) is a common public health problem in hospitalized patients and in patients undergoing procedures. More than one-third of all AKI cases occur in surgical settings.10,11 Over the past decade, both community-acquired and in-hospital AKIs rapidly increased in incidence in all major clinical settings.12-14 Patients with AKI have high rates of adverse outcomes during hospitalization and discharge.11,15 Sequelae of AKIs include worsening chronic kidney disease (CKD) and progression to end-stage renal disease, necessitating either long-term dialysis or transplantation.12 This in turn leads to exacerbated disability, diminished quality of life, and disproportionate burden on health care resources.
Much of our knowledge about postoperative AKI has been derived from cardiovascular, thoracic, and abdominal surgery settings. However, there is a paucity of data on epidemiology and trends for either AKI or associated outcomes in patients undergoing major orthopedic surgery. The few studies to date either were single-center or had inadequate sample sizes for appropriately powered analysis of the risk factors and outcomes related to AKI.16
In the study reported here, we analyzed a large cohort of patients from a nationwide multicenter database to determine the incidence of and risk factors for AKI. We also examined the mortality and adverse discharges associated with AKI after major joint surgery. Lastly, we assessed temporal trends in both incidence and outcomes of AKI, including the death risk attributable to AKI.
Methods
Database
We extracted our study cohort from the Nationwide Inpatient Sample (NIS) and the National Inpatient Sample of Healthcare Cost and Utilization Project (HCUP) compiled by the Agency for Healthcare Research and Quality.17 NIS, the largest inpatient care database in the United States, stores data from almost 8 million stays in about 1000 hospitals across the country each year. Its participating hospital pool consists of about 20% of US community hospitals, resulting in a sampling frame comprising about 90% of all hospital discharges in the United States. This allows for calculation of precise, weighted nationwide estimates. Data elements within NIS are drawn from hospital discharge abstracts that indicate all procedures performed. NIS also stores information on patient characteristics, length of stay (LOS), discharge disposition, postoperative morbidity, and observed in-hospital mortality. However, it stores no information on long-term follow-up or complications after discharge.
Data Analysis
For the period 2002–2012, we queried the NIS database for hip and knee arthroplasties with primary diagnosis codes for osteoarthritis and secondary codes for AKI. We excluded patients under age 18 years and patients with diagnosis codes for hip and knee fracture/necrosis, inflammatory/infectious arthritis, or bone neoplasms (Table 1). We then extracted baseline characteristics of the study population. Patient-level characteristics included age, sex, race, quartile classification of median household income according to postal (ZIP) code, and primary payer (Medicare/Medicaid, private insurance, self-pay, no charge). Hospital-level characteristics included hospital location (urban, rural), hospital bed size (small, medium, large), region (Northeast, Midwest/North Central, South, West), and teaching status. We defined illness severity and likelihood of death using Deyo’s modification of the Charlson Comorbidity Index (CCI), which draws on principal and secondary ICD-9-CM (International Classification of Diseases, Ninth Revision-Clinical Modification) diagnosis codes, procedure codes, and patient demographics to estimate a patient’s mortality risk. This method reliably predicts mortality and readmission in the orthopedic population.18,19 We assessed the effect of AKI on 4 outcomes, including in-hospital mortality, discharge disposition, LOS, and cost of stay. Discharge disposition was grouped by either (a) home or short-term facility or (b) adverse discharge. Home or short-term facility covered routine, short-term hospital, against medical advice, home intravenous provider, another rehabilitation facility, another institution for outpatient services, institution for outpatient services, discharged alive, and destination unknown; adverse discharge covered skilled nursing facility, intermediate care, hospice home, hospice medical facility, long-term care hospital, and certified nursing facility. This dichotomization of discharge disposition is often used in studies of NIS data.20
Statistical Analyses
We compared the baseline characteristics of hospitalized patients with and without AKI. To test for significance, we used the χ2 test for categorical variables, the Student t test for normally distributed continuous variables, the Wilcoxon rank sum test for non-normally distributed continuous variables, and the Cochran-Armitage test for trends in AKI incidence. We used survey logistic regression models to calculate adjusted odds ratios (ORs) with 95% confidence intervals (95% CIs) in order to estimate the predictors of AKI and the impact of AKI on hospital outcomes. We constructed final models after adjusting for confounders, testing for potential interactions, and ensuring no multicolinearity between covariates. Last, we computed the risk proportion of death attributable to AKI, indicating the proportion of deaths that could potentially be avoided if AKI and its complications were abrogated.21
We performed all statistical analyses with SAS Version 9.3 (SAS Institute) using designated weight values to produce weighted national estimates. The threshold for statistical significance was set at P < .01 (with ORs and 95% CIs that excluded 1).
Results
AKI Incidence, Risk Factors, and Trends
We identified 7,235,251 patients who underwent elective hip or knee arthroplasty for osteoarthritis between 2002 and 2012—an estimate consistent with data from the Centers for Disease Control and Prevention.22 Of that total, 94,367 (1.3%) had AKI. The proportion of discharges diagnosed with AKI increased rapidly over the decade, from 0.5% in 2002 to 1.8% to 1.9% in the period 2010–2012. This upward trend was highly significant (Ptrend < .001) (Figure 1). Patients with AKI (vs patients without AKI) were more likely to be older (mean age, 70 vs 66 years; P < .001), male (50.8% vs 38.4%; P < .001), and black (10.07% vs 5.15%; P<. 001). They were also found to have a significantly higher comorbidity score (mean CCI, 2.8 vs 1.5; P < .001) and higher proportions of comorbidities, including hypertension, CKD, atrial fibrillation, diabetes mellitus (DM), congestive heart failure, chronic liver disease, and hepatitis C virus infection. In addition, AKI was associated with perioperative myocardial infarction (MI), sepsis, cardiac catheterization, and blood transfusion. Regarding socioeconomic characteristics, patients with AKI were more likely to have Medicare/Medicaid insurance (72.26% vs 58.06%; P < .001) and to belong to the extremes of income categories (Table 2).
Using multivariable logistic regression, we found that increased age (1.11 increase in adjusted OR for every year older; 95% CI, 1.09-1.14; P < .001), male sex (adjusted OR, 1.65; 95% CI, 1.60-1.71; P < .001), and black race (adjusted OR, 1.57; 95% CI, 1.45-1.69; P < .001) were significantly associated with postoperative AKI. Regarding comorbidities, baseline CKD (adjusted OR, 8.64; 95% CI, 8.14-9.18; P < .001) and congestive heart failure (adjusted OR, 2.74; 95% CI, 2.57-2.92; P< .0001) were most significantly associated with AKI. Perioperative events, including sepsis (adjusted OR, 35.64; 95% CI, 30.28-41.96; P < .0001), MI (adjusted OR, 6.14; 95% CI, 5.17-7.28; P < .0001), and blood transfusion (adjusted OR, 2.28; 95% CI, 2.15-2.42; P < .0001), were also strongly associated with postoperative AKI. Last, compared with urban hospitals and small hospital bed size, rural hospitals (adjusted OR, 0.70; 95% CI, 0.60-0.81; P< .001) and large bed size (adjusted OR, 0.82; 95% CI, 0.70-0.93; P = .003) were associated with lower probability of developing AKI (Table 3).
Figure 2 elucidates the frequency of AKI based on a combination of key preoperative comorbid conditions and postoperative complications—demonstrating that the proportion of AKI cases associated with other postoperative complications is significantly higher in the CKD and concomitant DM/CKD patient populations. Patients hospitalized with CKD exhibited higher rates of AKI in cases involving blood transfusion (20.9% vs 1.8%; P < .001), acute MI (48.9% vs 13.8%; P < .001), and sepsis (74.7% vs 36.3%;P< .001) relative to patients without CKD. Similarly, patients with concomitant DM/CKD exhibited higher rates of AKI in cases involving blood transfusion (23% vs 1.9%; P< .001), acute MI (51.1% vs 12.1%; P< .001), and sepsis (75% vs 38.2%; P < .001) relative to patients without either condition. However, patients hospitalized with DM alone exhibited only marginally higher rates of AKI in cases involving blood transfusion (4.7% vs 2%; P < .01) and acute MI (19.2% vs 16.7%; P< .01) and a lower rate in cases involving sepsis (38.2% vs 41.7%; P < .01) relative to patients without DM. These data suggest that CKD is the most significant clinically relevant risk factor for AKI and that CKD may synergize with DM to raise the risk for AKI.
Outcomes
We then analyzed the impact of AKI on hospital outcomes, including in-hospital mortality, discharge disposition, LOS, and cost of care. Mortality was significantly higher in patients with AKI than in patients without it (2.08% vs 0.06%; P < .001). Even after adjusting for confounders (eg, demographics, comorbidity burden, perioperative sepsis, hospital-level characteristics), AKI was still associated with strikingly higher odds of in-hospital death (adjusted OR, 11.32; 95% CI, 9.34-13.74; P < .001). However, analysis of temporal trends indicated that the odds for adjusted mortality associated with AKI decreased from 18.09 to 9.45 (Ptrend = .01) over the period 2002–2012 (Figure 3). This decrease in odds of death was countered by an increase in incidence of AKI, resulting in a stable attributable risk proportion (97.9% in 2002 to 97.3% in 2012; Ptrend = .90) (Table 4). Regarding discharge disposition, patients with AKI were much less likely to be discharged home (41.35% vs 62.59%; P < .001) and more likely to be discharged to long-term care (56.37% vs 37.03%; P< .001). After adjustment for confounders, AKI was associated with significantly increased odds of adverse discharge (adjusted OR, 2.24; 95% CI, 2.12-2.36; P< .001). Analysis of temporal trends revealed no appreciable decrease in the adjusted odds of adverse discharge between 2002 (adjusted OR, 1.87; 95% CI, 1.37-2.55; P < .001) and 2012 (adjusted OR, 1.93; 95% CI, 1.76-2.11; P < .001) (Figure 4, Table 5). Last, both mean LOS (5 days vs 3 days; P < .001) and mean cost of hospitalization (US $22,269 vs $15,757; P < .001) were significantly higher in patients with AKI.
Discussion
In this study, we found that the incidence of AKI among hospitalized patients increased 4-fold between 2002 and 2012. Moreover, we identified numerous patient-specific, hospital-specific, perioperative risk factors for AKI. Most important, we found that AKI was associated with a strikingly higher risk of in-hospital death, and surviving patients were more likely to experience adverse discharge. Although the adjusted mortality rate associated with AKI decreased over that decade, the attributable risk proportion remained stable.
Few studies have addressed this significant public health concern. In one recent study in Australia, Kimmel and colleagues16 identified risk factors for AKI but lacked data on AKI outcomes. In a study of complications and mortality occurring after orthopedic surgery, Belmont and colleagues22 categorized complications as either local or systemic but did not examine renal complications. Only 2 other major studies have been conducted on renal outcomes associated with major joint surgery, and both were limited to patients with acute hip fractures. The first included acute fracture surgery patients and omitted elective joint surgery patients, and it evaluated admission renal function but not postoperative AKI.22 The second study had a sample size of only 170 patients.23 Thus, the literature leaves us with a crucial knowledge gap in renal outcomes and their postoperative impact in elective arthroplasties.
The present study filled this information gap by examining the incidence, risk factors, outcomes, and temporal trends of AKI after elective hip and knee arthroplasties. The increasing incidence of AKI in this surgical setting is similar to that of AKI in other surgical settings (cardiac and noncardiac).21 Although our analysis was limited by lack of perioperative management data, patients undergoing elective joint arthroplasty can experience kidney dysfunction for several reasons, including volume depletion, postoperative sepsis, and influence of medications, such as nonsteroidal anti-inflammatory drugs (NSAIDs), especially in older patients with more comorbidities and a higher burden of CKD. Each of these factors can cause renal dysfunction in patients having orthopedic procedures.24 Moreover, NSAID use among elective joint arthroplasty patients is likely higher because of an emphasis on multimodal analgesia, as recent randomized controlled trials have demonstrated the efficacy of NSAID use in controlling pain without increasing bleeding.25-27 Our results also demonstrated that the absolute incidence of AKI after orthopedic surgery is relatively low. One possible explanation for this phenomenon is that the definitions used were based on ICD-9-CM codes that underestimate the true incidence of AKI.
Consistent with other studies, we found that certain key preoperative comorbid conditions and postoperative events were associated with higher AKI risk. We stratified the rate of AKI associated with each postoperative event (sepsis, acute MI, cardiac catheterization, need for transfusion) by DM/CKD comorbidity. CKD was associated with significantly higher AKI risk across all postoperative complications. This information may provide clinicians with bedside information that can be used to determine which patients may be at higher or lower risk for AKI.
Our analysis of patient outcomes revealed that, though AKI was relatively uncommon, it increased the risk for death during hospitalization more than 10-fold between 2002 and 2012. Although the adjusted OR of in-hospital mortality decreased over the decade studied, the concurrent increase in AKI incidence caused the attributable risk of death associated with AKI to essentially remain the same. This observation is consistent with recent reports from cardiac surgery settings.21 These data together suggest that ameliorating occurrences of AKI would decrease mortality and increase quality of care for patients undergoing elective joint surgeries.
We also examined the effect of AKI on resource use by studying LOS, costs, and risk for adverse discharge. Much as in other surgical settings, AKI increased both LOS and overall hospitalization costs. More important, AKI was associated with increased adverse discharge (discharge to long-term care or nursing homes). Although exact reasons are unclear, we can speculate that postoperative renal dysfunction precludes early rehabilitation, impeding desired functional outcome and disposition.28,29 Given the projected increases in primary and revision hip and knee arthroplasties,5 these data predict that the impact of AKI on health outcomes will increase alarmingly in coming years.
There are limitations to our study. First, it was based on administrative data and lacked patient-level and laboratory data. As reported, the sensitivity of AKI codes remains moderate,30 so the true burden may be higher than indicated here. As the definition of AKI was based on administrative coding, we also could not estimate severity, though previous studies have found that administrative codes typically capture a more severe form of disease.31 Another limitation is that, because the data were deidentified, we could not delineate the risk for recurrent AKI in repeated surgical procedures, though this cohort unlikely was large enough to qualitatively affect our results. The third limitation is that, though we used CCI to adjust for the comorbidity burden, we were unable to account for other unmeasured confounders associated with increased AKI incidence, such as specific medication use. In addition, given the lack of patient-level data, we could not analyze the specific factors responsible for AKI in the perioperative period. Nevertheless, the strengths of a nationally representative sample, such as large sample size and generalizability, outweigh these limitations.
Conclusion
AKI is potentially an important quality indicator of elective joint surgery, and reducing its incidence is therefore essential for quality improvement. Given that hip and knee arthroplasties are projected to increase exponentially, as is the burden of comorbid conditions in this population, postoperative AKI will continue to have an incremental impact on health and health care resources. Thus, a carefully planned approach of interdisciplinary perioperative care is warranted to reduce both the risk and the consequences of this devastating condition.
Degenerative arthritis is a widespread chronic condition with an incidence of almost 43 million and annual health care costs of $60 billion in the United States alone.1 Although many cases can be managed symptomatically with medical therapy and intra-articular injections,2 many patients experience disease progression resulting in decreased ambulatory ability and work productivity. For these patients, elective hip and knee arthroplasties can drastically improve quality of life and functionality.3,4 Over the past decade, there has been a marked increase in the number of primary and revision total hip and knee arthroplasties performed in the United States. By 2030, the demand for primary total hip arthroplasties will grow an estimated 174%, to 572,000 procedures. Likewise, the demand for primary total knee arthroplasties is projected to grow by 673%, to 3.48 million procedures.5 However, though better surgical techniques and technology have led to improved functional outcomes, there is still substantial risk for complications in the perioperative period, especially in the geriatric population, in which substantial comorbidities are common.6-9
Acute kidney injury (AKI) is a common public health problem in hospitalized patients and in patients undergoing procedures. More than one-third of all AKI cases occur in surgical settings.10,11 Over the past decade, both community-acquired and in-hospital AKIs rapidly increased in incidence in all major clinical settings.12-14 Patients with AKI have high rates of adverse outcomes during hospitalization and discharge.11,15 Sequelae of AKIs include worsening chronic kidney disease (CKD) and progression to end-stage renal disease, necessitating either long-term dialysis or transplantation.12 This in turn leads to exacerbated disability, diminished quality of life, and disproportionate burden on health care resources.
Much of our knowledge about postoperative AKI has been derived from cardiovascular, thoracic, and abdominal surgery settings. However, there is a paucity of data on epidemiology and trends for either AKI or associated outcomes in patients undergoing major orthopedic surgery. The few studies to date either were single-center or had inadequate sample sizes for appropriately powered analysis of the risk factors and outcomes related to AKI.16
In the study reported here, we analyzed a large cohort of patients from a nationwide multicenter database to determine the incidence of and risk factors for AKI. We also examined the mortality and adverse discharges associated with AKI after major joint surgery. Lastly, we assessed temporal trends in both incidence and outcomes of AKI, including the death risk attributable to AKI.
Methods
Database
We extracted our study cohort from the Nationwide Inpatient Sample (NIS) and the National Inpatient Sample of Healthcare Cost and Utilization Project (HCUP) compiled by the Agency for Healthcare Research and Quality.17 NIS, the largest inpatient care database in the United States, stores data from almost 8 million stays in about 1000 hospitals across the country each year. Its participating hospital pool consists of about 20% of US community hospitals, resulting in a sampling frame comprising about 90% of all hospital discharges in the United States. This allows for calculation of precise, weighted nationwide estimates. Data elements within NIS are drawn from hospital discharge abstracts that indicate all procedures performed. NIS also stores information on patient characteristics, length of stay (LOS), discharge disposition, postoperative morbidity, and observed in-hospital mortality. However, it stores no information on long-term follow-up or complications after discharge.
Data Analysis
For the period 2002–2012, we queried the NIS database for hip and knee arthroplasties with primary diagnosis codes for osteoarthritis and secondary codes for AKI. We excluded patients under age 18 years and patients with diagnosis codes for hip and knee fracture/necrosis, inflammatory/infectious arthritis, or bone neoplasms (Table 1). We then extracted baseline characteristics of the study population. Patient-level characteristics included age, sex, race, quartile classification of median household income according to postal (ZIP) code, and primary payer (Medicare/Medicaid, private insurance, self-pay, no charge). Hospital-level characteristics included hospital location (urban, rural), hospital bed size (small, medium, large), region (Northeast, Midwest/North Central, South, West), and teaching status. We defined illness severity and likelihood of death using Deyo’s modification of the Charlson Comorbidity Index (CCI), which draws on principal and secondary ICD-9-CM (International Classification of Diseases, Ninth Revision-Clinical Modification) diagnosis codes, procedure codes, and patient demographics to estimate a patient’s mortality risk. This method reliably predicts mortality and readmission in the orthopedic population.18,19 We assessed the effect of AKI on 4 outcomes, including in-hospital mortality, discharge disposition, LOS, and cost of stay. Discharge disposition was grouped by either (a) home or short-term facility or (b) adverse discharge. Home or short-term facility covered routine, short-term hospital, against medical advice, home intravenous provider, another rehabilitation facility, another institution for outpatient services, institution for outpatient services, discharged alive, and destination unknown; adverse discharge covered skilled nursing facility, intermediate care, hospice home, hospice medical facility, long-term care hospital, and certified nursing facility. This dichotomization of discharge disposition is often used in studies of NIS data.20
Statistical Analyses
We compared the baseline characteristics of hospitalized patients with and without AKI. To test for significance, we used the χ2 test for categorical variables, the Student t test for normally distributed continuous variables, the Wilcoxon rank sum test for non-normally distributed continuous variables, and the Cochran-Armitage test for trends in AKI incidence. We used survey logistic regression models to calculate adjusted odds ratios (ORs) with 95% confidence intervals (95% CIs) in order to estimate the predictors of AKI and the impact of AKI on hospital outcomes. We constructed final models after adjusting for confounders, testing for potential interactions, and ensuring no multicolinearity between covariates. Last, we computed the risk proportion of death attributable to AKI, indicating the proportion of deaths that could potentially be avoided if AKI and its complications were abrogated.21
We performed all statistical analyses with SAS Version 9.3 (SAS Institute) using designated weight values to produce weighted national estimates. The threshold for statistical significance was set at P < .01 (with ORs and 95% CIs that excluded 1).
Results
AKI Incidence, Risk Factors, and Trends
We identified 7,235,251 patients who underwent elective hip or knee arthroplasty for osteoarthritis between 2002 and 2012—an estimate consistent with data from the Centers for Disease Control and Prevention.22 Of that total, 94,367 (1.3%) had AKI. The proportion of discharges diagnosed with AKI increased rapidly over the decade, from 0.5% in 2002 to 1.8% to 1.9% in the period 2010–2012. This upward trend was highly significant (Ptrend < .001) (Figure 1). Patients with AKI (vs patients without AKI) were more likely to be older (mean age, 70 vs 66 years; P < .001), male (50.8% vs 38.4%; P < .001), and black (10.07% vs 5.15%; P<. 001). They were also found to have a significantly higher comorbidity score (mean CCI, 2.8 vs 1.5; P < .001) and higher proportions of comorbidities, including hypertension, CKD, atrial fibrillation, diabetes mellitus (DM), congestive heart failure, chronic liver disease, and hepatitis C virus infection. In addition, AKI was associated with perioperative myocardial infarction (MI), sepsis, cardiac catheterization, and blood transfusion. Regarding socioeconomic characteristics, patients with AKI were more likely to have Medicare/Medicaid insurance (72.26% vs 58.06%; P < .001) and to belong to the extremes of income categories (Table 2).
Using multivariable logistic regression, we found that increased age (1.11 increase in adjusted OR for every year older; 95% CI, 1.09-1.14; P < .001), male sex (adjusted OR, 1.65; 95% CI, 1.60-1.71; P < .001), and black race (adjusted OR, 1.57; 95% CI, 1.45-1.69; P < .001) were significantly associated with postoperative AKI. Regarding comorbidities, baseline CKD (adjusted OR, 8.64; 95% CI, 8.14-9.18; P < .001) and congestive heart failure (adjusted OR, 2.74; 95% CI, 2.57-2.92; P< .0001) were most significantly associated with AKI. Perioperative events, including sepsis (adjusted OR, 35.64; 95% CI, 30.28-41.96; P < .0001), MI (adjusted OR, 6.14; 95% CI, 5.17-7.28; P < .0001), and blood transfusion (adjusted OR, 2.28; 95% CI, 2.15-2.42; P < .0001), were also strongly associated with postoperative AKI. Last, compared with urban hospitals and small hospital bed size, rural hospitals (adjusted OR, 0.70; 95% CI, 0.60-0.81; P< .001) and large bed size (adjusted OR, 0.82; 95% CI, 0.70-0.93; P = .003) were associated with lower probability of developing AKI (Table 3).
Figure 2 elucidates the frequency of AKI based on a combination of key preoperative comorbid conditions and postoperative complications—demonstrating that the proportion of AKI cases associated with other postoperative complications is significantly higher in the CKD and concomitant DM/CKD patient populations. Patients hospitalized with CKD exhibited higher rates of AKI in cases involving blood transfusion (20.9% vs 1.8%; P < .001), acute MI (48.9% vs 13.8%; P < .001), and sepsis (74.7% vs 36.3%;P< .001) relative to patients without CKD. Similarly, patients with concomitant DM/CKD exhibited higher rates of AKI in cases involving blood transfusion (23% vs 1.9%; P< .001), acute MI (51.1% vs 12.1%; P< .001), and sepsis (75% vs 38.2%; P < .001) relative to patients without either condition. However, patients hospitalized with DM alone exhibited only marginally higher rates of AKI in cases involving blood transfusion (4.7% vs 2%; P < .01) and acute MI (19.2% vs 16.7%; P< .01) and a lower rate in cases involving sepsis (38.2% vs 41.7%; P < .01) relative to patients without DM. These data suggest that CKD is the most significant clinically relevant risk factor for AKI and that CKD may synergize with DM to raise the risk for AKI.
Outcomes
We then analyzed the impact of AKI on hospital outcomes, including in-hospital mortality, discharge disposition, LOS, and cost of care. Mortality was significantly higher in patients with AKI than in patients without it (2.08% vs 0.06%; P < .001). Even after adjusting for confounders (eg, demographics, comorbidity burden, perioperative sepsis, hospital-level characteristics), AKI was still associated with strikingly higher odds of in-hospital death (adjusted OR, 11.32; 95% CI, 9.34-13.74; P < .001). However, analysis of temporal trends indicated that the odds for adjusted mortality associated with AKI decreased from 18.09 to 9.45 (Ptrend = .01) over the period 2002–2012 (Figure 3). This decrease in odds of death was countered by an increase in incidence of AKI, resulting in a stable attributable risk proportion (97.9% in 2002 to 97.3% in 2012; Ptrend = .90) (Table 4). Regarding discharge disposition, patients with AKI were much less likely to be discharged home (41.35% vs 62.59%; P < .001) and more likely to be discharged to long-term care (56.37% vs 37.03%; P< .001). After adjustment for confounders, AKI was associated with significantly increased odds of adverse discharge (adjusted OR, 2.24; 95% CI, 2.12-2.36; P< .001). Analysis of temporal trends revealed no appreciable decrease in the adjusted odds of adverse discharge between 2002 (adjusted OR, 1.87; 95% CI, 1.37-2.55; P < .001) and 2012 (adjusted OR, 1.93; 95% CI, 1.76-2.11; P < .001) (Figure 4, Table 5). Last, both mean LOS (5 days vs 3 days; P < .001) and mean cost of hospitalization (US $22,269 vs $15,757; P < .001) were significantly higher in patients with AKI.
Discussion
In this study, we found that the incidence of AKI among hospitalized patients increased 4-fold between 2002 and 2012. Moreover, we identified numerous patient-specific, hospital-specific, perioperative risk factors for AKI. Most important, we found that AKI was associated with a strikingly higher risk of in-hospital death, and surviving patients were more likely to experience adverse discharge. Although the adjusted mortality rate associated with AKI decreased over that decade, the attributable risk proportion remained stable.
Few studies have addressed this significant public health concern. In one recent study in Australia, Kimmel and colleagues16 identified risk factors for AKI but lacked data on AKI outcomes. In a study of complications and mortality occurring after orthopedic surgery, Belmont and colleagues22 categorized complications as either local or systemic but did not examine renal complications. Only 2 other major studies have been conducted on renal outcomes associated with major joint surgery, and both were limited to patients with acute hip fractures. The first included acute fracture surgery patients and omitted elective joint surgery patients, and it evaluated admission renal function but not postoperative AKI.22 The second study had a sample size of only 170 patients.23 Thus, the literature leaves us with a crucial knowledge gap in renal outcomes and their postoperative impact in elective arthroplasties.
The present study filled this information gap by examining the incidence, risk factors, outcomes, and temporal trends of AKI after elective hip and knee arthroplasties. The increasing incidence of AKI in this surgical setting is similar to that of AKI in other surgical settings (cardiac and noncardiac).21 Although our analysis was limited by lack of perioperative management data, patients undergoing elective joint arthroplasty can experience kidney dysfunction for several reasons, including volume depletion, postoperative sepsis, and influence of medications, such as nonsteroidal anti-inflammatory drugs (NSAIDs), especially in older patients with more comorbidities and a higher burden of CKD. Each of these factors can cause renal dysfunction in patients having orthopedic procedures.24 Moreover, NSAID use among elective joint arthroplasty patients is likely higher because of an emphasis on multimodal analgesia, as recent randomized controlled trials have demonstrated the efficacy of NSAID use in controlling pain without increasing bleeding.25-27 Our results also demonstrated that the absolute incidence of AKI after orthopedic surgery is relatively low. One possible explanation for this phenomenon is that the definitions used were based on ICD-9-CM codes that underestimate the true incidence of AKI.
Consistent with other studies, we found that certain key preoperative comorbid conditions and postoperative events were associated with higher AKI risk. We stratified the rate of AKI associated with each postoperative event (sepsis, acute MI, cardiac catheterization, need for transfusion) by DM/CKD comorbidity. CKD was associated with significantly higher AKI risk across all postoperative complications. This information may provide clinicians with bedside information that can be used to determine which patients may be at higher or lower risk for AKI.
Our analysis of patient outcomes revealed that, though AKI was relatively uncommon, it increased the risk for death during hospitalization more than 10-fold between 2002 and 2012. Although the adjusted OR of in-hospital mortality decreased over the decade studied, the concurrent increase in AKI incidence caused the attributable risk of death associated with AKI to essentially remain the same. This observation is consistent with recent reports from cardiac surgery settings.21 These data together suggest that ameliorating occurrences of AKI would decrease mortality and increase quality of care for patients undergoing elective joint surgeries.
We also examined the effect of AKI on resource use by studying LOS, costs, and risk for adverse discharge. Much as in other surgical settings, AKI increased both LOS and overall hospitalization costs. More important, AKI was associated with increased adverse discharge (discharge to long-term care or nursing homes). Although exact reasons are unclear, we can speculate that postoperative renal dysfunction precludes early rehabilitation, impeding desired functional outcome and disposition.28,29 Given the projected increases in primary and revision hip and knee arthroplasties,5 these data predict that the impact of AKI on health outcomes will increase alarmingly in coming years.
There are limitations to our study. First, it was based on administrative data and lacked patient-level and laboratory data. As reported, the sensitivity of AKI codes remains moderate,30 so the true burden may be higher than indicated here. As the definition of AKI was based on administrative coding, we also could not estimate severity, though previous studies have found that administrative codes typically capture a more severe form of disease.31 Another limitation is that, because the data were deidentified, we could not delineate the risk for recurrent AKI in repeated surgical procedures, though this cohort unlikely was large enough to qualitatively affect our results. The third limitation is that, though we used CCI to adjust for the comorbidity burden, we were unable to account for other unmeasured confounders associated with increased AKI incidence, such as specific medication use. In addition, given the lack of patient-level data, we could not analyze the specific factors responsible for AKI in the perioperative period. Nevertheless, the strengths of a nationally representative sample, such as large sample size and generalizability, outweigh these limitations.
Conclusion
AKI is potentially an important quality indicator of elective joint surgery, and reducing its incidence is therefore essential for quality improvement. Given that hip and knee arthroplasties are projected to increase exponentially, as is the burden of comorbid conditions in this population, postoperative AKI will continue to have an incremental impact on health and health care resources. Thus, a carefully planned approach of interdisciplinary perioperative care is warranted to reduce both the risk and the consequences of this devastating condition.
1. Reginster JY. The prevalence and burden of arthritis. Rheumatology. 2002;41(supp 1):3-6.
2. Kullenberg B, Runesson R, Tuvhag R, Olsson C, Resch S. Intraarticular corticosteroid injection: pain relief in osteoarthritis of the hip? J Rheumatol. 2004;31(11):2265-2268.
3. Kawasaki M, Hasegawa Y, Sakano S, Torii Y, Warashina H. Quality of life after several treatments for osteoarthritis of the hip. J Orthop Sci. 2003;8(1):32-35.
4. Ethgen O, Bruyère O, Richy F, Dardennes C, Reginster JY. Health-related quality of life in total hip and total knee arthroplasty. A qualitative and systematic review of the literature. J Bone Joint Surg Am. 2004;86(5):963-974.
5. Kurtz S, Ong K, Lau E, Mowat F, Halpern M. Projections of primary and revision hip and knee arthroplasty in the United States from 2005 to 2030. J Bone Joint Surg Am. 2007;89(4):780-785.
6. Matlock D, Earnest M, Epstein A. Utilization of elective hip and knee arthroplasty by age and payer. Clin Orthop Relat Res. 2008;466(4):914-919.
7. Parvizi J, Holiday AD, Ereth MH, Lewallen DG. The Frank Stinchfield Award. Sudden death during primary hip arthroplasty. Clin Orthop Relat Res. 1999;(369):39-48.
8. Parvizi J, Mui A, Purtill JJ, Sharkey PF, Hozack WJ, Rothman RH. Total joint arthroplasty: when do fatal or near-fatal complications occur? J Bone Joint Surg Am. 2007;89(1):27-32.
9. Parvizi J, Sullivan TA, Trousdale RT, Lewallen DG. Thirty-day mortality after total knee arthroplasty. J Bone Joint Surg Am. 2001;83(8):1157-1161.
10. Uchino S, Kellum JA, Bellomo R, et al; Beginning and Ending Supportive Therapy for the Kidney (BEST Kidney) Investigators. Acute renal failure in critically ill patients: a multinational, multicenter study. JAMA. 2005;294(7):813-818.
11. Thakar CV. Perioperative acute kidney injury. Adv Chronic Kidney Dis. 2013;20(1):67-75.
12. Hsu CY, Chertow GM, McCulloch CE, Fan D, Ordoñez JD, Go AS. Nonrecovery of kidney function and death after acute on chronic renal failure. Clin J Am Soc Nephrol. 2009;4(5):891-898.
13. Rewa O, Bagshaw SM. Acute kidney injury—epidemiology, outcomes and economics. Nat Rev Nephrol. 2014;10(4):193-207.
14. Thakar CV, Worley S, Arrigain S, Yared JP, Paganini EP. Influence of renal dysfunction on mortality after cardiac surgery: modifying effect of preoperative renal function. Kidney Int. 2005;67(3):1112-1119.
15. Zeng X, McMahon GM, Brunelli SM, Bates DW, Waikar SS. Incidence, outcomes, and comparisons across definitions of AKI in hospitalized individuals. Clin J Am Soc Nephrol. 2014;9(1):12-20.
16. Kimmel LA, Wilson S, Janardan JD, Liew SM, Walker RG. Incidence of acute kidney injury following total joint arthroplasty: a retrospective review by RIFLE criteria. Clin Kidney J. 2014;7(6):546-551.
17. Agency for Healthcare Research and Quality. Healthcare Cost and Utilization Project (HCUP) databases, 2002–2012. Rockville, MD: Agency for Healthcare Research and Quality.
18. Bjorgul K, Novicoff WM, Saleh KJ. Evaluating comorbidities in total hip and knee arthroplasty: available instruments. J Orthop Traumatol. 2010;11(4):203-209.
19. Voskuijl T, Hageman M, Ring D. Higher Charlson Comorbidity Index Scores are associated with readmission after orthopaedic surgery. Clin Orthop Relat Res. 2014;472(5):1638-1644.
20. Chertow GM, Burdick E, Honour M, Bonventre JV, Bates DW. Acute kidney injury, mortality, length of stay, and costs in hospitalized patients. J Am Soc Nephrol. 2005;16(11):3365-3370.
21. Lenihan CR, Montez-Rath ME, Mora Mangano CT, Chertow GM, Winkelmayer WC. Trends in acute kidney injury, associated use of dialysis, and mortality after cardiac surgery, 1999 to 2008. Ann Thorac Surg. 2013;95(1):20-28.
22. Belmont PJ Jr, Goodman GP, Waterman BR, Bader JO, Schoenfeld AJ. Thirty-day postoperative complications and mortality following total knee arthroplasty: incidence and risk factors among a national sample of 15,321 patients. J Bone Joint Surg Am. 2014;96(1):20-26.
23. Bennet SJ, Berry OM, Goddard J, Keating JF. Acute renal dysfunction following hip fracture. Injury. 2010;41(4):335-338.
24. Kateros K, Doulgerakis C, Galanakos SP, Sakellariou VI, Papadakis SA, Macheras GA. Analysis of kidney dysfunction in orthopaedic patients. BMC Nephrol. 2012;13:101.
25. Huang YM, Wang CM, Wang CT, Lin WP, Horng LC, Jiang CC. Perioperative celecoxib administration for pain management after total knee arthroplasty—a randomized, controlled study. BMC Musculoskelet Disord. 2008;9:77.
26. Kelley TC, Adams MJ, Mulliken BD, Dalury DF. Efficacy of multimodal perioperative analgesia protocol with periarticular medication injection in total knee arthroplasty: a randomized, double-blinded study. J Arthroplasty. 2013;28(8):1274-1277.
27. Lamplot JD, Wagner ER, Manning DW. Multimodal pain management in total knee arthroplasty: a prospective randomized controlled trial. J Arthroplasty. 2014;29(2):329-334.
28. Munin MC, Rudy TE, Glynn NW, Crossett LS, Rubash HE. Early inpatient rehabilitation after elective hip and knee arthroplasty. JAMA. 1998;279(11):847-852.
29. Pua YH, Ong PH. Association of early ambulation with length of stay and costs in total knee arthroplasty: retrospective cohort study. Am J Phys Med Rehabil. 2014;93(11):962-970.
30. Waikar SS, Wald R, Chertow GM, et al. Validity of International Classification of Diseases, Ninth Revision, Clinical Modification codes for acute renal failure. J Am Soc Nephrol. 2006;17(6):1688-1694.
31. Grams ME, Waikar SS, MacMahon B, Whelton S, Ballew SH, Coresh J. Performance and limitations of administrative data in the identification of AKI. Clin J Am Soc Nephrol. 2014;9(4):682-689.
1. Reginster JY. The prevalence and burden of arthritis. Rheumatology. 2002;41(supp 1):3-6.
2. Kullenberg B, Runesson R, Tuvhag R, Olsson C, Resch S. Intraarticular corticosteroid injection: pain relief in osteoarthritis of the hip? J Rheumatol. 2004;31(11):2265-2268.
3. Kawasaki M, Hasegawa Y, Sakano S, Torii Y, Warashina H. Quality of life after several treatments for osteoarthritis of the hip. J Orthop Sci. 2003;8(1):32-35.
4. Ethgen O, Bruyère O, Richy F, Dardennes C, Reginster JY. Health-related quality of life in total hip and total knee arthroplasty. A qualitative and systematic review of the literature. J Bone Joint Surg Am. 2004;86(5):963-974.
5. Kurtz S, Ong K, Lau E, Mowat F, Halpern M. Projections of primary and revision hip and knee arthroplasty in the United States from 2005 to 2030. J Bone Joint Surg Am. 2007;89(4):780-785.
6. Matlock D, Earnest M, Epstein A. Utilization of elective hip and knee arthroplasty by age and payer. Clin Orthop Relat Res. 2008;466(4):914-919.
7. Parvizi J, Holiday AD, Ereth MH, Lewallen DG. The Frank Stinchfield Award. Sudden death during primary hip arthroplasty. Clin Orthop Relat Res. 1999;(369):39-48.
8. Parvizi J, Mui A, Purtill JJ, Sharkey PF, Hozack WJ, Rothman RH. Total joint arthroplasty: when do fatal or near-fatal complications occur? J Bone Joint Surg Am. 2007;89(1):27-32.
9. Parvizi J, Sullivan TA, Trousdale RT, Lewallen DG. Thirty-day mortality after total knee arthroplasty. J Bone Joint Surg Am. 2001;83(8):1157-1161.
10. Uchino S, Kellum JA, Bellomo R, et al; Beginning and Ending Supportive Therapy for the Kidney (BEST Kidney) Investigators. Acute renal failure in critically ill patients: a multinational, multicenter study. JAMA. 2005;294(7):813-818.
11. Thakar CV. Perioperative acute kidney injury. Adv Chronic Kidney Dis. 2013;20(1):67-75.
12. Hsu CY, Chertow GM, McCulloch CE, Fan D, Ordoñez JD, Go AS. Nonrecovery of kidney function and death after acute on chronic renal failure. Clin J Am Soc Nephrol. 2009;4(5):891-898.
13. Rewa O, Bagshaw SM. Acute kidney injury—epidemiology, outcomes and economics. Nat Rev Nephrol. 2014;10(4):193-207.
14. Thakar CV, Worley S, Arrigain S, Yared JP, Paganini EP. Influence of renal dysfunction on mortality after cardiac surgery: modifying effect of preoperative renal function. Kidney Int. 2005;67(3):1112-1119.
15. Zeng X, McMahon GM, Brunelli SM, Bates DW, Waikar SS. Incidence, outcomes, and comparisons across definitions of AKI in hospitalized individuals. Clin J Am Soc Nephrol. 2014;9(1):12-20.
16. Kimmel LA, Wilson S, Janardan JD, Liew SM, Walker RG. Incidence of acute kidney injury following total joint arthroplasty: a retrospective review by RIFLE criteria. Clin Kidney J. 2014;7(6):546-551.
17. Agency for Healthcare Research and Quality. Healthcare Cost and Utilization Project (HCUP) databases, 2002–2012. Rockville, MD: Agency for Healthcare Research and Quality.
18. Bjorgul K, Novicoff WM, Saleh KJ. Evaluating comorbidities in total hip and knee arthroplasty: available instruments. J Orthop Traumatol. 2010;11(4):203-209.
19. Voskuijl T, Hageman M, Ring D. Higher Charlson Comorbidity Index Scores are associated with readmission after orthopaedic surgery. Clin Orthop Relat Res. 2014;472(5):1638-1644.
20. Chertow GM, Burdick E, Honour M, Bonventre JV, Bates DW. Acute kidney injury, mortality, length of stay, and costs in hospitalized patients. J Am Soc Nephrol. 2005;16(11):3365-3370.
21. Lenihan CR, Montez-Rath ME, Mora Mangano CT, Chertow GM, Winkelmayer WC. Trends in acute kidney injury, associated use of dialysis, and mortality after cardiac surgery, 1999 to 2008. Ann Thorac Surg. 2013;95(1):20-28.
22. Belmont PJ Jr, Goodman GP, Waterman BR, Bader JO, Schoenfeld AJ. Thirty-day postoperative complications and mortality following total knee arthroplasty: incidence and risk factors among a national sample of 15,321 patients. J Bone Joint Surg Am. 2014;96(1):20-26.
23. Bennet SJ, Berry OM, Goddard J, Keating JF. Acute renal dysfunction following hip fracture. Injury. 2010;41(4):335-338.
24. Kateros K, Doulgerakis C, Galanakos SP, Sakellariou VI, Papadakis SA, Macheras GA. Analysis of kidney dysfunction in orthopaedic patients. BMC Nephrol. 2012;13:101.
25. Huang YM, Wang CM, Wang CT, Lin WP, Horng LC, Jiang CC. Perioperative celecoxib administration for pain management after total knee arthroplasty—a randomized, controlled study. BMC Musculoskelet Disord. 2008;9:77.
26. Kelley TC, Adams MJ, Mulliken BD, Dalury DF. Efficacy of multimodal perioperative analgesia protocol with periarticular medication injection in total knee arthroplasty: a randomized, double-blinded study. J Arthroplasty. 2013;28(8):1274-1277.
27. Lamplot JD, Wagner ER, Manning DW. Multimodal pain management in total knee arthroplasty: a prospective randomized controlled trial. J Arthroplasty. 2014;29(2):329-334.
28. Munin MC, Rudy TE, Glynn NW, Crossett LS, Rubash HE. Early inpatient rehabilitation after elective hip and knee arthroplasty. JAMA. 1998;279(11):847-852.
29. Pua YH, Ong PH. Association of early ambulation with length of stay and costs in total knee arthroplasty: retrospective cohort study. Am J Phys Med Rehabil. 2014;93(11):962-970.
30. Waikar SS, Wald R, Chertow GM, et al. Validity of International Classification of Diseases, Ninth Revision, Clinical Modification codes for acute renal failure. J Am Soc Nephrol. 2006;17(6):1688-1694.
31. Grams ME, Waikar SS, MacMahon B, Whelton S, Ballew SH, Coresh J. Performance and limitations of administrative data in the identification of AKI. Clin J Am Soc Nephrol. 2014;9(4):682-689.
Analysis of Direct Costs of Outpatient Arthroscopic Rotator Cuff Repair
Musculoskeletal disorders, the leading cause of disability in the United States,1 account for more than half of all persons reporting missing a workday because of a medical condition.2 Shoulder disorders in particular play a significant role in the burden of musculoskeletal disorders and cost of care. In 2008, 18.9 million adults (8.2% of the US adult population) reported chronic shoulder pain.1 Among shoulder disorders, rotator cuff pathology is the most common cause of shoulder-related disability found by orthopedic surgeons.3 Rotator cuff surgery (RCS) is one of the most commonly performed orthopedic surgical procedures, and surgery volume is on the rise. One study found a 141% increase in rotator cuff repairs between the years 1996 (~41 per 100,000 population) and 2006 (~98 per 100,000 population).4
US health care costs are also increasing. In 2011, $2.7 trillion was spent on health care, representing 17.9% of the national gross domestic product (GDP). According to projections, costs will rise to $4.6 trillion by 2020.5 In particular, as patients continue to live longer and remain more active into their later years, the costs of treating and managing musculoskeletal disorders become more important from a public policy standpoint. In 2006, the cost of treating musculoskeletal disorders alone was $576 billion, representing 4.5% of that year’s GDP.2
Paramount in this era of rising costs is the idea of maximizing the value of health care dollars. Health care economists Porter and Teisberg6 defined value as patient health outcomes achieved per dollar of cost expended in a care cycle (diagnosis, treatment, ongoing management) for a particular disease or disorder. For proper management of value, outcomes and costs for an entire cycle of care must be determined. From a practical standpoint, this first requires determining the true cost of a care cycle—dollars spent on personnel, equipment, materials, and other resources required to deliver a particular service—rather than the amount charged or reimbursed for providing the service in question.7
Kaplan and Anderson8,9 described the TDABC (time-driven activity-based costing) algorithm for calculating the cost of delivering a service based on 2 parameters: unit cost of a particular resource, and time required to supply it. These parameters apply to material costs and labor costs. In the medical setting, the TDABC algorithm can be applied by defining a care delivery value chain for each aspect of patient care and then multiplying incremental cost per unit time by time required to deliver that resource (Figure 1). Tabulating the overall unit cost for each resource then yields the overall cost of the care cycle. Clinical outcomes data can then be determined and used to calculate overall value for the patient care cycle.
In the study reported here, we used the TDABC algorithm to calculate the direct financial costs of surgical treatment of rotator cuff tears confirmed by magnetic resonance imaging (MRI) in an academic medical center.
Methods
Per our institution’s Office for the Protection of Research Subjects, institutional review board (IRB) approval is required only for projects using “human subjects” as defined by federal policy. In the present study, no private information could be identified, and all data were obtained from hospital billing records without intervention or interaction with individual patients. Accordingly, IRB approval was deemed unnecessary for our economic cost analysis.
Billing records of a single academic fellowship-trained sports surgeon were reviewed to identify patients who underwent primary repair of an MRI-confirmed rotator cuff tear between April 1, 2009, and July 31, 2012. Patients who had undergone prior shoulder surgery of any type were excluded from the study. Operative reports were reviewed, and exact surgical procedures performed were noted. The operating surgeon selected the specific repair techniques, including single- or double-row repair, with emphasis on restoring footprint coverage and avoiding overtensioning.
All surgeries were performed in an outpatient surgical center owned and operated by the surgeon’s home university. Surgeries were performed by the attending physician assisted by a senior orthopedic resident. The RCS care cycle was divided into 3 phases (Figure 2):
1. Preoperative. Patient’s interaction with receptionist in surgery center, time with preoperative nurse and circulating nurse in preoperative area, resident check-in time, and time placing preoperative nerve block and consumable materials used during block placement.
2. Operative. Time in operating room with surgical team for RCS, consumable materials used during surgery (eg, anchors, shavers, drapes), anesthetic medications, shoulder abduction pillow placed on completion of surgery, and cost of instrument processing.
3. Postoperative. Time in postoperative recovery area with recovery room nursing staff.
Time in each portion of the care cycle was directly observed and tabulated by hospital volunteers in the surgery center. Institutional billing data were used to identify material resources consumed, and the actual cost paid by the hospital for these resources was obtained from internal records. Mean hourly salary data and standard benefit rates were obtained for surgery center staff. Attending physician salary was extrapolated from published mean market salary data for academic physicians and mean hours worked,10,11 and resident physician costs were tabulated from publically available institutional payroll data and average resident work hours at our institution. These cost data and times were then used to tabulate total cost for the RCS care cycle using the TDABC algorithm.
Results
We identified 28 shoulders in 26 patients (mean age, 54.5 years) who met the inclusion criteria. Of these 28 shoulders, 18 (64.3%) had an isolated supraspinatus tear, 8 (28.6%) had combined supraspinatus and infraspinatus tears, 1 (3.6%) had combined supraspinatus and subscapularis tears, and 1 (3.6%) had an isolated infraspinatus tear. Demographic data are listed in Table 1.
All patients received an interscalene nerve block in the preoperative area before being brought into the operating room. In our analysis, we included nerve block supply costs and the anesthesiologist’s mean time placing the nerve block.
In all cases, primary rotator cuff repair was performed with suture anchors (Parcus Medical) with the patient in the lateral decubitus position. In 13 (46%) of the 28 shoulders, this repair was described as “complex,” requiring double-row technique. Subacromial decompression and bursectomy were performed in addition to the rotator cuff repair. Labral débridement was performed in 23 patients, synovectomy in 10, biceps tenodesis with anchor (Smith & Nephew) in 1, and biceps tenotomy in 1. Mean time in operating room was 148 minutes; mean time in postoperative recovery unit was 105 minutes.
Directly observing the care cycle, hospital volunteers found that patients spent a mean of 15 minutes with the receptionist when they arrived in the outpatient surgical center, 25 minutes with nurses for check-in in the preoperative holding area, and 10 minutes with the anesthesiology resident and 15 minutes with the orthopedic surgery resident for preoperative evaluation and paperwork. Mean nerve block time was 20 minutes. Mean electrocardiogram (ECG) time (12 patients) was 15 minutes. The surgical technician spent a mean time of 20 minutes setting up the operating room before the patient was brought in and 15 minutes cleaning up after the patient was transferred to the recovery room. Costs of postoperative care in the recovery room were based on a 2:1 patient-to-nurse ratio, as is the standard practice in our outpatient surgery center.
Using the times mentioned and our hospital’s salary data—including standard hospital benefits rates of 33.5% for nonphysicians and 17.65% for physicians—we determined, using the TDABC algorithm, a direct cost of $5904.21 for this process cycle, excluding hospital overhead and indirect costs. Table 2 provides the overall cost breakdown. Compared with the direct economic cost, the mean hospital charge to insurers for the procedure was $31,459.35. Mean reimbursement from insurers was $9679.08.
Overall attending and resident physician costs were $1077.75, which consisted of $623.66 for the surgeon and $454.09 for the anesthesiologist (included placement of nerve block and administration of anesthesia during surgery). Preoperative bloodwork was obtained in 23 cases, adding a mean cost of $111.04 after adjusting for standard hospital markup. Preoperative ECG was performed in 12 cases, for an added mean cost of $7.30 based on the TDABC algorithm.
We also broke down costs by care cycle phase. The preoperative phase, excluding the preoperative laboratory studies and ECGs (not performed in all cases), cost $134.34 (2.3% of total costs); the operative phase cost $5718.01 (96.8% of total costs); and the postoperative phase cost $51.86 (0.9% of total costs). Within the operative phase, the cost of consumables (specifically, suture anchors) was the main cost driver. Mean anchor cost per case was $3432.67. “Complex” tears involving a double-row repair averaged $4570.25 in anchor cost per patient, as compared with $2522.60 in anchor costs for simple repairs.
Discussion
US health care costs continue to increase unsustainably, with rising pressure on hospitals and providers to deliver the highest value for each health care dollar. The present study is the first to calculate (using the TDABC algorithm) the direct economic cost ($5904.21) of the entire RCS care cycle at a university-based outpatient surgery center. Rent, utility costs, administrative costs, overhead, and other indirect costs at the surgery center were not included in this cost analysis, as they would be incurred irrespective of type of surgery performed. As such, our data isolate the procedure-specific costs of rotator cuff repair in order to provide a more meaningful comparison for other institutions, where indirect costs may be different.
In the literature, rigorous economic analysis of shoulder pathology is sparse. Kuye and colleagues12 systematically reviewed economic evaluations in shoulder surgery for the period 1980–2010 and noted more than 50% of the papers were published between 2005 and 2010.12 They also noted the poor quality of these studies and concluded more rigorous economic evaluations are needed to help justify the rising costs of shoulder-related treatments.
Several studies have directly evaluated costs associated with RCS. Cordasco and colleagues13 detailed the success of open rotator cuff repair as an outpatient procedure—noting its 43% cost savings ($4300 for outpatient vs $7500 for inpatient) and high patient satisfaction—using hospital charge data for operating room time, supplies, instruments, and postoperative slings. Churchill and Ghorai14 evaluated costs of mini-open and arthroscopic rotator cuff repairs in a statewide database and estimated the arthroscopic repair cost at $8985, compared with $7841 for the mini-open repair. They used reported hospital charge data, which were not itemized and did not include physician professional fees. Adla and colleagues,15 in a similar analysis of open versus arthroscopic cuff repair, estimated direct material costs of $1609.50 (arthroscopic) and $360.75 (open); these figures were converted from 2005 UK currency using the exchange rate cited in their paper. Salaries of surgeon, anesthesiologist, and other operating room personnel were said to be included in the operating room cost, but the authors’ paper did not include these data.
Two studies directly estimated the costs of arthroscopic rotator cuff repair. Hearnden and Tennent16 calculated the cost of RCS at their UK institution to be £2672, which included cost of operating room consumable materials, medication, and salaries of operating room personnel, including surgeon and anesthesiologist. Using online currency conversion from 2008 exchange rates and adjusting for inflation gave a corresponding US cost of $5449.63.17 Vitale and colleagues18 prospectively calculated costs of arthroscopic rotator cuff repair over a 1-year period using a cost-to-charge ratio from tabulated inpatient charges, procedure charges, and physician fees and payments abstracted from medical records, hospital billing, and administrative databases. Mean total cost for this cycle was $10,605.20, which included several costs (physical therapy, radiologist fees) not included in the present study. These studies, though more comprehensive than prior work, did not capture the entire cycle of surgical care.
Our study was designed to provide initial data on the direct costs of arthroscopic repair of the rotator cuff for the entire process cycle. Our overall cost estimate of $5904.21 differs significantly from prior work—not unexpected given the completely different cost methodology used.
Our study had several limitations. First, it was a single-surgeon evaluation, and a number of operating room variables (eg, use of adjunct instrumentation such as radiofrequency probes, differences in draping preferences) as well as surgeon volume in performing rotator cuff repairs might have substantially affected the reproducibility and generalizability of our data. Similarly, the large number of adjunctive procedures (eg, subacromial decompression, labral débridement) performed in conjunction with the rotator cuff repairs added operative time and therefore increased overall cost. Double-row repairs added operative time and increased the cost of consumable materials as well. Differences in surgeon preference for suture anchors may also be important, as anchors are a major cost driver and can vary significantly between vendors and institutions. Tear-related variables (eg, tear size, tear chronicity, degree of fatty cuff degeneration) were not controlled for and might have significantly affected operative time and associated cost. Resident involvement in the surgical procedure and anesthesia process in an academic setting prolongs surgical time and thus directly impacts costs.
In addition, we used the patient’s time in the operating room as a proxy for actual surgical time, as this was the only reliable and reproducible data point available in our electronic medical record. As such, an unquantifiable amount of surgeon time may have been overallocated to our cost estimate for time spent inducing anesthesia, positioning, helping take the patient off the operating table, and so on. However, as typical surgeon practice is to be involved in these tasks in the operating room, the possible overestimate of surgeon cost is likely minimal.
Our salary data for the TDABC algorithm were based on national averages for work hours and gross income for physicians and on hospital-based wage structure and may not be generalizable to other institutions. There may also be regional differences in work hours and salaries, which in turn would factor into a different per-minute cost for surgeon and anesthesiologist, depending on the exact geographic area where the surgery is performed. Costs may be higher at institutions that use certified nurse anesthetists rather than resident physicians because of the salary differences between these practitioners.
Moreover, the time that patients spend in the holding area—waiting to go into surgery and, after surgery, waiting for their ride home, for their prescriptions to be ready, and so forth—is an important variable to consider from a cost standpoint. However, as this time varied significantly and involved minimal contact with hospital personnel, we excluded its associated costs from our analysis. Similarly, and as already noted, hospital overhead and other indirect costs were excluded from analysis as well.
Conclusion
Using the TDABC algorithm, we found a direct economic cost of $5904.21 for RCS at our academic outpatient surgical center, with anchor cost the main cost driver. Judicious use of consumable resources is a key focus for cost containment in arthroscopic shoulder surgery, particularly with respect to implantable suture anchors. However, in the setting of more complex tears that require multiple anchors in a double-row repair construct, our pilot data may be useful to hospitals and surgery centers negotiating procedural reimbursement for the increased cost of complex repairs. Use of the TDABC algorithm for RCS and other procedures may also help in identifying opportunities to deliver more cost-effective health care.
1. American Academy of Orthopaedic Surgeons. The Burden of Musculoskeletal Diseases in the United States: Prevalence, Societal and Economic Cost. Rosemont, IL: American Academy of Orthopaedic Surgeons; 2011.
2. National health expenditure data. Centers for Medicare & Medicare Services website. https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/NationalHealthExpendData/index.html. Updated May 5, 2014. Accessed December 1, 2015.
3. Tashjian RZ. Epidemiology, natural history, and indications for treatment of rotator cuff tears. Clin Sports Med. 2012;31(4):589-604.
4. Colvin AC, Egorova N, Harrison AK, Moskowitz A, Flatow EL. National trends in rotator cuff repair. J Bone Joint Surg Am. 2012;94(3):227-233.
5. Black EM, Higgins LD, Warner JJ. Value-based shoulder surgery: practicing outcomes-driven, cost-conscious care. J Shoulder Elbow Surg. 2013;22(7):1000-1009.
6. Porter ME, Teisberg EO. Redefining Health Care: Creating Value-Based Competition on Results. Boston, MA: Harvard Business School Press; 2006.
7. Kaplan RS, Porter ME. How to solve the cost crisis in health care. Harv Bus Rev. 2011;89(9):46-52, 54, 56-61 passim.
8. Kaplan RS, Anderson SR. Time-driven activity-based costing. Harv Bus Rev. 2004;82(11):131-138, 150.
9. Kaplan RS, Anderson SR. Time-Driven Activity-Based Costing: A Simpler and More Powerful Path to Higher Profits. Boston, MA: Harvard Business Review Press; 2007.
10. American Academy of Orthopaedic Surgeons. Orthopaedic Practice in the U.S. 2012. Rosemont, IL: American Academy of Orthopaedic Surgeons; 2012.
11. Medical Group Management Association. Physician Compensation and Production Survey: 2012 Report Based on 2011 Data. Englewood, CO: Medical Group Management Association; 2012.
12. Kuye IO, Jain NB, Warner L, Herndon JH, Warner JJ. Economic evaluations in shoulder pathologies: a systematic review of the literature. J Shoulder Elbow Surg. 2012;21(3):367-375.
13. Cordasco FA, McGinley BJ, Charlton T. Rotator cuff repair as an outpatient procedure. J Shoulder Elbow Surg. 2000;9(1):27-30.
14. Churchill RS, Ghorai JK. Total cost and operating room time comparison of rotator cuff repair techniques at low, intermediate, and high volume centers: mini-open versus all-arthroscopic. J Shoulder Elbow Surg. 2010;19(5):716-721.
15. Adla DN, Rowsell M, Pandey R. Cost-effectiveness of open versus arthroscopic rotator cuff repair. J Shoulder Elbow Surg. 2010;19(2):258-261.
16. Hearnden A, Tennent D. The cost of shoulder arthroscopy: a comparison with national tariff. Ann R Coll Surg Engl. 2008;90(7):587-591.
17. Xrates currency conversion. http://www.x-rates.com/historical/?from=GBP&amount=1&date=2015-12-03. Accessed December 13, 2015.
18. Vitale MA, Vitale MG, Zivin JG, Braman JP, Bigliani LU, Flatow EL. Rotator cuff repair: an analysis of utility scores and cost-effectiveness. J Shoulder Elbow Surg. 2007;16(2):181-187.
Musculoskeletal disorders, the leading cause of disability in the United States,1 account for more than half of all persons reporting missing a workday because of a medical condition.2 Shoulder disorders in particular play a significant role in the burden of musculoskeletal disorders and cost of care. In 2008, 18.9 million adults (8.2% of the US adult population) reported chronic shoulder pain.1 Among shoulder disorders, rotator cuff pathology is the most common cause of shoulder-related disability found by orthopedic surgeons.3 Rotator cuff surgery (RCS) is one of the most commonly performed orthopedic surgical procedures, and surgery volume is on the rise. One study found a 141% increase in rotator cuff repairs between the years 1996 (~41 per 100,000 population) and 2006 (~98 per 100,000 population).4
US health care costs are also increasing. In 2011, $2.7 trillion was spent on health care, representing 17.9% of the national gross domestic product (GDP). According to projections, costs will rise to $4.6 trillion by 2020.5 In particular, as patients continue to live longer and remain more active into their later years, the costs of treating and managing musculoskeletal disorders become more important from a public policy standpoint. In 2006, the cost of treating musculoskeletal disorders alone was $576 billion, representing 4.5% of that year’s GDP.2
Paramount in this era of rising costs is the idea of maximizing the value of health care dollars. Health care economists Porter and Teisberg6 defined value as patient health outcomes achieved per dollar of cost expended in a care cycle (diagnosis, treatment, ongoing management) for a particular disease or disorder. For proper management of value, outcomes and costs for an entire cycle of care must be determined. From a practical standpoint, this first requires determining the true cost of a care cycle—dollars spent on personnel, equipment, materials, and other resources required to deliver a particular service—rather than the amount charged or reimbursed for providing the service in question.7
Kaplan and Anderson8,9 described the TDABC (time-driven activity-based costing) algorithm for calculating the cost of delivering a service based on 2 parameters: unit cost of a particular resource, and time required to supply it. These parameters apply to material costs and labor costs. In the medical setting, the TDABC algorithm can be applied by defining a care delivery value chain for each aspect of patient care and then multiplying incremental cost per unit time by time required to deliver that resource (Figure 1). Tabulating the overall unit cost for each resource then yields the overall cost of the care cycle. Clinical outcomes data can then be determined and used to calculate overall value for the patient care cycle.
In the study reported here, we used the TDABC algorithm to calculate the direct financial costs of surgical treatment of rotator cuff tears confirmed by magnetic resonance imaging (MRI) in an academic medical center.
Methods
Per our institution’s Office for the Protection of Research Subjects, institutional review board (IRB) approval is required only for projects using “human subjects” as defined by federal policy. In the present study, no private information could be identified, and all data were obtained from hospital billing records without intervention or interaction with individual patients. Accordingly, IRB approval was deemed unnecessary for our economic cost analysis.
Billing records of a single academic fellowship-trained sports surgeon were reviewed to identify patients who underwent primary repair of an MRI-confirmed rotator cuff tear between April 1, 2009, and July 31, 2012. Patients who had undergone prior shoulder surgery of any type were excluded from the study. Operative reports were reviewed, and exact surgical procedures performed were noted. The operating surgeon selected the specific repair techniques, including single- or double-row repair, with emphasis on restoring footprint coverage and avoiding overtensioning.
All surgeries were performed in an outpatient surgical center owned and operated by the surgeon’s home university. Surgeries were performed by the attending physician assisted by a senior orthopedic resident. The RCS care cycle was divided into 3 phases (Figure 2):
1. Preoperative. Patient’s interaction with receptionist in surgery center, time with preoperative nurse and circulating nurse in preoperative area, resident check-in time, and time placing preoperative nerve block and consumable materials used during block placement.
2. Operative. Time in operating room with surgical team for RCS, consumable materials used during surgery (eg, anchors, shavers, drapes), anesthetic medications, shoulder abduction pillow placed on completion of surgery, and cost of instrument processing.
3. Postoperative. Time in postoperative recovery area with recovery room nursing staff.
Time in each portion of the care cycle was directly observed and tabulated by hospital volunteers in the surgery center. Institutional billing data were used to identify material resources consumed, and the actual cost paid by the hospital for these resources was obtained from internal records. Mean hourly salary data and standard benefit rates were obtained for surgery center staff. Attending physician salary was extrapolated from published mean market salary data for academic physicians and mean hours worked,10,11 and resident physician costs were tabulated from publically available institutional payroll data and average resident work hours at our institution. These cost data and times were then used to tabulate total cost for the RCS care cycle using the TDABC algorithm.
Results
We identified 28 shoulders in 26 patients (mean age, 54.5 years) who met the inclusion criteria. Of these 28 shoulders, 18 (64.3%) had an isolated supraspinatus tear, 8 (28.6%) had combined supraspinatus and infraspinatus tears, 1 (3.6%) had combined supraspinatus and subscapularis tears, and 1 (3.6%) had an isolated infraspinatus tear. Demographic data are listed in Table 1.
All patients received an interscalene nerve block in the preoperative area before being brought into the operating room. In our analysis, we included nerve block supply costs and the anesthesiologist’s mean time placing the nerve block.
In all cases, primary rotator cuff repair was performed with suture anchors (Parcus Medical) with the patient in the lateral decubitus position. In 13 (46%) of the 28 shoulders, this repair was described as “complex,” requiring double-row technique. Subacromial decompression and bursectomy were performed in addition to the rotator cuff repair. Labral débridement was performed in 23 patients, synovectomy in 10, biceps tenodesis with anchor (Smith & Nephew) in 1, and biceps tenotomy in 1. Mean time in operating room was 148 minutes; mean time in postoperative recovery unit was 105 minutes.
Directly observing the care cycle, hospital volunteers found that patients spent a mean of 15 minutes with the receptionist when they arrived in the outpatient surgical center, 25 minutes with nurses for check-in in the preoperative holding area, and 10 minutes with the anesthesiology resident and 15 minutes with the orthopedic surgery resident for preoperative evaluation and paperwork. Mean nerve block time was 20 minutes. Mean electrocardiogram (ECG) time (12 patients) was 15 minutes. The surgical technician spent a mean time of 20 minutes setting up the operating room before the patient was brought in and 15 minutes cleaning up after the patient was transferred to the recovery room. Costs of postoperative care in the recovery room were based on a 2:1 patient-to-nurse ratio, as is the standard practice in our outpatient surgery center.
Using the times mentioned and our hospital’s salary data—including standard hospital benefits rates of 33.5% for nonphysicians and 17.65% for physicians—we determined, using the TDABC algorithm, a direct cost of $5904.21 for this process cycle, excluding hospital overhead and indirect costs. Table 2 provides the overall cost breakdown. Compared with the direct economic cost, the mean hospital charge to insurers for the procedure was $31,459.35. Mean reimbursement from insurers was $9679.08.
Overall attending and resident physician costs were $1077.75, which consisted of $623.66 for the surgeon and $454.09 for the anesthesiologist (included placement of nerve block and administration of anesthesia during surgery). Preoperative bloodwork was obtained in 23 cases, adding a mean cost of $111.04 after adjusting for standard hospital markup. Preoperative ECG was performed in 12 cases, for an added mean cost of $7.30 based on the TDABC algorithm.
We also broke down costs by care cycle phase. The preoperative phase, excluding the preoperative laboratory studies and ECGs (not performed in all cases), cost $134.34 (2.3% of total costs); the operative phase cost $5718.01 (96.8% of total costs); and the postoperative phase cost $51.86 (0.9% of total costs). Within the operative phase, the cost of consumables (specifically, suture anchors) was the main cost driver. Mean anchor cost per case was $3432.67. “Complex” tears involving a double-row repair averaged $4570.25 in anchor cost per patient, as compared with $2522.60 in anchor costs for simple repairs.
Discussion
US health care costs continue to increase unsustainably, with rising pressure on hospitals and providers to deliver the highest value for each health care dollar. The present study is the first to calculate (using the TDABC algorithm) the direct economic cost ($5904.21) of the entire RCS care cycle at a university-based outpatient surgery center. Rent, utility costs, administrative costs, overhead, and other indirect costs at the surgery center were not included in this cost analysis, as they would be incurred irrespective of type of surgery performed. As such, our data isolate the procedure-specific costs of rotator cuff repair in order to provide a more meaningful comparison for other institutions, where indirect costs may be different.
In the literature, rigorous economic analysis of shoulder pathology is sparse. Kuye and colleagues12 systematically reviewed economic evaluations in shoulder surgery for the period 1980–2010 and noted more than 50% of the papers were published between 2005 and 2010.12 They also noted the poor quality of these studies and concluded more rigorous economic evaluations are needed to help justify the rising costs of shoulder-related treatments.
Several studies have directly evaluated costs associated with RCS. Cordasco and colleagues13 detailed the success of open rotator cuff repair as an outpatient procedure—noting its 43% cost savings ($4300 for outpatient vs $7500 for inpatient) and high patient satisfaction—using hospital charge data for operating room time, supplies, instruments, and postoperative slings. Churchill and Ghorai14 evaluated costs of mini-open and arthroscopic rotator cuff repairs in a statewide database and estimated the arthroscopic repair cost at $8985, compared with $7841 for the mini-open repair. They used reported hospital charge data, which were not itemized and did not include physician professional fees. Adla and colleagues,15 in a similar analysis of open versus arthroscopic cuff repair, estimated direct material costs of $1609.50 (arthroscopic) and $360.75 (open); these figures were converted from 2005 UK currency using the exchange rate cited in their paper. Salaries of surgeon, anesthesiologist, and other operating room personnel were said to be included in the operating room cost, but the authors’ paper did not include these data.
Two studies directly estimated the costs of arthroscopic rotator cuff repair. Hearnden and Tennent16 calculated the cost of RCS at their UK institution to be £2672, which included cost of operating room consumable materials, medication, and salaries of operating room personnel, including surgeon and anesthesiologist. Using online currency conversion from 2008 exchange rates and adjusting for inflation gave a corresponding US cost of $5449.63.17 Vitale and colleagues18 prospectively calculated costs of arthroscopic rotator cuff repair over a 1-year period using a cost-to-charge ratio from tabulated inpatient charges, procedure charges, and physician fees and payments abstracted from medical records, hospital billing, and administrative databases. Mean total cost for this cycle was $10,605.20, which included several costs (physical therapy, radiologist fees) not included in the present study. These studies, though more comprehensive than prior work, did not capture the entire cycle of surgical care.
Our study was designed to provide initial data on the direct costs of arthroscopic repair of the rotator cuff for the entire process cycle. Our overall cost estimate of $5904.21 differs significantly from prior work—not unexpected given the completely different cost methodology used.
Our study had several limitations. First, it was a single-surgeon evaluation, and a number of operating room variables (eg, use of adjunct instrumentation such as radiofrequency probes, differences in draping preferences) as well as surgeon volume in performing rotator cuff repairs might have substantially affected the reproducibility and generalizability of our data. Similarly, the large number of adjunctive procedures (eg, subacromial decompression, labral débridement) performed in conjunction with the rotator cuff repairs added operative time and therefore increased overall cost. Double-row repairs added operative time and increased the cost of consumable materials as well. Differences in surgeon preference for suture anchors may also be important, as anchors are a major cost driver and can vary significantly between vendors and institutions. Tear-related variables (eg, tear size, tear chronicity, degree of fatty cuff degeneration) were not controlled for and might have significantly affected operative time and associated cost. Resident involvement in the surgical procedure and anesthesia process in an academic setting prolongs surgical time and thus directly impacts costs.
In addition, we used the patient’s time in the operating room as a proxy for actual surgical time, as this was the only reliable and reproducible data point available in our electronic medical record. As such, an unquantifiable amount of surgeon time may have been overallocated to our cost estimate for time spent inducing anesthesia, positioning, helping take the patient off the operating table, and so on. However, as typical surgeon practice is to be involved in these tasks in the operating room, the possible overestimate of surgeon cost is likely minimal.
Our salary data for the TDABC algorithm were based on national averages for work hours and gross income for physicians and on hospital-based wage structure and may not be generalizable to other institutions. There may also be regional differences in work hours and salaries, which in turn would factor into a different per-minute cost for surgeon and anesthesiologist, depending on the exact geographic area where the surgery is performed. Costs may be higher at institutions that use certified nurse anesthetists rather than resident physicians because of the salary differences between these practitioners.
Moreover, the time that patients spend in the holding area—waiting to go into surgery and, after surgery, waiting for their ride home, for their prescriptions to be ready, and so forth—is an important variable to consider from a cost standpoint. However, as this time varied significantly and involved minimal contact with hospital personnel, we excluded its associated costs from our analysis. Similarly, and as already noted, hospital overhead and other indirect costs were excluded from analysis as well.
Conclusion
Using the TDABC algorithm, we found a direct economic cost of $5904.21 for RCS at our academic outpatient surgical center, with anchor cost the main cost driver. Judicious use of consumable resources is a key focus for cost containment in arthroscopic shoulder surgery, particularly with respect to implantable suture anchors. However, in the setting of more complex tears that require multiple anchors in a double-row repair construct, our pilot data may be useful to hospitals and surgery centers negotiating procedural reimbursement for the increased cost of complex repairs. Use of the TDABC algorithm for RCS and other procedures may also help in identifying opportunities to deliver more cost-effective health care.
Musculoskeletal disorders, the leading cause of disability in the United States,1 account for more than half of all persons reporting missing a workday because of a medical condition.2 Shoulder disorders in particular play a significant role in the burden of musculoskeletal disorders and cost of care. In 2008, 18.9 million adults (8.2% of the US adult population) reported chronic shoulder pain.1 Among shoulder disorders, rotator cuff pathology is the most common cause of shoulder-related disability found by orthopedic surgeons.3 Rotator cuff surgery (RCS) is one of the most commonly performed orthopedic surgical procedures, and surgery volume is on the rise. One study found a 141% increase in rotator cuff repairs between the years 1996 (~41 per 100,000 population) and 2006 (~98 per 100,000 population).4
US health care costs are also increasing. In 2011, $2.7 trillion was spent on health care, representing 17.9% of the national gross domestic product (GDP). According to projections, costs will rise to $4.6 trillion by 2020.5 In particular, as patients continue to live longer and remain more active into their later years, the costs of treating and managing musculoskeletal disorders become more important from a public policy standpoint. In 2006, the cost of treating musculoskeletal disorders alone was $576 billion, representing 4.5% of that year’s GDP.2
Paramount in this era of rising costs is the idea of maximizing the value of health care dollars. Health care economists Porter and Teisberg6 defined value as patient health outcomes achieved per dollar of cost expended in a care cycle (diagnosis, treatment, ongoing management) for a particular disease or disorder. For proper management of value, outcomes and costs for an entire cycle of care must be determined. From a practical standpoint, this first requires determining the true cost of a care cycle—dollars spent on personnel, equipment, materials, and other resources required to deliver a particular service—rather than the amount charged or reimbursed for providing the service in question.7
Kaplan and Anderson8,9 described the TDABC (time-driven activity-based costing) algorithm for calculating the cost of delivering a service based on 2 parameters: unit cost of a particular resource, and time required to supply it. These parameters apply to material costs and labor costs. In the medical setting, the TDABC algorithm can be applied by defining a care delivery value chain for each aspect of patient care and then multiplying incremental cost per unit time by time required to deliver that resource (Figure 1). Tabulating the overall unit cost for each resource then yields the overall cost of the care cycle. Clinical outcomes data can then be determined and used to calculate overall value for the patient care cycle.
In the study reported here, we used the TDABC algorithm to calculate the direct financial costs of surgical treatment of rotator cuff tears confirmed by magnetic resonance imaging (MRI) in an academic medical center.
Methods
Per our institution’s Office for the Protection of Research Subjects, institutional review board (IRB) approval is required only for projects using “human subjects” as defined by federal policy. In the present study, no private information could be identified, and all data were obtained from hospital billing records without intervention or interaction with individual patients. Accordingly, IRB approval was deemed unnecessary for our economic cost analysis.
Billing records of a single academic fellowship-trained sports surgeon were reviewed to identify patients who underwent primary repair of an MRI-confirmed rotator cuff tear between April 1, 2009, and July 31, 2012. Patients who had undergone prior shoulder surgery of any type were excluded from the study. Operative reports were reviewed, and exact surgical procedures performed were noted. The operating surgeon selected the specific repair techniques, including single- or double-row repair, with emphasis on restoring footprint coverage and avoiding overtensioning.
All surgeries were performed in an outpatient surgical center owned and operated by the surgeon’s home university. Surgeries were performed by the attending physician assisted by a senior orthopedic resident. The RCS care cycle was divided into 3 phases (Figure 2):
1. Preoperative. Patient’s interaction with receptionist in surgery center, time with preoperative nurse and circulating nurse in preoperative area, resident check-in time, and time placing preoperative nerve block and consumable materials used during block placement.
2. Operative. Time in operating room with surgical team for RCS, consumable materials used during surgery (eg, anchors, shavers, drapes), anesthetic medications, shoulder abduction pillow placed on completion of surgery, and cost of instrument processing.
3. Postoperative. Time in postoperative recovery area with recovery room nursing staff.
Time in each portion of the care cycle was directly observed and tabulated by hospital volunteers in the surgery center. Institutional billing data were used to identify material resources consumed, and the actual cost paid by the hospital for these resources was obtained from internal records. Mean hourly salary data and standard benefit rates were obtained for surgery center staff. Attending physician salary was extrapolated from published mean market salary data for academic physicians and mean hours worked,10,11 and resident physician costs were tabulated from publically available institutional payroll data and average resident work hours at our institution. These cost data and times were then used to tabulate total cost for the RCS care cycle using the TDABC algorithm.
Results
We identified 28 shoulders in 26 patients (mean age, 54.5 years) who met the inclusion criteria. Of these 28 shoulders, 18 (64.3%) had an isolated supraspinatus tear, 8 (28.6%) had combined supraspinatus and infraspinatus tears, 1 (3.6%) had combined supraspinatus and subscapularis tears, and 1 (3.6%) had an isolated infraspinatus tear. Demographic data are listed in Table 1.
All patients received an interscalene nerve block in the preoperative area before being brought into the operating room. In our analysis, we included nerve block supply costs and the anesthesiologist’s mean time placing the nerve block.
In all cases, primary rotator cuff repair was performed with suture anchors (Parcus Medical) with the patient in the lateral decubitus position. In 13 (46%) of the 28 shoulders, this repair was described as “complex,” requiring double-row technique. Subacromial decompression and bursectomy were performed in addition to the rotator cuff repair. Labral débridement was performed in 23 patients, synovectomy in 10, biceps tenodesis with anchor (Smith & Nephew) in 1, and biceps tenotomy in 1. Mean time in operating room was 148 minutes; mean time in postoperative recovery unit was 105 minutes.
Directly observing the care cycle, hospital volunteers found that patients spent a mean of 15 minutes with the receptionist when they arrived in the outpatient surgical center, 25 minutes with nurses for check-in in the preoperative holding area, and 10 minutes with the anesthesiology resident and 15 minutes with the orthopedic surgery resident for preoperative evaluation and paperwork. Mean nerve block time was 20 minutes. Mean electrocardiogram (ECG) time (12 patients) was 15 minutes. The surgical technician spent a mean time of 20 minutes setting up the operating room before the patient was brought in and 15 minutes cleaning up after the patient was transferred to the recovery room. Costs of postoperative care in the recovery room were based on a 2:1 patient-to-nurse ratio, as is the standard practice in our outpatient surgery center.
Using the times mentioned and our hospital’s salary data—including standard hospital benefits rates of 33.5% for nonphysicians and 17.65% for physicians—we determined, using the TDABC algorithm, a direct cost of $5904.21 for this process cycle, excluding hospital overhead and indirect costs. Table 2 provides the overall cost breakdown. Compared with the direct economic cost, the mean hospital charge to insurers for the procedure was $31,459.35. Mean reimbursement from insurers was $9679.08.
Overall attending and resident physician costs were $1077.75, which consisted of $623.66 for the surgeon and $454.09 for the anesthesiologist (included placement of nerve block and administration of anesthesia during surgery). Preoperative bloodwork was obtained in 23 cases, adding a mean cost of $111.04 after adjusting for standard hospital markup. Preoperative ECG was performed in 12 cases, for an added mean cost of $7.30 based on the TDABC algorithm.
We also broke down costs by care cycle phase. The preoperative phase, excluding the preoperative laboratory studies and ECGs (not performed in all cases), cost $134.34 (2.3% of total costs); the operative phase cost $5718.01 (96.8% of total costs); and the postoperative phase cost $51.86 (0.9% of total costs). Within the operative phase, the cost of consumables (specifically, suture anchors) was the main cost driver. Mean anchor cost per case was $3432.67. “Complex” tears involving a double-row repair averaged $4570.25 in anchor cost per patient, as compared with $2522.60 in anchor costs for simple repairs.
Discussion
US health care costs continue to increase unsustainably, with rising pressure on hospitals and providers to deliver the highest value for each health care dollar. The present study is the first to calculate (using the TDABC algorithm) the direct economic cost ($5904.21) of the entire RCS care cycle at a university-based outpatient surgery center. Rent, utility costs, administrative costs, overhead, and other indirect costs at the surgery center were not included in this cost analysis, as they would be incurred irrespective of type of surgery performed. As such, our data isolate the procedure-specific costs of rotator cuff repair in order to provide a more meaningful comparison for other institutions, where indirect costs may be different.
In the literature, rigorous economic analysis of shoulder pathology is sparse. Kuye and colleagues12 systematically reviewed economic evaluations in shoulder surgery for the period 1980–2010 and noted more than 50% of the papers were published between 2005 and 2010.12 They also noted the poor quality of these studies and concluded more rigorous economic evaluations are needed to help justify the rising costs of shoulder-related treatments.
Several studies have directly evaluated costs associated with RCS. Cordasco and colleagues13 detailed the success of open rotator cuff repair as an outpatient procedure—noting its 43% cost savings ($4300 for outpatient vs $7500 for inpatient) and high patient satisfaction—using hospital charge data for operating room time, supplies, instruments, and postoperative slings. Churchill and Ghorai14 evaluated costs of mini-open and arthroscopic rotator cuff repairs in a statewide database and estimated the arthroscopic repair cost at $8985, compared with $7841 for the mini-open repair. They used reported hospital charge data, which were not itemized and did not include physician professional fees. Adla and colleagues,15 in a similar analysis of open versus arthroscopic cuff repair, estimated direct material costs of $1609.50 (arthroscopic) and $360.75 (open); these figures were converted from 2005 UK currency using the exchange rate cited in their paper. Salaries of surgeon, anesthesiologist, and other operating room personnel were said to be included in the operating room cost, but the authors’ paper did not include these data.
Two studies directly estimated the costs of arthroscopic rotator cuff repair. Hearnden and Tennent16 calculated the cost of RCS at their UK institution to be £2672, which included cost of operating room consumable materials, medication, and salaries of operating room personnel, including surgeon and anesthesiologist. Using online currency conversion from 2008 exchange rates and adjusting for inflation gave a corresponding US cost of $5449.63.17 Vitale and colleagues18 prospectively calculated costs of arthroscopic rotator cuff repair over a 1-year period using a cost-to-charge ratio from tabulated inpatient charges, procedure charges, and physician fees and payments abstracted from medical records, hospital billing, and administrative databases. Mean total cost for this cycle was $10,605.20, which included several costs (physical therapy, radiologist fees) not included in the present study. These studies, though more comprehensive than prior work, did not capture the entire cycle of surgical care.
Our study was designed to provide initial data on the direct costs of arthroscopic repair of the rotator cuff for the entire process cycle. Our overall cost estimate of $5904.21 differs significantly from prior work—not unexpected given the completely different cost methodology used.
Our study had several limitations. First, it was a single-surgeon evaluation, and a number of operating room variables (eg, use of adjunct instrumentation such as radiofrequency probes, differences in draping preferences) as well as surgeon volume in performing rotator cuff repairs might have substantially affected the reproducibility and generalizability of our data. Similarly, the large number of adjunctive procedures (eg, subacromial decompression, labral débridement) performed in conjunction with the rotator cuff repairs added operative time and therefore increased overall cost. Double-row repairs added operative time and increased the cost of consumable materials as well. Differences in surgeon preference for suture anchors may also be important, as anchors are a major cost driver and can vary significantly between vendors and institutions. Tear-related variables (eg, tear size, tear chronicity, degree of fatty cuff degeneration) were not controlled for and might have significantly affected operative time and associated cost. Resident involvement in the surgical procedure and anesthesia process in an academic setting prolongs surgical time and thus directly impacts costs.
In addition, we used the patient’s time in the operating room as a proxy for actual surgical time, as this was the only reliable and reproducible data point available in our electronic medical record. As such, an unquantifiable amount of surgeon time may have been overallocated to our cost estimate for time spent inducing anesthesia, positioning, helping take the patient off the operating table, and so on. However, as typical surgeon practice is to be involved in these tasks in the operating room, the possible overestimate of surgeon cost is likely minimal.
Our salary data for the TDABC algorithm were based on national averages for work hours and gross income for physicians and on hospital-based wage structure and may not be generalizable to other institutions. There may also be regional differences in work hours and salaries, which in turn would factor into a different per-minute cost for surgeon and anesthesiologist, depending on the exact geographic area where the surgery is performed. Costs may be higher at institutions that use certified nurse anesthetists rather than resident physicians because of the salary differences between these practitioners.
Moreover, the time that patients spend in the holding area—waiting to go into surgery and, after surgery, waiting for their ride home, for their prescriptions to be ready, and so forth—is an important variable to consider from a cost standpoint. However, as this time varied significantly and involved minimal contact with hospital personnel, we excluded its associated costs from our analysis. Similarly, and as already noted, hospital overhead and other indirect costs were excluded from analysis as well.
Conclusion
Using the TDABC algorithm, we found a direct economic cost of $5904.21 for RCS at our academic outpatient surgical center, with anchor cost the main cost driver. Judicious use of consumable resources is a key focus for cost containment in arthroscopic shoulder surgery, particularly with respect to implantable suture anchors. However, in the setting of more complex tears that require multiple anchors in a double-row repair construct, our pilot data may be useful to hospitals and surgery centers negotiating procedural reimbursement for the increased cost of complex repairs. Use of the TDABC algorithm for RCS and other procedures may also help in identifying opportunities to deliver more cost-effective health care.
1. American Academy of Orthopaedic Surgeons. The Burden of Musculoskeletal Diseases in the United States: Prevalence, Societal and Economic Cost. Rosemont, IL: American Academy of Orthopaedic Surgeons; 2011.
2. National health expenditure data. Centers for Medicare & Medicare Services website. https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/NationalHealthExpendData/index.html. Updated May 5, 2014. Accessed December 1, 2015.
3. Tashjian RZ. Epidemiology, natural history, and indications for treatment of rotator cuff tears. Clin Sports Med. 2012;31(4):589-604.
4. Colvin AC, Egorova N, Harrison AK, Moskowitz A, Flatow EL. National trends in rotator cuff repair. J Bone Joint Surg Am. 2012;94(3):227-233.
5. Black EM, Higgins LD, Warner JJ. Value-based shoulder surgery: practicing outcomes-driven, cost-conscious care. J Shoulder Elbow Surg. 2013;22(7):1000-1009.
6. Porter ME, Teisberg EO. Redefining Health Care: Creating Value-Based Competition on Results. Boston, MA: Harvard Business School Press; 2006.
7. Kaplan RS, Porter ME. How to solve the cost crisis in health care. Harv Bus Rev. 2011;89(9):46-52, 54, 56-61 passim.
8. Kaplan RS, Anderson SR. Time-driven activity-based costing. Harv Bus Rev. 2004;82(11):131-138, 150.
9. Kaplan RS, Anderson SR. Time-Driven Activity-Based Costing: A Simpler and More Powerful Path to Higher Profits. Boston, MA: Harvard Business Review Press; 2007.
10. American Academy of Orthopaedic Surgeons. Orthopaedic Practice in the U.S. 2012. Rosemont, IL: American Academy of Orthopaedic Surgeons; 2012.
11. Medical Group Management Association. Physician Compensation and Production Survey: 2012 Report Based on 2011 Data. Englewood, CO: Medical Group Management Association; 2012.
12. Kuye IO, Jain NB, Warner L, Herndon JH, Warner JJ. Economic evaluations in shoulder pathologies: a systematic review of the literature. J Shoulder Elbow Surg. 2012;21(3):367-375.
13. Cordasco FA, McGinley BJ, Charlton T. Rotator cuff repair as an outpatient procedure. J Shoulder Elbow Surg. 2000;9(1):27-30.
14. Churchill RS, Ghorai JK. Total cost and operating room time comparison of rotator cuff repair techniques at low, intermediate, and high volume centers: mini-open versus all-arthroscopic. J Shoulder Elbow Surg. 2010;19(5):716-721.
15. Adla DN, Rowsell M, Pandey R. Cost-effectiveness of open versus arthroscopic rotator cuff repair. J Shoulder Elbow Surg. 2010;19(2):258-261.
16. Hearnden A, Tennent D. The cost of shoulder arthroscopy: a comparison with national tariff. Ann R Coll Surg Engl. 2008;90(7):587-591.
17. Xrates currency conversion. http://www.x-rates.com/historical/?from=GBP&amount=1&date=2015-12-03. Accessed December 13, 2015.
18. Vitale MA, Vitale MG, Zivin JG, Braman JP, Bigliani LU, Flatow EL. Rotator cuff repair: an analysis of utility scores and cost-effectiveness. J Shoulder Elbow Surg. 2007;16(2):181-187.
1. American Academy of Orthopaedic Surgeons. The Burden of Musculoskeletal Diseases in the United States: Prevalence, Societal and Economic Cost. Rosemont, IL: American Academy of Orthopaedic Surgeons; 2011.
2. National health expenditure data. Centers for Medicare & Medicare Services website. https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/NationalHealthExpendData/index.html. Updated May 5, 2014. Accessed December 1, 2015.
3. Tashjian RZ. Epidemiology, natural history, and indications for treatment of rotator cuff tears. Clin Sports Med. 2012;31(4):589-604.
4. Colvin AC, Egorova N, Harrison AK, Moskowitz A, Flatow EL. National trends in rotator cuff repair. J Bone Joint Surg Am. 2012;94(3):227-233.
5. Black EM, Higgins LD, Warner JJ. Value-based shoulder surgery: practicing outcomes-driven, cost-conscious care. J Shoulder Elbow Surg. 2013;22(7):1000-1009.
6. Porter ME, Teisberg EO. Redefining Health Care: Creating Value-Based Competition on Results. Boston, MA: Harvard Business School Press; 2006.
7. Kaplan RS, Porter ME. How to solve the cost crisis in health care. Harv Bus Rev. 2011;89(9):46-52, 54, 56-61 passim.
8. Kaplan RS, Anderson SR. Time-driven activity-based costing. Harv Bus Rev. 2004;82(11):131-138, 150.
9. Kaplan RS, Anderson SR. Time-Driven Activity-Based Costing: A Simpler and More Powerful Path to Higher Profits. Boston, MA: Harvard Business Review Press; 2007.
10. American Academy of Orthopaedic Surgeons. Orthopaedic Practice in the U.S. 2012. Rosemont, IL: American Academy of Orthopaedic Surgeons; 2012.
11. Medical Group Management Association. Physician Compensation and Production Survey: 2012 Report Based on 2011 Data. Englewood, CO: Medical Group Management Association; 2012.
12. Kuye IO, Jain NB, Warner L, Herndon JH, Warner JJ. Economic evaluations in shoulder pathologies: a systematic review of the literature. J Shoulder Elbow Surg. 2012;21(3):367-375.
13. Cordasco FA, McGinley BJ, Charlton T. Rotator cuff repair as an outpatient procedure. J Shoulder Elbow Surg. 2000;9(1):27-30.
14. Churchill RS, Ghorai JK. Total cost and operating room time comparison of rotator cuff repair techniques at low, intermediate, and high volume centers: mini-open versus all-arthroscopic. J Shoulder Elbow Surg. 2010;19(5):716-721.
15. Adla DN, Rowsell M, Pandey R. Cost-effectiveness of open versus arthroscopic rotator cuff repair. J Shoulder Elbow Surg. 2010;19(2):258-261.
16. Hearnden A, Tennent D. The cost of shoulder arthroscopy: a comparison with national tariff. Ann R Coll Surg Engl. 2008;90(7):587-591.
17. Xrates currency conversion. http://www.x-rates.com/historical/?from=GBP&amount=1&date=2015-12-03. Accessed December 13, 2015.
18. Vitale MA, Vitale MG, Zivin JG, Braman JP, Bigliani LU, Flatow EL. Rotator cuff repair: an analysis of utility scores and cost-effectiveness. J Shoulder Elbow Surg. 2007;16(2):181-187.
The Right Choice? Kindness and Surgical Ethics: Reflections on a Friend and Mentor
As I sit down to write this column, I reflect on the news that my mentor and friend, Norman W. Thompson, M.D, FACS, passed away yesterday. I had the good fortune to spend 1 year as an endocrine surgery fellow with Dr. Thompson at the University of Michigan in 1995-96. That year was certainly the most significant of my training in terms of defining my professional life as an endocrine surgeon. However, as I think back on my time with Dr. Thompson, I am struck by how much more I learned from him than how to take out a thyroid or a parathyroid or manage multiple endocrine neoplasia.
Dr. Thompson was an excellent technical surgeon, and he would have had a tremendous career helping thousands of patients if that was all that he had done. However, he was much more than an excellent technician. He was also a great doctor. In order for a surgeon to be a great doctor, it is necessary to be technically excellent, but that alone is not sufficient. I believe that what makes a surgeon a great doctor is the combination of technical mastery with outstanding interpersonal skills and ethically sound clinical judgment. Dr. Thompson had all of that, and he was exceptionally kind.
Kindness is not a word that we commonly use in describing surgeons today. In an era of surgeons being pressured to see more patients and generate more RVUs [relative value units], it is unusual to hear kindness mentioned as an essential attribute of a great surgeon. However, Dr. Thompson’s kindness was immediately apparent to all who spent time with him. He treated each patient as a unique individual. In addition, he treated his trainees and his colleagues in Ann Arbor and around the world with respect and incredible humility. He was generous with his time and was always approachable no matter how inexperienced the surgeon asking him a question. Dr. Thompson was kind to all of us and made us feel that he valued spending time with us.
What does kindness have to do with a column that traditionally focuses on ethical issues in the practice of surgery? Although acting with kindness is not the same as acting in an ethical manner, I believe that there is more overlap of the terms than we often imagine. The kind surgeon is the one who treats people – whether they are patients or colleagues – as though they matter. The ethical surgeon respects the patient’s wishes and acts to benefit the patient as much as possible in all circumstances. I am certain that I have met ethical surgeons who were not kind, but I have met very few kind surgeons who are not ethical.
As someone who has spent significant time and energy in the last 19 years as a surgery faculty member trying to teach ethics, I am also struck by a clear truth. Actions always speak louder than words. It may be valuable to talk about the ethical principles that may come to play in a particularly difficult surgical case. Defining the competing interests and assessing the patient’s wishes are important components of the ethical practice of surgery. However, no amount of discussion of these issues can substitute for the value of behavior. Treating patients and colleagues with kindness and respect is modeling the behaviors of an ethical surgeon – perhaps learned from a wise and thoughtful mentor.
Dr. Thompson was an excellent role model for me and so many others in how he treated patients and everyone around him. As I see patients and perform surgery, I still hear myself saying many of the same things that he said many years ago. His genuine expressions of optimism before difficult operations, honesty in communicating, and sadness when things did not go well were tremendous examples to me of how a great doctor treats those around him. These lessons that I learned from Dr. Thompson have influenced my practice significantly, and I am grateful for the opportunity to try to model them on a daily basis.
Although I remain convinced that formal curricula in ethics and professionalism remain important in the education of today’s surgeons, it is valuable to remember the impact that the behaviors of those we respect have on us. Perhaps we surgeons more than other physicians are molded by the people who train us, but there is no question that the ethical behaviors of our teachers and mentors will have a greater impact than any lecture or manuscript. I want to acknowledge and commemorate the kindness and ethical behaviors that Dr. Thompson modeled daily for all who were fortunate enough to work with him.
Dr. Angelos is an ACS Fellow; the Linda Kohler Anderson Professor of Surgery and Surgical Ethics; chief, endocrine surgery; and associate director of the MacLean Center for Clinical Medical Ethics at the University of Chicago.
As I sit down to write this column, I reflect on the news that my mentor and friend, Norman W. Thompson, M.D, FACS, passed away yesterday. I had the good fortune to spend 1 year as an endocrine surgery fellow with Dr. Thompson at the University of Michigan in 1995-96. That year was certainly the most significant of my training in terms of defining my professional life as an endocrine surgeon. However, as I think back on my time with Dr. Thompson, I am struck by how much more I learned from him than how to take out a thyroid or a parathyroid or manage multiple endocrine neoplasia.
Dr. Thompson was an excellent technical surgeon, and he would have had a tremendous career helping thousands of patients if that was all that he had done. However, he was much more than an excellent technician. He was also a great doctor. In order for a surgeon to be a great doctor, it is necessary to be technically excellent, but that alone is not sufficient. I believe that what makes a surgeon a great doctor is the combination of technical mastery with outstanding interpersonal skills and ethically sound clinical judgment. Dr. Thompson had all of that, and he was exceptionally kind.
Kindness is not a word that we commonly use in describing surgeons today. In an era of surgeons being pressured to see more patients and generate more RVUs [relative value units], it is unusual to hear kindness mentioned as an essential attribute of a great surgeon. However, Dr. Thompson’s kindness was immediately apparent to all who spent time with him. He treated each patient as a unique individual. In addition, he treated his trainees and his colleagues in Ann Arbor and around the world with respect and incredible humility. He was generous with his time and was always approachable no matter how inexperienced the surgeon asking him a question. Dr. Thompson was kind to all of us and made us feel that he valued spending time with us.
What does kindness have to do with a column that traditionally focuses on ethical issues in the practice of surgery? Although acting with kindness is not the same as acting in an ethical manner, I believe that there is more overlap of the terms than we often imagine. The kind surgeon is the one who treats people – whether they are patients or colleagues – as though they matter. The ethical surgeon respects the patient’s wishes and acts to benefit the patient as much as possible in all circumstances. I am certain that I have met ethical surgeons who were not kind, but I have met very few kind surgeons who are not ethical.
As someone who has spent significant time and energy in the last 19 years as a surgery faculty member trying to teach ethics, I am also struck by a clear truth. Actions always speak louder than words. It may be valuable to talk about the ethical principles that may come to play in a particularly difficult surgical case. Defining the competing interests and assessing the patient’s wishes are important components of the ethical practice of surgery. However, no amount of discussion of these issues can substitute for the value of behavior. Treating patients and colleagues with kindness and respect is modeling the behaviors of an ethical surgeon – perhaps learned from a wise and thoughtful mentor.
Dr. Thompson was an excellent role model for me and so many others in how he treated patients and everyone around him. As I see patients and perform surgery, I still hear myself saying many of the same things that he said many years ago. His genuine expressions of optimism before difficult operations, honesty in communicating, and sadness when things did not go well were tremendous examples to me of how a great doctor treats those around him. These lessons that I learned from Dr. Thompson have influenced my practice significantly, and I am grateful for the opportunity to try to model them on a daily basis.
Although I remain convinced that formal curricula in ethics and professionalism remain important in the education of today’s surgeons, it is valuable to remember the impact that the behaviors of those we respect have on us. Perhaps we surgeons more than other physicians are molded by the people who train us, but there is no question that the ethical behaviors of our teachers and mentors will have a greater impact than any lecture or manuscript. I want to acknowledge and commemorate the kindness and ethical behaviors that Dr. Thompson modeled daily for all who were fortunate enough to work with him.
Dr. Angelos is an ACS Fellow; the Linda Kohler Anderson Professor of Surgery and Surgical Ethics; chief, endocrine surgery; and associate director of the MacLean Center for Clinical Medical Ethics at the University of Chicago.
As I sit down to write this column, I reflect on the news that my mentor and friend, Norman W. Thompson, M.D, FACS, passed away yesterday. I had the good fortune to spend 1 year as an endocrine surgery fellow with Dr. Thompson at the University of Michigan in 1995-96. That year was certainly the most significant of my training in terms of defining my professional life as an endocrine surgeon. However, as I think back on my time with Dr. Thompson, I am struck by how much more I learned from him than how to take out a thyroid or a parathyroid or manage multiple endocrine neoplasia.
Dr. Thompson was an excellent technical surgeon, and he would have had a tremendous career helping thousands of patients if that was all that he had done. However, he was much more than an excellent technician. He was also a great doctor. In order for a surgeon to be a great doctor, it is necessary to be technically excellent, but that alone is not sufficient. I believe that what makes a surgeon a great doctor is the combination of technical mastery with outstanding interpersonal skills and ethically sound clinical judgment. Dr. Thompson had all of that, and he was exceptionally kind.
Kindness is not a word that we commonly use in describing surgeons today. In an era of surgeons being pressured to see more patients and generate more RVUs [relative value units], it is unusual to hear kindness mentioned as an essential attribute of a great surgeon. However, Dr. Thompson’s kindness was immediately apparent to all who spent time with him. He treated each patient as a unique individual. In addition, he treated his trainees and his colleagues in Ann Arbor and around the world with respect and incredible humility. He was generous with his time and was always approachable no matter how inexperienced the surgeon asking him a question. Dr. Thompson was kind to all of us and made us feel that he valued spending time with us.
What does kindness have to do with a column that traditionally focuses on ethical issues in the practice of surgery? Although acting with kindness is not the same as acting in an ethical manner, I believe that there is more overlap of the terms than we often imagine. The kind surgeon is the one who treats people – whether they are patients or colleagues – as though they matter. The ethical surgeon respects the patient’s wishes and acts to benefit the patient as much as possible in all circumstances. I am certain that I have met ethical surgeons who were not kind, but I have met very few kind surgeons who are not ethical.
As someone who has spent significant time and energy in the last 19 years as a surgery faculty member trying to teach ethics, I am also struck by a clear truth. Actions always speak louder than words. It may be valuable to talk about the ethical principles that may come to play in a particularly difficult surgical case. Defining the competing interests and assessing the patient’s wishes are important components of the ethical practice of surgery. However, no amount of discussion of these issues can substitute for the value of behavior. Treating patients and colleagues with kindness and respect is modeling the behaviors of an ethical surgeon – perhaps learned from a wise and thoughtful mentor.
Dr. Thompson was an excellent role model for me and so many others in how he treated patients and everyone around him. As I see patients and perform surgery, I still hear myself saying many of the same things that he said many years ago. His genuine expressions of optimism before difficult operations, honesty in communicating, and sadness when things did not go well were tremendous examples to me of how a great doctor treats those around him. These lessons that I learned from Dr. Thompson have influenced my practice significantly, and I am grateful for the opportunity to try to model them on a daily basis.
Although I remain convinced that formal curricula in ethics and professionalism remain important in the education of today’s surgeons, it is valuable to remember the impact that the behaviors of those we respect have on us. Perhaps we surgeons more than other physicians are molded by the people who train us, but there is no question that the ethical behaviors of our teachers and mentors will have a greater impact than any lecture or manuscript. I want to acknowledge and commemorate the kindness and ethical behaviors that Dr. Thompson modeled daily for all who were fortunate enough to work with him.
Dr. Angelos is an ACS Fellow; the Linda Kohler Anderson Professor of Surgery and Surgical Ethics; chief, endocrine surgery; and associate director of the MacLean Center for Clinical Medical Ethics at the University of Chicago.
T-VEC: Advancing the Fight Against Melanoma
Following a phase III, open-label trial conducted by Andtbacka et al (J Clin Oncol. 2015;33:2780-2788), the US Food and Drug Administration recently approved the first oncolytic immunotherapy talimogene laherparepvec (T-VEC) for the treatment of unresectable cutaneous, subcutaneous, and nodal lesions in patients with advanced melanoma (stage IIIB/C–stage IV) following initial surgery.
A group of 436 patients with injectable melanomas (melanomas that are accessible via a percutaneous injection) that were not surgically resectable were randomly assigned (2:1) to treatment with intralesional T-VEC or subcutaneous granulocyte macrophage colony-stimulating factor (GM-CSF). The primary endpoint of the study was durable response rate (DRR), defined as objective response lasting continuously for 6 months or longer. Secondary endpoints included overall survival (OS) and overall response rate.
Talimogene laherparepvec was shown to extend DRRs compared to GM-CSF. Durable response rates were significantly higher with T-VEC (16.3%; 95% confidence interval [CI], 12.1%–20.5%) versus GM-CSF (2.1%; 95% CI, 0%–4.5%)(odds ratio, 8.9; P<.001).
In the OS analysis, a 4.4-month extension with T-VEC was observed; however, this was not deemed to be statistically significant (P=.051). The median OS was 23.3 months (95% CI, 19.5–29.6 months) with T-VEC and 18.9 months (95% CI, 16.0–23.7 months) with GM-CSF (hazard ratio, 0.79; 95% CI, 0.62–1.00; P=.051). Overall response rate also was higher in the T-VEC arm (26.4%; 95% CI, 21.4%–31.5%) versus GM-CSF (5.7%; 95% CI, 1.9%–9.5%).
Talimogene laherparepvec is a herpes simplex virus type 1–derived oncolytic immunotherapy designed to replicate within tumors and produce GM-CSF, which enhances systemic antitumor immune responses and induces tumor lysis.
In this study, T-VEC efficacy was greatest in patients with stage IIIB, IIIC, or IVM1a melanomas and in patients with treatment-naive disease. Differences in DRRs in patients with stage IIIB/C melanomas were 33% in the T-VEC group versus 0% for patients treated with GM-CSF alone. In the stage IVM1a group, DRR was 16% with T-VEC versus 2% with GM-CSF. The difference between both treatments was smaller in more advanced melanomas (IVM1b group, 3% vs 4%; IVM1c, 7% vs 3%). In the first-line treatment, the DRR with T-VEC was 24% versus 0% with GM-CSF. In the second-line and beyond, the DRR with T-VEC was 10% compared to 4% for GM-CSF.
The main adverse events seen in this study were fatigue, chills, and pyrexia. Serious adverse events occurred in 25.7% and 13.4% of participants in the T-VEC and GM-CSF arms, respectively, with disease progression (3.1% vs 1.6%) and cellulitis (2.4% vs 0.8%) being the most common. Six immune-mediated events occurred in the T-VEC group compared to 3 in the GM-CSF group.
Twelve patient deaths occurred within 30 days of the last dose of T-VEC; 9 were associated with progressive disease and the other 3 were associated with myocardial infarction, cardiac arrest, and sepsis, respectively. Four patient deaths were reported in the GM-CSF arm within the same 30 days.
What’s the Issue?
Immunotherapy represents a promising treatment option for metastatic melanoma. These promising results along with the US Food and Drug Administration’s approval of T-VEC will lead to further studies of the uses of T-VEC in combination with other therapies, including a phase I/II study to assess T-VEC in combination with ipilimumab for unresected melanomas (NCT01740297) and a phase III study of T-VEC in combination with pembrolizumab for unresected melanomas (NCT02263508). It is important for dermatologists to be familiar with the new frontier of melanoma treatments. How will these new immunotherapies affect your treatment of melanoma?
Following a phase III, open-label trial conducted by Andtbacka et al (J Clin Oncol. 2015;33:2780-2788), the US Food and Drug Administration recently approved the first oncolytic immunotherapy talimogene laherparepvec (T-VEC) for the treatment of unresectable cutaneous, subcutaneous, and nodal lesions in patients with advanced melanoma (stage IIIB/C–stage IV) following initial surgery.
A group of 436 patients with injectable melanomas (melanomas that are accessible via a percutaneous injection) that were not surgically resectable were randomly assigned (2:1) to treatment with intralesional T-VEC or subcutaneous granulocyte macrophage colony-stimulating factor (GM-CSF). The primary endpoint of the study was durable response rate (DRR), defined as objective response lasting continuously for 6 months or longer. Secondary endpoints included overall survival (OS) and overall response rate.
Talimogene laherparepvec was shown to extend DRRs compared to GM-CSF. Durable response rates were significantly higher with T-VEC (16.3%; 95% confidence interval [CI], 12.1%–20.5%) versus GM-CSF (2.1%; 95% CI, 0%–4.5%)(odds ratio, 8.9; P<.001).
In the OS analysis, a 4.4-month extension with T-VEC was observed; however, this was not deemed to be statistically significant (P=.051). The median OS was 23.3 months (95% CI, 19.5–29.6 months) with T-VEC and 18.9 months (95% CI, 16.0–23.7 months) with GM-CSF (hazard ratio, 0.79; 95% CI, 0.62–1.00; P=.051). Overall response rate also was higher in the T-VEC arm (26.4%; 95% CI, 21.4%–31.5%) versus GM-CSF (5.7%; 95% CI, 1.9%–9.5%).
Talimogene laherparepvec is a herpes simplex virus type 1–derived oncolytic immunotherapy designed to replicate within tumors and produce GM-CSF, which enhances systemic antitumor immune responses and induces tumor lysis.
In this study, T-VEC efficacy was greatest in patients with stage IIIB, IIIC, or IVM1a melanomas and in patients with treatment-naive disease. Differences in DRRs in patients with stage IIIB/C melanomas were 33% in the T-VEC group versus 0% for patients treated with GM-CSF alone. In the stage IVM1a group, DRR was 16% with T-VEC versus 2% with GM-CSF. The difference between both treatments was smaller in more advanced melanomas (IVM1b group, 3% vs 4%; IVM1c, 7% vs 3%). In the first-line treatment, the DRR with T-VEC was 24% versus 0% with GM-CSF. In the second-line and beyond, the DRR with T-VEC was 10% compared to 4% for GM-CSF.
The main adverse events seen in this study were fatigue, chills, and pyrexia. Serious adverse events occurred in 25.7% and 13.4% of participants in the T-VEC and GM-CSF arms, respectively, with disease progression (3.1% vs 1.6%) and cellulitis (2.4% vs 0.8%) being the most common. Six immune-mediated events occurred in the T-VEC group compared to 3 in the GM-CSF group.
Twelve patient deaths occurred within 30 days of the last dose of T-VEC; 9 were associated with progressive disease and the other 3 were associated with myocardial infarction, cardiac arrest, and sepsis, respectively. Four patient deaths were reported in the GM-CSF arm within the same 30 days.
What’s the Issue?
Immunotherapy represents a promising treatment option for metastatic melanoma. These promising results along with the US Food and Drug Administration’s approval of T-VEC will lead to further studies of the uses of T-VEC in combination with other therapies, including a phase I/II study to assess T-VEC in combination with ipilimumab for unresected melanomas (NCT01740297) and a phase III study of T-VEC in combination with pembrolizumab for unresected melanomas (NCT02263508). It is important for dermatologists to be familiar with the new frontier of melanoma treatments. How will these new immunotherapies affect your treatment of melanoma?
Following a phase III, open-label trial conducted by Andtbacka et al (J Clin Oncol. 2015;33:2780-2788), the US Food and Drug Administration recently approved the first oncolytic immunotherapy talimogene laherparepvec (T-VEC) for the treatment of unresectable cutaneous, subcutaneous, and nodal lesions in patients with advanced melanoma (stage IIIB/C–stage IV) following initial surgery.
A group of 436 patients with injectable melanomas (melanomas that are accessible via a percutaneous injection) that were not surgically resectable were randomly assigned (2:1) to treatment with intralesional T-VEC or subcutaneous granulocyte macrophage colony-stimulating factor (GM-CSF). The primary endpoint of the study was durable response rate (DRR), defined as objective response lasting continuously for 6 months or longer. Secondary endpoints included overall survival (OS) and overall response rate.
Talimogene laherparepvec was shown to extend DRRs compared to GM-CSF. Durable response rates were significantly higher with T-VEC (16.3%; 95% confidence interval [CI], 12.1%–20.5%) versus GM-CSF (2.1%; 95% CI, 0%–4.5%)(odds ratio, 8.9; P<.001).
In the OS analysis, a 4.4-month extension with T-VEC was observed; however, this was not deemed to be statistically significant (P=.051). The median OS was 23.3 months (95% CI, 19.5–29.6 months) with T-VEC and 18.9 months (95% CI, 16.0–23.7 months) with GM-CSF (hazard ratio, 0.79; 95% CI, 0.62–1.00; P=.051). Overall response rate also was higher in the T-VEC arm (26.4%; 95% CI, 21.4%–31.5%) versus GM-CSF (5.7%; 95% CI, 1.9%–9.5%).
Talimogene laherparepvec is a herpes simplex virus type 1–derived oncolytic immunotherapy designed to replicate within tumors and produce GM-CSF, which enhances systemic antitumor immune responses and induces tumor lysis.
In this study, T-VEC efficacy was greatest in patients with stage IIIB, IIIC, or IVM1a melanomas and in patients with treatment-naive disease. Differences in DRRs in patients with stage IIIB/C melanomas were 33% in the T-VEC group versus 0% for patients treated with GM-CSF alone. In the stage IVM1a group, DRR was 16% with T-VEC versus 2% with GM-CSF. The difference between both treatments was smaller in more advanced melanomas (IVM1b group, 3% vs 4%; IVM1c, 7% vs 3%). In the first-line treatment, the DRR with T-VEC was 24% versus 0% with GM-CSF. In the second-line and beyond, the DRR with T-VEC was 10% compared to 4% for GM-CSF.
The main adverse events seen in this study were fatigue, chills, and pyrexia. Serious adverse events occurred in 25.7% and 13.4% of participants in the T-VEC and GM-CSF arms, respectively, with disease progression (3.1% vs 1.6%) and cellulitis (2.4% vs 0.8%) being the most common. Six immune-mediated events occurred in the T-VEC group compared to 3 in the GM-CSF group.
Twelve patient deaths occurred within 30 days of the last dose of T-VEC; 9 were associated with progressive disease and the other 3 were associated with myocardial infarction, cardiac arrest, and sepsis, respectively. Four patient deaths were reported in the GM-CSF arm within the same 30 days.
What’s the Issue?
Immunotherapy represents a promising treatment option for metastatic melanoma. These promising results along with the US Food and Drug Administration’s approval of T-VEC will lead to further studies of the uses of T-VEC in combination with other therapies, including a phase I/II study to assess T-VEC in combination with ipilimumab for unresected melanomas (NCT01740297) and a phase III study of T-VEC in combination with pembrolizumab for unresected melanomas (NCT02263508). It is important for dermatologists to be familiar with the new frontier of melanoma treatments. How will these new immunotherapies affect your treatment of melanoma?
Video etiquette
FaceTime with my mother would be better described as ForeheadTime. She loves to use video for our Sunday calls, yet when she does, she always talks into her iPhone as if it’s a speakerphone. As a result, all I see is the top of her head. “Mom. Lower the phone. Mom, I can’t see you,” I must repeat weekly.
Video provides a richer experience compared with telephone. It allows for a deeper, emotional connection. That’s why moms like mine prefer it to telephone conversations. In medicine, video visits are uncommon, but that’s changing as payers are now reimbursing and patients are demanding the service. For many, they offer a far more convenient and still effective method to receive medical care. Psychiatry is an obvious example. Less obvious, but still effective examples, include endocrinology, pediatrics, primary care, surgery (post operatively), and dermatology.
Like the example with my mom, quality of the experience matters, and issues often arise not from the technology, but from the technique. Making eye contact is more difficult on video, and not looking patients in the eye can harm doctor-patient bonding. Here are a few basic tips when using video with your patients:
• Be sure the light source is in front of you. Having windows behind you often puts you in shadow.
• The best place for the camera is at the top of your screen. It’s nearly impossible to look into the camera and see the patient if the camera is next to the screen instead of above.
• Remember, to look directly at the patient, you have to look into the camera. This is tricky and easy to forget.
• Be sure your entire head and upper torso are in the frame. Talking heads can be intimidating.
• When possible, use a headset with a microphone. Headsets help both you and your patient hear better and give the patient an increased sense of privacy.
• Generally speaking, video visits take as long or longer than in-person visits. Remember to be patient as some of your patients may experience technical difficulties. Our IT colleagues have a word for it: “picnic,” which stands for “Problem In Chair Not In Computer.” You should also train your staff to aid you and the patients. For instance, if a patient is struggling with the computer, you might have your assistant help him or her while you move on to the next patient.
• Although the patient can be home, it is best for you to be in your office. It’s possible to do video consults from home, but it is more difficult because you have to ensure that both your technology and your environment are secure and private. Otherwise, you risk violating HIPAA or other compliance requirements.
• Be sure to get the appropriate consent before conducting a virtual visit. In California, it requires only verbal consent, but your state’s requirements might be different.
• As for your appearance, there’s a reason why Kennedy won the Kennedy-Nixon debates. Video does reveal details that you might not want emphasized. A two-day beard might appear hip in person but unkempt and uncaring online. Bold stripes or checks on your shirt sometimes appear distorted, so opt for solids in soft shades. Scrubs are okay, but be sure to check your neckline, particularly as you move about. Whether it’s clothing or accessories, avoid anything overly distracting.
Video visits have had a long, slow ramp-up, but they seem to be gaining momentum. You may not use them in your practice now, but it’s likely we all will someday. Soon.
Dr. Benabio is a partner physician in the department of dermatology of the Southern California Permanente Group in San Diego, and a volunteer clinical assistant professor at the University of California, San Diego. He is @dermdoc on Twitter.
FaceTime with my mother would be better described as ForeheadTime. She loves to use video for our Sunday calls, yet when she does, she always talks into her iPhone as if it’s a speakerphone. As a result, all I see is the top of her head. “Mom. Lower the phone. Mom, I can’t see you,” I must repeat weekly.
Video provides a richer experience compared with telephone. It allows for a deeper, emotional connection. That’s why moms like mine prefer it to telephone conversations. In medicine, video visits are uncommon, but that’s changing as payers are now reimbursing and patients are demanding the service. For many, they offer a far more convenient and still effective method to receive medical care. Psychiatry is an obvious example. Less obvious, but still effective examples, include endocrinology, pediatrics, primary care, surgery (post operatively), and dermatology.
Like the example with my mom, quality of the experience matters, and issues often arise not from the technology, but from the technique. Making eye contact is more difficult on video, and not looking patients in the eye can harm doctor-patient bonding. Here are a few basic tips when using video with your patients:
• Be sure the light source is in front of you. Having windows behind you often puts you in shadow.
• The best place for the camera is at the top of your screen. It’s nearly impossible to look into the camera and see the patient if the camera is next to the screen instead of above.
• Remember, to look directly at the patient, you have to look into the camera. This is tricky and easy to forget.
• Be sure your entire head and upper torso are in the frame. Talking heads can be intimidating.
• When possible, use a headset with a microphone. Headsets help both you and your patient hear better and give the patient an increased sense of privacy.
• Generally speaking, video visits take as long or longer than in-person visits. Remember to be patient as some of your patients may experience technical difficulties. Our IT colleagues have a word for it: “picnic,” which stands for “Problem In Chair Not In Computer.” You should also train your staff to aid you and the patients. For instance, if a patient is struggling with the computer, you might have your assistant help him or her while you move on to the next patient.
• Although the patient can be home, it is best for you to be in your office. It’s possible to do video consults from home, but it is more difficult because you have to ensure that both your technology and your environment are secure and private. Otherwise, you risk violating HIPAA or other compliance requirements.
• Be sure to get the appropriate consent before conducting a virtual visit. In California, it requires only verbal consent, but your state’s requirements might be different.
• As for your appearance, there’s a reason why Kennedy won the Kennedy-Nixon debates. Video does reveal details that you might not want emphasized. A two-day beard might appear hip in person but unkempt and uncaring online. Bold stripes or checks on your shirt sometimes appear distorted, so opt for solids in soft shades. Scrubs are okay, but be sure to check your neckline, particularly as you move about. Whether it’s clothing or accessories, avoid anything overly distracting.
Video visits have had a long, slow ramp-up, but they seem to be gaining momentum. You may not use them in your practice now, but it’s likely we all will someday. Soon.
Dr. Benabio is a partner physician in the department of dermatology of the Southern California Permanente Group in San Diego, and a volunteer clinical assistant professor at the University of California, San Diego. He is @dermdoc on Twitter.
FaceTime with my mother would be better described as ForeheadTime. She loves to use video for our Sunday calls, yet when she does, she always talks into her iPhone as if it’s a speakerphone. As a result, all I see is the top of her head. “Mom. Lower the phone. Mom, I can’t see you,” I must repeat weekly.
Video provides a richer experience compared with telephone. It allows for a deeper, emotional connection. That’s why moms like mine prefer it to telephone conversations. In medicine, video visits are uncommon, but that’s changing as payers are now reimbursing and patients are demanding the service. For many, they offer a far more convenient and still effective method to receive medical care. Psychiatry is an obvious example. Less obvious, but still effective examples, include endocrinology, pediatrics, primary care, surgery (post operatively), and dermatology.
Like the example with my mom, quality of the experience matters, and issues often arise not from the technology, but from the technique. Making eye contact is more difficult on video, and not looking patients in the eye can harm doctor-patient bonding. Here are a few basic tips when using video with your patients:
• Be sure the light source is in front of you. Having windows behind you often puts you in shadow.
• The best place for the camera is at the top of your screen. It’s nearly impossible to look into the camera and see the patient if the camera is next to the screen instead of above.
• Remember, to look directly at the patient, you have to look into the camera. This is tricky and easy to forget.
• Be sure your entire head and upper torso are in the frame. Talking heads can be intimidating.
• When possible, use a headset with a microphone. Headsets help both you and your patient hear better and give the patient an increased sense of privacy.
• Generally speaking, video visits take as long or longer than in-person visits. Remember to be patient as some of your patients may experience technical difficulties. Our IT colleagues have a word for it: “picnic,” which stands for “Problem In Chair Not In Computer.” You should also train your staff to aid you and the patients. For instance, if a patient is struggling with the computer, you might have your assistant help him or her while you move on to the next patient.
• Although the patient can be home, it is best for you to be in your office. It’s possible to do video consults from home, but it is more difficult because you have to ensure that both your technology and your environment are secure and private. Otherwise, you risk violating HIPAA or other compliance requirements.
• Be sure to get the appropriate consent before conducting a virtual visit. In California, it requires only verbal consent, but your state’s requirements might be different.
• As for your appearance, there’s a reason why Kennedy won the Kennedy-Nixon debates. Video does reveal details that you might not want emphasized. A two-day beard might appear hip in person but unkempt and uncaring online. Bold stripes or checks on your shirt sometimes appear distorted, so opt for solids in soft shades. Scrubs are okay, but be sure to check your neckline, particularly as you move about. Whether it’s clothing or accessories, avoid anything overly distracting.
Video visits have had a long, slow ramp-up, but they seem to be gaining momentum. You may not use them in your practice now, but it’s likely we all will someday. Soon.
Dr. Benabio is a partner physician in the department of dermatology of the Southern California Permanente Group in San Diego, and a volunteer clinical assistant professor at the University of California, San Diego. He is @dermdoc on Twitter.
Neurosurgery at the End of Life
The juxtaposition between my first 2 days of neurosurgery could not have been more profound. On my first day as a third-year medical student, the attending and chief resident let me take the lead on the first case: a straightforward brain biopsy. I got to make the incision, drill the burr hole, and perform the needle biopsy. I still remember the thrill of the technical challenge, the controlled violence of drilling into the skull, and the finesse of accessing the tumor core.
The buzz was so strong that I barely registered the diagnosis that was called back from the pathologist: glioblastoma. It was not until I saw the face of the disease the next morning that I understood the reality of a GBM diagnosis. That face belonged to a 47-year-old man who hadn’t slept all night, wide eyed with apprehension at what news I might bring. He beseeched me with questions, and though his aphasia left him stammering to get the words out, I knew exactly what he was asking: Would he live or die? It was a question I was in no position to answer. Instead, I reassured him that we were waiting on the final pathology, all the while trying to forget the fact that the frozen section suggested an aggressive subtype, surely heralding a poor prognosis.
In his poignant memoir, “Do No Harm: Stories of Life, Death and Brain Surgery” (New York: Thomas Dunne Book, 2015), Dr. Henry Marsh writes beautifully about how difficult it can be to find the balance between optimism and realism. In one memorable passage, Dr. Marsh shows a house officer a scan of a highly malignant brain tumor and asks him what he would say to the patient. The trainee reflexively hides behind jargon, skirting around what he knew to be the truth: This tumor would kill her. Marsh presses him to admit that he’s lying, before lamenting at how hard it is to improve these critical communication skills: “When I have had to break bad news I never know whether I have done it well or not. The patients aren’t going to ring me up afterward and say, ‘Mr. Marsh, I really liked the way you told me that I was going to die,’ or ‘Mr. Marsh, you were crap.’ You can only hope that you haven’t made too much of a mess of it.”
I could certainly relate to Dr. Marsh’s house officer as I walked away from my own patient. I felt almost deceitful withholding diagnostic information from him, even if I did the “right” thing. It made me wonder, why did I want to become a neurosurgeon? Surely to help people through some of the most difficult moments of their lives. But is it possible to be a source of comfort when you are required so often to be a harbinger of death? The answer depends on whether one can envision a role for the neurosurgeon beyond the mandate of “life at all costs.”
While the field has become known for its life-saving procedures, neurosurgeons are called just as often to preside over the end of their patient’s lives – work that requires just as much skill as any technical procedure. Dr. Marsh recognized the tremendous human cost of neglecting that work. For cases that appear “hopeless,” he writes, “We often end up operating because it’s easier than being honest, and it means that we can avoid a painful conversation.”
We are only beginning to understand the many issues that neurosurgical patients face at the end of life, but so far it is clear that neurosurgical trainees require substantive training in prognostication, communication, and palliation (Crit Care Med. 2015 Sep;43[9]:1964-77 1,2; J Neurooncol. 2009 Jan;91[1]:39-43). Is there room in the current training paradigm for more formal education in these domains? As we move further into the 21st century, we must embrace the need for masterful clinicians outside of the operating room if we are to ever challenge the axiom set forth by the renowned French surgeon, René Leriche, some 65 years ago: “Every surgeon carries within himself a small cemetery, where from time to time he goes to pray – a place of bitterness and regret, where he must look for an explanation for his failures.” Let us look forward to the day when this is no longer the case.
Stephen Miranda is a medical student from the University of Rochester, who is now working as a research fellow at Ariadne Labs, a joint center for health systems innovation at Brigham & Women’s Hospital and Harvard T.H. Chan School of Public Health, both in Boston.
The juxtaposition between my first 2 days of neurosurgery could not have been more profound. On my first day as a third-year medical student, the attending and chief resident let me take the lead on the first case: a straightforward brain biopsy. I got to make the incision, drill the burr hole, and perform the needle biopsy. I still remember the thrill of the technical challenge, the controlled violence of drilling into the skull, and the finesse of accessing the tumor core.
The buzz was so strong that I barely registered the diagnosis that was called back from the pathologist: glioblastoma. It was not until I saw the face of the disease the next morning that I understood the reality of a GBM diagnosis. That face belonged to a 47-year-old man who hadn’t slept all night, wide eyed with apprehension at what news I might bring. He beseeched me with questions, and though his aphasia left him stammering to get the words out, I knew exactly what he was asking: Would he live or die? It was a question I was in no position to answer. Instead, I reassured him that we were waiting on the final pathology, all the while trying to forget the fact that the frozen section suggested an aggressive subtype, surely heralding a poor prognosis.
In his poignant memoir, “Do No Harm: Stories of Life, Death and Brain Surgery” (New York: Thomas Dunne Book, 2015), Dr. Henry Marsh writes beautifully about how difficult it can be to find the balance between optimism and realism. In one memorable passage, Dr. Marsh shows a house officer a scan of a highly malignant brain tumor and asks him what he would say to the patient. The trainee reflexively hides behind jargon, skirting around what he knew to be the truth: This tumor would kill her. Marsh presses him to admit that he’s lying, before lamenting at how hard it is to improve these critical communication skills: “When I have had to break bad news I never know whether I have done it well or not. The patients aren’t going to ring me up afterward and say, ‘Mr. Marsh, I really liked the way you told me that I was going to die,’ or ‘Mr. Marsh, you were crap.’ You can only hope that you haven’t made too much of a mess of it.”
I could certainly relate to Dr. Marsh’s house officer as I walked away from my own patient. I felt almost deceitful withholding diagnostic information from him, even if I did the “right” thing. It made me wonder, why did I want to become a neurosurgeon? Surely to help people through some of the most difficult moments of their lives. But is it possible to be a source of comfort when you are required so often to be a harbinger of death? The answer depends on whether one can envision a role for the neurosurgeon beyond the mandate of “life at all costs.”
While the field has become known for its life-saving procedures, neurosurgeons are called just as often to preside over the end of their patient’s lives – work that requires just as much skill as any technical procedure. Dr. Marsh recognized the tremendous human cost of neglecting that work. For cases that appear “hopeless,” he writes, “We often end up operating because it’s easier than being honest, and it means that we can avoid a painful conversation.”
We are only beginning to understand the many issues that neurosurgical patients face at the end of life, but so far it is clear that neurosurgical trainees require substantive training in prognostication, communication, and palliation (Crit Care Med. 2015 Sep;43[9]:1964-77 1,2; J Neurooncol. 2009 Jan;91[1]:39-43). Is there room in the current training paradigm for more formal education in these domains? As we move further into the 21st century, we must embrace the need for masterful clinicians outside of the operating room if we are to ever challenge the axiom set forth by the renowned French surgeon, René Leriche, some 65 years ago: “Every surgeon carries within himself a small cemetery, where from time to time he goes to pray – a place of bitterness and regret, where he must look for an explanation for his failures.” Let us look forward to the day when this is no longer the case.
Stephen Miranda is a medical student from the University of Rochester, who is now working as a research fellow at Ariadne Labs, a joint center for health systems innovation at Brigham & Women’s Hospital and Harvard T.H. Chan School of Public Health, both in Boston.
The juxtaposition between my first 2 days of neurosurgery could not have been more profound. On my first day as a third-year medical student, the attending and chief resident let me take the lead on the first case: a straightforward brain biopsy. I got to make the incision, drill the burr hole, and perform the needle biopsy. I still remember the thrill of the technical challenge, the controlled violence of drilling into the skull, and the finesse of accessing the tumor core.
The buzz was so strong that I barely registered the diagnosis that was called back from the pathologist: glioblastoma. It was not until I saw the face of the disease the next morning that I understood the reality of a GBM diagnosis. That face belonged to a 47-year-old man who hadn’t slept all night, wide eyed with apprehension at what news I might bring. He beseeched me with questions, and though his aphasia left him stammering to get the words out, I knew exactly what he was asking: Would he live or die? It was a question I was in no position to answer. Instead, I reassured him that we were waiting on the final pathology, all the while trying to forget the fact that the frozen section suggested an aggressive subtype, surely heralding a poor prognosis.
In his poignant memoir, “Do No Harm: Stories of Life, Death and Brain Surgery” (New York: Thomas Dunne Book, 2015), Dr. Henry Marsh writes beautifully about how difficult it can be to find the balance between optimism and realism. In one memorable passage, Dr. Marsh shows a house officer a scan of a highly malignant brain tumor and asks him what he would say to the patient. The trainee reflexively hides behind jargon, skirting around what he knew to be the truth: This tumor would kill her. Marsh presses him to admit that he’s lying, before lamenting at how hard it is to improve these critical communication skills: “When I have had to break bad news I never know whether I have done it well or not. The patients aren’t going to ring me up afterward and say, ‘Mr. Marsh, I really liked the way you told me that I was going to die,’ or ‘Mr. Marsh, you were crap.’ You can only hope that you haven’t made too much of a mess of it.”
I could certainly relate to Dr. Marsh’s house officer as I walked away from my own patient. I felt almost deceitful withholding diagnostic information from him, even if I did the “right” thing. It made me wonder, why did I want to become a neurosurgeon? Surely to help people through some of the most difficult moments of their lives. But is it possible to be a source of comfort when you are required so often to be a harbinger of death? The answer depends on whether one can envision a role for the neurosurgeon beyond the mandate of “life at all costs.”
While the field has become known for its life-saving procedures, neurosurgeons are called just as often to preside over the end of their patient’s lives – work that requires just as much skill as any technical procedure. Dr. Marsh recognized the tremendous human cost of neglecting that work. For cases that appear “hopeless,” he writes, “We often end up operating because it’s easier than being honest, and it means that we can avoid a painful conversation.”
We are only beginning to understand the many issues that neurosurgical patients face at the end of life, but so far it is clear that neurosurgical trainees require substantive training in prognostication, communication, and palliation (Crit Care Med. 2015 Sep;43[9]:1964-77 1,2; J Neurooncol. 2009 Jan;91[1]:39-43). Is there room in the current training paradigm for more formal education in these domains? As we move further into the 21st century, we must embrace the need for masterful clinicians outside of the operating room if we are to ever challenge the axiom set forth by the renowned French surgeon, René Leriche, some 65 years ago: “Every surgeon carries within himself a small cemetery, where from time to time he goes to pray – a place of bitterness and regret, where he must look for an explanation for his failures.” Let us look forward to the day when this is no longer the case.
Stephen Miranda is a medical student from the University of Rochester, who is now working as a research fellow at Ariadne Labs, a joint center for health systems innovation at Brigham & Women’s Hospital and Harvard T.H. Chan School of Public Health, both in Boston.
