Patients with branch duct intraductal papillary mucinous neoplasms were about 19 times more likely to develop malignancies over 5 years compared with the general population, although they lacked worrisome features of malignancy at baseline.

The overall risk of malignancy in this cohort approached 8% and persisted for 10 years or more, said Ilaria Pergolini, MD, of Massachusetts General Hospital, Boston, and her associates. The findings support surveillance of this population past 5 years, although cysts that remain 1.5 cm or smaller for more than 5 years might be regarded as unlikely to become malignant, they wrote. The report appears in the November issue of Gastroenterology (doi: 10.1053/j.gastro.2017.07.019).

Few studies have explored branch duct intraductal papillary mucinous neoplasms (BD-IPMNs), which the researchers defined as unilocular or multilocular pancreatic cysts with a nondilated main pancreatic duct (smaller than 5 mm). To begin filling this gap, they retrospectively studied 577 patients with suspected or presumed BD-IPMNs followed at Massachusetts General Hospital. Patients underwent cross-sectional imaging 3 months or more after initial diagnosis at least once thereafter. Standardized incidence ratios were calculated based on population-level data for the United States from the National Cancer Institute’s Surveillance, Epidemiology, and End Results (SEER) program.

Patients tended to be in their mid-60s at diagnosis (range, 21-90 years) and 59% were female, said the researchers. Median follow-up time was 82 months and ranged between 6 and 329 months, but 63% of patients were followed for at least 5 years (median, 107 months), and about one in five were followed for more than a decade. Fully 83% of patients were asymptomatic at initial diagnosis, of which 10% subsequently became symptomatic. Most patients underwent diagnostic CT, but nearly half underwent MRI/MRCP and about a third underwent endoscopic ultrasound. At diagnosis, median cyst size was 14 mm (range, 2-54 mm) and 9% of patients had cysts measuring at least 3 cm. By the end of follow-up, 55% had larger cysts than at baseline, and cysts grew by a median of 0.9 mm per year.

At diagnosis, only 1% of patients had high-risk stigmata while 12% had worrisome features such as acute pancreatitis, cysts measuring at least 3 cm, thickened or enhancing cyst walls, nonenhancing mural nodules, main pancreatic duct size of 5-9 mm, an abrupt change in caliber of the main pancreatic duct, and lymphadenopathy. During follow-up, another 13% of patients developed new worrisome features and 9% developed high-risk stigmata, while 2% experienced regression of a nodule. In all, 36% of patients had cysts with either worrisome features, high-risk stigmata, or both at some point during the study.

Among 363 patients followed for at least 5 years, 20 (5.5%) were diagnosed with high-risk dysplasia or invasive neoplasms and 4.4% developed invasive cancer, for a standardized incidence ratio of 18.8 (95% confidence interval, 9.7-32.8; P less than .001). Among 108 patients who had cysts measuring 1.5 cm or less, only one individual developed a distinct ductal adenocarcinoma during 5 or more years of follow-up. But of 255 patients with larger cysts, the 5-year rate of malignancy was 7.5% (P = .01).

“The absence of worrisome features or high-risk stigmata at a 5-year time point does not exclude the development of pancreatic malignancy, and the risk in these patients is 18.8 times higher than that of the general population,” the researchers concluded. “Because of this, we strongly support continued surveillance after 5 years from the initial diagnosis.” Cysts that remain 1.5 cm or smaller for at least 5 years are probably low risk, they said. “This is an important issue for further investigation, since it may help reduce costs related to surveillance and improve patients’ quality of life.”

The investigators did not disclose external funding sources. They reported having no conflicts of interest.

Patients with branch duct intraductal papillary mucinous neoplasms were about 19 times more likely to develop malignancies over 5 years compared with the general population, although they lacked worrisome features of malignancy at baseline.

The overall risk of malignancy in this cohort approached 8% and persisted for 10 years or more, said Ilaria Pergolini, MD, of Massachusetts General Hospital, Boston, and her associates. The findings support surveillance of this population past 5 years, although cysts that remain 1.5 cm or smaller for more than 5 years might be regarded as unlikely to become malignant, they wrote. The report appears in the November issue of Gastroenterology (doi: 10.1053/j.gastro.2017.07.019).

Few studies have explored branch duct intraductal papillary mucinous neoplasms (BD-IPMNs), which the researchers defined as unilocular or multilocular pancreatic cysts with a nondilated main pancreatic duct (smaller than 5 mm). To begin filling this gap, they retrospectively studied 577 patients with suspected or presumed BD-IPMNs followed at Massachusetts General Hospital. Patients underwent cross-sectional imaging 3 months or more after initial diagnosis at least once thereafter. Standardized incidence ratios were calculated based on population-level data for the United States from the National Cancer Institute’s Surveillance, Epidemiology, and End Results (SEER) program.

Patients tended to be in their mid-60s at diagnosis (range, 21-90 years) and 59% were female, said the researchers. Median follow-up time was 82 months and ranged between 6 and 329 months, but 63% of patients were followed for at least 5 years (median, 107 months), and about one in five were followed for more than a decade. Fully 83% of patients were asymptomatic at initial diagnosis, of which 10% subsequently became symptomatic. Most patients underwent diagnostic CT, but nearly half underwent MRI/MRCP and about a third underwent endoscopic ultrasound. At diagnosis, median cyst size was 14 mm (range, 2-54 mm) and 9% of patients had cysts measuring at least 3 cm. By the end of follow-up, 55% had larger cysts than at baseline, and cysts grew by a median of 0.9 mm per year.

At diagnosis, only 1% of patients had high-risk stigmata while 12% had worrisome features such as acute pancreatitis, cysts measuring at least 3 cm, thickened or enhancing cyst walls, nonenhancing mural nodules, main pancreatic duct size of 5-9 mm, an abrupt change in caliber of the main pancreatic duct, and lymphadenopathy. During follow-up, another 13% of patients developed new worrisome features and 9% developed high-risk stigmata, while 2% experienced regression of a nodule. In all, 36% of patients had cysts with either worrisome features, high-risk stigmata, or both at some point during the study.

Among 363 patients followed for at least 5 years, 20 (5.5%) were diagnosed with high-risk dysplasia or invasive neoplasms and 4.4% developed invasive cancer, for a standardized incidence ratio of 18.8 (95% confidence interval, 9.7-32.8; P less than .001). Among 108 patients who had cysts measuring 1.5 cm or less, only one individual developed a distinct ductal adenocarcinoma during 5 or more years of follow-up. But of 255 patients with larger cysts, the 5-year rate of malignancy was 7.5% (P = .01).

“The absence of worrisome features or high-risk stigmata at a 5-year time point does not exclude the development of pancreatic malignancy, and the risk in these patients is 18.8 times higher than that of the general population,” the researchers concluded. “Because of this, we strongly support continued surveillance after 5 years from the initial diagnosis.” Cysts that remain 1.5 cm or smaller for at least 5 years are probably low risk, they said. “This is an important issue for further investigation, since it may help reduce costs related to surveillance and improve patients’ quality of life.”

The investigators did not disclose external funding sources. They reported having no conflicts of interest.

Patients with branch duct intraductal papillary mucinous neoplasms were about 19 times more likely to develop malignancies over 5 years compared with the general population, although they lacked worrisome features of malignancy at baseline.

The overall risk of malignancy in this cohort approached 8% and persisted for 10 years or more, said Ilaria Pergolini, MD, of Massachusetts General Hospital, Boston, and her associates. The findings support surveillance of this population past 5 years, although cysts that remain 1.5 cm or smaller for more than 5 years might be regarded as unlikely to become malignant, they wrote. The report appears in the November issue of Gastroenterology (doi: 10.1053/j.gastro.2017.07.019).

Few studies have explored branch duct intraductal papillary mucinous neoplasms (BD-IPMNs), which the researchers defined as unilocular or multilocular pancreatic cysts with a nondilated main pancreatic duct (smaller than 5 mm). To begin filling this gap, they retrospectively studied 577 patients with suspected or presumed BD-IPMNs followed at Massachusetts General Hospital. Patients underwent cross-sectional imaging 3 months or more after initial diagnosis at least once thereafter. Standardized incidence ratios were calculated based on population-level data for the United States from the National Cancer Institute’s Surveillance, Epidemiology, and End Results (SEER) program.

Patients tended to be in their mid-60s at diagnosis (range, 21-90 years) and 59% were female, said the researchers. Median follow-up time was 82 months and ranged between 6 and 329 months, but 63% of patients were followed for at least 5 years (median, 107 months), and about one in five were followed for more than a decade. Fully 83% of patients were asymptomatic at initial diagnosis, of which 10% subsequently became symptomatic. Most patients underwent diagnostic CT, but nearly half underwent MRI/MRCP and about a third underwent endoscopic ultrasound. At diagnosis, median cyst size was 14 mm (range, 2-54 mm) and 9% of patients had cysts measuring at least 3 cm. By the end of follow-up, 55% had larger cysts than at baseline, and cysts grew by a median of 0.9 mm per year.

At diagnosis, only 1% of patients had high-risk stigmata while 12% had worrisome features such as acute pancreatitis, cysts measuring at least 3 cm, thickened or enhancing cyst walls, nonenhancing mural nodules, main pancreatic duct size of 5-9 mm, an abrupt change in caliber of the main pancreatic duct, and lymphadenopathy. During follow-up, another 13% of patients developed new worrisome features and 9% developed high-risk stigmata, while 2% experienced regression of a nodule. In all, 36% of patients had cysts with either worrisome features, high-risk stigmata, or both at some point during the study.

Among 363 patients followed for at least 5 years, 20 (5.5%) were diagnosed with high-risk dysplasia or invasive neoplasms and 4.4% developed invasive cancer, for a standardized incidence ratio of 18.8 (95% confidence interval, 9.7-32.8; P less than .001). Among 108 patients who had cysts measuring 1.5 cm or less, only one individual developed a distinct ductal adenocarcinoma during 5 or more years of follow-up. But of 255 patients with larger cysts, the 5-year rate of malignancy was 7.5% (P = .01).

“The absence of worrisome features or high-risk stigmata at a 5-year time point does not exclude the development of pancreatic malignancy, and the risk in these patients is 18.8 times higher than that of the general population,” the researchers concluded. “Because of this, we strongly support continued surveillance after 5 years from the initial diagnosis.” Cysts that remain 1.5 cm or smaller for at least 5 years are probably low risk, they said. “This is an important issue for further investigation, since it may help reduce costs related to surveillance and improve patients’ quality of life.”

The investigators did not disclose external funding sources. They reported having no conflicts of interest.

Measuring hospital-acquired infection in a new way

Every day, hospitalists struggle with health care–associated infections, which 1 in 25 patients experiences, according to the Centers for Disease Control and Prevention.

These infections are often discussed in terms of the standardized infection ratio (SIR), but that measure may not assess overall performance, according to a study suggesting a new measure that could help large hospital systems better evaluate their infection outcomes by comparing them with those of their peers.

References

1. Centers for Disease Control and Prevention. Healthcare-associated infections. https://www.cdc.gov/hai/surveillance/. Accessed April 10, 2017.

2. Fakih MG, Skierczynski B, Bufalino A, et al. Taking advantage of public reporting: An infection composite score to assist evaluating hospital performance for infection prevention efforts. American Journal of Infection Control. (2016);44(12):1578-81.

Hospitalists lead in palliative care

According to a recent report, hospitalists made nearly half (48%) of all palliative care referrals in hospitals in 2015. The report comes from the Center to Advance Palliative Care and the National Palliative Care Research Center.

“The most important finding from this analysis is the near doubling of the number of people receiving palliative care services in U.S. hospital palliative care programs, from an average of 2.7% in 2009 to an average of 4.8% in 2015,” said Diane Meier, MD, director of the Center to Advance Palliative Care. “This suggests increasing recognition of the benefits of palliative care by health professionals and greater likelihood that those living with serious illness will receive state-of-the-art care.”

The report shows that hospitalists are the No. 1 source of referral to palliative care teams. “They see up close the suffering of their patients and families, their need for comprehensive whole-person care, and the beneficial impact of the added layer of support that palliative care provides,” she said.

“Hospitalists should work alongside their palliative care colleagues to develop standardized screening tools so that all patients and families who could benefit have access to the best quality of care during serious and complex illness,” Dr. Meier said. Hospitalists can also gain skills in communicating about prognosis and conducting family meetings, as well as safe and effective symptom management, through the online clinical training curriculum available at capc.org.
 

Reference

1. National Palliative Care Registry. How We Work: Trends and Insights in Hospital Palliative Care. https://registry.capc.org/wp-content/uploads/2017/02/How-We-Work-Trends-and-Insights-in-Hospital-Palliative-Care-2009-2015.pdf. Accessed April 7, 2017.

Improving outcomes for children with chronic conditions

Cincinnati Children’s Hospital Medical Center improved outcomes for 50% of pediatric patients by redesigning the way it cares for children with active chronic conditions, according to a new study.

The hospital implemented a Condition Outcomes Improvement Initiative, in which specialized clinical teams applied quality improvement principles to improve outcomes for pediatric patients with chronic illnesses.

Each improvement team focused on a specific chronic condition, such as juvenile arthritis, asthma, chronic kidney disease, or sickle cell disease. The improvement processes implemented included reviewing evidence to choose which outcomes to measure, developing condition-specific patient registries and data collection tools, classifying patients into defined risk groups, planning care before and after visits, and providing self-management and caregiver/parent support for patients and their families.

Study lead author Jennifer Lail, MD, FAAP, analyzed data from more than 27,000 pediatric patients from 18 improvement teams. Following implementation of the changes, half of patients had an improved outcome, and 11 of the 18 chronic condition teams achieved the goal of 20% improvement in their chosen clinical outcome, suggesting that clinical teams implementing quality improvement methods with multidisciplinary support can improve outcomes for populations with chronic conditions.
 

Reference

1. Lail J, et al. Applying the Chronic Care Model to Improve Care and Outcomes at a Pediatric Medical Center. Joint Commission Journal on Quality and Patient Safety. 2017;43(3):101-112.

FDA approves two new antibiotic tests

Hospitalists have two new FDA-approved tools available to help them make antibiotic treatment decisions.

The first is the expanded use of the Vidas Brahms PCT Assay, intended to be used in the hospital or emergency room. The test uses – for the first time – procalcitonin (PCT), a protein associated with the body’s response to a bacterial infection, as a biomarker that can help hospitalists make antibiotic management decisions in patients with those conditions. The results can help them determine if antibiotic treatment should be started or stopped in patients with lower respiratory tract infections (such as community-acquired pneumonia) and stopped in patients with sepsis.

The FDA has also allowed marketing of the PhenoTest BC Kit. This one is another first, the first test to identify organisms causing bloodstream infections and provide information about the antibiotics to which the organism is likely to respond.

The test can identify bacteria or yeast from a positive blood culture in approximately 1.5 hours (compared with traditional identification and antibiotic susceptibility tests, which can take one to two days). The test can identify 14 different species of bacteria and two species of yeast that cause bloodstream infections. It also provides antibiotic sensitivity information on 18 antibiotics. In addition, the test will identify the presence of two indicators of antibiotic resistance.
 

Quick byte

About a third of adverse events during hospitalizations involve a drug-related harm, resulting in longer hospital stays and increased costs, according to the New York Times. “The Institute of Medicine estimated that there are 400,000 preventable adverse drug events in hospitals each year, costing $3.5 billion. One-fifth of patients discharged from the hospital have a drug-related complication after returning home, many of which are preventable.”

Reference

1 Frakt A. How Many Pills Are Too Many? The New York Times. 2017 Apr 10. https://www.nytimes.com/2017/04/10/upshot/how-many-pills-are-too-many.html?rref=collection%2Fsectioncollection%2Fhealth&action=click&contentCollection=health&region=stream&module=stream_unit&version=latest&contentPlacement=6&pgtype=sectionfront&_r=0. Accessed April 9, 2017.

Measuring hospital-acquired infection in a new way

Every day, hospitalists struggle with health care–associated infections, which 1 in 25 patients experiences, according to the Centers for Disease Control and Prevention.

These infections are often discussed in terms of the standardized infection ratio (SIR), but that measure may not assess overall performance, according to a study suggesting a new measure that could help large hospital systems better evaluate their infection outcomes by comparing them with those of their peers.

References

1. Centers for Disease Control and Prevention. Healthcare-associated infections. https://www.cdc.gov/hai/surveillance/. Accessed April 10, 2017.

2. Fakih MG, Skierczynski B, Bufalino A, et al. Taking advantage of public reporting: An infection composite score to assist evaluating hospital performance for infection prevention efforts. American Journal of Infection Control. (2016);44(12):1578-81.

Hospitalists lead in palliative care

According to a recent report, hospitalists made nearly half (48%) of all palliative care referrals in hospitals in 2015. The report comes from the Center to Advance Palliative Care and the National Palliative Care Research Center.

“The most important finding from this analysis is the near doubling of the number of people receiving palliative care services in U.S. hospital palliative care programs, from an average of 2.7% in 2009 to an average of 4.8% in 2015,” said Diane Meier, MD, director of the Center to Advance Palliative Care. “This suggests increasing recognition of the benefits of palliative care by health professionals and greater likelihood that those living with serious illness will receive state-of-the-art care.”

The report shows that hospitalists are the No. 1 source of referral to palliative care teams. “They see up close the suffering of their patients and families, their need for comprehensive whole-person care, and the beneficial impact of the added layer of support that palliative care provides,” she said.

“Hospitalists should work alongside their palliative care colleagues to develop standardized screening tools so that all patients and families who could benefit have access to the best quality of care during serious and complex illness,” Dr. Meier said. Hospitalists can also gain skills in communicating about prognosis and conducting family meetings, as well as safe and effective symptom management, through the online clinical training curriculum available at capc.org.
 

Reference

1. National Palliative Care Registry. How We Work: Trends and Insights in Hospital Palliative Care. https://registry.capc.org/wp-content/uploads/2017/02/How-We-Work-Trends-and-Insights-in-Hospital-Palliative-Care-2009-2015.pdf. Accessed April 7, 2017.

Improving outcomes for children with chronic conditions

Cincinnati Children’s Hospital Medical Center improved outcomes for 50% of pediatric patients by redesigning the way it cares for children with active chronic conditions, according to a new study.

The hospital implemented a Condition Outcomes Improvement Initiative, in which specialized clinical teams applied quality improvement principles to improve outcomes for pediatric patients with chronic illnesses.

Each improvement team focused on a specific chronic condition, such as juvenile arthritis, asthma, chronic kidney disease, or sickle cell disease. The improvement processes implemented included reviewing evidence to choose which outcomes to measure, developing condition-specific patient registries and data collection tools, classifying patients into defined risk groups, planning care before and after visits, and providing self-management and caregiver/parent support for patients and their families.

Study lead author Jennifer Lail, MD, FAAP, analyzed data from more than 27,000 pediatric patients from 18 improvement teams. Following implementation of the changes, half of patients had an improved outcome, and 11 of the 18 chronic condition teams achieved the goal of 20% improvement in their chosen clinical outcome, suggesting that clinical teams implementing quality improvement methods with multidisciplinary support can improve outcomes for populations with chronic conditions.
 

Reference

1. Lail J, et al. Applying the Chronic Care Model to Improve Care and Outcomes at a Pediatric Medical Center. Joint Commission Journal on Quality and Patient Safety. 2017;43(3):101-112.

FDA approves two new antibiotic tests

Hospitalists have two new FDA-approved tools available to help them make antibiotic treatment decisions.

The first is the expanded use of the Vidas Brahms PCT Assay, intended to be used in the hospital or emergency room. The test uses – for the first time – procalcitonin (PCT), a protein associated with the body’s response to a bacterial infection, as a biomarker that can help hospitalists make antibiotic management decisions in patients with those conditions. The results can help them determine if antibiotic treatment should be started or stopped in patients with lower respiratory tract infections (such as community-acquired pneumonia) and stopped in patients with sepsis.

The FDA has also allowed marketing of the PhenoTest BC Kit. This one is another first, the first test to identify organisms causing bloodstream infections and provide information about the antibiotics to which the organism is likely to respond.

The test can identify bacteria or yeast from a positive blood culture in approximately 1.5 hours (compared with traditional identification and antibiotic susceptibility tests, which can take one to two days). The test can identify 14 different species of bacteria and two species of yeast that cause bloodstream infections. It also provides antibiotic sensitivity information on 18 antibiotics. In addition, the test will identify the presence of two indicators of antibiotic resistance.
 

Quick byte

About a third of adverse events during hospitalizations involve a drug-related harm, resulting in longer hospital stays and increased costs, according to the New York Times. “The Institute of Medicine estimated that there are 400,000 preventable adverse drug events in hospitals each year, costing $3.5 billion. One-fifth of patients discharged from the hospital have a drug-related complication after returning home, many of which are preventable.”

Reference

1 Frakt A. How Many Pills Are Too Many? The New York Times. 2017 Apr 10. https://www.nytimes.com/2017/04/10/upshot/how-many-pills-are-too-many.html?rref=collection%2Fsectioncollection%2Fhealth&action=click&contentCollection=health&region=stream&module=stream_unit&version=latest&contentPlacement=6&pgtype=sectionfront&_r=0. Accessed April 9, 2017.

Measuring hospital-acquired infection in a new way

Every day, hospitalists struggle with health care–associated infections, which 1 in 25 patients experiences, according to the Centers for Disease Control and Prevention.

These infections are often discussed in terms of the standardized infection ratio (SIR), but that measure may not assess overall performance, according to a study suggesting a new measure that could help large hospital systems better evaluate their infection outcomes by comparing them with those of their peers.

References

1. Centers for Disease Control and Prevention. Healthcare-associated infections. https://www.cdc.gov/hai/surveillance/. Accessed April 10, 2017.

2. Fakih MG, Skierczynski B, Bufalino A, et al. Taking advantage of public reporting: An infection composite score to assist evaluating hospital performance for infection prevention efforts. American Journal of Infection Control. (2016);44(12):1578-81.

Hospitalists lead in palliative care

According to a recent report, hospitalists made nearly half (48%) of all palliative care referrals in hospitals in 2015. The report comes from the Center to Advance Palliative Care and the National Palliative Care Research Center.

“The most important finding from this analysis is the near doubling of the number of people receiving palliative care services in U.S. hospital palliative care programs, from an average of 2.7% in 2009 to an average of 4.8% in 2015,” said Diane Meier, MD, director of the Center to Advance Palliative Care. “This suggests increasing recognition of the benefits of palliative care by health professionals and greater likelihood that those living with serious illness will receive state-of-the-art care.”

The report shows that hospitalists are the No. 1 source of referral to palliative care teams. “They see up close the suffering of their patients and families, their need for comprehensive whole-person care, and the beneficial impact of the added layer of support that palliative care provides,” she said.

“Hospitalists should work alongside their palliative care colleagues to develop standardized screening tools so that all patients and families who could benefit have access to the best quality of care during serious and complex illness,” Dr. Meier said. Hospitalists can also gain skills in communicating about prognosis and conducting family meetings, as well as safe and effective symptom management, through the online clinical training curriculum available at capc.org.
 

Reference

1. National Palliative Care Registry. How We Work: Trends and Insights in Hospital Palliative Care. https://registry.capc.org/wp-content/uploads/2017/02/How-We-Work-Trends-and-Insights-in-Hospital-Palliative-Care-2009-2015.pdf. Accessed April 7, 2017.

Improving outcomes for children with chronic conditions

Cincinnati Children’s Hospital Medical Center improved outcomes for 50% of pediatric patients by redesigning the way it cares for children with active chronic conditions, according to a new study.

The hospital implemented a Condition Outcomes Improvement Initiative, in which specialized clinical teams applied quality improvement principles to improve outcomes for pediatric patients with chronic illnesses.

Each improvement team focused on a specific chronic condition, such as juvenile arthritis, asthma, chronic kidney disease, or sickle cell disease. The improvement processes implemented included reviewing evidence to choose which outcomes to measure, developing condition-specific patient registries and data collection tools, classifying patients into defined risk groups, planning care before and after visits, and providing self-management and caregiver/parent support for patients and their families.

Study lead author Jennifer Lail, MD, FAAP, analyzed data from more than 27,000 pediatric patients from 18 improvement teams. Following implementation of the changes, half of patients had an improved outcome, and 11 of the 18 chronic condition teams achieved the goal of 20% improvement in their chosen clinical outcome, suggesting that clinical teams implementing quality improvement methods with multidisciplinary support can improve outcomes for populations with chronic conditions.
 

Reference

1. Lail J, et al. Applying the Chronic Care Model to Improve Care and Outcomes at a Pediatric Medical Center. Joint Commission Journal on Quality and Patient Safety. 2017;43(3):101-112.

FDA approves two new antibiotic tests

Hospitalists have two new FDA-approved tools available to help them make antibiotic treatment decisions.

The first is the expanded use of the Vidas Brahms PCT Assay, intended to be used in the hospital or emergency room. The test uses – for the first time – procalcitonin (PCT), a protein associated with the body’s response to a bacterial infection, as a biomarker that can help hospitalists make antibiotic management decisions in patients with those conditions. The results can help them determine if antibiotic treatment should be started or stopped in patients with lower respiratory tract infections (such as community-acquired pneumonia) and stopped in patients with sepsis.

The FDA has also allowed marketing of the PhenoTest BC Kit. This one is another first, the first test to identify organisms causing bloodstream infections and provide information about the antibiotics to which the organism is likely to respond.

The test can identify bacteria or yeast from a positive blood culture in approximately 1.5 hours (compared with traditional identification and antibiotic susceptibility tests, which can take one to two days). The test can identify 14 different species of bacteria and two species of yeast that cause bloodstream infections. It also provides antibiotic sensitivity information on 18 antibiotics. In addition, the test will identify the presence of two indicators of antibiotic resistance.
 

Quick byte

About a third of adverse events during hospitalizations involve a drug-related harm, resulting in longer hospital stays and increased costs, according to the New York Times. “The Institute of Medicine estimated that there are 400,000 preventable adverse drug events in hospitals each year, costing $3.5 billion. One-fifth of patients discharged from the hospital have a drug-related complication after returning home, many of which are preventable.”

Reference

1 Frakt A. How Many Pills Are Too Many? The New York Times. 2017 Apr 10. https://www.nytimes.com/2017/04/10/upshot/how-many-pills-are-too-many.html?rref=collection%2Fsectioncollection%2Fhealth&action=click&contentCollection=health&region=stream&module=stream_unit&version=latest&contentPlacement=6&pgtype=sectionfront&_r=0. Accessed April 9, 2017.

LISBON – People with type 2 diabetes who take metformin for many years are more likely to develop anemia than are those who do not, according to the results of a large analysis of data from an observational, population-based study with 20 years of follow-up.

“Metformin treatment was associated with a 6% higher risk of anemia for every cumulative year of metformin exposure,” Louise Donnelly, PhD, and her associates reported in a poster presentation at the annual meeting of the European Association for the Study of Diabetes. 

In an interview, Dr. Donnelly, a postdoctoral research assistant at the University of Dundee (Scotland), explained why they looked at the use of metformin and anemia risk in people with type 2 diabetes.

“The Diabetes Prevention Program (DPP) study showed that long-term metformin use in individuals with impaired glucose tolerance was associated with an increased risk of anemia, and this was independent of vitamin B₁₂ status,” she said (J Clin Endocrinol Metab. 2016;101:1754-61). “Anemia is a common finding in people with type 2 diabetes, but the impact of long-term metformin use on anemia hasn’t been studied.”

Dr. Donnelly and her associates obtained detailed information on metformin prescribing and hematology measures from electronic patient medical records from the Genetics of Diabetes Audit and Research in Tayside and Scotland (GoDARTS) cohort, based in Scotland. This database contains information on individuals with type 2 diabetes and matching controls and is available to researchers worldwide.

For the analysis, the team looked for people diagnosed from 1996 onward who had a baseline hemoglobin measurement. Of 6,440 individuals with type 2 diabetes in the GoDARTS cohort, just over half had a hemoglobin measurement.

“We used a definition of ‘moderate’ anemia and we excluded patients with mild anemia or worse at diabetes diagnosis,” Dr. Donnelly observed. Anemia was considered to be a hemoglobin level of less than 12 g/dL in women and less than 13 g/dL in men. In all, 280 individuals with anemia were excluded from further analysis as the aim was to follow people until they developed anemia, died, left the area, or until the end of the follow-up period, which was set at September 30, 2015. A discrete-time failure analysis was used to model the effect of cumulative metformin exposure on anemia risk.

After a median follow-up of 8 years and a median number of 11 hemoglobin measurements per patient, 2,487 study subjects (71%) had some exposure to metformin and 1,458 of the whole sample (41.8%) had become anemic. Of those who developed anemia, 745 (51%) were current metformin users, 194 (13%) were former users, and 519 (36%) had never taken metformin.

“Cumulative metformin use was independently associated with an increased risk of anemia,” Dr. Donnelly noted (odds ratio [OR], 1.06; 95% confidence interval [CI], 1.02-1.09; P = .0006). This association was not seen when they examined the data based on sulfonylurea use (OR 1.0; 95% CI 0.97-1.04, P = .8), she added.

“Anemia risk was higher with age at diagnosis, duration of diabetes, lower hemoglobin at baseline, and lower eGFR [estimated glomerular filtration rate],” she observed. ORs for first anemia event were 1.03 (95% CI, 1.02-1.04) for every year of increasing age, 1.05 (95% CI, 1.03-1.08) for every additional year since diabetes diagnosis, 0.70 (95% CI, 0.66-0.74) per 1 g/dL of hemoglobin at diagnosis, and eGFR 0.98 (95% CI, 0.98-1.01) per additional 1 mL/min per 1.73² (P less than .0001 for all).

Why cumulative metformin use is associated with an increased of anemia is unclear, however, and Dr. Donnelly noted that this needs further investigation. “We do have data from two other clinical trials now, showing similar results, and maybe through those data we might be able to untangle it.”

The team does not think the anemia is related to B₁₂ deficiency, however, as people who developed anemia while taking metformin were more likely to develop microcytic (12% vs. 7.3%) than macrocytic (7.6% vs. 12.3%), anemia, compared with people with anemia who were not exposed to metformin (P less than .0001).

“In terms of mechanism, we can only conjecture,” Ewan Pearson, MB, senior author of the study and professor of medicine at the University of Dundee, said during a discussion at the poster presentation. “It is important to stress that metformin is a great drug and we shouldn’t stop it because of a potentially increased risk of anemia.”

The Medical Research Council supported the work. Dr. Donnelly reported having no financial disclosures.
 

[email protected]

LISBON – People with type 2 diabetes who take metformin for many years are more likely to develop anemia than are those who do not, according to the results of a large analysis of data from an observational, population-based study with 20 years of follow-up.

“Metformin treatment was associated with a 6% higher risk of anemia for every cumulative year of metformin exposure,” Louise Donnelly, PhD, and her associates reported in a poster presentation at the annual meeting of the European Association for the Study of Diabetes. 

In an interview, Dr. Donnelly, a postdoctoral research assistant at the University of Dundee (Scotland), explained why they looked at the use of metformin and anemia risk in people with type 2 diabetes.

“The Diabetes Prevention Program (DPP) study showed that long-term metformin use in individuals with impaired glucose tolerance was associated with an increased risk of anemia, and this was independent of vitamin B₁₂ status,” she said (J Clin Endocrinol Metab. 2016;101:1754-61). “Anemia is a common finding in people with type 2 diabetes, but the impact of long-term metformin use on anemia hasn’t been studied.”

Dr. Donnelly and her associates obtained detailed information on metformin prescribing and hematology measures from electronic patient medical records from the Genetics of Diabetes Audit and Research in Tayside and Scotland (GoDARTS) cohort, based in Scotland. This database contains information on individuals with type 2 diabetes and matching controls and is available to researchers worldwide.

For the analysis, the team looked for people diagnosed from 1996 onward who had a baseline hemoglobin measurement. Of 6,440 individuals with type 2 diabetes in the GoDARTS cohort, just over half had a hemoglobin measurement.

“We used a definition of ‘moderate’ anemia and we excluded patients with mild anemia or worse at diabetes diagnosis,” Dr. Donnelly observed. Anemia was considered to be a hemoglobin level of less than 12 g/dL in women and less than 13 g/dL in men. In all, 280 individuals with anemia were excluded from further analysis as the aim was to follow people until they developed anemia, died, left the area, or until the end of the follow-up period, which was set at September 30, 2015. A discrete-time failure analysis was used to model the effect of cumulative metformin exposure on anemia risk.

After a median follow-up of 8 years and a median number of 11 hemoglobin measurements per patient, 2,487 study subjects (71%) had some exposure to metformin and 1,458 of the whole sample (41.8%) had become anemic. Of those who developed anemia, 745 (51%) were current metformin users, 194 (13%) were former users, and 519 (36%) had never taken metformin.

“Cumulative metformin use was independently associated with an increased risk of anemia,” Dr. Donnelly noted (odds ratio [OR], 1.06; 95% confidence interval [CI], 1.02-1.09; P = .0006). This association was not seen when they examined the data based on sulfonylurea use (OR 1.0; 95% CI 0.97-1.04, P = .8), she added.

“Anemia risk was higher with age at diagnosis, duration of diabetes, lower hemoglobin at baseline, and lower eGFR [estimated glomerular filtration rate],” she observed. ORs for first anemia event were 1.03 (95% CI, 1.02-1.04) for every year of increasing age, 1.05 (95% CI, 1.03-1.08) for every additional year since diabetes diagnosis, 0.70 (95% CI, 0.66-0.74) per 1 g/dL of hemoglobin at diagnosis, and eGFR 0.98 (95% CI, 0.98-1.01) per additional 1 mL/min per 1.73² (P less than .0001 for all).

Why cumulative metformin use is associated with an increased of anemia is unclear, however, and Dr. Donnelly noted that this needs further investigation. “We do have data from two other clinical trials now, showing similar results, and maybe through those data we might be able to untangle it.”

The team does not think the anemia is related to B₁₂ deficiency, however, as people who developed anemia while taking metformin were more likely to develop microcytic (12% vs. 7.3%) than macrocytic (7.6% vs. 12.3%), anemia, compared with people with anemia who were not exposed to metformin (P less than .0001).

“In terms of mechanism, we can only conjecture,” Ewan Pearson, MB, senior author of the study and professor of medicine at the University of Dundee, said during a discussion at the poster presentation. “It is important to stress that metformin is a great drug and we shouldn’t stop it because of a potentially increased risk of anemia.”

The Medical Research Council supported the work. Dr. Donnelly reported having no financial disclosures.
 

[email protected]

LISBON – People with type 2 diabetes who take metformin for many years are more likely to develop anemia than are those who do not, according to the results of a large analysis of data from an observational, population-based study with 20 years of follow-up.

“Metformin treatment was associated with a 6% higher risk of anemia for every cumulative year of metformin exposure,” Louise Donnelly, PhD, and her associates reported in a poster presentation at the annual meeting of the European Association for the Study of Diabetes. 

In an interview, Dr. Donnelly, a postdoctoral research assistant at the University of Dundee (Scotland), explained why they looked at the use of metformin and anemia risk in people with type 2 diabetes.

“The Diabetes Prevention Program (DPP) study showed that long-term metformin use in individuals with impaired glucose tolerance was associated with an increased risk of anemia, and this was independent of vitamin B₁₂ status,” she said (J Clin Endocrinol Metab. 2016;101:1754-61). “Anemia is a common finding in people with type 2 diabetes, but the impact of long-term metformin use on anemia hasn’t been studied.”

Dr. Donnelly and her associates obtained detailed information on metformin prescribing and hematology measures from electronic patient medical records from the Genetics of Diabetes Audit and Research in Tayside and Scotland (GoDARTS) cohort, based in Scotland. This database contains information on individuals with type 2 diabetes and matching controls and is available to researchers worldwide.

For the analysis, the team looked for people diagnosed from 1996 onward who had a baseline hemoglobin measurement. Of 6,440 individuals with type 2 diabetes in the GoDARTS cohort, just over half had a hemoglobin measurement.

“We used a definition of ‘moderate’ anemia and we excluded patients with mild anemia or worse at diabetes diagnosis,” Dr. Donnelly observed. Anemia was considered to be a hemoglobin level of less than 12 g/dL in women and less than 13 g/dL in men. In all, 280 individuals with anemia were excluded from further analysis as the aim was to follow people until they developed anemia, died, left the area, or until the end of the follow-up period, which was set at September 30, 2015. A discrete-time failure analysis was used to model the effect of cumulative metformin exposure on anemia risk.

After a median follow-up of 8 years and a median number of 11 hemoglobin measurements per patient, 2,487 study subjects (71%) had some exposure to metformin and 1,458 of the whole sample (41.8%) had become anemic. Of those who developed anemia, 745 (51%) were current metformin users, 194 (13%) were former users, and 519 (36%) had never taken metformin.

“Cumulative metformin use was independently associated with an increased risk of anemia,” Dr. Donnelly noted (odds ratio [OR], 1.06; 95% confidence interval [CI], 1.02-1.09; P = .0006). This association was not seen when they examined the data based on sulfonylurea use (OR 1.0; 95% CI 0.97-1.04, P = .8), she added.

“Anemia risk was higher with age at diagnosis, duration of diabetes, lower hemoglobin at baseline, and lower eGFR [estimated glomerular filtration rate],” she observed. ORs for first anemia event were 1.03 (95% CI, 1.02-1.04) for every year of increasing age, 1.05 (95% CI, 1.03-1.08) for every additional year since diabetes diagnosis, 0.70 (95% CI, 0.66-0.74) per 1 g/dL of hemoglobin at diagnosis, and eGFR 0.98 (95% CI, 0.98-1.01) per additional 1 mL/min per 1.73² (P less than .0001 for all).

Why cumulative metformin use is associated with an increased of anemia is unclear, however, and Dr. Donnelly noted that this needs further investigation. “We do have data from two other clinical trials now, showing similar results, and maybe through those data we might be able to untangle it.”

The team does not think the anemia is related to B₁₂ deficiency, however, as people who developed anemia while taking metformin were more likely to develop microcytic (12% vs. 7.3%) than macrocytic (7.6% vs. 12.3%), anemia, compared with people with anemia who were not exposed to metformin (P less than .0001).

“In terms of mechanism, we can only conjecture,” Ewan Pearson, MB, senior author of the study and professor of medicine at the University of Dundee, said during a discussion at the poster presentation. “It is important to stress that metformin is a great drug and we shouldn’t stop it because of a potentially increased risk of anemia.”

The Medical Research Council supported the work. Dr. Donnelly reported having no financial disclosures.
 

[email protected]

SAN FRANCISCO – When patients with contact dermatitis who have had a patch test positive to an allergen and are not improving despite avoiding cutaneous exposure, it’s important to consider the possibility of systemic exposure, according to Nina Botto, MD, of the department of dermatology, at the University of California, San Francisco.

“Theoretically, any allergen can cause a systemic contact dermatitis. The ones that we think about and encounter more frequently are earth metals like nickel and balsam of Peru, which is a component of many fragrances and flavorings,” she said in a video interview at the annual meeting of the Pacific Dermatologic Association.

In the interview, Dr. Botto, who is codirector of the Occupational and Contact Dermatitis Clinic at UCSF, provides recommendations on how to approach patients with systemic contact dermatitis, including dietary avoidance. But following these diets can be challenging. She recommends starting with avoiding cutaneous exposure to the suspected allergen. For patients not improving after two months of avoidance, “it may be reasonable to consider a diet,”she advised.

Dr. Botto cited the following two publications with tables and guidelines for diets as helpful resources for patients: Dermatitis. 2013 Jul-Aug;24(4):153-60 (for a diet low in balsam of Peru); and Dermatitis. 2013 Jul-Aug; 24(4):190-5 (for a diet low in nickel).

Another useful resource is the American Contact Dermatitis Society website, which produces a customized list of safe products for patients after they enter the allergen into the system.

Dr. Botto had no disclosures.

[email protected]

SAN FRANCISCO – When patients with contact dermatitis who have had a patch test positive to an allergen and are not improving despite avoiding cutaneous exposure, it’s important to consider the possibility of systemic exposure, according to Nina Botto, MD, of the department of dermatology, at the University of California, San Francisco.

“Theoretically, any allergen can cause a systemic contact dermatitis. The ones that we think about and encounter more frequently are earth metals like nickel and balsam of Peru, which is a component of many fragrances and flavorings,” she said in a video interview at the annual meeting of the Pacific Dermatologic Association.

In the interview, Dr. Botto, who is codirector of the Occupational and Contact Dermatitis Clinic at UCSF, provides recommendations on how to approach patients with systemic contact dermatitis, including dietary avoidance. But following these diets can be challenging. She recommends starting with avoiding cutaneous exposure to the suspected allergen. For patients not improving after two months of avoidance, “it may be reasonable to consider a diet,”she advised.

Dr. Botto cited the following two publications with tables and guidelines for diets as helpful resources for patients: Dermatitis. 2013 Jul-Aug;24(4):153-60 (for a diet low in balsam of Peru); and Dermatitis. 2013 Jul-Aug; 24(4):190-5 (for a diet low in nickel).

Another useful resource is the American Contact Dermatitis Society website, which produces a customized list of safe products for patients after they enter the allergen into the system.

Dr. Botto had no disclosures.

[email protected]

SAN FRANCISCO – When patients with contact dermatitis who have had a patch test positive to an allergen and are not improving despite avoiding cutaneous exposure, it’s important to consider the possibility of systemic exposure, according to Nina Botto, MD, of the department of dermatology, at the University of California, San Francisco.

“Theoretically, any allergen can cause a systemic contact dermatitis. The ones that we think about and encounter more frequently are earth metals like nickel and balsam of Peru, which is a component of many fragrances and flavorings,” she said in a video interview at the annual meeting of the Pacific Dermatologic Association.

In the interview, Dr. Botto, who is codirector of the Occupational and Contact Dermatitis Clinic at UCSF, provides recommendations on how to approach patients with systemic contact dermatitis, including dietary avoidance. But following these diets can be challenging. She recommends starting with avoiding cutaneous exposure to the suspected allergen. For patients not improving after two months of avoidance, “it may be reasonable to consider a diet,”she advised.

Dr. Botto cited the following two publications with tables and guidelines for diets as helpful resources for patients: Dermatitis. 2013 Jul-Aug;24(4):153-60 (for a diet low in balsam of Peru); and Dermatitis. 2013 Jul-Aug; 24(4):190-5 (for a diet low in nickel).

Another useful resource is the American Contact Dermatitis Society website, which produces a customized list of safe products for patients after they enter the allergen into the system.

Dr. Botto had no disclosures.

[email protected]

Cognitive reappraisal is a top-down emotional regulation skill associated with resilience – the capacity to adaptively overcome adversity.

A person with this ability, also known as cognitive flexibility or reframing, monitors negative thoughts or situations and intentionally changes the way he or she views them. This reframing can involve retaining a positive outlook, trying to create meaning from a difficult situation, or finding ways to exert control over specific circumstances (Front Behav Neurosci. 2013 Feb 15;7:10). Some individuals cope with their mental illness by creating their own models of their illness (Achieving Cultural Competency: A Case-Based Approach to Training Health Professionals, Hoboken, N.J.: Wiley-Blackwell Publishing, 2009).

Creating a model of illness is a type of reframing to help explain what’s happening to an individual by placing the locus of control either inside our ourselves, adjacent, or far away and uncontrollable. Depending on the model, there might be choice that results in action taken to face the mental illness. Sometimes, there is surrender, either to the illness or the treatment.

I asked my friend from home and my brother for their permission and sent them this piece to make sure they approved. I changed certain details about Ricardo’s story to protect his identity. With my brother, there was no way to change his identity, but he was touched and happy to be included. I also changed key facts about the patient I called Laura.

Dr. Posada is a third-year resident in the psychiatry and behavioral sciences department at George Washington University, Washington. She completed a bachelor’s degree at George Washington University. For 2 years after her undergraduate education, she worked at the National Institutes of Allergy and Infectious Diseases studying HIV pathogenesis. Dr. Posada completed her medical degree at the University of Texas Medical Branch in Galveston. Her interests include public psychiatry, health care policy, and health disparities, and she plans to pursue a fellowship in consult liaison psychiatry.

Cognitive reappraisal is a top-down emotional regulation skill associated with resilience – the capacity to adaptively overcome adversity.

A person with this ability, also known as cognitive flexibility or reframing, monitors negative thoughts or situations and intentionally changes the way he or she views them. This reframing can involve retaining a positive outlook, trying to create meaning from a difficult situation, or finding ways to exert control over specific circumstances (Front Behav Neurosci. 2013 Feb 15;7:10). Some individuals cope with their mental illness by creating their own models of their illness (Achieving Cultural Competency: A Case-Based Approach to Training Health Professionals, Hoboken, N.J.: Wiley-Blackwell Publishing, 2009).

Creating a model of illness is a type of reframing to help explain what’s happening to an individual by placing the locus of control either inside our ourselves, adjacent, or far away and uncontrollable. Depending on the model, there might be choice that results in action taken to face the mental illness. Sometimes, there is surrender, either to the illness or the treatment.

I asked my friend from home and my brother for their permission and sent them this piece to make sure they approved. I changed certain details about Ricardo’s story to protect his identity. With my brother, there was no way to change his identity, but he was touched and happy to be included. I also changed key facts about the patient I called Laura.

Dr. Posada is a third-year resident in the psychiatry and behavioral sciences department at George Washington University, Washington. She completed a bachelor’s degree at George Washington University. For 2 years after her undergraduate education, she worked at the National Institutes of Allergy and Infectious Diseases studying HIV pathogenesis. Dr. Posada completed her medical degree at the University of Texas Medical Branch in Galveston. Her interests include public psychiatry, health care policy, and health disparities, and she plans to pursue a fellowship in consult liaison psychiatry.

Cognitive reappraisal is a top-down emotional regulation skill associated with resilience – the capacity to adaptively overcome adversity.

A person with this ability, also known as cognitive flexibility or reframing, monitors negative thoughts or situations and intentionally changes the way he or she views them. This reframing can involve retaining a positive outlook, trying to create meaning from a difficult situation, or finding ways to exert control over specific circumstances (Front Behav Neurosci. 2013 Feb 15;7:10). Some individuals cope with their mental illness by creating their own models of their illness (Achieving Cultural Competency: A Case-Based Approach to Training Health Professionals, Hoboken, N.J.: Wiley-Blackwell Publishing, 2009).

Creating a model of illness is a type of reframing to help explain what’s happening to an individual by placing the locus of control either inside our ourselves, adjacent, or far away and uncontrollable. Depending on the model, there might be choice that results in action taken to face the mental illness. Sometimes, there is surrender, either to the illness or the treatment.

I asked my friend from home and my brother for their permission and sent them this piece to make sure they approved. I changed certain details about Ricardo’s story to protect his identity. With my brother, there was no way to change his identity, but he was touched and happy to be included. I also changed key facts about the patient I called Laura.

Dr. Posada is a third-year resident in the psychiatry and behavioral sciences department at George Washington University, Washington. She completed a bachelor’s degree at George Washington University. For 2 years after her undergraduate education, she worked at the National Institutes of Allergy and Infectious Diseases studying HIV pathogenesis. Dr. Posada completed her medical degree at the University of Texas Medical Branch in Galveston. Her interests include public psychiatry, health care policy, and health disparities, and she plans to pursue a fellowship in consult liaison psychiatry.

A 15-year-old African American girl presented to the emergency department with 3 days of fever, sore throat, nausea, vomiting, and poor appetite. She reported a 4-week history of fatigue, right hand pain and swelling, and a 6-kilogram weight loss for which she had seen her primary care provider several times. She reported no recent travel, sick contacts, or new medications.

It appears that there are potentially at least 2 separate problems: an acute one (past 3 days) and a more chronic one (past 4 weeks). These 2 problems may be directly related (ie, acute worsening of the more chronic problem), indirectly related (ie, the more chronic problem is leading to increased susceptibility to the acute problem, for instance, an evolving immunodeficiency predisposing to an opportunistic infection), or “true, true, but unrelated.” The clinical challenge is to keep one’s mind open to each of these potential scenarios and to avoid the tendency to focus on one of the problems and not pay enough attention to the other. Occam’s razor likely does not apply here.

Numerous common and typically transient diseases could cause the symptoms of the past 3 days, particularly infectious etiologies such as streptococcal pharyngitis or a viral infection. One cannot forget about these possibilities while contemplating the more worrisome symptoms of the past 4 weeks, especially weight loss in a growing adolescent. Patients may unintentionally lose weight for a variety of reasons, which can be broadly categorized by decreased caloric supply, gastrointestinal losses or malabsorption, and increased caloric demand; these categories are not mutually exclusive.

Lastly, 1 symptom may provide a more specific direction: the right hand pain and swelling of the past 4 weeks. More specifics, including the extent of the hand swelling, other areas of involvement, and the nature of her pain, will be helpful.

Her temperature was 99.5°F, heart rate 100 beats per minute, respiratory rate 18 breaths per minute, oxygen saturation 95% while breathing ambient air, blood pressure 99/56 mmHg, weight 44 kilograms, height 161 centimeters, and body mass index 17. She appeared generally ill and underweight. She had edematous and violaceous eyelids, dry cracked lips, and pharyngeal erythema with ulcerations of the hard palate. She had nontender cervical and inguinal lymphadenopathy. Her abdomen was tender to palpation in the lower quadrants without guarding or rebound; there was no organomegaly. A right knee effusion with overlying warmth was present without redness or decreased range of motion. She also had an enlarged third proximal interphalangeal joint and loss of palpable metacarpal phalangeal joint landmarks on her right hand. She was noted to be using her arms to move her legs when repositioning in bed.

These exam findings clearly point toward a systemic process but not 1 specific diagnosis. The presence of at least 2 inflamed joints points toward rheumatologic/inflammatory or infectious diseases. Localized edema (eyelids and right metacarpal phalangeal joints), oral ulcers, possible myositis, and arthritis point toward a systemic vasculitis (eg, granulomatosis with polyangiitis, Behçet disease). While Kawasaki disease is also a systemic vasculitis, the presence of oral ulcers and generalized lymphadenopathy argues against it. Inflammatory myopathies like polymyositis, and especially juvenile dermatomyositis, fit many aspects of this presentation with the violaceous eyelids and possible myositis, though no other cutaneous stigmata of this disease are evident (eg, no Gottron’s papules). Polyarthritis, violaceous eyelids, and possible myositis could be consistent with systemic lupus erythematosus (SLE).

The presence of oral ulcers and arthritis make other systemic inflammatory conditions, such as inflammatory bowel disease with arthritis and autoimmune- or infection-related hepatitis, possible. Infectious etiologies alone or in combination with a rheumatologic process are also possible given fevers and lymphadenopathy. In particular, herpesvirus infections (Epstein-Barr virus [EBV], cytomegalovirus [CMV], herpes simplex virus, or human herpes virus 6), human immunodeficiency virus (HIV), hepatitis C virus (HCV), and syphilis can cause oral ulcers and lymphadenopathy. Other potential infectious etiologies include subacute bacterial endocarditis and disseminated gonococcal infection given the presence of polyarthritis, but these infections are less likely as they do not explain all of the symptoms.

In summary, the differential diagnosis is broad and should be prioritized to consider systemic inflammatory conditions, including autoimmune and infectious (especially viral) syndromes, and initial work-up should focus on these etiologies.

All of the infectious disease studies returned negative for active infection and were consistent with prior EBV and CMV infections with positive IgG testing. The bone marrow biopsy revealed trilineage hematopoiesis with hemophagocytosis, mild fibrosis, and no blasts (Figure 2). Antibody studies for SLE returned with elevated antidouble stranded DNA antibodies >200,000 IU/L. Reference labs ultimately confirmed the presence of decreased natural killer (NK) cell function, elevated soluble interleukin-2 receptors (IL-2R), and elevated soluble cluster of differentiation 163 (CD163).

Because the differential diagnosis for new-onset pancytopenia encompasses many diseases across several medical subspecialties, a thorough history and physical exam are necessary to form a tailored clinical approach.¹ The primary causes of pediatric pancytopenia vary depending on geographic location because of the local prevalence of infectious agents and nutritional deficiency patterns. A retrospective study investigating the primary cause of pancytopenia in children without existing malignancy presenting to a US tertiary care hospital found that 64% of cases were due to infection, 28% were due to hematologic disease (most frequently aplastic anemia), and 8% were due to miscellaneous etiologies, including adverse drug reactions and autoimmune diseases.² In contrast, the most common cause of pancytopenia in pediatric patients presenting to a tertiary care hospital in India was megaloblastic anemia (28%), followed by infections (21%), acute leukemia (21%), and aplastic anemia (20%).³ While clinicians do (and should) consider malignancy as a cause of pancytopenia, there is sparse literature regarding the frequency of pancytopenia associated with the presentations of childhood malignancies.⁴ A study of pediatric patients with acute lymphoblastic anemia found that only 11% of newly diagnosed patients had pancytopenia at initial presentation.⁴

There are no official guidelines for the work-up of pediatric pancytopenia from any of the academic societies. Depending on the clinical history, initial laboratory investigation for pediatric pancytopenia may include complete blood cell count with differential, reticulocyte count, peripheral blood smear, complete metabolic panel, hemolysis labs (haptoglobin, LDH, Coombs test) and inflammatory markers (ESR, CRP, fibrinogen). Further investigation to clarify the specific etiology of pancytopenia can be guided by the results of these initial tests.

• Children with SLE tend to have greater involvement of major organ systems and more rapid accrual of organ damage than adults with SLE. Therefore, it is sometimes necessary to initiate immunosuppressive therapies before full diagnostic criteria are met, provided that malignancy and infection have been ruled out.
• While pancytopenia is common in pediatric patients with SLE, providers should make sure to consider coexisting diagnoses such as infection and MAS, both of which require different treatment strategies.
• It is important to consider HLH/MAS early in the work-up of pancytopenia, because early diagnosis and treatment improves clinical outcomes. Obtaining a ferritin level can aid in the work-up of pancytopenia because it is both a sensitive and specific marker of HLH/MAS when dramatically elevated.

Disclosure

 The authors report no conflicts of interest.

A 15-year-old African American girl presented to the emergency department with 3 days of fever, sore throat, nausea, vomiting, and poor appetite. She reported a 4-week history of fatigue, right hand pain and swelling, and a 6-kilogram weight loss for which she had seen her primary care provider several times. She reported no recent travel, sick contacts, or new medications.

It appears that there are potentially at least 2 separate problems: an acute one (past 3 days) and a more chronic one (past 4 weeks). These 2 problems may be directly related (ie, acute worsening of the more chronic problem), indirectly related (ie, the more chronic problem is leading to increased susceptibility to the acute problem, for instance, an evolving immunodeficiency predisposing to an opportunistic infection), or “true, true, but unrelated.” The clinical challenge is to keep one’s mind open to each of these potential scenarios and to avoid the tendency to focus on one of the problems and not pay enough attention to the other. Occam’s razor likely does not apply here.

Numerous common and typically transient diseases could cause the symptoms of the past 3 days, particularly infectious etiologies such as streptococcal pharyngitis or a viral infection. One cannot forget about these possibilities while contemplating the more worrisome symptoms of the past 4 weeks, especially weight loss in a growing adolescent. Patients may unintentionally lose weight for a variety of reasons, which can be broadly categorized by decreased caloric supply, gastrointestinal losses or malabsorption, and increased caloric demand; these categories are not mutually exclusive.

Lastly, 1 symptom may provide a more specific direction: the right hand pain and swelling of the past 4 weeks. More specifics, including the extent of the hand swelling, other areas of involvement, and the nature of her pain, will be helpful.

Her temperature was 99.5°F, heart rate 100 beats per minute, respiratory rate 18 breaths per minute, oxygen saturation 95% while breathing ambient air, blood pressure 99/56 mmHg, weight 44 kilograms, height 161 centimeters, and body mass index 17. She appeared generally ill and underweight. She had edematous and violaceous eyelids, dry cracked lips, and pharyngeal erythema with ulcerations of the hard palate. She had nontender cervical and inguinal lymphadenopathy. Her abdomen was tender to palpation in the lower quadrants without guarding or rebound; there was no organomegaly. A right knee effusion with overlying warmth was present without redness or decreased range of motion. She also had an enlarged third proximal interphalangeal joint and loss of palpable metacarpal phalangeal joint landmarks on her right hand. She was noted to be using her arms to move her legs when repositioning in bed.

These exam findings clearly point toward a systemic process but not 1 specific diagnosis. The presence of at least 2 inflamed joints points toward rheumatologic/inflammatory or infectious diseases. Localized edema (eyelids and right metacarpal phalangeal joints), oral ulcers, possible myositis, and arthritis point toward a systemic vasculitis (eg, granulomatosis with polyangiitis, Behçet disease). While Kawasaki disease is also a systemic vasculitis, the presence of oral ulcers and generalized lymphadenopathy argues against it. Inflammatory myopathies like polymyositis, and especially juvenile dermatomyositis, fit many aspects of this presentation with the violaceous eyelids and possible myositis, though no other cutaneous stigmata of this disease are evident (eg, no Gottron’s papules). Polyarthritis, violaceous eyelids, and possible myositis could be consistent with systemic lupus erythematosus (SLE).

The presence of oral ulcers and arthritis make other systemic inflammatory conditions, such as inflammatory bowel disease with arthritis and autoimmune- or infection-related hepatitis, possible. Infectious etiologies alone or in combination with a rheumatologic process are also possible given fevers and lymphadenopathy. In particular, herpesvirus infections (Epstein-Barr virus [EBV], cytomegalovirus [CMV], herpes simplex virus, or human herpes virus 6), human immunodeficiency virus (HIV), hepatitis C virus (HCV), and syphilis can cause oral ulcers and lymphadenopathy. Other potential infectious etiologies include subacute bacterial endocarditis and disseminated gonococcal infection given the presence of polyarthritis, but these infections are less likely as they do not explain all of the symptoms.

In summary, the differential diagnosis is broad and should be prioritized to consider systemic inflammatory conditions, including autoimmune and infectious (especially viral) syndromes, and initial work-up should focus on these etiologies.

All of the infectious disease studies returned negative for active infection and were consistent with prior EBV and CMV infections with positive IgG testing. The bone marrow biopsy revealed trilineage hematopoiesis with hemophagocytosis, mild fibrosis, and no blasts (Figure 2). Antibody studies for SLE returned with elevated antidouble stranded DNA antibodies >200,000 IU/L. Reference labs ultimately confirmed the presence of decreased natural killer (NK) cell function, elevated soluble interleukin-2 receptors (IL-2R), and elevated soluble cluster of differentiation 163 (CD163).

Because the differential diagnosis for new-onset pancytopenia encompasses many diseases across several medical subspecialties, a thorough history and physical exam are necessary to form a tailored clinical approach.¹ The primary causes of pediatric pancytopenia vary depending on geographic location because of the local prevalence of infectious agents and nutritional deficiency patterns. A retrospective study investigating the primary cause of pancytopenia in children without existing malignancy presenting to a US tertiary care hospital found that 64% of cases were due to infection, 28% were due to hematologic disease (most frequently aplastic anemia), and 8% were due to miscellaneous etiologies, including adverse drug reactions and autoimmune diseases.² In contrast, the most common cause of pancytopenia in pediatric patients presenting to a tertiary care hospital in India was megaloblastic anemia (28%), followed by infections (21%), acute leukemia (21%), and aplastic anemia (20%).³ While clinicians do (and should) consider malignancy as a cause of pancytopenia, there is sparse literature regarding the frequency of pancytopenia associated with the presentations of childhood malignancies.⁴ A study of pediatric patients with acute lymphoblastic anemia found that only 11% of newly diagnosed patients had pancytopenia at initial presentation.⁴

There are no official guidelines for the work-up of pediatric pancytopenia from any of the academic societies. Depending on the clinical history, initial laboratory investigation for pediatric pancytopenia may include complete blood cell count with differential, reticulocyte count, peripheral blood smear, complete metabolic panel, hemolysis labs (haptoglobin, LDH, Coombs test) and inflammatory markers (ESR, CRP, fibrinogen). Further investigation to clarify the specific etiology of pancytopenia can be guided by the results of these initial tests.

• Children with SLE tend to have greater involvement of major organ systems and more rapid accrual of organ damage than adults with SLE. Therefore, it is sometimes necessary to initiate immunosuppressive therapies before full diagnostic criteria are met, provided that malignancy and infection have been ruled out.
• While pancytopenia is common in pediatric patients with SLE, providers should make sure to consider coexisting diagnoses such as infection and MAS, both of which require different treatment strategies.
• It is important to consider HLH/MAS early in the work-up of pancytopenia, because early diagnosis and treatment improves clinical outcomes. Obtaining a ferritin level can aid in the work-up of pancytopenia because it is both a sensitive and specific marker of HLH/MAS when dramatically elevated.

Disclosure

 The authors report no conflicts of interest.

A 15-year-old African American girl presented to the emergency department with 3 days of fever, sore throat, nausea, vomiting, and poor appetite. She reported a 4-week history of fatigue, right hand pain and swelling, and a 6-kilogram weight loss for which she had seen her primary care provider several times. She reported no recent travel, sick contacts, or new medications.

It appears that there are potentially at least 2 separate problems: an acute one (past 3 days) and a more chronic one (past 4 weeks). These 2 problems may be directly related (ie, acute worsening of the more chronic problem), indirectly related (ie, the more chronic problem is leading to increased susceptibility to the acute problem, for instance, an evolving immunodeficiency predisposing to an opportunistic infection), or “true, true, but unrelated.” The clinical challenge is to keep one’s mind open to each of these potential scenarios and to avoid the tendency to focus on one of the problems and not pay enough attention to the other. Occam’s razor likely does not apply here.

Numerous common and typically transient diseases could cause the symptoms of the past 3 days, particularly infectious etiologies such as streptococcal pharyngitis or a viral infection. One cannot forget about these possibilities while contemplating the more worrisome symptoms of the past 4 weeks, especially weight loss in a growing adolescent. Patients may unintentionally lose weight for a variety of reasons, which can be broadly categorized by decreased caloric supply, gastrointestinal losses or malabsorption, and increased caloric demand; these categories are not mutually exclusive.

Lastly, 1 symptom may provide a more specific direction: the right hand pain and swelling of the past 4 weeks. More specifics, including the extent of the hand swelling, other areas of involvement, and the nature of her pain, will be helpful.

Her temperature was 99.5°F, heart rate 100 beats per minute, respiratory rate 18 breaths per minute, oxygen saturation 95% while breathing ambient air, blood pressure 99/56 mmHg, weight 44 kilograms, height 161 centimeters, and body mass index 17. She appeared generally ill and underweight. She had edematous and violaceous eyelids, dry cracked lips, and pharyngeal erythema with ulcerations of the hard palate. She had nontender cervical and inguinal lymphadenopathy. Her abdomen was tender to palpation in the lower quadrants without guarding or rebound; there was no organomegaly. A right knee effusion with overlying warmth was present without redness or decreased range of motion. She also had an enlarged third proximal interphalangeal joint and loss of palpable metacarpal phalangeal joint landmarks on her right hand. She was noted to be using her arms to move her legs when repositioning in bed.

These exam findings clearly point toward a systemic process but not 1 specific diagnosis. The presence of at least 2 inflamed joints points toward rheumatologic/inflammatory or infectious diseases. Localized edema (eyelids and right metacarpal phalangeal joints), oral ulcers, possible myositis, and arthritis point toward a systemic vasculitis (eg, granulomatosis with polyangiitis, Behçet disease). While Kawasaki disease is also a systemic vasculitis, the presence of oral ulcers and generalized lymphadenopathy argues against it. Inflammatory myopathies like polymyositis, and especially juvenile dermatomyositis, fit many aspects of this presentation with the violaceous eyelids and possible myositis, though no other cutaneous stigmata of this disease are evident (eg, no Gottron’s papules). Polyarthritis, violaceous eyelids, and possible myositis could be consistent with systemic lupus erythematosus (SLE).

The presence of oral ulcers and arthritis make other systemic inflammatory conditions, such as inflammatory bowel disease with arthritis and autoimmune- or infection-related hepatitis, possible. Infectious etiologies alone or in combination with a rheumatologic process are also possible given fevers and lymphadenopathy. In particular, herpesvirus infections (Epstein-Barr virus [EBV], cytomegalovirus [CMV], herpes simplex virus, or human herpes virus 6), human immunodeficiency virus (HIV), hepatitis C virus (HCV), and syphilis can cause oral ulcers and lymphadenopathy. Other potential infectious etiologies include subacute bacterial endocarditis and disseminated gonococcal infection given the presence of polyarthritis, but these infections are less likely as they do not explain all of the symptoms.

In summary, the differential diagnosis is broad and should be prioritized to consider systemic inflammatory conditions, including autoimmune and infectious (especially viral) syndromes, and initial work-up should focus on these etiologies.

All of the infectious disease studies returned negative for active infection and were consistent with prior EBV and CMV infections with positive IgG testing. The bone marrow biopsy revealed trilineage hematopoiesis with hemophagocytosis, mild fibrosis, and no blasts (Figure 2). Antibody studies for SLE returned with elevated antidouble stranded DNA antibodies >200,000 IU/L. Reference labs ultimately confirmed the presence of decreased natural killer (NK) cell function, elevated soluble interleukin-2 receptors (IL-2R), and elevated soluble cluster of differentiation 163 (CD163).

Because the differential diagnosis for new-onset pancytopenia encompasses many diseases across several medical subspecialties, a thorough history and physical exam are necessary to form a tailored clinical approach.¹ The primary causes of pediatric pancytopenia vary depending on geographic location because of the local prevalence of infectious agents and nutritional deficiency patterns. A retrospective study investigating the primary cause of pancytopenia in children without existing malignancy presenting to a US tertiary care hospital found that 64% of cases were due to infection, 28% were due to hematologic disease (most frequently aplastic anemia), and 8% were due to miscellaneous etiologies, including adverse drug reactions and autoimmune diseases.² In contrast, the most common cause of pancytopenia in pediatric patients presenting to a tertiary care hospital in India was megaloblastic anemia (28%), followed by infections (21%), acute leukemia (21%), and aplastic anemia (20%).³ While clinicians do (and should) consider malignancy as a cause of pancytopenia, there is sparse literature regarding the frequency of pancytopenia associated with the presentations of childhood malignancies.⁴ A study of pediatric patients with acute lymphoblastic anemia found that only 11% of newly diagnosed patients had pancytopenia at initial presentation.⁴

There are no official guidelines for the work-up of pediatric pancytopenia from any of the academic societies. Depending on the clinical history, initial laboratory investigation for pediatric pancytopenia may include complete blood cell count with differential, reticulocyte count, peripheral blood smear, complete metabolic panel, hemolysis labs (haptoglobin, LDH, Coombs test) and inflammatory markers (ESR, CRP, fibrinogen). Further investigation to clarify the specific etiology of pancytopenia can be guided by the results of these initial tests.

• Children with SLE tend to have greater involvement of major organ systems and more rapid accrual of organ damage than adults with SLE. Therefore, it is sometimes necessary to initiate immunosuppressive therapies before full diagnostic criteria are met, provided that malignancy and infection have been ruled out.
• While pancytopenia is common in pediatric patients with SLE, providers should make sure to consider coexisting diagnoses such as infection and MAS, both of which require different treatment strategies.
• It is important to consider HLH/MAS early in the work-up of pancytopenia, because early diagnosis and treatment improves clinical outcomes. Obtaining a ferritin level can aid in the work-up of pancytopenia because it is both a sensitive and specific marker of HLH/MAS when dramatically elevated.

Disclosure

 The authors report no conflicts of interest.

Pediatric hospital medicine (PHM) is one of the most rapidly growing disciplines in pediatrics,¹ with 8% of pediatric residency graduates each year entering the field.² Research plays an important role in advancing care in the field and is a critical component for board certification and fellowship accreditation.^3-6 The annual PHM conference, which has been jointly sponsored by the Academic Pediatric Association, the American Academy of Pediatrics, and the Society of Hospital Medicine, is an important venue for the dissemination of research findings. Abstract selection is determined by peer review; however, reviewers are provided with only a brief snapshot of the research, which may not contain sufficient information to fully evaluate the methodological quality of the work.^7-10 Additionally, while instructions are provided, reviewers often lack formal training in abstract review. Consequently, scores may vary.⁹

Publication in a peer-reviewed journal is considered a measure of research success because it requires more rigorous peer review than the abstract selection process at scientific meetings.^11-16 Rates of subsequent journal publication differ based on specialty and meeting, and they have been reported at 23% to 78%.^10,12,14-18 In pediatrics, publication rates after presentation at scientific meetings range from 36% to 63%, with mean time to publication ranging from 20 to 26 months following the meeting.^11,19,20 No studies have reviewed abstract submissions to the annual PHM meeting to determine if selection or presentation format is associated with subsequent publication in a peer-reviewed journal.

We sought to identify the publication rate of abstracts submitted to the 2014 PHM conference and determine whether presentation format was associated with the likelihood of subsequent journal publication or time to publication.

Study Design

Data for this retrospective cohort study were obtained from a database of all abstracts submitted for presentation at the 2014 PHM conference in Lake Buena Vista, Florida.

Main Exposures

The main exposure was presentation format, which was categorized as not presented (ie, rejected), poster presentation, or oral presentation. PHM has a blinded abstract peer-review process; in 2014, an average of 10 reviewers scored each abstract. Reviewers graded abstracts on a scale of 1 (best in category) to 7 (unacceptable for presentation) according to the following criteria: originality, scientific importance, methodological rigor, and quality of presentation. Abstracts with the lowest average scores in each content area, usually less than or equal to 3, were accepted as oral presentations while most abstracts with scores greater than 5 were rejected. For this study, information collected from each abstract included authors, if the primary author was a trainee, title, content area, and presentation format. Content areas included clinical research, educational research, health services research (HSR) and/or epidemiology, practice management research, and quality improvement. Abstracts were then grouped by presentation format and content area for analysis. The Pediatric Academic Societies (PAS) annual meeting, another common venue for the presentation of pediatric research, precedes the PHM conference. Because acceptance for PAS presentation may represent more strongly developed abstract submissions for PHM, we identified which abstracts had also been presented at the PAS conference that same year by cross-referencing authors and abstract titles with the PAS 2014 program.

Main Outcome Measures

All submissions were assessed for subsequent publication in peer-reviewed journals through January 2017 (30 months following the July 2014 PHM conference). To identify abstracts that went on to full publication, 2 authors (JC and LEH) independently searched for the lead author’s name and the presentation title in PubMed, Google Scholar, and MedEdPORTAL in January 2017. PubMed was searched using both the general search box and an advanced search for author and title. Google Scholar was added to capture manuscripts that may not have been indexed in PubMed at the time of our search. MedEdPORTAL, a common venue for the publication of educational initiatives that are not currently indexed in PubMed, was searched by lead author name via the general search box. If a full manuscript was published discussing similar outcomes or results and was written by the same authors who had submitted a PHM conference abstract, it was considered to have been published. The journal, month, and year of publication were recorded. For journals published every 2 months, the date of publication was recorded as falling between the 2 months. For those journals with biannual publication in the spring and fall, the months of March and October were used, respectively. The impact factor of the publication journal was also recorded for the year preceding publication. A journal’s impact factor is frequently used as a quantitative measure of journal quality and reflects the frequency with which a journal’s articles are cited in the scientific literature.²¹ Journals without an impact factor (eg, newer journals) were assigned a 0.

Data Analysis

All abstracts submitted to the PHM conference were analyzed based on content area and presentation format. The proportion of all abstracts subsequently published was determined for each format type and content area, and the odds ratio (OR) for publication after abstract submission was calculated using logistic regression. We calculated an adjusted OR for subsequent publication controlling for PAS presentation and the trainee status of the primary author. The journals most frequently publishing abstracts submitted to the PHM conference were identified. Median time to publication was calculated using the number of months elapsed between the PHM conference and publication date and compared across all abstract formats using Cox proportional hazards models adjusted for PAS presentation and trainee status. Kaplan-Meier survival curves were also generated for each of the 3 formats and compared using log-rank tests. The median impact factor was determined for each abstract format and compared using Wilcoxon rank-sum tests. Median impact factor by content area was compared using a Kruskal-Wallis test. All statistical analyses were performed using SAS version 9.2 (SAS Institute, Cary, NC). P values < 0.05 were considered statistically significant. In accordance with the Common Rule²² and the policies of the Cincinnati Children’s Hospital Medical Center Institutional Review Board, this research was not considered human subjects research.

For the 2014 PHM meeting, 226 abstracts were submitted, of which 183 (81.0%) were selected for presentation, including 154 (68.0%) as poster presentations and 29 (12.8%) as oral presentations. Of all submitted abstracts, 82 (36.3%) were published within 30 months following the meeting. Eighty-one of these (98.8%) were identified via PubMed, and 1 was found only in MedEdPORTAL. No additional publications were found via Google Scholar. The presenting author for the PHM abstract was the first author for 87.8% (n = 72) of the publications. A trainee was the presenting author for only 2 of these abstracts. For the publications in which the first author was not the presenting author, the presenting author was the senior author in 2 of the publications and the second or third author on the remaining 8. Of the abstracts accepted for presentation, 70 (38.3%) were subsequently published. Abstracts accepted for oral presentation had almost 7-fold greater odds of subsequent publication than those that were rejected (Table 1; OR 6.8; 95% confidence interval [CI], 2.4-19.4). Differences in the odds of publication for rejected abstracts compared with those accepted for poster presentation were not statistically significant (OR 1.2; 95% CI, 0.5-2.5).

About one-third of abstracts submitted to the 2014 PHM conference were subsequently published in peer-reviewed journals within 30 months of the conference. Compared with rejected abstracts, the rate of publication was significantly higher for abstracts selected for oral presentation but not for those selected for poster presentation. For abstracts ultimately published in journals, selection for oral presentation was significantly associated with both a shorter time to publication and a higher median journal impact factor compared with rejected abstracts. Time to publication and median journal impact factor were similar between rejected abstracts and those accepted for poster presentation. Our findings suggest that abstract reviewers may be able to identify which abstracts will ultimately withstand more stringent peer review in the publication process when accepting abstracts for oral presentation. However, the selection for poster presentation versus rejection may not be indicative of future publication or the impact factor of the subsequent publication journal.

Previous studies have reviewed publication rates after meetings of the European Society for Pediatric Urology (publication rate of 47%),¹¹ the Ambulatory Pediatric Association (now the Academic Pediatric Association; publication rate of 47%), the American Pediatric Society/Society for Pediatric Research (publication rate of 54%), and the PAS (publication rate of 45%).^19,20 Our lower publication rate of 36.3% may be attributed to the shorter follow-up time in our study (30 months from the PHM conference), whereas prior studies monitored for publication up to 60 months after the PAS conference.²⁰ Factors associated with subsequent publication include statistically significant results, a large sample size, and a randomized controlled trial study design.^15,16 The primary reason for nonpublication for up to 80% of abstracts is failure to submit a manuscript for publication.²³ A lack of time and fear of rejection after peer review are commonly cited explanations.^18,23,24 Individuals may view acceptance for an oral presentation as positive reinforcement and be more motivated to pursue subsequent manuscript publication than individuals whose abstracts are offered poster presentations or are rejected. Trainees frequently present abstracts at scientific meetings, representing 40.3% of primary authors submitting abstracts to PHM in 2014, but may not have sufficient time or mentorship to develop a complete manuscript.¹⁸ To our knowledge, there have been no publications that assess the impact of trainee status on subsequent publication after conference submission.

Our study demonstrated that selection for oral presentation was associated with subsequent publication, shorter time to publication, and publication in journals with higher impact factors. A 2005 Cochrane review also demonstrated that selection for oral presentation was associated with subsequent journal publication.¹⁶ Abstracts accepted for oral publication may represent work further along in the research process, with more developed methodology and results. The shorter time to publication for abstracts accepted for oral presentation could also reflect feedback provided by conference attendees after the presentation, whereas poster sessions frequently lack a formalized process for critique.

Carroll et al. found no difference in time to publication between abstracts accepted for presentation at the PAS and rejected abstracts.²⁰ Previous studies demonstrate that most abstracts presented at scientific meetings that are subsequently accepted for publication are published within 2 to 3 years of the meeting,¹² with publication rates as high as 98% within 3 years of presentation.¹⁷ In contrast to Carroll et al., we found that abstracts accepted for oral presentation had a 4-fold greater likelihood of publication at each month than rejected abstracts. However, abstracts accepted for poster presentation did not have a significant difference in the proportional hazard ratio models for publication compared with rejected abstracts. Because space considerations limit the number of abstracts that can be accepted for presentation at a conference, some abstracts that are suitable for future publication may have been rejected due to a lack of space. Because researchers often use scientific meetings as a forum to receive peer feedback,¹² authors who present at conferences may take more time to write a manuscript in order to incorporate this feedback.

The most common journal in which submitted abstracts were subsequently published was Hospital Pediatrics, representing twice as many published manuscripts as the second most frequent journal, Pediatrics. Hospital Pediatrics, which was first published in 2011, did not have an impact factor assigned during the study period. Yet, as a peer-reviewed journal dedicated to the field of PHM, it is well aligned with the research presented at the PHM meeting. It is unclear if Hospital Pediatrics is a journal to which pediatric hospitalists tend to submit manuscripts initially or if manuscripts are frequently submitted elsewhere prior to their publication in Hospital Pediatrics. Submission to other journals first likely extends the time to publication, especially for abstracts accepted for poster presentation, which may describe studies with less developed methods or results.

This study has several limitations. Previous studies have demonstrated mean time to publication of 12 to 32 months following abstract presentation with a median time of 19.6 months.¹⁶ Because we only have a 30-month follow-up, there may be abstracts still in the review process that are yet to be published, especially because the length of the review process varies by journal. We based our literature search on the first author of each PHM conference abstract submission, assuming that this presenting author would be one of the publishing authors even if not remaining first author; if this was not the case, we may have missed some abstracts that were subsequently published in full. Likewise, if a presenting author’s last name changed prior to the publication of a manuscript, a publication may have been missed. This limitation would cause us to underestimate the overall publication rate. It is not clear whether this would differentially affect the method of presentation. However, in this study, there was concordance between the presenting author and the publication’s first author in 87.8% of the abstracts subsequently published in full. Presenting authors who did not remain the first author on the published manuscript maintained authorship as either the senior author or second or third author, which may represent changes in the degree of involvement or a division of responsibilities for individuals working on a project together. While our search methods were comprehensive, there is a possibility that abstracts may have been published in a venue that was not searched. Additionally, we only reviewed abstracts submitted to PHM for 1 year. As the field matures and the number of fellowship programs increases, the quality of submitted abstracts may increase, leading to higher publication rates or shorter times to publication. It is also possible that the publication rate may not be reflective of PHM as a field because hospitalists may submit their work to conferences other than the PHM. Lastly, it may be more challenging to interpret any differences in impact factor because some journals, including Hospital Pediatrics (which represented a plurality of poster presentation abstracts that were subsequently published and is a relatively new journal), did not have an impact factor assigned during the study period. Assigning a 0 to journals without an impact factor may artificially lower the average impact factor reported. Furthermore, an impact factor, which is based on the frequency with which an individual journal’s articles are cited in scientific or medical publications, may not necessarily reflect a journal’s quality.

Of the 226 abstracts submitted to the 2014 PHM conference, approximately one-third were published in peer-reviewed journals within 30 months of the conference. Selection for oral presentation was found to be associated with subsequent publication as well as publication in journals with higher impact factors. The overall low publication rate may indicate a need for increased mentorship and resources for research development in this growing specialty. Improved mechanisms for author feedback at poster sessions may provide constructive suggestions for further development of these projects into full manuscripts or opportunities for trainees and early-career hospitalists to network with more experienced researchers in the field.

Disclosure

Drs. Herrmann, Hall, Kyler, Andrews, Williams, and Shah and Mr. Cochran have nothing to disclose. Dr. Wilson reports personal fees from the American Academy of Pediatrics during the conduct of the study. The authors have no financial relationships relevant to this article to disclose.

Pediatric hospital medicine (PHM) is one of the most rapidly growing disciplines in pediatrics,¹ with 8% of pediatric residency graduates each year entering the field.² Research plays an important role in advancing care in the field and is a critical component for board certification and fellowship accreditation.^3-6 The annual PHM conference, which has been jointly sponsored by the Academic Pediatric Association, the American Academy of Pediatrics, and the Society of Hospital Medicine, is an important venue for the dissemination of research findings. Abstract selection is determined by peer review; however, reviewers are provided with only a brief snapshot of the research, which may not contain sufficient information to fully evaluate the methodological quality of the work.^7-10 Additionally, while instructions are provided, reviewers often lack formal training in abstract review. Consequently, scores may vary.⁹

Publication in a peer-reviewed journal is considered a measure of research success because it requires more rigorous peer review than the abstract selection process at scientific meetings.^11-16 Rates of subsequent journal publication differ based on specialty and meeting, and they have been reported at 23% to 78%.^10,12,14-18 In pediatrics, publication rates after presentation at scientific meetings range from 36% to 63%, with mean time to publication ranging from 20 to 26 months following the meeting.^11,19,20 No studies have reviewed abstract submissions to the annual PHM meeting to determine if selection or presentation format is associated with subsequent publication in a peer-reviewed journal.

We sought to identify the publication rate of abstracts submitted to the 2014 PHM conference and determine whether presentation format was associated with the likelihood of subsequent journal publication or time to publication.

Study Design

Data for this retrospective cohort study were obtained from a database of all abstracts submitted for presentation at the 2014 PHM conference in Lake Buena Vista, Florida.

Main Exposures

The main exposure was presentation format, which was categorized as not presented (ie, rejected), poster presentation, or oral presentation. PHM has a blinded abstract peer-review process; in 2014, an average of 10 reviewers scored each abstract. Reviewers graded abstracts on a scale of 1 (best in category) to 7 (unacceptable for presentation) according to the following criteria: originality, scientific importance, methodological rigor, and quality of presentation. Abstracts with the lowest average scores in each content area, usually less than or equal to 3, were accepted as oral presentations while most abstracts with scores greater than 5 were rejected. For this study, information collected from each abstract included authors, if the primary author was a trainee, title, content area, and presentation format. Content areas included clinical research, educational research, health services research (HSR) and/or epidemiology, practice management research, and quality improvement. Abstracts were then grouped by presentation format and content area for analysis. The Pediatric Academic Societies (PAS) annual meeting, another common venue for the presentation of pediatric research, precedes the PHM conference. Because acceptance for PAS presentation may represent more strongly developed abstract submissions for PHM, we identified which abstracts had also been presented at the PAS conference that same year by cross-referencing authors and abstract titles with the PAS 2014 program.

Main Outcome Measures

All submissions were assessed for subsequent publication in peer-reviewed journals through January 2017 (30 months following the July 2014 PHM conference). To identify abstracts that went on to full publication, 2 authors (JC and LEH) independently searched for the lead author’s name and the presentation title in PubMed, Google Scholar, and MedEdPORTAL in January 2017. PubMed was searched using both the general search box and an advanced search for author and title. Google Scholar was added to capture manuscripts that may not have been indexed in PubMed at the time of our search. MedEdPORTAL, a common venue for the publication of educational initiatives that are not currently indexed in PubMed, was searched by lead author name via the general search box. If a full manuscript was published discussing similar outcomes or results and was written by the same authors who had submitted a PHM conference abstract, it was considered to have been published. The journal, month, and year of publication were recorded. For journals published every 2 months, the date of publication was recorded as falling between the 2 months. For those journals with biannual publication in the spring and fall, the months of March and October were used, respectively. The impact factor of the publication journal was also recorded for the year preceding publication. A journal’s impact factor is frequently used as a quantitative measure of journal quality and reflects the frequency with which a journal’s articles are cited in the scientific literature.²¹ Journals without an impact factor (eg, newer journals) were assigned a 0.

Data Analysis

All abstracts submitted to the PHM conference were analyzed based on content area and presentation format. The proportion of all abstracts subsequently published was determined for each format type and content area, and the odds ratio (OR) for publication after abstract submission was calculated using logistic regression. We calculated an adjusted OR for subsequent publication controlling for PAS presentation and the trainee status of the primary author. The journals most frequently publishing abstracts submitted to the PHM conference were identified. Median time to publication was calculated using the number of months elapsed between the PHM conference and publication date and compared across all abstract formats using Cox proportional hazards models adjusted for PAS presentation and trainee status. Kaplan-Meier survival curves were also generated for each of the 3 formats and compared using log-rank tests. The median impact factor was determined for each abstract format and compared using Wilcoxon rank-sum tests. Median impact factor by content area was compared using a Kruskal-Wallis test. All statistical analyses were performed using SAS version 9.2 (SAS Institute, Cary, NC). P values < 0.05 were considered statistically significant. In accordance with the Common Rule²² and the policies of the Cincinnati Children’s Hospital Medical Center Institutional Review Board, this research was not considered human subjects research.

For the 2014 PHM meeting, 226 abstracts were submitted, of which 183 (81.0%) were selected for presentation, including 154 (68.0%) as poster presentations and 29 (12.8%) as oral presentations. Of all submitted abstracts, 82 (36.3%) were published within 30 months following the meeting. Eighty-one of these (98.8%) were identified via PubMed, and 1 was found only in MedEdPORTAL. No additional publications were found via Google Scholar. The presenting author for the PHM abstract was the first author for 87.8% (n = 72) of the publications. A trainee was the presenting author for only 2 of these abstracts. For the publications in which the first author was not the presenting author, the presenting author was the senior author in 2 of the publications and the second or third author on the remaining 8. Of the abstracts accepted for presentation, 70 (38.3%) were subsequently published. Abstracts accepted for oral presentation had almost 7-fold greater odds of subsequent publication than those that were rejected (Table 1; OR 6.8; 95% confidence interval [CI], 2.4-19.4). Differences in the odds of publication for rejected abstracts compared with those accepted for poster presentation were not statistically significant (OR 1.2; 95% CI, 0.5-2.5).

About one-third of abstracts submitted to the 2014 PHM conference were subsequently published in peer-reviewed journals within 30 months of the conference. Compared with rejected abstracts, the rate of publication was significantly higher for abstracts selected for oral presentation but not for those selected for poster presentation. For abstracts ultimately published in journals, selection for oral presentation was significantly associated with both a shorter time to publication and a higher median journal impact factor compared with rejected abstracts. Time to publication and median journal impact factor were similar between rejected abstracts and those accepted for poster presentation. Our findings suggest that abstract reviewers may be able to identify which abstracts will ultimately withstand more stringent peer review in the publication process when accepting abstracts for oral presentation. However, the selection for poster presentation versus rejection may not be indicative of future publication or the impact factor of the subsequent publication journal.

Previous studies have reviewed publication rates after meetings of the European Society for Pediatric Urology (publication rate of 47%),¹¹ the Ambulatory Pediatric Association (now the Academic Pediatric Association; publication rate of 47%), the American Pediatric Society/Society for Pediatric Research (publication rate of 54%), and the PAS (publication rate of 45%).^19,20 Our lower publication rate of 36.3% may be attributed to the shorter follow-up time in our study (30 months from the PHM conference), whereas prior studies monitored for publication up to 60 months after the PAS conference.²⁰ Factors associated with subsequent publication include statistically significant results, a large sample size, and a randomized controlled trial study design.^15,16 The primary reason for nonpublication for up to 80% of abstracts is failure to submit a manuscript for publication.²³ A lack of time and fear of rejection after peer review are commonly cited explanations.^18,23,24 Individuals may view acceptance for an oral presentation as positive reinforcement and be more motivated to pursue subsequent manuscript publication than individuals whose abstracts are offered poster presentations or are rejected. Trainees frequently present abstracts at scientific meetings, representing 40.3% of primary authors submitting abstracts to PHM in 2014, but may not have sufficient time or mentorship to develop a complete manuscript.¹⁸ To our knowledge, there have been no publications that assess the impact of trainee status on subsequent publication after conference submission.

Our study demonstrated that selection for oral presentation was associated with subsequent publication, shorter time to publication, and publication in journals with higher impact factors. A 2005 Cochrane review also demonstrated that selection for oral presentation was associated with subsequent journal publication.¹⁶ Abstracts accepted for oral publication may represent work further along in the research process, with more developed methodology and results. The shorter time to publication for abstracts accepted for oral presentation could also reflect feedback provided by conference attendees after the presentation, whereas poster sessions frequently lack a formalized process for critique.

Carroll et al. found no difference in time to publication between abstracts accepted for presentation at the PAS and rejected abstracts.²⁰ Previous studies demonstrate that most abstracts presented at scientific meetings that are subsequently accepted for publication are published within 2 to 3 years of the meeting,¹² with publication rates as high as 98% within 3 years of presentation.¹⁷ In contrast to Carroll et al., we found that abstracts accepted for oral presentation had a 4-fold greater likelihood of publication at each month than rejected abstracts. However, abstracts accepted for poster presentation did not have a significant difference in the proportional hazard ratio models for publication compared with rejected abstracts. Because space considerations limit the number of abstracts that can be accepted for presentation at a conference, some abstracts that are suitable for future publication may have been rejected due to a lack of space. Because researchers often use scientific meetings as a forum to receive peer feedback,¹² authors who present at conferences may take more time to write a manuscript in order to incorporate this feedback.

The most common journal in which submitted abstracts were subsequently published was Hospital Pediatrics, representing twice as many published manuscripts as the second most frequent journal, Pediatrics. Hospital Pediatrics, which was first published in 2011, did not have an impact factor assigned during the study period. Yet, as a peer-reviewed journal dedicated to the field of PHM, it is well aligned with the research presented at the PHM meeting. It is unclear if Hospital Pediatrics is a journal to which pediatric hospitalists tend to submit manuscripts initially or if manuscripts are frequently submitted elsewhere prior to their publication in Hospital Pediatrics. Submission to other journals first likely extends the time to publication, especially for abstracts accepted for poster presentation, which may describe studies with less developed methods or results.

This study has several limitations. Previous studies have demonstrated mean time to publication of 12 to 32 months following abstract presentation with a median time of 19.6 months.¹⁶ Because we only have a 30-month follow-up, there may be abstracts still in the review process that are yet to be published, especially because the length of the review process varies by journal. We based our literature search on the first author of each PHM conference abstract submission, assuming that this presenting author would be one of the publishing authors even if not remaining first author; if this was not the case, we may have missed some abstracts that were subsequently published in full. Likewise, if a presenting author’s last name changed prior to the publication of a manuscript, a publication may have been missed. This limitation would cause us to underestimate the overall publication rate. It is not clear whether this would differentially affect the method of presentation. However, in this study, there was concordance between the presenting author and the publication’s first author in 87.8% of the abstracts subsequently published in full. Presenting authors who did not remain the first author on the published manuscript maintained authorship as either the senior author or second or third author, which may represent changes in the degree of involvement or a division of responsibilities for individuals working on a project together. While our search methods were comprehensive, there is a possibility that abstracts may have been published in a venue that was not searched. Additionally, we only reviewed abstracts submitted to PHM for 1 year. As the field matures and the number of fellowship programs increases, the quality of submitted abstracts may increase, leading to higher publication rates or shorter times to publication. It is also possible that the publication rate may not be reflective of PHM as a field because hospitalists may submit their work to conferences other than the PHM. Lastly, it may be more challenging to interpret any differences in impact factor because some journals, including Hospital Pediatrics (which represented a plurality of poster presentation abstracts that were subsequently published and is a relatively new journal), did not have an impact factor assigned during the study period. Assigning a 0 to journals without an impact factor may artificially lower the average impact factor reported. Furthermore, an impact factor, which is based on the frequency with which an individual journal’s articles are cited in scientific or medical publications, may not necessarily reflect a journal’s quality.

Of the 226 abstracts submitted to the 2014 PHM conference, approximately one-third were published in peer-reviewed journals within 30 months of the conference. Selection for oral presentation was found to be associated with subsequent publication as well as publication in journals with higher impact factors. The overall low publication rate may indicate a need for increased mentorship and resources for research development in this growing specialty. Improved mechanisms for author feedback at poster sessions may provide constructive suggestions for further development of these projects into full manuscripts or opportunities for trainees and early-career hospitalists to network with more experienced researchers in the field.

Disclosure

Drs. Herrmann, Hall, Kyler, Andrews, Williams, and Shah and Mr. Cochran have nothing to disclose. Dr. Wilson reports personal fees from the American Academy of Pediatrics during the conduct of the study. The authors have no financial relationships relevant to this article to disclose.

Pediatric hospital medicine (PHM) is one of the most rapidly growing disciplines in pediatrics,¹ with 8% of pediatric residency graduates each year entering the field.² Research plays an important role in advancing care in the field and is a critical component for board certification and fellowship accreditation.^3-6 The annual PHM conference, which has been jointly sponsored by the Academic Pediatric Association, the American Academy of Pediatrics, and the Society of Hospital Medicine, is an important venue for the dissemination of research findings. Abstract selection is determined by peer review; however, reviewers are provided with only a brief snapshot of the research, which may not contain sufficient information to fully evaluate the methodological quality of the work.^7-10 Additionally, while instructions are provided, reviewers often lack formal training in abstract review. Consequently, scores may vary.⁹

Publication in a peer-reviewed journal is considered a measure of research success because it requires more rigorous peer review than the abstract selection process at scientific meetings.^11-16 Rates of subsequent journal publication differ based on specialty and meeting, and they have been reported at 23% to 78%.^10,12,14-18 In pediatrics, publication rates after presentation at scientific meetings range from 36% to 63%, with mean time to publication ranging from 20 to 26 months following the meeting.^11,19,20 No studies have reviewed abstract submissions to the annual PHM meeting to determine if selection or presentation format is associated with subsequent publication in a peer-reviewed journal.

We sought to identify the publication rate of abstracts submitted to the 2014 PHM conference and determine whether presentation format was associated with the likelihood of subsequent journal publication or time to publication.

Study Design

Data for this retrospective cohort study were obtained from a database of all abstracts submitted for presentation at the 2014 PHM conference in Lake Buena Vista, Florida.

Main Exposures

The main exposure was presentation format, which was categorized as not presented (ie, rejected), poster presentation, or oral presentation. PHM has a blinded abstract peer-review process; in 2014, an average of 10 reviewers scored each abstract. Reviewers graded abstracts on a scale of 1 (best in category) to 7 (unacceptable for presentation) according to the following criteria: originality, scientific importance, methodological rigor, and quality of presentation. Abstracts with the lowest average scores in each content area, usually less than or equal to 3, were accepted as oral presentations while most abstracts with scores greater than 5 were rejected. For this study, information collected from each abstract included authors, if the primary author was a trainee, title, content area, and presentation format. Content areas included clinical research, educational research, health services research (HSR) and/or epidemiology, practice management research, and quality improvement. Abstracts were then grouped by presentation format and content area for analysis. The Pediatric Academic Societies (PAS) annual meeting, another common venue for the presentation of pediatric research, precedes the PHM conference. Because acceptance for PAS presentation may represent more strongly developed abstract submissions for PHM, we identified which abstracts had also been presented at the PAS conference that same year by cross-referencing authors and abstract titles with the PAS 2014 program.

Main Outcome Measures

All submissions were assessed for subsequent publication in peer-reviewed journals through January 2017 (30 months following the July 2014 PHM conference). To identify abstracts that went on to full publication, 2 authors (JC and LEH) independently searched for the lead author’s name and the presentation title in PubMed, Google Scholar, and MedEdPORTAL in January 2017. PubMed was searched using both the general search box and an advanced search for author and title. Google Scholar was added to capture manuscripts that may not have been indexed in PubMed at the time of our search. MedEdPORTAL, a common venue for the publication of educational initiatives that are not currently indexed in PubMed, was searched by lead author name via the general search box. If a full manuscript was published discussing similar outcomes or results and was written by the same authors who had submitted a PHM conference abstract, it was considered to have been published. The journal, month, and year of publication were recorded. For journals published every 2 months, the date of publication was recorded as falling between the 2 months. For those journals with biannual publication in the spring and fall, the months of March and October were used, respectively. The impact factor of the publication journal was also recorded for the year preceding publication. A journal’s impact factor is frequently used as a quantitative measure of journal quality and reflects the frequency with which a journal’s articles are cited in the scientific literature.²¹ Journals without an impact factor (eg, newer journals) were assigned a 0.

Data Analysis

All abstracts submitted to the PHM conference were analyzed based on content area and presentation format. The proportion of all abstracts subsequently published was determined for each format type and content area, and the odds ratio (OR) for publication after abstract submission was calculated using logistic regression. We calculated an adjusted OR for subsequent publication controlling for PAS presentation and the trainee status of the primary author. The journals most frequently publishing abstracts submitted to the PHM conference were identified. Median time to publication was calculated using the number of months elapsed between the PHM conference and publication date and compared across all abstract formats using Cox proportional hazards models adjusted for PAS presentation and trainee status. Kaplan-Meier survival curves were also generated for each of the 3 formats and compared using log-rank tests. The median impact factor was determined for each abstract format and compared using Wilcoxon rank-sum tests. Median impact factor by content area was compared using a Kruskal-Wallis test. All statistical analyses were performed using SAS version 9.2 (SAS Institute, Cary, NC). P values < 0.05 were considered statistically significant. In accordance with the Common Rule²² and the policies of the Cincinnati Children’s Hospital Medical Center Institutional Review Board, this research was not considered human subjects research.

For the 2014 PHM meeting, 226 abstracts were submitted, of which 183 (81.0%) were selected for presentation, including 154 (68.0%) as poster presentations and 29 (12.8%) as oral presentations. Of all submitted abstracts, 82 (36.3%) were published within 30 months following the meeting. Eighty-one of these (98.8%) were identified via PubMed, and 1 was found only in MedEdPORTAL. No additional publications were found via Google Scholar. The presenting author for the PHM abstract was the first author for 87.8% (n = 72) of the publications. A trainee was the presenting author for only 2 of these abstracts. For the publications in which the first author was not the presenting author, the presenting author was the senior author in 2 of the publications and the second or third author on the remaining 8. Of the abstracts accepted for presentation, 70 (38.3%) were subsequently published. Abstracts accepted for oral presentation had almost 7-fold greater odds of subsequent publication than those that were rejected (Table 1; OR 6.8; 95% confidence interval [CI], 2.4-19.4). Differences in the odds of publication for rejected abstracts compared with those accepted for poster presentation were not statistically significant (OR 1.2; 95% CI, 0.5-2.5).

About one-third of abstracts submitted to the 2014 PHM conference were subsequently published in peer-reviewed journals within 30 months of the conference. Compared with rejected abstracts, the rate of publication was significantly higher for abstracts selected for oral presentation but not for those selected for poster presentation. For abstracts ultimately published in journals, selection for oral presentation was significantly associated with both a shorter time to publication and a higher median journal impact factor compared with rejected abstracts. Time to publication and median journal impact factor were similar between rejected abstracts and those accepted for poster presentation. Our findings suggest that abstract reviewers may be able to identify which abstracts will ultimately withstand more stringent peer review in the publication process when accepting abstracts for oral presentation. However, the selection for poster presentation versus rejection may not be indicative of future publication or the impact factor of the subsequent publication journal.

Previous studies have reviewed publication rates after meetings of the European Society for Pediatric Urology (publication rate of 47%),¹¹ the Ambulatory Pediatric Association (now the Academic Pediatric Association; publication rate of 47%), the American Pediatric Society/Society for Pediatric Research (publication rate of 54%), and the PAS (publication rate of 45%).^19,20 Our lower publication rate of 36.3% may be attributed to the shorter follow-up time in our study (30 months from the PHM conference), whereas prior studies monitored for publication up to 60 months after the PAS conference.²⁰ Factors associated with subsequent publication include statistically significant results, a large sample size, and a randomized controlled trial study design.^15,16 The primary reason for nonpublication for up to 80% of abstracts is failure to submit a manuscript for publication.²³ A lack of time and fear of rejection after peer review are commonly cited explanations.^18,23,24 Individuals may view acceptance for an oral presentation as positive reinforcement and be more motivated to pursue subsequent manuscript publication than individuals whose abstracts are offered poster presentations or are rejected. Trainees frequently present abstracts at scientific meetings, representing 40.3% of primary authors submitting abstracts to PHM in 2014, but may not have sufficient time or mentorship to develop a complete manuscript.¹⁸ To our knowledge, there have been no publications that assess the impact of trainee status on subsequent publication after conference submission.

Our study demonstrated that selection for oral presentation was associated with subsequent publication, shorter time to publication, and publication in journals with higher impact factors. A 2005 Cochrane review also demonstrated that selection for oral presentation was associated with subsequent journal publication.¹⁶ Abstracts accepted for oral publication may represent work further along in the research process, with more developed methodology and results. The shorter time to publication for abstracts accepted for oral presentation could also reflect feedback provided by conference attendees after the presentation, whereas poster sessions frequently lack a formalized process for critique.

Carroll et al. found no difference in time to publication between abstracts accepted for presentation at the PAS and rejected abstracts.²⁰ Previous studies demonstrate that most abstracts presented at scientific meetings that are subsequently accepted for publication are published within 2 to 3 years of the meeting,¹² with publication rates as high as 98% within 3 years of presentation.¹⁷ In contrast to Carroll et al., we found that abstracts accepted for oral presentation had a 4-fold greater likelihood of publication at each month than rejected abstracts. However, abstracts accepted for poster presentation did not have a significant difference in the proportional hazard ratio models for publication compared with rejected abstracts. Because space considerations limit the number of abstracts that can be accepted for presentation at a conference, some abstracts that are suitable for future publication may have been rejected due to a lack of space. Because researchers often use scientific meetings as a forum to receive peer feedback,¹² authors who present at conferences may take more time to write a manuscript in order to incorporate this feedback.

The most common journal in which submitted abstracts were subsequently published was Hospital Pediatrics, representing twice as many published manuscripts as the second most frequent journal, Pediatrics. Hospital Pediatrics, which was first published in 2011, did not have an impact factor assigned during the study period. Yet, as a peer-reviewed journal dedicated to the field of PHM, it is well aligned with the research presented at the PHM meeting. It is unclear if Hospital Pediatrics is a journal to which pediatric hospitalists tend to submit manuscripts initially or if manuscripts are frequently submitted elsewhere prior to their publication in Hospital Pediatrics. Submission to other journals first likely extends the time to publication, especially for abstracts accepted for poster presentation, which may describe studies with less developed methods or results.

This study has several limitations. Previous studies have demonstrated mean time to publication of 12 to 32 months following abstract presentation with a median time of 19.6 months.¹⁶ Because we only have a 30-month follow-up, there may be abstracts still in the review process that are yet to be published, especially because the length of the review process varies by journal. We based our literature search on the first author of each PHM conference abstract submission, assuming that this presenting author would be one of the publishing authors even if not remaining first author; if this was not the case, we may have missed some abstracts that were subsequently published in full. Likewise, if a presenting author’s last name changed prior to the publication of a manuscript, a publication may have been missed. This limitation would cause us to underestimate the overall publication rate. It is not clear whether this would differentially affect the method of presentation. However, in this study, there was concordance between the presenting author and the publication’s first author in 87.8% of the abstracts subsequently published in full. Presenting authors who did not remain the first author on the published manuscript maintained authorship as either the senior author or second or third author, which may represent changes in the degree of involvement or a division of responsibilities for individuals working on a project together. While our search methods were comprehensive, there is a possibility that abstracts may have been published in a venue that was not searched. Additionally, we only reviewed abstracts submitted to PHM for 1 year. As the field matures and the number of fellowship programs increases, the quality of submitted abstracts may increase, leading to higher publication rates or shorter times to publication. It is also possible that the publication rate may not be reflective of PHM as a field because hospitalists may submit their work to conferences other than the PHM. Lastly, it may be more challenging to interpret any differences in impact factor because some journals, including Hospital Pediatrics (which represented a plurality of poster presentation abstracts that were subsequently published and is a relatively new journal), did not have an impact factor assigned during the study period. Assigning a 0 to journals without an impact factor may artificially lower the average impact factor reported. Furthermore, an impact factor, which is based on the frequency with which an individual journal’s articles are cited in scientific or medical publications, may not necessarily reflect a journal’s quality.

Of the 226 abstracts submitted to the 2014 PHM conference, approximately one-third were published in peer-reviewed journals within 30 months of the conference. Selection for oral presentation was found to be associated with subsequent publication as well as publication in journals with higher impact factors. The overall low publication rate may indicate a need for increased mentorship and resources for research development in this growing specialty. Improved mechanisms for author feedback at poster sessions may provide constructive suggestions for further development of these projects into full manuscripts or opportunities for trainees and early-career hospitalists to network with more experienced researchers in the field.

Disclosure

Drs. Herrmann, Hall, Kyler, Andrews, Williams, and Shah and Mr. Cochran have nothing to disclose. Dr. Wilson reports personal fees from the American Academy of Pediatrics during the conduct of the study. The authors have no financial relationships relevant to this article to disclose.

Healthcare systems are targeting effective strategies to improve patient safety and reduce hospital readmissions. Hospital readmissions can be detrimental to patients’ health, a source of avoidable healthcare costs, and are frequently a reflection of the quality of patient care during transitions of care. Medication reconciliation (Med Rec) was identified as 1 of 12 interventions that may reduce 30-day readmissions; however, rigorously designed studies are scarce.^1,2 Published systematic reviews and meta-analyses have produced mixed conclusions regarding the impact of Med Rec on unplanned 30-day readmissions.^2-4

In several studies, researchers have established the positive impact of Med Rec on reducing patient medication discrepancies and potential adverse drug events.^4-8 Pharmacy-led Med Rec interventions have been shown to easily identify more clinically relevant and higher impact medication discrepancies when compared to usual care.⁸ In a systematic review, Mueller et al.² suggest that there are several interrelated elements that determine if a Med Rec intervention will influence hospital readmissions. These elements form a multicomponent “bundle” of interventions, including a systematic medication history process, admission reconciliation, patient education on discharge, discharge reconciliation, and communication to outpatient providers.⁹ Several prospective randomized controlled studies have demonstrated lower readmission rates and fewer visits to the emergency department (ED) after implementing a comprehensive, interprofessional, bundled intervention (including Med Rec) from admission to discharge.^10-13 A 2016 systematic review and meta-analysis specifically evaluated pharmacy-led Med Rec programs (the majority of which included interventions involving multicomponent bundles) and demonstrated a significant reduction in posthospital healthcare utilization.¹⁴

Although comprehensive, interprofessional, bundled interventions have been shown to reduce readmission rates and ED visits in randomized controlled trials (RCTs), limited resources often prevent hospitals from consistently implementing all aspects of these multicomponent interventions. In practice, clinicians may provide varying components of the bundle, such as the combination of admission medication history by the pharmacist and discharge Med Rec completed by the physician alone. The unique impact of combined pharmacist and prescriber Med Rec interventions from admission to discharge on readmissions remains inconclusive. Further, it is unclear which high-risk patient groups will benefit the most from these interventions. We set out to evaluate the impact of an enhanced, interprofessional Med Rec process from admission to discharge (characterized within the context of a novel taxonomy continuum that specifies clinician involvement and intensity of services) on readmissions to hospital and ED visits within 30 days of discharge.

We conducted a retrospective, observational, analytical cohort study using QuadraMed’s Computerized Patient Record and the EMITT (Electronic Medication Information Transfer Tool)¹⁵ to collect data from 2007 to 2011.

Setting

The study was conducted at a 417-bed tertiary care teaching hospital in Toronto, Ontario, Canada.

Med Rec Process and Description of Exposure (Intervention)

The targeted clinical areas had sustained interprofessional models of patient care in place from admission to discharge. They also were actively using an in-house EMITT to facilitate the documentation and tracking of Med Rec efforts throughout patient admission, transfer, and discharge.¹⁵ On admission, the pharmacist conducted a best possible medication history (BPMH). A BPMH provides the cornerstone for Med Rec. It differs from a routine medication history in that it involves (1) a systematic process for interviewing the patient (or family) and (2) a review of at least one other reliable source of information (eg, a provincial medication database, an inspection of medication vials, or contact with the community pharmacy) to obtain and verify patient medications (prescribed and nonprescribed). The pharmacist recorded the BPMH in the electronic patient record. The application supported admission and discharge Med Rec. On discharge, there were 2 options: (1) the prescriber alone would review and complete the discharge Med Rec and generate electronic prescriptions (Table 1, Silver level care) or (2) the pharmacist would collaborate with the prescriber to complete the discharge reconciliation and the prescriber would electronically generate prescriptions (Table 1, Gold level care). All clinical areas had a combined pharmacist and prescriber Med Rec model in place at admission, but the proportion of patients receiving discharge reconciliation completed by pharmacist and prescriber versus the prescriber-alone varied based on the individual clinician’s practices.

Patient Selection

All consecutive hospitalized patients admitted and discharged by the general internal medicine [GIM] service from March 2007 to December 2011 were included. The GIM service was chosen for the main analysis because they had been performing the intervention for the longest period of time and had the largest population of patients. Patients were identified via their hospital-specific medical record identification number and specific hospital-visit number. Patients were excluded if any of the following occurred: (1) the length of stay of their index admission was less than 24 hours; (2) they died during the visit; (3) they were transferred to a separate acute care inpatient facility; or (4) they left hospital against medical advice. Patient visits were excluded as index cases from the analysis if they were returning within 90 days of a previous discharge.

Outcomes

The primary study outcome was the occurrence of an inpatient readmission or ED visit within 30 days of discharge. In our secondary analyses, we examined the impact of the intervention on high-risk patient populations, such as those ≥65 years of age, with a length of stay, acuity of admission, Charlson comorbidity index, and emergency department visits in past 6 months (LACE) index score ≥10 (see supplementary Appendix 1 for LACE score description), on high-alert medications (1 or more of warfarin, insulin, digoxin, and opioids), and on ≥10 medications.

Data Collection

Identification of Exposure of Interest

We used the electronic database to capture all patients who received pharmacist and prescriber supported admission-to-discharge reconciliation. We explicitly defined increasing intensity of Med Rec care in categories of Bronze, Silver, and Gold care levels (Table 1). The exposed (intervention) group received an enhanced Med Rec bundle (patients receiving Gold level care). The control group was made of patients receiving a partial Med Rec Bundle (patients receiving Silver or Bronze level of care or below).

Determination of Hospital Visits

A search of administrative databases was used to determine if patients admitted to the targeted services had an ED visit or urgent inpatient admission to the study hospital within 30 days.

Statistical Analysis

A logistic regression for outcomes was performed. This yielded an adjusted odds ratio with a 95% confidence interval (CI) between the intervention and control groups. Statistical significance was determined with a 2-sided α level of 0.05. In the analysis, we used Statistical Analysis Software version 9.2.

In our multivariate logistic regression model, we adjusted for confounding factors that might influence the patients’ risk of readmission or the type of Med Rec they received upon discharge. By using administrative databases, patient level demographics, and the Charlson comorbidity index, the most responsible diagnosis and disease burden were collected. Medication-related factors collected included the number of medications on discharge and the presence of predefined high-alert medications. The number of medications on the medication discharge list was determined by using the electronic database. The final adjustment model included age, gender, the number of medications on discharge, and the LACE index score (supplementary Appendix 1). The LACE index score has been validated in Ontario, Canada, populations to quantify the risk of death or unplanned readmission within 30 days of discharge.²⁴

Propensity Score Adjustment

Propensity scoring (probability of treatment assignment conditional on observed baseline characteristics) was planned a priori to account for possible factors that would impact whether a patient received the intervention or control care levels. The propensity score for receiving Med Rec was computed from a logistic model using Med Rec as the outcome. A structured iterative approach was used to refine this model to achieve covariate balance within the matched pairs. Covariate balance was measured by the standardized difference, in which an absolute standardized difference >10% represents meaningful imbalance.²⁵ From the original cohort, we attempted to match patients who had the intervention to patients from the control by means of a matching algorithm using the logit of the propensity score for receiving the intervention.²⁶

Subgroup Analysis

We also examined the impact of the intervention on high-risk patient populations such as those ≥65 years of age, with a LACE index score ≥10, on high-alert medications, and on ≥10 medications. A univariate analysis was conducted to identify patient-related risk predictors that may be independently correlated with a higher risk of hospital visits.

Baseline Characteristics

A total of 8678 patients representing 9931 unique visits met the inclusion criteria for analysis. There were 2541 unique visits (approximately 26% of visits) in the intervention group that received Gold level care and 7390 unique visits in the control group. The patients in the control group were largely patients who received the original standard of care at the institution, Silver level care (67% of the control group). Patients who received Bronze level care or less comprised 33% of the control group.

Patients in the intervention group were significantly older (average of 68 years old versus 64 years old) and on more medications. They also notably had a longer duration of stay in hospital, an increased percentage of visits with a LACE index score ≥10, and were more likely to be discharged home on a high-alert medication and with supports (Table 2).

Main Analysis

The main unadjusted analysis of GIM patients (n = 9931 visits) did not detect a difference in 30-day ED visits and readmissions between the intervention group (540 out of 2541; 21.2%) and control (1423 out of 7390; 19.3%; Table 3). By using a multivariate logistic regression model to account for age, sex, LACE index, and number of medications on discharge, the adjusted odds ratio was 1.06 (95% CI, 0.95-1.19; P = 0.33). After propensity score adjustment, the relative risk of readmission was 0.88 (16.7% vs 18.9%; 95% CI, 0.59-1.32; P = 0.54).

Secondary Analyses

In each predefined high-risk patient subgroup (age ≥65, LACE index score ≥10, number of discharge medications ≥10, and the presence of high-alert medications), analyses of our primary endpoint did not detect significant adjusted odds ratios (Table 4). In our univariate analysis, increasing number of medications, LACE index score, and male gender were independently correlated with a higher risk of hospital visits (supplementary Appendix 2).

Med Rec is widely recommended as a patient safety strategy to prevent clinically significant medication discrepancies at transitions in care.^4-9 However, Med Rec varies widely in terms of what it entails and who delivers it, with the preponderance of evidence suggesting an impact on clinically significant medication discrepancies only when interprofessional care delivered includes a central role for pharmacists.²⁷ Furthermore, Med Rec appears to impact short term readmissions only when embedded in a broader, multifaceted, bundled intervention in which pharmacists or other team members educate patients about their medications and deliver postdischarge follow-up phone calls.^10-13

As very few hospitals have the resources to sustainably deliver intensive care bundles that are represented in RCTs (characterized by Platinum and Diamond levels of care in Table 1), in our observational study, we sought to explore whether a resource-attainable, enhanced Med Rec care bundle (Gold level) had an impact on hospital utilization compared to partial Med Rec care bundles (Bronze and Silver levels). In our findings, we did not detect a significant difference on ED visits and readmissions within 30 days between enhanced and partial care bundles. In a secondary analysis of the influence of the intervention on prespecified high-risk patient subgroups, we also did not detect a difference.

As far as we are aware, our long-term, observational study is the largest to date to explore a real-life, enhanced Med Rec intervention and examine its impact on meaningful patient outcomes. We extrapolated that our intervention group received several critical attributes of a successful bundle as discussed by Mueller in a systematic review.² Our intervention included the following: (1) a systematic BPMH process on admission; (2) integrated admission-to-discharge reconciliation processes; (3) discharge delineation of medication changes since admission; (4) pharmacist involvement in reconciliation from admission to discharge; (5) an electronic platform; and (6) formal discharge reconciliation with interprofessional collaboration. Additional components in the bundle described by Mueller included the following: patient education at discharge, postdischarge communication with the patient, and communication with outpatient providers and medication management.

In our results, we did not find a difference in outcomes between the intervention and control groups. Therefore, it is possible that the enhanced bundle’s focus on interprofessional involvement in discharge reconciliation (Gold care level) has no impact on hospital utilization compared to partial care bundles (Silver and Bronze levels). Kwan et al.³ describe similar findings in their systematic review, in which they evaluated the effects of hospital-based Med Rec on unintentional discrepancies with nontrivial risks for harm to patients on 30-day postdischarge hospital visits. Kwan et al.³ concluded that larger well-designed studies are required to further evaluate this outcome, but authors of current published studies suggest that Med Rec alone probably does not reduce postdischarge hospital utilization within 30 days. Med Rec may have a more significant impact on utilization when bundled with other interventions that improve discharge coordination.³

There may be several reasons why we were unable to detect a significant difference between the intervention and control groups. One limitation is that our nonrandomized, retrospective design may have led to unmeasured confounders that impacted allocation into the intervention group versus the control group. It was notable that patients in the intervention group had an increased age, longer duration of hospital stay, more medications, and high-alert medications on discharge compared to the control group and that may have biased our results towards the null hypothesis. Although the propensity score analysis attempted to adjust for this, it also did not detect a significant difference between groups.

In addition, the existing standard of care during the study period allowed for patients in the control group to receive varying levels of Med Rec. Ideally, we would have compared the intervention to a placebo group that did not receive any Med Rec-related care elements. However, as this was a real-life observational study, the majority of patients received some Med Rec services as a part of the standard of care. As a result, 67% of patients in the control group received Silver level Med Rec with a BPMH, admission reconciliation, and prescriber-only discharge reconciliation. This may have made it more difficult to show an incremental benefit on readmissions between the intervention and control.

Also, our primary outcome of all-cause ED or hospital readmissions within 30 days may not have been sensitive enough to detect the effect of Med Rec interventions alone. Only a small proportion of readmissions within 30 days of discharge are preventable and many patient and community level factors responsible for readmissions cannot be controlled by the hospital’s actions.²⁸ Comprehensive pharmacy interventions have demonstrated decreased hospitalizations and emergency visits at 12 months; however, the largest impact was seen on the more specific outcome of medication-related hospitalizations (80% reduction).²⁹ Lastly, another limitation was that we were unable to capture hospital visits to other centres. However, in our region, almost 75% of readmissions are to the same site as the initial hospitalization.³⁰

Overall, our findings in this study and novel characterization of Med Rec services are relevant to many hospital sites that are striving to implement integrated Med Rec with limited healthcare resources. Although interprofessional Med Rec likely reduces clinically significant medication discrepancies, enhanced interprofessional Med Rec on discharge (Gold Med Rec) alone may not be enough to impact hospital utilization compared to partial Med Rec services (Silver and Bronze Med Rec). Further research into practical, targeted Med Rec bundles on more specific outcomes (such as preventable postdischarge adverse events, “avoidable” hospital readmissions, and medication-related readmissions) may detect a significant benefit.

A long-term observational evaluation of interprofessional Med Rec did not detect a difference in 30-day postdischarge patient hospital visits between patients who received enhanced versus partial Med Rec patient care bundles. Researchers of future prospective studies could focus on evaluating high-risk populations or specific elements of Med Rec services on avoidable medication-related hospital admissions and postdischarge adverse drug events.

Acknowledgments

The authors thank Nita Dhir, MBA.

Presented as a poster and oral presentation at the 2012 American College of Clinical Pharmacy Annual Meeting, Hollywood, Florida, October 21-24, 2012, and as an encore poster presentation at the Canadian Society of Hospital Pharmacists Professional Practice Conference, Toronto, Canada, Feb 3, 2013.

Disclosure

The authors declare no conflicts of interest related to the manuscript submitted. All monies used for the research came from the University Health Network Department of Pharmacy Budget, including the pharmacy residency program.

Healthcare systems are targeting effective strategies to improve patient safety and reduce hospital readmissions. Hospital readmissions can be detrimental to patients’ health, a source of avoidable healthcare costs, and are frequently a reflection of the quality of patient care during transitions of care. Medication reconciliation (Med Rec) was identified as 1 of 12 interventions that may reduce 30-day readmissions; however, rigorously designed studies are scarce.^1,2 Published systematic reviews and meta-analyses have produced mixed conclusions regarding the impact of Med Rec on unplanned 30-day readmissions.^2-4

In several studies, researchers have established the positive impact of Med Rec on reducing patient medication discrepancies and potential adverse drug events.^4-8 Pharmacy-led Med Rec interventions have been shown to easily identify more clinically relevant and higher impact medication discrepancies when compared to usual care.⁸ In a systematic review, Mueller et al.² suggest that there are several interrelated elements that determine if a Med Rec intervention will influence hospital readmissions. These elements form a multicomponent “bundle” of interventions, including a systematic medication history process, admission reconciliation, patient education on discharge, discharge reconciliation, and communication to outpatient providers.⁹ Several prospective randomized controlled studies have demonstrated lower readmission rates and fewer visits to the emergency department (ED) after implementing a comprehensive, interprofessional, bundled intervention (including Med Rec) from admission to discharge.^10-13 A 2016 systematic review and meta-analysis specifically evaluated pharmacy-led Med Rec programs (the majority of which included interventions involving multicomponent bundles) and demonstrated a significant reduction in posthospital healthcare utilization.¹⁴

Although comprehensive, interprofessional, bundled interventions have been shown to reduce readmission rates and ED visits in randomized controlled trials (RCTs), limited resources often prevent hospitals from consistently implementing all aspects of these multicomponent interventions. In practice, clinicians may provide varying components of the bundle, such as the combination of admission medication history by the pharmacist and discharge Med Rec completed by the physician alone. The unique impact of combined pharmacist and prescriber Med Rec interventions from admission to discharge on readmissions remains inconclusive. Further, it is unclear which high-risk patient groups will benefit the most from these interventions. We set out to evaluate the impact of an enhanced, interprofessional Med Rec process from admission to discharge (characterized within the context of a novel taxonomy continuum that specifies clinician involvement and intensity of services) on readmissions to hospital and ED visits within 30 days of discharge.

We conducted a retrospective, observational, analytical cohort study using QuadraMed’s Computerized Patient Record and the EMITT (Electronic Medication Information Transfer Tool)¹⁵ to collect data from 2007 to 2011.

Setting

The study was conducted at a 417-bed tertiary care teaching hospital in Toronto, Ontario, Canada.

Med Rec Process and Description of Exposure (Intervention)

The targeted clinical areas had sustained interprofessional models of patient care in place from admission to discharge. They also were actively using an in-house EMITT to facilitate the documentation and tracking of Med Rec efforts throughout patient admission, transfer, and discharge.¹⁵ On admission, the pharmacist conducted a best possible medication history (BPMH). A BPMH provides the cornerstone for Med Rec. It differs from a routine medication history in that it involves (1) a systematic process for interviewing the patient (or family) and (2) a review of at least one other reliable source of information (eg, a provincial medication database, an inspection of medication vials, or contact with the community pharmacy) to obtain and verify patient medications (prescribed and nonprescribed). The pharmacist recorded the BPMH in the electronic patient record. The application supported admission and discharge Med Rec. On discharge, there were 2 options: (1) the prescriber alone would review and complete the discharge Med Rec and generate electronic prescriptions (Table 1, Silver level care) or (2) the pharmacist would collaborate with the prescriber to complete the discharge reconciliation and the prescriber would electronically generate prescriptions (Table 1, Gold level care). All clinical areas had a combined pharmacist and prescriber Med Rec model in place at admission, but the proportion of patients receiving discharge reconciliation completed by pharmacist and prescriber versus the prescriber-alone varied based on the individual clinician’s practices.

Patient Selection

All consecutive hospitalized patients admitted and discharged by the general internal medicine [GIM] service from March 2007 to December 2011 were included. The GIM service was chosen for the main analysis because they had been performing the intervention for the longest period of time and had the largest population of patients. Patients were identified via their hospital-specific medical record identification number and specific hospital-visit number. Patients were excluded if any of the following occurred: (1) the length of stay of their index admission was less than 24 hours; (2) they died during the visit; (3) they were transferred to a separate acute care inpatient facility; or (4) they left hospital against medical advice. Patient visits were excluded as index cases from the analysis if they were returning within 90 days of a previous discharge.

Outcomes

The primary study outcome was the occurrence of an inpatient readmission or ED visit within 30 days of discharge. In our secondary analyses, we examined the impact of the intervention on high-risk patient populations, such as those ≥65 years of age, with a length of stay, acuity of admission, Charlson comorbidity index, and emergency department visits in past 6 months (LACE) index score ≥10 (see supplementary Appendix 1 for LACE score description), on high-alert medications (1 or more of warfarin, insulin, digoxin, and opioids), and on ≥10 medications.

Data Collection

Identification of Exposure of Interest

We used the electronic database to capture all patients who received pharmacist and prescriber supported admission-to-discharge reconciliation. We explicitly defined increasing intensity of Med Rec care in categories of Bronze, Silver, and Gold care levels (Table 1). The exposed (intervention) group received an enhanced Med Rec bundle (patients receiving Gold level care). The control group was made of patients receiving a partial Med Rec Bundle (patients receiving Silver or Bronze level of care or below).

Determination of Hospital Visits

A search of administrative databases was used to determine if patients admitted to the targeted services had an ED visit or urgent inpatient admission to the study hospital within 30 days.

Statistical Analysis

A logistic regression for outcomes was performed. This yielded an adjusted odds ratio with a 95% confidence interval (CI) between the intervention and control groups. Statistical significance was determined with a 2-sided α level of 0.05. In the analysis, we used Statistical Analysis Software version 9.2.

In our multivariate logistic regression model, we adjusted for confounding factors that might influence the patients’ risk of readmission or the type of Med Rec they received upon discharge. By using administrative databases, patient level demographics, and the Charlson comorbidity index, the most responsible diagnosis and disease burden were collected. Medication-related factors collected included the number of medications on discharge and the presence of predefined high-alert medications. The number of medications on the medication discharge list was determined by using the electronic database. The final adjustment model included age, gender, the number of medications on discharge, and the LACE index score (supplementary Appendix 1). The LACE index score has been validated in Ontario, Canada, populations to quantify the risk of death or unplanned readmission within 30 days of discharge.²⁴

Propensity Score Adjustment

Propensity scoring (probability of treatment assignment conditional on observed baseline characteristics) was planned a priori to account for possible factors that would impact whether a patient received the intervention or control care levels. The propensity score for receiving Med Rec was computed from a logistic model using Med Rec as the outcome. A structured iterative approach was used to refine this model to achieve covariate balance within the matched pairs. Covariate balance was measured by the standardized difference, in which an absolute standardized difference >10% represents meaningful imbalance.²⁵ From the original cohort, we attempted to match patients who had the intervention to patients from the control by means of a matching algorithm using the logit of the propensity score for receiving the intervention.²⁶

Subgroup Analysis

We also examined the impact of the intervention on high-risk patient populations such as those ≥65 years of age, with a LACE index score ≥10, on high-alert medications, and on ≥10 medications. A univariate analysis was conducted to identify patient-related risk predictors that may be independently correlated with a higher risk of hospital visits.

Baseline Characteristics

A total of 8678 patients representing 9931 unique visits met the inclusion criteria for analysis. There were 2541 unique visits (approximately 26% of visits) in the intervention group that received Gold level care and 7390 unique visits in the control group. The patients in the control group were largely patients who received the original standard of care at the institution, Silver level care (67% of the control group). Patients who received Bronze level care or less comprised 33% of the control group.

Patients in the intervention group were significantly older (average of 68 years old versus 64 years old) and on more medications. They also notably had a longer duration of stay in hospital, an increased percentage of visits with a LACE index score ≥10, and were more likely to be discharged home on a high-alert medication and with supports (Table 2).

Main Analysis

The main unadjusted analysis of GIM patients (n = 9931 visits) did not detect a difference in 30-day ED visits and readmissions between the intervention group (540 out of 2541; 21.2%) and control (1423 out of 7390; 19.3%; Table 3). By using a multivariate logistic regression model to account for age, sex, LACE index, and number of medications on discharge, the adjusted odds ratio was 1.06 (95% CI, 0.95-1.19; P = 0.33). After propensity score adjustment, the relative risk of readmission was 0.88 (16.7% vs 18.9%; 95% CI, 0.59-1.32; P = 0.54).

Secondary Analyses

In each predefined high-risk patient subgroup (age ≥65, LACE index score ≥10, number of discharge medications ≥10, and the presence of high-alert medications), analyses of our primary endpoint did not detect significant adjusted odds ratios (Table 4). In our univariate analysis, increasing number of medications, LACE index score, and male gender were independently correlated with a higher risk of hospital visits (supplementary Appendix 2).

Med Rec is widely recommended as a patient safety strategy to prevent clinically significant medication discrepancies at transitions in care.^4-9 However, Med Rec varies widely in terms of what it entails and who delivers it, with the preponderance of evidence suggesting an impact on clinically significant medication discrepancies only when interprofessional care delivered includes a central role for pharmacists.²⁷ Furthermore, Med Rec appears to impact short term readmissions only when embedded in a broader, multifaceted, bundled intervention in which pharmacists or other team members educate patients about their medications and deliver postdischarge follow-up phone calls.^10-13

As very few hospitals have the resources to sustainably deliver intensive care bundles that are represented in RCTs (characterized by Platinum and Diamond levels of care in Table 1), in our observational study, we sought to explore whether a resource-attainable, enhanced Med Rec care bundle (Gold level) had an impact on hospital utilization compared to partial Med Rec care bundles (Bronze and Silver levels). In our findings, we did not detect a significant difference on ED visits and readmissions within 30 days between enhanced and partial care bundles. In a secondary analysis of the influence of the intervention on prespecified high-risk patient subgroups, we also did not detect a difference.

As far as we are aware, our long-term, observational study is the largest to date to explore a real-life, enhanced Med Rec intervention and examine its impact on meaningful patient outcomes. We extrapolated that our intervention group received several critical attributes of a successful bundle as discussed by Mueller in a systematic review.² Our intervention included the following: (1) a systematic BPMH process on admission; (2) integrated admission-to-discharge reconciliation processes; (3) discharge delineation of medication changes since admission; (4) pharmacist involvement in reconciliation from admission to discharge; (5) an electronic platform; and (6) formal discharge reconciliation with interprofessional collaboration. Additional components in the bundle described by Mueller included the following: patient education at discharge, postdischarge communication with the patient, and communication with outpatient providers and medication management.

In our results, we did not find a difference in outcomes between the intervention and control groups. Therefore, it is possible that the enhanced bundle’s focus on interprofessional involvement in discharge reconciliation (Gold care level) has no impact on hospital utilization compared to partial care bundles (Silver and Bronze levels). Kwan et al.³ describe similar findings in their systematic review, in which they evaluated the effects of hospital-based Med Rec on unintentional discrepancies with nontrivial risks for harm to patients on 30-day postdischarge hospital visits. Kwan et al.³ concluded that larger well-designed studies are required to further evaluate this outcome, but authors of current published studies suggest that Med Rec alone probably does not reduce postdischarge hospital utilization within 30 days. Med Rec may have a more significant impact on utilization when bundled with other interventions that improve discharge coordination.³

There may be several reasons why we were unable to detect a significant difference between the intervention and control groups. One limitation is that our nonrandomized, retrospective design may have led to unmeasured confounders that impacted allocation into the intervention group versus the control group. It was notable that patients in the intervention group had an increased age, longer duration of hospital stay, more medications, and high-alert medications on discharge compared to the control group and that may have biased our results towards the null hypothesis. Although the propensity score analysis attempted to adjust for this, it also did not detect a significant difference between groups.

In addition, the existing standard of care during the study period allowed for patients in the control group to receive varying levels of Med Rec. Ideally, we would have compared the intervention to a placebo group that did not receive any Med Rec-related care elements. However, as this was a real-life observational study, the majority of patients received some Med Rec services as a part of the standard of care. As a result, 67% of patients in the control group received Silver level Med Rec with a BPMH, admission reconciliation, and prescriber-only discharge reconciliation. This may have made it more difficult to show an incremental benefit on readmissions between the intervention and control.

Also, our primary outcome of all-cause ED or hospital readmissions within 30 days may not have been sensitive enough to detect the effect of Med Rec interventions alone. Only a small proportion of readmissions within 30 days of discharge are preventable and many patient and community level factors responsible for readmissions cannot be controlled by the hospital’s actions.²⁸ Comprehensive pharmacy interventions have demonstrated decreased hospitalizations and emergency visits at 12 months; however, the largest impact was seen on the more specific outcome of medication-related hospitalizations (80% reduction).²⁹ Lastly, another limitation was that we were unable to capture hospital visits to other centres. However, in our region, almost 75% of readmissions are to the same site as the initial hospitalization.³⁰

Overall, our findings in this study and novel characterization of Med Rec services are relevant to many hospital sites that are striving to implement integrated Med Rec with limited healthcare resources. Although interprofessional Med Rec likely reduces clinically significant medication discrepancies, enhanced interprofessional Med Rec on discharge (Gold Med Rec) alone may not be enough to impact hospital utilization compared to partial Med Rec services (Silver and Bronze Med Rec). Further research into practical, targeted Med Rec bundles on more specific outcomes (such as preventable postdischarge adverse events, “avoidable” hospital readmissions, and medication-related readmissions) may detect a significant benefit.

A long-term observational evaluation of interprofessional Med Rec did not detect a difference in 30-day postdischarge patient hospital visits between patients who received enhanced versus partial Med Rec patient care bundles. Researchers of future prospective studies could focus on evaluating high-risk populations or specific elements of Med Rec services on avoidable medication-related hospital admissions and postdischarge adverse drug events.

Acknowledgments

The authors thank Nita Dhir, MBA.

Presented as a poster and oral presentation at the 2012 American College of Clinical Pharmacy Annual Meeting, Hollywood, Florida, October 21-24, 2012, and as an encore poster presentation at the Canadian Society of Hospital Pharmacists Professional Practice Conference, Toronto, Canada, Feb 3, 2013.

Disclosure

The authors declare no conflicts of interest related to the manuscript submitted. All monies used for the research came from the University Health Network Department of Pharmacy Budget, including the pharmacy residency program.

Healthcare systems are targeting effective strategies to improve patient safety and reduce hospital readmissions. Hospital readmissions can be detrimental to patients’ health, a source of avoidable healthcare costs, and are frequently a reflection of the quality of patient care during transitions of care. Medication reconciliation (Med Rec) was identified as 1 of 12 interventions that may reduce 30-day readmissions; however, rigorously designed studies are scarce.^1,2 Published systematic reviews and meta-analyses have produced mixed conclusions regarding the impact of Med Rec on unplanned 30-day readmissions.^2-4

In several studies, researchers have established the positive impact of Med Rec on reducing patient medication discrepancies and potential adverse drug events.^4-8 Pharmacy-led Med Rec interventions have been shown to easily identify more clinically relevant and higher impact medication discrepancies when compared to usual care.⁸ In a systematic review, Mueller et al.² suggest that there are several interrelated elements that determine if a Med Rec intervention will influence hospital readmissions. These elements form a multicomponent “bundle” of interventions, including a systematic medication history process, admission reconciliation, patient education on discharge, discharge reconciliation, and communication to outpatient providers.⁹ Several prospective randomized controlled studies have demonstrated lower readmission rates and fewer visits to the emergency department (ED) after implementing a comprehensive, interprofessional, bundled intervention (including Med Rec) from admission to discharge.^10-13 A 2016 systematic review and meta-analysis specifically evaluated pharmacy-led Med Rec programs (the majority of which included interventions involving multicomponent bundles) and demonstrated a significant reduction in posthospital healthcare utilization.¹⁴

Although comprehensive, interprofessional, bundled interventions have been shown to reduce readmission rates and ED visits in randomized controlled trials (RCTs), limited resources often prevent hospitals from consistently implementing all aspects of these multicomponent interventions. In practice, clinicians may provide varying components of the bundle, such as the combination of admission medication history by the pharmacist and discharge Med Rec completed by the physician alone. The unique impact of combined pharmacist and prescriber Med Rec interventions from admission to discharge on readmissions remains inconclusive. Further, it is unclear which high-risk patient groups will benefit the most from these interventions. We set out to evaluate the impact of an enhanced, interprofessional Med Rec process from admission to discharge (characterized within the context of a novel taxonomy continuum that specifies clinician involvement and intensity of services) on readmissions to hospital and ED visits within 30 days of discharge.

We conducted a retrospective, observational, analytical cohort study using QuadraMed’s Computerized Patient Record and the EMITT (Electronic Medication Information Transfer Tool)¹⁵ to collect data from 2007 to 2011.

Setting

The study was conducted at a 417-bed tertiary care teaching hospital in Toronto, Ontario, Canada.

Med Rec Process and Description of Exposure (Intervention)

The targeted clinical areas had sustained interprofessional models of patient care in place from admission to discharge. They also were actively using an in-house EMITT to facilitate the documentation and tracking of Med Rec efforts throughout patient admission, transfer, and discharge.¹⁵ On admission, the pharmacist conducted a best possible medication history (BPMH). A BPMH provides the cornerstone for Med Rec. It differs from a routine medication history in that it involves (1) a systematic process for interviewing the patient (or family) and (2) a review of at least one other reliable source of information (eg, a provincial medication database, an inspection of medication vials, or contact with the community pharmacy) to obtain and verify patient medications (prescribed and nonprescribed). The pharmacist recorded the BPMH in the electronic patient record. The application supported admission and discharge Med Rec. On discharge, there were 2 options: (1) the prescriber alone would review and complete the discharge Med Rec and generate electronic prescriptions (Table 1, Silver level care) or (2) the pharmacist would collaborate with the prescriber to complete the discharge reconciliation and the prescriber would electronically generate prescriptions (Table 1, Gold level care). All clinical areas had a combined pharmacist and prescriber Med Rec model in place at admission, but the proportion of patients receiving discharge reconciliation completed by pharmacist and prescriber versus the prescriber-alone varied based on the individual clinician’s practices.

Patient Selection

All consecutive hospitalized patients admitted and discharged by the general internal medicine [GIM] service from March 2007 to December 2011 were included. The GIM service was chosen for the main analysis because they had been performing the intervention for the longest period of time and had the largest population of patients. Patients were identified via their hospital-specific medical record identification number and specific hospital-visit number. Patients were excluded if any of the following occurred: (1) the length of stay of their index admission was less than 24 hours; (2) they died during the visit; (3) they were transferred to a separate acute care inpatient facility; or (4) they left hospital against medical advice. Patient visits were excluded as index cases from the analysis if they were returning within 90 days of a previous discharge.

Outcomes

The primary study outcome was the occurrence of an inpatient readmission or ED visit within 30 days of discharge. In our secondary analyses, we examined the impact of the intervention on high-risk patient populations, such as those ≥65 years of age, with a length of stay, acuity of admission, Charlson comorbidity index, and emergency department visits in past 6 months (LACE) index score ≥10 (see supplementary Appendix 1 for LACE score description), on high-alert medications (1 or more of warfarin, insulin, digoxin, and opioids), and on ≥10 medications.

Data Collection

Identification of Exposure of Interest

We used the electronic database to capture all patients who received pharmacist and prescriber supported admission-to-discharge reconciliation. We explicitly defined increasing intensity of Med Rec care in categories of Bronze, Silver, and Gold care levels (Table 1). The exposed (intervention) group received an enhanced Med Rec bundle (patients receiving Gold level care). The control group was made of patients receiving a partial Med Rec Bundle (patients receiving Silver or Bronze level of care or below).

Determination of Hospital Visits

A search of administrative databases was used to determine if patients admitted to the targeted services had an ED visit or urgent inpatient admission to the study hospital within 30 days.

Statistical Analysis

A logistic regression for outcomes was performed. This yielded an adjusted odds ratio with a 95% confidence interval (CI) between the intervention and control groups. Statistical significance was determined with a 2-sided α level of 0.05. In the analysis, we used Statistical Analysis Software version 9.2.

In our multivariate logistic regression model, we adjusted for confounding factors that might influence the patients’ risk of readmission or the type of Med Rec they received upon discharge. By using administrative databases, patient level demographics, and the Charlson comorbidity index, the most responsible diagnosis and disease burden were collected. Medication-related factors collected included the number of medications on discharge and the presence of predefined high-alert medications. The number of medications on the medication discharge list was determined by using the electronic database. The final adjustment model included age, gender, the number of medications on discharge, and the LACE index score (supplementary Appendix 1). The LACE index score has been validated in Ontario, Canada, populations to quantify the risk of death or unplanned readmission within 30 days of discharge.²⁴

Propensity Score Adjustment

Propensity scoring (probability of treatment assignment conditional on observed baseline characteristics) was planned a priori to account for possible factors that would impact whether a patient received the intervention or control care levels. The propensity score for receiving Med Rec was computed from a logistic model using Med Rec as the outcome. A structured iterative approach was used to refine this model to achieve covariate balance within the matched pairs. Covariate balance was measured by the standardized difference, in which an absolute standardized difference >10% represents meaningful imbalance.²⁵ From the original cohort, we attempted to match patients who had the intervention to patients from the control by means of a matching algorithm using the logit of the propensity score for receiving the intervention.²⁶

Subgroup Analysis

We also examined the impact of the intervention on high-risk patient populations such as those ≥65 years of age, with a LACE index score ≥10, on high-alert medications, and on ≥10 medications. A univariate analysis was conducted to identify patient-related risk predictors that may be independently correlated with a higher risk of hospital visits.

Baseline Characteristics

A total of 8678 patients representing 9931 unique visits met the inclusion criteria for analysis. There were 2541 unique visits (approximately 26% of visits) in the intervention group that received Gold level care and 7390 unique visits in the control group. The patients in the control group were largely patients who received the original standard of care at the institution, Silver level care (67% of the control group). Patients who received Bronze level care or less comprised 33% of the control group.

Patients in the intervention group were significantly older (average of 68 years old versus 64 years old) and on more medications. They also notably had a longer duration of stay in hospital, an increased percentage of visits with a LACE index score ≥10, and were more likely to be discharged home on a high-alert medication and with supports (Table 2).

Main Analysis

The main unadjusted analysis of GIM patients (n = 9931 visits) did not detect a difference in 30-day ED visits and readmissions between the intervention group (540 out of 2541; 21.2%) and control (1423 out of 7390; 19.3%; Table 3). By using a multivariate logistic regression model to account for age, sex, LACE index, and number of medications on discharge, the adjusted odds ratio was 1.06 (95% CI, 0.95-1.19; P = 0.33). After propensity score adjustment, the relative risk of readmission was 0.88 (16.7% vs 18.9%; 95% CI, 0.59-1.32; P = 0.54).

Secondary Analyses

In each predefined high-risk patient subgroup (age ≥65, LACE index score ≥10, number of discharge medications ≥10, and the presence of high-alert medications), analyses of our primary endpoint did not detect significant adjusted odds ratios (Table 4). In our univariate analysis, increasing number of medications, LACE index score, and male gender were independently correlated with a higher risk of hospital visits (supplementary Appendix 2).

Med Rec is widely recommended as a patient safety strategy to prevent clinically significant medication discrepancies at transitions in care.^4-9 However, Med Rec varies widely in terms of what it entails and who delivers it, with the preponderance of evidence suggesting an impact on clinically significant medication discrepancies only when interprofessional care delivered includes a central role for pharmacists.²⁷ Furthermore, Med Rec appears to impact short term readmissions only when embedded in a broader, multifaceted, bundled intervention in which pharmacists or other team members educate patients about their medications and deliver postdischarge follow-up phone calls.^10-13

As very few hospitals have the resources to sustainably deliver intensive care bundles that are represented in RCTs (characterized by Platinum and Diamond levels of care in Table 1), in our observational study, we sought to explore whether a resource-attainable, enhanced Med Rec care bundle (Gold level) had an impact on hospital utilization compared to partial Med Rec care bundles (Bronze and Silver levels). In our findings, we did not detect a significant difference on ED visits and readmissions within 30 days between enhanced and partial care bundles. In a secondary analysis of the influence of the intervention on prespecified high-risk patient subgroups, we also did not detect a difference.

As far as we are aware, our long-term, observational study is the largest to date to explore a real-life, enhanced Med Rec intervention and examine its impact on meaningful patient outcomes. We extrapolated that our intervention group received several critical attributes of a successful bundle as discussed by Mueller in a systematic review.² Our intervention included the following: (1) a systematic BPMH process on admission; (2) integrated admission-to-discharge reconciliation processes; (3) discharge delineation of medication changes since admission; (4) pharmacist involvement in reconciliation from admission to discharge; (5) an electronic platform; and (6) formal discharge reconciliation with interprofessional collaboration. Additional components in the bundle described by Mueller included the following: patient education at discharge, postdischarge communication with the patient, and communication with outpatient providers and medication management.

In our results, we did not find a difference in outcomes between the intervention and control groups. Therefore, it is possible that the enhanced bundle’s focus on interprofessional involvement in discharge reconciliation (Gold care level) has no impact on hospital utilization compared to partial care bundles (Silver and Bronze levels). Kwan et al.³ describe similar findings in their systematic review, in which they evaluated the effects of hospital-based Med Rec on unintentional discrepancies with nontrivial risks for harm to patients on 30-day postdischarge hospital visits. Kwan et al.³ concluded that larger well-designed studies are required to further evaluate this outcome, but authors of current published studies suggest that Med Rec alone probably does not reduce postdischarge hospital utilization within 30 days. Med Rec may have a more significant impact on utilization when bundled with other interventions that improve discharge coordination.³

There may be several reasons why we were unable to detect a significant difference between the intervention and control groups. One limitation is that our nonrandomized, retrospective design may have led to unmeasured confounders that impacted allocation into the intervention group versus the control group. It was notable that patients in the intervention group had an increased age, longer duration of hospital stay, more medications, and high-alert medications on discharge compared to the control group and that may have biased our results towards the null hypothesis. Although the propensity score analysis attempted to adjust for this, it also did not detect a significant difference between groups.

In addition, the existing standard of care during the study period allowed for patients in the control group to receive varying levels of Med Rec. Ideally, we would have compared the intervention to a placebo group that did not receive any Med Rec-related care elements. However, as this was a real-life observational study, the majority of patients received some Med Rec services as a part of the standard of care. As a result, 67% of patients in the control group received Silver level Med Rec with a BPMH, admission reconciliation, and prescriber-only discharge reconciliation. This may have made it more difficult to show an incremental benefit on readmissions between the intervention and control.

Also, our primary outcome of all-cause ED or hospital readmissions within 30 days may not have been sensitive enough to detect the effect of Med Rec interventions alone. Only a small proportion of readmissions within 30 days of discharge are preventable and many patient and community level factors responsible for readmissions cannot be controlled by the hospital’s actions.²⁸ Comprehensive pharmacy interventions have demonstrated decreased hospitalizations and emergency visits at 12 months; however, the largest impact was seen on the more specific outcome of medication-related hospitalizations (80% reduction).²⁹ Lastly, another limitation was that we were unable to capture hospital visits to other centres. However, in our region, almost 75% of readmissions are to the same site as the initial hospitalization.³⁰

Overall, our findings in this study and novel characterization of Med Rec services are relevant to many hospital sites that are striving to implement integrated Med Rec with limited healthcare resources. Although interprofessional Med Rec likely reduces clinically significant medication discrepancies, enhanced interprofessional Med Rec on discharge (Gold Med Rec) alone may not be enough to impact hospital utilization compared to partial Med Rec services (Silver and Bronze Med Rec). Further research into practical, targeted Med Rec bundles on more specific outcomes (such as preventable postdischarge adverse events, “avoidable” hospital readmissions, and medication-related readmissions) may detect a significant benefit.

A long-term observational evaluation of interprofessional Med Rec did not detect a difference in 30-day postdischarge patient hospital visits between patients who received enhanced versus partial Med Rec patient care bundles. Researchers of future prospective studies could focus on evaluating high-risk populations or specific elements of Med Rec services on avoidable medication-related hospital admissions and postdischarge adverse drug events.

Acknowledgments

The authors thank Nita Dhir, MBA.

Presented as a poster and oral presentation at the 2012 American College of Clinical Pharmacy Annual Meeting, Hollywood, Florida, October 21-24, 2012, and as an encore poster presentation at the Canadian Society of Hospital Pharmacists Professional Practice Conference, Toronto, Canada, Feb 3, 2013.

Disclosure

The authors declare no conflicts of interest related to the manuscript submitted. All monies used for the research came from the University Health Network Department of Pharmacy Budget, including the pharmacy residency program.

The lack of mentorship in hospital medicine has been previously documented,^1-3 but there is scant literature about solutions to the problem.⁴ In other disciplines, data suggest that the guidance of a mentor has a positive influence on academic productivity and professional satisfaction. Mentored faculty at all levels in their careers are more successful at producing peer-reviewed publications, procuring grant support, and maintaining confidence in their career trajectory.^5,6 In one study, mentored faculty physicians reported receiving career advice, improving communication skills, and growing their professional networks.⁷ Another study found that the primary benefits of physician mentoring were improved professional and personal well-being.⁸ Whether early-career hospitalists would have similarly favorable responses to a structured mentorship program is unknown. We report our experience in implementing a pilot mentorship program to support junior hospitalists at a large academic medical center.

The mentorship program was implemented from October 2015 to June 2016 in the Hospital Medicine Unit (HMU) of the Massachusetts General Hospital (MGH), a teaching affiliate of Harvard Medical School.  

Program Goals, Design, and Development

In collaboration with the MGH Center for Faculty Development (CFD), we offered 3 training sessions over a period of 9 months, for both mentors and mentees, on how to maximize mentorship success. Funding was provided by the MGH Division of General Internal Medicine and CFD. There were no external funding sources. This study was exempt by the Partners Institutional Review Board.

Participants

Mentees had to be hired at >0.5 full-time equivalent and have 3 years or fewer of hospitalist experience. Mentors were physicians with at least 7 years of hospital medicine experience. All HMU faculty who met the criteria were invited to participate on a voluntary basis.

Mentor–Mentee Matching

Mentors were paired with 1 or 2 mentees. Participant information such as history of mentorship and areas of interest for mentorship was collected. Two authors matched mentors and mentees to maximize similarities in these areas. Four mentors were paired with 2 mentees each, and 12 mentors were paired with 1 mentee each.

Mentorship Training Sessions

The program provided 3 mentorship-training lunch sessions for both mentees and mentors during the 9-month program. To enrich attendance, mentees were provided coverage for their clinical duties. The initial training session provided an opportunity to meet, articulate expectations and challenges, and develop action plans with individualized goals for the mentoring relationship. The second training session occurred at the midpoint. Pairs considered their mentorship status, evaluated their progress, and discussed strategies for optimizing their experience. At the final training session, participants reflected on their mentoring relationships, identified their extended network of mentoring support, and set expectations regarding whether the mentoring relationship would continue.

Mentorship Meetings

In addition to the training sessions, mentee–mentor pairs were expected to meet a minimum of 2 times during the formal mentorship program. CFD experts performed participant outreach via e-mail to assess progress. Mentees were given dining facility gift cards to support meetings with their mentors.

Program Evaluation

Confidential, anonymous semiquantitative surveys were used to assess the efficacy of this prospective, nonrandomized intervention study. An online survey platform was utilized to assess the frequency of mentorship meetings, satisfaction and challenges with mentorship, perception of support, degree of career satisfaction, and perceived need for and value of mentoring. Data were collected from both mentors and mentees prior to the first training session and after completion of the program. To preserve anonymity and encourage responses, surveys did not contain identifying information. As such, individual respondent data were not directly matched pre- and postintervention.

Statistical Analysis

Individual satisfaction scores (ranked 1 to 5, with 5 being very satisfied) were assigned to each response within each of the 18 domains. A composite satisfaction score was then calculated for each respondent both pre- and postintervention. An unpaired Student’s t test was first used to assess change in overall satisfaction scores pre- and postintervention. As there was a statistically significant change in this aggregate score, Wilcoxon rank sum testing was used to compare ordinal scores pre- and postintervention within each of the 18 domains. The proportion of respondents ranking their satisfaction in each domain as satisfied or very satisfied was also compared pre- and postmentorship. This approach of modified “top-box” reporting is similar to prior major national survey-based experiences.⁹

Program Participation and Response Rate

Of the 25 eligible mentees, 16 (64%) participated in the mentorship program. Of the 20 eligible mentors, 12 (60%) participated. One participating mentee and 1 mentor left the institution during the intervention period. Fourteen mentees (response rate: 88%) and 9 mentors (response rate: 75%) completed the preintervention survey. Ten mentees (response rate: 63%) and 8 mentors (response rate: 67%) completed the postintervention survey.

Mentor Characteristics

Ninety-two percent of mentors were clinician educators. The mentors had 21 peer-reviewed publications during the year of the study, 25% of the mentors had external research funding, 75% had internal funding for projects or administrative roles, and 75% were above the rank of instructor. Most mentors were married with children.

Mentorship Meetings and the Mentorship Network

All participants attended at least 2 of the 3 trainings. For the mentees who completed the postintervention survey, 9 (90%) met with their mentors 3 or more additional times, and 8 (80%) were connected by their mentor to at least 1 additional faculty mentor.

Perceptions and Overall Satisfaction with Mentorship

Prior to starting the mentoring relationship, 86% of mentees and 78% of mentors anticipated that differing career goals would be a challenge to a successful mentor–mentee relationship. At the end of the program, only 30% of mentees and 38% of mentors felt that such differences were a challenge. Ninety percent of mentees and 88% of mentors were satisfied or very satisfied with their mentorship match. Forty-three percent of mentees felt supported by the HMU prior to the mentorship program, while 90% felt supported after the program. All the mentees agreed that future HMU faculty should participate in a similar program.

Impact of Mentorship on Critical Domains

At baseline, the following domains were most commonly rated as very important by mentees: career planning, professional connectedness, producing scholarly work, finding an area of expertise, balancing work and family life, and job satisfaction (Figure 1). There was a significant improvement in composite satisfaction scores after completion of the mentorship program (54.5 ± 6.2 vs 65 ± 14.9, P = 0.02). The influence of the mentorship program on all domains is shown in Figure 2. After completion of the mentorship program, there was a significant improvement in mentee satisfaction in the following domains: career planning, professional connectedness, self-reflection, research skills, and mentoring skills.

Our pilot structured mentorship program for junior hospitalists was feasible and led to improved satisfaction in select key career domains. Other mentoring or faculty coaching programs have been studied in several fields of medicine^10-12; however, to our knowledge, there have not been published data studying a structured mentorship program for junior faculty in hospital medicine. Our intervention prioritized not only optimizing mentorship matches but also formalizing training sessions led by content experts.

After experiencing a structured mentoring relationship, most mentees felt a greater sense of support, were satisfied with their mentoring experiences, were connected to additional faculty, and had significant improvement in satisfaction in key career domains. Satisfaction with other self-identified “very important” domains, including scholarly activity, finding an area of expertise, job satisfaction, and work and family-life balance, did not significantly improve by the end of the program.

Perceived challenges to mentoring did not persist to the same degree with the implementation of a structured program. This highlights the importance of building mentorship skill sets (such as mentoring across differences and goal setting) through expert-led training sessions and perhaps also the importance of matching based on career goals.

This study has several limitations, including a small sample size, modest response rate, and short study period. Additionally, the assessment relied on self-reporting. This study was performed at a large academic institution, and mentors were almost all clinician educators with some research experience, which limits generalizability. Surveys were entirely anonymized and did not contain identifying information, so individual respondent data could not be matched pre- and postintervention. Given that this was an observational study without a control group, mentorship can only be said to be associated with, and not necessarily causally linked to, the observed improvements. Other cointerventions occurring during the same time frame that may have impacted satisfaction include annual career conferences, changing leadership, and other faculty development seminars. Finally, given the study design and the reliance on survey-based data, the net improvement in satisfaction scores may be influenced by the Hawthorne effect.

Effective and sustainable career development requires mentorship. In our pilot study, implementing a personalized and structured mentorship program for junior hospitalists focusing on building mentor–mentee relationships was feasible and was met with satisfaction. Indeed, the proportion of junior hospitalists who felt supported more than doubled, which could potentially improve academic productivity, recruitment, and retention. Larger prospective studies with a longer follow-up are needed to assess the impact of a structured mentorship program on hospitalist careers.

Acknowledgments

The authors would like to thank each of the participants in the HMU Mentorship Program and the MGH CFD and Division of General Internal Medicine for supporting this effort.

Disclosure 

Funding was provided by the MGH DGIM and CFD. Dr. Regina O’Neill reports the following relevant financial relationship: Massachusetts General Hospital Center for Faculty Development (consultant). All other authors report no other financial or other conflicts of interest to disclose.

The lack of mentorship in hospital medicine has been previously documented,^1-3 but there is scant literature about solutions to the problem.⁴ In other disciplines, data suggest that the guidance of a mentor has a positive influence on academic productivity and professional satisfaction. Mentored faculty at all levels in their careers are more successful at producing peer-reviewed publications, procuring grant support, and maintaining confidence in their career trajectory.^5,6 In one study, mentored faculty physicians reported receiving career advice, improving communication skills, and growing their professional networks.⁷ Another study found that the primary benefits of physician mentoring were improved professional and personal well-being.⁸ Whether early-career hospitalists would have similarly favorable responses to a structured mentorship program is unknown. We report our experience in implementing a pilot mentorship program to support junior hospitalists at a large academic medical center.

The mentorship program was implemented from October 2015 to June 2016 in the Hospital Medicine Unit (HMU) of the Massachusetts General Hospital (MGH), a teaching affiliate of Harvard Medical School.  

Program Goals, Design, and Development

In collaboration with the MGH Center for Faculty Development (CFD), we offered 3 training sessions over a period of 9 months, for both mentors and mentees, on how to maximize mentorship success. Funding was provided by the MGH Division of General Internal Medicine and CFD. There were no external funding sources. This study was exempt by the Partners Institutional Review Board.

Participants

Mentees had to be hired at >0.5 full-time equivalent and have 3 years or fewer of hospitalist experience. Mentors were physicians with at least 7 years of hospital medicine experience. All HMU faculty who met the criteria were invited to participate on a voluntary basis.

Mentor–Mentee Matching

Mentors were paired with 1 or 2 mentees. Participant information such as history of mentorship and areas of interest for mentorship was collected. Two authors matched mentors and mentees to maximize similarities in these areas. Four mentors were paired with 2 mentees each, and 12 mentors were paired with 1 mentee each.

Mentorship Training Sessions

The program provided 3 mentorship-training lunch sessions for both mentees and mentors during the 9-month program. To enrich attendance, mentees were provided coverage for their clinical duties. The initial training session provided an opportunity to meet, articulate expectations and challenges, and develop action plans with individualized goals for the mentoring relationship. The second training session occurred at the midpoint. Pairs considered their mentorship status, evaluated their progress, and discussed strategies for optimizing their experience. At the final training session, participants reflected on their mentoring relationships, identified their extended network of mentoring support, and set expectations regarding whether the mentoring relationship would continue.

Mentorship Meetings

In addition to the training sessions, mentee–mentor pairs were expected to meet a minimum of 2 times during the formal mentorship program. CFD experts performed participant outreach via e-mail to assess progress. Mentees were given dining facility gift cards to support meetings with their mentors.

Program Evaluation

Confidential, anonymous semiquantitative surveys were used to assess the efficacy of this prospective, nonrandomized intervention study. An online survey platform was utilized to assess the frequency of mentorship meetings, satisfaction and challenges with mentorship, perception of support, degree of career satisfaction, and perceived need for and value of mentoring. Data were collected from both mentors and mentees prior to the first training session and after completion of the program. To preserve anonymity and encourage responses, surveys did not contain identifying information. As such, individual respondent data were not directly matched pre- and postintervention.

Statistical Analysis

Individual satisfaction scores (ranked 1 to 5, with 5 being very satisfied) were assigned to each response within each of the 18 domains. A composite satisfaction score was then calculated for each respondent both pre- and postintervention. An unpaired Student’s t test was first used to assess change in overall satisfaction scores pre- and postintervention. As there was a statistically significant change in this aggregate score, Wilcoxon rank sum testing was used to compare ordinal scores pre- and postintervention within each of the 18 domains. The proportion of respondents ranking their satisfaction in each domain as satisfied or very satisfied was also compared pre- and postmentorship. This approach of modified “top-box” reporting is similar to prior major national survey-based experiences.⁹

Program Participation and Response Rate

Of the 25 eligible mentees, 16 (64%) participated in the mentorship program. Of the 20 eligible mentors, 12 (60%) participated. One participating mentee and 1 mentor left the institution during the intervention period. Fourteen mentees (response rate: 88%) and 9 mentors (response rate: 75%) completed the preintervention survey. Ten mentees (response rate: 63%) and 8 mentors (response rate: 67%) completed the postintervention survey.

Mentor Characteristics

Ninety-two percent of mentors were clinician educators. The mentors had 21 peer-reviewed publications during the year of the study, 25% of the mentors had external research funding, 75% had internal funding for projects or administrative roles, and 75% were above the rank of instructor. Most mentors were married with children.

Mentorship Meetings and the Mentorship Network

All participants attended at least 2 of the 3 trainings. For the mentees who completed the postintervention survey, 9 (90%) met with their mentors 3 or more additional times, and 8 (80%) were connected by their mentor to at least 1 additional faculty mentor.

Perceptions and Overall Satisfaction with Mentorship

Prior to starting the mentoring relationship, 86% of mentees and 78% of mentors anticipated that differing career goals would be a challenge to a successful mentor–mentee relationship. At the end of the program, only 30% of mentees and 38% of mentors felt that such differences were a challenge. Ninety percent of mentees and 88% of mentors were satisfied or very satisfied with their mentorship match. Forty-three percent of mentees felt supported by the HMU prior to the mentorship program, while 90% felt supported after the program. All the mentees agreed that future HMU faculty should participate in a similar program.

Impact of Mentorship on Critical Domains

At baseline, the following domains were most commonly rated as very important by mentees: career planning, professional connectedness, producing scholarly work, finding an area of expertise, balancing work and family life, and job satisfaction (Figure 1). There was a significant improvement in composite satisfaction scores after completion of the mentorship program (54.5 ± 6.2 vs 65 ± 14.9, P = 0.02). The influence of the mentorship program on all domains is shown in Figure 2. After completion of the mentorship program, there was a significant improvement in mentee satisfaction in the following domains: career planning, professional connectedness, self-reflection, research skills, and mentoring skills.

Our pilot structured mentorship program for junior hospitalists was feasible and led to improved satisfaction in select key career domains. Other mentoring or faculty coaching programs have been studied in several fields of medicine^10-12; however, to our knowledge, there have not been published data studying a structured mentorship program for junior faculty in hospital medicine. Our intervention prioritized not only optimizing mentorship matches but also formalizing training sessions led by content experts.

After experiencing a structured mentoring relationship, most mentees felt a greater sense of support, were satisfied with their mentoring experiences, were connected to additional faculty, and had significant improvement in satisfaction in key career domains. Satisfaction with other self-identified “very important” domains, including scholarly activity, finding an area of expertise, job satisfaction, and work and family-life balance, did not significantly improve by the end of the program.

Perceived challenges to mentoring did not persist to the same degree with the implementation of a structured program. This highlights the importance of building mentorship skill sets (such as mentoring across differences and goal setting) through expert-led training sessions and perhaps also the importance of matching based on career goals.

This study has several limitations, including a small sample size, modest response rate, and short study period. Additionally, the assessment relied on self-reporting. This study was performed at a large academic institution, and mentors were almost all clinician educators with some research experience, which limits generalizability. Surveys were entirely anonymized and did not contain identifying information, so individual respondent data could not be matched pre- and postintervention. Given that this was an observational study without a control group, mentorship can only be said to be associated with, and not necessarily causally linked to, the observed improvements. Other cointerventions occurring during the same time frame that may have impacted satisfaction include annual career conferences, changing leadership, and other faculty development seminars. Finally, given the study design and the reliance on survey-based data, the net improvement in satisfaction scores may be influenced by the Hawthorne effect.

Effective and sustainable career development requires mentorship. In our pilot study, implementing a personalized and structured mentorship program for junior hospitalists focusing on building mentor–mentee relationships was feasible and was met with satisfaction. Indeed, the proportion of junior hospitalists who felt supported more than doubled, which could potentially improve academic productivity, recruitment, and retention. Larger prospective studies with a longer follow-up are needed to assess the impact of a structured mentorship program on hospitalist careers.

Acknowledgments

The authors would like to thank each of the participants in the HMU Mentorship Program and the MGH CFD and Division of General Internal Medicine for supporting this effort.

Disclosure 

Funding was provided by the MGH DGIM and CFD. Dr. Regina O’Neill reports the following relevant financial relationship: Massachusetts General Hospital Center for Faculty Development (consultant). All other authors report no other financial or other conflicts of interest to disclose.

The lack of mentorship in hospital medicine has been previously documented,^1-3 but there is scant literature about solutions to the problem.⁴ In other disciplines, data suggest that the guidance of a mentor has a positive influence on academic productivity and professional satisfaction. Mentored faculty at all levels in their careers are more successful at producing peer-reviewed publications, procuring grant support, and maintaining confidence in their career trajectory.^5,6 In one study, mentored faculty physicians reported receiving career advice, improving communication skills, and growing their professional networks.⁷ Another study found that the primary benefits of physician mentoring were improved professional and personal well-being.⁸ Whether early-career hospitalists would have similarly favorable responses to a structured mentorship program is unknown. We report our experience in implementing a pilot mentorship program to support junior hospitalists at a large academic medical center.

The mentorship program was implemented from October 2015 to June 2016 in the Hospital Medicine Unit (HMU) of the Massachusetts General Hospital (MGH), a teaching affiliate of Harvard Medical School.  

Program Goals, Design, and Development

In collaboration with the MGH Center for Faculty Development (CFD), we offered 3 training sessions over a period of 9 months, for both mentors and mentees, on how to maximize mentorship success. Funding was provided by the MGH Division of General Internal Medicine and CFD. There were no external funding sources. This study was exempt by the Partners Institutional Review Board.

Participants

Mentees had to be hired at >0.5 full-time equivalent and have 3 years or fewer of hospitalist experience. Mentors were physicians with at least 7 years of hospital medicine experience. All HMU faculty who met the criteria were invited to participate on a voluntary basis.

Mentor–Mentee Matching

Mentors were paired with 1 or 2 mentees. Participant information such as history of mentorship and areas of interest for mentorship was collected. Two authors matched mentors and mentees to maximize similarities in these areas. Four mentors were paired with 2 mentees each, and 12 mentors were paired with 1 mentee each.

Mentorship Training Sessions

The program provided 3 mentorship-training lunch sessions for both mentees and mentors during the 9-month program. To enrich attendance, mentees were provided coverage for their clinical duties. The initial training session provided an opportunity to meet, articulate expectations and challenges, and develop action plans with individualized goals for the mentoring relationship. The second training session occurred at the midpoint. Pairs considered their mentorship status, evaluated their progress, and discussed strategies for optimizing their experience. At the final training session, participants reflected on their mentoring relationships, identified their extended network of mentoring support, and set expectations regarding whether the mentoring relationship would continue.

Mentorship Meetings

In addition to the training sessions, mentee–mentor pairs were expected to meet a minimum of 2 times during the formal mentorship program. CFD experts performed participant outreach via e-mail to assess progress. Mentees were given dining facility gift cards to support meetings with their mentors.

Program Evaluation

Confidential, anonymous semiquantitative surveys were used to assess the efficacy of this prospective, nonrandomized intervention study. An online survey platform was utilized to assess the frequency of mentorship meetings, satisfaction and challenges with mentorship, perception of support, degree of career satisfaction, and perceived need for and value of mentoring. Data were collected from both mentors and mentees prior to the first training session and after completion of the program. To preserve anonymity and encourage responses, surveys did not contain identifying information. As such, individual respondent data were not directly matched pre- and postintervention.

Statistical Analysis

Individual satisfaction scores (ranked 1 to 5, with 5 being very satisfied) were assigned to each response within each of the 18 domains. A composite satisfaction score was then calculated for each respondent both pre- and postintervention. An unpaired Student’s t test was first used to assess change in overall satisfaction scores pre- and postintervention. As there was a statistically significant change in this aggregate score, Wilcoxon rank sum testing was used to compare ordinal scores pre- and postintervention within each of the 18 domains. The proportion of respondents ranking their satisfaction in each domain as satisfied or very satisfied was also compared pre- and postmentorship. This approach of modified “top-box” reporting is similar to prior major national survey-based experiences.⁹

Program Participation and Response Rate

Of the 25 eligible mentees, 16 (64%) participated in the mentorship program. Of the 20 eligible mentors, 12 (60%) participated. One participating mentee and 1 mentor left the institution during the intervention period. Fourteen mentees (response rate: 88%) and 9 mentors (response rate: 75%) completed the preintervention survey. Ten mentees (response rate: 63%) and 8 mentors (response rate: 67%) completed the postintervention survey.

Mentor Characteristics

Ninety-two percent of mentors were clinician educators. The mentors had 21 peer-reviewed publications during the year of the study, 25% of the mentors had external research funding, 75% had internal funding for projects or administrative roles, and 75% were above the rank of instructor. Most mentors were married with children.

Mentorship Meetings and the Mentorship Network

All participants attended at least 2 of the 3 trainings. For the mentees who completed the postintervention survey, 9 (90%) met with their mentors 3 or more additional times, and 8 (80%) were connected by their mentor to at least 1 additional faculty mentor.

Perceptions and Overall Satisfaction with Mentorship

Prior to starting the mentoring relationship, 86% of mentees and 78% of mentors anticipated that differing career goals would be a challenge to a successful mentor–mentee relationship. At the end of the program, only 30% of mentees and 38% of mentors felt that such differences were a challenge. Ninety percent of mentees and 88% of mentors were satisfied or very satisfied with their mentorship match. Forty-three percent of mentees felt supported by the HMU prior to the mentorship program, while 90% felt supported after the program. All the mentees agreed that future HMU faculty should participate in a similar program.

Impact of Mentorship on Critical Domains

At baseline, the following domains were most commonly rated as very important by mentees: career planning, professional connectedness, producing scholarly work, finding an area of expertise, balancing work and family life, and job satisfaction (Figure 1). There was a significant improvement in composite satisfaction scores after completion of the mentorship program (54.5 ± 6.2 vs 65 ± 14.9, P = 0.02). The influence of the mentorship program on all domains is shown in Figure 2. After completion of the mentorship program, there was a significant improvement in mentee satisfaction in the following domains: career planning, professional connectedness, self-reflection, research skills, and mentoring skills.

Our pilot structured mentorship program for junior hospitalists was feasible and led to improved satisfaction in select key career domains. Other mentoring or faculty coaching programs have been studied in several fields of medicine^10-12; however, to our knowledge, there have not been published data studying a structured mentorship program for junior faculty in hospital medicine. Our intervention prioritized not only optimizing mentorship matches but also formalizing training sessions led by content experts.

After experiencing a structured mentoring relationship, most mentees felt a greater sense of support, were satisfied with their mentoring experiences, were connected to additional faculty, and had significant improvement in satisfaction in key career domains. Satisfaction with other self-identified “very important” domains, including scholarly activity, finding an area of expertise, job satisfaction, and work and family-life balance, did not significantly improve by the end of the program.

Perceived challenges to mentoring did not persist to the same degree with the implementation of a structured program. This highlights the importance of building mentorship skill sets (such as mentoring across differences and goal setting) through expert-led training sessions and perhaps also the importance of matching based on career goals.

This study has several limitations, including a small sample size, modest response rate, and short study period. Additionally, the assessment relied on self-reporting. This study was performed at a large academic institution, and mentors were almost all clinician educators with some research experience, which limits generalizability. Surveys were entirely anonymized and did not contain identifying information, so individual respondent data could not be matched pre- and postintervention. Given that this was an observational study without a control group, mentorship can only be said to be associated with, and not necessarily causally linked to, the observed improvements. Other cointerventions occurring during the same time frame that may have impacted satisfaction include annual career conferences, changing leadership, and other faculty development seminars. Finally, given the study design and the reliance on survey-based data, the net improvement in satisfaction scores may be influenced by the Hawthorne effect.

Effective and sustainable career development requires mentorship. In our pilot study, implementing a personalized and structured mentorship program for junior hospitalists focusing on building mentor–mentee relationships was feasible and was met with satisfaction. Indeed, the proportion of junior hospitalists who felt supported more than doubled, which could potentially improve academic productivity, recruitment, and retention. Larger prospective studies with a longer follow-up are needed to assess the impact of a structured mentorship program on hospitalist careers.

Acknowledgments

The authors would like to thank each of the participants in the HMU Mentorship Program and the MGH CFD and Division of General Internal Medicine for supporting this effort.

Disclosure 

Funding was provided by the MGH DGIM and CFD. Dr. Regina O’Neill reports the following relevant financial relationship: Massachusetts General Hospital Center for Faculty Development (consultant). All other authors report no other financial or other conflicts of interest to disclose.