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Histone levels may predict thrombocytopenia
Image by Eric Smith
Measuring circulating histones may help physicians predict the onset of thrombocytopenia or allow them to monitor the condition in patients who are critically ill, according to researchers.
They noted that histones induce profound thrombocytopenia in mice and are associated with organ injury when released after extensive cell damage in patients who are critically ill.
So the team decided to examine the association between circulating histones and thrombocytopenia in patients in the intensive care unit (ICU).
Cheng-Hock Toh, MD, of the University of Liverpool in the UK, and his colleagues conducted this research and reported the results in a letter to JAMA.
The researchers analyzed 56 patients with thrombocytopenia and 56 controls with normal platelet counts who were admitted to the ICU at Royal Liverpool University Hospital between June 2013 and January 2014.
Thrombocytopenia was defined as a platelet count less than 150 × 103/µL, a 25% or greater decrease in platelet count, or both within the first 96 hours of ICU admission.
The researchers noted that, at approximately 30 µg/mL, histones bind platelets and cause platelet aggregation, which results in profound thrombocytopenia in mice.
So the team used this as a cutoff to stratify thrombocytopenic patients. A “high” level of histones was 30 µg/mL or greater, and a “low” level was below 30 µg/mL.
The researchers detected circulating histones in 51 of the thrombocytopenic patients and 31 controls—91% and 55%, respectively (P<0.001). Histone levels were 2.5- to 5.5-fold higher in thrombocytopenic patients than in controls.
Thrombocytopenic patients with high histone levels at ICU admission had significantly lower platelet counts and a significantly higher percentage of decrease in platelet counts at 24 hours (P=0.02 and P=0.04, respectively) and 48 hours (P=0.003 and P=0.005, respectively) after admission.
High admission histone levels were associated with moderate to severe thrombocytopenia and the development of clinically important thrombocytopenia (P<0.001).
A 30 µg/mL histone concentration was able to predict thrombocytopenia with 76% sensitivity and 91% specificity. The positive predictive value was 79.4%, and the negative predictive value was 89.2%.
Image by Eric Smith
Measuring circulating histones may help physicians predict the onset of thrombocytopenia or allow them to monitor the condition in patients who are critically ill, according to researchers.
They noted that histones induce profound thrombocytopenia in mice and are associated with organ injury when released after extensive cell damage in patients who are critically ill.
So the team decided to examine the association between circulating histones and thrombocytopenia in patients in the intensive care unit (ICU).
Cheng-Hock Toh, MD, of the University of Liverpool in the UK, and his colleagues conducted this research and reported the results in a letter to JAMA.
The researchers analyzed 56 patients with thrombocytopenia and 56 controls with normal platelet counts who were admitted to the ICU at Royal Liverpool University Hospital between June 2013 and January 2014.
Thrombocytopenia was defined as a platelet count less than 150 × 103/µL, a 25% or greater decrease in platelet count, or both within the first 96 hours of ICU admission.
The researchers noted that, at approximately 30 µg/mL, histones bind platelets and cause platelet aggregation, which results in profound thrombocytopenia in mice.
So the team used this as a cutoff to stratify thrombocytopenic patients. A “high” level of histones was 30 µg/mL or greater, and a “low” level was below 30 µg/mL.
The researchers detected circulating histones in 51 of the thrombocytopenic patients and 31 controls—91% and 55%, respectively (P<0.001). Histone levels were 2.5- to 5.5-fold higher in thrombocytopenic patients than in controls.
Thrombocytopenic patients with high histone levels at ICU admission had significantly lower platelet counts and a significantly higher percentage of decrease in platelet counts at 24 hours (P=0.02 and P=0.04, respectively) and 48 hours (P=0.003 and P=0.005, respectively) after admission.
High admission histone levels were associated with moderate to severe thrombocytopenia and the development of clinically important thrombocytopenia (P<0.001).
A 30 µg/mL histone concentration was able to predict thrombocytopenia with 76% sensitivity and 91% specificity. The positive predictive value was 79.4%, and the negative predictive value was 89.2%.
Image by Eric Smith
Measuring circulating histones may help physicians predict the onset of thrombocytopenia or allow them to monitor the condition in patients who are critically ill, according to researchers.
They noted that histones induce profound thrombocytopenia in mice and are associated with organ injury when released after extensive cell damage in patients who are critically ill.
So the team decided to examine the association between circulating histones and thrombocytopenia in patients in the intensive care unit (ICU).
Cheng-Hock Toh, MD, of the University of Liverpool in the UK, and his colleagues conducted this research and reported the results in a letter to JAMA.
The researchers analyzed 56 patients with thrombocytopenia and 56 controls with normal platelet counts who were admitted to the ICU at Royal Liverpool University Hospital between June 2013 and January 2014.
Thrombocytopenia was defined as a platelet count less than 150 × 103/µL, a 25% or greater decrease in platelet count, or both within the first 96 hours of ICU admission.
The researchers noted that, at approximately 30 µg/mL, histones bind platelets and cause platelet aggregation, which results in profound thrombocytopenia in mice.
So the team used this as a cutoff to stratify thrombocytopenic patients. A “high” level of histones was 30 µg/mL or greater, and a “low” level was below 30 µg/mL.
The researchers detected circulating histones in 51 of the thrombocytopenic patients and 31 controls—91% and 55%, respectively (P<0.001). Histone levels were 2.5- to 5.5-fold higher in thrombocytopenic patients than in controls.
Thrombocytopenic patients with high histone levels at ICU admission had significantly lower platelet counts and a significantly higher percentage of decrease in platelet counts at 24 hours (P=0.02 and P=0.04, respectively) and 48 hours (P=0.003 and P=0.005, respectively) after admission.
High admission histone levels were associated with moderate to severe thrombocytopenia and the development of clinically important thrombocytopenia (P<0.001).
A 30 µg/mL histone concentration was able to predict thrombocytopenia with 76% sensitivity and 91% specificity. The positive predictive value was 79.4%, and the negative predictive value was 89.2%.
Adjunct T-cell therapy granted orphan designation
The US Food and Drug Administration (FDA) has granted orphan drug designation for BPX-501, an adjunct T-cell therapy.
The designation is for the combination of BPX-501 genetically modified T cells and the activator agent rimiducid as replacement T-cell therapy for the treatment of immunodeficiency and graft-versus-host disease (GVHD) after allogeneic hematopoietic stem cell transplant (HSCT).
BPX-501 consists of genetically modified donor T cells incorporating the CaspaCIDe safety switch, which is designed to eliminate cells in the event of toxicity.
The CaspaCIDe switch consists of the CID-binding domain coupled to the signaling domain of caspase-9, an enzyme that is part of the apoptotic pathway. Infusion of rimiducid is designed to trigger activation of this domain of caspase-9 (iCasp9), which leads to selective apoptosis of the CaspaCIDe-containing cells.
This technology is intended to provide a safety net to eliminate BPX-501 alloreactive T cells if severe GVHD occurs, ostensibly enabling physicians to more safely perform haploidentical HSCTs by adding back the BPX-501 genetically engineered T cells to speed immune reconstitution and provide control over viral infections.
Following an allogeneic HSCT, a lack of sufficient mature T cells constitutes immune deficiency that can contribute to infections, viral reactivation, and relapse.
The ability to correct this immune deficiency by adding back mature donor T cells, without raising the risk of uncontrollable GVHD, has the potential to change the risk profile of allogeneic transplant, according to Bellicum Pharmaceuticals, the company developing BPX-501.
BPX-501 is being evaluated in multiple phase 1/2 trials in adults and pediatric patients with leukemias, lymphomas, and genetic blood diseases in the US and Europe.
About orphan designation
The FDA’s Office of Orphan Products Development grants orphan designation to drugs and biologics intended to treat, diagnose, or prevent rare diseases and disorders that affect fewer than 200,000 people in the US.
Orphan designation qualifies a company for various development incentives, including tax credits for qualified clinical testing and marketing exclusivity for a period of 7 years.
The US Food and Drug Administration (FDA) has granted orphan drug designation for BPX-501, an adjunct T-cell therapy.
The designation is for the combination of BPX-501 genetically modified T cells and the activator agent rimiducid as replacement T-cell therapy for the treatment of immunodeficiency and graft-versus-host disease (GVHD) after allogeneic hematopoietic stem cell transplant (HSCT).
BPX-501 consists of genetically modified donor T cells incorporating the CaspaCIDe safety switch, which is designed to eliminate cells in the event of toxicity.
The CaspaCIDe switch consists of the CID-binding domain coupled to the signaling domain of caspase-9, an enzyme that is part of the apoptotic pathway. Infusion of rimiducid is designed to trigger activation of this domain of caspase-9 (iCasp9), which leads to selective apoptosis of the CaspaCIDe-containing cells.
This technology is intended to provide a safety net to eliminate BPX-501 alloreactive T cells if severe GVHD occurs, ostensibly enabling physicians to more safely perform haploidentical HSCTs by adding back the BPX-501 genetically engineered T cells to speed immune reconstitution and provide control over viral infections.
Following an allogeneic HSCT, a lack of sufficient mature T cells constitutes immune deficiency that can contribute to infections, viral reactivation, and relapse.
The ability to correct this immune deficiency by adding back mature donor T cells, without raising the risk of uncontrollable GVHD, has the potential to change the risk profile of allogeneic transplant, according to Bellicum Pharmaceuticals, the company developing BPX-501.
BPX-501 is being evaluated in multiple phase 1/2 trials in adults and pediatric patients with leukemias, lymphomas, and genetic blood diseases in the US and Europe.
About orphan designation
The FDA’s Office of Orphan Products Development grants orphan designation to drugs and biologics intended to treat, diagnose, or prevent rare diseases and disorders that affect fewer than 200,000 people in the US.
Orphan designation qualifies a company for various development incentives, including tax credits for qualified clinical testing and marketing exclusivity for a period of 7 years.
The US Food and Drug Administration (FDA) has granted orphan drug designation for BPX-501, an adjunct T-cell therapy.
The designation is for the combination of BPX-501 genetically modified T cells and the activator agent rimiducid as replacement T-cell therapy for the treatment of immunodeficiency and graft-versus-host disease (GVHD) after allogeneic hematopoietic stem cell transplant (HSCT).
BPX-501 consists of genetically modified donor T cells incorporating the CaspaCIDe safety switch, which is designed to eliminate cells in the event of toxicity.
The CaspaCIDe switch consists of the CID-binding domain coupled to the signaling domain of caspase-9, an enzyme that is part of the apoptotic pathway. Infusion of rimiducid is designed to trigger activation of this domain of caspase-9 (iCasp9), which leads to selective apoptosis of the CaspaCIDe-containing cells.
This technology is intended to provide a safety net to eliminate BPX-501 alloreactive T cells if severe GVHD occurs, ostensibly enabling physicians to more safely perform haploidentical HSCTs by adding back the BPX-501 genetically engineered T cells to speed immune reconstitution and provide control over viral infections.
Following an allogeneic HSCT, a lack of sufficient mature T cells constitutes immune deficiency that can contribute to infections, viral reactivation, and relapse.
The ability to correct this immune deficiency by adding back mature donor T cells, without raising the risk of uncontrollable GVHD, has the potential to change the risk profile of allogeneic transplant, according to Bellicum Pharmaceuticals, the company developing BPX-501.
BPX-501 is being evaluated in multiple phase 1/2 trials in adults and pediatric patients with leukemias, lymphomas, and genetic blood diseases in the US and Europe.
About orphan designation
The FDA’s Office of Orphan Products Development grants orphan designation to drugs and biologics intended to treat, diagnose, or prevent rare diseases and disorders that affect fewer than 200,000 people in the US.
Orphan designation qualifies a company for various development incentives, including tax credits for qualified clinical testing and marketing exclusivity for a period of 7 years.
MSC product may treat refractory aGVHD
HONOLULU—A mesenchymal stem cell (MSC) product has shown promise for treating children with steroid-refractory acute graft-versus-host disease (aGVHD), according to researchers.
The product, remestemcel-L (MSC-100-IV, formerly Prochymal), produced an overall response rate of 65% by 28 days after treatment.
And patients who responded to remestemcel-L had significantly better survival at day 100 than patients who did not respond.
Joanne Kurtzberg, MD, of Duke University Medical Center in Durham, North Carolina, presented these data at the 2016 BMT Tandem Meetings (abstract 54). The study was sponsored by Mesoblast, the company developing remestemcel-L.
“There is a critical and urgent need for an effective and well-tolerated treatment for the very ill children who develop [GVHD] after a bone marrow transplant,” Dr Kurtzberg said. “While, historically, there is a high mortality rate associated with this complication, we are now seeing the majority of children who receive Mesoblast’s cell therapy respond and survive.”
For this study, Dr Kurtzberg and her colleagues assessed 241 children treated in Mesoblast’s Expanded Access Program, which was conducted at 50 sites in North American and Europe from 2007 to 2014.
Forty-five percent of the children received a bone marrow transplant, 31% received cord blood, and 45% had a mismatched transplant. Their median age was 9.6 (range, 2 months-18 years), 61% were male, and 60% were Caucasian.
All of the patients had steroid-refractory aGVHD. Thirty percent had grade C GVHD, 50% had grade D, 50% had multi-organ disease, and 79% were classified as “high-risk” disease.
Treatment
All 241 children received remestemcel-L, which consists of bone-marrow derived and culture-expanded human MSCs. The initial treatment was 2 million MSCs/kg twice a week for 4 weeks, at least 3 days apart.
Continued treatment consisted of 2 million MSCs/kg once a week for 4 weeks if patients achieved a partial or mixed response (improvement in one organ with deterioration in another organ) at the day-28 assessment.
The patients received a total of 2434 infusions. The median number of infusions was 11 (range, 1-24), and the median duration of treatment was 46 days (range, 1-186). Eighty-one percent (123/152) of eligible patients with a partial or mixed response at day 28 received continued therapy of 1 infusion a week for 4 weeks.
Results
Fifty-seven percent of patients (n=138) had at least 1 serious adverse event. About 5% (n=11) were considered treatment-related, and 1.7% (n=4) led to study discontinuation. There was 1 infusion reaction.
Thirty-four percent of patients (n=81) died through day 100, and 2.5% (n=6) experienced a relapse of their underlying disease.
At day 28 after treatment, the overall response rate was 65%, with a complete response rate of 14% and partial response rate of 51%. Responses were observed for all aGVHD grades and did not differ by baseline organ involvement.
When remestemcel-L was used as front-line therapy following steroid failure, the response rate was 81%. In patients with gastrointestinal and liver disease, the overall response rates were 65% and 62%, respectively.
Children who achieved a response at day 28 had significantly improved survival, compared to those who did not—82% and 39%, respectively (P<0.0001).
Extending therapy beyond day 28 in children who had a mixed response at day 28 resulted in significantly improved survival as well. Survival was 72% for these patients, compared to 18% for patients with a mixed response who did not receive additional therapy (P=0.003).
Mesoblast is now conducting a 60-patient, open label, phase 3 trial using remestemcel-L as front-line therapy in children with steroid-refractory aGVHD.
HONOLULU—A mesenchymal stem cell (MSC) product has shown promise for treating children with steroid-refractory acute graft-versus-host disease (aGVHD), according to researchers.
The product, remestemcel-L (MSC-100-IV, formerly Prochymal), produced an overall response rate of 65% by 28 days after treatment.
And patients who responded to remestemcel-L had significantly better survival at day 100 than patients who did not respond.
Joanne Kurtzberg, MD, of Duke University Medical Center in Durham, North Carolina, presented these data at the 2016 BMT Tandem Meetings (abstract 54). The study was sponsored by Mesoblast, the company developing remestemcel-L.
“There is a critical and urgent need for an effective and well-tolerated treatment for the very ill children who develop [GVHD] after a bone marrow transplant,” Dr Kurtzberg said. “While, historically, there is a high mortality rate associated with this complication, we are now seeing the majority of children who receive Mesoblast’s cell therapy respond and survive.”
For this study, Dr Kurtzberg and her colleagues assessed 241 children treated in Mesoblast’s Expanded Access Program, which was conducted at 50 sites in North American and Europe from 2007 to 2014.
Forty-five percent of the children received a bone marrow transplant, 31% received cord blood, and 45% had a mismatched transplant. Their median age was 9.6 (range, 2 months-18 years), 61% were male, and 60% were Caucasian.
All of the patients had steroid-refractory aGVHD. Thirty percent had grade C GVHD, 50% had grade D, 50% had multi-organ disease, and 79% were classified as “high-risk” disease.
Treatment
All 241 children received remestemcel-L, which consists of bone-marrow derived and culture-expanded human MSCs. The initial treatment was 2 million MSCs/kg twice a week for 4 weeks, at least 3 days apart.
Continued treatment consisted of 2 million MSCs/kg once a week for 4 weeks if patients achieved a partial or mixed response (improvement in one organ with deterioration in another organ) at the day-28 assessment.
The patients received a total of 2434 infusions. The median number of infusions was 11 (range, 1-24), and the median duration of treatment was 46 days (range, 1-186). Eighty-one percent (123/152) of eligible patients with a partial or mixed response at day 28 received continued therapy of 1 infusion a week for 4 weeks.
Results
Fifty-seven percent of patients (n=138) had at least 1 serious adverse event. About 5% (n=11) were considered treatment-related, and 1.7% (n=4) led to study discontinuation. There was 1 infusion reaction.
Thirty-four percent of patients (n=81) died through day 100, and 2.5% (n=6) experienced a relapse of their underlying disease.
At day 28 after treatment, the overall response rate was 65%, with a complete response rate of 14% and partial response rate of 51%. Responses were observed for all aGVHD grades and did not differ by baseline organ involvement.
When remestemcel-L was used as front-line therapy following steroid failure, the response rate was 81%. In patients with gastrointestinal and liver disease, the overall response rates were 65% and 62%, respectively.
Children who achieved a response at day 28 had significantly improved survival, compared to those who did not—82% and 39%, respectively (P<0.0001).
Extending therapy beyond day 28 in children who had a mixed response at day 28 resulted in significantly improved survival as well. Survival was 72% for these patients, compared to 18% for patients with a mixed response who did not receive additional therapy (P=0.003).
Mesoblast is now conducting a 60-patient, open label, phase 3 trial using remestemcel-L as front-line therapy in children with steroid-refractory aGVHD.
HONOLULU—A mesenchymal stem cell (MSC) product has shown promise for treating children with steroid-refractory acute graft-versus-host disease (aGVHD), according to researchers.
The product, remestemcel-L (MSC-100-IV, formerly Prochymal), produced an overall response rate of 65% by 28 days after treatment.
And patients who responded to remestemcel-L had significantly better survival at day 100 than patients who did not respond.
Joanne Kurtzberg, MD, of Duke University Medical Center in Durham, North Carolina, presented these data at the 2016 BMT Tandem Meetings (abstract 54). The study was sponsored by Mesoblast, the company developing remestemcel-L.
“There is a critical and urgent need for an effective and well-tolerated treatment for the very ill children who develop [GVHD] after a bone marrow transplant,” Dr Kurtzberg said. “While, historically, there is a high mortality rate associated with this complication, we are now seeing the majority of children who receive Mesoblast’s cell therapy respond and survive.”
For this study, Dr Kurtzberg and her colleagues assessed 241 children treated in Mesoblast’s Expanded Access Program, which was conducted at 50 sites in North American and Europe from 2007 to 2014.
Forty-five percent of the children received a bone marrow transplant, 31% received cord blood, and 45% had a mismatched transplant. Their median age was 9.6 (range, 2 months-18 years), 61% were male, and 60% were Caucasian.
All of the patients had steroid-refractory aGVHD. Thirty percent had grade C GVHD, 50% had grade D, 50% had multi-organ disease, and 79% were classified as “high-risk” disease.
Treatment
All 241 children received remestemcel-L, which consists of bone-marrow derived and culture-expanded human MSCs. The initial treatment was 2 million MSCs/kg twice a week for 4 weeks, at least 3 days apart.
Continued treatment consisted of 2 million MSCs/kg once a week for 4 weeks if patients achieved a partial or mixed response (improvement in one organ with deterioration in another organ) at the day-28 assessment.
The patients received a total of 2434 infusions. The median number of infusions was 11 (range, 1-24), and the median duration of treatment was 46 days (range, 1-186). Eighty-one percent (123/152) of eligible patients with a partial or mixed response at day 28 received continued therapy of 1 infusion a week for 4 weeks.
Results
Fifty-seven percent of patients (n=138) had at least 1 serious adverse event. About 5% (n=11) were considered treatment-related, and 1.7% (n=4) led to study discontinuation. There was 1 infusion reaction.
Thirty-four percent of patients (n=81) died through day 100, and 2.5% (n=6) experienced a relapse of their underlying disease.
At day 28 after treatment, the overall response rate was 65%, with a complete response rate of 14% and partial response rate of 51%. Responses were observed for all aGVHD grades and did not differ by baseline organ involvement.
When remestemcel-L was used as front-line therapy following steroid failure, the response rate was 81%. In patients with gastrointestinal and liver disease, the overall response rates were 65% and 62%, respectively.
Children who achieved a response at day 28 had significantly improved survival, compared to those who did not—82% and 39%, respectively (P<0.0001).
Extending therapy beyond day 28 in children who had a mixed response at day 28 resulted in significantly improved survival as well. Survival was 72% for these patients, compared to 18% for patients with a mixed response who did not receive additional therapy (P=0.003).
Mesoblast is now conducting a 60-patient, open label, phase 3 trial using remestemcel-L as front-line therapy in children with steroid-refractory aGVHD.
Poverty tied to early relapse in kids with ALL
Photo by Logan Tuttle
A new study suggests children with acute lymphoblastic leukemia (ALL) are more likely to suffer early relapse if they live in high-poverty areas.
All of the children studied received the same treatment, and the rates of relapse were similar regardless of poverty level.
But early relapse was more common among children from poorer areas. These children also had a lower rate of 5-year overall survival, but the difference was not significant.
Kira Bona, MD, of Dana-Farber Cancer Institute in Boston, Massachusetts, and her colleagues reported these results in Pediatric Blood & Cancer.
The team examined outcomes for 575 children, ages 1 to 18, with newly diagnosed ALL who were treated on Dana-Farber Cancer Institute ALL Consortium Protocols at 7 major academic medical centers in the US between 2000 and 2010.
Using US Census Bureau criteria, the investigators defined high-poverty areas as zip codes where 20% or more of residents have incomes below the federal poverty level. For a family of 4, this translates to an annual income of $24,250 or less.
Dr Bona and her colleagues found the overall rates of relapse were similar between children from low-poverty areas and those from high-poverty areas.
However, the timing of relapse differed significantly. Ninety-two percent of children from high-poverty areas who relapsed suffered early relapse (less than 36 months after first achieving complete remission), while 48% of the other children who relapsed did so early (P=0.008).
The 5-year overall survival was 85% for children from high-poverty areas and 92% for children from low-poverty areas. This difference is statistically significant when considered on its own (P=0.02) but not when the analysis is adjusted for other factors (P=0.07).
Still, the investigators said this suggests a possible disparity in survival.
“These children are getting the same best possible care at well-resourced institutions from highly trained clinicians, and we’re still seeing disparities,” Dr Bona said. “In trying to improve cure rates, we, as a field, have focused almost exclusively on biology. If we want to move forward, we also have to look at social determinants.”
Next steps
Dr Bona and her colleagues are undertaking further research designed to delve deeper into the relationship between socioeconomic status and outcomes and to allow for the development of poverty-targeted interventions.
As part of a prospective trial for children with ALL, the researchers will investigate associations between disease outcomes and the socioeconomic status of patients’ families, using a targetable measure of socioeconomic status called material hardship (food, housing, and/or energy insecurity).
The researchers will also investigate possible mechanisms underlying the relationship between socioeconomic status and early relapse, including adherence to oral chemotherapy and delays or dose reductions in chemotherapy due to a child’s underlying health.
In another study, investigators will conduct in-depth interviews with patients’ families, probing their knowledge and experience to pinpoint factors that might explain the disparity in outcomes and identify factors that can be targeted with interventions.
“Doing these next 2 studies is incredibly important,” Dr Bona said. “This study told us that simply providing the current best treatment regimen is not good enough if our goal is to cure every child with cancer.”
“At the same time that we develop new drugs and new treatment protocols, we need to address social determinants of health. Findings from these next studies will help us develop specific interventions to address disparities in outcomes. That’s an amazing opportunity.”
Photo by Logan Tuttle
A new study suggests children with acute lymphoblastic leukemia (ALL) are more likely to suffer early relapse if they live in high-poverty areas.
All of the children studied received the same treatment, and the rates of relapse were similar regardless of poverty level.
But early relapse was more common among children from poorer areas. These children also had a lower rate of 5-year overall survival, but the difference was not significant.
Kira Bona, MD, of Dana-Farber Cancer Institute in Boston, Massachusetts, and her colleagues reported these results in Pediatric Blood & Cancer.
The team examined outcomes for 575 children, ages 1 to 18, with newly diagnosed ALL who were treated on Dana-Farber Cancer Institute ALL Consortium Protocols at 7 major academic medical centers in the US between 2000 and 2010.
Using US Census Bureau criteria, the investigators defined high-poverty areas as zip codes where 20% or more of residents have incomes below the federal poverty level. For a family of 4, this translates to an annual income of $24,250 or less.
Dr Bona and her colleagues found the overall rates of relapse were similar between children from low-poverty areas and those from high-poverty areas.
However, the timing of relapse differed significantly. Ninety-two percent of children from high-poverty areas who relapsed suffered early relapse (less than 36 months after first achieving complete remission), while 48% of the other children who relapsed did so early (P=0.008).
The 5-year overall survival was 85% for children from high-poverty areas and 92% for children from low-poverty areas. This difference is statistically significant when considered on its own (P=0.02) but not when the analysis is adjusted for other factors (P=0.07).
Still, the investigators said this suggests a possible disparity in survival.
“These children are getting the same best possible care at well-resourced institutions from highly trained clinicians, and we’re still seeing disparities,” Dr Bona said. “In trying to improve cure rates, we, as a field, have focused almost exclusively on biology. If we want to move forward, we also have to look at social determinants.”
Next steps
Dr Bona and her colleagues are undertaking further research designed to delve deeper into the relationship between socioeconomic status and outcomes and to allow for the development of poverty-targeted interventions.
As part of a prospective trial for children with ALL, the researchers will investigate associations between disease outcomes and the socioeconomic status of patients’ families, using a targetable measure of socioeconomic status called material hardship (food, housing, and/or energy insecurity).
The researchers will also investigate possible mechanisms underlying the relationship between socioeconomic status and early relapse, including adherence to oral chemotherapy and delays or dose reductions in chemotherapy due to a child’s underlying health.
In another study, investigators will conduct in-depth interviews with patients’ families, probing their knowledge and experience to pinpoint factors that might explain the disparity in outcomes and identify factors that can be targeted with interventions.
“Doing these next 2 studies is incredibly important,” Dr Bona said. “This study told us that simply providing the current best treatment regimen is not good enough if our goal is to cure every child with cancer.”
“At the same time that we develop new drugs and new treatment protocols, we need to address social determinants of health. Findings from these next studies will help us develop specific interventions to address disparities in outcomes. That’s an amazing opportunity.”
Photo by Logan Tuttle
A new study suggests children with acute lymphoblastic leukemia (ALL) are more likely to suffer early relapse if they live in high-poverty areas.
All of the children studied received the same treatment, and the rates of relapse were similar regardless of poverty level.
But early relapse was more common among children from poorer areas. These children also had a lower rate of 5-year overall survival, but the difference was not significant.
Kira Bona, MD, of Dana-Farber Cancer Institute in Boston, Massachusetts, and her colleagues reported these results in Pediatric Blood & Cancer.
The team examined outcomes for 575 children, ages 1 to 18, with newly diagnosed ALL who were treated on Dana-Farber Cancer Institute ALL Consortium Protocols at 7 major academic medical centers in the US between 2000 and 2010.
Using US Census Bureau criteria, the investigators defined high-poverty areas as zip codes where 20% or more of residents have incomes below the federal poverty level. For a family of 4, this translates to an annual income of $24,250 or less.
Dr Bona and her colleagues found the overall rates of relapse were similar between children from low-poverty areas and those from high-poverty areas.
However, the timing of relapse differed significantly. Ninety-two percent of children from high-poverty areas who relapsed suffered early relapse (less than 36 months after first achieving complete remission), while 48% of the other children who relapsed did so early (P=0.008).
The 5-year overall survival was 85% for children from high-poverty areas and 92% for children from low-poverty areas. This difference is statistically significant when considered on its own (P=0.02) but not when the analysis is adjusted for other factors (P=0.07).
Still, the investigators said this suggests a possible disparity in survival.
“These children are getting the same best possible care at well-resourced institutions from highly trained clinicians, and we’re still seeing disparities,” Dr Bona said. “In trying to improve cure rates, we, as a field, have focused almost exclusively on biology. If we want to move forward, we also have to look at social determinants.”
Next steps
Dr Bona and her colleagues are undertaking further research designed to delve deeper into the relationship between socioeconomic status and outcomes and to allow for the development of poverty-targeted interventions.
As part of a prospective trial for children with ALL, the researchers will investigate associations between disease outcomes and the socioeconomic status of patients’ families, using a targetable measure of socioeconomic status called material hardship (food, housing, and/or energy insecurity).
The researchers will also investigate possible mechanisms underlying the relationship between socioeconomic status and early relapse, including adherence to oral chemotherapy and delays or dose reductions in chemotherapy due to a child’s underlying health.
In another study, investigators will conduct in-depth interviews with patients’ families, probing their knowledge and experience to pinpoint factors that might explain the disparity in outcomes and identify factors that can be targeted with interventions.
“Doing these next 2 studies is incredibly important,” Dr Bona said. “This study told us that simply providing the current best treatment regimen is not good enough if our goal is to cure every child with cancer.”
“At the same time that we develop new drugs and new treatment protocols, we need to address social determinants of health. Findings from these next studies will help us develop specific interventions to address disparities in outcomes. That’s an amazing opportunity.”
Regionalized Care and Adverse Events
Failures in communication among healthcare professionals are known threats to patient safety. These failures account for over 60% of root causes of sentinel events, the most serious events reported to The Joint Commission.[1] As such, identifying both patterns of effective communication as well as barriers to successful communication has been a focus of efforts aimed at improving patient safety. However, to date, the majority of this work has centered on improving communication in settings such as the operating room and intensive care unit,[2, 3, 4] or at times of care transitions.[5, 6, 7, 8]
Unique barriers exist for effective interdisciplinary communication in the hospital setting, particularly physiciannurse communication regarding shared hospitalized patients.[9] Traditionally, care of hospitalized patients is provided by physicians, nurses, and other team members working in varied workflow patterns, leading to dispersed team membership, where each team member cares for different groups of patients in different locations across the hospital. This dispersion is further heightened on teaching services, where residents' rotation schedules lead to frequent changes of care team membership, leaving inpatient care teams particularly vulnerable to ineffective communication. Evidence suggests that communication between nurses and physicians is currently suboptimal, leading to frequent disagreement regarding the patient's plan of care.[9, 10] This divergence between physician and nursing perceptions of patients' care plans may leave patients at greater risk of adverse events (AEs).
Several studies have examined the effects of regionalized inpatient care teams, where multidisciplinary team members care for the same patients on the same hospital unit, on communication and patient outcomes.[4, 11, 12, 13, 14] Results of these studies have been inconsistent, perhaps due to the particular characteristics of the care teams or to the study methodology. Thus, further rigorously done studies are required to better understand the impact of team regionalization on patient care. The goal of this study was to examine whether the implementation of regionalized inpatient care teams was associated with improvements in care team communication and preventable AEs.
METHODS
Setting, Patients, and Study Design
We performed a cohort analysis of patients at a 700‐bed tertiary care center, pre‐ and postregionalization of inpatient general medicine care teams. Our study protocol was approved by the Partners Healthcare Human Subjects Review Committee. Patients were eligible for inclusion if they were 18 years of age or older and discharged from the general medicine service (GMS) from any of the 3 participating nursing units between April 1, 2012 and June 19, 2012 (preregionalization) or April 1, 2013 and June 19, 2013 (postregionalization).
Intervention
On June 20, 2012, regionalized care was implemented on the GMS such that each of 3 GMS teams was localized to 1 of 3, 15‐bed nursing units. Prior to regionalization, the GMS physician care teams, each consisting of 1 hospitalist attending, 1 medical resident, and 2 medical interns, would care for patients on an average of 7 and up to 13 different nursing units on a given day.
Regionalized care consisted of a multifaceted intervention codeveloped by hospitalist, residency, nursing, emergency department, and hospital leadership and included: (1) regionalizing GMS teams as much as possible; (2) change in resident call structure from a traditional 4‐day call cycle to daily admitting; (3) collaborative efforts to enhance GMS patient discharges before noon to promote regionalized placement of patients without prolonging time in the emergency department (ED); (4) daily morning and postround multidisciplinary huddles to prioritize sicker patients and discharges; (5) encouragement of daily rounds at patients' bedsides with presence of physician team, nurse, and team pharmacist if available; (6) creation of unit‐ and team‐level performance reports; and (7) creation of unit‐based physician and nursing co‐leadership (Figure 1).[15]

Concordance of Plan
Concordance of plan was measured via a 7‐question survey previously developed, pilot tested, and used to measure the impact of regionalized care on care team communication between inpatient nursephysician team members.[9] The survey was administered in‐person by 1 of 8 trained research assistants (RAs) (4/emntervention period) to nurse and intern pairs caring for patients on the study units pre‐ and postregionalization. GMS patients were eligible for inclusion if surveys could be administered to their nurse and intern within the first 24 hours of admission to the unit and within 48 hours of admission to the hospital, based on RA availability (thus excluding patients admitted on Fridays as surveys were not conducted over the weekend). Most often, all eligible patients admitted to the study units during time periods of data collection were included in the study. On limited occasions, the daily supply of patients surpassed RA capacity for inclusion, at which time computer‐generated randomization was utilized to randomly select patients for inclusion. Nurse and intern pairs were surveyed once during a patient's hospitalization, although they could be surveyed more than once about different patients, and patients could be included more than once if rehospitalized on the study unit and cared for by a different nurseintern pair. Of the 472 selected eligible patients, the nurses and interns of 418 patients were available and consented to survey administration, representing 361 unique nurse and intern pairs and 399 unique patients.
Each member of the pair was asked about 7 specific aspects of the patient's care plan for that day in isolation from the other team member, including: (1) the patient's primary diagnosis, (2) the patient's expressed chief concern, (3) the day's scheduled tests, (4) the day's scheduled procedures, (5) consulting services involved, (6) medication changes made that day, and (7) the patient's expected discharge date. In addition, each pair was asked the name of the other team member (ie, the nurse was asked the name of the intern and vice versa), and whether or not the patient care plan for the day had been discussed with the other team member, where concordance was defined as both members agreeing the plan had been discussed. All responses were recorded verbatim. Pairs were surveyed independently between 12 pm and 2 pm, limiting confounding by evolving plans of care over time.
Each set of surveys were then reviewed by 2 of 4 trained adjudicators, and responses to each question were scored as complete, partial, or no agreement. Rules for degree of agreement were based upon previously utilized parameters[9] as well as biweekly meetings during which common themes and disagreements in ratings were discussed, and rules generated to create consensus (see Supporting Information, Appendix, in the online version of this article).
Adverse Event Detection
Of the patients meeting eligibility criteria, 200 patients were randomly selected using computer‐generated randomization from each time period for AE outcome assessment, for a total of 400 patients.
Each patient's electronic medical record was retrospectively reviewed by a trained clinician using a previously validated screening tool to detect any possible AEs.[11] Any positive screen prompted documentation of a narrative summary including a short description of the possible AE and pertinent associated data. We defined AE as any injury due to medical management rather than the natural history of the illness, and further limited this definition to only include AEs that occurred on the study unit or as a result of care on that unit.
Two of 4 trained adjudicators, blinded to time period, then separately reviewed each narrative summary using previously validated 6‐point confidence scales to determine the presence and preventability of AE, with confidence ratings of 4 or greater used as cutoffs.[11] All AEs were also scored on a 4‐point severity scale (trivial, clinically significant, serious, or life threatening), with severe AE defined as serious or life threatening. Lastly, adjudicators grouped AEs into 1 of 10 prespecified categories.[11] Any disagreements in ratings or groupings were discussed by all 4 adjudicators to reach consensus.
Data Analysis
Patient characteristics are presented using descriptive statistics and were compared in the pre‐ and postregionalization time periods using 2 or t tests as appropriate.
To analyze whether regionalized care was associated with concordance of plan, adjudicated survey questions were assigned points of 1, 0.5, and 0 for complete, partial, and no agreement, respectively. Total mean concordance scores for any patient ranged from 0 to 7 points, and were divided by total number of answered questions (up to 7) for a range of 0 to 1. Total mean concordance scores as well as mean concordance score per survey question were compared pre‐ versus postregionalization using t tests. In sensitivity analyses, adjudicated survey responses were dichotomized with complete and partial agreement deemed concordant responses. Percent concordance for each question was then compared pre‐ versus postregionalization using 2 analysis. Questions about the name of the other team member and discussion of daily care plan with the other team member were excluded from total concordance score calculations and were compared individually pre‐ versus postregionalization, because they are not directly about the plan of care.
To analyze the association of regionalization with odds of preventable AE, we performed multivariable logistic regression adjusted for patient age, sex, race, language, and Elixhauser comorbidity score,[16] and utilized generalized estimating equations to account for clustering by hospital unit. Secondary outcomes included severe preventable AEs, nonpreventable AEs, and category of preventable AEs using similar methodology. Two‐sided P values <0.05 were considered significant, and SAS version 9.2 (SAS Institute Inc., Cary, NC) was used for all analyses.
RESULTS
The fidelity of the intervention in achieving its goal of regionalized care is discussed separately.[15] Briefly, the intervention was successful at achieving 85% regionalization by team (ie, average daily percentage of team's patients assigned to team's unit) and 87% regionalization by unit (ie, average daily percentage of unit's patients with assigned team) following implementation, compared to 20% regionalization by team and unit in the preintervention period. Importantly, the average daily census of physician care teams rose by 32%, from a mean of 10.8 patients/physician care team preregionalization to a mean of 14.3 patients/physician care team postregionalization.
Concordance of Plan
Of the 418 nurse and intern paired surveys, 4 surveys were excluded due to repeat surveys of the same patient during the same hospitalization, for a total of 197 distinct paired surveys preregionalization and 217 paired surveys postregionalization. There were no statistically significant differences in patients' age, sex, race, language, admission source, length of stay, Elixhauser comorbidity score and diagnosis‐related group weight pre‐ versus postregionalization (Table 1).
Characteristic | Concordance of Care Plan | Adverse Events | ||||
---|---|---|---|---|---|---|
Pre, n = 197 | Post, n = 217 | P Value | Pre, n = 198 | Post, n = 194 | P Value | |
| ||||||
Age, mean (SD) | 60.5 (19.4) | 57.6 (20.8) | 0.15 | 60.4 (18.9) | 58.0 (21.2) | 0.24 |
Male, n (%) | 77 (39.1) | 92 (42.4) | 0.49 | 94 (47.5) | 85 (43.8) | 0.55 |
Race/ethnicity, n (%) | 0.34 | 0.12 | ||||
White | 134 (68.0) | 141 (65.0) | 132 (66.5) | 121 (62.4) | ||
Black | 42 (21.3) | 45 (20.7) | 41 (20.8) | 54 (27.8) | ||
Hispanic | 18 (9.1) | 21 (9.7) | 22 (11.3) | 13 (6.8) | ||
Other/unknown | 3 (1.5) | 10 (4.6) | 3 (1.4) | 6 (2.9) | ||
Language, n (%) | 0.30 | 0.73 | ||||
English | 183 (92.9) | 203 (93.5) | 176 (88.7) | 175 (90.2) | ||
Spanish | 6 (3.0) | 10 (4.6) | 10 (5.2) | 10 (5.3) | ||
Other | 8 (4.1) | 4 (1.8) | 12 (6.1) | 9 (4.5) | ||
Admitting source, n (%) | 1.00 | 0.10 | ||||
Physician office | 13 (6.6) | 13 (6.0) | 13 (6.6) | 6 (3.1) | ||
Emergency department | 136 (69.0) | 150 (69.1) | 126 (63.6) | 127 (65.5) | ||
Transfer from different hospital | 40 (20.3) | 45 (20.7) | 54 (27.3) | 50 (25.8) | ||
Transfer from skilled nursing facility | 8 (4.1) | 9 (4.2) | 5 (2.5) | 11 (5.6) | ||
Length of stay, d, median (IQR) | 3.0 (4.0) | 3.0 (4.0) | 0.57 | 4.0 (5.0) | 3.0 (4.0) | 0.16 |
Elixhauser Comorbidity Score, mean (SD) | 8.0 (8.8) | 8.3 (9.3) | 0.74 | 8.0 (8.6) | 7.8 (8.4) | 0.86 |
DRG weight, mean (SD) | 1.6 (1.0) | 1.5 (1.0) | 0.37 | 1.5 (0.93) | 1.5 (1.1) | 0.96 |
Kappa scores for adjudications of concordance surveys (defined as both adjudicators scoring the same level of agreement (ie, both complete or partial agreement versus no agreement) ranged from 0.69 to 0.95, by question. There were no significant differences in total mean concordance scores in the care plan pre‐ versus postregionalization (0.65 vs 0.67, P = 0.26) (Table 2). Similarly, there were no significant differences in mean concordance score for each survey question, except agreement on expected date of discharge (0.56 vs 0.68, P = 0.003), knowledge of the other provider's name, and agreement that discussion of the daily plan had taken place with the other pair member. Similar results were seen when results were dichotomized (ie, partial or complete agreement vs no agreement) (Table 2).
Concordance Outcome | Pre, n = 197 | Post, n = 217 | P Value |
---|---|---|---|
| |||
Concordance score* | |||
Total concordance score, mean (SD) | 0.65 (0.17) | 0.67 (0.16) | 0.26 |
Subgroups | |||
Diagnosis | 0.77 (0.32) | 0.72 (0.35) | 0.11 |
Patient's chief concern | 0.48 (0.44) | 0.48 (0.43) | 0.94 |
Tests today | 0.67 (0.40) | 0.71 (0.42) | 0.36 |
Procedures today | 0.93 (0.25) | 0.92 (0.25) | 0.71 |
Medication changes today | 0.56 (0.44) | 0.59 (0.43) | 0.54 |
Consulting services | 0.59 (0.44) | 0.60 (0.44) | 0.82 |
Expected discharge date | 0.56 (0.44) | 0.68 (0.38) | 0.003 |
Responding clinician knowledge of nurse's name | 0.56 (0.50) | 0.86 (0.35) | <0.001 |
Nurse's knowledge of responding clinician's name | 0.56 (0.50) | 0.88 (0.33) | <0.001 |
Plan discussed | 0.73 (0.45) | 0.88 (0.32) | <0.001 |
Percent concordance, mean (SD) | |||
Diagnosis | 92.0 (27.3) | 88.6 (31.9) | 0.25 |
Patient's chief concern | 59.6 (49.1) | 60.6 (49.0) | 0.84 |
Tests today | 78.9 (40.9) | 77.2 (42.1) | 0.67 |
Procedures today | 93.5 (24.8) | 94.1 (23.7) | 0.80 |
Medication changes today | 66.3 (33.6) | 69.9 (46.0) | 0.44 |
Consulting services | 69.3 (46.2) | 68.9 (46.4) | 0.93 |
Expected discharge date | 67.5 (47.0) | 82.6 (38.0) | <0.001 |
Responding clinician knowledge of nurse's name | 55.7 (49.8) | 85.6 (35.2) | <0.001 |
Nurse's knowledge of responding clinician's name | 55.9 (49.8) | 87.9 (32.8) | <0.001 |
Plan discussed | 72.9 (44.6) | 88.2 (32.3) | <0.001 |
Adverse Events
Of the 400 patients screened for AEs, 8 were excluded due to missing medical record number (5) and discharge outside of study period (3). Of the final 392 patient screens (198 pre, 194 post), there were no significant differences in patients' age, sex, race, language, length of stay, or Elixhauser score pre‐ versus postregionalization (Table 1).
Kappa scores for adjudicator agreement were 0.35 for presence of AE and 0.34 for preventability of AE. Of the 392 reviewed patient records, there were 133 total AEs detected (66 pre, 67 post), 27 preventable AEs (13 pre, 14 post), and 9 severe preventable AEs (4 pre, 5 post) (Table 3). There was no significant difference in the adjusted odds of preventable AEs post‐ versus preregionalization (adjusted odds ratio: 1.37, 95% confidence interval: 0.69, 2.69). Although the low number of AEs rated as severe or life threatening precluded adjusted analysis, unadjusted results similarly demonstrated no difference in odds of severe preventable AEs pre‐ versus postregionalization. As expected, there was no significant difference in adjusted odds of nonpreventable AE after implementation of regionalized care (Table 3).
Adverse Events | No. of Adverse Events | Adjusted Odds Ratio Post vs Pre (95% CI) | |
---|---|---|---|
Pre, n = 198 | Post, n = 194 | ||
| |||
Preventable | 13 | 14 | 1.37 (0.69, 2.69) |
Serious and preventable | 4 | 5 | |
Nonpreventable | 47 | 50 | 1.20 (0.85, 1.75) |
Similarly, there were no significant differences in category of preventable AE pre‐ versus postregionalization. The most frequent preventable AEs in both time periods were those related to adverse drug events and to manifestations of poor glycemic control, examples of which are illustrated (Table 4).
| |
Adverse drug event | 29‐year‐old male with history of alcohol abuse, complicated by prior withdrawal seizures/emntensive care unit admissions, presented with alcohol withdrawal. Started on standing and PRN lorazepam, kept on home medications including standing clonidine, gabapentin, citalopram, quetiapine. Became somnolent due to polypharmacy, ultimately discontinued quetiapine as discovered took only as needed at home for insomnia |
Manifestations of poor glycemic control | 78‐year‐old male with recently diagnosed lymphoma, distant history of bladder and prostate cancer status post ileal loop diversion, presented status post syncopal event; during event, spilled boiling water on himself leading to second‐degree burns on 3% of his body. Initially admitted to trauma/burn service, ultimately transferred to medical service for ongoing multiple medical issues including obstructive uropathy, acute on chronic renal failure. Adverse event was hyperglycemia (>350 mg/dL on >2 consecutive readings) in the setting of holding his home insulin detemir and insulin aspart (had been placed on insulin aspart sliding scale alone). After hyperglycemic episodes, was placed back on weight‐based basal/nutritional insulin |
DISCUSSION
In this study of general medicine patients at a large academic medical center, we found that regionalization of care teams on general medicine services was associated with improved recognition of care team members and agreement on estimated date of patient discharge, but was not associated with improvement in overall nurse and physician concordance of the patient care plan, or the odds of preventable AEs.
This intervention importantly addresses the barrier of dispersion of team membership, a well‐recognized barrier to interdisciplinary collaboration,[17, 18] particularly with resident physician teams due to frequently changing team membership. Localization of all team members, in addition to encouragement of daily collaborative bedside rounds as part of the regionalization initiative, likely contributed to our observed improvement in team member identification and discussion of daily care plans. Similarly, regionalization resulted in improved agreement in estimations of date of patient discharge. Focus on early patient discharges was an integral part of the implementation efforts; we therefore hypothesize that mutual focus on discharge planning by both nurses and responding clinicians may have explained this observed result.
On the other hand, regionalization did not appreciably improve the overall concordance of care plan between nurses and interns, despite a significant increase in team members agreeing that the plan had been discussed. Our findings support similar prior research demonstrating that regionalizing hospitalist attendings to single nursing units had limited impact on agreement of care plan between physicians and nurses.[13] Similarly, in settings where physicians and nurses are inherently regionalized, such as the intensive care unit[4] or the operating room,[3] communication between physicians and nurses remains difficult. Collectively, our findings suggest that colocalization of physicians and nurses alone is likely insufficient to improve measured communication between care team members. Existing literature suggests that more standardized approaches to improve communication, such as structured communication tools used during daily inpatient care[19, 20] or formalized team training,[21, 22, 23] lead to improvements in communication and collaboration. Despite these findings, it is important to highlight that this study did not assess other measures of workplace culture, such as teamwork and care team cohesiveness, which may have been positively affected by this intervention, even without measurable effect on concordance of care plan. Additionally, as noted, the average daily census on each team increased by almost a third postintervention, which may have impeded improvements in care team communication.
In addition, we found that our intervention had no significant impact on preventable AEs or severe preventable AEs. Although we cannot exclude the possibility that more subtle AEs were missed with our methodology, our results indicate that regionalized care alone may be inadequate to improve major patient safety outcomes. As discussed, the volume of patients did increase postintervention; thus, another way to state our results is that we were able to increase the daily volume of patients without any significant decreases in patient safety. Nevertheless, the results on patient safety were less than desired. A recent review of interdisciplinary team care interventions on general medical wards similarly demonstrated underwhelming improvements in patient safety outcomes, although the reviewed interventions did not specifically address preventable AEs, a gap in the literature commented on by the authors.[24] Other albeit limited literature has demonstrated improvement in patient safety outcomes via multifaceted efforts aimed at improving care team member communication. Notably, these efforts include colocalization of care team members to single units but also involve additional measures to improve communication and collaboration between care team members, such as structured communication during interdisciplinary rounds, and certification of key interdisciplinary teamwork skills.[11, 14] Although our regionalized care intervention included many similar features to these accountable care units (ACUs) including unit‐based care teams, unit‐level performance reporting, and unit‐based physician and nursing coleadership, significant differences existed. Notably, in addition to the above features, the ACU model also incorporated highly structured communication models for interdisciplinary rounding, and certification processes to ensure an appropriate communication skill base among care team members.[14] Thus, although creation of regionalized care teams is likely a necessary precursor to implementation of these additional measures, alone it may be insufficient to improve patient safety outcomes.
Importantly, in our study we identified that adverse drug events and manifestations of poor glycemic control occurred in high frequency both before and following implementation of regionalized care, supporting other literature that describes the prevalence of these AEs.[11, 25, 26, 27] These results suggest that targeted interventions to address these specific AEs are likely necessary. Notably, the intervention units in our study did not consistently employ clinical pharmacists assigned specifically to that unit's care team to allow for integration within the care team. As prior research has suggested that greater collaboration with clinical pharmacists results in reduction of adverse drug events,[28] next steps may include improved integration of team‐based pharmacists into the activities of the regionalized care teams. Inpatient management of diabetes also requires specific interventions,[29, 30, 31] only some of which may be addressable by having regionalized care and better interdisciplinary communication.
Our findings are subject to several limitations. First, this was a single‐site study and thus our findings may not be generalizable to other institutions. However, regionalized care is increasingly encouraged to optimize communication between care team members.[17, 18] Therefore, our null findings may be pertinent to other institutions looking to improve patient safety outcomes, demonstrating that additional initiatives will likely be required. Second, our modes of outcome measurement possess limitations. In measuring concordance of care plan, although previously used survey techniques were employed,[9] the concordance survey has not been formally validated, and we believe some of the questions may have led to ambiguity on the part of the responders that may have resulted in less accurate responses, thus biasing toward the null. Similarly, in measuring AEs, the screening tool relied on retrospective chart review looking for specific AE types[11] and thus may not have captured more subtle AEs. Additionally, our study may have been underpowered to demonstrate significant reduction in preventable AEs, although other studies of similar methodology demonstrated significant results with similar sample size.[11] This was due in part to our lower‐than‐expected baseline AE rate (6.6% compared with approximately 10.3% in previous studies).[11] Lastly, our study solely examined the association of regionalization with concordance of care plan and preventable AEs, but importantly excluded other clinically important outcomes that may have been positively (or negatively) impacted by these regionalization efforts, such as ED wait times, provider efficiency (eg, fewer pages, less time in transit, more time at the bedside), interdisciplinary teamwork, or patient or provider satisfaction.
CONCLUSION
In summary, our findings suggest that regionalized care teams alone may be insufficient to effectively promote communication between care team members regarding the care plan or to lead to improvements in patient safety, although we recognize that there may have been benefits (or unintended harms) not measured in this study but are nonetheless important for clinical care and workplace culture. This is an important lesson, as many hospitals move toward regionalized care in an effort to improve patient safety outcomes. However, strengthening the infrastructure by colocalizing care team members to maximize opportunity for communication is likely a necessary first step toward facilitating implementation of additional initiatives that may lead to more robust patient safety improvements, such as structured interdisciplinary bedside rounds (eg, facilitating and training all team members to fulfill specific roles), teamwork training, and certification of key interdisciplinary teamwork skills. Additionally, close examination of identified prevalent and preventable AEs can help to determine which additional initiatives are most likely to have greatest impact in improving patient safety.
Disclosures: This research was supported by funds provided by Brigham and Women's Hospital (BWH) and by funds provided by the Department of Medicine at BWH. All authors had full access to all of the data in the study and were integrally involved in the design, implementation, data collection, and analyses. The first author, Dr. Stephanie Mueller, takes responsibility for the integrity for the data and the accuracy of the data analysis. Dr. Schnipper reports grants from Sanofi Aventis, outside the submitted work.
- Joint Commission on Accreditation of Healthcare Organizations. Understanding and Preventing Sentinel Events in Your Health Care Organization. Oak Brook, IL: Joint Commission; 2008.
- Communication failures in the operating room: an observational classification of recurrent types and effects. Qual Saf Health Care. 2004;13(5):330–334. , , , et al.
- Operating room teamwork among physicians and nurses: teamwork in the eye of the beholder. J Am Coll Surg. 2006;202(5):746–752. , , , et al.
- Discrepant attitudes about teamwork among critical care nurses and physicians. Crit Care Med. 2003;31(3):956–959. , , .
- Communication failures in patient sign‐out and suggestions for improvement: a critical incident analysis. Qual Saf Health Care. 2005;14(6):401–407. , , , , .
- Changes in medical errors after implementation of a handoff program. N Engl J Med. 2014;371(19):1803–1812. , , , et al.
- Communication and information deficits in patients discharged to rehabilitation facilities: an evaluation of five acute care hospitals. J Hosp Med. 2009;4(8):E28–E33. , , , et al.
- Deficits in communication and information transfer between hospital‐based and primary care physicians: implications for patient safety and continuity of care. JAMA. 2007;297(8):831–841. , , , , , .
- Patterns of nurse‐physician communication and agreement on the plan of care. Qual Saf Health Care. 2010;19(3):195–199. , , , et al.
- Can we talk? Priorities for patient care differed among health care providers. In: Henriksen K, Battles JB, Marks ES, Lewin DI, eds. Advances in Patient Safety: From Research to Implementation. Vol 1. Rockville, MD: Agency for Healthcare Research and Quality; 2005. , , , , , .
- Structured interdisciplinary rounds in a medical teaching unit: improving patient safety. Arch Intern Med. 2011;171(7):678–684. , , , et al.
- Improving teamwork: impact of structured interdisciplinary rounds on a hospitalist unit. J Hosp Med. 2011;6(2):88–93. , , , , , .
- Impact of localizing physicians to hospital units on nurse‐physician communication and agreement on the plan of care. J Gen Intern Med. 2009;24(11):1223–1227. , , , et al.
- Reorganizing a hospital ward as an accountable care unit. J Hosp Med. 2015;10(1):36–40. , , , et al.
- 5th time's a charm: creation of unit‐based care teams in a high occupancy hospital [abstract]. J Hosp Med. 2015;10 (suppl. 2). Available at: http://www.shmabstracts.com/abstract/5th‐times‐a‐charm‐creation‐of‐unit‐based‐care‐teams‐in‐a‐high‐occupancy‐hospital. Accessed July 28, 2015. , , , et al.
- Comorbidity measures for use with administrative data. Med Care. 1998;36(1):8–27. , , , .
- Teamwork on inpatient medical units: assessing attitudes and barriers. Qual Saf Health Care. 2010;19(2):117–121. , , , , , .
- A model for quality improvement programs in academic departments of medicine. Am J Med. 2008;121(10):922–929. , , , et al.
- Improving nurse‐physician communication and satisfaction in the intensive care unit with a daily goals worksheet. Am J Crit Care. 2006;15(2):217–222. , , , , .
- Improving communication in the ICU using daily goals. J Crit Care. 2003;18(2):71–75. , , , , , .
- Effect of crew resource management training in a multidisciplinary obstetrical setting. Int J Qual Health Care. 2008;20(4):254–263. , , , et al.
- Error reduction and performance improvement in the emergency department through formal teamwork training: evaluation results of the MedTeams project. Health Serv Res. 2002;37(6):1553–1581. , , , et al.
- Effects of teamwork training on adverse outcomes and process of care in labor and delivery: a randomized controlled trial. Obstet Gynecol. 2007;109(1):48–55. , , , et al.
- Effects of interdisciplinary team care interventions on general medical wards: a systematic review. JAMA Intern Med. 2015;175(8):1288–1298. , , , et al.
- Patient risk factors for adverse drug events in hospitalized patients. ADE Prevention Study Group. Arch Intern Med. 1999;159(21):2553–2560. , , , et al.
- Effect of a pharmacist intervention on clinically important medication errors after hospital discharge: a randomized trial. Ann Intern Med. 2012;157(1):1–10. , , , et al.
- Use of a standardized protocol to decrease medication errors and adverse events related to sliding scale insulin. Qual Saf Health Care. 2006;15(2):89–91. , , , .
- Clinical pharmacists and inpatient medical care: a systematic review. Arch Intern Med. 2006;166(9):955–964. , , , .
- Improved inpatient use of basal insulin, reduced hypoglycemia, and improved glycemic control: effect of structured subcutaneous insulin orders and an insulin management algorithm. J Hosp Med. 2009;4(1):3–15. , , , , .
- Effects of a computerized order set on the inpatient management of hyperglycemia: a cluster‐randomized controlled trial. Endocr Pract. 2010;16(2):209–218. , , , .
- Effects of a subcutaneous insulin protocol, clinical education, and computerized order set on the quality of inpatient management of hyperglycemia: results of a clinical trial. J Hosp Med. 2009;4(1):16–27. , , , .
Failures in communication among healthcare professionals are known threats to patient safety. These failures account for over 60% of root causes of sentinel events, the most serious events reported to The Joint Commission.[1] As such, identifying both patterns of effective communication as well as barriers to successful communication has been a focus of efforts aimed at improving patient safety. However, to date, the majority of this work has centered on improving communication in settings such as the operating room and intensive care unit,[2, 3, 4] or at times of care transitions.[5, 6, 7, 8]
Unique barriers exist for effective interdisciplinary communication in the hospital setting, particularly physiciannurse communication regarding shared hospitalized patients.[9] Traditionally, care of hospitalized patients is provided by physicians, nurses, and other team members working in varied workflow patterns, leading to dispersed team membership, where each team member cares for different groups of patients in different locations across the hospital. This dispersion is further heightened on teaching services, where residents' rotation schedules lead to frequent changes of care team membership, leaving inpatient care teams particularly vulnerable to ineffective communication. Evidence suggests that communication between nurses and physicians is currently suboptimal, leading to frequent disagreement regarding the patient's plan of care.[9, 10] This divergence between physician and nursing perceptions of patients' care plans may leave patients at greater risk of adverse events (AEs).
Several studies have examined the effects of regionalized inpatient care teams, where multidisciplinary team members care for the same patients on the same hospital unit, on communication and patient outcomes.[4, 11, 12, 13, 14] Results of these studies have been inconsistent, perhaps due to the particular characteristics of the care teams or to the study methodology. Thus, further rigorously done studies are required to better understand the impact of team regionalization on patient care. The goal of this study was to examine whether the implementation of regionalized inpatient care teams was associated with improvements in care team communication and preventable AEs.
METHODS
Setting, Patients, and Study Design
We performed a cohort analysis of patients at a 700‐bed tertiary care center, pre‐ and postregionalization of inpatient general medicine care teams. Our study protocol was approved by the Partners Healthcare Human Subjects Review Committee. Patients were eligible for inclusion if they were 18 years of age or older and discharged from the general medicine service (GMS) from any of the 3 participating nursing units between April 1, 2012 and June 19, 2012 (preregionalization) or April 1, 2013 and June 19, 2013 (postregionalization).
Intervention
On June 20, 2012, regionalized care was implemented on the GMS such that each of 3 GMS teams was localized to 1 of 3, 15‐bed nursing units. Prior to regionalization, the GMS physician care teams, each consisting of 1 hospitalist attending, 1 medical resident, and 2 medical interns, would care for patients on an average of 7 and up to 13 different nursing units on a given day.
Regionalized care consisted of a multifaceted intervention codeveloped by hospitalist, residency, nursing, emergency department, and hospital leadership and included: (1) regionalizing GMS teams as much as possible; (2) change in resident call structure from a traditional 4‐day call cycle to daily admitting; (3) collaborative efforts to enhance GMS patient discharges before noon to promote regionalized placement of patients without prolonging time in the emergency department (ED); (4) daily morning and postround multidisciplinary huddles to prioritize sicker patients and discharges; (5) encouragement of daily rounds at patients' bedsides with presence of physician team, nurse, and team pharmacist if available; (6) creation of unit‐ and team‐level performance reports; and (7) creation of unit‐based physician and nursing co‐leadership (Figure 1).[15]

Concordance of Plan
Concordance of plan was measured via a 7‐question survey previously developed, pilot tested, and used to measure the impact of regionalized care on care team communication between inpatient nursephysician team members.[9] The survey was administered in‐person by 1 of 8 trained research assistants (RAs) (4/emntervention period) to nurse and intern pairs caring for patients on the study units pre‐ and postregionalization. GMS patients were eligible for inclusion if surveys could be administered to their nurse and intern within the first 24 hours of admission to the unit and within 48 hours of admission to the hospital, based on RA availability (thus excluding patients admitted on Fridays as surveys were not conducted over the weekend). Most often, all eligible patients admitted to the study units during time periods of data collection were included in the study. On limited occasions, the daily supply of patients surpassed RA capacity for inclusion, at which time computer‐generated randomization was utilized to randomly select patients for inclusion. Nurse and intern pairs were surveyed once during a patient's hospitalization, although they could be surveyed more than once about different patients, and patients could be included more than once if rehospitalized on the study unit and cared for by a different nurseintern pair. Of the 472 selected eligible patients, the nurses and interns of 418 patients were available and consented to survey administration, representing 361 unique nurse and intern pairs and 399 unique patients.
Each member of the pair was asked about 7 specific aspects of the patient's care plan for that day in isolation from the other team member, including: (1) the patient's primary diagnosis, (2) the patient's expressed chief concern, (3) the day's scheduled tests, (4) the day's scheduled procedures, (5) consulting services involved, (6) medication changes made that day, and (7) the patient's expected discharge date. In addition, each pair was asked the name of the other team member (ie, the nurse was asked the name of the intern and vice versa), and whether or not the patient care plan for the day had been discussed with the other team member, where concordance was defined as both members agreeing the plan had been discussed. All responses were recorded verbatim. Pairs were surveyed independently between 12 pm and 2 pm, limiting confounding by evolving plans of care over time.
Each set of surveys were then reviewed by 2 of 4 trained adjudicators, and responses to each question were scored as complete, partial, or no agreement. Rules for degree of agreement were based upon previously utilized parameters[9] as well as biweekly meetings during which common themes and disagreements in ratings were discussed, and rules generated to create consensus (see Supporting Information, Appendix, in the online version of this article).
Adverse Event Detection
Of the patients meeting eligibility criteria, 200 patients were randomly selected using computer‐generated randomization from each time period for AE outcome assessment, for a total of 400 patients.
Each patient's electronic medical record was retrospectively reviewed by a trained clinician using a previously validated screening tool to detect any possible AEs.[11] Any positive screen prompted documentation of a narrative summary including a short description of the possible AE and pertinent associated data. We defined AE as any injury due to medical management rather than the natural history of the illness, and further limited this definition to only include AEs that occurred on the study unit or as a result of care on that unit.
Two of 4 trained adjudicators, blinded to time period, then separately reviewed each narrative summary using previously validated 6‐point confidence scales to determine the presence and preventability of AE, with confidence ratings of 4 or greater used as cutoffs.[11] All AEs were also scored on a 4‐point severity scale (trivial, clinically significant, serious, or life threatening), with severe AE defined as serious or life threatening. Lastly, adjudicators grouped AEs into 1 of 10 prespecified categories.[11] Any disagreements in ratings or groupings were discussed by all 4 adjudicators to reach consensus.
Data Analysis
Patient characteristics are presented using descriptive statistics and were compared in the pre‐ and postregionalization time periods using 2 or t tests as appropriate.
To analyze whether regionalized care was associated with concordance of plan, adjudicated survey questions were assigned points of 1, 0.5, and 0 for complete, partial, and no agreement, respectively. Total mean concordance scores for any patient ranged from 0 to 7 points, and were divided by total number of answered questions (up to 7) for a range of 0 to 1. Total mean concordance scores as well as mean concordance score per survey question were compared pre‐ versus postregionalization using t tests. In sensitivity analyses, adjudicated survey responses were dichotomized with complete and partial agreement deemed concordant responses. Percent concordance for each question was then compared pre‐ versus postregionalization using 2 analysis. Questions about the name of the other team member and discussion of daily care plan with the other team member were excluded from total concordance score calculations and were compared individually pre‐ versus postregionalization, because they are not directly about the plan of care.
To analyze the association of regionalization with odds of preventable AE, we performed multivariable logistic regression adjusted for patient age, sex, race, language, and Elixhauser comorbidity score,[16] and utilized generalized estimating equations to account for clustering by hospital unit. Secondary outcomes included severe preventable AEs, nonpreventable AEs, and category of preventable AEs using similar methodology. Two‐sided P values <0.05 were considered significant, and SAS version 9.2 (SAS Institute Inc., Cary, NC) was used for all analyses.
RESULTS
The fidelity of the intervention in achieving its goal of regionalized care is discussed separately.[15] Briefly, the intervention was successful at achieving 85% regionalization by team (ie, average daily percentage of team's patients assigned to team's unit) and 87% regionalization by unit (ie, average daily percentage of unit's patients with assigned team) following implementation, compared to 20% regionalization by team and unit in the preintervention period. Importantly, the average daily census of physician care teams rose by 32%, from a mean of 10.8 patients/physician care team preregionalization to a mean of 14.3 patients/physician care team postregionalization.
Concordance of Plan
Of the 418 nurse and intern paired surveys, 4 surveys were excluded due to repeat surveys of the same patient during the same hospitalization, for a total of 197 distinct paired surveys preregionalization and 217 paired surveys postregionalization. There were no statistically significant differences in patients' age, sex, race, language, admission source, length of stay, Elixhauser comorbidity score and diagnosis‐related group weight pre‐ versus postregionalization (Table 1).
Characteristic | Concordance of Care Plan | Adverse Events | ||||
---|---|---|---|---|---|---|
Pre, n = 197 | Post, n = 217 | P Value | Pre, n = 198 | Post, n = 194 | P Value | |
| ||||||
Age, mean (SD) | 60.5 (19.4) | 57.6 (20.8) | 0.15 | 60.4 (18.9) | 58.0 (21.2) | 0.24 |
Male, n (%) | 77 (39.1) | 92 (42.4) | 0.49 | 94 (47.5) | 85 (43.8) | 0.55 |
Race/ethnicity, n (%) | 0.34 | 0.12 | ||||
White | 134 (68.0) | 141 (65.0) | 132 (66.5) | 121 (62.4) | ||
Black | 42 (21.3) | 45 (20.7) | 41 (20.8) | 54 (27.8) | ||
Hispanic | 18 (9.1) | 21 (9.7) | 22 (11.3) | 13 (6.8) | ||
Other/unknown | 3 (1.5) | 10 (4.6) | 3 (1.4) | 6 (2.9) | ||
Language, n (%) | 0.30 | 0.73 | ||||
English | 183 (92.9) | 203 (93.5) | 176 (88.7) | 175 (90.2) | ||
Spanish | 6 (3.0) | 10 (4.6) | 10 (5.2) | 10 (5.3) | ||
Other | 8 (4.1) | 4 (1.8) | 12 (6.1) | 9 (4.5) | ||
Admitting source, n (%) | 1.00 | 0.10 | ||||
Physician office | 13 (6.6) | 13 (6.0) | 13 (6.6) | 6 (3.1) | ||
Emergency department | 136 (69.0) | 150 (69.1) | 126 (63.6) | 127 (65.5) | ||
Transfer from different hospital | 40 (20.3) | 45 (20.7) | 54 (27.3) | 50 (25.8) | ||
Transfer from skilled nursing facility | 8 (4.1) | 9 (4.2) | 5 (2.5) | 11 (5.6) | ||
Length of stay, d, median (IQR) | 3.0 (4.0) | 3.0 (4.0) | 0.57 | 4.0 (5.0) | 3.0 (4.0) | 0.16 |
Elixhauser Comorbidity Score, mean (SD) | 8.0 (8.8) | 8.3 (9.3) | 0.74 | 8.0 (8.6) | 7.8 (8.4) | 0.86 |
DRG weight, mean (SD) | 1.6 (1.0) | 1.5 (1.0) | 0.37 | 1.5 (0.93) | 1.5 (1.1) | 0.96 |
Kappa scores for adjudications of concordance surveys (defined as both adjudicators scoring the same level of agreement (ie, both complete or partial agreement versus no agreement) ranged from 0.69 to 0.95, by question. There were no significant differences in total mean concordance scores in the care plan pre‐ versus postregionalization (0.65 vs 0.67, P = 0.26) (Table 2). Similarly, there were no significant differences in mean concordance score for each survey question, except agreement on expected date of discharge (0.56 vs 0.68, P = 0.003), knowledge of the other provider's name, and agreement that discussion of the daily plan had taken place with the other pair member. Similar results were seen when results were dichotomized (ie, partial or complete agreement vs no agreement) (Table 2).
Concordance Outcome | Pre, n = 197 | Post, n = 217 | P Value |
---|---|---|---|
| |||
Concordance score* | |||
Total concordance score, mean (SD) | 0.65 (0.17) | 0.67 (0.16) | 0.26 |
Subgroups | |||
Diagnosis | 0.77 (0.32) | 0.72 (0.35) | 0.11 |
Patient's chief concern | 0.48 (0.44) | 0.48 (0.43) | 0.94 |
Tests today | 0.67 (0.40) | 0.71 (0.42) | 0.36 |
Procedures today | 0.93 (0.25) | 0.92 (0.25) | 0.71 |
Medication changes today | 0.56 (0.44) | 0.59 (0.43) | 0.54 |
Consulting services | 0.59 (0.44) | 0.60 (0.44) | 0.82 |
Expected discharge date | 0.56 (0.44) | 0.68 (0.38) | 0.003 |
Responding clinician knowledge of nurse's name | 0.56 (0.50) | 0.86 (0.35) | <0.001 |
Nurse's knowledge of responding clinician's name | 0.56 (0.50) | 0.88 (0.33) | <0.001 |
Plan discussed | 0.73 (0.45) | 0.88 (0.32) | <0.001 |
Percent concordance, mean (SD) | |||
Diagnosis | 92.0 (27.3) | 88.6 (31.9) | 0.25 |
Patient's chief concern | 59.6 (49.1) | 60.6 (49.0) | 0.84 |
Tests today | 78.9 (40.9) | 77.2 (42.1) | 0.67 |
Procedures today | 93.5 (24.8) | 94.1 (23.7) | 0.80 |
Medication changes today | 66.3 (33.6) | 69.9 (46.0) | 0.44 |
Consulting services | 69.3 (46.2) | 68.9 (46.4) | 0.93 |
Expected discharge date | 67.5 (47.0) | 82.6 (38.0) | <0.001 |
Responding clinician knowledge of nurse's name | 55.7 (49.8) | 85.6 (35.2) | <0.001 |
Nurse's knowledge of responding clinician's name | 55.9 (49.8) | 87.9 (32.8) | <0.001 |
Plan discussed | 72.9 (44.6) | 88.2 (32.3) | <0.001 |
Adverse Events
Of the 400 patients screened for AEs, 8 were excluded due to missing medical record number (5) and discharge outside of study period (3). Of the final 392 patient screens (198 pre, 194 post), there were no significant differences in patients' age, sex, race, language, length of stay, or Elixhauser score pre‐ versus postregionalization (Table 1).
Kappa scores for adjudicator agreement were 0.35 for presence of AE and 0.34 for preventability of AE. Of the 392 reviewed patient records, there were 133 total AEs detected (66 pre, 67 post), 27 preventable AEs (13 pre, 14 post), and 9 severe preventable AEs (4 pre, 5 post) (Table 3). There was no significant difference in the adjusted odds of preventable AEs post‐ versus preregionalization (adjusted odds ratio: 1.37, 95% confidence interval: 0.69, 2.69). Although the low number of AEs rated as severe or life threatening precluded adjusted analysis, unadjusted results similarly demonstrated no difference in odds of severe preventable AEs pre‐ versus postregionalization. As expected, there was no significant difference in adjusted odds of nonpreventable AE after implementation of regionalized care (Table 3).
Adverse Events | No. of Adverse Events | Adjusted Odds Ratio Post vs Pre (95% CI) | |
---|---|---|---|
Pre, n = 198 | Post, n = 194 | ||
| |||
Preventable | 13 | 14 | 1.37 (0.69, 2.69) |
Serious and preventable | 4 | 5 | |
Nonpreventable | 47 | 50 | 1.20 (0.85, 1.75) |
Similarly, there were no significant differences in category of preventable AE pre‐ versus postregionalization. The most frequent preventable AEs in both time periods were those related to adverse drug events and to manifestations of poor glycemic control, examples of which are illustrated (Table 4).
| |
Adverse drug event | 29‐year‐old male with history of alcohol abuse, complicated by prior withdrawal seizures/emntensive care unit admissions, presented with alcohol withdrawal. Started on standing and PRN lorazepam, kept on home medications including standing clonidine, gabapentin, citalopram, quetiapine. Became somnolent due to polypharmacy, ultimately discontinued quetiapine as discovered took only as needed at home for insomnia |
Manifestations of poor glycemic control | 78‐year‐old male with recently diagnosed lymphoma, distant history of bladder and prostate cancer status post ileal loop diversion, presented status post syncopal event; during event, spilled boiling water on himself leading to second‐degree burns on 3% of his body. Initially admitted to trauma/burn service, ultimately transferred to medical service for ongoing multiple medical issues including obstructive uropathy, acute on chronic renal failure. Adverse event was hyperglycemia (>350 mg/dL on >2 consecutive readings) in the setting of holding his home insulin detemir and insulin aspart (had been placed on insulin aspart sliding scale alone). After hyperglycemic episodes, was placed back on weight‐based basal/nutritional insulin |
DISCUSSION
In this study of general medicine patients at a large academic medical center, we found that regionalization of care teams on general medicine services was associated with improved recognition of care team members and agreement on estimated date of patient discharge, but was not associated with improvement in overall nurse and physician concordance of the patient care plan, or the odds of preventable AEs.
This intervention importantly addresses the barrier of dispersion of team membership, a well‐recognized barrier to interdisciplinary collaboration,[17, 18] particularly with resident physician teams due to frequently changing team membership. Localization of all team members, in addition to encouragement of daily collaborative bedside rounds as part of the regionalization initiative, likely contributed to our observed improvement in team member identification and discussion of daily care plans. Similarly, regionalization resulted in improved agreement in estimations of date of patient discharge. Focus on early patient discharges was an integral part of the implementation efforts; we therefore hypothesize that mutual focus on discharge planning by both nurses and responding clinicians may have explained this observed result.
On the other hand, regionalization did not appreciably improve the overall concordance of care plan between nurses and interns, despite a significant increase in team members agreeing that the plan had been discussed. Our findings support similar prior research demonstrating that regionalizing hospitalist attendings to single nursing units had limited impact on agreement of care plan between physicians and nurses.[13] Similarly, in settings where physicians and nurses are inherently regionalized, such as the intensive care unit[4] or the operating room,[3] communication between physicians and nurses remains difficult. Collectively, our findings suggest that colocalization of physicians and nurses alone is likely insufficient to improve measured communication between care team members. Existing literature suggests that more standardized approaches to improve communication, such as structured communication tools used during daily inpatient care[19, 20] or formalized team training,[21, 22, 23] lead to improvements in communication and collaboration. Despite these findings, it is important to highlight that this study did not assess other measures of workplace culture, such as teamwork and care team cohesiveness, which may have been positively affected by this intervention, even without measurable effect on concordance of care plan. Additionally, as noted, the average daily census on each team increased by almost a third postintervention, which may have impeded improvements in care team communication.
In addition, we found that our intervention had no significant impact on preventable AEs or severe preventable AEs. Although we cannot exclude the possibility that more subtle AEs were missed with our methodology, our results indicate that regionalized care alone may be inadequate to improve major patient safety outcomes. As discussed, the volume of patients did increase postintervention; thus, another way to state our results is that we were able to increase the daily volume of patients without any significant decreases in patient safety. Nevertheless, the results on patient safety were less than desired. A recent review of interdisciplinary team care interventions on general medical wards similarly demonstrated underwhelming improvements in patient safety outcomes, although the reviewed interventions did not specifically address preventable AEs, a gap in the literature commented on by the authors.[24] Other albeit limited literature has demonstrated improvement in patient safety outcomes via multifaceted efforts aimed at improving care team member communication. Notably, these efforts include colocalization of care team members to single units but also involve additional measures to improve communication and collaboration between care team members, such as structured communication during interdisciplinary rounds, and certification of key interdisciplinary teamwork skills.[11, 14] Although our regionalized care intervention included many similar features to these accountable care units (ACUs) including unit‐based care teams, unit‐level performance reporting, and unit‐based physician and nursing coleadership, significant differences existed. Notably, in addition to the above features, the ACU model also incorporated highly structured communication models for interdisciplinary rounding, and certification processes to ensure an appropriate communication skill base among care team members.[14] Thus, although creation of regionalized care teams is likely a necessary precursor to implementation of these additional measures, alone it may be insufficient to improve patient safety outcomes.
Importantly, in our study we identified that adverse drug events and manifestations of poor glycemic control occurred in high frequency both before and following implementation of regionalized care, supporting other literature that describes the prevalence of these AEs.[11, 25, 26, 27] These results suggest that targeted interventions to address these specific AEs are likely necessary. Notably, the intervention units in our study did not consistently employ clinical pharmacists assigned specifically to that unit's care team to allow for integration within the care team. As prior research has suggested that greater collaboration with clinical pharmacists results in reduction of adverse drug events,[28] next steps may include improved integration of team‐based pharmacists into the activities of the regionalized care teams. Inpatient management of diabetes also requires specific interventions,[29, 30, 31] only some of which may be addressable by having regionalized care and better interdisciplinary communication.
Our findings are subject to several limitations. First, this was a single‐site study and thus our findings may not be generalizable to other institutions. However, regionalized care is increasingly encouraged to optimize communication between care team members.[17, 18] Therefore, our null findings may be pertinent to other institutions looking to improve patient safety outcomes, demonstrating that additional initiatives will likely be required. Second, our modes of outcome measurement possess limitations. In measuring concordance of care plan, although previously used survey techniques were employed,[9] the concordance survey has not been formally validated, and we believe some of the questions may have led to ambiguity on the part of the responders that may have resulted in less accurate responses, thus biasing toward the null. Similarly, in measuring AEs, the screening tool relied on retrospective chart review looking for specific AE types[11] and thus may not have captured more subtle AEs. Additionally, our study may have been underpowered to demonstrate significant reduction in preventable AEs, although other studies of similar methodology demonstrated significant results with similar sample size.[11] This was due in part to our lower‐than‐expected baseline AE rate (6.6% compared with approximately 10.3% in previous studies).[11] Lastly, our study solely examined the association of regionalization with concordance of care plan and preventable AEs, but importantly excluded other clinically important outcomes that may have been positively (or negatively) impacted by these regionalization efforts, such as ED wait times, provider efficiency (eg, fewer pages, less time in transit, more time at the bedside), interdisciplinary teamwork, or patient or provider satisfaction.
CONCLUSION
In summary, our findings suggest that regionalized care teams alone may be insufficient to effectively promote communication between care team members regarding the care plan or to lead to improvements in patient safety, although we recognize that there may have been benefits (or unintended harms) not measured in this study but are nonetheless important for clinical care and workplace culture. This is an important lesson, as many hospitals move toward regionalized care in an effort to improve patient safety outcomes. However, strengthening the infrastructure by colocalizing care team members to maximize opportunity for communication is likely a necessary first step toward facilitating implementation of additional initiatives that may lead to more robust patient safety improvements, such as structured interdisciplinary bedside rounds (eg, facilitating and training all team members to fulfill specific roles), teamwork training, and certification of key interdisciplinary teamwork skills. Additionally, close examination of identified prevalent and preventable AEs can help to determine which additional initiatives are most likely to have greatest impact in improving patient safety.
Disclosures: This research was supported by funds provided by Brigham and Women's Hospital (BWH) and by funds provided by the Department of Medicine at BWH. All authors had full access to all of the data in the study and were integrally involved in the design, implementation, data collection, and analyses. The first author, Dr. Stephanie Mueller, takes responsibility for the integrity for the data and the accuracy of the data analysis. Dr. Schnipper reports grants from Sanofi Aventis, outside the submitted work.
Failures in communication among healthcare professionals are known threats to patient safety. These failures account for over 60% of root causes of sentinel events, the most serious events reported to The Joint Commission.[1] As such, identifying both patterns of effective communication as well as barriers to successful communication has been a focus of efforts aimed at improving patient safety. However, to date, the majority of this work has centered on improving communication in settings such as the operating room and intensive care unit,[2, 3, 4] or at times of care transitions.[5, 6, 7, 8]
Unique barriers exist for effective interdisciplinary communication in the hospital setting, particularly physiciannurse communication regarding shared hospitalized patients.[9] Traditionally, care of hospitalized patients is provided by physicians, nurses, and other team members working in varied workflow patterns, leading to dispersed team membership, where each team member cares for different groups of patients in different locations across the hospital. This dispersion is further heightened on teaching services, where residents' rotation schedules lead to frequent changes of care team membership, leaving inpatient care teams particularly vulnerable to ineffective communication. Evidence suggests that communication between nurses and physicians is currently suboptimal, leading to frequent disagreement regarding the patient's plan of care.[9, 10] This divergence between physician and nursing perceptions of patients' care plans may leave patients at greater risk of adverse events (AEs).
Several studies have examined the effects of regionalized inpatient care teams, where multidisciplinary team members care for the same patients on the same hospital unit, on communication and patient outcomes.[4, 11, 12, 13, 14] Results of these studies have been inconsistent, perhaps due to the particular characteristics of the care teams or to the study methodology. Thus, further rigorously done studies are required to better understand the impact of team regionalization on patient care. The goal of this study was to examine whether the implementation of regionalized inpatient care teams was associated with improvements in care team communication and preventable AEs.
METHODS
Setting, Patients, and Study Design
We performed a cohort analysis of patients at a 700‐bed tertiary care center, pre‐ and postregionalization of inpatient general medicine care teams. Our study protocol was approved by the Partners Healthcare Human Subjects Review Committee. Patients were eligible for inclusion if they were 18 years of age or older and discharged from the general medicine service (GMS) from any of the 3 participating nursing units between April 1, 2012 and June 19, 2012 (preregionalization) or April 1, 2013 and June 19, 2013 (postregionalization).
Intervention
On June 20, 2012, regionalized care was implemented on the GMS such that each of 3 GMS teams was localized to 1 of 3, 15‐bed nursing units. Prior to regionalization, the GMS physician care teams, each consisting of 1 hospitalist attending, 1 medical resident, and 2 medical interns, would care for patients on an average of 7 and up to 13 different nursing units on a given day.
Regionalized care consisted of a multifaceted intervention codeveloped by hospitalist, residency, nursing, emergency department, and hospital leadership and included: (1) regionalizing GMS teams as much as possible; (2) change in resident call structure from a traditional 4‐day call cycle to daily admitting; (3) collaborative efforts to enhance GMS patient discharges before noon to promote regionalized placement of patients without prolonging time in the emergency department (ED); (4) daily morning and postround multidisciplinary huddles to prioritize sicker patients and discharges; (5) encouragement of daily rounds at patients' bedsides with presence of physician team, nurse, and team pharmacist if available; (6) creation of unit‐ and team‐level performance reports; and (7) creation of unit‐based physician and nursing co‐leadership (Figure 1).[15]

Concordance of Plan
Concordance of plan was measured via a 7‐question survey previously developed, pilot tested, and used to measure the impact of regionalized care on care team communication between inpatient nursephysician team members.[9] The survey was administered in‐person by 1 of 8 trained research assistants (RAs) (4/emntervention period) to nurse and intern pairs caring for patients on the study units pre‐ and postregionalization. GMS patients were eligible for inclusion if surveys could be administered to their nurse and intern within the first 24 hours of admission to the unit and within 48 hours of admission to the hospital, based on RA availability (thus excluding patients admitted on Fridays as surveys were not conducted over the weekend). Most often, all eligible patients admitted to the study units during time periods of data collection were included in the study. On limited occasions, the daily supply of patients surpassed RA capacity for inclusion, at which time computer‐generated randomization was utilized to randomly select patients for inclusion. Nurse and intern pairs were surveyed once during a patient's hospitalization, although they could be surveyed more than once about different patients, and patients could be included more than once if rehospitalized on the study unit and cared for by a different nurseintern pair. Of the 472 selected eligible patients, the nurses and interns of 418 patients were available and consented to survey administration, representing 361 unique nurse and intern pairs and 399 unique patients.
Each member of the pair was asked about 7 specific aspects of the patient's care plan for that day in isolation from the other team member, including: (1) the patient's primary diagnosis, (2) the patient's expressed chief concern, (3) the day's scheduled tests, (4) the day's scheduled procedures, (5) consulting services involved, (6) medication changes made that day, and (7) the patient's expected discharge date. In addition, each pair was asked the name of the other team member (ie, the nurse was asked the name of the intern and vice versa), and whether or not the patient care plan for the day had been discussed with the other team member, where concordance was defined as both members agreeing the plan had been discussed. All responses were recorded verbatim. Pairs were surveyed independently between 12 pm and 2 pm, limiting confounding by evolving plans of care over time.
Each set of surveys were then reviewed by 2 of 4 trained adjudicators, and responses to each question were scored as complete, partial, or no agreement. Rules for degree of agreement were based upon previously utilized parameters[9] as well as biweekly meetings during which common themes and disagreements in ratings were discussed, and rules generated to create consensus (see Supporting Information, Appendix, in the online version of this article).
Adverse Event Detection
Of the patients meeting eligibility criteria, 200 patients were randomly selected using computer‐generated randomization from each time period for AE outcome assessment, for a total of 400 patients.
Each patient's electronic medical record was retrospectively reviewed by a trained clinician using a previously validated screening tool to detect any possible AEs.[11] Any positive screen prompted documentation of a narrative summary including a short description of the possible AE and pertinent associated data. We defined AE as any injury due to medical management rather than the natural history of the illness, and further limited this definition to only include AEs that occurred on the study unit or as a result of care on that unit.
Two of 4 trained adjudicators, blinded to time period, then separately reviewed each narrative summary using previously validated 6‐point confidence scales to determine the presence and preventability of AE, with confidence ratings of 4 or greater used as cutoffs.[11] All AEs were also scored on a 4‐point severity scale (trivial, clinically significant, serious, or life threatening), with severe AE defined as serious or life threatening. Lastly, adjudicators grouped AEs into 1 of 10 prespecified categories.[11] Any disagreements in ratings or groupings were discussed by all 4 adjudicators to reach consensus.
Data Analysis
Patient characteristics are presented using descriptive statistics and were compared in the pre‐ and postregionalization time periods using 2 or t tests as appropriate.
To analyze whether regionalized care was associated with concordance of plan, adjudicated survey questions were assigned points of 1, 0.5, and 0 for complete, partial, and no agreement, respectively. Total mean concordance scores for any patient ranged from 0 to 7 points, and were divided by total number of answered questions (up to 7) for a range of 0 to 1. Total mean concordance scores as well as mean concordance score per survey question were compared pre‐ versus postregionalization using t tests. In sensitivity analyses, adjudicated survey responses were dichotomized with complete and partial agreement deemed concordant responses. Percent concordance for each question was then compared pre‐ versus postregionalization using 2 analysis. Questions about the name of the other team member and discussion of daily care plan with the other team member were excluded from total concordance score calculations and were compared individually pre‐ versus postregionalization, because they are not directly about the plan of care.
To analyze the association of regionalization with odds of preventable AE, we performed multivariable logistic regression adjusted for patient age, sex, race, language, and Elixhauser comorbidity score,[16] and utilized generalized estimating equations to account for clustering by hospital unit. Secondary outcomes included severe preventable AEs, nonpreventable AEs, and category of preventable AEs using similar methodology. Two‐sided P values <0.05 were considered significant, and SAS version 9.2 (SAS Institute Inc., Cary, NC) was used for all analyses.
RESULTS
The fidelity of the intervention in achieving its goal of regionalized care is discussed separately.[15] Briefly, the intervention was successful at achieving 85% regionalization by team (ie, average daily percentage of team's patients assigned to team's unit) and 87% regionalization by unit (ie, average daily percentage of unit's patients with assigned team) following implementation, compared to 20% regionalization by team and unit in the preintervention period. Importantly, the average daily census of physician care teams rose by 32%, from a mean of 10.8 patients/physician care team preregionalization to a mean of 14.3 patients/physician care team postregionalization.
Concordance of Plan
Of the 418 nurse and intern paired surveys, 4 surveys were excluded due to repeat surveys of the same patient during the same hospitalization, for a total of 197 distinct paired surveys preregionalization and 217 paired surveys postregionalization. There were no statistically significant differences in patients' age, sex, race, language, admission source, length of stay, Elixhauser comorbidity score and diagnosis‐related group weight pre‐ versus postregionalization (Table 1).
Characteristic | Concordance of Care Plan | Adverse Events | ||||
---|---|---|---|---|---|---|
Pre, n = 197 | Post, n = 217 | P Value | Pre, n = 198 | Post, n = 194 | P Value | |
| ||||||
Age, mean (SD) | 60.5 (19.4) | 57.6 (20.8) | 0.15 | 60.4 (18.9) | 58.0 (21.2) | 0.24 |
Male, n (%) | 77 (39.1) | 92 (42.4) | 0.49 | 94 (47.5) | 85 (43.8) | 0.55 |
Race/ethnicity, n (%) | 0.34 | 0.12 | ||||
White | 134 (68.0) | 141 (65.0) | 132 (66.5) | 121 (62.4) | ||
Black | 42 (21.3) | 45 (20.7) | 41 (20.8) | 54 (27.8) | ||
Hispanic | 18 (9.1) | 21 (9.7) | 22 (11.3) | 13 (6.8) | ||
Other/unknown | 3 (1.5) | 10 (4.6) | 3 (1.4) | 6 (2.9) | ||
Language, n (%) | 0.30 | 0.73 | ||||
English | 183 (92.9) | 203 (93.5) | 176 (88.7) | 175 (90.2) | ||
Spanish | 6 (3.0) | 10 (4.6) | 10 (5.2) | 10 (5.3) | ||
Other | 8 (4.1) | 4 (1.8) | 12 (6.1) | 9 (4.5) | ||
Admitting source, n (%) | 1.00 | 0.10 | ||||
Physician office | 13 (6.6) | 13 (6.0) | 13 (6.6) | 6 (3.1) | ||
Emergency department | 136 (69.0) | 150 (69.1) | 126 (63.6) | 127 (65.5) | ||
Transfer from different hospital | 40 (20.3) | 45 (20.7) | 54 (27.3) | 50 (25.8) | ||
Transfer from skilled nursing facility | 8 (4.1) | 9 (4.2) | 5 (2.5) | 11 (5.6) | ||
Length of stay, d, median (IQR) | 3.0 (4.0) | 3.0 (4.0) | 0.57 | 4.0 (5.0) | 3.0 (4.0) | 0.16 |
Elixhauser Comorbidity Score, mean (SD) | 8.0 (8.8) | 8.3 (9.3) | 0.74 | 8.0 (8.6) | 7.8 (8.4) | 0.86 |
DRG weight, mean (SD) | 1.6 (1.0) | 1.5 (1.0) | 0.37 | 1.5 (0.93) | 1.5 (1.1) | 0.96 |
Kappa scores for adjudications of concordance surveys (defined as both adjudicators scoring the same level of agreement (ie, both complete or partial agreement versus no agreement) ranged from 0.69 to 0.95, by question. There were no significant differences in total mean concordance scores in the care plan pre‐ versus postregionalization (0.65 vs 0.67, P = 0.26) (Table 2). Similarly, there were no significant differences in mean concordance score for each survey question, except agreement on expected date of discharge (0.56 vs 0.68, P = 0.003), knowledge of the other provider's name, and agreement that discussion of the daily plan had taken place with the other pair member. Similar results were seen when results were dichotomized (ie, partial or complete agreement vs no agreement) (Table 2).
Concordance Outcome | Pre, n = 197 | Post, n = 217 | P Value |
---|---|---|---|
| |||
Concordance score* | |||
Total concordance score, mean (SD) | 0.65 (0.17) | 0.67 (0.16) | 0.26 |
Subgroups | |||
Diagnosis | 0.77 (0.32) | 0.72 (0.35) | 0.11 |
Patient's chief concern | 0.48 (0.44) | 0.48 (0.43) | 0.94 |
Tests today | 0.67 (0.40) | 0.71 (0.42) | 0.36 |
Procedures today | 0.93 (0.25) | 0.92 (0.25) | 0.71 |
Medication changes today | 0.56 (0.44) | 0.59 (0.43) | 0.54 |
Consulting services | 0.59 (0.44) | 0.60 (0.44) | 0.82 |
Expected discharge date | 0.56 (0.44) | 0.68 (0.38) | 0.003 |
Responding clinician knowledge of nurse's name | 0.56 (0.50) | 0.86 (0.35) | <0.001 |
Nurse's knowledge of responding clinician's name | 0.56 (0.50) | 0.88 (0.33) | <0.001 |
Plan discussed | 0.73 (0.45) | 0.88 (0.32) | <0.001 |
Percent concordance, mean (SD) | |||
Diagnosis | 92.0 (27.3) | 88.6 (31.9) | 0.25 |
Patient's chief concern | 59.6 (49.1) | 60.6 (49.0) | 0.84 |
Tests today | 78.9 (40.9) | 77.2 (42.1) | 0.67 |
Procedures today | 93.5 (24.8) | 94.1 (23.7) | 0.80 |
Medication changes today | 66.3 (33.6) | 69.9 (46.0) | 0.44 |
Consulting services | 69.3 (46.2) | 68.9 (46.4) | 0.93 |
Expected discharge date | 67.5 (47.0) | 82.6 (38.0) | <0.001 |
Responding clinician knowledge of nurse's name | 55.7 (49.8) | 85.6 (35.2) | <0.001 |
Nurse's knowledge of responding clinician's name | 55.9 (49.8) | 87.9 (32.8) | <0.001 |
Plan discussed | 72.9 (44.6) | 88.2 (32.3) | <0.001 |
Adverse Events
Of the 400 patients screened for AEs, 8 were excluded due to missing medical record number (5) and discharge outside of study period (3). Of the final 392 patient screens (198 pre, 194 post), there were no significant differences in patients' age, sex, race, language, length of stay, or Elixhauser score pre‐ versus postregionalization (Table 1).
Kappa scores for adjudicator agreement were 0.35 for presence of AE and 0.34 for preventability of AE. Of the 392 reviewed patient records, there were 133 total AEs detected (66 pre, 67 post), 27 preventable AEs (13 pre, 14 post), and 9 severe preventable AEs (4 pre, 5 post) (Table 3). There was no significant difference in the adjusted odds of preventable AEs post‐ versus preregionalization (adjusted odds ratio: 1.37, 95% confidence interval: 0.69, 2.69). Although the low number of AEs rated as severe or life threatening precluded adjusted analysis, unadjusted results similarly demonstrated no difference in odds of severe preventable AEs pre‐ versus postregionalization. As expected, there was no significant difference in adjusted odds of nonpreventable AE after implementation of regionalized care (Table 3).
Adverse Events | No. of Adverse Events | Adjusted Odds Ratio Post vs Pre (95% CI) | |
---|---|---|---|
Pre, n = 198 | Post, n = 194 | ||
| |||
Preventable | 13 | 14 | 1.37 (0.69, 2.69) |
Serious and preventable | 4 | 5 | |
Nonpreventable | 47 | 50 | 1.20 (0.85, 1.75) |
Similarly, there were no significant differences in category of preventable AE pre‐ versus postregionalization. The most frequent preventable AEs in both time periods were those related to adverse drug events and to manifestations of poor glycemic control, examples of which are illustrated (Table 4).
| |
Adverse drug event | 29‐year‐old male with history of alcohol abuse, complicated by prior withdrawal seizures/emntensive care unit admissions, presented with alcohol withdrawal. Started on standing and PRN lorazepam, kept on home medications including standing clonidine, gabapentin, citalopram, quetiapine. Became somnolent due to polypharmacy, ultimately discontinued quetiapine as discovered took only as needed at home for insomnia |
Manifestations of poor glycemic control | 78‐year‐old male with recently diagnosed lymphoma, distant history of bladder and prostate cancer status post ileal loop diversion, presented status post syncopal event; during event, spilled boiling water on himself leading to second‐degree burns on 3% of his body. Initially admitted to trauma/burn service, ultimately transferred to medical service for ongoing multiple medical issues including obstructive uropathy, acute on chronic renal failure. Adverse event was hyperglycemia (>350 mg/dL on >2 consecutive readings) in the setting of holding his home insulin detemir and insulin aspart (had been placed on insulin aspart sliding scale alone). After hyperglycemic episodes, was placed back on weight‐based basal/nutritional insulin |
DISCUSSION
In this study of general medicine patients at a large academic medical center, we found that regionalization of care teams on general medicine services was associated with improved recognition of care team members and agreement on estimated date of patient discharge, but was not associated with improvement in overall nurse and physician concordance of the patient care plan, or the odds of preventable AEs.
This intervention importantly addresses the barrier of dispersion of team membership, a well‐recognized barrier to interdisciplinary collaboration,[17, 18] particularly with resident physician teams due to frequently changing team membership. Localization of all team members, in addition to encouragement of daily collaborative bedside rounds as part of the regionalization initiative, likely contributed to our observed improvement in team member identification and discussion of daily care plans. Similarly, regionalization resulted in improved agreement in estimations of date of patient discharge. Focus on early patient discharges was an integral part of the implementation efforts; we therefore hypothesize that mutual focus on discharge planning by both nurses and responding clinicians may have explained this observed result.
On the other hand, regionalization did not appreciably improve the overall concordance of care plan between nurses and interns, despite a significant increase in team members agreeing that the plan had been discussed. Our findings support similar prior research demonstrating that regionalizing hospitalist attendings to single nursing units had limited impact on agreement of care plan between physicians and nurses.[13] Similarly, in settings where physicians and nurses are inherently regionalized, such as the intensive care unit[4] or the operating room,[3] communication between physicians and nurses remains difficult. Collectively, our findings suggest that colocalization of physicians and nurses alone is likely insufficient to improve measured communication between care team members. Existing literature suggests that more standardized approaches to improve communication, such as structured communication tools used during daily inpatient care[19, 20] or formalized team training,[21, 22, 23] lead to improvements in communication and collaboration. Despite these findings, it is important to highlight that this study did not assess other measures of workplace culture, such as teamwork and care team cohesiveness, which may have been positively affected by this intervention, even without measurable effect on concordance of care plan. Additionally, as noted, the average daily census on each team increased by almost a third postintervention, which may have impeded improvements in care team communication.
In addition, we found that our intervention had no significant impact on preventable AEs or severe preventable AEs. Although we cannot exclude the possibility that more subtle AEs were missed with our methodology, our results indicate that regionalized care alone may be inadequate to improve major patient safety outcomes. As discussed, the volume of patients did increase postintervention; thus, another way to state our results is that we were able to increase the daily volume of patients without any significant decreases in patient safety. Nevertheless, the results on patient safety were less than desired. A recent review of interdisciplinary team care interventions on general medical wards similarly demonstrated underwhelming improvements in patient safety outcomes, although the reviewed interventions did not specifically address preventable AEs, a gap in the literature commented on by the authors.[24] Other albeit limited literature has demonstrated improvement in patient safety outcomes via multifaceted efforts aimed at improving care team member communication. Notably, these efforts include colocalization of care team members to single units but also involve additional measures to improve communication and collaboration between care team members, such as structured communication during interdisciplinary rounds, and certification of key interdisciplinary teamwork skills.[11, 14] Although our regionalized care intervention included many similar features to these accountable care units (ACUs) including unit‐based care teams, unit‐level performance reporting, and unit‐based physician and nursing coleadership, significant differences existed. Notably, in addition to the above features, the ACU model also incorporated highly structured communication models for interdisciplinary rounding, and certification processes to ensure an appropriate communication skill base among care team members.[14] Thus, although creation of regionalized care teams is likely a necessary precursor to implementation of these additional measures, alone it may be insufficient to improve patient safety outcomes.
Importantly, in our study we identified that adverse drug events and manifestations of poor glycemic control occurred in high frequency both before and following implementation of regionalized care, supporting other literature that describes the prevalence of these AEs.[11, 25, 26, 27] These results suggest that targeted interventions to address these specific AEs are likely necessary. Notably, the intervention units in our study did not consistently employ clinical pharmacists assigned specifically to that unit's care team to allow for integration within the care team. As prior research has suggested that greater collaboration with clinical pharmacists results in reduction of adverse drug events,[28] next steps may include improved integration of team‐based pharmacists into the activities of the regionalized care teams. Inpatient management of diabetes also requires specific interventions,[29, 30, 31] only some of which may be addressable by having regionalized care and better interdisciplinary communication.
Our findings are subject to several limitations. First, this was a single‐site study and thus our findings may not be generalizable to other institutions. However, regionalized care is increasingly encouraged to optimize communication between care team members.[17, 18] Therefore, our null findings may be pertinent to other institutions looking to improve patient safety outcomes, demonstrating that additional initiatives will likely be required. Second, our modes of outcome measurement possess limitations. In measuring concordance of care plan, although previously used survey techniques were employed,[9] the concordance survey has not been formally validated, and we believe some of the questions may have led to ambiguity on the part of the responders that may have resulted in less accurate responses, thus biasing toward the null. Similarly, in measuring AEs, the screening tool relied on retrospective chart review looking for specific AE types[11] and thus may not have captured more subtle AEs. Additionally, our study may have been underpowered to demonstrate significant reduction in preventable AEs, although other studies of similar methodology demonstrated significant results with similar sample size.[11] This was due in part to our lower‐than‐expected baseline AE rate (6.6% compared with approximately 10.3% in previous studies).[11] Lastly, our study solely examined the association of regionalization with concordance of care plan and preventable AEs, but importantly excluded other clinically important outcomes that may have been positively (or negatively) impacted by these regionalization efforts, such as ED wait times, provider efficiency (eg, fewer pages, less time in transit, more time at the bedside), interdisciplinary teamwork, or patient or provider satisfaction.
CONCLUSION
In summary, our findings suggest that regionalized care teams alone may be insufficient to effectively promote communication between care team members regarding the care plan or to lead to improvements in patient safety, although we recognize that there may have been benefits (or unintended harms) not measured in this study but are nonetheless important for clinical care and workplace culture. This is an important lesson, as many hospitals move toward regionalized care in an effort to improve patient safety outcomes. However, strengthening the infrastructure by colocalizing care team members to maximize opportunity for communication is likely a necessary first step toward facilitating implementation of additional initiatives that may lead to more robust patient safety improvements, such as structured interdisciplinary bedside rounds (eg, facilitating and training all team members to fulfill specific roles), teamwork training, and certification of key interdisciplinary teamwork skills. Additionally, close examination of identified prevalent and preventable AEs can help to determine which additional initiatives are most likely to have greatest impact in improving patient safety.
Disclosures: This research was supported by funds provided by Brigham and Women's Hospital (BWH) and by funds provided by the Department of Medicine at BWH. All authors had full access to all of the data in the study and were integrally involved in the design, implementation, data collection, and analyses. The first author, Dr. Stephanie Mueller, takes responsibility for the integrity for the data and the accuracy of the data analysis. Dr. Schnipper reports grants from Sanofi Aventis, outside the submitted work.
- Joint Commission on Accreditation of Healthcare Organizations. Understanding and Preventing Sentinel Events in Your Health Care Organization. Oak Brook, IL: Joint Commission; 2008.
- Communication failures in the operating room: an observational classification of recurrent types and effects. Qual Saf Health Care. 2004;13(5):330–334. , , , et al.
- Operating room teamwork among physicians and nurses: teamwork in the eye of the beholder. J Am Coll Surg. 2006;202(5):746–752. , , , et al.
- Discrepant attitudes about teamwork among critical care nurses and physicians. Crit Care Med. 2003;31(3):956–959. , , .
- Communication failures in patient sign‐out and suggestions for improvement: a critical incident analysis. Qual Saf Health Care. 2005;14(6):401–407. , , , , .
- Changes in medical errors after implementation of a handoff program. N Engl J Med. 2014;371(19):1803–1812. , , , et al.
- Communication and information deficits in patients discharged to rehabilitation facilities: an evaluation of five acute care hospitals. J Hosp Med. 2009;4(8):E28–E33. , , , et al.
- Deficits in communication and information transfer between hospital‐based and primary care physicians: implications for patient safety and continuity of care. JAMA. 2007;297(8):831–841. , , , , , .
- Patterns of nurse‐physician communication and agreement on the plan of care. Qual Saf Health Care. 2010;19(3):195–199. , , , et al.
- Can we talk? Priorities for patient care differed among health care providers. In: Henriksen K, Battles JB, Marks ES, Lewin DI, eds. Advances in Patient Safety: From Research to Implementation. Vol 1. Rockville, MD: Agency for Healthcare Research and Quality; 2005. , , , , , .
- Structured interdisciplinary rounds in a medical teaching unit: improving patient safety. Arch Intern Med. 2011;171(7):678–684. , , , et al.
- Improving teamwork: impact of structured interdisciplinary rounds on a hospitalist unit. J Hosp Med. 2011;6(2):88–93. , , , , , .
- Impact of localizing physicians to hospital units on nurse‐physician communication and agreement on the plan of care. J Gen Intern Med. 2009;24(11):1223–1227. , , , et al.
- Reorganizing a hospital ward as an accountable care unit. J Hosp Med. 2015;10(1):36–40. , , , et al.
- 5th time's a charm: creation of unit‐based care teams in a high occupancy hospital [abstract]. J Hosp Med. 2015;10 (suppl. 2). Available at: http://www.shmabstracts.com/abstract/5th‐times‐a‐charm‐creation‐of‐unit‐based‐care‐teams‐in‐a‐high‐occupancy‐hospital. Accessed July 28, 2015. , , , et al.
- Comorbidity measures for use with administrative data. Med Care. 1998;36(1):8–27. , , , .
- Teamwork on inpatient medical units: assessing attitudes and barriers. Qual Saf Health Care. 2010;19(2):117–121. , , , , , .
- A model for quality improvement programs in academic departments of medicine. Am J Med. 2008;121(10):922–929. , , , et al.
- Improving nurse‐physician communication and satisfaction in the intensive care unit with a daily goals worksheet. Am J Crit Care. 2006;15(2):217–222. , , , , .
- Improving communication in the ICU using daily goals. J Crit Care. 2003;18(2):71–75. , , , , , .
- Effect of crew resource management training in a multidisciplinary obstetrical setting. Int J Qual Health Care. 2008;20(4):254–263. , , , et al.
- Error reduction and performance improvement in the emergency department through formal teamwork training: evaluation results of the MedTeams project. Health Serv Res. 2002;37(6):1553–1581. , , , et al.
- Effects of teamwork training on adverse outcomes and process of care in labor and delivery: a randomized controlled trial. Obstet Gynecol. 2007;109(1):48–55. , , , et al.
- Effects of interdisciplinary team care interventions on general medical wards: a systematic review. JAMA Intern Med. 2015;175(8):1288–1298. , , , et al.
- Patient risk factors for adverse drug events in hospitalized patients. ADE Prevention Study Group. Arch Intern Med. 1999;159(21):2553–2560. , , , et al.
- Effect of a pharmacist intervention on clinically important medication errors after hospital discharge: a randomized trial. Ann Intern Med. 2012;157(1):1–10. , , , et al.
- Use of a standardized protocol to decrease medication errors and adverse events related to sliding scale insulin. Qual Saf Health Care. 2006;15(2):89–91. , , , .
- Clinical pharmacists and inpatient medical care: a systematic review. Arch Intern Med. 2006;166(9):955–964. , , , .
- Improved inpatient use of basal insulin, reduced hypoglycemia, and improved glycemic control: effect of structured subcutaneous insulin orders and an insulin management algorithm. J Hosp Med. 2009;4(1):3–15. , , , , .
- Effects of a computerized order set on the inpatient management of hyperglycemia: a cluster‐randomized controlled trial. Endocr Pract. 2010;16(2):209–218. , , , .
- Effects of a subcutaneous insulin protocol, clinical education, and computerized order set on the quality of inpatient management of hyperglycemia: results of a clinical trial. J Hosp Med. 2009;4(1):16–27. , , , .
- Joint Commission on Accreditation of Healthcare Organizations. Understanding and Preventing Sentinel Events in Your Health Care Organization. Oak Brook, IL: Joint Commission; 2008.
- Communication failures in the operating room: an observational classification of recurrent types and effects. Qual Saf Health Care. 2004;13(5):330–334. , , , et al.
- Operating room teamwork among physicians and nurses: teamwork in the eye of the beholder. J Am Coll Surg. 2006;202(5):746–752. , , , et al.
- Discrepant attitudes about teamwork among critical care nurses and physicians. Crit Care Med. 2003;31(3):956–959. , , .
- Communication failures in patient sign‐out and suggestions for improvement: a critical incident analysis. Qual Saf Health Care. 2005;14(6):401–407. , , , , .
- Changes in medical errors after implementation of a handoff program. N Engl J Med. 2014;371(19):1803–1812. , , , et al.
- Communication and information deficits in patients discharged to rehabilitation facilities: an evaluation of five acute care hospitals. J Hosp Med. 2009;4(8):E28–E33. , , , et al.
- Deficits in communication and information transfer between hospital‐based and primary care physicians: implications for patient safety and continuity of care. JAMA. 2007;297(8):831–841. , , , , , .
- Patterns of nurse‐physician communication and agreement on the plan of care. Qual Saf Health Care. 2010;19(3):195–199. , , , et al.
- Can we talk? Priorities for patient care differed among health care providers. In: Henriksen K, Battles JB, Marks ES, Lewin DI, eds. Advances in Patient Safety: From Research to Implementation. Vol 1. Rockville, MD: Agency for Healthcare Research and Quality; 2005. , , , , , .
- Structured interdisciplinary rounds in a medical teaching unit: improving patient safety. Arch Intern Med. 2011;171(7):678–684. , , , et al.
- Improving teamwork: impact of structured interdisciplinary rounds on a hospitalist unit. J Hosp Med. 2011;6(2):88–93. , , , , , .
- Impact of localizing physicians to hospital units on nurse‐physician communication and agreement on the plan of care. J Gen Intern Med. 2009;24(11):1223–1227. , , , et al.
- Reorganizing a hospital ward as an accountable care unit. J Hosp Med. 2015;10(1):36–40. , , , et al.
- 5th time's a charm: creation of unit‐based care teams in a high occupancy hospital [abstract]. J Hosp Med. 2015;10 (suppl. 2). Available at: http://www.shmabstracts.com/abstract/5th‐times‐a‐charm‐creation‐of‐unit‐based‐care‐teams‐in‐a‐high‐occupancy‐hospital. Accessed July 28, 2015. , , , et al.
- Comorbidity measures for use with administrative data. Med Care. 1998;36(1):8–27. , , , .
- Teamwork on inpatient medical units: assessing attitudes and barriers. Qual Saf Health Care. 2010;19(2):117–121. , , , , , .
- A model for quality improvement programs in academic departments of medicine. Am J Med. 2008;121(10):922–929. , , , et al.
- Improving nurse‐physician communication and satisfaction in the intensive care unit with a daily goals worksheet. Am J Crit Care. 2006;15(2):217–222. , , , , .
- Improving communication in the ICU using daily goals. J Crit Care. 2003;18(2):71–75. , , , , , .
- Effect of crew resource management training in a multidisciplinary obstetrical setting. Int J Qual Health Care. 2008;20(4):254–263. , , , et al.
- Error reduction and performance improvement in the emergency department through formal teamwork training: evaluation results of the MedTeams project. Health Serv Res. 2002;37(6):1553–1581. , , , et al.
- Effects of teamwork training on adverse outcomes and process of care in labor and delivery: a randomized controlled trial. Obstet Gynecol. 2007;109(1):48–55. , , , et al.
- Effects of interdisciplinary team care interventions on general medical wards: a systematic review. JAMA Intern Med. 2015;175(8):1288–1298. , , , et al.
- Patient risk factors for adverse drug events in hospitalized patients. ADE Prevention Study Group. Arch Intern Med. 1999;159(21):2553–2560. , , , et al.
- Effect of a pharmacist intervention on clinically important medication errors after hospital discharge: a randomized trial. Ann Intern Med. 2012;157(1):1–10. , , , et al.
- Use of a standardized protocol to decrease medication errors and adverse events related to sliding scale insulin. Qual Saf Health Care. 2006;15(2):89–91. , , , .
- Clinical pharmacists and inpatient medical care: a systematic review. Arch Intern Med. 2006;166(9):955–964. , , , .
- Improved inpatient use of basal insulin, reduced hypoglycemia, and improved glycemic control: effect of structured subcutaneous insulin orders and an insulin management algorithm. J Hosp Med. 2009;4(1):3–15. , , , , .
- Effects of a computerized order set on the inpatient management of hyperglycemia: a cluster‐randomized controlled trial. Endocr Pract. 2010;16(2):209–218. , , , .
- Effects of a subcutaneous insulin protocol, clinical education, and computerized order set on the quality of inpatient management of hyperglycemia: results of a clinical trial. J Hosp Med. 2009;4(1):16–27. , , , .
Damage to nearby structure common cause of hernia malpractice claim
JACKSONVILLE, FLA. – General surgeons are among the most sued physicians, and hernia repair is one of the most common operations they perform, so a study was conducted to drill down into the legal data on hernia repair to determine what about the operation is most likely to get surgeons in trouble.
They found that a failure to diagnose a complication caused by damage to a nearby structure during the operation was the most common cause for a malpractice suit for hernia repair, Dr. Nadeem Haddad of the Mayo Clinic in Rochester, Minn., reported at the Association for Academic Surgery/Society of University Surgeons Academic Surgical Congress.
“Hernia repair with more than 1 million cases annually is one of the most common surgical procedures,” Dr. Haddad said. “The most common type of operation for malpractice was inguinal hernia repair. The majority of cases were elective cases where the informed consent was not breached.”
The researchers sampled data on 250 malpractice cases arising from hernia surgery filed with the Westlaw Next legal database between 1985 and 2015, Dr. Haddad said. He added that the sample is not inclusive of all malpractice cases related to hernia repair in that time. “Our objective was to analyze reasons for litigation related to hernia repairs,” he said.
Among the hernia cases from the database, physicians (defendants) won 59%, patients (plaintiffs) won around 27%, and the remainder went to settlement before a verdict. Award payments ranged from $10,000 for a case where a Penrose drain was left in the patient to $16 million in the case of death of an infant due to perioperative hyperkalemia.
Eighty-four percent of the cases in the study involved inguinal or ventral hernia repair, Dr. Haddad said, but the Westlaw Next database did not differentiate between the two types of procedures. Nor did it separate out pediatric or adult repairs. Westlaw Next provides the alleged reason for litigation and gives details about lawsuits. The researchers classified the alleged reasons for the lawsuits based on the time period in which they happened: preoperatively, intraoperatively, and postoperatively.
“The single most common reason for malpractice in hernia repair was failure to diagnose a complication following damage to a surrounding structure,” Dr. Haddad said.
The state of New York had the highest number of medical malpractice cases (46), followed closely by California (42). In 15% of cases (38) the patients claimed a breach of informed consent by the surgeon
“While understanding the reasons why surgeons go to trial, the risk of future lawsuits may lessen if measures are enacted to prevent such outcomes,” Dr. Haddad said. “Following protocols in diagnosis and management, attention to good surgical technique, and keeping a checklist of possible complications are some of the ways to improve patients safety and decrease chances of litigation.”
Dr. Haddad and coauthors had no financial relationships to disclose.
JACKSONVILLE, FLA. – General surgeons are among the most sued physicians, and hernia repair is one of the most common operations they perform, so a study was conducted to drill down into the legal data on hernia repair to determine what about the operation is most likely to get surgeons in trouble.
They found that a failure to diagnose a complication caused by damage to a nearby structure during the operation was the most common cause for a malpractice suit for hernia repair, Dr. Nadeem Haddad of the Mayo Clinic in Rochester, Minn., reported at the Association for Academic Surgery/Society of University Surgeons Academic Surgical Congress.
“Hernia repair with more than 1 million cases annually is one of the most common surgical procedures,” Dr. Haddad said. “The most common type of operation for malpractice was inguinal hernia repair. The majority of cases were elective cases where the informed consent was not breached.”
The researchers sampled data on 250 malpractice cases arising from hernia surgery filed with the Westlaw Next legal database between 1985 and 2015, Dr. Haddad said. He added that the sample is not inclusive of all malpractice cases related to hernia repair in that time. “Our objective was to analyze reasons for litigation related to hernia repairs,” he said.
Among the hernia cases from the database, physicians (defendants) won 59%, patients (plaintiffs) won around 27%, and the remainder went to settlement before a verdict. Award payments ranged from $10,000 for a case where a Penrose drain was left in the patient to $16 million in the case of death of an infant due to perioperative hyperkalemia.
Eighty-four percent of the cases in the study involved inguinal or ventral hernia repair, Dr. Haddad said, but the Westlaw Next database did not differentiate between the two types of procedures. Nor did it separate out pediatric or adult repairs. Westlaw Next provides the alleged reason for litigation and gives details about lawsuits. The researchers classified the alleged reasons for the lawsuits based on the time period in which they happened: preoperatively, intraoperatively, and postoperatively.
“The single most common reason for malpractice in hernia repair was failure to diagnose a complication following damage to a surrounding structure,” Dr. Haddad said.
The state of New York had the highest number of medical malpractice cases (46), followed closely by California (42). In 15% of cases (38) the patients claimed a breach of informed consent by the surgeon
“While understanding the reasons why surgeons go to trial, the risk of future lawsuits may lessen if measures are enacted to prevent such outcomes,” Dr. Haddad said. “Following protocols in diagnosis and management, attention to good surgical technique, and keeping a checklist of possible complications are some of the ways to improve patients safety and decrease chances of litigation.”
Dr. Haddad and coauthors had no financial relationships to disclose.
JACKSONVILLE, FLA. – General surgeons are among the most sued physicians, and hernia repair is one of the most common operations they perform, so a study was conducted to drill down into the legal data on hernia repair to determine what about the operation is most likely to get surgeons in trouble.
They found that a failure to diagnose a complication caused by damage to a nearby structure during the operation was the most common cause for a malpractice suit for hernia repair, Dr. Nadeem Haddad of the Mayo Clinic in Rochester, Minn., reported at the Association for Academic Surgery/Society of University Surgeons Academic Surgical Congress.
“Hernia repair with more than 1 million cases annually is one of the most common surgical procedures,” Dr. Haddad said. “The most common type of operation for malpractice was inguinal hernia repair. The majority of cases were elective cases where the informed consent was not breached.”
The researchers sampled data on 250 malpractice cases arising from hernia surgery filed with the Westlaw Next legal database between 1985 and 2015, Dr. Haddad said. He added that the sample is not inclusive of all malpractice cases related to hernia repair in that time. “Our objective was to analyze reasons for litigation related to hernia repairs,” he said.
Among the hernia cases from the database, physicians (defendants) won 59%, patients (plaintiffs) won around 27%, and the remainder went to settlement before a verdict. Award payments ranged from $10,000 for a case where a Penrose drain was left in the patient to $16 million in the case of death of an infant due to perioperative hyperkalemia.
Eighty-four percent of the cases in the study involved inguinal or ventral hernia repair, Dr. Haddad said, but the Westlaw Next database did not differentiate between the two types of procedures. Nor did it separate out pediatric or adult repairs. Westlaw Next provides the alleged reason for litigation and gives details about lawsuits. The researchers classified the alleged reasons for the lawsuits based on the time period in which they happened: preoperatively, intraoperatively, and postoperatively.
“The single most common reason for malpractice in hernia repair was failure to diagnose a complication following damage to a surrounding structure,” Dr. Haddad said.
The state of New York had the highest number of medical malpractice cases (46), followed closely by California (42). In 15% of cases (38) the patients claimed a breach of informed consent by the surgeon
“While understanding the reasons why surgeons go to trial, the risk of future lawsuits may lessen if measures are enacted to prevent such outcomes,” Dr. Haddad said. “Following protocols in diagnosis and management, attention to good surgical technique, and keeping a checklist of possible complications are some of the ways to improve patients safety and decrease chances of litigation.”
Dr. Haddad and coauthors had no financial relationships to disclose.
AT THE ANNUAL ACADEMIC SURGICAL CONGRESS
Key clinical point: Failure to diagnose a complication caused by damage to a nearby structure during hernia repair surgery is the most common cause for a malpractice claim for hernia repair.
Major finding: In malpractice cases involving hernia surgery that go to trial, 59% of the rulings are for the plaintiff physicians and about 14% go to settlement before a judge or jury decision.
Data source: Sample of 250 hernia surgical malpractice cases from 1985 to 2015 in the Westlaw Next legal database.
Disclosures: The study authors reported having no financial disclosures.
Potential biomarkers of gray matter damage in MS identified
NEW ORLEANS – Protein profiling of cerebrospinal fluid and MRI has revealed the involvement of exacerbated gray matter demyelination and brain atrophy in the progression of multiple sclerosis.
The pattern of the cerebrospinal fluid (CSF) biomarkers, which correspond to the extent of gray matter damage, have potential value in stratifying patients in terms of disease severity from the onset of multiple sclerosis (MS), Roberta Magliozzi, Ph.D., of the University of Verona (Italy) said at the meeting held by the Americas Committee for Treatment and Research in Multiple Sclerosis.
Gray matter atrophy and the accumulation of cortical lesions are central to the progressive clinical deterioration that occurs in MS. The damage involves a “compartmentalized immune response” featuring meningeal infiltration of certain immune cells, which is associated with increased cortical demyelination and meningeal inflammation. The gray matter damage and inflammation are harbingers of earlier onset and rapid progression of neurological damage in MS, and a more severe disease outcome.
“We sought to find a combination of CSF biomarkers [and] neuropathological and early neuroimaging correlates of disease progression in order to predict onset and rate of MS progression,” Dr. Magliozzi explained.
The investigators assessed gray matter damage with MRI and analyzed CSF proteins in 36 MS patients and 12 healthy controls and also acquired and analyzed meningeal and CSF samples after death from 20 individuals with secondary progressive MS (SPMS) and 10 healthy individuals to detect inflammatory mediators associated with meningeal infiltration that were released to the CSF.
MS patients with meningeal infiltration displayed more extensive gray matter demyelination and more rapid disease progression. They also demonstrated a “pronounced proinflammatory CSF profile” featuring overexpression of an array of molecules associated with chronic inflammation. Patients with less gray matter damage displayed a pattern of increased regulatory molecules. Consistent with the patient data, similar expression patterns were evident in the meninges and CSF samples of postmortem SPMS cases with a higher level of meningeal inflammation and gray matter demyelination.
“Meningeal infiltrates may represent the main source of intrathecal inflammatory activity mediating the gradient of cortical tissue injury since early disease stages and in progressive MS,” Dr. Magliozzi said.
The markedly different CSF profiles in patients with more and less extensive gray matter damage may be an exploitable characteristic to stratify patients early in the course of MS, with benefits in disease prognosis and monitoring, and treatment that is more rationally geared to the patient’s condition.
“The results indicate that we may be able to get an image-based functional profile of patients in relapse, which would be a phenomenal finding,” Dr. Jerry Wolinsky of the University of Texas Health Science Center at Houston, commented in a press conference following the presentation.
The study was funded by Progressive MS Alliance. Dr. Magliozzi had no disclosures.
NEW ORLEANS – Protein profiling of cerebrospinal fluid and MRI has revealed the involvement of exacerbated gray matter demyelination and brain atrophy in the progression of multiple sclerosis.
The pattern of the cerebrospinal fluid (CSF) biomarkers, which correspond to the extent of gray matter damage, have potential value in stratifying patients in terms of disease severity from the onset of multiple sclerosis (MS), Roberta Magliozzi, Ph.D., of the University of Verona (Italy) said at the meeting held by the Americas Committee for Treatment and Research in Multiple Sclerosis.
Gray matter atrophy and the accumulation of cortical lesions are central to the progressive clinical deterioration that occurs in MS. The damage involves a “compartmentalized immune response” featuring meningeal infiltration of certain immune cells, which is associated with increased cortical demyelination and meningeal inflammation. The gray matter damage and inflammation are harbingers of earlier onset and rapid progression of neurological damage in MS, and a more severe disease outcome.
“We sought to find a combination of CSF biomarkers [and] neuropathological and early neuroimaging correlates of disease progression in order to predict onset and rate of MS progression,” Dr. Magliozzi explained.
The investigators assessed gray matter damage with MRI and analyzed CSF proteins in 36 MS patients and 12 healthy controls and also acquired and analyzed meningeal and CSF samples after death from 20 individuals with secondary progressive MS (SPMS) and 10 healthy individuals to detect inflammatory mediators associated with meningeal infiltration that were released to the CSF.
MS patients with meningeal infiltration displayed more extensive gray matter demyelination and more rapid disease progression. They also demonstrated a “pronounced proinflammatory CSF profile” featuring overexpression of an array of molecules associated with chronic inflammation. Patients with less gray matter damage displayed a pattern of increased regulatory molecules. Consistent with the patient data, similar expression patterns were evident in the meninges and CSF samples of postmortem SPMS cases with a higher level of meningeal inflammation and gray matter demyelination.
“Meningeal infiltrates may represent the main source of intrathecal inflammatory activity mediating the gradient of cortical tissue injury since early disease stages and in progressive MS,” Dr. Magliozzi said.
The markedly different CSF profiles in patients with more and less extensive gray matter damage may be an exploitable characteristic to stratify patients early in the course of MS, with benefits in disease prognosis and monitoring, and treatment that is more rationally geared to the patient’s condition.
“The results indicate that we may be able to get an image-based functional profile of patients in relapse, which would be a phenomenal finding,” Dr. Jerry Wolinsky of the University of Texas Health Science Center at Houston, commented in a press conference following the presentation.
The study was funded by Progressive MS Alliance. Dr. Magliozzi had no disclosures.
NEW ORLEANS – Protein profiling of cerebrospinal fluid and MRI has revealed the involvement of exacerbated gray matter demyelination and brain atrophy in the progression of multiple sclerosis.
The pattern of the cerebrospinal fluid (CSF) biomarkers, which correspond to the extent of gray matter damage, have potential value in stratifying patients in terms of disease severity from the onset of multiple sclerosis (MS), Roberta Magliozzi, Ph.D., of the University of Verona (Italy) said at the meeting held by the Americas Committee for Treatment and Research in Multiple Sclerosis.
Gray matter atrophy and the accumulation of cortical lesions are central to the progressive clinical deterioration that occurs in MS. The damage involves a “compartmentalized immune response” featuring meningeal infiltration of certain immune cells, which is associated with increased cortical demyelination and meningeal inflammation. The gray matter damage and inflammation are harbingers of earlier onset and rapid progression of neurological damage in MS, and a more severe disease outcome.
“We sought to find a combination of CSF biomarkers [and] neuropathological and early neuroimaging correlates of disease progression in order to predict onset and rate of MS progression,” Dr. Magliozzi explained.
The investigators assessed gray matter damage with MRI and analyzed CSF proteins in 36 MS patients and 12 healthy controls and also acquired and analyzed meningeal and CSF samples after death from 20 individuals with secondary progressive MS (SPMS) and 10 healthy individuals to detect inflammatory mediators associated with meningeal infiltration that were released to the CSF.
MS patients with meningeal infiltration displayed more extensive gray matter demyelination and more rapid disease progression. They also demonstrated a “pronounced proinflammatory CSF profile” featuring overexpression of an array of molecules associated with chronic inflammation. Patients with less gray matter damage displayed a pattern of increased regulatory molecules. Consistent with the patient data, similar expression patterns were evident in the meninges and CSF samples of postmortem SPMS cases with a higher level of meningeal inflammation and gray matter demyelination.
“Meningeal infiltrates may represent the main source of intrathecal inflammatory activity mediating the gradient of cortical tissue injury since early disease stages and in progressive MS,” Dr. Magliozzi said.
The markedly different CSF profiles in patients with more and less extensive gray matter damage may be an exploitable characteristic to stratify patients early in the course of MS, with benefits in disease prognosis and monitoring, and treatment that is more rationally geared to the patient’s condition.
“The results indicate that we may be able to get an image-based functional profile of patients in relapse, which would be a phenomenal finding,” Dr. Jerry Wolinsky of the University of Texas Health Science Center at Houston, commented in a press conference following the presentation.
The study was funded by Progressive MS Alliance. Dr. Magliozzi had no disclosures.
AT ACTRIMS FORUM 2016
Key clinical point: The different CSF profiles in patients with more and less extensive gray matter damage may be useful to stratify patients early in the course of MS.
Major finding: Protein profiling of CSF and brain MRI has revealed the involvement of exacerbated gray matter demyelination and brain atrophy in the progression of multiple sclerosis.
Data source: A cohort study of 36 MS patients and 12 healthy controls and a postmortem study of 20 individuals with secondary progressive MS and 10 healthy individuals.
Disclosures: The study was funded by Progressive MS Alliance. Dr. Magliozzi had no disclosures.
Fibromyalgia doesn’t fit the disease model



You can help victims of hazing recover from psychological and physical harm
Initiation has been a part of the tradition of many sororities, fraternities, sports teams, and other organizations to screen and evaluate potential members. Initiation activities can range from humorous, such as pulling pranks on others, to more serious, such as being able to recite the organization’s rules and creed. It is used in the hopes of increasing a new member’s commitment to the group, with the goal of creating group cohesion.
Hazing is not initiation
Hazing is the use of ritualized physical, sexual, and psychological abuse in the guise of initiation. Hazing activities do not help identify the qualities that a person needs for group membership, and can lead to severe physical and psychological harm. Many hazing rituals are done behind closed doors, some with a vow of secrecy.
Studies indicate that 47% of students have been hazed before college, and that 3 of every 5 college students have been subjected to hazing.1 Military and sports teams also have a high rate of hazing; 40% of athletes report that a coach or advisor knew about the hazing.2
Dangers of hazing
Victims of hazing might be brought to the emergency room with severe injury, including broken bones, burns, alcohol intoxication–related injury, chest trauma, multi-organ system failure, sexual trauma, and other medical emergencies, or could die from injuries sustained during hazing activities.
In the 44 states where hazing is illegal, hazing participants could be held be civilly and criminally liable for their actions. Hazing victims may be required to commit crimes, ranging from destruction of property to kidnapping. One-half of all hazing activities involve the use of alcohol,2 and 82% of hazing-related deaths involve alcohol.1
What is your role in treating hazing victims?
You might be called on to treat the psychological symptoms of hazing, including:
- depression
- anxiety
- acute stress syndrome
- alcohol- and drug-related delirium
- posttraumatic stress syndrome.
In addition, you might find yourself needing to:
Arrange for medical care immediately if the patient has a medical problem or an injury.
Contact a victim advocacy programif the victim has made allegations about, or there is evidence of, sexual assault, rape, other sexual injury, or physical or psychological violence.
Notify appropriate law enforcement personnel.
Notify the leadership of the organization (eg, team, school, club) within which the hazing occurred.
Perform a psychiatric assessment and provide treatment for the victim. Some symptoms seen in victims of hazing include sleep disturbance and insomnia, poor grades, eating disorders, depression, anxiety, feelings of low self-esteem and self-worth, trust issues, and symptoms commonly seen in patients with posttraumatic stress syndrome. Symptoms sometimes appear immediately after a hazing event; other times, they develop weeks later. Supportive counseling, stabilization, and advocacy are the immediate goals.
Provide education and treatment for the perpetrator. Unlike bullying, most hazing is not instituted to harm the victim but is seen as a tradition and ritual to increase commitment and bonding. The perpetrator might feel surprise and guilt as to the harm that was done to the victim. Observers of hazing rituals might be traumatized by viewing participants humiliated or abused, and both observers and perpetrators as participants may face legal consequences. Counseling and group debriefing provide education and help them cope with these issues.
Act as a consultant to schools, teams, and other organizations to ensure that group cohesion and team building is obtained in a way that benefits the group and does not harm a member or the organization.
Psychiatrists can provide literature and information especially to adolescent and young adult patients who are at highest risk of hazing. Handouts, informational brochures and posters and be placed in the waiting areas for patient to view. These can be found online (such as www.doe.in.gov/sites/default/files/safety/and-hazing.pdf) or obtained from local colleges and school systems.
1. Allan EJ, Madden M. Hazing in view: students at risk. http://www.stophazing.org/wp-content/uploads/2014/06/hazing_in_view_web1.pdf. Published March 11, 2008. Accessed May 18, 2015.
2. McBride HC. Parents beware: hazing poses significant danger to new college students. CRC Health. http://www.crchealth.com/treatment/treatment-for-teens/alcohol-addiction/hazing. Accessed May 18, 2015.
Initiation has been a part of the tradition of many sororities, fraternities, sports teams, and other organizations to screen and evaluate potential members. Initiation activities can range from humorous, such as pulling pranks on others, to more serious, such as being able to recite the organization’s rules and creed. It is used in the hopes of increasing a new member’s commitment to the group, with the goal of creating group cohesion.
Hazing is not initiation
Hazing is the use of ritualized physical, sexual, and psychological abuse in the guise of initiation. Hazing activities do not help identify the qualities that a person needs for group membership, and can lead to severe physical and psychological harm. Many hazing rituals are done behind closed doors, some with a vow of secrecy.
Studies indicate that 47% of students have been hazed before college, and that 3 of every 5 college students have been subjected to hazing.1 Military and sports teams also have a high rate of hazing; 40% of athletes report that a coach or advisor knew about the hazing.2
Dangers of hazing
Victims of hazing might be brought to the emergency room with severe injury, including broken bones, burns, alcohol intoxication–related injury, chest trauma, multi-organ system failure, sexual trauma, and other medical emergencies, or could die from injuries sustained during hazing activities.
In the 44 states where hazing is illegal, hazing participants could be held be civilly and criminally liable for their actions. Hazing victims may be required to commit crimes, ranging from destruction of property to kidnapping. One-half of all hazing activities involve the use of alcohol,2 and 82% of hazing-related deaths involve alcohol.1
What is your role in treating hazing victims?
You might be called on to treat the psychological symptoms of hazing, including:
- depression
- anxiety
- acute stress syndrome
- alcohol- and drug-related delirium
- posttraumatic stress syndrome.
In addition, you might find yourself needing to:
Arrange for medical care immediately if the patient has a medical problem or an injury.
Contact a victim advocacy programif the victim has made allegations about, or there is evidence of, sexual assault, rape, other sexual injury, or physical or psychological violence.
Notify appropriate law enforcement personnel.
Notify the leadership of the organization (eg, team, school, club) within which the hazing occurred.
Perform a psychiatric assessment and provide treatment for the victim. Some symptoms seen in victims of hazing include sleep disturbance and insomnia, poor grades, eating disorders, depression, anxiety, feelings of low self-esteem and self-worth, trust issues, and symptoms commonly seen in patients with posttraumatic stress syndrome. Symptoms sometimes appear immediately after a hazing event; other times, they develop weeks later. Supportive counseling, stabilization, and advocacy are the immediate goals.
Provide education and treatment for the perpetrator. Unlike bullying, most hazing is not instituted to harm the victim but is seen as a tradition and ritual to increase commitment and bonding. The perpetrator might feel surprise and guilt as to the harm that was done to the victim. Observers of hazing rituals might be traumatized by viewing participants humiliated or abused, and both observers and perpetrators as participants may face legal consequences. Counseling and group debriefing provide education and help them cope with these issues.
Act as a consultant to schools, teams, and other organizations to ensure that group cohesion and team building is obtained in a way that benefits the group and does not harm a member or the organization.
Psychiatrists can provide literature and information especially to adolescent and young adult patients who are at highest risk of hazing. Handouts, informational brochures and posters and be placed in the waiting areas for patient to view. These can be found online (such as www.doe.in.gov/sites/default/files/safety/and-hazing.pdf) or obtained from local colleges and school systems.
Initiation has been a part of the tradition of many sororities, fraternities, sports teams, and other organizations to screen and evaluate potential members. Initiation activities can range from humorous, such as pulling pranks on others, to more serious, such as being able to recite the organization’s rules and creed. It is used in the hopes of increasing a new member’s commitment to the group, with the goal of creating group cohesion.
Hazing is not initiation
Hazing is the use of ritualized physical, sexual, and psychological abuse in the guise of initiation. Hazing activities do not help identify the qualities that a person needs for group membership, and can lead to severe physical and psychological harm. Many hazing rituals are done behind closed doors, some with a vow of secrecy.
Studies indicate that 47% of students have been hazed before college, and that 3 of every 5 college students have been subjected to hazing.1 Military and sports teams also have a high rate of hazing; 40% of athletes report that a coach or advisor knew about the hazing.2
Dangers of hazing
Victims of hazing might be brought to the emergency room with severe injury, including broken bones, burns, alcohol intoxication–related injury, chest trauma, multi-organ system failure, sexual trauma, and other medical emergencies, or could die from injuries sustained during hazing activities.
In the 44 states where hazing is illegal, hazing participants could be held be civilly and criminally liable for their actions. Hazing victims may be required to commit crimes, ranging from destruction of property to kidnapping. One-half of all hazing activities involve the use of alcohol,2 and 82% of hazing-related deaths involve alcohol.1
What is your role in treating hazing victims?
You might be called on to treat the psychological symptoms of hazing, including:
- depression
- anxiety
- acute stress syndrome
- alcohol- and drug-related delirium
- posttraumatic stress syndrome.
In addition, you might find yourself needing to:
Arrange for medical care immediately if the patient has a medical problem or an injury.
Contact a victim advocacy programif the victim has made allegations about, or there is evidence of, sexual assault, rape, other sexual injury, or physical or psychological violence.
Notify appropriate law enforcement personnel.
Notify the leadership of the organization (eg, team, school, club) within which the hazing occurred.
Perform a psychiatric assessment and provide treatment for the victim. Some symptoms seen in victims of hazing include sleep disturbance and insomnia, poor grades, eating disorders, depression, anxiety, feelings of low self-esteem and self-worth, trust issues, and symptoms commonly seen in patients with posttraumatic stress syndrome. Symptoms sometimes appear immediately after a hazing event; other times, they develop weeks later. Supportive counseling, stabilization, and advocacy are the immediate goals.
Provide education and treatment for the perpetrator. Unlike bullying, most hazing is not instituted to harm the victim but is seen as a tradition and ritual to increase commitment and bonding. The perpetrator might feel surprise and guilt as to the harm that was done to the victim. Observers of hazing rituals might be traumatized by viewing participants humiliated or abused, and both observers and perpetrators as participants may face legal consequences. Counseling and group debriefing provide education and help them cope with these issues.
Act as a consultant to schools, teams, and other organizations to ensure that group cohesion and team building is obtained in a way that benefits the group and does not harm a member or the organization.
Psychiatrists can provide literature and information especially to adolescent and young adult patients who are at highest risk of hazing. Handouts, informational brochures and posters and be placed in the waiting areas for patient to view. These can be found online (such as www.doe.in.gov/sites/default/files/safety/and-hazing.pdf) or obtained from local colleges and school systems.
1. Allan EJ, Madden M. Hazing in view: students at risk. http://www.stophazing.org/wp-content/uploads/2014/06/hazing_in_view_web1.pdf. Published March 11, 2008. Accessed May 18, 2015.
2. McBride HC. Parents beware: hazing poses significant danger to new college students. CRC Health. http://www.crchealth.com/treatment/treatment-for-teens/alcohol-addiction/hazing. Accessed May 18, 2015.
1. Allan EJ, Madden M. Hazing in view: students at risk. http://www.stophazing.org/wp-content/uploads/2014/06/hazing_in_view_web1.pdf. Published March 11, 2008. Accessed May 18, 2015.
2. McBride HC. Parents beware: hazing poses significant danger to new college students. CRC Health. http://www.crchealth.com/treatment/treatment-for-teens/alcohol-addiction/hazing. Accessed May 18, 2015.
Reducing morbidity and mortality from common medical conditions in schizophrenia
Life expectancy for both males and females has been increasing over the past several decades to an average of 76 years. However, the life expectancy among individuals with schizophrenia in the United States is 61 years—a 20% reduction.1 Patients with schizophrenia are known to be at increased risk of several comorbid medical conditions, such as type 2 diabetes mellitus (T2DM), coronary artery disease, and digestive and liver disorders, compared with healthy people (Figure, page 32).2-5 This risk may be heightened by several factors, including sedentary lifestyle, a high rate of cigarette use, poor self-management skills, homelessness, and poor diet.
Although substantial attention is paid to the psychiatric and behavioral management of schizophrenia, many barriers impede the detection and treatment of patients’ medical conditions, which have been implicated in excess unforeseen deaths. Patients with schizophrenia might experience delays in diagnosis, leading to more acute comorbidity at time of diagnosis and premature mortality
Cardiovascular disease is the leading cause of death among psychiatric patients.6 Key risk factors for cardiovascular disease include smoking, obesity, hypertension, dyslipidemia, diabetes, and lack of physical activity, all of which are more prevalent among patients with schizophrenia.7 In addition, antipsychotics are associated with adverse metabolic effects.8 In general, smoking and obesity are the most modifiable and preventable risk factors for many medical conditions, such as cardiovascular disease, hyperlipidemia, diabetes, and many forms of cancer (Table 1).
In this article, we discuss how to manage common medical comorbidities in patients with schizophrenia. Comprehensive management for all these medical conditions in this population is beyond the scope of this article; we limit ourselves to discussing (1) how common these conditions are in patients with schizophrenia compared with the general population and (2) what can be done in psychiatric practice to manage these medical comorbidities (Box).
Obesity
Obesity—defined as body mass index (BMI) of >30—is common among patients with schizophrenia. The condition leads to poor self-image, decreased treatment adherence, and an increased risk of many chronic medical conditions (Table 1). Being overweight or obese can increase stigma and social discrimination, which will undermine self-esteem and, in turn, affect adherence with medications, leading to relapse.
The prevalence of obesity among patients with schizophrenia is almost double that of the general population9 (Figure2-5). Several factors predispose these patients to overweight or obese, including sedentary lifestyle, lack of exercise, a high-fat diet, medications side effects, and genetic factors. Recent studies report the incidence of weight gain among patients treated with antipsychotics is as high as 80%10 (Table 2).
Mechanisms involved in antipsychotic-induced weight gain are not completely understood, but antagonism of serotonergic (5-HT2C, 5-HT1A), histamine (H1), dopamine (D2), muscarinic, and other receptors are involved in modulation of food intake. Decreased energy expenditure also has been blamed for antipsychotic-induced weight gain.10
Pharmacotherapy and bariatric surgery can be as effective among patients with schizophrenia as they are among the general population. Maintaining a BMI of <25 kg/m2 lowers the risk of cardiovascular disease by 35% to 55%.6 Metformin has modest potential for offsetting weight gain and providing some metabolic control in overweight outpatients with schizophrenia,11 and should be considered early when treating at-risk patients.
Managing obesity. Clinicians can apply several measures to manage obesity in a patient with schizophrenia:
- Educate the patient, and the family, about the risks of being overweight or obese.
- Monitor weight and BMI at each visit.
- Advise smoking cessation.
- When clinically appropriate, switch to an antipsychotic with a lower risk of weight gain—eg, from olanzapine or high-dose quetiapine to a high- or medium-potency typical antipsychotic (eg, haloperidol, perphenazine), ziprasidone, aripiprazole, iloperidone, and lurasidone (Table 2, page 36).
- Consider prophylactic use of metformin with an antipsychotic; the drug has modest potential for offsetting weight gain and providing better metabolic control in an overweight patient with schizophrenia.11
- Encourage the patient to engage in modest physical activity; for example, a 20-minute walk, every day, reduces the risk of cardiovascular disease by 35% to 55%.6
- Recommend a formal lifestyle modification program, such as behavioral group-based treatment for weight reduction.12
- Refer the patient and family to a dietitian.
Type 2 diabetes mellitus
There is strong association between T2DM and schizophrenia that is related to abnormal glucose regulation independent of any adverse medication effect.13 Ryan et al14 reported that first-episode, drug-naïve patients with schizophrenia had a higher level of intra-abdominal fat than age- and BMI-matched healthy controls, suggesting that schizophrenia could be associated with changes in adiposity that might increase the risk of insulin resistance, hyperlipidemia, and dyslipidemia. Mechanisms that increase the risk of T2DM in schizophrenia include genetic and environmental factors, such as family history, lack of physical activity, and poor diet.
Diagnosis. All patients with schizophrenia should be evaluated for undiagnosed diabetes. The diagnosis of T2DM is made by documenting:
- a fasting plasma glucose reading of ≥126 mg/dL
- symptoms of T2DM, along with a random plasma glucose reading of ≥200 mg/dL
- 2-hour reading of a plasma glucose level >200 mg/dL on an oral glucose tolerance test.
Recent guidelines also suggest using a hemoglobin A1c value cutoff of ≥6.5% to diagnose T2DM.
In the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) study, 38% of patients with schizophrenia and diabetes were not receiving any treatment for T2DM.15
Risk factors for T2DM are:
- BMI >25
- a first-degree relative with diabetes
- lack of physical activity
- being a member of a high-risk ethnic group (African American, Hispanic American, Native American, Asian American, or Pacific Islander)
- having delivered a baby >9 lb or having had gestational diabetes
- hypertension
- high-density lipoprotein (HDL) cholesterol level of ≤35 mg/dL
- triglyceride level of ≥250 mg/dL
- history of an abnormal glucose tolerance test
- history of abnormal findings on a fasting plasma glucose test
- history of vascular disease.
Early detection and management.
- Educate the patient and family about signs and symptoms of T2DM, such as polyuria, nocturia, polydipsia, fatigue, visual disturbances, and (in women) vulvitis. Also, psychiatrists should be aware of, and inquire about, symptoms of diabetic ketoacidosis.
- At the start of therapy with any antipsychotic, particularly a second-generation antipsychotic (SGA), ask patients about a family history of diabetes and measure the hemoglobin A1c value.
- Monitor the hemoglobin A1c level 4 months after starting an antipsychotic, then annually, in a patient with significant risk factors for diabetes.
- Monitor blood glucose every 6 months in patients with no change from initial results and more frequently in those with significant risk factors for diabetes and those who gain weight.
- Order a lipid panel and measure the serum glucose level to rule out dyslipidemia and diabetes, because a patient with high lipid levels and diabetes is at higher risk of developing cardiovascular conditions.
- Advocate for smoking cessation.
- Switch to an antipsychotic with a lower risk of diabetes when clinically appropriate, such as switching a patient from olanzapine or high-dose quetiapine to a high- or medium-potency typical antipsychotic (such as haloperidol or perphenazine), ziprasidone, aripiprazole, iloperidone, and lurasidone (Table 2).
- Consider prophylactic use of metformin along with antipsychotics. Metformin has been used to improve insulin sensitivity and can lead to weight loss in diabetic and non-diabetic patients. The drug has modest potential for offsetting weight gain and providing better metabolic control in overweight outpatients with schizophrenia.11 Metformin is simple to use, does not lead to hypoglycemia, does not require serum glucose monitoring, and has a favorable safety profile.11
- Educate the patient about modest physical activity. For example, a 20-minute walk every day reduces the risk of cardiovascular disease by 35% to 55%.6
- Refer the patient to a dietitian to develop an appropriate diet plan.
- When diabetes is diagnosed, ensure appropriate follow-up and initiation or continuation of therapy with a general practitioner or an endocrinologist.
- Reinforce the need for ongoing follow-up and compliance with therapy for diabetes.
Hyperlipidemia and dyslipidemia
Elevated cholesterol and triglyceride levels are associated with cardiovascular diseases, such as ischemic heart disease and myocardial infarction. A 10% increase in cholesterol levels is associated with a 20% to 30% increase in the risk of coronary artery disease; lowering cholesterol by 10% decreases the risk by 20% to 30%.16 Triglyceride levels ≥250 mg/dL are associated with 2-fold higher risk of cardiovascular disease.16
The incidence of dyslipidemia is not as well studied as diabetes in patients with schizophrenia. There is increased prevalence of dyslipidemia in patients with schizophrenia compared with the general population because of obesity, lack of physical activity, and poor dietary habits.16
Data regarding the effects of first-generation antipsychotics (FGAs) on lipid levels are limited, but high-potency drugs, such as haloperidol, seem to carry a lower risk of hyperlipidemia than low-potency drugs, such as chlorpromazine and thioridazine.17 A comprehensive review on the effects of SGAs on plasma lipid levels suggested that clozapine, olanzapine, and quetiapine are associated with a higher risk of dyslipidemia17 (Table 2).
In the CATIE study, olanzapine and clozapine were associated with a greater increase in the serum level of cholesterol and triglycerides compared with other antipsychotics, even after adjusting for treatment duration. Furthermore, a retrospective chart review of patients who switched to aripiprazole from other SGAs showed a decrease in levels of total cholesterol and low-density lipoprotein cholesterol15 (Table 2).
Patients with schizophrenia are more likely to have dyslipidemia go undiagnosed, and therefore are less likely to be treated for the disorder. In the CATIE study, 88% of patients with dyslipidemia were not receiving any treatment.15
Management for dyslipidemia.
- Educate the patient and family about risks involved with dyslipidemia.
- Monitor weight and BMI at each visit.
- Monitor lipids to rule out dyslipidemia. Obtain a pretreatment fasting or random lipid profile for any patient receiving an antipsychotic; repeat at least every 6 months after starting the antipsychotic.
- Counsel the patient to quit smoking.
- Switch to an antipsychotic with lower risk of weight gain and dyslipidemia, such as switching from olanzapine or high-dose quetiapine to high- or medium-potency typical antipsychotics (such as, haloperidol or perphenazine), ziprasidone, aripiprazole, iloperidone, and lurasidone (Table 2).
- Educate and encourage the patient about modest physical activity. For example, a 20-minute walk everyday will reduce cardiovascular disease risk by 35% to 55%.6
- Refer to a dietitian if indicated.
- Ensure follow-up and initiation of treatment with a general practitioner.
- Educate and encourage the patient about modest physical activity. For example, a 20-minute walk everyday will reduce cardiovascular disease risk by 35% to 55%.
Metabolic syndrome
Metabolic syndrome is cluster of cardiovascular risk factors, including central adiposity, hyperglycemia, dyslipidemia, and hypertension. The National Cholesterol Education Program’s Adult Treatment Panel III report defines metabolic syndrome as the presence of 3 of 5 of the following factors:
- abdominal obesity (waist circumference of >40 inches in men, or >35 inches in women)
- triglyceride level, >150 mg/dL
- HDL cholesterol, <40 mg/dL in men and <50 mg/dL in women
- blood pressure, >130/85 mm Hg
- fasting plasma glucose level, >110 mg/dL.
The presence of metabolic syndrome in the general population is a strong predictor of cardiovascular diseases and diabetes.18 The adverse effects of metabolic syndrome are thought to relate to atherogenic dyslipidemia, higher blood pressure, insulin resistance with or without glucose intolerance, a proinflammatory state, and a prothrombotic state.
The prevalence of metabolic syndrome in patients with schizophrenia is 2- to 3-fold higher than the general population.19 In the CATIE study, approximately one-third of patients met criteria for metabolic syndrome at baseline.15 In a prospective study, De Hert et al20 reported that patients who were started on a SGA had more than twice the rate of developing metabolic syndrome compared with those treated with a FGA (Table 2). Other possible causes of metabolic syndrome are visceral adiposity and insulin resistance.16Management of the metabolic syndrome involves addressing the individual components that have been described in the preceding sections on T2DM and dyslipidemia.
Hepatitis C
Hepatitis C virus (HCV) infection is thought to be the most common blood-borne illness, with an estimated prevalence of 1% of the U.S. population. Some studies suggest that as many as 16% of people with schizophrenia have HCV infection.4 Risk factors for HCV infection include unsafe sexual practices, prostitution, homosexuality, homelessness, and IV drug use.
HCV treatments typically have involved regimens with interferon alfa, which is associated with significant neuropsychiatric side effects, including depression and suicide. There is a dearth of research on treatment of HCV in patients with schizophrenia; however, at least 1 study suggests that there was no increase in psychiatric symptoms in patients treated with interferon-containing regimens.21 There is even less evidence to guide the use of newer, non-interferon–based HCV treatment regimens that are better tolerated and have a higher response rate in the general population; there is reason, however, to be hopeful about their potential in patients with schizophrenia and HCV infection.
Managing HCV infection.
- Educate the patients and family about risk factors associated with contracting HCV.
- Screen for HCV infection in patients with schizophrenia because there is higher prevalence of HCV in these patients compared with the general population.
- When HCV infection is diagnosed, educate the patients and family about available treatments.
- Facilitate referral to an HCV specialist for appropriate treatment.
HIV/AIDS
HIV infection is highly prevalent among people suffering from severe mental illness such as schizophrenia. The incidence of HIV/AIDS in patients with schizophrenia is estimated to be 4% to 23%, compared with 0.6% in the general population.22 Risk factors associated with a higher incidence of HIV/AIDS in patients with schizophrenia are lack of knowledge about contracting HIV, unsafe sexual practices, prostitution, homosexuality, homelessness, and IV drug use.22
Managing HIV/AIDS.
- Educate the patient and family about risk factors associated with contracting HIV/AIDS.
- Educate patients about safe sex practices.
- All patients with schizophrenia should be screened for HIV because there is 10-fold higher HIV prevalence in schizophrenia compared with the general population.
- When HIV infection is diagnosed, facilitate referral to a HIV or infectious disease specialist for treatment.
- Educate the patient in whom HIV/AIDS has been diagnosed about the importance of (1) adherence to his (her) HIV medication regimen and (2) follow-up visits with an infectious disease practitioner and appropriate laboratory tests.
- Educate the patient’s family and significant other about the illness.
- Screen for and treat substance use.
- At each visit, inquire about the patient’s adherence to HIV medical therapy, viral load, and CD4 cell count.
Chronic obstructive pulmonary disease
Patients with schizophrenia are more likely to suffer from respiratory disease, such as chronic obstructive pulmonary disease (COPD) and asthma, compared with the general population.23 Smoking is a major risk factor for COPD. In a study by Dickerson et al,24 64% of people with schizophrenia were current smokers, compared with 19% of those without mental illness.
A high rate of smoking rate among people with schizophrenia suggests a “self-medication” hypothesis: That is, stimulation of CNS nicotinic cholinergic receptors treats the negative symptoms of schizophrenia and overcomes the dopamine blocking effects of antipsychotics.25 Among SGAs, only clozapine has a substantial body of evidence to support its association with decreased smoking behavior.
Managing COPD.
- Educate the patient and family about risk factors associated with COPD and smoking.
- Screen for tobacco use at each visit; try to increase motivation to quit smoking.
- Educate the patients and family about the value and availability of smoking cessation programs.
- Prescribe medication to help with smoking cessation when needed. Bupropion and varenicline have been shown to be effective in patients with schizophrenia; nicotine replacement therapies are safe and can be helpful.
- When treating a patient who is in the process of quitting, encourage and help him to maintain his commitment and enlist support from his family.
- Refer to an appropriate medical provider (primary care provider or pulmonologist) for a patient with an established or suspected diagnosis of COPD.
Cancer
Since 1909, when the Board of Control of the Commissioners in Lunacy for England and Wales noted the possibility of a decreased incidence in cancer among psychiatric patients, this connection has been a matter of controversy.26 Subsequent research has been equivocal; the prevalence of cancer has been reported to be either increased, similar, or decreased compared with the general population.26-28 Risk factors for cancer, including smoking, obesity, poor diet, sedentary lifestyle, and hyperprolactinemia, are more common among patients with schizophrenia.
Genetic factors and a possible protective effect from antipsychotics have been cited as potential causes of decreased prevalence. Clozapine is associated with an increased risk of leukemia. No conclusion can be drawn about the overall prevalence of cancer in schizophrenia.
Managing cancer in a patient with schizophrenia, however, poses a significant challenge29; he might lack capacity to make decisions about cancer treatment. The patient—or his surrogate decision-makers—need to carefully weigh current quality of life against potential benefits of treatment and risks of side effects. Adherence to complex, often toxic, therapies can be challenging for the patient with psychosis. Successful cancer treatment often requires close collaboration between the cancer treatment team and the patient’s support system, including the treating psychiatrist and case management teams.
Bottom Line
Patients with schizophrenia are at higher risk of developing comorbid medical
conditions because of the illness itself, lifestyle behaviors, genetics, and adverse
effects of medications. Because mental health clinicians focus attention on the
psychiatric and behavioral aspect of treatment, often there is delay in screening,
detecting, and treating medical comorbidities. This screening can be done in any
psychiatric practice, which can lead to timely management for those conditions
and preventing premature mortality in patients with schizophrenia.
1. Brown S, Inskip H, Barraclough B. Causes of the excess mortality of schizophrenia. Br J Psychiatry. 2000;177:212-217.
2. De Hert M, Correl CU, Bobes J, et al. Physical illness in patients with severe mental disorder. I. Prevalence, impact of medications, and disparities in health care. World Psychiatry. 2011;10(1):52-77.
3. Roger VL, Go AS, Lloyd-Jones DM, et al; American Heart Association Statistics Committee and Stroke Statistics Subcommittee. Heart disease and stroke statistics update-2011 update. Circulation. 2011;123(4):e18-e209. doi: 10.1161/CIR.0b013e3182009701.
4. Rosenberg SD, Goodman LA, Osher FC, et al. Prevalence of HIV, hepatitis B, and hepatitis C in people with severe mental illness. Am J Public Health. 2001;91(1):31-37.
5. Lovre D, Mauvais-Jarvis F. Trends in prevalence of the metabolic syndrome. JAMA. 2015;314(9):950.
6. Hennekens CH, Hennekens AR, Hollar D, et al. Schizophrenia and increased risks of cardiovascular disease. Am Heart J. 2005;150(6):1115-1121.
7. Bushe CJ, Taylor M, Haukka J. Mortality in schizophrenia: a measurable clinical point. J Psychopharmacol. 2010;24(suppl 4):17-25.
8. Nasrallah HA, Meyer JM, Goff DC, et al. Low rates of treatment for hypertension, dyslipidemia and diabetes in schizophrenia: data from the CATIE schizophrenia trial sample at baseline. Schizophr Res. 2006;86(1-3):15-22.
9. Allison DB, Fontaine KR, Heo M et al. The distribution of body mass index among individuals with and without schizophrenia. J Clin Psychiatry. 1999;60(4):215-220.
10. Allison DB, Mentore JL, Heo M, et al. Antipsychotic-induced weight gain: a comprehensive research synthesis. Am J Psychiatry. 1999;156(11):1686-1696.
11. Jarskog LF, Hamer RM, Catellier DJ, et al; METS Investigators. Metformin for weight loss and metabolic control in overweight outpatients with schizophrenia and schizoaffective disorder. Am J Psychiatry. 2013;170(9):1032-1040.
12. Ganguli R. Behavioral therapy for weight loss in patients with schizophrenia. J Clin Psychiatry. 2007;68(suppl 4):19-25.
13. Kohen D. Diabetes mellitus and schizophrenia: historical perspective. Br J Psychiatry Suppl. 2004;47:S64-S66.
14. Ryan MC, Flanagan S, Kinsella U, et al. The effects of atypical antipsychotics on visceral fat distribution in first episode, drug naïve patients with schizophrenia. Life Sci. 2004;74(16):1999-2008.
15. McEvoy JP, Meyer JM, Goff DC, et al. Prevalence of the metabolic syndrome in patients with schizophrenia: baseline results from the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) schizophrenia trial and comparison with national estimates from NHANES III. Schizophr Res. 2005;80(1):19-32.
16. Barnett AH, Mackin P, Chaudhry I, et al. Minimising metabolic and cardiovascular risk in schizophrenia: diabetes, obesity and dyslipidaemia. J Psychopharmacol. 2007;21(4):357-373.
17. Meyer JM, Koro CE. The effects of antipsychotic therapy on serum lipids: a comprehensive review. Schizophr Res. 2004;70(1):1-17.
18. Sacks FM. Metabolic syndrome: epidemiology and consequences. J Clin Psychiatry. 2004;65(suppl 18):3-12.
19. De Hert M, Schreurs V, Vancampfort D, et al. Metabolic syndrome in people with schizophrenia: a review. World Psychiatry. 2009;8(1):15-22.
20. De Hert M, Hanssens L, Wampers M, et al. Prevalence and incidence rates of metabolic abnormalities and diabetes in a prospective study of patients treated with second-generation antipsychotics. Schizophr Bull. 2007;33:560.
21. Huckans M, Mitchell A, Pavawalla S, et al. The influence of antiviral therapy on psychiatric symptoms among patients with hepatitis C and schizophrenia. Antivir Ther. 2010;15(1):111-119.
22. Davidson S, Judd F, Jolley D, et al. Risk factors for HIV/AIDS and hepatitis C among the chronic mentally ill. Aust N Z J Psychiatry. 2001;35(2):203-209.
23. Copeland LA, Mortensen EM, Zeber JE, et al. Pulmonary disease among inpatient decendents: impact of schizophrenia. Prog Neuropsychopharmacol Biol Psychiatry. 2007;31(3):720-726.
24. Dickerson F, Stallings CR, Origoni AE, et al. Cigarette smoking among persons with schizophrenia or bipolar disorder in routine clinical settings, 1999-2011. Psychiatr Serv. 2013;64(1):44-50.
25. Dalack GW, Healy DJ, Meador-Woodruff JH. Nicotine dependence in schizophrenia: clinical phenomena and laboratory findings. Am J Psychiatry. 1998;155(11):1490-1501.
26. Hodgson R, Wildgust HJ, Bushe CJ. Cancer and schizophrenia: is there a paradox? J Psychopharmacol. 2010;24(suppl 4):51-60.
27. Hippisley-Cox J, Vinogradova Y, Coupland C, et al. Risk of malignancy in patients with schizophrenia or bipolar disorder: nested case-control study. Arch Gen Psychiatry. 2007;64(12):1368-1376.
28. Grinshpoon A, Barchana M, Ponizovsky A, et al. Cancer in schizophrenia: is the risk higher or lower? Schizophr Res. 2005;73(2-3):333-341.
29. Hwang M, Farasatpour M, Williams CD, et al. Adjuvant chemotherapy for breast cancer patients with schizophrenia. Oncol Lett. 2012;3(4):845-850.
Life expectancy for both males and females has been increasing over the past several decades to an average of 76 years. However, the life expectancy among individuals with schizophrenia in the United States is 61 years—a 20% reduction.1 Patients with schizophrenia are known to be at increased risk of several comorbid medical conditions, such as type 2 diabetes mellitus (T2DM), coronary artery disease, and digestive and liver disorders, compared with healthy people (Figure, page 32).2-5 This risk may be heightened by several factors, including sedentary lifestyle, a high rate of cigarette use, poor self-management skills, homelessness, and poor diet.
Although substantial attention is paid to the psychiatric and behavioral management of schizophrenia, many barriers impede the detection and treatment of patients’ medical conditions, which have been implicated in excess unforeseen deaths. Patients with schizophrenia might experience delays in diagnosis, leading to more acute comorbidity at time of diagnosis and premature mortality
Cardiovascular disease is the leading cause of death among psychiatric patients.6 Key risk factors for cardiovascular disease include smoking, obesity, hypertension, dyslipidemia, diabetes, and lack of physical activity, all of which are more prevalent among patients with schizophrenia.7 In addition, antipsychotics are associated with adverse metabolic effects.8 In general, smoking and obesity are the most modifiable and preventable risk factors for many medical conditions, such as cardiovascular disease, hyperlipidemia, diabetes, and many forms of cancer (Table 1).
In this article, we discuss how to manage common medical comorbidities in patients with schizophrenia. Comprehensive management for all these medical conditions in this population is beyond the scope of this article; we limit ourselves to discussing (1) how common these conditions are in patients with schizophrenia compared with the general population and (2) what can be done in psychiatric practice to manage these medical comorbidities (Box).
Obesity
Obesity—defined as body mass index (BMI) of >30—is common among patients with schizophrenia. The condition leads to poor self-image, decreased treatment adherence, and an increased risk of many chronic medical conditions (Table 1). Being overweight or obese can increase stigma and social discrimination, which will undermine self-esteem and, in turn, affect adherence with medications, leading to relapse.
The prevalence of obesity among patients with schizophrenia is almost double that of the general population9 (Figure2-5). Several factors predispose these patients to overweight or obese, including sedentary lifestyle, lack of exercise, a high-fat diet, medications side effects, and genetic factors. Recent studies report the incidence of weight gain among patients treated with antipsychotics is as high as 80%10 (Table 2).
Mechanisms involved in antipsychotic-induced weight gain are not completely understood, but antagonism of serotonergic (5-HT2C, 5-HT1A), histamine (H1), dopamine (D2), muscarinic, and other receptors are involved in modulation of food intake. Decreased energy expenditure also has been blamed for antipsychotic-induced weight gain.10
Pharmacotherapy and bariatric surgery can be as effective among patients with schizophrenia as they are among the general population. Maintaining a BMI of <25 kg/m2 lowers the risk of cardiovascular disease by 35% to 55%.6 Metformin has modest potential for offsetting weight gain and providing some metabolic control in overweight outpatients with schizophrenia,11 and should be considered early when treating at-risk patients.
Managing obesity. Clinicians can apply several measures to manage obesity in a patient with schizophrenia:
- Educate the patient, and the family, about the risks of being overweight or obese.
- Monitor weight and BMI at each visit.
- Advise smoking cessation.
- When clinically appropriate, switch to an antipsychotic with a lower risk of weight gain—eg, from olanzapine or high-dose quetiapine to a high- or medium-potency typical antipsychotic (eg, haloperidol, perphenazine), ziprasidone, aripiprazole, iloperidone, and lurasidone (Table 2, page 36).
- Consider prophylactic use of metformin with an antipsychotic; the drug has modest potential for offsetting weight gain and providing better metabolic control in an overweight patient with schizophrenia.11
- Encourage the patient to engage in modest physical activity; for example, a 20-minute walk, every day, reduces the risk of cardiovascular disease by 35% to 55%.6
- Recommend a formal lifestyle modification program, such as behavioral group-based treatment for weight reduction.12
- Refer the patient and family to a dietitian.
Type 2 diabetes mellitus
There is strong association between T2DM and schizophrenia that is related to abnormal glucose regulation independent of any adverse medication effect.13 Ryan et al14 reported that first-episode, drug-naïve patients with schizophrenia had a higher level of intra-abdominal fat than age- and BMI-matched healthy controls, suggesting that schizophrenia could be associated with changes in adiposity that might increase the risk of insulin resistance, hyperlipidemia, and dyslipidemia. Mechanisms that increase the risk of T2DM in schizophrenia include genetic and environmental factors, such as family history, lack of physical activity, and poor diet.
Diagnosis. All patients with schizophrenia should be evaluated for undiagnosed diabetes. The diagnosis of T2DM is made by documenting:
- a fasting plasma glucose reading of ≥126 mg/dL
- symptoms of T2DM, along with a random plasma glucose reading of ≥200 mg/dL
- 2-hour reading of a plasma glucose level >200 mg/dL on an oral glucose tolerance test.
Recent guidelines also suggest using a hemoglobin A1c value cutoff of ≥6.5% to diagnose T2DM.
In the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) study, 38% of patients with schizophrenia and diabetes were not receiving any treatment for T2DM.15
Risk factors for T2DM are:
- BMI >25
- a first-degree relative with diabetes
- lack of physical activity
- being a member of a high-risk ethnic group (African American, Hispanic American, Native American, Asian American, or Pacific Islander)
- having delivered a baby >9 lb or having had gestational diabetes
- hypertension
- high-density lipoprotein (HDL) cholesterol level of ≤35 mg/dL
- triglyceride level of ≥250 mg/dL
- history of an abnormal glucose tolerance test
- history of abnormal findings on a fasting plasma glucose test
- history of vascular disease.
Early detection and management.
- Educate the patient and family about signs and symptoms of T2DM, such as polyuria, nocturia, polydipsia, fatigue, visual disturbances, and (in women) vulvitis. Also, psychiatrists should be aware of, and inquire about, symptoms of diabetic ketoacidosis.
- At the start of therapy with any antipsychotic, particularly a second-generation antipsychotic (SGA), ask patients about a family history of diabetes and measure the hemoglobin A1c value.
- Monitor the hemoglobin A1c level 4 months after starting an antipsychotic, then annually, in a patient with significant risk factors for diabetes.
- Monitor blood glucose every 6 months in patients with no change from initial results and more frequently in those with significant risk factors for diabetes and those who gain weight.
- Order a lipid panel and measure the serum glucose level to rule out dyslipidemia and diabetes, because a patient with high lipid levels and diabetes is at higher risk of developing cardiovascular conditions.
- Advocate for smoking cessation.
- Switch to an antipsychotic with a lower risk of diabetes when clinically appropriate, such as switching a patient from olanzapine or high-dose quetiapine to a high- or medium-potency typical antipsychotic (such as haloperidol or perphenazine), ziprasidone, aripiprazole, iloperidone, and lurasidone (Table 2).
- Consider prophylactic use of metformin along with antipsychotics. Metformin has been used to improve insulin sensitivity and can lead to weight loss in diabetic and non-diabetic patients. The drug has modest potential for offsetting weight gain and providing better metabolic control in overweight outpatients with schizophrenia.11 Metformin is simple to use, does not lead to hypoglycemia, does not require serum glucose monitoring, and has a favorable safety profile.11
- Educate the patient about modest physical activity. For example, a 20-minute walk every day reduces the risk of cardiovascular disease by 35% to 55%.6
- Refer the patient to a dietitian to develop an appropriate diet plan.
- When diabetes is diagnosed, ensure appropriate follow-up and initiation or continuation of therapy with a general practitioner or an endocrinologist.
- Reinforce the need for ongoing follow-up and compliance with therapy for diabetes.
Hyperlipidemia and dyslipidemia
Elevated cholesterol and triglyceride levels are associated with cardiovascular diseases, such as ischemic heart disease and myocardial infarction. A 10% increase in cholesterol levels is associated with a 20% to 30% increase in the risk of coronary artery disease; lowering cholesterol by 10% decreases the risk by 20% to 30%.16 Triglyceride levels ≥250 mg/dL are associated with 2-fold higher risk of cardiovascular disease.16
The incidence of dyslipidemia is not as well studied as diabetes in patients with schizophrenia. There is increased prevalence of dyslipidemia in patients with schizophrenia compared with the general population because of obesity, lack of physical activity, and poor dietary habits.16
Data regarding the effects of first-generation antipsychotics (FGAs) on lipid levels are limited, but high-potency drugs, such as haloperidol, seem to carry a lower risk of hyperlipidemia than low-potency drugs, such as chlorpromazine and thioridazine.17 A comprehensive review on the effects of SGAs on plasma lipid levels suggested that clozapine, olanzapine, and quetiapine are associated with a higher risk of dyslipidemia17 (Table 2).
In the CATIE study, olanzapine and clozapine were associated with a greater increase in the serum level of cholesterol and triglycerides compared with other antipsychotics, even after adjusting for treatment duration. Furthermore, a retrospective chart review of patients who switched to aripiprazole from other SGAs showed a decrease in levels of total cholesterol and low-density lipoprotein cholesterol15 (Table 2).
Patients with schizophrenia are more likely to have dyslipidemia go undiagnosed, and therefore are less likely to be treated for the disorder. In the CATIE study, 88% of patients with dyslipidemia were not receiving any treatment.15
Management for dyslipidemia.
- Educate the patient and family about risks involved with dyslipidemia.
- Monitor weight and BMI at each visit.
- Monitor lipids to rule out dyslipidemia. Obtain a pretreatment fasting or random lipid profile for any patient receiving an antipsychotic; repeat at least every 6 months after starting the antipsychotic.
- Counsel the patient to quit smoking.
- Switch to an antipsychotic with lower risk of weight gain and dyslipidemia, such as switching from olanzapine or high-dose quetiapine to high- or medium-potency typical antipsychotics (such as, haloperidol or perphenazine), ziprasidone, aripiprazole, iloperidone, and lurasidone (Table 2).
- Educate and encourage the patient about modest physical activity. For example, a 20-minute walk everyday will reduce cardiovascular disease risk by 35% to 55%.6
- Refer to a dietitian if indicated.
- Ensure follow-up and initiation of treatment with a general practitioner.
- Educate and encourage the patient about modest physical activity. For example, a 20-minute walk everyday will reduce cardiovascular disease risk by 35% to 55%.
Metabolic syndrome
Metabolic syndrome is cluster of cardiovascular risk factors, including central adiposity, hyperglycemia, dyslipidemia, and hypertension. The National Cholesterol Education Program’s Adult Treatment Panel III report defines metabolic syndrome as the presence of 3 of 5 of the following factors:
- abdominal obesity (waist circumference of >40 inches in men, or >35 inches in women)
- triglyceride level, >150 mg/dL
- HDL cholesterol, <40 mg/dL in men and <50 mg/dL in women
- blood pressure, >130/85 mm Hg
- fasting plasma glucose level, >110 mg/dL.
The presence of metabolic syndrome in the general population is a strong predictor of cardiovascular diseases and diabetes.18 The adverse effects of metabolic syndrome are thought to relate to atherogenic dyslipidemia, higher blood pressure, insulin resistance with or without glucose intolerance, a proinflammatory state, and a prothrombotic state.
The prevalence of metabolic syndrome in patients with schizophrenia is 2- to 3-fold higher than the general population.19 In the CATIE study, approximately one-third of patients met criteria for metabolic syndrome at baseline.15 In a prospective study, De Hert et al20 reported that patients who were started on a SGA had more than twice the rate of developing metabolic syndrome compared with those treated with a FGA (Table 2). Other possible causes of metabolic syndrome are visceral adiposity and insulin resistance.16Management of the metabolic syndrome involves addressing the individual components that have been described in the preceding sections on T2DM and dyslipidemia.
Hepatitis C
Hepatitis C virus (HCV) infection is thought to be the most common blood-borne illness, with an estimated prevalence of 1% of the U.S. population. Some studies suggest that as many as 16% of people with schizophrenia have HCV infection.4 Risk factors for HCV infection include unsafe sexual practices, prostitution, homosexuality, homelessness, and IV drug use.
HCV treatments typically have involved regimens with interferon alfa, which is associated with significant neuropsychiatric side effects, including depression and suicide. There is a dearth of research on treatment of HCV in patients with schizophrenia; however, at least 1 study suggests that there was no increase in psychiatric symptoms in patients treated with interferon-containing regimens.21 There is even less evidence to guide the use of newer, non-interferon–based HCV treatment regimens that are better tolerated and have a higher response rate in the general population; there is reason, however, to be hopeful about their potential in patients with schizophrenia and HCV infection.
Managing HCV infection.
- Educate the patients and family about risk factors associated with contracting HCV.
- Screen for HCV infection in patients with schizophrenia because there is higher prevalence of HCV in these patients compared with the general population.
- When HCV infection is diagnosed, educate the patients and family about available treatments.
- Facilitate referral to an HCV specialist for appropriate treatment.
HIV/AIDS
HIV infection is highly prevalent among people suffering from severe mental illness such as schizophrenia. The incidence of HIV/AIDS in patients with schizophrenia is estimated to be 4% to 23%, compared with 0.6% in the general population.22 Risk factors associated with a higher incidence of HIV/AIDS in patients with schizophrenia are lack of knowledge about contracting HIV, unsafe sexual practices, prostitution, homosexuality, homelessness, and IV drug use.22
Managing HIV/AIDS.
- Educate the patient and family about risk factors associated with contracting HIV/AIDS.
- Educate patients about safe sex practices.
- All patients with schizophrenia should be screened for HIV because there is 10-fold higher HIV prevalence in schizophrenia compared with the general population.
- When HIV infection is diagnosed, facilitate referral to a HIV or infectious disease specialist for treatment.
- Educate the patient in whom HIV/AIDS has been diagnosed about the importance of (1) adherence to his (her) HIV medication regimen and (2) follow-up visits with an infectious disease practitioner and appropriate laboratory tests.
- Educate the patient’s family and significant other about the illness.
- Screen for and treat substance use.
- At each visit, inquire about the patient’s adherence to HIV medical therapy, viral load, and CD4 cell count.
Chronic obstructive pulmonary disease
Patients with schizophrenia are more likely to suffer from respiratory disease, such as chronic obstructive pulmonary disease (COPD) and asthma, compared with the general population.23 Smoking is a major risk factor for COPD. In a study by Dickerson et al,24 64% of people with schizophrenia were current smokers, compared with 19% of those without mental illness.
A high rate of smoking rate among people with schizophrenia suggests a “self-medication” hypothesis: That is, stimulation of CNS nicotinic cholinergic receptors treats the negative symptoms of schizophrenia and overcomes the dopamine blocking effects of antipsychotics.25 Among SGAs, only clozapine has a substantial body of evidence to support its association with decreased smoking behavior.
Managing COPD.
- Educate the patient and family about risk factors associated with COPD and smoking.
- Screen for tobacco use at each visit; try to increase motivation to quit smoking.
- Educate the patients and family about the value and availability of smoking cessation programs.
- Prescribe medication to help with smoking cessation when needed. Bupropion and varenicline have been shown to be effective in patients with schizophrenia; nicotine replacement therapies are safe and can be helpful.
- When treating a patient who is in the process of quitting, encourage and help him to maintain his commitment and enlist support from his family.
- Refer to an appropriate medical provider (primary care provider or pulmonologist) for a patient with an established or suspected diagnosis of COPD.
Cancer
Since 1909, when the Board of Control of the Commissioners in Lunacy for England and Wales noted the possibility of a decreased incidence in cancer among psychiatric patients, this connection has been a matter of controversy.26 Subsequent research has been equivocal; the prevalence of cancer has been reported to be either increased, similar, or decreased compared with the general population.26-28 Risk factors for cancer, including smoking, obesity, poor diet, sedentary lifestyle, and hyperprolactinemia, are more common among patients with schizophrenia.
Genetic factors and a possible protective effect from antipsychotics have been cited as potential causes of decreased prevalence. Clozapine is associated with an increased risk of leukemia. No conclusion can be drawn about the overall prevalence of cancer in schizophrenia.
Managing cancer in a patient with schizophrenia, however, poses a significant challenge29; he might lack capacity to make decisions about cancer treatment. The patient—or his surrogate decision-makers—need to carefully weigh current quality of life against potential benefits of treatment and risks of side effects. Adherence to complex, often toxic, therapies can be challenging for the patient with psychosis. Successful cancer treatment often requires close collaboration between the cancer treatment team and the patient’s support system, including the treating psychiatrist and case management teams.
Bottom Line
Patients with schizophrenia are at higher risk of developing comorbid medical
conditions because of the illness itself, lifestyle behaviors, genetics, and adverse
effects of medications. Because mental health clinicians focus attention on the
psychiatric and behavioral aspect of treatment, often there is delay in screening,
detecting, and treating medical comorbidities. This screening can be done in any
psychiatric practice, which can lead to timely management for those conditions
and preventing premature mortality in patients with schizophrenia.
Life expectancy for both males and females has been increasing over the past several decades to an average of 76 years. However, the life expectancy among individuals with schizophrenia in the United States is 61 years—a 20% reduction.1 Patients with schizophrenia are known to be at increased risk of several comorbid medical conditions, such as type 2 diabetes mellitus (T2DM), coronary artery disease, and digestive and liver disorders, compared with healthy people (Figure, page 32).2-5 This risk may be heightened by several factors, including sedentary lifestyle, a high rate of cigarette use, poor self-management skills, homelessness, and poor diet.
Although substantial attention is paid to the psychiatric and behavioral management of schizophrenia, many barriers impede the detection and treatment of patients’ medical conditions, which have been implicated in excess unforeseen deaths. Patients with schizophrenia might experience delays in diagnosis, leading to more acute comorbidity at time of diagnosis and premature mortality
Cardiovascular disease is the leading cause of death among psychiatric patients.6 Key risk factors for cardiovascular disease include smoking, obesity, hypertension, dyslipidemia, diabetes, and lack of physical activity, all of which are more prevalent among patients with schizophrenia.7 In addition, antipsychotics are associated with adverse metabolic effects.8 In general, smoking and obesity are the most modifiable and preventable risk factors for many medical conditions, such as cardiovascular disease, hyperlipidemia, diabetes, and many forms of cancer (Table 1).
In this article, we discuss how to manage common medical comorbidities in patients with schizophrenia. Comprehensive management for all these medical conditions in this population is beyond the scope of this article; we limit ourselves to discussing (1) how common these conditions are in patients with schizophrenia compared with the general population and (2) what can be done in psychiatric practice to manage these medical comorbidities (Box).
Obesity
Obesity—defined as body mass index (BMI) of >30—is common among patients with schizophrenia. The condition leads to poor self-image, decreased treatment adherence, and an increased risk of many chronic medical conditions (Table 1). Being overweight or obese can increase stigma and social discrimination, which will undermine self-esteem and, in turn, affect adherence with medications, leading to relapse.
The prevalence of obesity among patients with schizophrenia is almost double that of the general population9 (Figure2-5). Several factors predispose these patients to overweight or obese, including sedentary lifestyle, lack of exercise, a high-fat diet, medications side effects, and genetic factors. Recent studies report the incidence of weight gain among patients treated with antipsychotics is as high as 80%10 (Table 2).
Mechanisms involved in antipsychotic-induced weight gain are not completely understood, but antagonism of serotonergic (5-HT2C, 5-HT1A), histamine (H1), dopamine (D2), muscarinic, and other receptors are involved in modulation of food intake. Decreased energy expenditure also has been blamed for antipsychotic-induced weight gain.10
Pharmacotherapy and bariatric surgery can be as effective among patients with schizophrenia as they are among the general population. Maintaining a BMI of <25 kg/m2 lowers the risk of cardiovascular disease by 35% to 55%.6 Metformin has modest potential for offsetting weight gain and providing some metabolic control in overweight outpatients with schizophrenia,11 and should be considered early when treating at-risk patients.
Managing obesity. Clinicians can apply several measures to manage obesity in a patient with schizophrenia:
- Educate the patient, and the family, about the risks of being overweight or obese.
- Monitor weight and BMI at each visit.
- Advise smoking cessation.
- When clinically appropriate, switch to an antipsychotic with a lower risk of weight gain—eg, from olanzapine or high-dose quetiapine to a high- or medium-potency typical antipsychotic (eg, haloperidol, perphenazine), ziprasidone, aripiprazole, iloperidone, and lurasidone (Table 2, page 36).
- Consider prophylactic use of metformin with an antipsychotic; the drug has modest potential for offsetting weight gain and providing better metabolic control in an overweight patient with schizophrenia.11
- Encourage the patient to engage in modest physical activity; for example, a 20-minute walk, every day, reduces the risk of cardiovascular disease by 35% to 55%.6
- Recommend a formal lifestyle modification program, such as behavioral group-based treatment for weight reduction.12
- Refer the patient and family to a dietitian.
Type 2 diabetes mellitus
There is strong association between T2DM and schizophrenia that is related to abnormal glucose regulation independent of any adverse medication effect.13 Ryan et al14 reported that first-episode, drug-naïve patients with schizophrenia had a higher level of intra-abdominal fat than age- and BMI-matched healthy controls, suggesting that schizophrenia could be associated with changes in adiposity that might increase the risk of insulin resistance, hyperlipidemia, and dyslipidemia. Mechanisms that increase the risk of T2DM in schizophrenia include genetic and environmental factors, such as family history, lack of physical activity, and poor diet.
Diagnosis. All patients with schizophrenia should be evaluated for undiagnosed diabetes. The diagnosis of T2DM is made by documenting:
- a fasting plasma glucose reading of ≥126 mg/dL
- symptoms of T2DM, along with a random plasma glucose reading of ≥200 mg/dL
- 2-hour reading of a plasma glucose level >200 mg/dL on an oral glucose tolerance test.
Recent guidelines also suggest using a hemoglobin A1c value cutoff of ≥6.5% to diagnose T2DM.
In the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) study, 38% of patients with schizophrenia and diabetes were not receiving any treatment for T2DM.15
Risk factors for T2DM are:
- BMI >25
- a first-degree relative with diabetes
- lack of physical activity
- being a member of a high-risk ethnic group (African American, Hispanic American, Native American, Asian American, or Pacific Islander)
- having delivered a baby >9 lb or having had gestational diabetes
- hypertension
- high-density lipoprotein (HDL) cholesterol level of ≤35 mg/dL
- triglyceride level of ≥250 mg/dL
- history of an abnormal glucose tolerance test
- history of abnormal findings on a fasting plasma glucose test
- history of vascular disease.
Early detection and management.
- Educate the patient and family about signs and symptoms of T2DM, such as polyuria, nocturia, polydipsia, fatigue, visual disturbances, and (in women) vulvitis. Also, psychiatrists should be aware of, and inquire about, symptoms of diabetic ketoacidosis.
- At the start of therapy with any antipsychotic, particularly a second-generation antipsychotic (SGA), ask patients about a family history of diabetes and measure the hemoglobin A1c value.
- Monitor the hemoglobin A1c level 4 months after starting an antipsychotic, then annually, in a patient with significant risk factors for diabetes.
- Monitor blood glucose every 6 months in patients with no change from initial results and more frequently in those with significant risk factors for diabetes and those who gain weight.
- Order a lipid panel and measure the serum glucose level to rule out dyslipidemia and diabetes, because a patient with high lipid levels and diabetes is at higher risk of developing cardiovascular conditions.
- Advocate for smoking cessation.
- Switch to an antipsychotic with a lower risk of diabetes when clinically appropriate, such as switching a patient from olanzapine or high-dose quetiapine to a high- or medium-potency typical antipsychotic (such as haloperidol or perphenazine), ziprasidone, aripiprazole, iloperidone, and lurasidone (Table 2).
- Consider prophylactic use of metformin along with antipsychotics. Metformin has been used to improve insulin sensitivity and can lead to weight loss in diabetic and non-diabetic patients. The drug has modest potential for offsetting weight gain and providing better metabolic control in overweight outpatients with schizophrenia.11 Metformin is simple to use, does not lead to hypoglycemia, does not require serum glucose monitoring, and has a favorable safety profile.11
- Educate the patient about modest physical activity. For example, a 20-minute walk every day reduces the risk of cardiovascular disease by 35% to 55%.6
- Refer the patient to a dietitian to develop an appropriate diet plan.
- When diabetes is diagnosed, ensure appropriate follow-up and initiation or continuation of therapy with a general practitioner or an endocrinologist.
- Reinforce the need for ongoing follow-up and compliance with therapy for diabetes.
Hyperlipidemia and dyslipidemia
Elevated cholesterol and triglyceride levels are associated with cardiovascular diseases, such as ischemic heart disease and myocardial infarction. A 10% increase in cholesterol levels is associated with a 20% to 30% increase in the risk of coronary artery disease; lowering cholesterol by 10% decreases the risk by 20% to 30%.16 Triglyceride levels ≥250 mg/dL are associated with 2-fold higher risk of cardiovascular disease.16
The incidence of dyslipidemia is not as well studied as diabetes in patients with schizophrenia. There is increased prevalence of dyslipidemia in patients with schizophrenia compared with the general population because of obesity, lack of physical activity, and poor dietary habits.16
Data regarding the effects of first-generation antipsychotics (FGAs) on lipid levels are limited, but high-potency drugs, such as haloperidol, seem to carry a lower risk of hyperlipidemia than low-potency drugs, such as chlorpromazine and thioridazine.17 A comprehensive review on the effects of SGAs on plasma lipid levels suggested that clozapine, olanzapine, and quetiapine are associated with a higher risk of dyslipidemia17 (Table 2).
In the CATIE study, olanzapine and clozapine were associated with a greater increase in the serum level of cholesterol and triglycerides compared with other antipsychotics, even after adjusting for treatment duration. Furthermore, a retrospective chart review of patients who switched to aripiprazole from other SGAs showed a decrease in levels of total cholesterol and low-density lipoprotein cholesterol15 (Table 2).
Patients with schizophrenia are more likely to have dyslipidemia go undiagnosed, and therefore are less likely to be treated for the disorder. In the CATIE study, 88% of patients with dyslipidemia were not receiving any treatment.15
Management for dyslipidemia.
- Educate the patient and family about risks involved with dyslipidemia.
- Monitor weight and BMI at each visit.
- Monitor lipids to rule out dyslipidemia. Obtain a pretreatment fasting or random lipid profile for any patient receiving an antipsychotic; repeat at least every 6 months after starting the antipsychotic.
- Counsel the patient to quit smoking.
- Switch to an antipsychotic with lower risk of weight gain and dyslipidemia, such as switching from olanzapine or high-dose quetiapine to high- or medium-potency typical antipsychotics (such as, haloperidol or perphenazine), ziprasidone, aripiprazole, iloperidone, and lurasidone (Table 2).
- Educate and encourage the patient about modest physical activity. For example, a 20-minute walk everyday will reduce cardiovascular disease risk by 35% to 55%.6
- Refer to a dietitian if indicated.
- Ensure follow-up and initiation of treatment with a general practitioner.
- Educate and encourage the patient about modest physical activity. For example, a 20-minute walk everyday will reduce cardiovascular disease risk by 35% to 55%.
Metabolic syndrome
Metabolic syndrome is cluster of cardiovascular risk factors, including central adiposity, hyperglycemia, dyslipidemia, and hypertension. The National Cholesterol Education Program’s Adult Treatment Panel III report defines metabolic syndrome as the presence of 3 of 5 of the following factors:
- abdominal obesity (waist circumference of >40 inches in men, or >35 inches in women)
- triglyceride level, >150 mg/dL
- HDL cholesterol, <40 mg/dL in men and <50 mg/dL in women
- blood pressure, >130/85 mm Hg
- fasting plasma glucose level, >110 mg/dL.
The presence of metabolic syndrome in the general population is a strong predictor of cardiovascular diseases and diabetes.18 The adverse effects of metabolic syndrome are thought to relate to atherogenic dyslipidemia, higher blood pressure, insulin resistance with or without glucose intolerance, a proinflammatory state, and a prothrombotic state.
The prevalence of metabolic syndrome in patients with schizophrenia is 2- to 3-fold higher than the general population.19 In the CATIE study, approximately one-third of patients met criteria for metabolic syndrome at baseline.15 In a prospective study, De Hert et al20 reported that patients who were started on a SGA had more than twice the rate of developing metabolic syndrome compared with those treated with a FGA (Table 2). Other possible causes of metabolic syndrome are visceral adiposity and insulin resistance.16Management of the metabolic syndrome involves addressing the individual components that have been described in the preceding sections on T2DM and dyslipidemia.
Hepatitis C
Hepatitis C virus (HCV) infection is thought to be the most common blood-borne illness, with an estimated prevalence of 1% of the U.S. population. Some studies suggest that as many as 16% of people with schizophrenia have HCV infection.4 Risk factors for HCV infection include unsafe sexual practices, prostitution, homosexuality, homelessness, and IV drug use.
HCV treatments typically have involved regimens with interferon alfa, which is associated with significant neuropsychiatric side effects, including depression and suicide. There is a dearth of research on treatment of HCV in patients with schizophrenia; however, at least 1 study suggests that there was no increase in psychiatric symptoms in patients treated with interferon-containing regimens.21 There is even less evidence to guide the use of newer, non-interferon–based HCV treatment regimens that are better tolerated and have a higher response rate in the general population; there is reason, however, to be hopeful about their potential in patients with schizophrenia and HCV infection.
Managing HCV infection.
- Educate the patients and family about risk factors associated with contracting HCV.
- Screen for HCV infection in patients with schizophrenia because there is higher prevalence of HCV in these patients compared with the general population.
- When HCV infection is diagnosed, educate the patients and family about available treatments.
- Facilitate referral to an HCV specialist for appropriate treatment.
HIV/AIDS
HIV infection is highly prevalent among people suffering from severe mental illness such as schizophrenia. The incidence of HIV/AIDS in patients with schizophrenia is estimated to be 4% to 23%, compared with 0.6% in the general population.22 Risk factors associated with a higher incidence of HIV/AIDS in patients with schizophrenia are lack of knowledge about contracting HIV, unsafe sexual practices, prostitution, homosexuality, homelessness, and IV drug use.22
Managing HIV/AIDS.
- Educate the patient and family about risk factors associated with contracting HIV/AIDS.
- Educate patients about safe sex practices.
- All patients with schizophrenia should be screened for HIV because there is 10-fold higher HIV prevalence in schizophrenia compared with the general population.
- When HIV infection is diagnosed, facilitate referral to a HIV or infectious disease specialist for treatment.
- Educate the patient in whom HIV/AIDS has been diagnosed about the importance of (1) adherence to his (her) HIV medication regimen and (2) follow-up visits with an infectious disease practitioner and appropriate laboratory tests.
- Educate the patient’s family and significant other about the illness.
- Screen for and treat substance use.
- At each visit, inquire about the patient’s adherence to HIV medical therapy, viral load, and CD4 cell count.
Chronic obstructive pulmonary disease
Patients with schizophrenia are more likely to suffer from respiratory disease, such as chronic obstructive pulmonary disease (COPD) and asthma, compared with the general population.23 Smoking is a major risk factor for COPD. In a study by Dickerson et al,24 64% of people with schizophrenia were current smokers, compared with 19% of those without mental illness.
A high rate of smoking rate among people with schizophrenia suggests a “self-medication” hypothesis: That is, stimulation of CNS nicotinic cholinergic receptors treats the negative symptoms of schizophrenia and overcomes the dopamine blocking effects of antipsychotics.25 Among SGAs, only clozapine has a substantial body of evidence to support its association with decreased smoking behavior.
Managing COPD.
- Educate the patient and family about risk factors associated with COPD and smoking.
- Screen for tobacco use at each visit; try to increase motivation to quit smoking.
- Educate the patients and family about the value and availability of smoking cessation programs.
- Prescribe medication to help with smoking cessation when needed. Bupropion and varenicline have been shown to be effective in patients with schizophrenia; nicotine replacement therapies are safe and can be helpful.
- When treating a patient who is in the process of quitting, encourage and help him to maintain his commitment and enlist support from his family.
- Refer to an appropriate medical provider (primary care provider or pulmonologist) for a patient with an established or suspected diagnosis of COPD.
Cancer
Since 1909, when the Board of Control of the Commissioners in Lunacy for England and Wales noted the possibility of a decreased incidence in cancer among psychiatric patients, this connection has been a matter of controversy.26 Subsequent research has been equivocal; the prevalence of cancer has been reported to be either increased, similar, or decreased compared with the general population.26-28 Risk factors for cancer, including smoking, obesity, poor diet, sedentary lifestyle, and hyperprolactinemia, are more common among patients with schizophrenia.
Genetic factors and a possible protective effect from antipsychotics have been cited as potential causes of decreased prevalence. Clozapine is associated with an increased risk of leukemia. No conclusion can be drawn about the overall prevalence of cancer in schizophrenia.
Managing cancer in a patient with schizophrenia, however, poses a significant challenge29; he might lack capacity to make decisions about cancer treatment. The patient—or his surrogate decision-makers—need to carefully weigh current quality of life against potential benefits of treatment and risks of side effects. Adherence to complex, often toxic, therapies can be challenging for the patient with psychosis. Successful cancer treatment often requires close collaboration between the cancer treatment team and the patient’s support system, including the treating psychiatrist and case management teams.
Bottom Line
Patients with schizophrenia are at higher risk of developing comorbid medical
conditions because of the illness itself, lifestyle behaviors, genetics, and adverse
effects of medications. Because mental health clinicians focus attention on the
psychiatric and behavioral aspect of treatment, often there is delay in screening,
detecting, and treating medical comorbidities. This screening can be done in any
psychiatric practice, which can lead to timely management for those conditions
and preventing premature mortality in patients with schizophrenia.
1. Brown S, Inskip H, Barraclough B. Causes of the excess mortality of schizophrenia. Br J Psychiatry. 2000;177:212-217.
2. De Hert M, Correl CU, Bobes J, et al. Physical illness in patients with severe mental disorder. I. Prevalence, impact of medications, and disparities in health care. World Psychiatry. 2011;10(1):52-77.
3. Roger VL, Go AS, Lloyd-Jones DM, et al; American Heart Association Statistics Committee and Stroke Statistics Subcommittee. Heart disease and stroke statistics update-2011 update. Circulation. 2011;123(4):e18-e209. doi: 10.1161/CIR.0b013e3182009701.
4. Rosenberg SD, Goodman LA, Osher FC, et al. Prevalence of HIV, hepatitis B, and hepatitis C in people with severe mental illness. Am J Public Health. 2001;91(1):31-37.
5. Lovre D, Mauvais-Jarvis F. Trends in prevalence of the metabolic syndrome. JAMA. 2015;314(9):950.
6. Hennekens CH, Hennekens AR, Hollar D, et al. Schizophrenia and increased risks of cardiovascular disease. Am Heart J. 2005;150(6):1115-1121.
7. Bushe CJ, Taylor M, Haukka J. Mortality in schizophrenia: a measurable clinical point. J Psychopharmacol. 2010;24(suppl 4):17-25.
8. Nasrallah HA, Meyer JM, Goff DC, et al. Low rates of treatment for hypertension, dyslipidemia and diabetes in schizophrenia: data from the CATIE schizophrenia trial sample at baseline. Schizophr Res. 2006;86(1-3):15-22.
9. Allison DB, Fontaine KR, Heo M et al. The distribution of body mass index among individuals with and without schizophrenia. J Clin Psychiatry. 1999;60(4):215-220.
10. Allison DB, Mentore JL, Heo M, et al. Antipsychotic-induced weight gain: a comprehensive research synthesis. Am J Psychiatry. 1999;156(11):1686-1696.
11. Jarskog LF, Hamer RM, Catellier DJ, et al; METS Investigators. Metformin for weight loss and metabolic control in overweight outpatients with schizophrenia and schizoaffective disorder. Am J Psychiatry. 2013;170(9):1032-1040.
12. Ganguli R. Behavioral therapy for weight loss in patients with schizophrenia. J Clin Psychiatry. 2007;68(suppl 4):19-25.
13. Kohen D. Diabetes mellitus and schizophrenia: historical perspective. Br J Psychiatry Suppl. 2004;47:S64-S66.
14. Ryan MC, Flanagan S, Kinsella U, et al. The effects of atypical antipsychotics on visceral fat distribution in first episode, drug naïve patients with schizophrenia. Life Sci. 2004;74(16):1999-2008.
15. McEvoy JP, Meyer JM, Goff DC, et al. Prevalence of the metabolic syndrome in patients with schizophrenia: baseline results from the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) schizophrenia trial and comparison with national estimates from NHANES III. Schizophr Res. 2005;80(1):19-32.
16. Barnett AH, Mackin P, Chaudhry I, et al. Minimising metabolic and cardiovascular risk in schizophrenia: diabetes, obesity and dyslipidaemia. J Psychopharmacol. 2007;21(4):357-373.
17. Meyer JM, Koro CE. The effects of antipsychotic therapy on serum lipids: a comprehensive review. Schizophr Res. 2004;70(1):1-17.
18. Sacks FM. Metabolic syndrome: epidemiology and consequences. J Clin Psychiatry. 2004;65(suppl 18):3-12.
19. De Hert M, Schreurs V, Vancampfort D, et al. Metabolic syndrome in people with schizophrenia: a review. World Psychiatry. 2009;8(1):15-22.
20. De Hert M, Hanssens L, Wampers M, et al. Prevalence and incidence rates of metabolic abnormalities and diabetes in a prospective study of patients treated with second-generation antipsychotics. Schizophr Bull. 2007;33:560.
21. Huckans M, Mitchell A, Pavawalla S, et al. The influence of antiviral therapy on psychiatric symptoms among patients with hepatitis C and schizophrenia. Antivir Ther. 2010;15(1):111-119.
22. Davidson S, Judd F, Jolley D, et al. Risk factors for HIV/AIDS and hepatitis C among the chronic mentally ill. Aust N Z J Psychiatry. 2001;35(2):203-209.
23. Copeland LA, Mortensen EM, Zeber JE, et al. Pulmonary disease among inpatient decendents: impact of schizophrenia. Prog Neuropsychopharmacol Biol Psychiatry. 2007;31(3):720-726.
24. Dickerson F, Stallings CR, Origoni AE, et al. Cigarette smoking among persons with schizophrenia or bipolar disorder in routine clinical settings, 1999-2011. Psychiatr Serv. 2013;64(1):44-50.
25. Dalack GW, Healy DJ, Meador-Woodruff JH. Nicotine dependence in schizophrenia: clinical phenomena and laboratory findings. Am J Psychiatry. 1998;155(11):1490-1501.
26. Hodgson R, Wildgust HJ, Bushe CJ. Cancer and schizophrenia: is there a paradox? J Psychopharmacol. 2010;24(suppl 4):51-60.
27. Hippisley-Cox J, Vinogradova Y, Coupland C, et al. Risk of malignancy in patients with schizophrenia or bipolar disorder: nested case-control study. Arch Gen Psychiatry. 2007;64(12):1368-1376.
28. Grinshpoon A, Barchana M, Ponizovsky A, et al. Cancer in schizophrenia: is the risk higher or lower? Schizophr Res. 2005;73(2-3):333-341.
29. Hwang M, Farasatpour M, Williams CD, et al. Adjuvant chemotherapy for breast cancer patients with schizophrenia. Oncol Lett. 2012;3(4):845-850.
1. Brown S, Inskip H, Barraclough B. Causes of the excess mortality of schizophrenia. Br J Psychiatry. 2000;177:212-217.
2. De Hert M, Correl CU, Bobes J, et al. Physical illness in patients with severe mental disorder. I. Prevalence, impact of medications, and disparities in health care. World Psychiatry. 2011;10(1):52-77.
3. Roger VL, Go AS, Lloyd-Jones DM, et al; American Heart Association Statistics Committee and Stroke Statistics Subcommittee. Heart disease and stroke statistics update-2011 update. Circulation. 2011;123(4):e18-e209. doi: 10.1161/CIR.0b013e3182009701.
4. Rosenberg SD, Goodman LA, Osher FC, et al. Prevalence of HIV, hepatitis B, and hepatitis C in people with severe mental illness. Am J Public Health. 2001;91(1):31-37.
5. Lovre D, Mauvais-Jarvis F. Trends in prevalence of the metabolic syndrome. JAMA. 2015;314(9):950.
6. Hennekens CH, Hennekens AR, Hollar D, et al. Schizophrenia and increased risks of cardiovascular disease. Am Heart J. 2005;150(6):1115-1121.
7. Bushe CJ, Taylor M, Haukka J. Mortality in schizophrenia: a measurable clinical point. J Psychopharmacol. 2010;24(suppl 4):17-25.
8. Nasrallah HA, Meyer JM, Goff DC, et al. Low rates of treatment for hypertension, dyslipidemia and diabetes in schizophrenia: data from the CATIE schizophrenia trial sample at baseline. Schizophr Res. 2006;86(1-3):15-22.
9. Allison DB, Fontaine KR, Heo M et al. The distribution of body mass index among individuals with and without schizophrenia. J Clin Psychiatry. 1999;60(4):215-220.
10. Allison DB, Mentore JL, Heo M, et al. Antipsychotic-induced weight gain: a comprehensive research synthesis. Am J Psychiatry. 1999;156(11):1686-1696.
11. Jarskog LF, Hamer RM, Catellier DJ, et al; METS Investigators. Metformin for weight loss and metabolic control in overweight outpatients with schizophrenia and schizoaffective disorder. Am J Psychiatry. 2013;170(9):1032-1040.
12. Ganguli R. Behavioral therapy for weight loss in patients with schizophrenia. J Clin Psychiatry. 2007;68(suppl 4):19-25.
13. Kohen D. Diabetes mellitus and schizophrenia: historical perspective. Br J Psychiatry Suppl. 2004;47:S64-S66.
14. Ryan MC, Flanagan S, Kinsella U, et al. The effects of atypical antipsychotics on visceral fat distribution in first episode, drug naïve patients with schizophrenia. Life Sci. 2004;74(16):1999-2008.
15. McEvoy JP, Meyer JM, Goff DC, et al. Prevalence of the metabolic syndrome in patients with schizophrenia: baseline results from the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) schizophrenia trial and comparison with national estimates from NHANES III. Schizophr Res. 2005;80(1):19-32.
16. Barnett AH, Mackin P, Chaudhry I, et al. Minimising metabolic and cardiovascular risk in schizophrenia: diabetes, obesity and dyslipidaemia. J Psychopharmacol. 2007;21(4):357-373.
17. Meyer JM, Koro CE. The effects of antipsychotic therapy on serum lipids: a comprehensive review. Schizophr Res. 2004;70(1):1-17.
18. Sacks FM. Metabolic syndrome: epidemiology and consequences. J Clin Psychiatry. 2004;65(suppl 18):3-12.
19. De Hert M, Schreurs V, Vancampfort D, et al. Metabolic syndrome in people with schizophrenia: a review. World Psychiatry. 2009;8(1):15-22.
20. De Hert M, Hanssens L, Wampers M, et al. Prevalence and incidence rates of metabolic abnormalities and diabetes in a prospective study of patients treated with second-generation antipsychotics. Schizophr Bull. 2007;33:560.
21. Huckans M, Mitchell A, Pavawalla S, et al. The influence of antiviral therapy on psychiatric symptoms among patients with hepatitis C and schizophrenia. Antivir Ther. 2010;15(1):111-119.
22. Davidson S, Judd F, Jolley D, et al. Risk factors for HIV/AIDS and hepatitis C among the chronic mentally ill. Aust N Z J Psychiatry. 2001;35(2):203-209.
23. Copeland LA, Mortensen EM, Zeber JE, et al. Pulmonary disease among inpatient decendents: impact of schizophrenia. Prog Neuropsychopharmacol Biol Psychiatry. 2007;31(3):720-726.
24. Dickerson F, Stallings CR, Origoni AE, et al. Cigarette smoking among persons with schizophrenia or bipolar disorder in routine clinical settings, 1999-2011. Psychiatr Serv. 2013;64(1):44-50.
25. Dalack GW, Healy DJ, Meador-Woodruff JH. Nicotine dependence in schizophrenia: clinical phenomena and laboratory findings. Am J Psychiatry. 1998;155(11):1490-1501.
26. Hodgson R, Wildgust HJ, Bushe CJ. Cancer and schizophrenia: is there a paradox? J Psychopharmacol. 2010;24(suppl 4):51-60.
27. Hippisley-Cox J, Vinogradova Y, Coupland C, et al. Risk of malignancy in patients with schizophrenia or bipolar disorder: nested case-control study. Arch Gen Psychiatry. 2007;64(12):1368-1376.
28. Grinshpoon A, Barchana M, Ponizovsky A, et al. Cancer in schizophrenia: is the risk higher or lower? Schizophr Res. 2005;73(2-3):333-341.
29. Hwang M, Farasatpour M, Williams CD, et al. Adjuvant chemotherapy for breast cancer patients with schizophrenia. Oncol Lett. 2012;3(4):845-850.