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Vaccine gets orphan designation for ATLL
The European Medicines Agency (EMA) has granted orphan drug designation for a therapeutic vaccine candidate known as THV02 to treat adult T-cell leukemia/lymphoma (ATLL).
THV02 is an experimental treatment composed of 2 lentiviral vectors to be used in a prime/boost regimen in ATLL patients infected by the HTLV-1 virus.
Both investigational drugs encode the same antigens, derived from 4 proteins of the HTLV-1 virus.
THV02 is intended to induce an immune response against HTLV antigens born by ATLL with the aim of enabling the patients’ immune system to fight leukemic cells.
Preclinical evaluation has suggested that THV02 is safe, and the vaccine has presented an “unprecedented” immunogenicity profile in several models, according to THERAVECTYS, the company developing THV02.
“Preclinical immunogenicity results obtained to date are very promising, and we are really excited by the prospect of bringing a safe and better-tolerated alternative to patients who are desperately in need of a treatment,” said Déborah Revaud, the senior scientist in charge of developing THV02.
The EMA grants orphan designation to drugs in development intended for the treatment, prevention, or diagnosis of life-threatening or chronically debilitating diseases occurring in fewer than 5 in 10,000 people.
The designation allows sponsors to benefit from an accelerated development process, financial incentives, and a 10-year period of market exclusivity once the drug is on the market.
“We are extremely pleased that the European Medicines Agency has granted an orphan drug status to our vaccine candidate against ATLL,” said Emmanuelle Sabbah-Petrover, PhD, head of regulatory affairs at THERAVECTYS.
“We expect to recruit our first patients towards the end of Q3 2015 in Europe and advance further developments in the US and in Japan in 2016.”
Should THV02 demonstrate a convincing safety and efficacy profile during its development against ATLL, THERAVECTYS said it will consider developing the vaccine for HTLV-related infections as treatment and possibly as prophylaxis. 
The European Medicines Agency (EMA) has granted orphan drug designation for a therapeutic vaccine candidate known as THV02 to treat adult T-cell leukemia/lymphoma (ATLL).
THV02 is an experimental treatment composed of 2 lentiviral vectors to be used in a prime/boost regimen in ATLL patients infected by the HTLV-1 virus.
Both investigational drugs encode the same antigens, derived from 4 proteins of the HTLV-1 virus.
THV02 is intended to induce an immune response against HTLV antigens born by ATLL with the aim of enabling the patients’ immune system to fight leukemic cells.
Preclinical evaluation has suggested that THV02 is safe, and the vaccine has presented an “unprecedented” immunogenicity profile in several models, according to THERAVECTYS, the company developing THV02.
“Preclinical immunogenicity results obtained to date are very promising, and we are really excited by the prospect of bringing a safe and better-tolerated alternative to patients who are desperately in need of a treatment,” said Déborah Revaud, the senior scientist in charge of developing THV02.
The EMA grants orphan designation to drugs in development intended for the treatment, prevention, or diagnosis of life-threatening or chronically debilitating diseases occurring in fewer than 5 in 10,000 people.
The designation allows sponsors to benefit from an accelerated development process, financial incentives, and a 10-year period of market exclusivity once the drug is on the market.
“We are extremely pleased that the European Medicines Agency has granted an orphan drug status to our vaccine candidate against ATLL,” said Emmanuelle Sabbah-Petrover, PhD, head of regulatory affairs at THERAVECTYS.
“We expect to recruit our first patients towards the end of Q3 2015 in Europe and advance further developments in the US and in Japan in 2016.”
Should THV02 demonstrate a convincing safety and efficacy profile during its development against ATLL, THERAVECTYS said it will consider developing the vaccine for HTLV-related infections as treatment and possibly as prophylaxis.
The European Medicines Agency (EMA) has granted orphan drug designation for a therapeutic vaccine candidate known as THV02 to treat adult T-cell leukemia/lymphoma (ATLL).
THV02 is an experimental treatment composed of 2 lentiviral vectors to be used in a prime/boost regimen in ATLL patients infected by the HTLV-1 virus.
Both investigational drugs encode the same antigens, derived from 4 proteins of the HTLV-1 virus.
THV02 is intended to induce an immune response against HTLV antigens born by ATLL with the aim of enabling the patients’ immune system to fight leukemic cells.
Preclinical evaluation has suggested that THV02 is safe, and the vaccine has presented an “unprecedented” immunogenicity profile in several models, according to THERAVECTYS, the company developing THV02.
“Preclinical immunogenicity results obtained to date are very promising, and we are really excited by the prospect of bringing a safe and better-tolerated alternative to patients who are desperately in need of a treatment,” said Déborah Revaud, the senior scientist in charge of developing THV02.
The EMA grants orphan designation to drugs in development intended for the treatment, prevention, or diagnosis of life-threatening or chronically debilitating diseases occurring in fewer than 5 in 10,000 people.
The designation allows sponsors to benefit from an accelerated development process, financial incentives, and a 10-year period of market exclusivity once the drug is on the market.
“We are extremely pleased that the European Medicines Agency has granted an orphan drug status to our vaccine candidate against ATLL,” said Emmanuelle Sabbah-Petrover, PhD, head of regulatory affairs at THERAVECTYS.
“We expect to recruit our first patients towards the end of Q3 2015 in Europe and advance further developments in the US and in Japan in 2016.”
Should THV02 demonstrate a convincing safety and efficacy profile during its development against ATLL, THERAVECTYS said it will consider developing the vaccine for HTLV-related infections as treatment and possibly as prophylaxis.
Team creates new cells for modeling malaria
infection in iPSC-derived liver
cells 8 days after infection
Credit: Shengyong Ng et al.
Researchers say they’ve found a way to grow liver-like cells from induced pluripotent stem cells (iPSCs).
The liver-like cells can be infected with several strains of the malaria parasite and respond to existing drugs the same way mature human liver cells do.
The new cells, described in Stem Cell Reports, could allow scientists to test drugs on cells from people with different genetic backgrounds, who may respond differently to malaria infection and treatment.
Modeling infection
Until now, malaria researchers have not had many reliable ways to test new drugs in liver tissue.
“What’s historically been done is people have tried to make do with the systems that were available,” said study author Sangeeta Bhatia, MD, PhD, of the Massachusetts Institute of Technology in Cambridge.
In 2013, Dr Bhatia and her colleagues showed they could model malaria infection in hepatocytes from human donors. However, this generates only a limited supply from each donor, and not all of the cells work well for drug studies.
The researchers then turned to iPSCs, which can be generated from human skin cells by adding reprogramming factors. To create liver cells, the researchers added a series of growth factors, including hepatocyte growth factor, to the iPSCs.
The team generated these cells in 2012 and used them to model infection of hepatitis C. However, these cells, known as hepatocyte-like cells, did not seem to be as mature as real adult liver cells.
In the current study, the researchers found these cells could be infected with several strains of malaria. But, initially, the cells did not respond to drugs in the same way as adult liver cells.
In particular, they were not sensitive to primaquine, which works only if cells have a certain set of drug-metabolism enzymes found in mature liver cells.
To induce the cells to become more mature and turn on these metabolic enzymes, the researchers added a molecule they had identified in a previous study. This compound, which the researchers call a “maturin,” stimulated the cells to turn on those enzymes, which made them sensitive to primaquine.
Toward better drugs
The team is now working with the nonprofit foundation Medical Malaria Ventures to test about 10 potential malaria drugs that are in the pipeline, first using adult donor liver cells and then the hepatocyte-like cells generated in this study.
These cells could also prove useful to help identify new drug targets, the researchers said. In this study, they found the liver-like cells can be infected with malaria when they are still in the equivalent of fetal stages of development, when they become hepatoblasts, which are precursors to hepatocytes.
In future studies, the researchers plan to investigate which genes get turned on when the cells become susceptible to infection, which may suggest new targets for malaria drugs.
They also hope to compare the genes needed for malaria infection with those needed for hepatitis infection, in hopes of identifying common pathways to target for both diseases.
infection in iPSC-derived liver
cells 8 days after infection
Credit: Shengyong Ng et al.
Researchers say they’ve found a way to grow liver-like cells from induced pluripotent stem cells (iPSCs).
The liver-like cells can be infected with several strains of the malaria parasite and respond to existing drugs the same way mature human liver cells do.
The new cells, described in Stem Cell Reports, could allow scientists to test drugs on cells from people with different genetic backgrounds, who may respond differently to malaria infection and treatment.
Modeling infection
Until now, malaria researchers have not had many reliable ways to test new drugs in liver tissue.
“What’s historically been done is people have tried to make do with the systems that were available,” said study author Sangeeta Bhatia, MD, PhD, of the Massachusetts Institute of Technology in Cambridge.
In 2013, Dr Bhatia and her colleagues showed they could model malaria infection in hepatocytes from human donors. However, this generates only a limited supply from each donor, and not all of the cells work well for drug studies.
The researchers then turned to iPSCs, which can be generated from human skin cells by adding reprogramming factors. To create liver cells, the researchers added a series of growth factors, including hepatocyte growth factor, to the iPSCs.
The team generated these cells in 2012 and used them to model infection of hepatitis C. However, these cells, known as hepatocyte-like cells, did not seem to be as mature as real adult liver cells.
In the current study, the researchers found these cells could be infected with several strains of malaria. But, initially, the cells did not respond to drugs in the same way as adult liver cells.
In particular, they were not sensitive to primaquine, which works only if cells have a certain set of drug-metabolism enzymes found in mature liver cells.
To induce the cells to become more mature and turn on these metabolic enzymes, the researchers added a molecule they had identified in a previous study. This compound, which the researchers call a “maturin,” stimulated the cells to turn on those enzymes, which made them sensitive to primaquine.
Toward better drugs
The team is now working with the nonprofit foundation Medical Malaria Ventures to test about 10 potential malaria drugs that are in the pipeline, first using adult donor liver cells and then the hepatocyte-like cells generated in this study.
These cells could also prove useful to help identify new drug targets, the researchers said. In this study, they found the liver-like cells can be infected with malaria when they are still in the equivalent of fetal stages of development, when they become hepatoblasts, which are precursors to hepatocytes.
In future studies, the researchers plan to investigate which genes get turned on when the cells become susceptible to infection, which may suggest new targets for malaria drugs.
They also hope to compare the genes needed for malaria infection with those needed for hepatitis infection, in hopes of identifying common pathways to target for both diseases.
infection in iPSC-derived liver
cells 8 days after infection
Credit: Shengyong Ng et al.
Researchers say they’ve found a way to grow liver-like cells from induced pluripotent stem cells (iPSCs).
The liver-like cells can be infected with several strains of the malaria parasite and respond to existing drugs the same way mature human liver cells do.
The new cells, described in Stem Cell Reports, could allow scientists to test drugs on cells from people with different genetic backgrounds, who may respond differently to malaria infection and treatment.
Modeling infection
Until now, malaria researchers have not had many reliable ways to test new drugs in liver tissue.
“What’s historically been done is people have tried to make do with the systems that were available,” said study author Sangeeta Bhatia, MD, PhD, of the Massachusetts Institute of Technology in Cambridge.
In 2013, Dr Bhatia and her colleagues showed they could model malaria infection in hepatocytes from human donors. However, this generates only a limited supply from each donor, and not all of the cells work well for drug studies.
The researchers then turned to iPSCs, which can be generated from human skin cells by adding reprogramming factors. To create liver cells, the researchers added a series of growth factors, including hepatocyte growth factor, to the iPSCs.
The team generated these cells in 2012 and used them to model infection of hepatitis C. However, these cells, known as hepatocyte-like cells, did not seem to be as mature as real adult liver cells.
In the current study, the researchers found these cells could be infected with several strains of malaria. But, initially, the cells did not respond to drugs in the same way as adult liver cells.
In particular, they were not sensitive to primaquine, which works only if cells have a certain set of drug-metabolism enzymes found in mature liver cells.
To induce the cells to become more mature and turn on these metabolic enzymes, the researchers added a molecule they had identified in a previous study. This compound, which the researchers call a “maturin,” stimulated the cells to turn on those enzymes, which made them sensitive to primaquine.
Toward better drugs
The team is now working with the nonprofit foundation Medical Malaria Ventures to test about 10 potential malaria drugs that are in the pipeline, first using adult donor liver cells and then the hepatocyte-like cells generated in this study.
These cells could also prove useful to help identify new drug targets, the researchers said. In this study, they found the liver-like cells can be infected with malaria when they are still in the equivalent of fetal stages of development, when they become hepatoblasts, which are precursors to hepatocytes.
In future studies, the researchers plan to investigate which genes get turned on when the cells become susceptible to infection, which may suggest new targets for malaria drugs.
They also hope to compare the genes needed for malaria infection with those needed for hepatitis infection, in hopes of identifying common pathways to target for both diseases.
Neurological Rare Disease Special Report
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Click here to download the PDF.
Click here to download the PDF.
Weight Loss Achieved with Medication Can Delay Onset of Type 2 Diabetes in At-Risk Individuals
Study Overview
Objective. To determine the effect of phentermine and topiramate extended release (PHEN/TPM ER) treatment on progression to type 2 diabetes and/or cardiometabolic disease in subjects with prediabetes and/or metabolic syndrome (MetS) at baseline.
Design. Sub-group analysis of a larger double-blind, randomized, placebo-controlled trial of PHEN/TPM ER in overweight and obese adults.
Setting and participants. The larger study had 2 phases —a 56-week weight loss trial (CONQUER, n = 866), followed by an extension of the drug trial out to 108 weeks (SEQUEL, n = 675) in a sub-group of CONQUER participants. The CONQUER trial, based at 93 U.S. centers, enrolled overweight or obese patients with at least 2 obesity-related comorbidities and randomly assigned them to receive either placebo or PHEN/TPM ER at a lower (7.5 mg/46 mg) or higher (15 mg/92 mg) daily dose. All 3 groups also received lifestyle modification counseling that included an evidence-based diet and exercise curriculum. Participants received study drug and lifestyle counseling in the setting of monthly visits during the 60- (CONQUER) or 108-week (SEQUEL) follow-up period.
The analyses presented in this paper focus on the 475 participants who completed both CONQUER and SEQUEL and who were characterized as pre-diabetic or as having the metabolic syndrome (MetS) at baseline. Pre-diabetes was defined as having a blood glucose level of 100–125 mg/dL or higher while fasting, or 140–199 mg/dL after an oral glucose tolerance test (GTT). MetS was characterized in participants who displayed 3 or more of the following at baseline: waist circumference ≥ 102 cm in men or 88 cm in women; triglycerides ≥ 150 mg/dL or on a lipid-lowering medication; HDL < 40 mg/dL in men or < 50 mg/dL in women; systolic BP ≥ 130 mm Hg or diastolic BP ≥ 85 mm Hg (or on antihypertensive); and fasting glucose ≥ 100 mg/dL or on treatment for elevated glucose.
Main outcome measures. The primary outcome for this study was percent weight loss at 108 weeks of follow-up (or early termination). Secondary outcomes included cardiometabolic changes, such as development of type 2 diabetes and changes in lipid measures, blood pressure, and waist circumference. These were assessed at baseline, week 56, and week 108 (or at early termination). Rates of progression to type 2 diabetes were compared between the treatment groups using chi-square testing. Intention-to-treat (ITT) ANCOVA analysis was performed with multiple imputation techniques to address missing data, as well as with an alternative analysis using last observation carried forward.
Results. The study arms were similar with respect to baseline characteristics. Average age was 51 years in the high dose PHEN/TPM ER arm and 52 in the other arms. Over half (65%) of participants were women and 86% were Caucasian. Mean BMI was 36 kg/m2 (class II obesity). Over half of participants were on antihypertensive medications at baseline but with well-controlled blood pressure (mean 128/80 mm Hg). Of the 475 people in this analysis, 316 met criteria for prediabetes, 451 for MetS, and 292 for both prediabetes and MetS.
Weight loss at 2 years was significantly greater in subjects taking PHEN/TPM ER (10.9% in the lower dose group, 12.1% in the higher dose group) compared to those taking placebo (2.5%) (P < 0.001). Mirroring weight loss results, type 2 diabetes incidence was also significantly lower in the drug treatment arms than in the placebo arm at 2 years after randomization—annualized incidence was 6.1% for placebo vs. 1.8% for lower-dose drug and 1.3% for higher-dose drug (P < 0.05). Greater weight loss was associated with greater decrease in diabetes incidence across all 3 arms of the study. Those persons who did not achieve at least a 5% weight loss at 2 years had the highest annualized risk of developing diabetes (6.3%), compared with a 0.9% risk among those who lost at least 15% of their weight. Improvements in other cardiometabolic parameters, including HDL, triglycerides, waist circumference, and insulin sensitivity index, was more common among the PHEN/TPM ER participants compared with placebo. Blood pressure decreased slightly for all 3 groups and there was no significant difference between the drug arms and the placebo arm.
Discontinuation of study medication occurred in all 3 groups (3.1% in placebo, 6.1% in lower-dose medication, and 5.5% in higher-dose medication), with serious adverse events in 5%, 7%, and 8.5%, respectively. There were no deaths.
Conclusion. PHEN/TPM ER administered over a 2-year period significantly improved weight loss and decreased progression to type 2 diabetes relative to placebo in a group of at-risk participants.
Commentary
Diabetes and related cardiometabolic disease are major contributors to morbidity and mortality in adults. With the exception of invasive treatments such as bariatric surgery, reversal of diabetes once it is established has proven quite difficult [1,2], and thus there is an increased emphasis from the public health and medical communities on preventing the development of this disease in the first place. Complicating the picture, recently broadened criteria for pre-diabetes will likely result in a very large number of these at-risk individuals being identified [3,4]. Although intensive lifestyle interventions resulting in a 5% to 7% weight loss among pre-diabetics have been shown to delay progression to diabetes [5], the translation of these programs into real-world settings has, so far, shown less promise than the original randomized trials might have indicated [4]. Although there is ongoing work to try to improve results and uptake in community-based lifestyle intervention programs, for many patients and clinicians these resource-intensive programs currently prove difficult to do well on a large scale.
Alternative methods of helping patients achieve and maintain that critical > 5% weight loss are desperately needed, not only for preventing diabetes, but also for impacting the numerous other risks associated with obesity. This particular trial capitalized on the notion that it is probably successful weight loss, not the intervention format used to achieve that weight loss, which drives decreased diabetes risk. This study was a sub-analysis of a larger randomized trial, and many of the strengths of that larger study are therefore reflected in this paper. Participants and study staff were blinded to treatment arm with the use of placebo, a very important strength when adverse reactions and drug intolerances need to be measured. Furthermore, this likely equalized motivation to comply with the lifestyle recommendations across the treatment arms—this might not have been the case if patients were aware that they were or were not receiving study drug. Another key strength of the study is its duration. PHEN/TPM ER is unique in that it is approved by the FDA for long-term use. Whereas many studies of weight loss show maximum intervention effect at about 6 months followed by weight regain, this study showed sustained weight loss up to 2 years after starting therapy, presumably because participants could actually continue the therapy for the full 2 years. Most importantly, the intervention itself (medication plus low-intensity lifestyle counseling) is likely highly replicable in clinical practice.
There are some important limitations to consider when interpreting the results from this study. First, the participants analyzed in this paper were comprised entirely of people who had already participated in a full year of the parent study and therefore probably represent a sub-group that might have been experiencing greater success as a result of their participation, potentially generating an overly optimistic estimate of weight loss and health effect for all of the groups relative to what might be seen in a general population. This feature of the design also limits this study’s ability to comment on drug intolerance or early adverse reactions—those who didn’t stick with the pills for at least a year would not have been included in these analyses. In terms of generalizability, although the infrastructure required from a clinical standpoint is much lower for an intervention like this (prescribing a medication) compared to an intensive lifestyle intervention, these drugs are still costly, and many insurers/providers may not offer them on formulary. Thus, to realize the long-term benefits of sustained weight loss, patients may need to face significant out-of-pocket costs, which may limit uptake of this therapy to those with financial means. For this and other reasons, it will be important to do future studies looking at how quickly weight is re-gained once people stop taking the medication. Another threat to generalizability is the racial makeup of the participants—the vast majority of them were non-Hispanic white. Furthermore, although a majority of the participants had hypertension, it was well-controlled in all (a prerequisite for taking the medication), and it is unclear whether in a real-world patient population hypertension would be adequately controlled in a large number of patients.
Another issue to consider when looking at the use of weight loss medications for prevention of diabetes is the relative risk of prolonged medication use compared with the risk for developing diabetes. Clearly, for obese patients who are interested in losing weight for other reasons, prevention of diabetes is a wonderful side effect of achieving that goal. However, it is worth noting that even in the highest-risk group of participants in this study (those who lost < 5% of weight), the annualized risk of developing diabetes was about 6% (< 20% cumulative risk projected over 3 years). Compare this to the 7% to 8% serious adverse event rate observed in those on drug therapy. Although the medication did reduce annualized diabetes risk significantly, the vast majority of people in all the arms did not develop diabetes during follow-up. This drives home the point that our current categorization of pre-diabetes is far from perfect in identifying people who are at imminent risk of becoming diabetic, and reinforces the notion that any treatment we provide to them in the name of diabetes prevention should be free from risk of harm. Rather than applying a long-term medication with potentially harmful side effects to a large group of at-risk patients, more research is needed to provide tools for clinicians to think carefully about which of their patients are truly at highest risk of going on to develop diabetes in the near future.
Applications for Clinical Practice
Although clinicians ought not use PHEN/TPM ER exclusively for diabetes prevention based on the results from this trial, delay of diabetes onset is a possible and important benefit of the use of PHEN/TPM ER in obese patients, provided that they are willing to also make and sustain lifestyle changes in order to lose a clinically significant amount of weight.
—Kristina Lewis, MD, MPH
1. Gregg EW, Chen H, Wagenknecht LE, et al. Association of an intensive lifestyle intervention with remission of type 2 diabetes. JAMA 2012;308:2489-96.
2. Arterburn DE, O’Connor PJ. A look ahead at the future of diabetes prevention and treatment. JAMA 2012;308:2517–8.
3. Yudkin JS, Montori VM. The epidemic of pre-diabetes: the medicine and the politics. BMJ. 2014;349:g4485.
4. Kahn R, Davidson MB. The reality of type 2 diabetes prevention. Diabetes care 2014;37:943-9.
5. Knowler WC, Fowler SE, Hamman RF, et al. 10-year follow-up of diabetes incidence and weight loss in the Diabetes Prevention Program Outcomes Study. Lancet 2009;374:1677–86.
Study Overview
Objective. To determine the effect of phentermine and topiramate extended release (PHEN/TPM ER) treatment on progression to type 2 diabetes and/or cardiometabolic disease in subjects with prediabetes and/or metabolic syndrome (MetS) at baseline.
Design. Sub-group analysis of a larger double-blind, randomized, placebo-controlled trial of PHEN/TPM ER in overweight and obese adults.
Setting and participants. The larger study had 2 phases —a 56-week weight loss trial (CONQUER, n = 866), followed by an extension of the drug trial out to 108 weeks (SEQUEL, n = 675) in a sub-group of CONQUER participants. The CONQUER trial, based at 93 U.S. centers, enrolled overweight or obese patients with at least 2 obesity-related comorbidities and randomly assigned them to receive either placebo or PHEN/TPM ER at a lower (7.5 mg/46 mg) or higher (15 mg/92 mg) daily dose. All 3 groups also received lifestyle modification counseling that included an evidence-based diet and exercise curriculum. Participants received study drug and lifestyle counseling in the setting of monthly visits during the 60- (CONQUER) or 108-week (SEQUEL) follow-up period.
The analyses presented in this paper focus on the 475 participants who completed both CONQUER and SEQUEL and who were characterized as pre-diabetic or as having the metabolic syndrome (MetS) at baseline. Pre-diabetes was defined as having a blood glucose level of 100–125 mg/dL or higher while fasting, or 140–199 mg/dL after an oral glucose tolerance test (GTT). MetS was characterized in participants who displayed 3 or more of the following at baseline: waist circumference ≥ 102 cm in men or 88 cm in women; triglycerides ≥ 150 mg/dL or on a lipid-lowering medication; HDL < 40 mg/dL in men or < 50 mg/dL in women; systolic BP ≥ 130 mm Hg or diastolic BP ≥ 85 mm Hg (or on antihypertensive); and fasting glucose ≥ 100 mg/dL or on treatment for elevated glucose.
Main outcome measures. The primary outcome for this study was percent weight loss at 108 weeks of follow-up (or early termination). Secondary outcomes included cardiometabolic changes, such as development of type 2 diabetes and changes in lipid measures, blood pressure, and waist circumference. These were assessed at baseline, week 56, and week 108 (or at early termination). Rates of progression to type 2 diabetes were compared between the treatment groups using chi-square testing. Intention-to-treat (ITT) ANCOVA analysis was performed with multiple imputation techniques to address missing data, as well as with an alternative analysis using last observation carried forward.
Results. The study arms were similar with respect to baseline characteristics. Average age was 51 years in the high dose PHEN/TPM ER arm and 52 in the other arms. Over half (65%) of participants were women and 86% were Caucasian. Mean BMI was 36 kg/m2 (class II obesity). Over half of participants were on antihypertensive medications at baseline but with well-controlled blood pressure (mean 128/80 mm Hg). Of the 475 people in this analysis, 316 met criteria for prediabetes, 451 for MetS, and 292 for both prediabetes and MetS.
Weight loss at 2 years was significantly greater in subjects taking PHEN/TPM ER (10.9% in the lower dose group, 12.1% in the higher dose group) compared to those taking placebo (2.5%) (P < 0.001). Mirroring weight loss results, type 2 diabetes incidence was also significantly lower in the drug treatment arms than in the placebo arm at 2 years after randomization—annualized incidence was 6.1% for placebo vs. 1.8% for lower-dose drug and 1.3% for higher-dose drug (P < 0.05). Greater weight loss was associated with greater decrease in diabetes incidence across all 3 arms of the study. Those persons who did not achieve at least a 5% weight loss at 2 years had the highest annualized risk of developing diabetes (6.3%), compared with a 0.9% risk among those who lost at least 15% of their weight. Improvements in other cardiometabolic parameters, including HDL, triglycerides, waist circumference, and insulin sensitivity index, was more common among the PHEN/TPM ER participants compared with placebo. Blood pressure decreased slightly for all 3 groups and there was no significant difference between the drug arms and the placebo arm.
Discontinuation of study medication occurred in all 3 groups (3.1% in placebo, 6.1% in lower-dose medication, and 5.5% in higher-dose medication), with serious adverse events in 5%, 7%, and 8.5%, respectively. There were no deaths.
Conclusion. PHEN/TPM ER administered over a 2-year period significantly improved weight loss and decreased progression to type 2 diabetes relative to placebo in a group of at-risk participants.
Commentary
Diabetes and related cardiometabolic disease are major contributors to morbidity and mortality in adults. With the exception of invasive treatments such as bariatric surgery, reversal of diabetes once it is established has proven quite difficult [1,2], and thus there is an increased emphasis from the public health and medical communities on preventing the development of this disease in the first place. Complicating the picture, recently broadened criteria for pre-diabetes will likely result in a very large number of these at-risk individuals being identified [3,4]. Although intensive lifestyle interventions resulting in a 5% to 7% weight loss among pre-diabetics have been shown to delay progression to diabetes [5], the translation of these programs into real-world settings has, so far, shown less promise than the original randomized trials might have indicated [4]. Although there is ongoing work to try to improve results and uptake in community-based lifestyle intervention programs, for many patients and clinicians these resource-intensive programs currently prove difficult to do well on a large scale.
Alternative methods of helping patients achieve and maintain that critical > 5% weight loss are desperately needed, not only for preventing diabetes, but also for impacting the numerous other risks associated with obesity. This particular trial capitalized on the notion that it is probably successful weight loss, not the intervention format used to achieve that weight loss, which drives decreased diabetes risk. This study was a sub-analysis of a larger randomized trial, and many of the strengths of that larger study are therefore reflected in this paper. Participants and study staff were blinded to treatment arm with the use of placebo, a very important strength when adverse reactions and drug intolerances need to be measured. Furthermore, this likely equalized motivation to comply with the lifestyle recommendations across the treatment arms—this might not have been the case if patients were aware that they were or were not receiving study drug. Another key strength of the study is its duration. PHEN/TPM ER is unique in that it is approved by the FDA for long-term use. Whereas many studies of weight loss show maximum intervention effect at about 6 months followed by weight regain, this study showed sustained weight loss up to 2 years after starting therapy, presumably because participants could actually continue the therapy for the full 2 years. Most importantly, the intervention itself (medication plus low-intensity lifestyle counseling) is likely highly replicable in clinical practice.
There are some important limitations to consider when interpreting the results from this study. First, the participants analyzed in this paper were comprised entirely of people who had already participated in a full year of the parent study and therefore probably represent a sub-group that might have been experiencing greater success as a result of their participation, potentially generating an overly optimistic estimate of weight loss and health effect for all of the groups relative to what might be seen in a general population. This feature of the design also limits this study’s ability to comment on drug intolerance or early adverse reactions—those who didn’t stick with the pills for at least a year would not have been included in these analyses. In terms of generalizability, although the infrastructure required from a clinical standpoint is much lower for an intervention like this (prescribing a medication) compared to an intensive lifestyle intervention, these drugs are still costly, and many insurers/providers may not offer them on formulary. Thus, to realize the long-term benefits of sustained weight loss, patients may need to face significant out-of-pocket costs, which may limit uptake of this therapy to those with financial means. For this and other reasons, it will be important to do future studies looking at how quickly weight is re-gained once people stop taking the medication. Another threat to generalizability is the racial makeup of the participants—the vast majority of them were non-Hispanic white. Furthermore, although a majority of the participants had hypertension, it was well-controlled in all (a prerequisite for taking the medication), and it is unclear whether in a real-world patient population hypertension would be adequately controlled in a large number of patients.
Another issue to consider when looking at the use of weight loss medications for prevention of diabetes is the relative risk of prolonged medication use compared with the risk for developing diabetes. Clearly, for obese patients who are interested in losing weight for other reasons, prevention of diabetes is a wonderful side effect of achieving that goal. However, it is worth noting that even in the highest-risk group of participants in this study (those who lost < 5% of weight), the annualized risk of developing diabetes was about 6% (< 20% cumulative risk projected over 3 years). Compare this to the 7% to 8% serious adverse event rate observed in those on drug therapy. Although the medication did reduce annualized diabetes risk significantly, the vast majority of people in all the arms did not develop diabetes during follow-up. This drives home the point that our current categorization of pre-diabetes is far from perfect in identifying people who are at imminent risk of becoming diabetic, and reinforces the notion that any treatment we provide to them in the name of diabetes prevention should be free from risk of harm. Rather than applying a long-term medication with potentially harmful side effects to a large group of at-risk patients, more research is needed to provide tools for clinicians to think carefully about which of their patients are truly at highest risk of going on to develop diabetes in the near future.
Applications for Clinical Practice
Although clinicians ought not use PHEN/TPM ER exclusively for diabetes prevention based on the results from this trial, delay of diabetes onset is a possible and important benefit of the use of PHEN/TPM ER in obese patients, provided that they are willing to also make and sustain lifestyle changes in order to lose a clinically significant amount of weight.
—Kristina Lewis, MD, MPH
Study Overview
Objective. To determine the effect of phentermine and topiramate extended release (PHEN/TPM ER) treatment on progression to type 2 diabetes and/or cardiometabolic disease in subjects with prediabetes and/or metabolic syndrome (MetS) at baseline.
Design. Sub-group analysis of a larger double-blind, randomized, placebo-controlled trial of PHEN/TPM ER in overweight and obese adults.
Setting and participants. The larger study had 2 phases —a 56-week weight loss trial (CONQUER, n = 866), followed by an extension of the drug trial out to 108 weeks (SEQUEL, n = 675) in a sub-group of CONQUER participants. The CONQUER trial, based at 93 U.S. centers, enrolled overweight or obese patients with at least 2 obesity-related comorbidities and randomly assigned them to receive either placebo or PHEN/TPM ER at a lower (7.5 mg/46 mg) or higher (15 mg/92 mg) daily dose. All 3 groups also received lifestyle modification counseling that included an evidence-based diet and exercise curriculum. Participants received study drug and lifestyle counseling in the setting of monthly visits during the 60- (CONQUER) or 108-week (SEQUEL) follow-up period.
The analyses presented in this paper focus on the 475 participants who completed both CONQUER and SEQUEL and who were characterized as pre-diabetic or as having the metabolic syndrome (MetS) at baseline. Pre-diabetes was defined as having a blood glucose level of 100–125 mg/dL or higher while fasting, or 140–199 mg/dL after an oral glucose tolerance test (GTT). MetS was characterized in participants who displayed 3 or more of the following at baseline: waist circumference ≥ 102 cm in men or 88 cm in women; triglycerides ≥ 150 mg/dL or on a lipid-lowering medication; HDL < 40 mg/dL in men or < 50 mg/dL in women; systolic BP ≥ 130 mm Hg or diastolic BP ≥ 85 mm Hg (or on antihypertensive); and fasting glucose ≥ 100 mg/dL or on treatment for elevated glucose.
Main outcome measures. The primary outcome for this study was percent weight loss at 108 weeks of follow-up (or early termination). Secondary outcomes included cardiometabolic changes, such as development of type 2 diabetes and changes in lipid measures, blood pressure, and waist circumference. These were assessed at baseline, week 56, and week 108 (or at early termination). Rates of progression to type 2 diabetes were compared between the treatment groups using chi-square testing. Intention-to-treat (ITT) ANCOVA analysis was performed with multiple imputation techniques to address missing data, as well as with an alternative analysis using last observation carried forward.
Results. The study arms were similar with respect to baseline characteristics. Average age was 51 years in the high dose PHEN/TPM ER arm and 52 in the other arms. Over half (65%) of participants were women and 86% were Caucasian. Mean BMI was 36 kg/m2 (class II obesity). Over half of participants were on antihypertensive medications at baseline but with well-controlled blood pressure (mean 128/80 mm Hg). Of the 475 people in this analysis, 316 met criteria for prediabetes, 451 for MetS, and 292 for both prediabetes and MetS.
Weight loss at 2 years was significantly greater in subjects taking PHEN/TPM ER (10.9% in the lower dose group, 12.1% in the higher dose group) compared to those taking placebo (2.5%) (P < 0.001). Mirroring weight loss results, type 2 diabetes incidence was also significantly lower in the drug treatment arms than in the placebo arm at 2 years after randomization—annualized incidence was 6.1% for placebo vs. 1.8% for lower-dose drug and 1.3% for higher-dose drug (P < 0.05). Greater weight loss was associated with greater decrease in diabetes incidence across all 3 arms of the study. Those persons who did not achieve at least a 5% weight loss at 2 years had the highest annualized risk of developing diabetes (6.3%), compared with a 0.9% risk among those who lost at least 15% of their weight. Improvements in other cardiometabolic parameters, including HDL, triglycerides, waist circumference, and insulin sensitivity index, was more common among the PHEN/TPM ER participants compared with placebo. Blood pressure decreased slightly for all 3 groups and there was no significant difference between the drug arms and the placebo arm.
Discontinuation of study medication occurred in all 3 groups (3.1% in placebo, 6.1% in lower-dose medication, and 5.5% in higher-dose medication), with serious adverse events in 5%, 7%, and 8.5%, respectively. There were no deaths.
Conclusion. PHEN/TPM ER administered over a 2-year period significantly improved weight loss and decreased progression to type 2 diabetes relative to placebo in a group of at-risk participants.
Commentary
Diabetes and related cardiometabolic disease are major contributors to morbidity and mortality in adults. With the exception of invasive treatments such as bariatric surgery, reversal of diabetes once it is established has proven quite difficult [1,2], and thus there is an increased emphasis from the public health and medical communities on preventing the development of this disease in the first place. Complicating the picture, recently broadened criteria for pre-diabetes will likely result in a very large number of these at-risk individuals being identified [3,4]. Although intensive lifestyle interventions resulting in a 5% to 7% weight loss among pre-diabetics have been shown to delay progression to diabetes [5], the translation of these programs into real-world settings has, so far, shown less promise than the original randomized trials might have indicated [4]. Although there is ongoing work to try to improve results and uptake in community-based lifestyle intervention programs, for many patients and clinicians these resource-intensive programs currently prove difficult to do well on a large scale.
Alternative methods of helping patients achieve and maintain that critical > 5% weight loss are desperately needed, not only for preventing diabetes, but also for impacting the numerous other risks associated with obesity. This particular trial capitalized on the notion that it is probably successful weight loss, not the intervention format used to achieve that weight loss, which drives decreased diabetes risk. This study was a sub-analysis of a larger randomized trial, and many of the strengths of that larger study are therefore reflected in this paper. Participants and study staff were blinded to treatment arm with the use of placebo, a very important strength when adverse reactions and drug intolerances need to be measured. Furthermore, this likely equalized motivation to comply with the lifestyle recommendations across the treatment arms—this might not have been the case if patients were aware that they were or were not receiving study drug. Another key strength of the study is its duration. PHEN/TPM ER is unique in that it is approved by the FDA for long-term use. Whereas many studies of weight loss show maximum intervention effect at about 6 months followed by weight regain, this study showed sustained weight loss up to 2 years after starting therapy, presumably because participants could actually continue the therapy for the full 2 years. Most importantly, the intervention itself (medication plus low-intensity lifestyle counseling) is likely highly replicable in clinical practice.
There are some important limitations to consider when interpreting the results from this study. First, the participants analyzed in this paper were comprised entirely of people who had already participated in a full year of the parent study and therefore probably represent a sub-group that might have been experiencing greater success as a result of their participation, potentially generating an overly optimistic estimate of weight loss and health effect for all of the groups relative to what might be seen in a general population. This feature of the design also limits this study’s ability to comment on drug intolerance or early adverse reactions—those who didn’t stick with the pills for at least a year would not have been included in these analyses. In terms of generalizability, although the infrastructure required from a clinical standpoint is much lower for an intervention like this (prescribing a medication) compared to an intensive lifestyle intervention, these drugs are still costly, and many insurers/providers may not offer them on formulary. Thus, to realize the long-term benefits of sustained weight loss, patients may need to face significant out-of-pocket costs, which may limit uptake of this therapy to those with financial means. For this and other reasons, it will be important to do future studies looking at how quickly weight is re-gained once people stop taking the medication. Another threat to generalizability is the racial makeup of the participants—the vast majority of them were non-Hispanic white. Furthermore, although a majority of the participants had hypertension, it was well-controlled in all (a prerequisite for taking the medication), and it is unclear whether in a real-world patient population hypertension would be adequately controlled in a large number of patients.
Another issue to consider when looking at the use of weight loss medications for prevention of diabetes is the relative risk of prolonged medication use compared with the risk for developing diabetes. Clearly, for obese patients who are interested in losing weight for other reasons, prevention of diabetes is a wonderful side effect of achieving that goal. However, it is worth noting that even in the highest-risk group of participants in this study (those who lost < 5% of weight), the annualized risk of developing diabetes was about 6% (< 20% cumulative risk projected over 3 years). Compare this to the 7% to 8% serious adverse event rate observed in those on drug therapy. Although the medication did reduce annualized diabetes risk significantly, the vast majority of people in all the arms did not develop diabetes during follow-up. This drives home the point that our current categorization of pre-diabetes is far from perfect in identifying people who are at imminent risk of becoming diabetic, and reinforces the notion that any treatment we provide to them in the name of diabetes prevention should be free from risk of harm. Rather than applying a long-term medication with potentially harmful side effects to a large group of at-risk patients, more research is needed to provide tools for clinicians to think carefully about which of their patients are truly at highest risk of going on to develop diabetes in the near future.
Applications for Clinical Practice
Although clinicians ought not use PHEN/TPM ER exclusively for diabetes prevention based on the results from this trial, delay of diabetes onset is a possible and important benefit of the use of PHEN/TPM ER in obese patients, provided that they are willing to also make and sustain lifestyle changes in order to lose a clinically significant amount of weight.
—Kristina Lewis, MD, MPH
1. Gregg EW, Chen H, Wagenknecht LE, et al. Association of an intensive lifestyle intervention with remission of type 2 diabetes. JAMA 2012;308:2489-96.
2. Arterburn DE, O’Connor PJ. A look ahead at the future of diabetes prevention and treatment. JAMA 2012;308:2517–8.
3. Yudkin JS, Montori VM. The epidemic of pre-diabetes: the medicine and the politics. BMJ. 2014;349:g4485.
4. Kahn R, Davidson MB. The reality of type 2 diabetes prevention. Diabetes care 2014;37:943-9.
5. Knowler WC, Fowler SE, Hamman RF, et al. 10-year follow-up of diabetes incidence and weight loss in the Diabetes Prevention Program Outcomes Study. Lancet 2009;374:1677–86.
1. Gregg EW, Chen H, Wagenknecht LE, et al. Association of an intensive lifestyle intervention with remission of type 2 diabetes. JAMA 2012;308:2489-96.
2. Arterburn DE, O’Connor PJ. A look ahead at the future of diabetes prevention and treatment. JAMA 2012;308:2517–8.
3. Yudkin JS, Montori VM. The epidemic of pre-diabetes: the medicine and the politics. BMJ. 2014;349:g4485.
4. Kahn R, Davidson MB. The reality of type 2 diabetes prevention. Diabetes care 2014;37:943-9.
5. Knowler WC, Fowler SE, Hamman RF, et al. 10-year follow-up of diabetes incidence and weight loss in the Diabetes Prevention Program Outcomes Study. Lancet 2009;374:1677–86.
Real-world CAS results in Medicare patients not up to trial standards
The presence of competing risks and overall lower levels of provider proficiency appeared to limit the benefits of carotid artery stenting in Medicare beneficiaries, according to the results of a large retrospective cohort study of the Centers for Medicare & Medicaid Services CAS database (2005-2009).
Periprocedural mortality was more than twice the rate in this patient population than in those earlier patients those involved in the pivotal CREST and SAPPHIRE clinical trials, according to a report published online Jan. 12 in JAMA Neurology [doi:10.1001/jamaneurol.2014.3638].
“The higher risk of periprocedural complications and the burden of competing risks owing to age and comorbidity burden must be carefully considered when deciding between carotid stenosis treatments for Medicare beneficiaries,” according to Jessica J. Jalbert, Ph.D., of Brigham and Women’s Hospital and Harvard Medical School, Boston, and her colleagues.
Over 22,000 patients were assessed in the study. The mean patient age was just over 76 years, 60.5% were men, and 94% were white. Approximately half were symptomatic, 91.2% were at high surgical risk, and 97.4% had carotid stenosis of at least 70%.
Almost 80% of the patients undergoing carotid artery stenting (CAS) met the SAPPHIRE trial indications and about half met at least one of the SAPPHIRE criteria for high surgical risk.
In the mean follow-up of approximately 2 years, mortality risks exceeded one-third for patients who were 80 years of age or older (41.5% mortality risk), symptomatic (37.3% risk), at high surgical risk with symptomatic carotid stenosis of at least 50% (37.3% risk), or admitted nonelectively (36.2% risk). In addition, among asymptomatic patients, mortality after the periprocedural period exceeded one-third for patients at least 80 years old.
Of particular concern, few of these Medicare beneficiaries undergoing CAS as per the National Coverage Determinations were treated by providers with proficiency levels similar to those required in the clinical trials. This is a potential problem because lower annual volume and early operator experience are associated with increased periprocedural mortality, the authors wrote.
CAS was performed primarily by male physicians (98.4%), specializing in cardiology (52.9%), practicing within a group (79.4%), and residing in the South (42.5%). The mean number of past-year CAS procedures performed was only 13.9 for physicians and 29.8 for hospitals. This translated to more than 80% of the physicians not meeting the minimum CAS volume requirements and/or minimum complication rates of the SAPPHIRE trial, and more than 90% not meeting the requirements of the CREST trial.
“Our results may support concerns about the limited generalizability of [randomized clinical trial] findings,” the researchers stated.
“Real-world observational studies comparing CAS, carotid endarterectomy, and medical management are needed to determine the performance of carotid stenosis treatment options for Medicare beneficiaries,” Dr. Jalbert and her colleagues concluded.
The authors reported no relevant disclosures. The study was funded by the Agency for Healthcare Research and Quality, U.S. Department of Health & Human Services.
The presence of competing risks and overall lower levels of provider proficiency appeared to limit the benefits of carotid artery stenting in Medicare beneficiaries, according to the results of a large retrospective cohort study of the Centers for Medicare & Medicaid Services CAS database (2005-2009).
Periprocedural mortality was more than twice the rate in this patient population than in those earlier patients those involved in the pivotal CREST and SAPPHIRE clinical trials, according to a report published online Jan. 12 in JAMA Neurology [doi:10.1001/jamaneurol.2014.3638].
“The higher risk of periprocedural complications and the burden of competing risks owing to age and comorbidity burden must be carefully considered when deciding between carotid stenosis treatments for Medicare beneficiaries,” according to Jessica J. Jalbert, Ph.D., of Brigham and Women’s Hospital and Harvard Medical School, Boston, and her colleagues.
Over 22,000 patients were assessed in the study. The mean patient age was just over 76 years, 60.5% were men, and 94% were white. Approximately half were symptomatic, 91.2% were at high surgical risk, and 97.4% had carotid stenosis of at least 70%.
Almost 80% of the patients undergoing carotid artery stenting (CAS) met the SAPPHIRE trial indications and about half met at least one of the SAPPHIRE criteria for high surgical risk.
In the mean follow-up of approximately 2 years, mortality risks exceeded one-third for patients who were 80 years of age or older (41.5% mortality risk), symptomatic (37.3% risk), at high surgical risk with symptomatic carotid stenosis of at least 50% (37.3% risk), or admitted nonelectively (36.2% risk). In addition, among asymptomatic patients, mortality after the periprocedural period exceeded one-third for patients at least 80 years old.
Of particular concern, few of these Medicare beneficiaries undergoing CAS as per the National Coverage Determinations were treated by providers with proficiency levels similar to those required in the clinical trials. This is a potential problem because lower annual volume and early operator experience are associated with increased periprocedural mortality, the authors wrote.
CAS was performed primarily by male physicians (98.4%), specializing in cardiology (52.9%), practicing within a group (79.4%), and residing in the South (42.5%). The mean number of past-year CAS procedures performed was only 13.9 for physicians and 29.8 for hospitals. This translated to more than 80% of the physicians not meeting the minimum CAS volume requirements and/or minimum complication rates of the SAPPHIRE trial, and more than 90% not meeting the requirements of the CREST trial.
“Our results may support concerns about the limited generalizability of [randomized clinical trial] findings,” the researchers stated.
“Real-world observational studies comparing CAS, carotid endarterectomy, and medical management are needed to determine the performance of carotid stenosis treatment options for Medicare beneficiaries,” Dr. Jalbert and her colleagues concluded.
The authors reported no relevant disclosures. The study was funded by the Agency for Healthcare Research and Quality, U.S. Department of Health & Human Services.
The presence of competing risks and overall lower levels of provider proficiency appeared to limit the benefits of carotid artery stenting in Medicare beneficiaries, according to the results of a large retrospective cohort study of the Centers for Medicare & Medicaid Services CAS database (2005-2009).
Periprocedural mortality was more than twice the rate in this patient population than in those earlier patients those involved in the pivotal CREST and SAPPHIRE clinical trials, according to a report published online Jan. 12 in JAMA Neurology [doi:10.1001/jamaneurol.2014.3638].
“The higher risk of periprocedural complications and the burden of competing risks owing to age and comorbidity burden must be carefully considered when deciding between carotid stenosis treatments for Medicare beneficiaries,” according to Jessica J. Jalbert, Ph.D., of Brigham and Women’s Hospital and Harvard Medical School, Boston, and her colleagues.
Over 22,000 patients were assessed in the study. The mean patient age was just over 76 years, 60.5% were men, and 94% were white. Approximately half were symptomatic, 91.2% were at high surgical risk, and 97.4% had carotid stenosis of at least 70%.
Almost 80% of the patients undergoing carotid artery stenting (CAS) met the SAPPHIRE trial indications and about half met at least one of the SAPPHIRE criteria for high surgical risk.
In the mean follow-up of approximately 2 years, mortality risks exceeded one-third for patients who were 80 years of age or older (41.5% mortality risk), symptomatic (37.3% risk), at high surgical risk with symptomatic carotid stenosis of at least 50% (37.3% risk), or admitted nonelectively (36.2% risk). In addition, among asymptomatic patients, mortality after the periprocedural period exceeded one-third for patients at least 80 years old.
Of particular concern, few of these Medicare beneficiaries undergoing CAS as per the National Coverage Determinations were treated by providers with proficiency levels similar to those required in the clinical trials. This is a potential problem because lower annual volume and early operator experience are associated with increased periprocedural mortality, the authors wrote.
CAS was performed primarily by male physicians (98.4%), specializing in cardiology (52.9%), practicing within a group (79.4%), and residing in the South (42.5%). The mean number of past-year CAS procedures performed was only 13.9 for physicians and 29.8 for hospitals. This translated to more than 80% of the physicians not meeting the minimum CAS volume requirements and/or minimum complication rates of the SAPPHIRE trial, and more than 90% not meeting the requirements of the CREST trial.
“Our results may support concerns about the limited generalizability of [randomized clinical trial] findings,” the researchers stated.
“Real-world observational studies comparing CAS, carotid endarterectomy, and medical management are needed to determine the performance of carotid stenosis treatment options for Medicare beneficiaries,” Dr. Jalbert and her colleagues concluded.
The authors reported no relevant disclosures. The study was funded by the Agency for Healthcare Research and Quality, U.S. Department of Health & Human Services.
FROM JAMA NEUROLOGY
Key clinical point: Mortality risks exceeded one-third for patients who were 80 years of age or older, symptomatic, at high surgical risk with symptomatic carotid stenosis of at least 50%, or admitted nonelectively.
Major finding: More than 80% of the physicians performing CAS in the real world did not meet the minimum CAS volume requirements and/or minimum complication rates of the SAPPPHIRE trial.
Data source: Data were obtained from a large retrospective cohort study of the Centers for Medicare and Medicaid Services CAS database (2005-2009).
Disclosures: The authors reported no relevant disclosures.
MicroRNA may be therapeutic target for ALK- ALCL
SAN FRANCISCO—MicroRNA-155 (miR-155) can act as an oncogenic driver in ALK− anaplastic large-cell lymphoma (ALCL) and may therefore be a therapeutic target for the disease, according to a presentation at the 7th Annual T-cell Lymphoma Forum.
Analyzing patient samples and cell lines, researchers discovered that miR-155 is highly expressed in ALK− ALCL but is nearly absent in ALK+ ALCL.
They also found evidence suggesting that miR-155 drives tumor growth in mouse models of ALK− ALCL.
Philipp Staber, MD, PhD, of the Medical University of Vienna in Austria, presented these findings at the meeting.
Dr Staber and his colleagues previously found (Merkel et al, PNAS 2010) that miR-155 was highly expressed in ALK− ALCL. So they decided to take a closer look at the phenomenon.
They assessed miR-155 expression in samples from patients with ALK+ or ALK− ALCL, as well as 6 ALCL cell lines.
miR-155 expression was significantly higher in the ALK− patient samples than in the ALK+ samples (P<0.001). And it was significantly higher (P<0.001) in the ALK− cell lines (DL-40, Mac1, and Mac2a) than in the ALK+ cell lines (K299, SR789, and SUP-M2).
Dr Staber and his colleagues then overexpressed miR-155 in ALK+ ALCL cell lines (K299 and SR789). And they observed a decrease in known target genes of miR-155—C/EBPβ, SOCS1, and SHIP1.
The researchers also observed an inverse correlation between miR-155 host gene promoter methylation and miR-155 expression in an ALCL+ cell line, which suggested that ALK activity has no direct effect on miR-155 levels.
The team treated the K299 cell line with the ALK inhibitor crizotinib at 100 nM, 200 nM, and 400 nM doses and found that miR-155 did not increase at any dose. Dr Staber noted, however, that the researchers were only able to treat cells for a maximum of 24 hours.
The group then discovered that anti-miR-155 mimics could reduce tumor growth in mouse models of ALK- ALCL. Mice were injected with Mac1 or Mac2a cells transfected with anti-miR-155, control RNA, or pre-miR-155 oligos.
In both Mac1 and Mac2 models, tumors were substantially smaller in the anti-mir-155 mice than in the pre-miR-155 mice (P=0.038 and P=0.006, respectively). But tumor growth was not significantly reduced compared to controls.
“Immunohistochemistry in these tumors shows quite a clear picture,” Dr Staber said. “The C/EBPβ target gene is overexpressed when using anti-miR-155, and [expression is decreased] with overexpression of miR-155. And the same is true for SOCS1. STAT3 signaling is increased through overexpression of miR-155.”
The researchers observed the same effect in ALK− ALCL patient samples.
Using ALK+ cell lines (K299 and SR789), the team went on to show that miR-155 suppresses IL-8 expression and induces IL-22 expression, a finding they verified in mice.
“IL-8 is a direct target of C/EBPβ, and C/EBPβ, as shown before, is a target of miR-155, so this makes sense,” Dr Staber said. “On the other hand, IL-22 is a strong inducer of STAT3 signaling, which is strongly induced when we increase miR-155 expression.”
Dr Staber and his colleagues concluded that these findings, when taken together, suggest that miR-155 could be a therapeutic target for ALK− ALCL.
SAN FRANCISCO—MicroRNA-155 (miR-155) can act as an oncogenic driver in ALK− anaplastic large-cell lymphoma (ALCL) and may therefore be a therapeutic target for the disease, according to a presentation at the 7th Annual T-cell Lymphoma Forum.
Analyzing patient samples and cell lines, researchers discovered that miR-155 is highly expressed in ALK− ALCL but is nearly absent in ALK+ ALCL.
They also found evidence suggesting that miR-155 drives tumor growth in mouse models of ALK− ALCL.
Philipp Staber, MD, PhD, of the Medical University of Vienna in Austria, presented these findings at the meeting.
Dr Staber and his colleagues previously found (Merkel et al, PNAS 2010) that miR-155 was highly expressed in ALK− ALCL. So they decided to take a closer look at the phenomenon.
They assessed miR-155 expression in samples from patients with ALK+ or ALK− ALCL, as well as 6 ALCL cell lines.
miR-155 expression was significantly higher in the ALK− patient samples than in the ALK+ samples (P<0.001). And it was significantly higher (P<0.001) in the ALK− cell lines (DL-40, Mac1, and Mac2a) than in the ALK+ cell lines (K299, SR789, and SUP-M2).
Dr Staber and his colleagues then overexpressed miR-155 in ALK+ ALCL cell lines (K299 and SR789). And they observed a decrease in known target genes of miR-155—C/EBPβ, SOCS1, and SHIP1.
The researchers also observed an inverse correlation between miR-155 host gene promoter methylation and miR-155 expression in an ALCL+ cell line, which suggested that ALK activity has no direct effect on miR-155 levels.
The team treated the K299 cell line with the ALK inhibitor crizotinib at 100 nM, 200 nM, and 400 nM doses and found that miR-155 did not increase at any dose. Dr Staber noted, however, that the researchers were only able to treat cells for a maximum of 24 hours.
The group then discovered that anti-miR-155 mimics could reduce tumor growth in mouse models of ALK- ALCL. Mice were injected with Mac1 or Mac2a cells transfected with anti-miR-155, control RNA, or pre-miR-155 oligos.
In both Mac1 and Mac2 models, tumors were substantially smaller in the anti-mir-155 mice than in the pre-miR-155 mice (P=0.038 and P=0.006, respectively). But tumor growth was not significantly reduced compared to controls.
“Immunohistochemistry in these tumors shows quite a clear picture,” Dr Staber said. “The C/EBPβ target gene is overexpressed when using anti-miR-155, and [expression is decreased] with overexpression of miR-155. And the same is true for SOCS1. STAT3 signaling is increased through overexpression of miR-155.”
The researchers observed the same effect in ALK− ALCL patient samples.
Using ALK+ cell lines (K299 and SR789), the team went on to show that miR-155 suppresses IL-8 expression and induces IL-22 expression, a finding they verified in mice.
“IL-8 is a direct target of C/EBPβ, and C/EBPβ, as shown before, is a target of miR-155, so this makes sense,” Dr Staber said. “On the other hand, IL-22 is a strong inducer of STAT3 signaling, which is strongly induced when we increase miR-155 expression.”
Dr Staber and his colleagues concluded that these findings, when taken together, suggest that miR-155 could be a therapeutic target for ALK− ALCL.
SAN FRANCISCO—MicroRNA-155 (miR-155) can act as an oncogenic driver in ALK− anaplastic large-cell lymphoma (ALCL) and may therefore be a therapeutic target for the disease, according to a presentation at the 7th Annual T-cell Lymphoma Forum.
Analyzing patient samples and cell lines, researchers discovered that miR-155 is highly expressed in ALK− ALCL but is nearly absent in ALK+ ALCL.
They also found evidence suggesting that miR-155 drives tumor growth in mouse models of ALK− ALCL.
Philipp Staber, MD, PhD, of the Medical University of Vienna in Austria, presented these findings at the meeting.
Dr Staber and his colleagues previously found (Merkel et al, PNAS 2010) that miR-155 was highly expressed in ALK− ALCL. So they decided to take a closer look at the phenomenon.
They assessed miR-155 expression in samples from patients with ALK+ or ALK− ALCL, as well as 6 ALCL cell lines.
miR-155 expression was significantly higher in the ALK− patient samples than in the ALK+ samples (P<0.001). And it was significantly higher (P<0.001) in the ALK− cell lines (DL-40, Mac1, and Mac2a) than in the ALK+ cell lines (K299, SR789, and SUP-M2).
Dr Staber and his colleagues then overexpressed miR-155 in ALK+ ALCL cell lines (K299 and SR789). And they observed a decrease in known target genes of miR-155—C/EBPβ, SOCS1, and SHIP1.
The researchers also observed an inverse correlation between miR-155 host gene promoter methylation and miR-155 expression in an ALCL+ cell line, which suggested that ALK activity has no direct effect on miR-155 levels.
The team treated the K299 cell line with the ALK inhibitor crizotinib at 100 nM, 200 nM, and 400 nM doses and found that miR-155 did not increase at any dose. Dr Staber noted, however, that the researchers were only able to treat cells for a maximum of 24 hours.
The group then discovered that anti-miR-155 mimics could reduce tumor growth in mouse models of ALK- ALCL. Mice were injected with Mac1 or Mac2a cells transfected with anti-miR-155, control RNA, or pre-miR-155 oligos.
In both Mac1 and Mac2 models, tumors were substantially smaller in the anti-mir-155 mice than in the pre-miR-155 mice (P=0.038 and P=0.006, respectively). But tumor growth was not significantly reduced compared to controls.
“Immunohistochemistry in these tumors shows quite a clear picture,” Dr Staber said. “The C/EBPβ target gene is overexpressed when using anti-miR-155, and [expression is decreased] with overexpression of miR-155. And the same is true for SOCS1. STAT3 signaling is increased through overexpression of miR-155.”
The researchers observed the same effect in ALK− ALCL patient samples.
Using ALK+ cell lines (K299 and SR789), the team went on to show that miR-155 suppresses IL-8 expression and induces IL-22 expression, a finding they verified in mice.
“IL-8 is a direct target of C/EBPβ, and C/EBPβ, as shown before, is a target of miR-155, so this makes sense,” Dr Staber said. “On the other hand, IL-22 is a strong inducer of STAT3 signaling, which is strongly induced when we increase miR-155 expression.”
Dr Staber and his colleagues concluded that these findings, when taken together, suggest that miR-155 could be a therapeutic target for ALK− ALCL.
Memory T cells can fight CMV infection
CMV infection
Transplanting a small number of antiviral memory T cells along with donor hematopoietic stem cells can fight and may even prevent cytomegalovirus (CMV) disease in transplant recipients, according to preclinical research published in the Journal of Immunology.
To date, researchers have focused on developing anti-CMV immunotherapy with effector-phenotype CD8+ T cells (TEFF cells), which attack and kill virally infected host cells.
But Christopher Snyder, PhD, of Thomas Jefferson University in Philadelphia, Pennsylvania, and his colleagues found that CMV-specific TEFF cells divide poorly in response to CMV infection or reactivation in mouse models.
So they wondered if CMV-specific memory-phenotype CD8+ T cells (TM cells)—which act more like stem cells—could help control the infection long-term.
The group showed that a small number of TM cells were enough to produce and repeatedly replenish all of the TEFF cells needed to fight CMV.
The infused TM cells became major contributors to the recipient antiviral immune response, persisting for at least 3 months’ time and producing TEFF cells at a steady stream.
To determine whether these cells have counterparts in humans, Dr Snyder and his colleagues compared the genomic fingerprints of mouse and human TM cells that were specific for CMV. Results showed the two had similar profiles.
“This suggested that human and mouse CMV-specific memory T cells are very similar populations,” said study author Michael Quinn, an MD/PhD student at Thomas Jefferson University.
“Therefore, infusing similar cells into humans could improve on immunotherapeutic methods for controlling CMV infection. This may be a valuable approach to keep the disease from emerging in people.”
Dr Snyder added, “Our data argue for developing new clinical trials focused specifically on using these T memory cells, in order to determine if it would indeed be better than current therapeutic options.”
CMV infection
Transplanting a small number of antiviral memory T cells along with donor hematopoietic stem cells can fight and may even prevent cytomegalovirus (CMV) disease in transplant recipients, according to preclinical research published in the Journal of Immunology.
To date, researchers have focused on developing anti-CMV immunotherapy with effector-phenotype CD8+ T cells (TEFF cells), which attack and kill virally infected host cells.
But Christopher Snyder, PhD, of Thomas Jefferson University in Philadelphia, Pennsylvania, and his colleagues found that CMV-specific TEFF cells divide poorly in response to CMV infection or reactivation in mouse models.
So they wondered if CMV-specific memory-phenotype CD8+ T cells (TM cells)—which act more like stem cells—could help control the infection long-term.
The group showed that a small number of TM cells were enough to produce and repeatedly replenish all of the TEFF cells needed to fight CMV.
The infused TM cells became major contributors to the recipient antiviral immune response, persisting for at least 3 months’ time and producing TEFF cells at a steady stream.
To determine whether these cells have counterparts in humans, Dr Snyder and his colleagues compared the genomic fingerprints of mouse and human TM cells that were specific for CMV. Results showed the two had similar profiles.
“This suggested that human and mouse CMV-specific memory T cells are very similar populations,” said study author Michael Quinn, an MD/PhD student at Thomas Jefferson University.
“Therefore, infusing similar cells into humans could improve on immunotherapeutic methods for controlling CMV infection. This may be a valuable approach to keep the disease from emerging in people.”
Dr Snyder added, “Our data argue for developing new clinical trials focused specifically on using these T memory cells, in order to determine if it would indeed be better than current therapeutic options.”
CMV infection
Transplanting a small number of antiviral memory T cells along with donor hematopoietic stem cells can fight and may even prevent cytomegalovirus (CMV) disease in transplant recipients, according to preclinical research published in the Journal of Immunology.
To date, researchers have focused on developing anti-CMV immunotherapy with effector-phenotype CD8+ T cells (TEFF cells), which attack and kill virally infected host cells.
But Christopher Snyder, PhD, of Thomas Jefferson University in Philadelphia, Pennsylvania, and his colleagues found that CMV-specific TEFF cells divide poorly in response to CMV infection or reactivation in mouse models.
So they wondered if CMV-specific memory-phenotype CD8+ T cells (TM cells)—which act more like stem cells—could help control the infection long-term.
The group showed that a small number of TM cells were enough to produce and repeatedly replenish all of the TEFF cells needed to fight CMV.
The infused TM cells became major contributors to the recipient antiviral immune response, persisting for at least 3 months’ time and producing TEFF cells at a steady stream.
To determine whether these cells have counterparts in humans, Dr Snyder and his colleagues compared the genomic fingerprints of mouse and human TM cells that were specific for CMV. Results showed the two had similar profiles.
“This suggested that human and mouse CMV-specific memory T cells are very similar populations,” said study author Michael Quinn, an MD/PhD student at Thomas Jefferson University.
“Therefore, infusing similar cells into humans could improve on immunotherapeutic methods for controlling CMV infection. This may be a valuable approach to keep the disease from emerging in people.”
Dr Snyder added, “Our data argue for developing new clinical trials focused specifically on using these T memory cells, in order to determine if it would indeed be better than current therapeutic options.”
mAb shows ‘modest activity’ in rel/ref MM
Photo by Linda Bartlett
The monoclonal IgM antibody PAT-SM6 was “well-tolerated” and showed “modest clinical activity” in patients with relapsed or refractory multiple myeloma (MM), researchers reported in haematologica.
Adverse events occurred in all 12 patients enrolled in the phase 1/2a study, but most were considered unrelated to treatment.
A third of patients, all of whom had progressive disease upon study entry, achieved stable disease after receiving PAT-SM6. The remaining patients progressed.
Leo Rasche, MD, of University Hospital Wurzburg in Germany, and his colleagues conducted this study. It was funded, in part, by Patrys Limited, the company developing PAT-SM6.
The study included 12 heavily pretreated MM patients. They had a median age of 69.5 years and a long-standing history of MM (range, 3.25 to 15.75 years). They had received a median of 3.9 prior lines of therapy (range, 2-7).
Patients received 4 escalating doses of PAT-SM6, over a period of 2 weeks, via intravenous infusions at 0.3 mg/kg, 1 mg/kg, 3 mg/kg, and 6 mg/kg.
Safety data
There were 54 treatment-emergent adverse events in all 12 patients. However, there were no dose-limiting toxicities and no deaths. The maximum tolerated dose has not been reached.
More than 80% of the adverse events were of mild to moderate intensity. Two patients (16.6%) each experienced a single serious event. One patient had acute back pain, and one had a bile duct stone. Neither of these events was considered treatment-related.
Twenty-one adverse events were considered treatment-related. This included leukopenia (66.6%), neutropenia (50%), hypertension (16.6%), catheter-related thrombophlebitis (8.3%), injection site erythema (8.3%), slight headache (8.3%), C-reactive protein increase (8.3%), and hypertriglyceridemia (8.3%).
Efficacy data
Most patients progressed following treatment, but 4 (33.3%) had stable disease. The investigators noted that stable disease is not necessarily connected with a clinical benefit, so they analyzed the 4 patients in detail.
Patient 4, who received PAT-SM6 at 1 mg/kg, entered the study with high-risk disease. The patient had 13q deletion and 1q21 gain, had received 5 prior lines of therapy, and was refractory to novel agents, including pomalidomide and bortezomib.
The patient was treatment-free for 1 month prior to receiving PAT-SM6. During treatment, there were no symptoms of active myeloma, and the patient asked to continue salvage therapy 1 week after the end of the study.
Patient 7, who received PAT-SM6 at 3 mg/kg, had been diagnosed with MM for 15 years and had received 4 prior lines of therapy.
The patient’s treatment-free interval before receiving PAT-SM6 was 30 months. After PAT-SM6, the patient was therapy-free for 4.6 months.
Patient 10, who received PAT-SM6 at 6mg/kg, had 6 prior lines of therapy, including tandem autologous stem cell transplant and several polychemotherapeutic regimens.
The patient was therapy-free for 4 months prior to receiving PAT-SM6. The patient requested salvage therapy 1 month after receiving PAT-SM6.
Patient 11, who received PAT-SM6 at 6mg/kg, had 4 prior lines of therapy and was refractory to both lenalidomide and thalidomide.
The patient’s treatment-free interval prior to PAT-SM6 was 12 months. After PAT-SM6, the patient was therapy-free for 5.2 months.
The researchers said additional trials testing PAT-SM6 in combination with other MM therapies are planned. PAT-SM6 has received orphan drug designation for MM in the US and the European Union.
Photo by Linda Bartlett
The monoclonal IgM antibody PAT-SM6 was “well-tolerated” and showed “modest clinical activity” in patients with relapsed or refractory multiple myeloma (MM), researchers reported in haematologica.
Adverse events occurred in all 12 patients enrolled in the phase 1/2a study, but most were considered unrelated to treatment.
A third of patients, all of whom had progressive disease upon study entry, achieved stable disease after receiving PAT-SM6. The remaining patients progressed.
Leo Rasche, MD, of University Hospital Wurzburg in Germany, and his colleagues conducted this study. It was funded, in part, by Patrys Limited, the company developing PAT-SM6.
The study included 12 heavily pretreated MM patients. They had a median age of 69.5 years and a long-standing history of MM (range, 3.25 to 15.75 years). They had received a median of 3.9 prior lines of therapy (range, 2-7).
Patients received 4 escalating doses of PAT-SM6, over a period of 2 weeks, via intravenous infusions at 0.3 mg/kg, 1 mg/kg, 3 mg/kg, and 6 mg/kg.
Safety data
There were 54 treatment-emergent adverse events in all 12 patients. However, there were no dose-limiting toxicities and no deaths. The maximum tolerated dose has not been reached.
More than 80% of the adverse events were of mild to moderate intensity. Two patients (16.6%) each experienced a single serious event. One patient had acute back pain, and one had a bile duct stone. Neither of these events was considered treatment-related.
Twenty-one adverse events were considered treatment-related. This included leukopenia (66.6%), neutropenia (50%), hypertension (16.6%), catheter-related thrombophlebitis (8.3%), injection site erythema (8.3%), slight headache (8.3%), C-reactive protein increase (8.3%), and hypertriglyceridemia (8.3%).
Efficacy data
Most patients progressed following treatment, but 4 (33.3%) had stable disease. The investigators noted that stable disease is not necessarily connected with a clinical benefit, so they analyzed the 4 patients in detail.
Patient 4, who received PAT-SM6 at 1 mg/kg, entered the study with high-risk disease. The patient had 13q deletion and 1q21 gain, had received 5 prior lines of therapy, and was refractory to novel agents, including pomalidomide and bortezomib.
The patient was treatment-free for 1 month prior to receiving PAT-SM6. During treatment, there were no symptoms of active myeloma, and the patient asked to continue salvage therapy 1 week after the end of the study.
Patient 7, who received PAT-SM6 at 3 mg/kg, had been diagnosed with MM for 15 years and had received 4 prior lines of therapy.
The patient’s treatment-free interval before receiving PAT-SM6 was 30 months. After PAT-SM6, the patient was therapy-free for 4.6 months.
Patient 10, who received PAT-SM6 at 6mg/kg, had 6 prior lines of therapy, including tandem autologous stem cell transplant and several polychemotherapeutic regimens.
The patient was therapy-free for 4 months prior to receiving PAT-SM6. The patient requested salvage therapy 1 month after receiving PAT-SM6.
Patient 11, who received PAT-SM6 at 6mg/kg, had 4 prior lines of therapy and was refractory to both lenalidomide and thalidomide.
The patient’s treatment-free interval prior to PAT-SM6 was 12 months. After PAT-SM6, the patient was therapy-free for 5.2 months.
The researchers said additional trials testing PAT-SM6 in combination with other MM therapies are planned. PAT-SM6 has received orphan drug designation for MM in the US and the European Union.
Photo by Linda Bartlett
The monoclonal IgM antibody PAT-SM6 was “well-tolerated” and showed “modest clinical activity” in patients with relapsed or refractory multiple myeloma (MM), researchers reported in haematologica.
Adverse events occurred in all 12 patients enrolled in the phase 1/2a study, but most were considered unrelated to treatment.
A third of patients, all of whom had progressive disease upon study entry, achieved stable disease after receiving PAT-SM6. The remaining patients progressed.
Leo Rasche, MD, of University Hospital Wurzburg in Germany, and his colleagues conducted this study. It was funded, in part, by Patrys Limited, the company developing PAT-SM6.
The study included 12 heavily pretreated MM patients. They had a median age of 69.5 years and a long-standing history of MM (range, 3.25 to 15.75 years). They had received a median of 3.9 prior lines of therapy (range, 2-7).
Patients received 4 escalating doses of PAT-SM6, over a period of 2 weeks, via intravenous infusions at 0.3 mg/kg, 1 mg/kg, 3 mg/kg, and 6 mg/kg.
Safety data
There were 54 treatment-emergent adverse events in all 12 patients. However, there were no dose-limiting toxicities and no deaths. The maximum tolerated dose has not been reached.
More than 80% of the adverse events were of mild to moderate intensity. Two patients (16.6%) each experienced a single serious event. One patient had acute back pain, and one had a bile duct stone. Neither of these events was considered treatment-related.
Twenty-one adverse events were considered treatment-related. This included leukopenia (66.6%), neutropenia (50%), hypertension (16.6%), catheter-related thrombophlebitis (8.3%), injection site erythema (8.3%), slight headache (8.3%), C-reactive protein increase (8.3%), and hypertriglyceridemia (8.3%).
Efficacy data
Most patients progressed following treatment, but 4 (33.3%) had stable disease. The investigators noted that stable disease is not necessarily connected with a clinical benefit, so they analyzed the 4 patients in detail.
Patient 4, who received PAT-SM6 at 1 mg/kg, entered the study with high-risk disease. The patient had 13q deletion and 1q21 gain, had received 5 prior lines of therapy, and was refractory to novel agents, including pomalidomide and bortezomib.
The patient was treatment-free for 1 month prior to receiving PAT-SM6. During treatment, there were no symptoms of active myeloma, and the patient asked to continue salvage therapy 1 week after the end of the study.
Patient 7, who received PAT-SM6 at 3 mg/kg, had been diagnosed with MM for 15 years and had received 4 prior lines of therapy.
The patient’s treatment-free interval before receiving PAT-SM6 was 30 months. After PAT-SM6, the patient was therapy-free for 4.6 months.
Patient 10, who received PAT-SM6 at 6mg/kg, had 6 prior lines of therapy, including tandem autologous stem cell transplant and several polychemotherapeutic regimens.
The patient was therapy-free for 4 months prior to receiving PAT-SM6. The patient requested salvage therapy 1 month after receiving PAT-SM6.
Patient 11, who received PAT-SM6 at 6mg/kg, had 4 prior lines of therapy and was refractory to both lenalidomide and thalidomide.
The patient’s treatment-free interval prior to PAT-SM6 was 12 months. After PAT-SM6, the patient was therapy-free for 5.2 months.
The researchers said additional trials testing PAT-SM6 in combination with other MM therapies are planned. PAT-SM6 has received orphan drug designation for MM in the US and the European Union.
Vitamin A as malaria prophylaxis
Photo by Sarah Mattison
New research suggests vitamin A may reduce the risk of malaria in young children.
The study showed that children under 5 living in sub-Saharan Africa were 54% less likely to develop malaria if they had been given a single, large dose of vitamin A.
The finding, published in eLife, indicates that vitamin A may be able to protect children from the malaria parasite, especially if administered during the wet season, when malaria-infected mosquitos are most prevalent.
“Now, we need to test vitamin A in a randomized, controlled, clinical trial to better understand whether this could really be an effective way to prevent this disease,” said study author Maria-Graciela Hollm-Delgado, PhD, of the Johns Hopkins Bloomberg School of Public Health in Baltimore, Maryland.
Dr Hollm-Delgado and her colleagues analyzed national survey data from 4 sub-Saharan countries—Burkina Faso, Mozambique, Rwanda, and Senegal—on children between the ages of 6 months and 59 months.
The goal was to determine the risk of Plasmodium parasitemia (n=8390) and Plasmodium falciparum-specific antigenemia (n=6121) following vitamin A supplementation and vaccinations.
The researchers found the measles and polio vaccines were not associated with malaria. And Bacille Calmette Guerin vaccination was associated with an increased risk of antigenemia (relative risk [RR]=4.06) but not parasitemia.
Only vitamin A was protective against malaria. Children who received vitamin A were less likely to present with parasitemia (RR=0.46) and antigenemia (RR=0.23).
Vitamin A appeared to be more protective under certain circumstances, including when administered during the rainy season, as well as when given to older children and when more time had passed since supplementation.
The researchers aren’t certain why vitamin A would reduce the rate of malaria infection, but they suspect it is because vitamin A, which is known to boost immunity and improve the ability to fight off infection, may help the body clear out the malaria parasite more quickly.
Only 62% of children in the study had received vitamin A supplementation, even though World Health Organization guidelines recommend that all children in sub-Saharan Africa receive a single, large dose of vitamin A.
Rates were higher for many vaccinations, Dr Hollm-Delgado said, noting that the guidelines for vitamin A aren’t as specific as they are for most vaccinations.
Photo by Sarah Mattison
New research suggests vitamin A may reduce the risk of malaria in young children.
The study showed that children under 5 living in sub-Saharan Africa were 54% less likely to develop malaria if they had been given a single, large dose of vitamin A.
The finding, published in eLife, indicates that vitamin A may be able to protect children from the malaria parasite, especially if administered during the wet season, when malaria-infected mosquitos are most prevalent.
“Now, we need to test vitamin A in a randomized, controlled, clinical trial to better understand whether this could really be an effective way to prevent this disease,” said study author Maria-Graciela Hollm-Delgado, PhD, of the Johns Hopkins Bloomberg School of Public Health in Baltimore, Maryland.
Dr Hollm-Delgado and her colleagues analyzed national survey data from 4 sub-Saharan countries—Burkina Faso, Mozambique, Rwanda, and Senegal—on children between the ages of 6 months and 59 months.
The goal was to determine the risk of Plasmodium parasitemia (n=8390) and Plasmodium falciparum-specific antigenemia (n=6121) following vitamin A supplementation and vaccinations.
The researchers found the measles and polio vaccines were not associated with malaria. And Bacille Calmette Guerin vaccination was associated with an increased risk of antigenemia (relative risk [RR]=4.06) but not parasitemia.
Only vitamin A was protective against malaria. Children who received vitamin A were less likely to present with parasitemia (RR=0.46) and antigenemia (RR=0.23).
Vitamin A appeared to be more protective under certain circumstances, including when administered during the rainy season, as well as when given to older children and when more time had passed since supplementation.
The researchers aren’t certain why vitamin A would reduce the rate of malaria infection, but they suspect it is because vitamin A, which is known to boost immunity and improve the ability to fight off infection, may help the body clear out the malaria parasite more quickly.
Only 62% of children in the study had received vitamin A supplementation, even though World Health Organization guidelines recommend that all children in sub-Saharan Africa receive a single, large dose of vitamin A.
Rates were higher for many vaccinations, Dr Hollm-Delgado said, noting that the guidelines for vitamin A aren’t as specific as they are for most vaccinations.
Photo by Sarah Mattison
New research suggests vitamin A may reduce the risk of malaria in young children.
The study showed that children under 5 living in sub-Saharan Africa were 54% less likely to develop malaria if they had been given a single, large dose of vitamin A.
The finding, published in eLife, indicates that vitamin A may be able to protect children from the malaria parasite, especially if administered during the wet season, when malaria-infected mosquitos are most prevalent.
“Now, we need to test vitamin A in a randomized, controlled, clinical trial to better understand whether this could really be an effective way to prevent this disease,” said study author Maria-Graciela Hollm-Delgado, PhD, of the Johns Hopkins Bloomberg School of Public Health in Baltimore, Maryland.
Dr Hollm-Delgado and her colleagues analyzed national survey data from 4 sub-Saharan countries—Burkina Faso, Mozambique, Rwanda, and Senegal—on children between the ages of 6 months and 59 months.
The goal was to determine the risk of Plasmodium parasitemia (n=8390) and Plasmodium falciparum-specific antigenemia (n=6121) following vitamin A supplementation and vaccinations.
The researchers found the measles and polio vaccines were not associated with malaria. And Bacille Calmette Guerin vaccination was associated with an increased risk of antigenemia (relative risk [RR]=4.06) but not parasitemia.
Only vitamin A was protective against malaria. Children who received vitamin A were less likely to present with parasitemia (RR=0.46) and antigenemia (RR=0.23).
Vitamin A appeared to be more protective under certain circumstances, including when administered during the rainy season, as well as when given to older children and when more time had passed since supplementation.
The researchers aren’t certain why vitamin A would reduce the rate of malaria infection, but they suspect it is because vitamin A, which is known to boost immunity and improve the ability to fight off infection, may help the body clear out the malaria parasite more quickly.
Only 62% of children in the study had received vitamin A supplementation, even though World Health Organization guidelines recommend that all children in sub-Saharan Africa receive a single, large dose of vitamin A.
Rates were higher for many vaccinations, Dr Hollm-Delgado said, noting that the guidelines for vitamin A aren’t as specific as they are for most vaccinations.
Hospital Renovation Patient Satisfaction
Hospitals are expensive and complex facilities to build and renovate. It is estimated $200 billion is being spent in the United States during this decade on hospital construction and renovation, and further expenditures in this area are expected.[1] Aging hospital infrastructure, competition, and health system expansion have motivated institutions to invest in renovation and new hospital building construction.[2, 3, 4, 5, 6, 7] There is a trend toward patient‐centered design in new hospital construction. Features of this trend include same‐handed design (ie, rooms on a unit have all beds oriented in the same direction and do not share headwalls); use of sound absorbent materials to reduced ambient noise[7, 8, 9]; rooms with improved view and increased natural lighting to reduce anxiety, decrease delirium, and increase sense of wellbeing[10, 11, 12]; incorporation of natural elements like gardens, water features, and art[12, 13, 14, 15, 16, 17, 18]; single‐patient rooms to reduce transmission of infection and enhance privacy and visitor comfort[7, 19, 20]; presence of comfortable waiting rooms and visitor accommodations to enhance comfort and family participation[21, 22, 23]; and hotel‐like amenities such as on‐demand entertainment and room service menus.[24, 25]
There is a belief among some hospital leaders that patients are generally unable to distinguish their positive experience with a pleasing healthcare environment from their positive experience with care, and thus improving facilities will lead to improved satisfaction across the board.[26, 27] In a controlled study of hospitalized patients, appealing rooms were associated with increased satisfaction with services including housekeeping and food service staff, meals, as well as physicians and overall satisfaction.[26] A 2012 survey of hospital leadership found that expanding and renovating facilities was considered a top priority in improving patient satisfaction, with 82% of the respondents stating that this was important.[27]
Despite these attitudes, the impact of patient‐centered design on patient satisfaction is not well understood. Studies have shown that renovations and hospital construction that incorporates noise reduction strategies, positive distraction, patient and caregiver control, attractive waiting rooms, improved patient room appearance, private rooms, and large windows result in improved satisfaction with nursing, noise level, unit environment and cleanliness, perceived wait time, discharge preparedness, and overall care. [7, 19, 20, 23, 28] However, these studies were limited by small sample size, inclusion of a narrow group of patients (eg, ambulatory, obstetric, geriatric rehabilitation, intensive care unit), and concurrent use of interventions other than design improvement (eg, nurse and patient education). Many of these studies did not use the ubiquitous Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) and Press Ganey patient satisfaction surveys.
We sought to determine the changes in patient satisfaction that occurred during a natural experiment, in which clinical units (comprising stable nursing, physician, and unit teams) were relocated from an historic clinical building to a new clinical building that featured patient‐centered design, using HCAHPS and Press Ganey surveys and a large study population. We hypothesized that new building features would positively impact both facility related (eg, noise level), nonfacility related (eg, physician and housekeeping service related), and overall satisfaction.
METHODS
This was a retrospective analysis of prospectively collected Press Ganey and HCAPHS patient satisfaction survey data for a single academic tertiary care hospital.[29] The research project was reviewed and approved by the institutional review board.
Participants
All patients discharged from 12 clinical units that relocated to the new clinical building and returned patient satisfaction surveys served as study patients. The moved units included the coronary care unit, cardiac step down unit, medical intensive care unit, neuro critical care unit, surgical intensive care unit, orthopedic unit, neurology unit, neurosurgery unit, obstetrics units, gynecology unit, urology unit, cardiothoracic surgery unit, and the transplant surgery and renal transplant unit. Patients on clinical units that did not move served as concurrent controls.
Exposure
Patients admitted to the new clinical building experienced several patient‐centered design features. These features included easy access to healing gardens with a water feature, soaring lobbies, a collection of more than 500 works of art, well‐decorated and light‐filled patient rooms with sleeping accommodations for family members, sound‐absorbing features in patient care corridors ranging from acoustical ceiling tiles to a quiet nurse‐call system, and an interactive television network with Internet, movies, and games. All patients during the baseline period and control patients during the study period were located in typical patient rooms with standard hospital amenities. No other major patient satisfaction interventions were initiated during the pre‐ or postperiod in either arm of the study; ongoing patient satisfaction efforts (such as unit‐based customer care representatives) were deployed broadly and not restricted to the new clinical building. Clinical teams comprised of physicians, nurses, and ancillary staff did not change significantly after the move.
Time Periods
The move to new clinical building occurred on May 1, 2012. After allowing for a 15‐day washout period, the postmove period included Press Ganey and HCAHPS surveys returned for discharges that occurred during a 7.5‐month period between May 15, 2102 and December 31, 2012. Baseline data included Press Ganey and HCAHPS surveys returned for discharges in the preceding 12 months (May 1, 2011 to April 30, 2012). Sensitivity analysis using only 7.5 months of baseline data did not reveal any significant difference when compared with 12‐month baseline data, and we report only data from the 12‐month baseline period.
Instruments
Press Ganey and HCAHPS patient satisfaction surveys were sent via mail in the same envelope. Fifty percent of the discharged patients were randomized to receive the surveys. The Press Ganey survey contained 33 items covering across several subdomains including room, meal, nursing, physician, ancillary staff, visitor, discharge, and overall satisfaction. The HCAHPS survey contained 29 Centers for Medicare and Medicaid Services (CMS)‐mandated items, of which 21 are related to patient satisfaction. The development and testing and methods for administration and reporting of the HCAHPS survey have been previously described.[30, 31] Press Ganey patient satisfaction survey results have been reported in the literature.[32, 33]
Outcome Variables
Press Ganey and HCAHPS patient satisfaction survey responses were the primary outcome variables of the study. The survey items were categorized as facility related (eg, noise level), nonfacility related (eg, physician and nursing staff satisfaction), and overall satisfaction related.
Covariates
Age, sex, length of stay (LOS), insurance type, and all‐payer refined diagnosis‐related groupassociated illness complexity were included as covariates.
Statistical Analysis
Percent top‐box scores were calculated for each survey item as the percent of patients who responded very good for a given item on Press Ganey survey items and always or definitely yes or 9 or 10 on HCAHPS survey items. CMS utilizes percent top‐box scores to calculate payments under the Value Based Purchasing (VBP) program and to report the results publicly. Numerous studies have also reported percent top‐box scores for HCAHPS survey results.[31, 32, 33, 34]
Odds ratios of premove versus postmove percentage of top‐box scores, adjusted for age, sex, LOS, complexity of illness, and insurance type were determined using logistic regression for the units that moved. Similar scores were calculated for unmoved units to detect secular trends. To determine whether the differences between the moved and unmoved units were significant, we introduced the interaction term (moved vs unmoved unit status) (pre‐ vs postmove time period) into the logistic regression models and examined the adjusted P value for this term. All statistical analysis was performed using SAS Institute Inc.'s (Cary, NC) JMP Pro 10.0.0.
RESULTS
The study included 1648 respondents in the moved units in the baseline period (ie, units designated to move to a new clinical building) and 1373 respondents in the postmove period. There were 1593 respondents in the control group during the baseline period and 1049 respondents in the postmove period. For the units that moved, survey response rates were 28.5% prior to the move and 28.3% after the move. For the units that did not move, survey response rates were 20.9% prior to the move and 22.7% after the move. A majority of survey respondents on the nursing units that moved were white, male, and had private insurance (Table 1). There were no significant differences between respondents across these characteristics between the pre‐ and postmove periods. Mean age and LOS were also similar. For these units, there were 70.5% private rooms prior to the move and 100% after the move. For the unmoved units, 58.9% of the rooms were private in the baseline period and 72.7% were private in the study period. Similar to the units that moved, characteristics of the respondents on the unmoved units also did not differ significantly in the postmove period.
| Patient demographics | Moved Units (N=3,021) | Unmoved Units (N=2,642) | ||||
|---|---|---|---|---|---|---|
| Pre | Post | P Value | Pre | Post | P Value | |
| ||||||
| White | 75.3% | 78.2% | 0.07 | 66.7% | 68.5% | 0.31 |
| Mean age, y | 57.3 | 57.4 | 0.84 | 57.3 | 57.1 | 0.81 |
| Male | 54.3% | 53.0% | 0.48 | 40.5% | 42.3% | 0.23 |
| Self‐reported health | ||||||
| Excellent or very good | 54.7% | 51.2% | 0.04 | 38.7% | 39.5% | 0.11 |
| Good | 27.8% | 32.0% | 29.3% | 32.2% | ||
| Fair or poor | 17.5% | 16.9% | 32.0% | 28.3% | ||
| Self‐reported language | ||||||
| English | 96.0% | 97.2% | 0.06 | 96.8% | 97.1% | 0.63 |
| Other | 4.0% | 2.8% | 3.2% | 2.9% | ||
| Self‐reported education | ||||||
| Less than high school | 5.8% | 5.0% | 0.24 | 10.8% | 10.4% | 0.24 |
| High school grad | 46.4% | 44.2% | 48.6% | 45.5% | ||
| College grad or more | 47.7% | 50.7% | 40.7% | 44.7% | ||
| Insurance type | ||||||
| Medicaid | 6.7% | 5.5% | 0.11 | 10.8% | 9.0% | 0.32 |
| Medicare | 32.0% | 35.5% | 36.0% | 36.1% | ||
| Private insurance | 55.6% | 52.8% | 48.0% | 50.3% | ||
| Mean APRDRG complexity* | 2.1 | 2.1 | 0.09 | 2.3 | 2.3 | 0.14 |
| Mean LOS | 4.7 | 5.0 | 0.12 | 4.9 | 5.0 | 0.77 |
| Service | ||||||
| Medicine | 15.4% | 16.2% | 0.51 | 40.0% | 34.5% | 0.10 |
| Surgery | 50.7% | 45.7% | 40.1% | 44.1% | ||
| Neurosciences | 20.3% | 24.1% | 6.0% | 6.0% | ||
| Obstetrics/gynecology | 7.5% | 8.2% | 5.7% | 5.6% | ||
The move was associated with significant improvements in facility‐related satisfaction (Tables 2 and 3). The most prominent increases in satisfaction were with pleasantness of dcor (33.6% vs 66.2%), noise level (39.9% vs 59.3%), and visitor accommodation and comfort (50.0% vs 70.3 %). There was improvement in satisfaction related to cleanliness of the room (49.0% vs 68.6 %), but no significant increase in satisfaction with courtesy of the person cleaning the room (59.8% vs 67.7%) when compared with units that did move.
| Satisfaction Domain | Moved Units | Unmoved Units | P Value of the Difference in Odds Ratio Between Moved and Unmoved Units | |||||
|---|---|---|---|---|---|---|---|---|
| % Top Box | Adjusted Odds Ratio* (95% CI) | % Top Box | Adjusted Odds Ratio* (95% CI) | |||||
| Pre | Post | Pre | Post | |||||
| ||||||||
| FACILITY RELATED | ||||||||
| Hospital environment | ||||||||
| Cleanliness of the room and bathroom | 61.0 | 70.8 | 1.62 (1.40‐1.90) | 64.0 | 69.2 | 1.24 (1.03‐1.48) | 0.03 | |
| Quietness of the room | 51.3 | 65.4 | 1.89 (1.63‐2.19) | 58.6 | 60.3 | 1.08 (0.90‐1.28) | <0.0001 | |
| NONFACILITY RELATED | ||||||||
| Nursing communication | ||||||||
| Nurses treated with courtesy/respect | 84.0 | 86.7 | 1.28 (1.05‐1.57) | 83.6 | 87.1 | 1.29 (1.02‐1.64) | 0.92 | |
| Nurses listened | 73.1 | 76.4 | 1.21 (1.03‐1.43) | 74.2 | 75.5 | 1.05 (0.86‐1.27) | 0.26 | |
| Nurses explained | 75.0 | 76.6 | 1.10 (0.94‐1.30) | 76.0 | 76.2 | 1.00 (0.82‐1.21) | 0.43 | |
| Physician communication | ||||||||
| Doctors treated with courtesy/respect | 89.5 | 90.5 | 1.13 (0.89‐1.42) | 84.9 | 87.3 | 1.20 (0.94‐1.53) | 0.77 | |
| Doctors listened | 81.4 | 81.0 | 0.93 (0.83‐1.19) | 77.7 | 77.1 | 0.94 (0.77‐1.15) | 0.68 | |
| Doctors explained | 79.2 | 79.0 | 1.00(0.84‐1.19) | 75.7 | 74.4 | 0.92 (0.76‐1.12) | 0.49 | |
| Other | ||||||||
| Help toileting as soon as you wanted | 61.8 | 63.7 | 1.08 (0.89‐1.32) | 62.3 | 60.6 | 0.92 (0.71‐1.18) | 0.31 | |
| Pain well controlled | 63.2 | 63.8 | 1.06 (0.90‐1.25) | 62.0 | 62.6 | 0.99 (0.81‐1.20) | 060 | |
| Staff do everything to help with pain | 77.7 | 80.1 | 1.19 (0.99‐1.44) | 76.8 | 75.7 | 0.90 (0.75‐1.13) | 0.07 | |
| Staff describe medicine side effects | 47.0 | 47.6 | 1.05 (0.89‐1.24) | 49.2 | 47.1 | 0.91 (0.74‐1.11) | 0.32 | |
| Tell you what new medicine was for | 76.4 | 76.4 | 1.02 (0.84‐1.25) | 77.1 | 78.8 | 1.09(0.85‐1.39) | 0.65 | |
| Overall | ||||||||
| Rate hospital (010) | 75.0 | 83.3 | 1.71 (1.44‐2.05) | 75.7 | 77.6 | 1.06 (0.87‐1.29) | 0.006 | |
| Recommend hospital | 82.5 | 87.1 | 1.43 (1.18‐1.76) | 81.4 | 82.0 | 0.98 (0.79‐1.22) | 0.03 | |
| Satisfaction Domain | Moved Unit | Unmoved Unit | P Value of the Difference in Odds Ratio Between Moved and Unmoved Units | ||||
|---|---|---|---|---|---|---|---|
| % Top Box | Adjusted Odds Ratio* (95% CI) | % Top Box | Adjusted Odds Ratio* (95% CI) | ||||
| Pre | Post | Pre | Post | ||||
| |||||||
| FACILITY RELATED | |||||||
| Room | |||||||
| Pleasantness of room dcor | 33.6 | 64.8 | 3.77 (3.24‐4.38) | 41.6 | 47.0 | 1.21 (1.02‐1.44) | <0.0001 |
| Room cleanliness | 49.0 | 68.6 | 2.35 (2.02‐2.73) | 51.6 | 59.1 | 1.32 (1.12‐1.58) | <0.0001 |
| Room temperature | 43.1 | 54.9 | 1.64 (1.43‐1.90) | 45.0 | 48.8 | 1.14 (0.96‐1.36) | 0.002 |
| Noise level in and around the room | 40.2 | 59.2 | 2.23 (1.92‐2.58) | 45.5 | 47.6 | 1.07 (0.90‐1.22) | <0.0001 |
| Visitor related | |||||||
| Accommodations and comfort of visitors | 50.0 | 70.3 | 2.44 (2.10‐2.83) | 55.3 | 59.1 | 1.14 (0.96‐1.35) | <0.0001 |
| NONFACILITY RELATED | |||||||
| Food | |||||||
| Temperature of the food | 31.1 | 33.6 | 1.15 (0.99‐1.34) | 34.0 | 38.9 | 1.23 (1.02‐1.47) | 0.51 |
| Quality of the food | 25.8 | 27.1 | 1.10 (0.93‐1.30) | 30.2 | 36.2 | 1.32 (1.10‐1.59) | 0.12 |
| Courtesy of the person who served food | 63.9 | 62.3 | 0.93 (0.80‐1.10) | 66.0 | 61.4 | 0.82 (0.69‐0.98) | 0.26 |
| Nursing | |||||||
| Friendliness/courtesy of the nurses | 76.3 | 82.8 | 1.49 (1.26‐1.79) | 77.7 | 80.1 | 1.10 (0.90‐1.37) | 0.04 |
| Promptness of response to call | 60.1 | 62.6 | 1.14 (0.98‐1.33) | 59.2 | 62.0 | 1.10 (0.91‐1.31) | 0.80 |
| Nurses' attitude toward requests | 71.0 | 75.8 | 1.30 (1.11‐1.54) | 70.5 | 72.4 | 1.06 (0.88‐1.28) | 0.13 |
| Attention to special/personal needs | 66.7 | 72.2 | 1.32 (1.13‐1.54) | 67.8 | 70.3 | 1.09 (0.91‐1.31) | 0.16 |
| Nurses kept you informed | 64.3 | 72.2 | 1.46 (1.25‐1.70) | 65.8 | 69.8 | 1.17 (0.98‐1.41) | 0.88 |
| Skill of the nurses | 75.3 | 79.5 | 1.28 (1.08‐1.52) | 74.3 | 78.6 | 1.23 (1.01‐1.51) | 0.89 |
| Ancillary staff | |||||||
| Courtesy of the person cleaning the room | 59.8 | 67.7 | 1.41 (1.21‐1.65) | 61.2 | 66.5 | 1.24 (1.03‐1.49) | 0.28 |
| Courtesy of the person who took blood | 66.5 | 68.1 | 1.10 (0.94‐1.28) | 63.2 | 63.1 | 0.96 (0.76‐1.08) | 0.34 |
| Courtesy of the person who started the IV | 70.0 | 71.7 | 1.09 (0.93‐1.28) | 66.6 | 69.3 | 1.11 (0.92‐1.33) | 0.88 |
| Visitor related | |||||||
| Staff attitude toward visitors | 68.1 | 79.4 | 1.84 (1.56‐2.18) | 70.3 | 72.2 | 1.06 (0.87‐1.28) | <0.0001 |
| Physician | |||||||
| Time physician spent with you | 55.0 | 58.9 | 1.20 (1.04‐1.39) | 53.2 | 55.9 | 1.10 (0.92‐1.30) | 0.46 |
| Physician concern questions/worries | 67.2 | 70.7 | 1.20 (1.03‐1.40) | 64.3 | 66.1 | 1.05 (0.88‐1.26) | 0.31 |
| Physician kept you informed | 65.3 | 67.5 | 1.12 (0.96‐1.30) | 61.6 | 63.2 | 1.05 (0.88‐1.25) | 0.58 |
| Friendliness/courtesy of physician | 76.3 | 78.1 | 1.11 (0.93‐1.31) | 71.0 | 73.3 | 1.08 (0.90‐1.31) | 0.89 |
| Skill of physician | 85.4 | 88.5 | 1.35 (1.09‐1.68) | 78.0 | 81.0 | 1.15 (0.93‐1.43) | 0.34 |
| Discharge | |||||||
| Extent felt ready for discharge | 62.0 | 66.7 | 1.23 (1.07‐1.44) | 59.2 | 62.3 | 1.10 (0.92‐1.30) | 0.35 |
| Speed of discharge process | 50.7 | 54.2 | 1.16 (1.01‐1.33) | 47.8 | 50.0 | 1.07 (0.90‐1.27) | 0.49 |
| Instructions for care at home | 66.4 | 71.1 | 1.25 (1.06‐1.46) | 64.0 | 67.7 | 1.16 (0.97‐1.39) | 0.54 |
| Staff concern for your privacy | 65.3 | 71.8 | 1.37 (1.17‐0.85) | 63.6 | 66.2 | 1.10 (0.91‐1.31) | 0.07 |
| Miscellaneous | |||||||
| How well your pain was controlled | 64.2 | 66.5 | 1.14 (0.97‐1.32) | 60.2 | 62.6 | 1.07 (0.89‐1.28) | 0.66 |
| Staff addressed emotional needs | 60.0 | 63.4 | 1.19 (1.02‐1.38) | 55.1 | 60.2 | 1.20 (1.01‐1.42) | 0.90 |
| Response to concerns/complaints | 61.1 | 64.5 | 1.19 (1.02‐1.38) | 57.2 | 60.1 | 1.10 (0.92‐1.31) | 0.57 |
| Overall | |||||||
| Staff worked together to care for you | 72.6 | 77.2 | 1.29 (1.10‐1.52) | 70.3 | 73.2 | 1.13 (0.93‐1.37) | 0.30 |
| Likelihood of recommending hospital | 79.1 | 84.3 | 1.44 (1.20‐1.74) | 76.3 | 79.2 | 1.14 (0.93‐1.39) | 0.10 |
| Overall rating of care given | 76.8 | 83.0 | 1.50 (1.25‐1.80) | 74.7 | 77.2 | 1.10 (0.90‐1.34) | 0.03 |
With regard to nonfacility‐related satisfaction, there were statistically higher scores in several nursing, physician, and discharge‐related satisfaction domains after the move. However, these changes were not associated with the move to the new clinical building as they were not significantly different from improvements on the unmoved units. Among nonfacility‐related items, only staff attitude toward visitors showed significant improvement (68.1% vs 79.4%). There was a significant improvement in hospital rating (75.0% vs 83.3% in the moved units and 75.7% vs 77.6% in the unmoved units). However, the other 3 measures of overall satisfaction did not show significant improvement associated with the move to the new clinical building when compared to the concurrent controls.
DISCUSSION
Contrary to our hypothesis and a belief held by many, we found that patients appeared able to distinguish their experience with hospital environment from their experience with providers and other services. Improvement in hospital facilities with incorporation of patient‐centered features was associated with improvements that were largely limited to increases in satisfaction with quietness, cleanliness, temperature, and dcor of the room along with visitor‐related satisfaction. Notably, there was no significant improvement in satisfaction related to physicians, nurses, housekeeping, and other service staff. There was improvement in satisfaction with staff attitude toward visitors, but this can be attributed to availability of visitor‐friendly facilities. There was a significant improvement in 1 of the 4 measures of overall satisfaction. Our findings also support the construct validity of HCAHPS and Press Ganey patient satisfaction surveys.
Ours is one of the largest studies on patient satisfaction related to patient‐centered design features in the inpatient acute care setting. Swan et al. also studied patients in an acute inpatient setting and compared satisfaction related to appealing versus typical hospital rooms. Patients were matched for case mix, insurance, gender, types of medical services received and LOS, and were served by the same set of physicians and similar food service and housekeeping staff.[26] Unlike our study, they found improved satisfaction related to physicians, housekeeping staff, food service staff, meals, and overall satisfaction. However, the study had some limitations. In particular, the study sample was self‐selected because the patients in this group were required to pay an extra daily fee to utilize the appealing room. Additionally, there were only 177 patients across the 2 groups, and the actual differences in satisfaction scores were small. Our sample was larger and patients in the study group were admitted to units in the new clinical buildings by the same criteria as they were admitted to the historic building prior to the move, and there were no significant differences in baseline characteristics between the comparison groups.
Jansen et al. also found broad improvements in patient satisfaction in a study of over 309 maternity unit patients in a new construction, all private‐room maternity unit with more appealing design elements and comfort features for visitors.[7] Improved satisfaction was noted with the physical environment, nursing care, assistance with feeding, respect for privacy, and discharge planning. However, it is difficult to extrapolate the results of this study to other settings, as maternity unit patients constitute a unique patient demographic with unique care needs. Additionally, when compared with patients in the control group, the patients in the study group were cared for by nurses who had a lower workload and who were not assigned other patients with more complex needs. Because nursing availability may be expected to impact satisfaction with clinical domains, the impact of private and appealing room may very well have been limited to improved satisfaction with the physical environment.
Despite the widespread belief among healthcare leadership that facility renovation or expansion is a vital strategy for improving patient satisfaction, our study shows that this may not be a dominant factor.[27] In fact, the Planetree model showed that improvement in satisfaction related to physical environment and nursing care was associated with implementation of both patient‐centered design features as well as with utilization of nurses that were trained to provide personalized care, educate patients, and involve patients and family.[28] It is more likely that provider‐level interventions will have a greater impact on provider level and overall satisfaction. This idea is supported by a recent JD Powers study suggesting that facilities represent only 19% of overall satisfaction in the inpatient setting.[35]
Although our study focused on patient‐centered design features, several renovation and construction projects have also focused on design features that improve patient safety and provider satisfaction, workflow, efficiency, productivity, stress, and time spent in direct care.[9] Interventions in these areas may lead to improvement in patient outcomes and perhaps lead to improvement in patient satisfaction; however, this relationship has not been well established at present.
In an era of cost containment, healthcare administrators are faced with high‐priced interventions, competing needs, limited resources, low profit margins, and often unclear evidence on cost‐effectiveness and return on investment of healthcare design features. Benefits are related to competitive advantage, higher reputation, patient retention, decreased malpractice costs, and increased Medicare payments through VBP programs that incentivize improved performance on quality metrics and patient satisfaction surveys. Our study supports the idea that a significant improvement in patient satisfaction related to creature comforts can be achieved with investment in patient‐centered design features. However, our findings also suggest that institutions should perform an individualized cost‐benefit analysis related to improvements in this narrow area of patient satisfaction. In our study, incorporation of patient‐centered design features resulted in improvement on 2 VBP HCAHPS measures, and its contribution toward total performance score under the VBP program would be limited.
Strengths of our study include the use of concurrent controls and our ability to capitalize on a natural experiment in which care teams remained constant before and after a move to a new clinical building. However, our study has some limitations. It was conducted at a single tertiary care academic center that predominantly serves an inner city population and referral patients seeking specialized care. Drivers of patient satisfaction may be different in community hospitals, and a different relationship may be observed between patient‐centered design and domains of patient satisfaction in this setting. Further studies in different hospital settings are needed to confirm our findings. Additionally, we were limited by the low response rate of the surveys. However, this is a widespread problem with all patient satisfaction research utilizing voluntary surveys, and our response rates are consistent with those previously reported.[34, 36, 37, 38] Furthermore, low response rates have not impeded the implementation of pay‐for‐performance programs on a national scale using HCHAPS.
In conclusion, our study suggests that hospitals should not use outdated facilities as an excuse for achievement of suboptimal satisfaction scores. Patients respond positively to creature comforts, pleasing surroundings, and visitor‐friendly facilities but can distinguish these positive experiences from experiences in other patient satisfaction domains. In our study, the move to a higher‐amenity building had only a modest impact on overall patient satisfaction, perhaps because clinical care is the primary driver of this outcome. Contrary to belief held by some hospital leaders, major strides in overall satisfaction across the board and other subdomains of satisfaction likely require intervention in areas other than facility renovation and expansion.
Disclosures
Zishan Siddiqui, MD, was supported by the Osler Center of Clinical Excellence Faculty Scholarship Grant. Funds from Johns Hopkins Hospitalist Scholars Program supported the research project. The authors have no conflict of interests to disclose.
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- , , , . Same‐handed and mirrored unit configurations: is there a difference in patient and nurse outcomes? J Nurs Adm. 2011;41(6):273–279.
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- , , . Effects of exposure to nature and abstract pictures on patients recovering from open heart surgery. J Soc Psychophysiol Res. 1993;30:7.
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- , , , . Post‐occupancy evaluation of healing gardens in a pediatric cancer center. Landsc Urban Plan. 2005;73(2):167–183.
- . Healing gardens in hospitals. Interdiscip Des Res J. 2007;1(1):1–27.
- , . Restorative gardens. BMJ. 1993;306(6885):1080–1081.
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- , . Sunny hospital rooms expedite recovery from severe and refractory depressions. J Affect Disord. 1996;40(1‐2):49–51.
- . Art in hospital spaces: the role of hospitals in an aestheticised society. Int J Cult Policy. 2007;13(1):85–101.
- , , . Renovation of a semiprivate patient room. Bowman Center Geriatric Rehabilitation Unit. Nurs Clin North Am 1995;30(1):97–115.
- , , , et al. (2013). Effect of intensive care environment on family and patient satisfaction: a before‐after study. Intensive Care Med. 2013;39(9):1626–1634.
- , , , , . Outcomes of environmental appraisal of different hospital waiting areas. Environ Behav. 2003;35(6):842–869.
- . Redesigning the neurocritical care unit to enhance family participation and improve outcomes. Cleve Clin J Med. 2009;76(suppl 2):S70–S74.
- , . The ecology of the patient visit: physical attractiveness, waiting times, and perceived quality of care. J Ambul Care Manage. 2008;31(2):128–141.
- . Patient satisfaction and the new consumer. Hosp Health Netw. 2006;80(57):59–62.
- . Patient satisfaction. Hospitals embrace hotel‐like amenities. Hosp Health Netw. 2007;81(11):24–26.
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- . Patient experience and HCAHPS: little consensus on a top priority. Health Leaders Media website. Available at http://www.healthleadersmedia.com/intelligence/detail.cfm?content_id=28289334(2):125–133.
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- Hospital Consumer Assessment of Healthcare Providers and Systems. Summary analysis. http://www.hcahpsonline.org/SummaryAnalyses.aspx. Accessed October 1, 2014.
- Centers for Medicare 44(2 pt 1):501–518.
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Hospitals are expensive and complex facilities to build and renovate. It is estimated $200 billion is being spent in the United States during this decade on hospital construction and renovation, and further expenditures in this area are expected.[1] Aging hospital infrastructure, competition, and health system expansion have motivated institutions to invest in renovation and new hospital building construction.[2, 3, 4, 5, 6, 7] There is a trend toward patient‐centered design in new hospital construction. Features of this trend include same‐handed design (ie, rooms on a unit have all beds oriented in the same direction and do not share headwalls); use of sound absorbent materials to reduced ambient noise[7, 8, 9]; rooms with improved view and increased natural lighting to reduce anxiety, decrease delirium, and increase sense of wellbeing[10, 11, 12]; incorporation of natural elements like gardens, water features, and art[12, 13, 14, 15, 16, 17, 18]; single‐patient rooms to reduce transmission of infection and enhance privacy and visitor comfort[7, 19, 20]; presence of comfortable waiting rooms and visitor accommodations to enhance comfort and family participation[21, 22, 23]; and hotel‐like amenities such as on‐demand entertainment and room service menus.[24, 25]
There is a belief among some hospital leaders that patients are generally unable to distinguish their positive experience with a pleasing healthcare environment from their positive experience with care, and thus improving facilities will lead to improved satisfaction across the board.[26, 27] In a controlled study of hospitalized patients, appealing rooms were associated with increased satisfaction with services including housekeeping and food service staff, meals, as well as physicians and overall satisfaction.[26] A 2012 survey of hospital leadership found that expanding and renovating facilities was considered a top priority in improving patient satisfaction, with 82% of the respondents stating that this was important.[27]
Despite these attitudes, the impact of patient‐centered design on patient satisfaction is not well understood. Studies have shown that renovations and hospital construction that incorporates noise reduction strategies, positive distraction, patient and caregiver control, attractive waiting rooms, improved patient room appearance, private rooms, and large windows result in improved satisfaction with nursing, noise level, unit environment and cleanliness, perceived wait time, discharge preparedness, and overall care. [7, 19, 20, 23, 28] However, these studies were limited by small sample size, inclusion of a narrow group of patients (eg, ambulatory, obstetric, geriatric rehabilitation, intensive care unit), and concurrent use of interventions other than design improvement (eg, nurse and patient education). Many of these studies did not use the ubiquitous Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) and Press Ganey patient satisfaction surveys.
We sought to determine the changes in patient satisfaction that occurred during a natural experiment, in which clinical units (comprising stable nursing, physician, and unit teams) were relocated from an historic clinical building to a new clinical building that featured patient‐centered design, using HCAHPS and Press Ganey surveys and a large study population. We hypothesized that new building features would positively impact both facility related (eg, noise level), nonfacility related (eg, physician and housekeeping service related), and overall satisfaction.
METHODS
This was a retrospective analysis of prospectively collected Press Ganey and HCAPHS patient satisfaction survey data for a single academic tertiary care hospital.[29] The research project was reviewed and approved by the institutional review board.
Participants
All patients discharged from 12 clinical units that relocated to the new clinical building and returned patient satisfaction surveys served as study patients. The moved units included the coronary care unit, cardiac step down unit, medical intensive care unit, neuro critical care unit, surgical intensive care unit, orthopedic unit, neurology unit, neurosurgery unit, obstetrics units, gynecology unit, urology unit, cardiothoracic surgery unit, and the transplant surgery and renal transplant unit. Patients on clinical units that did not move served as concurrent controls.
Exposure
Patients admitted to the new clinical building experienced several patient‐centered design features. These features included easy access to healing gardens with a water feature, soaring lobbies, a collection of more than 500 works of art, well‐decorated and light‐filled patient rooms with sleeping accommodations for family members, sound‐absorbing features in patient care corridors ranging from acoustical ceiling tiles to a quiet nurse‐call system, and an interactive television network with Internet, movies, and games. All patients during the baseline period and control patients during the study period were located in typical patient rooms with standard hospital amenities. No other major patient satisfaction interventions were initiated during the pre‐ or postperiod in either arm of the study; ongoing patient satisfaction efforts (such as unit‐based customer care representatives) were deployed broadly and not restricted to the new clinical building. Clinical teams comprised of physicians, nurses, and ancillary staff did not change significantly after the move.
Time Periods
The move to new clinical building occurred on May 1, 2012. After allowing for a 15‐day washout period, the postmove period included Press Ganey and HCAHPS surveys returned for discharges that occurred during a 7.5‐month period between May 15, 2102 and December 31, 2012. Baseline data included Press Ganey and HCAHPS surveys returned for discharges in the preceding 12 months (May 1, 2011 to April 30, 2012). Sensitivity analysis using only 7.5 months of baseline data did not reveal any significant difference when compared with 12‐month baseline data, and we report only data from the 12‐month baseline period.
Instruments
Press Ganey and HCAHPS patient satisfaction surveys were sent via mail in the same envelope. Fifty percent of the discharged patients were randomized to receive the surveys. The Press Ganey survey contained 33 items covering across several subdomains including room, meal, nursing, physician, ancillary staff, visitor, discharge, and overall satisfaction. The HCAHPS survey contained 29 Centers for Medicare and Medicaid Services (CMS)‐mandated items, of which 21 are related to patient satisfaction. The development and testing and methods for administration and reporting of the HCAHPS survey have been previously described.[30, 31] Press Ganey patient satisfaction survey results have been reported in the literature.[32, 33]
Outcome Variables
Press Ganey and HCAHPS patient satisfaction survey responses were the primary outcome variables of the study. The survey items were categorized as facility related (eg, noise level), nonfacility related (eg, physician and nursing staff satisfaction), and overall satisfaction related.
Covariates
Age, sex, length of stay (LOS), insurance type, and all‐payer refined diagnosis‐related groupassociated illness complexity were included as covariates.
Statistical Analysis
Percent top‐box scores were calculated for each survey item as the percent of patients who responded very good for a given item on Press Ganey survey items and always or definitely yes or 9 or 10 on HCAHPS survey items. CMS utilizes percent top‐box scores to calculate payments under the Value Based Purchasing (VBP) program and to report the results publicly. Numerous studies have also reported percent top‐box scores for HCAHPS survey results.[31, 32, 33, 34]
Odds ratios of premove versus postmove percentage of top‐box scores, adjusted for age, sex, LOS, complexity of illness, and insurance type were determined using logistic regression for the units that moved. Similar scores were calculated for unmoved units to detect secular trends. To determine whether the differences between the moved and unmoved units were significant, we introduced the interaction term (moved vs unmoved unit status) (pre‐ vs postmove time period) into the logistic regression models and examined the adjusted P value for this term. All statistical analysis was performed using SAS Institute Inc.'s (Cary, NC) JMP Pro 10.0.0.
RESULTS
The study included 1648 respondents in the moved units in the baseline period (ie, units designated to move to a new clinical building) and 1373 respondents in the postmove period. There were 1593 respondents in the control group during the baseline period and 1049 respondents in the postmove period. For the units that moved, survey response rates were 28.5% prior to the move and 28.3% after the move. For the units that did not move, survey response rates were 20.9% prior to the move and 22.7% after the move. A majority of survey respondents on the nursing units that moved were white, male, and had private insurance (Table 1). There were no significant differences between respondents across these characteristics between the pre‐ and postmove periods. Mean age and LOS were also similar. For these units, there were 70.5% private rooms prior to the move and 100% after the move. For the unmoved units, 58.9% of the rooms were private in the baseline period and 72.7% were private in the study period. Similar to the units that moved, characteristics of the respondents on the unmoved units also did not differ significantly in the postmove period.
| Patient demographics | Moved Units (N=3,021) | Unmoved Units (N=2,642) | ||||
|---|---|---|---|---|---|---|
| Pre | Post | P Value | Pre | Post | P Value | |
| ||||||
| White | 75.3% | 78.2% | 0.07 | 66.7% | 68.5% | 0.31 |
| Mean age, y | 57.3 | 57.4 | 0.84 | 57.3 | 57.1 | 0.81 |
| Male | 54.3% | 53.0% | 0.48 | 40.5% | 42.3% | 0.23 |
| Self‐reported health | ||||||
| Excellent or very good | 54.7% | 51.2% | 0.04 | 38.7% | 39.5% | 0.11 |
| Good | 27.8% | 32.0% | 29.3% | 32.2% | ||
| Fair or poor | 17.5% | 16.9% | 32.0% | 28.3% | ||
| Self‐reported language | ||||||
| English | 96.0% | 97.2% | 0.06 | 96.8% | 97.1% | 0.63 |
| Other | 4.0% | 2.8% | 3.2% | 2.9% | ||
| Self‐reported education | ||||||
| Less than high school | 5.8% | 5.0% | 0.24 | 10.8% | 10.4% | 0.24 |
| High school grad | 46.4% | 44.2% | 48.6% | 45.5% | ||
| College grad or more | 47.7% | 50.7% | 40.7% | 44.7% | ||
| Insurance type | ||||||
| Medicaid | 6.7% | 5.5% | 0.11 | 10.8% | 9.0% | 0.32 |
| Medicare | 32.0% | 35.5% | 36.0% | 36.1% | ||
| Private insurance | 55.6% | 52.8% | 48.0% | 50.3% | ||
| Mean APRDRG complexity* | 2.1 | 2.1 | 0.09 | 2.3 | 2.3 | 0.14 |
| Mean LOS | 4.7 | 5.0 | 0.12 | 4.9 | 5.0 | 0.77 |
| Service | ||||||
| Medicine | 15.4% | 16.2% | 0.51 | 40.0% | 34.5% | 0.10 |
| Surgery | 50.7% | 45.7% | 40.1% | 44.1% | ||
| Neurosciences | 20.3% | 24.1% | 6.0% | 6.0% | ||
| Obstetrics/gynecology | 7.5% | 8.2% | 5.7% | 5.6% | ||
The move was associated with significant improvements in facility‐related satisfaction (Tables 2 and 3). The most prominent increases in satisfaction were with pleasantness of dcor (33.6% vs 66.2%), noise level (39.9% vs 59.3%), and visitor accommodation and comfort (50.0% vs 70.3 %). There was improvement in satisfaction related to cleanliness of the room (49.0% vs 68.6 %), but no significant increase in satisfaction with courtesy of the person cleaning the room (59.8% vs 67.7%) when compared with units that did move.
| Satisfaction Domain | Moved Units | Unmoved Units | P Value of the Difference in Odds Ratio Between Moved and Unmoved Units | |||||
|---|---|---|---|---|---|---|---|---|
| % Top Box | Adjusted Odds Ratio* (95% CI) | % Top Box | Adjusted Odds Ratio* (95% CI) | |||||
| Pre | Post | Pre | Post | |||||
| ||||||||
| FACILITY RELATED | ||||||||
| Hospital environment | ||||||||
| Cleanliness of the room and bathroom | 61.0 | 70.8 | 1.62 (1.40‐1.90) | 64.0 | 69.2 | 1.24 (1.03‐1.48) | 0.03 | |
| Quietness of the room | 51.3 | 65.4 | 1.89 (1.63‐2.19) | 58.6 | 60.3 | 1.08 (0.90‐1.28) | <0.0001 | |
| NONFACILITY RELATED | ||||||||
| Nursing communication | ||||||||
| Nurses treated with courtesy/respect | 84.0 | 86.7 | 1.28 (1.05‐1.57) | 83.6 | 87.1 | 1.29 (1.02‐1.64) | 0.92 | |
| Nurses listened | 73.1 | 76.4 | 1.21 (1.03‐1.43) | 74.2 | 75.5 | 1.05 (0.86‐1.27) | 0.26 | |
| Nurses explained | 75.0 | 76.6 | 1.10 (0.94‐1.30) | 76.0 | 76.2 | 1.00 (0.82‐1.21) | 0.43 | |
| Physician communication | ||||||||
| Doctors treated with courtesy/respect | 89.5 | 90.5 | 1.13 (0.89‐1.42) | 84.9 | 87.3 | 1.20 (0.94‐1.53) | 0.77 | |
| Doctors listened | 81.4 | 81.0 | 0.93 (0.83‐1.19) | 77.7 | 77.1 | 0.94 (0.77‐1.15) | 0.68 | |
| Doctors explained | 79.2 | 79.0 | 1.00(0.84‐1.19) | 75.7 | 74.4 | 0.92 (0.76‐1.12) | 0.49 | |
| Other | ||||||||
| Help toileting as soon as you wanted | 61.8 | 63.7 | 1.08 (0.89‐1.32) | 62.3 | 60.6 | 0.92 (0.71‐1.18) | 0.31 | |
| Pain well controlled | 63.2 | 63.8 | 1.06 (0.90‐1.25) | 62.0 | 62.6 | 0.99 (0.81‐1.20) | 060 | |
| Staff do everything to help with pain | 77.7 | 80.1 | 1.19 (0.99‐1.44) | 76.8 | 75.7 | 0.90 (0.75‐1.13) | 0.07 | |
| Staff describe medicine side effects | 47.0 | 47.6 | 1.05 (0.89‐1.24) | 49.2 | 47.1 | 0.91 (0.74‐1.11) | 0.32 | |
| Tell you what new medicine was for | 76.4 | 76.4 | 1.02 (0.84‐1.25) | 77.1 | 78.8 | 1.09(0.85‐1.39) | 0.65 | |
| Overall | ||||||||
| Rate hospital (010) | 75.0 | 83.3 | 1.71 (1.44‐2.05) | 75.7 | 77.6 | 1.06 (0.87‐1.29) | 0.006 | |
| Recommend hospital | 82.5 | 87.1 | 1.43 (1.18‐1.76) | 81.4 | 82.0 | 0.98 (0.79‐1.22) | 0.03 | |
| Satisfaction Domain | Moved Unit | Unmoved Unit | P Value of the Difference in Odds Ratio Between Moved and Unmoved Units | ||||
|---|---|---|---|---|---|---|---|
| % Top Box | Adjusted Odds Ratio* (95% CI) | % Top Box | Adjusted Odds Ratio* (95% CI) | ||||
| Pre | Post | Pre | Post | ||||
| |||||||
| FACILITY RELATED | |||||||
| Room | |||||||
| Pleasantness of room dcor | 33.6 | 64.8 | 3.77 (3.24‐4.38) | 41.6 | 47.0 | 1.21 (1.02‐1.44) | <0.0001 |
| Room cleanliness | 49.0 | 68.6 | 2.35 (2.02‐2.73) | 51.6 | 59.1 | 1.32 (1.12‐1.58) | <0.0001 |
| Room temperature | 43.1 | 54.9 | 1.64 (1.43‐1.90) | 45.0 | 48.8 | 1.14 (0.96‐1.36) | 0.002 |
| Noise level in and around the room | 40.2 | 59.2 | 2.23 (1.92‐2.58) | 45.5 | 47.6 | 1.07 (0.90‐1.22) | <0.0001 |
| Visitor related | |||||||
| Accommodations and comfort of visitors | 50.0 | 70.3 | 2.44 (2.10‐2.83) | 55.3 | 59.1 | 1.14 (0.96‐1.35) | <0.0001 |
| NONFACILITY RELATED | |||||||
| Food | |||||||
| Temperature of the food | 31.1 | 33.6 | 1.15 (0.99‐1.34) | 34.0 | 38.9 | 1.23 (1.02‐1.47) | 0.51 |
| Quality of the food | 25.8 | 27.1 | 1.10 (0.93‐1.30) | 30.2 | 36.2 | 1.32 (1.10‐1.59) | 0.12 |
| Courtesy of the person who served food | 63.9 | 62.3 | 0.93 (0.80‐1.10) | 66.0 | 61.4 | 0.82 (0.69‐0.98) | 0.26 |
| Nursing | |||||||
| Friendliness/courtesy of the nurses | 76.3 | 82.8 | 1.49 (1.26‐1.79) | 77.7 | 80.1 | 1.10 (0.90‐1.37) | 0.04 |
| Promptness of response to call | 60.1 | 62.6 | 1.14 (0.98‐1.33) | 59.2 | 62.0 | 1.10 (0.91‐1.31) | 0.80 |
| Nurses' attitude toward requests | 71.0 | 75.8 | 1.30 (1.11‐1.54) | 70.5 | 72.4 | 1.06 (0.88‐1.28) | 0.13 |
| Attention to special/personal needs | 66.7 | 72.2 | 1.32 (1.13‐1.54) | 67.8 | 70.3 | 1.09 (0.91‐1.31) | 0.16 |
| Nurses kept you informed | 64.3 | 72.2 | 1.46 (1.25‐1.70) | 65.8 | 69.8 | 1.17 (0.98‐1.41) | 0.88 |
| Skill of the nurses | 75.3 | 79.5 | 1.28 (1.08‐1.52) | 74.3 | 78.6 | 1.23 (1.01‐1.51) | 0.89 |
| Ancillary staff | |||||||
| Courtesy of the person cleaning the room | 59.8 | 67.7 | 1.41 (1.21‐1.65) | 61.2 | 66.5 | 1.24 (1.03‐1.49) | 0.28 |
| Courtesy of the person who took blood | 66.5 | 68.1 | 1.10 (0.94‐1.28) | 63.2 | 63.1 | 0.96 (0.76‐1.08) | 0.34 |
| Courtesy of the person who started the IV | 70.0 | 71.7 | 1.09 (0.93‐1.28) | 66.6 | 69.3 | 1.11 (0.92‐1.33) | 0.88 |
| Visitor related | |||||||
| Staff attitude toward visitors | 68.1 | 79.4 | 1.84 (1.56‐2.18) | 70.3 | 72.2 | 1.06 (0.87‐1.28) | <0.0001 |
| Physician | |||||||
| Time physician spent with you | 55.0 | 58.9 | 1.20 (1.04‐1.39) | 53.2 | 55.9 | 1.10 (0.92‐1.30) | 0.46 |
| Physician concern questions/worries | 67.2 | 70.7 | 1.20 (1.03‐1.40) | 64.3 | 66.1 | 1.05 (0.88‐1.26) | 0.31 |
| Physician kept you informed | 65.3 | 67.5 | 1.12 (0.96‐1.30) | 61.6 | 63.2 | 1.05 (0.88‐1.25) | 0.58 |
| Friendliness/courtesy of physician | 76.3 | 78.1 | 1.11 (0.93‐1.31) | 71.0 | 73.3 | 1.08 (0.90‐1.31) | 0.89 |
| Skill of physician | 85.4 | 88.5 | 1.35 (1.09‐1.68) | 78.0 | 81.0 | 1.15 (0.93‐1.43) | 0.34 |
| Discharge | |||||||
| Extent felt ready for discharge | 62.0 | 66.7 | 1.23 (1.07‐1.44) | 59.2 | 62.3 | 1.10 (0.92‐1.30) | 0.35 |
| Speed of discharge process | 50.7 | 54.2 | 1.16 (1.01‐1.33) | 47.8 | 50.0 | 1.07 (0.90‐1.27) | 0.49 |
| Instructions for care at home | 66.4 | 71.1 | 1.25 (1.06‐1.46) | 64.0 | 67.7 | 1.16 (0.97‐1.39) | 0.54 |
| Staff concern for your privacy | 65.3 | 71.8 | 1.37 (1.17‐0.85) | 63.6 | 66.2 | 1.10 (0.91‐1.31) | 0.07 |
| Miscellaneous | |||||||
| How well your pain was controlled | 64.2 | 66.5 | 1.14 (0.97‐1.32) | 60.2 | 62.6 | 1.07 (0.89‐1.28) | 0.66 |
| Staff addressed emotional needs | 60.0 | 63.4 | 1.19 (1.02‐1.38) | 55.1 | 60.2 | 1.20 (1.01‐1.42) | 0.90 |
| Response to concerns/complaints | 61.1 | 64.5 | 1.19 (1.02‐1.38) | 57.2 | 60.1 | 1.10 (0.92‐1.31) | 0.57 |
| Overall | |||||||
| Staff worked together to care for you | 72.6 | 77.2 | 1.29 (1.10‐1.52) | 70.3 | 73.2 | 1.13 (0.93‐1.37) | 0.30 |
| Likelihood of recommending hospital | 79.1 | 84.3 | 1.44 (1.20‐1.74) | 76.3 | 79.2 | 1.14 (0.93‐1.39) | 0.10 |
| Overall rating of care given | 76.8 | 83.0 | 1.50 (1.25‐1.80) | 74.7 | 77.2 | 1.10 (0.90‐1.34) | 0.03 |
With regard to nonfacility‐related satisfaction, there were statistically higher scores in several nursing, physician, and discharge‐related satisfaction domains after the move. However, these changes were not associated with the move to the new clinical building as they were not significantly different from improvements on the unmoved units. Among nonfacility‐related items, only staff attitude toward visitors showed significant improvement (68.1% vs 79.4%). There was a significant improvement in hospital rating (75.0% vs 83.3% in the moved units and 75.7% vs 77.6% in the unmoved units). However, the other 3 measures of overall satisfaction did not show significant improvement associated with the move to the new clinical building when compared to the concurrent controls.
DISCUSSION
Contrary to our hypothesis and a belief held by many, we found that patients appeared able to distinguish their experience with hospital environment from their experience with providers and other services. Improvement in hospital facilities with incorporation of patient‐centered features was associated with improvements that were largely limited to increases in satisfaction with quietness, cleanliness, temperature, and dcor of the room along with visitor‐related satisfaction. Notably, there was no significant improvement in satisfaction related to physicians, nurses, housekeeping, and other service staff. There was improvement in satisfaction with staff attitude toward visitors, but this can be attributed to availability of visitor‐friendly facilities. There was a significant improvement in 1 of the 4 measures of overall satisfaction. Our findings also support the construct validity of HCAHPS and Press Ganey patient satisfaction surveys.
Ours is one of the largest studies on patient satisfaction related to patient‐centered design features in the inpatient acute care setting. Swan et al. also studied patients in an acute inpatient setting and compared satisfaction related to appealing versus typical hospital rooms. Patients were matched for case mix, insurance, gender, types of medical services received and LOS, and were served by the same set of physicians and similar food service and housekeeping staff.[26] Unlike our study, they found improved satisfaction related to physicians, housekeeping staff, food service staff, meals, and overall satisfaction. However, the study had some limitations. In particular, the study sample was self‐selected because the patients in this group were required to pay an extra daily fee to utilize the appealing room. Additionally, there were only 177 patients across the 2 groups, and the actual differences in satisfaction scores were small. Our sample was larger and patients in the study group were admitted to units in the new clinical buildings by the same criteria as they were admitted to the historic building prior to the move, and there were no significant differences in baseline characteristics between the comparison groups.
Jansen et al. also found broad improvements in patient satisfaction in a study of over 309 maternity unit patients in a new construction, all private‐room maternity unit with more appealing design elements and comfort features for visitors.[7] Improved satisfaction was noted with the physical environment, nursing care, assistance with feeding, respect for privacy, and discharge planning. However, it is difficult to extrapolate the results of this study to other settings, as maternity unit patients constitute a unique patient demographic with unique care needs. Additionally, when compared with patients in the control group, the patients in the study group were cared for by nurses who had a lower workload and who were not assigned other patients with more complex needs. Because nursing availability may be expected to impact satisfaction with clinical domains, the impact of private and appealing room may very well have been limited to improved satisfaction with the physical environment.
Despite the widespread belief among healthcare leadership that facility renovation or expansion is a vital strategy for improving patient satisfaction, our study shows that this may not be a dominant factor.[27] In fact, the Planetree model showed that improvement in satisfaction related to physical environment and nursing care was associated with implementation of both patient‐centered design features as well as with utilization of nurses that were trained to provide personalized care, educate patients, and involve patients and family.[28] It is more likely that provider‐level interventions will have a greater impact on provider level and overall satisfaction. This idea is supported by a recent JD Powers study suggesting that facilities represent only 19% of overall satisfaction in the inpatient setting.[35]
Although our study focused on patient‐centered design features, several renovation and construction projects have also focused on design features that improve patient safety and provider satisfaction, workflow, efficiency, productivity, stress, and time spent in direct care.[9] Interventions in these areas may lead to improvement in patient outcomes and perhaps lead to improvement in patient satisfaction; however, this relationship has not been well established at present.
In an era of cost containment, healthcare administrators are faced with high‐priced interventions, competing needs, limited resources, low profit margins, and often unclear evidence on cost‐effectiveness and return on investment of healthcare design features. Benefits are related to competitive advantage, higher reputation, patient retention, decreased malpractice costs, and increased Medicare payments through VBP programs that incentivize improved performance on quality metrics and patient satisfaction surveys. Our study supports the idea that a significant improvement in patient satisfaction related to creature comforts can be achieved with investment in patient‐centered design features. However, our findings also suggest that institutions should perform an individualized cost‐benefit analysis related to improvements in this narrow area of patient satisfaction. In our study, incorporation of patient‐centered design features resulted in improvement on 2 VBP HCAHPS measures, and its contribution toward total performance score under the VBP program would be limited.
Strengths of our study include the use of concurrent controls and our ability to capitalize on a natural experiment in which care teams remained constant before and after a move to a new clinical building. However, our study has some limitations. It was conducted at a single tertiary care academic center that predominantly serves an inner city population and referral patients seeking specialized care. Drivers of patient satisfaction may be different in community hospitals, and a different relationship may be observed between patient‐centered design and domains of patient satisfaction in this setting. Further studies in different hospital settings are needed to confirm our findings. Additionally, we were limited by the low response rate of the surveys. However, this is a widespread problem with all patient satisfaction research utilizing voluntary surveys, and our response rates are consistent with those previously reported.[34, 36, 37, 38] Furthermore, low response rates have not impeded the implementation of pay‐for‐performance programs on a national scale using HCHAPS.
In conclusion, our study suggests that hospitals should not use outdated facilities as an excuse for achievement of suboptimal satisfaction scores. Patients respond positively to creature comforts, pleasing surroundings, and visitor‐friendly facilities but can distinguish these positive experiences from experiences in other patient satisfaction domains. In our study, the move to a higher‐amenity building had only a modest impact on overall patient satisfaction, perhaps because clinical care is the primary driver of this outcome. Contrary to belief held by some hospital leaders, major strides in overall satisfaction across the board and other subdomains of satisfaction likely require intervention in areas other than facility renovation and expansion.
Disclosures
Zishan Siddiqui, MD, was supported by the Osler Center of Clinical Excellence Faculty Scholarship Grant. Funds from Johns Hopkins Hospitalist Scholars Program supported the research project. The authors have no conflict of interests to disclose.
Hospitals are expensive and complex facilities to build and renovate. It is estimated $200 billion is being spent in the United States during this decade on hospital construction and renovation, and further expenditures in this area are expected.[1] Aging hospital infrastructure, competition, and health system expansion have motivated institutions to invest in renovation and new hospital building construction.[2, 3, 4, 5, 6, 7] There is a trend toward patient‐centered design in new hospital construction. Features of this trend include same‐handed design (ie, rooms on a unit have all beds oriented in the same direction and do not share headwalls); use of sound absorbent materials to reduced ambient noise[7, 8, 9]; rooms with improved view and increased natural lighting to reduce anxiety, decrease delirium, and increase sense of wellbeing[10, 11, 12]; incorporation of natural elements like gardens, water features, and art[12, 13, 14, 15, 16, 17, 18]; single‐patient rooms to reduce transmission of infection and enhance privacy and visitor comfort[7, 19, 20]; presence of comfortable waiting rooms and visitor accommodations to enhance comfort and family participation[21, 22, 23]; and hotel‐like amenities such as on‐demand entertainment and room service menus.[24, 25]
There is a belief among some hospital leaders that patients are generally unable to distinguish their positive experience with a pleasing healthcare environment from their positive experience with care, and thus improving facilities will lead to improved satisfaction across the board.[26, 27] In a controlled study of hospitalized patients, appealing rooms were associated with increased satisfaction with services including housekeeping and food service staff, meals, as well as physicians and overall satisfaction.[26] A 2012 survey of hospital leadership found that expanding and renovating facilities was considered a top priority in improving patient satisfaction, with 82% of the respondents stating that this was important.[27]
Despite these attitudes, the impact of patient‐centered design on patient satisfaction is not well understood. Studies have shown that renovations and hospital construction that incorporates noise reduction strategies, positive distraction, patient and caregiver control, attractive waiting rooms, improved patient room appearance, private rooms, and large windows result in improved satisfaction with nursing, noise level, unit environment and cleanliness, perceived wait time, discharge preparedness, and overall care. [7, 19, 20, 23, 28] However, these studies were limited by small sample size, inclusion of a narrow group of patients (eg, ambulatory, obstetric, geriatric rehabilitation, intensive care unit), and concurrent use of interventions other than design improvement (eg, nurse and patient education). Many of these studies did not use the ubiquitous Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) and Press Ganey patient satisfaction surveys.
We sought to determine the changes in patient satisfaction that occurred during a natural experiment, in which clinical units (comprising stable nursing, physician, and unit teams) were relocated from an historic clinical building to a new clinical building that featured patient‐centered design, using HCAHPS and Press Ganey surveys and a large study population. We hypothesized that new building features would positively impact both facility related (eg, noise level), nonfacility related (eg, physician and housekeeping service related), and overall satisfaction.
METHODS
This was a retrospective analysis of prospectively collected Press Ganey and HCAPHS patient satisfaction survey data for a single academic tertiary care hospital.[29] The research project was reviewed and approved by the institutional review board.
Participants
All patients discharged from 12 clinical units that relocated to the new clinical building and returned patient satisfaction surveys served as study patients. The moved units included the coronary care unit, cardiac step down unit, medical intensive care unit, neuro critical care unit, surgical intensive care unit, orthopedic unit, neurology unit, neurosurgery unit, obstetrics units, gynecology unit, urology unit, cardiothoracic surgery unit, and the transplant surgery and renal transplant unit. Patients on clinical units that did not move served as concurrent controls.
Exposure
Patients admitted to the new clinical building experienced several patient‐centered design features. These features included easy access to healing gardens with a water feature, soaring lobbies, a collection of more than 500 works of art, well‐decorated and light‐filled patient rooms with sleeping accommodations for family members, sound‐absorbing features in patient care corridors ranging from acoustical ceiling tiles to a quiet nurse‐call system, and an interactive television network with Internet, movies, and games. All patients during the baseline period and control patients during the study period were located in typical patient rooms with standard hospital amenities. No other major patient satisfaction interventions were initiated during the pre‐ or postperiod in either arm of the study; ongoing patient satisfaction efforts (such as unit‐based customer care representatives) were deployed broadly and not restricted to the new clinical building. Clinical teams comprised of physicians, nurses, and ancillary staff did not change significantly after the move.
Time Periods
The move to new clinical building occurred on May 1, 2012. After allowing for a 15‐day washout period, the postmove period included Press Ganey and HCAHPS surveys returned for discharges that occurred during a 7.5‐month period between May 15, 2102 and December 31, 2012. Baseline data included Press Ganey and HCAHPS surveys returned for discharges in the preceding 12 months (May 1, 2011 to April 30, 2012). Sensitivity analysis using only 7.5 months of baseline data did not reveal any significant difference when compared with 12‐month baseline data, and we report only data from the 12‐month baseline period.
Instruments
Press Ganey and HCAHPS patient satisfaction surveys were sent via mail in the same envelope. Fifty percent of the discharged patients were randomized to receive the surveys. The Press Ganey survey contained 33 items covering across several subdomains including room, meal, nursing, physician, ancillary staff, visitor, discharge, and overall satisfaction. The HCAHPS survey contained 29 Centers for Medicare and Medicaid Services (CMS)‐mandated items, of which 21 are related to patient satisfaction. The development and testing and methods for administration and reporting of the HCAHPS survey have been previously described.[30, 31] Press Ganey patient satisfaction survey results have been reported in the literature.[32, 33]
Outcome Variables
Press Ganey and HCAHPS patient satisfaction survey responses were the primary outcome variables of the study. The survey items were categorized as facility related (eg, noise level), nonfacility related (eg, physician and nursing staff satisfaction), and overall satisfaction related.
Covariates
Age, sex, length of stay (LOS), insurance type, and all‐payer refined diagnosis‐related groupassociated illness complexity were included as covariates.
Statistical Analysis
Percent top‐box scores were calculated for each survey item as the percent of patients who responded very good for a given item on Press Ganey survey items and always or definitely yes or 9 or 10 on HCAHPS survey items. CMS utilizes percent top‐box scores to calculate payments under the Value Based Purchasing (VBP) program and to report the results publicly. Numerous studies have also reported percent top‐box scores for HCAHPS survey results.[31, 32, 33, 34]
Odds ratios of premove versus postmove percentage of top‐box scores, adjusted for age, sex, LOS, complexity of illness, and insurance type were determined using logistic regression for the units that moved. Similar scores were calculated for unmoved units to detect secular trends. To determine whether the differences between the moved and unmoved units were significant, we introduced the interaction term (moved vs unmoved unit status) (pre‐ vs postmove time period) into the logistic regression models and examined the adjusted P value for this term. All statistical analysis was performed using SAS Institute Inc.'s (Cary, NC) JMP Pro 10.0.0.
RESULTS
The study included 1648 respondents in the moved units in the baseline period (ie, units designated to move to a new clinical building) and 1373 respondents in the postmove period. There were 1593 respondents in the control group during the baseline period and 1049 respondents in the postmove period. For the units that moved, survey response rates were 28.5% prior to the move and 28.3% after the move. For the units that did not move, survey response rates were 20.9% prior to the move and 22.7% after the move. A majority of survey respondents on the nursing units that moved were white, male, and had private insurance (Table 1). There were no significant differences between respondents across these characteristics between the pre‐ and postmove periods. Mean age and LOS were also similar. For these units, there were 70.5% private rooms prior to the move and 100% after the move. For the unmoved units, 58.9% of the rooms were private in the baseline period and 72.7% were private in the study period. Similar to the units that moved, characteristics of the respondents on the unmoved units also did not differ significantly in the postmove period.
| Patient demographics | Moved Units (N=3,021) | Unmoved Units (N=2,642) | ||||
|---|---|---|---|---|---|---|
| Pre | Post | P Value | Pre | Post | P Value | |
| ||||||
| White | 75.3% | 78.2% | 0.07 | 66.7% | 68.5% | 0.31 |
| Mean age, y | 57.3 | 57.4 | 0.84 | 57.3 | 57.1 | 0.81 |
| Male | 54.3% | 53.0% | 0.48 | 40.5% | 42.3% | 0.23 |
| Self‐reported health | ||||||
| Excellent or very good | 54.7% | 51.2% | 0.04 | 38.7% | 39.5% | 0.11 |
| Good | 27.8% | 32.0% | 29.3% | 32.2% | ||
| Fair or poor | 17.5% | 16.9% | 32.0% | 28.3% | ||
| Self‐reported language | ||||||
| English | 96.0% | 97.2% | 0.06 | 96.8% | 97.1% | 0.63 |
| Other | 4.0% | 2.8% | 3.2% | 2.9% | ||
| Self‐reported education | ||||||
| Less than high school | 5.8% | 5.0% | 0.24 | 10.8% | 10.4% | 0.24 |
| High school grad | 46.4% | 44.2% | 48.6% | 45.5% | ||
| College grad or more | 47.7% | 50.7% | 40.7% | 44.7% | ||
| Insurance type | ||||||
| Medicaid | 6.7% | 5.5% | 0.11 | 10.8% | 9.0% | 0.32 |
| Medicare | 32.0% | 35.5% | 36.0% | 36.1% | ||
| Private insurance | 55.6% | 52.8% | 48.0% | 50.3% | ||
| Mean APRDRG complexity* | 2.1 | 2.1 | 0.09 | 2.3 | 2.3 | 0.14 |
| Mean LOS | 4.7 | 5.0 | 0.12 | 4.9 | 5.0 | 0.77 |
| Service | ||||||
| Medicine | 15.4% | 16.2% | 0.51 | 40.0% | 34.5% | 0.10 |
| Surgery | 50.7% | 45.7% | 40.1% | 44.1% | ||
| Neurosciences | 20.3% | 24.1% | 6.0% | 6.0% | ||
| Obstetrics/gynecology | 7.5% | 8.2% | 5.7% | 5.6% | ||
The move was associated with significant improvements in facility‐related satisfaction (Tables 2 and 3). The most prominent increases in satisfaction were with pleasantness of dcor (33.6% vs 66.2%), noise level (39.9% vs 59.3%), and visitor accommodation and comfort (50.0% vs 70.3 %). There was improvement in satisfaction related to cleanliness of the room (49.0% vs 68.6 %), but no significant increase in satisfaction with courtesy of the person cleaning the room (59.8% vs 67.7%) when compared with units that did move.
| Satisfaction Domain | Moved Units | Unmoved Units | P Value of the Difference in Odds Ratio Between Moved and Unmoved Units | |||||
|---|---|---|---|---|---|---|---|---|
| % Top Box | Adjusted Odds Ratio* (95% CI) | % Top Box | Adjusted Odds Ratio* (95% CI) | |||||
| Pre | Post | Pre | Post | |||||
| ||||||||
| FACILITY RELATED | ||||||||
| Hospital environment | ||||||||
| Cleanliness of the room and bathroom | 61.0 | 70.8 | 1.62 (1.40‐1.90) | 64.0 | 69.2 | 1.24 (1.03‐1.48) | 0.03 | |
| Quietness of the room | 51.3 | 65.4 | 1.89 (1.63‐2.19) | 58.6 | 60.3 | 1.08 (0.90‐1.28) | <0.0001 | |
| NONFACILITY RELATED | ||||||||
| Nursing communication | ||||||||
| Nurses treated with courtesy/respect | 84.0 | 86.7 | 1.28 (1.05‐1.57) | 83.6 | 87.1 | 1.29 (1.02‐1.64) | 0.92 | |
| Nurses listened | 73.1 | 76.4 | 1.21 (1.03‐1.43) | 74.2 | 75.5 | 1.05 (0.86‐1.27) | 0.26 | |
| Nurses explained | 75.0 | 76.6 | 1.10 (0.94‐1.30) | 76.0 | 76.2 | 1.00 (0.82‐1.21) | 0.43 | |
| Physician communication | ||||||||
| Doctors treated with courtesy/respect | 89.5 | 90.5 | 1.13 (0.89‐1.42) | 84.9 | 87.3 | 1.20 (0.94‐1.53) | 0.77 | |
| Doctors listened | 81.4 | 81.0 | 0.93 (0.83‐1.19) | 77.7 | 77.1 | 0.94 (0.77‐1.15) | 0.68 | |
| Doctors explained | 79.2 | 79.0 | 1.00(0.84‐1.19) | 75.7 | 74.4 | 0.92 (0.76‐1.12) | 0.49 | |
| Other | ||||||||
| Help toileting as soon as you wanted | 61.8 | 63.7 | 1.08 (0.89‐1.32) | 62.3 | 60.6 | 0.92 (0.71‐1.18) | 0.31 | |
| Pain well controlled | 63.2 | 63.8 | 1.06 (0.90‐1.25) | 62.0 | 62.6 | 0.99 (0.81‐1.20) | 060 | |
| Staff do everything to help with pain | 77.7 | 80.1 | 1.19 (0.99‐1.44) | 76.8 | 75.7 | 0.90 (0.75‐1.13) | 0.07 | |
| Staff describe medicine side effects | 47.0 | 47.6 | 1.05 (0.89‐1.24) | 49.2 | 47.1 | 0.91 (0.74‐1.11) | 0.32 | |
| Tell you what new medicine was for | 76.4 | 76.4 | 1.02 (0.84‐1.25) | 77.1 | 78.8 | 1.09(0.85‐1.39) | 0.65 | |
| Overall | ||||||||
| Rate hospital (010) | 75.0 | 83.3 | 1.71 (1.44‐2.05) | 75.7 | 77.6 | 1.06 (0.87‐1.29) | 0.006 | |
| Recommend hospital | 82.5 | 87.1 | 1.43 (1.18‐1.76) | 81.4 | 82.0 | 0.98 (0.79‐1.22) | 0.03 | |
| Satisfaction Domain | Moved Unit | Unmoved Unit | P Value of the Difference in Odds Ratio Between Moved and Unmoved Units | ||||
|---|---|---|---|---|---|---|---|
| % Top Box | Adjusted Odds Ratio* (95% CI) | % Top Box | Adjusted Odds Ratio* (95% CI) | ||||
| Pre | Post | Pre | Post | ||||
| |||||||
| FACILITY RELATED | |||||||
| Room | |||||||
| Pleasantness of room dcor | 33.6 | 64.8 | 3.77 (3.24‐4.38) | 41.6 | 47.0 | 1.21 (1.02‐1.44) | <0.0001 |
| Room cleanliness | 49.0 | 68.6 | 2.35 (2.02‐2.73) | 51.6 | 59.1 | 1.32 (1.12‐1.58) | <0.0001 |
| Room temperature | 43.1 | 54.9 | 1.64 (1.43‐1.90) | 45.0 | 48.8 | 1.14 (0.96‐1.36) | 0.002 |
| Noise level in and around the room | 40.2 | 59.2 | 2.23 (1.92‐2.58) | 45.5 | 47.6 | 1.07 (0.90‐1.22) | <0.0001 |
| Visitor related | |||||||
| Accommodations and comfort of visitors | 50.0 | 70.3 | 2.44 (2.10‐2.83) | 55.3 | 59.1 | 1.14 (0.96‐1.35) | <0.0001 |
| NONFACILITY RELATED | |||||||
| Food | |||||||
| Temperature of the food | 31.1 | 33.6 | 1.15 (0.99‐1.34) | 34.0 | 38.9 | 1.23 (1.02‐1.47) | 0.51 |
| Quality of the food | 25.8 | 27.1 | 1.10 (0.93‐1.30) | 30.2 | 36.2 | 1.32 (1.10‐1.59) | 0.12 |
| Courtesy of the person who served food | 63.9 | 62.3 | 0.93 (0.80‐1.10) | 66.0 | 61.4 | 0.82 (0.69‐0.98) | 0.26 |
| Nursing | |||||||
| Friendliness/courtesy of the nurses | 76.3 | 82.8 | 1.49 (1.26‐1.79) | 77.7 | 80.1 | 1.10 (0.90‐1.37) | 0.04 |
| Promptness of response to call | 60.1 | 62.6 | 1.14 (0.98‐1.33) | 59.2 | 62.0 | 1.10 (0.91‐1.31) | 0.80 |
| Nurses' attitude toward requests | 71.0 | 75.8 | 1.30 (1.11‐1.54) | 70.5 | 72.4 | 1.06 (0.88‐1.28) | 0.13 |
| Attention to special/personal needs | 66.7 | 72.2 | 1.32 (1.13‐1.54) | 67.8 | 70.3 | 1.09 (0.91‐1.31) | 0.16 |
| Nurses kept you informed | 64.3 | 72.2 | 1.46 (1.25‐1.70) | 65.8 | 69.8 | 1.17 (0.98‐1.41) | 0.88 |
| Skill of the nurses | 75.3 | 79.5 | 1.28 (1.08‐1.52) | 74.3 | 78.6 | 1.23 (1.01‐1.51) | 0.89 |
| Ancillary staff | |||||||
| Courtesy of the person cleaning the room | 59.8 | 67.7 | 1.41 (1.21‐1.65) | 61.2 | 66.5 | 1.24 (1.03‐1.49) | 0.28 |
| Courtesy of the person who took blood | 66.5 | 68.1 | 1.10 (0.94‐1.28) | 63.2 | 63.1 | 0.96 (0.76‐1.08) | 0.34 |
| Courtesy of the person who started the IV | 70.0 | 71.7 | 1.09 (0.93‐1.28) | 66.6 | 69.3 | 1.11 (0.92‐1.33) | 0.88 |
| Visitor related | |||||||
| Staff attitude toward visitors | 68.1 | 79.4 | 1.84 (1.56‐2.18) | 70.3 | 72.2 | 1.06 (0.87‐1.28) | <0.0001 |
| Physician | |||||||
| Time physician spent with you | 55.0 | 58.9 | 1.20 (1.04‐1.39) | 53.2 | 55.9 | 1.10 (0.92‐1.30) | 0.46 |
| Physician concern questions/worries | 67.2 | 70.7 | 1.20 (1.03‐1.40) | 64.3 | 66.1 | 1.05 (0.88‐1.26) | 0.31 |
| Physician kept you informed | 65.3 | 67.5 | 1.12 (0.96‐1.30) | 61.6 | 63.2 | 1.05 (0.88‐1.25) | 0.58 |
| Friendliness/courtesy of physician | 76.3 | 78.1 | 1.11 (0.93‐1.31) | 71.0 | 73.3 | 1.08 (0.90‐1.31) | 0.89 |
| Skill of physician | 85.4 | 88.5 | 1.35 (1.09‐1.68) | 78.0 | 81.0 | 1.15 (0.93‐1.43) | 0.34 |
| Discharge | |||||||
| Extent felt ready for discharge | 62.0 | 66.7 | 1.23 (1.07‐1.44) | 59.2 | 62.3 | 1.10 (0.92‐1.30) | 0.35 |
| Speed of discharge process | 50.7 | 54.2 | 1.16 (1.01‐1.33) | 47.8 | 50.0 | 1.07 (0.90‐1.27) | 0.49 |
| Instructions for care at home | 66.4 | 71.1 | 1.25 (1.06‐1.46) | 64.0 | 67.7 | 1.16 (0.97‐1.39) | 0.54 |
| Staff concern for your privacy | 65.3 | 71.8 | 1.37 (1.17‐0.85) | 63.6 | 66.2 | 1.10 (0.91‐1.31) | 0.07 |
| Miscellaneous | |||||||
| How well your pain was controlled | 64.2 | 66.5 | 1.14 (0.97‐1.32) | 60.2 | 62.6 | 1.07 (0.89‐1.28) | 0.66 |
| Staff addressed emotional needs | 60.0 | 63.4 | 1.19 (1.02‐1.38) | 55.1 | 60.2 | 1.20 (1.01‐1.42) | 0.90 |
| Response to concerns/complaints | 61.1 | 64.5 | 1.19 (1.02‐1.38) | 57.2 | 60.1 | 1.10 (0.92‐1.31) | 0.57 |
| Overall | |||||||
| Staff worked together to care for you | 72.6 | 77.2 | 1.29 (1.10‐1.52) | 70.3 | 73.2 | 1.13 (0.93‐1.37) | 0.30 |
| Likelihood of recommending hospital | 79.1 | 84.3 | 1.44 (1.20‐1.74) | 76.3 | 79.2 | 1.14 (0.93‐1.39) | 0.10 |
| Overall rating of care given | 76.8 | 83.0 | 1.50 (1.25‐1.80) | 74.7 | 77.2 | 1.10 (0.90‐1.34) | 0.03 |
With regard to nonfacility‐related satisfaction, there were statistically higher scores in several nursing, physician, and discharge‐related satisfaction domains after the move. However, these changes were not associated with the move to the new clinical building as they were not significantly different from improvements on the unmoved units. Among nonfacility‐related items, only staff attitude toward visitors showed significant improvement (68.1% vs 79.4%). There was a significant improvement in hospital rating (75.0% vs 83.3% in the moved units and 75.7% vs 77.6% in the unmoved units). However, the other 3 measures of overall satisfaction did not show significant improvement associated with the move to the new clinical building when compared to the concurrent controls.
DISCUSSION
Contrary to our hypothesis and a belief held by many, we found that patients appeared able to distinguish their experience with hospital environment from their experience with providers and other services. Improvement in hospital facilities with incorporation of patient‐centered features was associated with improvements that were largely limited to increases in satisfaction with quietness, cleanliness, temperature, and dcor of the room along with visitor‐related satisfaction. Notably, there was no significant improvement in satisfaction related to physicians, nurses, housekeeping, and other service staff. There was improvement in satisfaction with staff attitude toward visitors, but this can be attributed to availability of visitor‐friendly facilities. There was a significant improvement in 1 of the 4 measures of overall satisfaction. Our findings also support the construct validity of HCAHPS and Press Ganey patient satisfaction surveys.
Ours is one of the largest studies on patient satisfaction related to patient‐centered design features in the inpatient acute care setting. Swan et al. also studied patients in an acute inpatient setting and compared satisfaction related to appealing versus typical hospital rooms. Patients were matched for case mix, insurance, gender, types of medical services received and LOS, and were served by the same set of physicians and similar food service and housekeeping staff.[26] Unlike our study, they found improved satisfaction related to physicians, housekeeping staff, food service staff, meals, and overall satisfaction. However, the study had some limitations. In particular, the study sample was self‐selected because the patients in this group were required to pay an extra daily fee to utilize the appealing room. Additionally, there were only 177 patients across the 2 groups, and the actual differences in satisfaction scores were small. Our sample was larger and patients in the study group were admitted to units in the new clinical buildings by the same criteria as they were admitted to the historic building prior to the move, and there were no significant differences in baseline characteristics between the comparison groups.
Jansen et al. also found broad improvements in patient satisfaction in a study of over 309 maternity unit patients in a new construction, all private‐room maternity unit with more appealing design elements and comfort features for visitors.[7] Improved satisfaction was noted with the physical environment, nursing care, assistance with feeding, respect for privacy, and discharge planning. However, it is difficult to extrapolate the results of this study to other settings, as maternity unit patients constitute a unique patient demographic with unique care needs. Additionally, when compared with patients in the control group, the patients in the study group were cared for by nurses who had a lower workload and who were not assigned other patients with more complex needs. Because nursing availability may be expected to impact satisfaction with clinical domains, the impact of private and appealing room may very well have been limited to improved satisfaction with the physical environment.
Despite the widespread belief among healthcare leadership that facility renovation or expansion is a vital strategy for improving patient satisfaction, our study shows that this may not be a dominant factor.[27] In fact, the Planetree model showed that improvement in satisfaction related to physical environment and nursing care was associated with implementation of both patient‐centered design features as well as with utilization of nurses that were trained to provide personalized care, educate patients, and involve patients and family.[28] It is more likely that provider‐level interventions will have a greater impact on provider level and overall satisfaction. This idea is supported by a recent JD Powers study suggesting that facilities represent only 19% of overall satisfaction in the inpatient setting.[35]
Although our study focused on patient‐centered design features, several renovation and construction projects have also focused on design features that improve patient safety and provider satisfaction, workflow, efficiency, productivity, stress, and time spent in direct care.[9] Interventions in these areas may lead to improvement in patient outcomes and perhaps lead to improvement in patient satisfaction; however, this relationship has not been well established at present.
In an era of cost containment, healthcare administrators are faced with high‐priced interventions, competing needs, limited resources, low profit margins, and often unclear evidence on cost‐effectiveness and return on investment of healthcare design features. Benefits are related to competitive advantage, higher reputation, patient retention, decreased malpractice costs, and increased Medicare payments through VBP programs that incentivize improved performance on quality metrics and patient satisfaction surveys. Our study supports the idea that a significant improvement in patient satisfaction related to creature comforts can be achieved with investment in patient‐centered design features. However, our findings also suggest that institutions should perform an individualized cost‐benefit analysis related to improvements in this narrow area of patient satisfaction. In our study, incorporation of patient‐centered design features resulted in improvement on 2 VBP HCAHPS measures, and its contribution toward total performance score under the VBP program would be limited.
Strengths of our study include the use of concurrent controls and our ability to capitalize on a natural experiment in which care teams remained constant before and after a move to a new clinical building. However, our study has some limitations. It was conducted at a single tertiary care academic center that predominantly serves an inner city population and referral patients seeking specialized care. Drivers of patient satisfaction may be different in community hospitals, and a different relationship may be observed between patient‐centered design and domains of patient satisfaction in this setting. Further studies in different hospital settings are needed to confirm our findings. Additionally, we were limited by the low response rate of the surveys. However, this is a widespread problem with all patient satisfaction research utilizing voluntary surveys, and our response rates are consistent with those previously reported.[34, 36, 37, 38] Furthermore, low response rates have not impeded the implementation of pay‐for‐performance programs on a national scale using HCHAPS.
In conclusion, our study suggests that hospitals should not use outdated facilities as an excuse for achievement of suboptimal satisfaction scores. Patients respond positively to creature comforts, pleasing surroundings, and visitor‐friendly facilities but can distinguish these positive experiences from experiences in other patient satisfaction domains. In our study, the move to a higher‐amenity building had only a modest impact on overall patient satisfaction, perhaps because clinical care is the primary driver of this outcome. Contrary to belief held by some hospital leaders, major strides in overall satisfaction across the board and other subdomains of satisfaction likely require intervention in areas other than facility renovation and expansion.
Disclosures
Zishan Siddiqui, MD, was supported by the Osler Center of Clinical Excellence Faculty Scholarship Grant. Funds from Johns Hopkins Hospitalist Scholars Program supported the research project. The authors have no conflict of interests to disclose.
- , . Create a blueprint for successful hospital construction. Nurs Manage. 2006;37(6):39–44.
- Walter Reed National Military Medical Center website. Facts at a glance. Available at: http://www.wrnmmc.capmed.mil/About%20Us/SitePages/Facts.aspx. Accessed June 19, 2013.
- . Keys to collaboration. Healthcare Design website. Available at: http://www.healthcaredesignmagazine.com/building‐ideas/keys‐collaboration. Accessed June 19, 2013.
- . A tale of 4 hospitals. Healthcare Design website. Available at: http://www.healthcaredesignmagazine.com/building‐ideas/tale‐4‐hospitals. Accessed June 19, 2013.
- . Gateway to the east. Healthcare Design website. Available at: http://www.healthcaredesignmagazine.com/building‐ideas/gateway‐east. Accessed June 19, 2013.
- . Lessons learned. Healthcare Design website. Available at: http://www.healthcaredesignmagazine.com/building‐ideas/lessons‐learned. Accessed June 19, 2013.
- , , , , . Single room maternity care and client satisfaction. Birth. 2000;27(4):235–243.
- , , , . Same‐handed and mirrored unit configurations: is there a difference in patient and nurse outcomes? J Nurs Adm. 2011;41(6):273–279.
- , . The Pebble Projects: coordinated evidence‐based case studies. Build Res Inform. 2008;36(2):129–145.
- , , . Effects of exposure to nature and abstract pictures on patients recovering from open heart surgery. J Soc Psychophysiol Res. 1993;30:7.
- , , , . Postoperative delirium. Curr Drug Targets. 2005;6(7):807–814.
- . Stimulus deprivation in windowless rooms. Anaesthesia. 1977;32(7):598–602.
- , , , . Post‐occupancy evaluation of healing gardens in a pediatric cancer center. Landsc Urban Plan. 2005;73(2):167–183.
- . Healing gardens in hospitals. Interdiscip Des Res J. 2007;1(1):1–27.
- , . Restorative gardens. BMJ. 1993;306(6885):1080–1081.
- . Effects of interior design on wellness: theory and recent scientific research. J Health Care Inter Des. 1991;3:97–109.
- , . Sunny hospital rooms expedite recovery from severe and refractory depressions. J Affect Disord. 1996;40(1‐2):49–51.
- . Art in hospital spaces: the role of hospitals in an aestheticised society. Int J Cult Policy. 2007;13(1):85–101.
- , , . Renovation of a semiprivate patient room. Bowman Center Geriatric Rehabilitation Unit. Nurs Clin North Am 1995;30(1):97–115.
- , , , et al. (2013). Effect of intensive care environment on family and patient satisfaction: a before‐after study. Intensive Care Med. 2013;39(9):1626–1634.
- , , , , . Outcomes of environmental appraisal of different hospital waiting areas. Environ Behav. 2003;35(6):842–869.
- . Redesigning the neurocritical care unit to enhance family participation and improve outcomes. Cleve Clin J Med. 2009;76(suppl 2):S70–S74.
- , . The ecology of the patient visit: physical attractiveness, waiting times, and perceived quality of care. J Ambul Care Manage. 2008;31(2):128–141.
- . Patient satisfaction and the new consumer. Hosp Health Netw. 2006;80(57):59–62.
- . Patient satisfaction. Hospitals embrace hotel‐like amenities. Hosp Health Netw. 2007;81(11):24–26.
- , , . Do appealing hospital rooms increase patient evaluations of physicians, nurses, and hospital services? Health Care Manage Rev. 2003;28(3):254–264.
- . Patient experience and HCAHPS: little consensus on a top priority. Health Leaders Media website. Available at http://www.healthleadersmedia.com/intelligence/detail.cfm?content_id=28289334(2):125–133.
- Centers for Medicare 67:27–37.
- Hospital Consumer Assessment of Healthcare Providers and Systems. Summary analysis. http://www.hcahpsonline.org/SummaryAnalyses.aspx. Accessed October 1, 2014.
- Centers for Medicare 44(2 pt 1):501–518.
- J.D. Power and Associates. Patient satisfaction influenced more by hospital staff than by the hospital facilities. Available at: http://www.jdpower.com/press‐releases/2012‐national‐patient‐experience‐study#sthash.gSv6wAdc.dpuf. Accessed December 10, 2013.
- , , , , . Racial and ethnic differences in a patient survey: patients' values, ratings, and reports regarding physician primary care performance in a large health maintenance organization. Med Care. 2000;38(3): 300–310.
- , , , . Patient experience in safety‐net hospitals implications for improving care and Value‐Based Purchasing patient experience in safety‐net hospitals. Arch Intern Med. 2012;172(16):1204–1210.
- , , , . Comparison of Hospital Consumer Assessment of Healthcare Providers and Systems patient satisfaction scores for specialty hospitals and general medical hospitals: confounding effect of survey response rate. J Hosp Med. 2014;9(9):590–593.
- , . Create a blueprint for successful hospital construction. Nurs Manage. 2006;37(6):39–44.
- Walter Reed National Military Medical Center website. Facts at a glance. Available at: http://www.wrnmmc.capmed.mil/About%20Us/SitePages/Facts.aspx. Accessed June 19, 2013.
- . Keys to collaboration. Healthcare Design website. Available at: http://www.healthcaredesignmagazine.com/building‐ideas/keys‐collaboration. Accessed June 19, 2013.
- . A tale of 4 hospitals. Healthcare Design website. Available at: http://www.healthcaredesignmagazine.com/building‐ideas/tale‐4‐hospitals. Accessed June 19, 2013.
- . Gateway to the east. Healthcare Design website. Available at: http://www.healthcaredesignmagazine.com/building‐ideas/gateway‐east. Accessed June 19, 2013.
- . Lessons learned. Healthcare Design website. Available at: http://www.healthcaredesignmagazine.com/building‐ideas/lessons‐learned. Accessed June 19, 2013.
- , , , , . Single room maternity care and client satisfaction. Birth. 2000;27(4):235–243.
- , , , . Same‐handed and mirrored unit configurations: is there a difference in patient and nurse outcomes? J Nurs Adm. 2011;41(6):273–279.
- , . The Pebble Projects: coordinated evidence‐based case studies. Build Res Inform. 2008;36(2):129–145.
- , , . Effects of exposure to nature and abstract pictures on patients recovering from open heart surgery. J Soc Psychophysiol Res. 1993;30:7.
- , , , . Postoperative delirium. Curr Drug Targets. 2005;6(7):807–814.
- . Stimulus deprivation in windowless rooms. Anaesthesia. 1977;32(7):598–602.
- , , , . Post‐occupancy evaluation of healing gardens in a pediatric cancer center. Landsc Urban Plan. 2005;73(2):167–183.
- . Healing gardens in hospitals. Interdiscip Des Res J. 2007;1(1):1–27.
- , . Restorative gardens. BMJ. 1993;306(6885):1080–1081.
- . Effects of interior design on wellness: theory and recent scientific research. J Health Care Inter Des. 1991;3:97–109.
- , . Sunny hospital rooms expedite recovery from severe and refractory depressions. J Affect Disord. 1996;40(1‐2):49–51.
- . Art in hospital spaces: the role of hospitals in an aestheticised society. Int J Cult Policy. 2007;13(1):85–101.
- , , . Renovation of a semiprivate patient room. Bowman Center Geriatric Rehabilitation Unit. Nurs Clin North Am 1995;30(1):97–115.
- , , , et al. (2013). Effect of intensive care environment on family and patient satisfaction: a before‐after study. Intensive Care Med. 2013;39(9):1626–1634.
- , , , , . Outcomes of environmental appraisal of different hospital waiting areas. Environ Behav. 2003;35(6):842–869.
- . Redesigning the neurocritical care unit to enhance family participation and improve outcomes. Cleve Clin J Med. 2009;76(suppl 2):S70–S74.
- , . The ecology of the patient visit: physical attractiveness, waiting times, and perceived quality of care. J Ambul Care Manage. 2008;31(2):128–141.
- . Patient satisfaction and the new consumer. Hosp Health Netw. 2006;80(57):59–62.
- . Patient satisfaction. Hospitals embrace hotel‐like amenities. Hosp Health Netw. 2007;81(11):24–26.
- , , . Do appealing hospital rooms increase patient evaluations of physicians, nurses, and hospital services? Health Care Manage Rev. 2003;28(3):254–264.
- . Patient experience and HCAHPS: little consensus on a top priority. Health Leaders Media website. Available at http://www.healthleadersmedia.com/intelligence/detail.cfm?content_id=28289334(2):125–133.
- Centers for Medicare 67:27–37.
- Hospital Consumer Assessment of Healthcare Providers and Systems. Summary analysis. http://www.hcahpsonline.org/SummaryAnalyses.aspx. Accessed October 1, 2014.
- Centers for Medicare 44(2 pt 1):501–518.
- J.D. Power and Associates. Patient satisfaction influenced more by hospital staff than by the hospital facilities. Available at: http://www.jdpower.com/press‐releases/2012‐national‐patient‐experience‐study#sthash.gSv6wAdc.dpuf. Accessed December 10, 2013.
- , , , , . Racial and ethnic differences in a patient survey: patients' values, ratings, and reports regarding physician primary care performance in a large health maintenance organization. Med Care. 2000;38(3): 300–310.
- , , , . Patient experience in safety‐net hospitals implications for improving care and Value‐Based Purchasing patient experience in safety‐net hospitals. Arch Intern Med. 2012;172(16):1204–1210.
- , , , . Comparison of Hospital Consumer Assessment of Healthcare Providers and Systems patient satisfaction scores for specialty hospitals and general medical hospitals: confounding effect of survey response rate. J Hosp Med. 2014;9(9):590–593.
© 2014 Society of Hospital Medicine