Journal of Cardiac Failure Vol. 21 No. 9 2015
Editorial Comment
Personalized Care for Patients With Heart Failure and Diabetes: Can We Afford Not to Do It? YIN GE, MD,1,2 AND DOUGLAS S. LEE, MD, PhD1,2,3,4 Toronto, Canada
The rise of chronic disease presents a major challenge for contemporary health care delivery. It is increasingly recognized that many patients with chronic illnesses have competing comorbidities, often requiring the involvement of many physicians and services.1 In particular, the management of concurrent heart failure (HF) and diabetes presents a unique challenge. Diabetes is a risk factor for the development of new-onset HF, acting not only via accelerated atherosclerotic disease, but also through direct alteration in cardiac structure.2,3 Conversely, patients with HF are predisposed to develop diabetes. Sud et al recently reported that the incidence of a de novo diabetes diagnosis after discharge from hospital with HF varied from 5% to 30% within 5 years, depending on admission blood glucose (Fig. 1).4 Patients with HF exhibit significantly impaired functional capacity and reduced quality of life, which often lead to hospital readmission during follow-up.5 Interventions to improve self-care and physical functioning may have substantial benefits. In this issue of the Journal of Cardiac Failure, Dunbar et al report the findings of a randomized controlled trial of a multicomponent intervention aimed to improve quality of life and functional status in multimorbid patients with HF.6 Specifically, the study examined participants with both HF and diabetesdthe intersection of 2 chronic diseases. In a companion paper,
Reilly et al report on the cost-effectiveness analysis of the intervention.7 The intervention was individualized and patient centered. Each patient received a series of longitudinal selfmonitoring educational sessions with trained research nurses using semistructured scripts. Participants were instructed on the interaction of HF and diabetes symptoms and encouraged to ask questions. The educational format was subsequently adapted to optimize it for each patient’s health literacy. Participants were also provided with strategies to enhance dietary, medication, and provider follow-up adherence. The intervention was reinforced with a home visit by the research nurse at 48e72 hours and scripted telephone calls at 7e10 days and 1, 2, and 4 months after discharge. The impact was significant, although inconsistencies were present. There was improvement in the Minnesota Living With Heart Failure Questionnaire (MLHFQ) in the intervention group, which was sustained at 6 months. However, there was also improvement in the control group, such that the difference between the active intervention and control groups was attenuated, albeit still clinically significant. There was also benefit demonstrated in the EuroQol visual analog scale (EQVAS), although the benefit was somewhat inconsistent between the EQVAS and EuroQol 5Dimension (EQ-5D) at 6 months. Notably, there was no change in the Audit of Diabetes-Dependent Quality of Life, although the authors report many factors that may have contributed to this finding. From a functional standpoint, there was significant improvement in the 6-minute walk test (6MWT), with an average difference of 84.8 feet in the intervention arm and 39.2 feet in the control arm. Missing data in the 6MWT results is a potential limitation. However, the selfreported ability to perform routine physical activities was increased, which was consistent with an overall improvement in functional status. Although the findings of Dunbar et al are promising, there are several questions that remain unanswered. First, it is unknown if the findings would be generalizable to the broader population of patients with HF and diabetes. In their study, the authors included only recently
From the 1Institute for Clinical Evaluative Sciences, University of Toronto, Toronto, Canada; 2Peter Munk Cardiac Centre, University of Toronto, Toronto, Canada; 3Institute for Health Policy, Management and Evaluation, University of Toronto, Toronto, Canada and 4Joint Department of Medical Imaging, University of Toronto, Toronto, Canada. Manuscript received July 8, 2015; revised manuscript received July 13, 2015; revised manuscript accepted July 13, 2015. Reprint requests: Douglas S. Lee, MD, PhD, Senior Scientist, Institute for Clinical Evaluative Sciences, Associate Professor of Medicine, University of Toronto, Institute for Clinical Evaluative Sciences, 2075 Bayview Avenue, Room G-106, Toronto, Ontario M4N 3M5, Canada. Tel: þ1 416-340-3861; Fax: þ1 416-340-3036. E-mail: [email protected] See page 739 for disclosure information. 1071-9164/$ - see front matter Ó 2015 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.cardfail.2015.07.004
738
Personalized Care for Patients With HF
Ge and Lee
739
Fig. 1. Risk of developing de novo diabetes according to presentation blood glucose in men and women admitted for heart failure. Reproduced with permission from Sud et al.4
hospitalized patients who had previous hospitalization for HF, thereby selecting a population at the highest risk of morbidity and mortality. Moreover, of the 747 patients screened, only 134 were randomized into the study. There were also differences in the study cohort compared with other population-based studies of patients with HF. In this study, the mean age was 57.4 years, and almost twothirds were men, whereas in population-based studies of unselected patients with HF the mean age is w75 years and roughly one-half are women.8e11 Second, although there was a nonsignificant trend, the study did not detect a difference in the harder clinical outcome of hospital readmission. This is very relevant because reducing hospital readmissions is a key priority in health care policy.12 The primary outcome findings reported in the study by Dunbar et al focused on intermediate surrogate end points. In the companion paper reported by Reilly et al, the intervention did not significantly reduce the proportion of patients who were readmitted, although the overall hospital length of stay was shorter in the intervention group. Of note, the readmission rate was high in this study, with 41% of patients being readmitted within 6 months for cardiovascular or diabetes-related causes. In total, there were 108 readmissions during the follow-up period, which is equivalent to 4 readmissions for every 5 patients recruited into the trial, highlighting their highrisk nature. It is unknown if the intervention would be able to detect a difference in readmission rates in an adequately powered trial. The cost-effectiveness of the intervention was remarkable. Despite the multimodal nature of the intervention, the cost of the intervention was relatively low, estimated to be $131 per participant. Over 6 months of follow-up, a significant proportion of the health careerelated costs were attributable to hospital-based care, with an overall mean difference of $7,647 favoring the intervention arm. However, it should be noted that the 95% confidence interval crossed zero and as a consequence the difference in
unadjusted costs was not statistically significant. The authors used a bootstrap procedure to examine the cost savings per quality-adjusted life-year provided by the intervention, and after 1,000 replications 79% of samples were in the quadrant indicative of lower cost and greater effectiveness. Although the cost-effectiveness during the 6-month study period was promising, readmissions remain an issue over the lifetime of patients with HF. It is unknown whether this intervention, which aims to improve functional status and perceived quality of life, would have a sustained long-term effect as patients demonstrate progressive functional decline.5 In summary, Dunbar, Reilly, et al should be congratulated for conducting these studies. They are important steps in improving the quality of life and outcomes of patients with HF. However, greater potential impact in the population of patients with concurrent HF and diabetes may be realized by demonstration of effects on clinically meaningful outcomes in multicenter studies. Disclosures None.
References 1. Barnett K, Mercer SW, Norbury M, Watt G, Wyke S, Guthrie B. Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study. Lancet 2012;380:37e43. 2. van Melle JP, Bot M, de Jonge P, de Boer RA, van Veldhuisen DJ, Whooley MA. Diabetes, glycemic control, and new-onset heart failure in patients with stable coronary artery disease: Data from the heart and soul study. Diabetes Care 2010;33:2084e9. 3. Voors AA, van der Horst IC. Diabetes: a driver for heart failure. Heart 2011;97:774e80. 4. Sud M, Wang X, Austin PC, Lipscombe LL, Newton GE, Tu JV, et al. Presentation blood glucose and death, hospitalization, and future
740 Journal of Cardiac Failure Vol. 21 No. 9 September 2015 diabetes risk in patients with acute heart failure syndromes. Eur Heart J 2015;36:924e31. 5. Chun S, Tu JV, Wijeysundera HC, Austin PC, Wang X, Levy D, et al. Lifetime analysis of hospitalizations and survival of patients newly admitted with heart failure. Circ Heart Fail 2012; 5:414e21. 6. Dunbar SB, Reilly CM, Gary R, Higgins MK, Culler S, Butts B, et al. Randomized clinical trial of an integrated self-care intervention for persons with heart failure and diabetes: quality of life and physical functioning outcomes. J Card Fail 2015;21:719e29. 7. Reilly CM, Butler J, Culler SD, Gary RA, Higgins M, Schindler P, et al. An economic evaluation of a self-care intervention in persons with heart failure and diabetes. J Card Fail 2015;21:730e7.
8. Ho KK, Pinsky JL, Kannel WB, Levy D. The epidemiology of heart failure: the Framingham study. J Am Coll Cardiol 1993;22:6Ae13A. 9. MacIntyre K, Capewell S, Stewart S, Chalmers JW, Boyd J, Finlayson A, et al. Evidence of improving prognosis in heart failure: trends in case fatality in 66 547 patients hospitalized between 1986 and 1995. Circulation 2000;102:1126e31. 10. Mosterd A, Hoes AW. Clinical epidemiology of heart failure. Heart 2007;93:1137e46. 11. Lee DS, Stitt A, Austin PC, Stukel TA, Schull MJ, Chong A, et al. Prediction of heart failure mortality in emergent care: a cohort study. Ann Intern Med 2012;156:767e75. W-261e2. 12. Desai AS, Stevenson LW. Rehospitalization for heart failure: Predict or prevent? Circulation 2012;126:501e56.
Editorial Comment
Personalized Care for Patients With Heart Failure and Diabetes: Can We Afford Not to Do It? YIN GE, MD,1,2 AND DOUGLAS S. LEE, MD, PhD1,2,3,4 Toronto, Canada
The rise of chronic disease presents a major challenge for contemporary health care delivery. It is increasingly recognized that many patients with chronic illnesses have competing comorbidities, often requiring the involvement of many physicians and services.1 In particular, the management of concurrent heart failure (HF) and diabetes presents a unique challenge. Diabetes is a risk factor for the development of new-onset HF, acting not only via accelerated atherosclerotic disease, but also through direct alteration in cardiac structure.2,3 Conversely, patients with HF are predisposed to develop diabetes. Sud et al recently reported that the incidence of a de novo diabetes diagnosis after discharge from hospital with HF varied from 5% to 30% within 5 years, depending on admission blood glucose (Fig. 1).4 Patients with HF exhibit significantly impaired functional capacity and reduced quality of life, which often lead to hospital readmission during follow-up.5 Interventions to improve self-care and physical functioning may have substantial benefits. In this issue of the Journal of Cardiac Failure, Dunbar et al report the findings of a randomized controlled trial of a multicomponent intervention aimed to improve quality of life and functional status in multimorbid patients with HF.6 Specifically, the study examined participants with both HF and diabetesdthe intersection of 2 chronic diseases. In a companion paper,
Reilly et al report on the cost-effectiveness analysis of the intervention.7 The intervention was individualized and patient centered. Each patient received a series of longitudinal selfmonitoring educational sessions with trained research nurses using semistructured scripts. Participants were instructed on the interaction of HF and diabetes symptoms and encouraged to ask questions. The educational format was subsequently adapted to optimize it for each patient’s health literacy. Participants were also provided with strategies to enhance dietary, medication, and provider follow-up adherence. The intervention was reinforced with a home visit by the research nurse at 48e72 hours and scripted telephone calls at 7e10 days and 1, 2, and 4 months after discharge. The impact was significant, although inconsistencies were present. There was improvement in the Minnesota Living With Heart Failure Questionnaire (MLHFQ) in the intervention group, which was sustained at 6 months. However, there was also improvement in the control group, such that the difference between the active intervention and control groups was attenuated, albeit still clinically significant. There was also benefit demonstrated in the EuroQol visual analog scale (EQVAS), although the benefit was somewhat inconsistent between the EQVAS and EuroQol 5Dimension (EQ-5D) at 6 months. Notably, there was no change in the Audit of Diabetes-Dependent Quality of Life, although the authors report many factors that may have contributed to this finding. From a functional standpoint, there was significant improvement in the 6-minute walk test (6MWT), with an average difference of 84.8 feet in the intervention arm and 39.2 feet in the control arm. Missing data in the 6MWT results is a potential limitation. However, the selfreported ability to perform routine physical activities was increased, which was consistent with an overall improvement in functional status. Although the findings of Dunbar et al are promising, there are several questions that remain unanswered. First, it is unknown if the findings would be generalizable to the broader population of patients with HF and diabetes. In their study, the authors included only recently
From the 1Institute for Clinical Evaluative Sciences, University of Toronto, Toronto, Canada; 2Peter Munk Cardiac Centre, University of Toronto, Toronto, Canada; 3Institute for Health Policy, Management and Evaluation, University of Toronto, Toronto, Canada and 4Joint Department of Medical Imaging, University of Toronto, Toronto, Canada. Manuscript received July 8, 2015; revised manuscript received July 13, 2015; revised manuscript accepted July 13, 2015. Reprint requests: Douglas S. Lee, MD, PhD, Senior Scientist, Institute for Clinical Evaluative Sciences, Associate Professor of Medicine, University of Toronto, Institute for Clinical Evaluative Sciences, 2075 Bayview Avenue, Room G-106, Toronto, Ontario M4N 3M5, Canada. Tel: þ1 416-340-3861; Fax: þ1 416-340-3036. E-mail: [email protected] See page 739 for disclosure information. 1071-9164/$ - see front matter Ó 2015 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.cardfail.2015.07.004
738
Personalized Care for Patients With HF
Ge and Lee
739
Fig. 1. Risk of developing de novo diabetes according to presentation blood glucose in men and women admitted for heart failure. Reproduced with permission from Sud et al.4
hospitalized patients who had previous hospitalization for HF, thereby selecting a population at the highest risk of morbidity and mortality. Moreover, of the 747 patients screened, only 134 were randomized into the study. There were also differences in the study cohort compared with other population-based studies of patients with HF. In this study, the mean age was 57.4 years, and almost twothirds were men, whereas in population-based studies of unselected patients with HF the mean age is w75 years and roughly one-half are women.8e11 Second, although there was a nonsignificant trend, the study did not detect a difference in the harder clinical outcome of hospital readmission. This is very relevant because reducing hospital readmissions is a key priority in health care policy.12 The primary outcome findings reported in the study by Dunbar et al focused on intermediate surrogate end points. In the companion paper reported by Reilly et al, the intervention did not significantly reduce the proportion of patients who were readmitted, although the overall hospital length of stay was shorter in the intervention group. Of note, the readmission rate was high in this study, with 41% of patients being readmitted within 6 months for cardiovascular or diabetes-related causes. In total, there were 108 readmissions during the follow-up period, which is equivalent to 4 readmissions for every 5 patients recruited into the trial, highlighting their highrisk nature. It is unknown if the intervention would be able to detect a difference in readmission rates in an adequately powered trial. The cost-effectiveness of the intervention was remarkable. Despite the multimodal nature of the intervention, the cost of the intervention was relatively low, estimated to be $131 per participant. Over 6 months of follow-up, a significant proportion of the health careerelated costs were attributable to hospital-based care, with an overall mean difference of $7,647 favoring the intervention arm. However, it should be noted that the 95% confidence interval crossed zero and as a consequence the difference in
unadjusted costs was not statistically significant. The authors used a bootstrap procedure to examine the cost savings per quality-adjusted life-year provided by the intervention, and after 1,000 replications 79% of samples were in the quadrant indicative of lower cost and greater effectiveness. Although the cost-effectiveness during the 6-month study period was promising, readmissions remain an issue over the lifetime of patients with HF. It is unknown whether this intervention, which aims to improve functional status and perceived quality of life, would have a sustained long-term effect as patients demonstrate progressive functional decline.5 In summary, Dunbar, Reilly, et al should be congratulated for conducting these studies. They are important steps in improving the quality of life and outcomes of patients with HF. However, greater potential impact in the population of patients with concurrent HF and diabetes may be realized by demonstration of effects on clinically meaningful outcomes in multicenter studies. Disclosures None.
References 1. Barnett K, Mercer SW, Norbury M, Watt G, Wyke S, Guthrie B. Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study. Lancet 2012;380:37e43. 2. van Melle JP, Bot M, de Jonge P, de Boer RA, van Veldhuisen DJ, Whooley MA. Diabetes, glycemic control, and new-onset heart failure in patients with stable coronary artery disease: Data from the heart and soul study. Diabetes Care 2010;33:2084e9. 3. Voors AA, van der Horst IC. Diabetes: a driver for heart failure. Heart 2011;97:774e80. 4. Sud M, Wang X, Austin PC, Lipscombe LL, Newton GE, Tu JV, et al. Presentation blood glucose and death, hospitalization, and future
740 Journal of Cardiac Failure Vol. 21 No. 9 September 2015 diabetes risk in patients with acute heart failure syndromes. Eur Heart J 2015;36:924e31. 5. Chun S, Tu JV, Wijeysundera HC, Austin PC, Wang X, Levy D, et al. Lifetime analysis of hospitalizations and survival of patients newly admitted with heart failure. Circ Heart Fail 2012; 5:414e21. 6. Dunbar SB, Reilly CM, Gary R, Higgins MK, Culler S, Butts B, et al. Randomized clinical trial of an integrated self-care intervention for persons with heart failure and diabetes: quality of life and physical functioning outcomes. J Card Fail 2015;21:719e29. 7. Reilly CM, Butler J, Culler SD, Gary RA, Higgins M, Schindler P, et al. An economic evaluation of a self-care intervention in persons with heart failure and diabetes. J Card Fail 2015;21:730e7.
8. Ho KK, Pinsky JL, Kannel WB, Levy D. The epidemiology of heart failure: the Framingham study. J Am Coll Cardiol 1993;22:6Ae13A. 9. MacIntyre K, Capewell S, Stewart S, Chalmers JW, Boyd J, Finlayson A, et al. Evidence of improving prognosis in heart failure: trends in case fatality in 66 547 patients hospitalized between 1986 and 1995. Circulation 2000;102:1126e31. 10. Mosterd A, Hoes AW. Clinical epidemiology of heart failure. Heart 2007;93:1137e46. 11. Lee DS, Stitt A, Austin PC, Stukel TA, Schull MJ, Chong A, et al. Prediction of heart failure mortality in emergent care: a cohort study. Ann Intern Med 2012;156:767e75. W-261e2. 12. Desai AS, Stevenson LW. Rehospitalization for heart failure: Predict or prevent? Circulation 2012;126:501e56.
