- Email: [email protected]
President's Page: Employing Shared Decision-Making Models to Improve Care and Patient Value: A Cardiovascular Professional Initiative
Journal of the American College of Cardiology © 2010 by the American College of Cardiology Foundation Published by Elsevier Inc.
Vol. 56, No. 24, 2010 ISSN 0735-1097/$36.00 doi:10.1016/j.jacc.2010.11.004
ACC NEWS
President’s Page: Employing Shared DecisionMaking Models to Improve Care and Patient Value: A Cardiovascular Professional Initiative
I
n their book “Redefining Health Care,” Michael Porter and Elizabeth Olmsted Teisberg wrote that when it comes to improving health care delivery, “the right objective for health care is to increase value for patients, which is the quality of patient outcomes relative to the dollars expended” (1). This is an obvious and laudable goal. The challenge, however, lies in determining what defines “value” for patients and how that value can be maximized within the routine flow of patient care. An increasingly important concept garnering attention among both policy makers and health care professionals is shared decision-making. Shared decision-making is “the process of interacting with patients who wish to be involved in arriving at an informed, values-based choice among two or more medically reasonable alternatives” (2). In its recent report to the secretary of the Department of Health and Human Services, the National Quality Forum emphasized the goal of shared decision-making, by explicitly stating that “all patients, their families, and their caregivers [should] have access to information and assistance that enables them to make shared and informed decisions about their treatment options” (3). No field better represents the opportunity to achieve this goal than cardiology. Cardiovascular disease is not only the largest cause of mortality for men and women, but it also substantially impairs the quality of life of afflicted individuals. Moreover, we have numerous diagnostic and therapeutic strategies with which to assess our patients and improve their outcomes. However, many of our treatments alter risk without impacting outcomes (e.g., the number needed to treat with statins to prevent an event can exceed 100); improve quality of life without improving survival (e.g., percutaneous coronary intervention [PCI] for stable angina); or improve survival while diminishing quality of life (e.g., implantable cardiac-defibrillators [ICDs] in patients with inappropriate shocks and no fatal arrhythmias). Thus, although some patients may want to fully avail themselves of cardiac treatments, others, based upon their age, comorbidities, or preferences, may not. Our profession is thus poised to make substantial contributions to the entire health care system by developing methods to support shared decision-making. Successfully supporting shared decision-making requires several critical components: estimating patients’ outcomes as a function of their individual risks, defining these outcomes as a function of alternative treatments, and sharing this information with patients in a manner that they can understand. Accomplishing these tasks moves health care much closer to the Institute of Medicine’s vision for a safer, evidence-based, equitable, efficient, patient-centered system (4). To accomplish the first 2 tasks, cardiology has numerous clinical trials and observational registries from which prediction models of outcomes (survival, hospital admissions, or quality of life) can be generated. In fact, the American College of Cardiology already has several risk models from our National Cardiovascular Data Registry (NCDR) that are poised to serve as valuable supports for medical decision-making if integrated into the routine flow of patient care. Although one could consider the utility of shared decision-making tools in selecting treatment approaches for coronary disease (medicines alone, PCI, or coronary artery by-
Ralph Brindis, MD, MPH, FACC ACC President
John A. Spertus, MD, MPH, FACC Lauer/Missouri Endowed Chair at Saint Luke’s Mid America Heart Institute/UMKC; Co-Founder Health Outcomes Sciences, LLC
Our profession is thus poised to make substantial contributions to the entire health care system by developing methods to support shared decision-making.
JACC Vol. 56, No. 24, 2010 December 7, 2010:2046–8
pass grafting), heart failure (resynchronization therapy, left ventricular assist devices, ICDs), atrial fibrillation (rate vs. rhythm control or ablation), or peripheral/carotid artery disease (noninvasive vs. peripheral vs. surgical revascularization), even within a given procedure there are numerous opportunities for shared decision-making. As a case in point, after a patient has selected PCI there are alternative treatment strategies that could be supported by an infrastructure for shared decision-making. For example, the choice of drug-eluting stents (DES) versus baremetal stents has a huge impact on patients. With DES, patients need to remain on dual antiplatelet therapy for a longer time (5), and with bare-metal stents, the benefit varies as a function of a patient’s risk for restenosis (6,7). Proactively engaging patients in such a choice— even one as seemingly simple as selecting a stent type for PCI— might allow patients to have a greater understanding of their disease and inspire greater accountability and hopefully improved adherence with dual antiplatelet therapy prescribed after DES placement. Shared decision-making could be useful when it comes to medical devices as well, particularly in the cardiovascular world. By using data already being collected via registries such as the ICD Registry, cardiovascular professionals could better inform patients of the costs and risks/ benefits of ICDs based on their age and sex. For example, a 60-year-old female with heart failure may consider an ICD for primary prevention of sudden cardiac death, as the life expectancy of a woman her age with heart failure and an ICD is 14.9 years compared to 12.7 years if she went without an ICD implant. On the flip side, an 80year-old male might choose to go without an ICD for primary prevention of sudden cardiac death, given the knowledge that the life expectancy of a man his age suffering from heart failure is 5 years, while the life expectancy of a male his age with heart failure and an ICD implant is only 6.2 years, taking into account the possibility of ICD implant complications or even inappropriate shocks (8). A seldom appreciated benefit of shared decision-making may be better insight by the clinician into the risks and benefits of treatment. For example, bleeding during PCI is the most common noncardiac complication of the procedure, and the NCDR has produced a valid risk model for predicting bleeding complications after PCI (9). However, the model to date has not been used in clinical care, and a recent analysis of the NCDR has shown a risktreatment paradox, in which patients at the highest risk of bleeding are preferentially not treated with effective bleed-
Brindis and Spertus President’s Page
2047
ing avoidance therapies, while those at the lowest risk for bleeding are (10). This is not only economically inefficient (using expensive interventions in those with the least potential to benefit, while avoiding them in those with the greatest potential to benefit), but it also worsens patient safety. Deploying an estimate of patients’ bleeding risk at the time of intervention can not only inform the patients about their risks, but could also be leveraged by physicians to target bivalirudin, closure devices, or inpatient admissions for closer observation after the procedure in those with moderate or high risk for periprocedural bleeding. The College is currently partnering with others to deploy its risk models within a patient-centered, individualized informed consent process to assist both patients and their physicians (11). If patients and physicians are to maximally benefit from improved medical decision-making, then several steps need to be taken. First, both clinical trials and registries need to start producing valid, clinically-useful risk prediction models of patients’ outcomes (12). Second, more research into how best to incorporate access to these models into clinical care and how they should be presented to patients and doctors needs to be performed. Finally, we need to recognize and reward the importance—and time required—to engage in shared decision-making. Toward this end, payers need to embrace the importance of shared decision-making by reimbursing clinicians for the time and resources needed to engage patients in an evidence-based discussion of their treatment options. An even more subtle point is that regulators need to appreciate that sometimes fully-informed patients may not select those therapies demanded by current performance measures. While the exclusions for some performance measures include patientcentered reasons for not selecting therapy, documenting these is not easy and there are concerns that clinicians who do a better job of following patients’ preferences may inadvertently appear to be performing lower-quality care. Until there is a system in place that rewards health care providers for quality outcomes and evidence-based care versus the volume of care provided, this will continue to be a major hindrance to the shared decision-making model. We have a ways to go before the shared decision-making model can be adopted on a national scale. That being said, the goals of shared decision making—to increase patient knowledge; encourage patient involvement in decision making; facilitate more realistic expectations of treatment options; and potentially reduce costs—are all ones we can and should support.
2048
Brindis and Spertus President’s Page
Toward that end, the College strongly supports both the application and research in the arena of shared decisionmaking. Our core values as cardiovascular professionals will continue to move us forward with identifying the challenges and opportunities associated with shared decision-making, in order to ensure that future shared decision-making models best meet the needs of patients and/or their families. Address correspondence to:
Ralph Brindis, MD, MPH, FACC American College of Cardiology 2400 N Street NW Washington, DC 20037 E-mail: [email protected]
REFERENCES
1. Porter ME, Teisberg EO. Redefining Health Care. Boston, MA: Harvard Business School Publishing, 2006. 2. O’Connor AM, Llewellyn-Thomas HA, Flood AB. Modifying Unwarranted Variations In Health Care: Shared Decision Making Using Patient Decision Aids. Health Affairs. October 7, 2004. 3. National Priorities Partnership. Input to the Secretary of Health and Human Services on Priorities for the 2011 National Quality Strategy. Available at: http://qualityforum.org/WorkArea/linkit.aspx?Link Identier⫽id&ItemID⫽43235. Accessed November 4, 2010.
JACC Vol. 56, No. 24, 2010 December 7, 2010:2046–8 4. Institute of Medicine. Crossing the Quality Chasm: A New Health System for the Twenty-first Century. Washington, DC: National Academy Press, 2001. 5. Grines CL, Bonow RO, Casey DE Jr., et al. Prevention of premature discontinuation of dual antiplatelet therapy in patients with coronary artery stents: a science advisory from the American Heart Association, American College of Cardiology, Society for Cardiovascular Angiography and Interventions, American College of Surgeons, and American Dental Association, with representation from the American College of Physicians. J Am Coll Cardiol 2007;49:734 –9. 6. Tu JV, Bowen J, Chiu M, et al. Effectiveness and safety of drugeluting stents in Ontario. N Engl J Med 2007;357:1393– 402. 7. Stone GW, Parise H, Witzenbichler B, et al. Selection criteria for drug-eluting versus bare-metal stents and the impact of routine angiographic follow-up: 2-year insights from the HORIZONS-AMI (Harmonizing Outcomes With Revascularization and Stents in Acute Myocardial Infarction) trial. J Am Coll Cardiol 2010;56:1597– 604. 8. Patient-Centered Education and Research. Salt Lake City, Utah. Available at: http://www.patient-centered.org. Accessed November 8, 2010. 9. Mehta SK, Frutkin AD, Lindsey JB, et al. Bleeding in patients undergoing percutaneous coronary intervention: the development of a clinical risk algorithm from the National Cardiovascular Data Registry. Circ Cardiovasc Intervent 2009;2:222–9. 10. Marso SP, Amin AP, House JA, et al. Association between use of bleeding avoidance strategies and risk of periprocedural bleeding among patients undergoing percutaneous coronary intervention. JAMA 2010;303:2156 – 64. 11. Arnold SV, Decker C, Ahmad H, et al. Converting the informed consent from a perfunctory process to an evidence-based foundation for patient decision making. Circ Cardiovascular Qual Outcomes 2008;1:21–2. 12. Kent DM, Rothwell PM, Ioannidis JP, Altman DG, Hayward RA. Assessing and reporting heterogeneity in treatment effects in clinical trials: a proposal. Trials 2010;11:85.
Vol. 56, No. 24, 2010 ISSN 0735-1097/$36.00 doi:10.1016/j.jacc.2010.11.004
ACC NEWS
President’s Page: Employing Shared DecisionMaking Models to Improve Care and Patient Value: A Cardiovascular Professional Initiative
I
n their book “Redefining Health Care,” Michael Porter and Elizabeth Olmsted Teisberg wrote that when it comes to improving health care delivery, “the right objective for health care is to increase value for patients, which is the quality of patient outcomes relative to the dollars expended” (1). This is an obvious and laudable goal. The challenge, however, lies in determining what defines “value” for patients and how that value can be maximized within the routine flow of patient care. An increasingly important concept garnering attention among both policy makers and health care professionals is shared decision-making. Shared decision-making is “the process of interacting with patients who wish to be involved in arriving at an informed, values-based choice among two or more medically reasonable alternatives” (2). In its recent report to the secretary of the Department of Health and Human Services, the National Quality Forum emphasized the goal of shared decision-making, by explicitly stating that “all patients, their families, and their caregivers [should] have access to information and assistance that enables them to make shared and informed decisions about their treatment options” (3). No field better represents the opportunity to achieve this goal than cardiology. Cardiovascular disease is not only the largest cause of mortality for men and women, but it also substantially impairs the quality of life of afflicted individuals. Moreover, we have numerous diagnostic and therapeutic strategies with which to assess our patients and improve their outcomes. However, many of our treatments alter risk without impacting outcomes (e.g., the number needed to treat with statins to prevent an event can exceed 100); improve quality of life without improving survival (e.g., percutaneous coronary intervention [PCI] for stable angina); or improve survival while diminishing quality of life (e.g., implantable cardiac-defibrillators [ICDs] in patients with inappropriate shocks and no fatal arrhythmias). Thus, although some patients may want to fully avail themselves of cardiac treatments, others, based upon their age, comorbidities, or preferences, may not. Our profession is thus poised to make substantial contributions to the entire health care system by developing methods to support shared decision-making. Successfully supporting shared decision-making requires several critical components: estimating patients’ outcomes as a function of their individual risks, defining these outcomes as a function of alternative treatments, and sharing this information with patients in a manner that they can understand. Accomplishing these tasks moves health care much closer to the Institute of Medicine’s vision for a safer, evidence-based, equitable, efficient, patient-centered system (4). To accomplish the first 2 tasks, cardiology has numerous clinical trials and observational registries from which prediction models of outcomes (survival, hospital admissions, or quality of life) can be generated. In fact, the American College of Cardiology already has several risk models from our National Cardiovascular Data Registry (NCDR) that are poised to serve as valuable supports for medical decision-making if integrated into the routine flow of patient care. Although one could consider the utility of shared decision-making tools in selecting treatment approaches for coronary disease (medicines alone, PCI, or coronary artery by-
Ralph Brindis, MD, MPH, FACC ACC President
John A. Spertus, MD, MPH, FACC Lauer/Missouri Endowed Chair at Saint Luke’s Mid America Heart Institute/UMKC; Co-Founder Health Outcomes Sciences, LLC
Our profession is thus poised to make substantial contributions to the entire health care system by developing methods to support shared decision-making.
JACC Vol. 56, No. 24, 2010 December 7, 2010:2046–8
pass grafting), heart failure (resynchronization therapy, left ventricular assist devices, ICDs), atrial fibrillation (rate vs. rhythm control or ablation), or peripheral/carotid artery disease (noninvasive vs. peripheral vs. surgical revascularization), even within a given procedure there are numerous opportunities for shared decision-making. As a case in point, after a patient has selected PCI there are alternative treatment strategies that could be supported by an infrastructure for shared decision-making. For example, the choice of drug-eluting stents (DES) versus baremetal stents has a huge impact on patients. With DES, patients need to remain on dual antiplatelet therapy for a longer time (5), and with bare-metal stents, the benefit varies as a function of a patient’s risk for restenosis (6,7). Proactively engaging patients in such a choice— even one as seemingly simple as selecting a stent type for PCI— might allow patients to have a greater understanding of their disease and inspire greater accountability and hopefully improved adherence with dual antiplatelet therapy prescribed after DES placement. Shared decision-making could be useful when it comes to medical devices as well, particularly in the cardiovascular world. By using data already being collected via registries such as the ICD Registry, cardiovascular professionals could better inform patients of the costs and risks/ benefits of ICDs based on their age and sex. For example, a 60-year-old female with heart failure may consider an ICD for primary prevention of sudden cardiac death, as the life expectancy of a woman her age with heart failure and an ICD is 14.9 years compared to 12.7 years if she went without an ICD implant. On the flip side, an 80year-old male might choose to go without an ICD for primary prevention of sudden cardiac death, given the knowledge that the life expectancy of a man his age suffering from heart failure is 5 years, while the life expectancy of a male his age with heart failure and an ICD implant is only 6.2 years, taking into account the possibility of ICD implant complications or even inappropriate shocks (8). A seldom appreciated benefit of shared decision-making may be better insight by the clinician into the risks and benefits of treatment. For example, bleeding during PCI is the most common noncardiac complication of the procedure, and the NCDR has produced a valid risk model for predicting bleeding complications after PCI (9). However, the model to date has not been used in clinical care, and a recent analysis of the NCDR has shown a risktreatment paradox, in which patients at the highest risk of bleeding are preferentially not treated with effective bleed-
Brindis and Spertus President’s Page
2047
ing avoidance therapies, while those at the lowest risk for bleeding are (10). This is not only economically inefficient (using expensive interventions in those with the least potential to benefit, while avoiding them in those with the greatest potential to benefit), but it also worsens patient safety. Deploying an estimate of patients’ bleeding risk at the time of intervention can not only inform the patients about their risks, but could also be leveraged by physicians to target bivalirudin, closure devices, or inpatient admissions for closer observation after the procedure in those with moderate or high risk for periprocedural bleeding. The College is currently partnering with others to deploy its risk models within a patient-centered, individualized informed consent process to assist both patients and their physicians (11). If patients and physicians are to maximally benefit from improved medical decision-making, then several steps need to be taken. First, both clinical trials and registries need to start producing valid, clinically-useful risk prediction models of patients’ outcomes (12). Second, more research into how best to incorporate access to these models into clinical care and how they should be presented to patients and doctors needs to be performed. Finally, we need to recognize and reward the importance—and time required—to engage in shared decision-making. Toward this end, payers need to embrace the importance of shared decision-making by reimbursing clinicians for the time and resources needed to engage patients in an evidence-based discussion of their treatment options. An even more subtle point is that regulators need to appreciate that sometimes fully-informed patients may not select those therapies demanded by current performance measures. While the exclusions for some performance measures include patientcentered reasons for not selecting therapy, documenting these is not easy and there are concerns that clinicians who do a better job of following patients’ preferences may inadvertently appear to be performing lower-quality care. Until there is a system in place that rewards health care providers for quality outcomes and evidence-based care versus the volume of care provided, this will continue to be a major hindrance to the shared decision-making model. We have a ways to go before the shared decision-making model can be adopted on a national scale. That being said, the goals of shared decision making—to increase patient knowledge; encourage patient involvement in decision making; facilitate more realistic expectations of treatment options; and potentially reduce costs—are all ones we can and should support.
2048
Brindis and Spertus President’s Page
Toward that end, the College strongly supports both the application and research in the arena of shared decisionmaking. Our core values as cardiovascular professionals will continue to move us forward with identifying the challenges and opportunities associated with shared decision-making, in order to ensure that future shared decision-making models best meet the needs of patients and/or their families. Address correspondence to:
Ralph Brindis, MD, MPH, FACC American College of Cardiology 2400 N Street NW Washington, DC 20037 E-mail: [email protected]
REFERENCES
1. Porter ME, Teisberg EO. Redefining Health Care. Boston, MA: Harvard Business School Publishing, 2006. 2. O’Connor AM, Llewellyn-Thomas HA, Flood AB. Modifying Unwarranted Variations In Health Care: Shared Decision Making Using Patient Decision Aids. Health Affairs. October 7, 2004. 3. National Priorities Partnership. Input to the Secretary of Health and Human Services on Priorities for the 2011 National Quality Strategy. Available at: http://qualityforum.org/WorkArea/linkit.aspx?Link Identier⫽id&ItemID⫽43235. Accessed November 4, 2010.
JACC Vol. 56, No. 24, 2010 December 7, 2010:2046–8 4. Institute of Medicine. Crossing the Quality Chasm: A New Health System for the Twenty-first Century. Washington, DC: National Academy Press, 2001. 5. Grines CL, Bonow RO, Casey DE Jr., et al. Prevention of premature discontinuation of dual antiplatelet therapy in patients with coronary artery stents: a science advisory from the American Heart Association, American College of Cardiology, Society for Cardiovascular Angiography and Interventions, American College of Surgeons, and American Dental Association, with representation from the American College of Physicians. J Am Coll Cardiol 2007;49:734 –9. 6. Tu JV, Bowen J, Chiu M, et al. Effectiveness and safety of drugeluting stents in Ontario. N Engl J Med 2007;357:1393– 402. 7. Stone GW, Parise H, Witzenbichler B, et al. Selection criteria for drug-eluting versus bare-metal stents and the impact of routine angiographic follow-up: 2-year insights from the HORIZONS-AMI (Harmonizing Outcomes With Revascularization and Stents in Acute Myocardial Infarction) trial. J Am Coll Cardiol 2010;56:1597– 604. 8. Patient-Centered Education and Research. Salt Lake City, Utah. Available at: http://www.patient-centered.org. Accessed November 8, 2010. 9. Mehta SK, Frutkin AD, Lindsey JB, et al. Bleeding in patients undergoing percutaneous coronary intervention: the development of a clinical risk algorithm from the National Cardiovascular Data Registry. Circ Cardiovasc Intervent 2009;2:222–9. 10. Marso SP, Amin AP, House JA, et al. Association between use of bleeding avoidance strategies and risk of periprocedural bleeding among patients undergoing percutaneous coronary intervention. JAMA 2010;303:2156 – 64. 11. Arnold SV, Decker C, Ahmad H, et al. Converting the informed consent from a perfunctory process to an evidence-based foundation for patient decision making. Circ Cardiovascular Qual Outcomes 2008;1:21–2. 12. Kent DM, Rothwell PM, Ioannidis JP, Altman DG, Hayward RA. Assessing and reporting heterogeneity in treatment effects in clinical trials: a proposal. Trials 2010;11:85.