- Email: [email protected]
Understanding Population Health Through Diabetes Population Management
Understanding Population H e a l t h T h ro u g h D i a b e t e s Population Management Joanna Mitri,
MD, MS*,
Robert Gabbay,
MD, PhD
KEYWORDS Population health Population management Chronic disease Diabetes KEY POINTS Chronic diseases, in particular diabetes, are major drivers of cost in health care. Most of the costs related to diabetes are a result of preventable complications. Population health management’s goals in diabetes are to reduce cost and improve quality of care. Population health can address diabetes management challenges in many ways.
INTRODUCTION
There is a continued increase in the US population. Life expectancy and the proportion of individuals older than 65 year old are increasing.1 Chronic diseases including diabetes are the leading cause of death and constitute 46% of the global disease burden.2 Health care services are costly and complex for individuals with chronic diseases.3 In parallel, there is a shortage of physicians in most medical specialties.4 Specifically, the demand for endocrinologists is expected to increase secondary to the aging population with diabetes and obesity. It has been suggested that this demand will exceed the capacity of the endocrinology workforce. A more coordinated team based approach between endocrinologists, primary care providers, and other key team members will be needed to manage the population of patients with diabetes. The United States health care system is facing quality and cost challenges, a major driver of cost being chronic disease. According to the Centers for Disease Control and Prevention, more than 75% of our nation’s health care spending is on individuals with chronic conditions. Health systems are not oriented toward managing chronic diseases. Chronic disease management is complex and it entails multiple factors over
Disclosures: The authors have nothing to disclose. Joslin Diabetes Center, Lipid Clinic, Adult Diabetes, 1 Joslin Place, Boston, MA 02215, USA * Corresponding author. Joslin Diabetes Center, Lipid Clinic, Adult Diabetes, 1 Joslin Place, #239, Boston, MA 02215. E-mail address: [email protected] Endocrinol Metab Clin N Am - (2016) -–http://dx.doi.org/10.1016/j.ecl.2016.06.006 0889-8529/16/ª 2016 Elsevier Inc. All rights reserved.
endo.theclinics.com
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Mitri & Gabbay
a lifetime, as well as a more horizontal and integrated approach, with patient, family, and the community being active participants. The increasing global burden of chronic diseases necessitates stronger leadership by policymakers, advocates, and health care professionals. Developing effective strategies to prevent and manage these conditions is a global health priority.5 In an effort to reduce cost and improve quality of care in patients with chronic diseases, population health management has to do with organization of the health care system delivery system in a way that meets these 2 goals. Diabetes has often been an initial target disease for the key principles of chronic disease and population management given its high cost, prevalence, and available evidence-based quality metrics. This type of thinking requires a mental shift from simply focusing on individual patients one at a time to a broader perspective where the quality of care of a population of patients is tracked, and system based efforts are used to shift the health of that overall population of patients toward better quality and lower long-term costs by reducing complications. Herein, we describe several efforts to improve population management for diabetes, outline some of the challenges of measuring quality, and highlight system changes that can facilitate better care of those with chronic diseases such as diabetes. DIABETES, A CHRONIC DISEASE
The worldwide prevalence of diabetes has been increasing over the past few decades.6 The estimated prevalence of diabetes is 12% to 14% among US adults based on the National Health and Nutrition Examination Survey data. Diabetes represents a major threat to public health in many countries of the world. The costs associated with diabetes are sizable and noted to be 245 billion annually in the United States alone.7 Diabetes affects 29 million people—9.3% of the US population.8 Out of these, only 21 million have been officially diagnosed; 8 million remain undiagnosed. More important, an estimated 79 million American adults aged 20 years or older have prediabetes. The leading cause of kidney failure, nontraumatic lower limb amputations, and new cases of blindness remains diabetes, and it remains the major cause of cardiovascular disease. Based on these numbers, there is an urgent need for national plans to improve diabetes prevention and quality of care. International health organizations are also monitoring quality of care indicators at the population level; however, this monitoring remains a challenge for many countries.9 There are large gaps between what guidelines recommend and actual achievement of care goals.10 Individualized glycemic control and multifactorial risk reduction are the cornerstones of high-quality diabetes care. Despite national decline in hemoglobin A1c, 33% to 49% of patients still do not meet targets for glycemic, blood pressure or cholesterol control. Only 14% of patients meet targets for all 3 measures and nonsmoking status.10 It is likely that patient factors play a role in this; however, the persistent variation in quality of diabetes care across providers and practice settings indicate a problem at the system level. The health care system is fragmented and poorly designed to coordinate care management for chronic diseases. There are unmet needs for an increasing number of people who have a chronic disease such as diabetes. Health care reform calls for new approaches to diabetes care delivery and greater emphasis on improving the efficiency and ability of health systems to respond to chronic disease to prevent diabetes and its complications in an equitable manner. Reversing the diabetes epidemic requires remaking of our health care delivery system by focusing on proactive prevention, improved delivery of care, and continuous access to coordinated, evidence-based management of chronic diseases.
Diabetes Population Management
Diabetes management extends beyond blood glucose control. Regulation of metabolic risk factors such as body weight, blood pressure, and lipid profile is needed. In addition, preventative strategies such as annual eye and foot examinations, and lifestyle modifications such as physical activity, dietary modification, and smoking cessation require extensive counseling and coordination. Although there are guidelines for goals in diabetes management, there is a need to individualize care for patients, particularly when it comes to glycemic goals. POPULATION MANAGEMENT
Despite increasing awareness of population health management, the concept remains unclearly defined and even less well-understood. Population health has been defined as the health outcomes of a group of individuals, including the distribution of such outcomes within the group. Whereas medical care is a key factor that affects health outcomes, other factors include public health interventions, social and physical environment, genetics, and individual behavior.11 Based on this concept, there have been some efforts to combine health care with social services to improve population health.12 Population health management is an approach to medicine that improves patient access to care and helps patients to navigate the complex health care system. It facilitates care delivery across the general population and helps patients to make the best possible health care decisions. The goal is to improve care and reduce health care cost by keeping the patient population as healthy as possible and reducing the need for expensive interventions such as emergency department visits, hospitalizations, and procedures. The advent of shared accountability financial arrangements between delivery systems and purchasers has created significant financial incentives to focus on population health management and measuring and reporting its outcomes. Accountable care organizations, at-risk contracting, and value-based payment all involve the continuum of US health care payment models that aim to reward health care systems beyond the traditional fee-for-service model. Fundamentally, these payment models incentivize better population management by rewarding health systems for better quality outcomes, and diabetes fits nicely in this framework because most of the costs associated with diabetes are related to long-term complications, which can be reduced significantly with better management of intermediate outcomes such as hemoglobin A1c, blood pressure, and lipids. Health care systems are shifting from fee-forservice to different types of value-based and shared risk alternative payments models like accountable care organizations. This shift provides an enormous opportunity for the health systems to invest in services that have traditionally been poorly reimbursed (eg, diabetes self-management education and support) to lower overall health care costs. Population health management requires major changes at the system and provider levels. Providers have learned to care for an individual patient seeking care rather than managing an entire population of individuals. In a new era of value-based and shared risk payment, providers will need to learn how to work together by coordinating care and exchanging health information. Health care organizations, on the other hand, need to adapt to a new reimbursement models, change structure and leadership approaches. The Centers for Medicare and Medicaid Services reimbursement is shifting dramatically. The goal is to have 85% of all Medicare fee-for-service payments tied to quality by 2016% and 90% by 2018. Also, 30% of Medicare payments will be tied to quality or value through alternative payment models such as accountable care
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organizations and bundled payment arrangements by the end of 2016, and 50% of payments by the end of 2018. Health care providers will be accountable for the quality and cost of the care they deliver to patient populations under accountable care organizations and bundled payment arrangements (Box 1).13 THE CHALLENGES WITH MEASURING POPULATION HEALTH
Measuring is where successful population health management starts. One of the challenges lies in how to measure success and failure. The most common measures are: 1. Process measures: these measures are the specific steps in a process, ensuring appropriate processes have occurred, like yearly eye examinations. 2. Intermediate measures: these are physiologic or biochemical values, like control of hemoglobin A1c, blood pressure, or low-density lipoprotein cholesterol value. These precede and may lead to longer-range end result outcomes. 3. Finally, true disease outcomes are measures of a reduction of complications, for example, fewer amputations or cases of blindness. The most widely used quality measures in the United States are The Healthcare Effectiveness Data and Information Set measures. These measures are used by more than 90% of America’s health plans to measure performance on important dimensions of care and service. They also form the basis for the Provider Recognition Program by the National Center for Quality Assurance and used for provider recognition. The 81 Healthcare Effectiveness Data and Information Set measures are divided into 5 domains of care: effectiveness of care, access and availability of care, experience of care, utilization and relative resource use, and health plan descriptive information.14 These measures evolve over time but currently for diabetes include the percentage of patients: Testing blood glucose level (hemoglobin A1c test); Controlling hemoglobin A1c level; Screening for serum cholesterol level (low-density lipoprotein cholesterol screening); Controlling serum cholesterol level; Examining eyes for retinal disease; Monitoring for kidney disease; Controlling high blood pressure; and Medical assistance with smoking cessation. Although Healthcare Effectiveness Data and Information Set measures have been reported for many years, there is a need for more refined measures for population
Box 1 Goals of population health management 1. Reduce the frequency of acute and chronic complications of chronic diseases. 2. Lower the cost per service through an integrated delivery of care team approach. 3. Improve the overall patient experience. 4. Promote patient engagement and empower patients to better self-manage their health, and participate in the decision making process.
Diabetes Population Management
health management. A consensus development conference was convened by the American Diabetes Association to discuss the future of performance measurement in diabetes. One of the raised questions was the future of quality measurement in diabetes. Several new opportunities for quality measurement in diabetes were identified, and included clinical action measures, weighted quality measures, personalized riskbased quality measures, measures of overtreatment, and quality measures for primary prevention of diabetes. Additional opportunities involve incorporating measures of adherence into performances measures, incorporating costs into quality measures, and using performance measurement to reduce, not worsen, health disparities.15 Data analysis is an integral part of population health management. Data should report on mortality rates, health status, disease prevalence, and even patient experience. These reports are the basis for quality reporting to payers or outside entities and they serve as a measure of provider’s quality of care and patient outcomes. This only emphasizes the need of programs that can incorporate different types of data, include patient self-reports and be able to reports on different subpopulation. In this way, trends and gaps can be identified. Most of the measures neglect the distribution of outcomes within these subpopulations, which can only inevitably widen health gaps by improving the health of some, while leaving marginalized communities behind. Most health care providers and organizations see the critical importance of population health management; however, they do not have the information technology infrastructure that is required to implement it successfully. To advance population health management, providers also must develop electronic registries with populationwide databases that are not limited to patients with specific diseases. ROLE OF INFORMATION TECHNOLOGY
The current tools used by organizations do not have the ability to store, manage, and distribute comprehensive, timely, and relevant information to the degree needed for population management. There is a need for electronic registries with populationwide databases. Registries capture clinical data, claims data, administrative data, and self-reported patient data to power clinical decisions and identify gaps in care. There is a wealth of information at the disposal of health systems, but typically they are not integrated into a single system that can provide real time data for providers. Using this information will facilitate delivery of information-powered care to patients in real time to advance clinical outcomes, improve quality, and lower costs. Organizations need to identify and invest in physician leaders, who can manage and drive the results. Sharing data on quality of care across provides can spur opportunities for “healthy competition,” as different providers work to improve their outcomes compared with their peers. Appropriate leadership can promote better quality by highlighting those that have achieved better outcomes and spread their approaches to other providers who have been less successful. Ongoing outcome reporting can then ensure that the providers are continuously focused on improved population outcomes. Clinical information professionals are in the midst of the greatest transformation in the history of the US health care system. POPULATION HEALTH AND DIABETES Challenges in Diabetes Timely diagnosis
One of the ongoing challenges in diabetes is timely diagnosis. The median delay from the onset of diabetes to physician diagnosis is 2.4 years, with more than 7% of cases remaining undiagnosed for at least 7.5 years.16 By the time type 2 diabetes is
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diagnosed, many patients have already developed microvascular complications. Population health management tools can be used to identify those at high risk for diabetes and ensure timely screening for diabetes occurs. Transition of care
Diabetes is a complex disease requiring care by multiple specialists and care providers. It has been shown that errors could result from lack of communication and coordination among providers as well as lack of effective data sharing.17 One particularly problematic area where disconnects can play a role is when transitioning from an acute care setting. Hospital readmissions can be reduced by better coordination of care from the inpatient to outpatient settings.18 Patients with diabetes have a significantly higher hospital readmission rate and better coordination of care is key to reducing this trend. Self-management
Behavioral management is a critical element in disease management. Providers face the major challenge of getting patients with chronic diseases to take more responsibility for their own health. Empowering patients is time consuming and cannot be achieved easily in a typically short visit. Engagement plays an important role in adherence to the care plan. Every individual must take responsibility for promoting his or her own health. However, individual’s health behaviors are influenced by many factors, including the patient’s family, culture, environment, socioeconomic status, insurance, care access, and health literacy. Many patients will require support and assistance to improve illness self-management. Diabetes self-management education improves psychosocial and clinical outcomes in patients with diabetes,19 but is typically underused. How Population Health Can Address Diabetes
Being a chronic and progressive illness, diabetes requires early diagnosis, effective coordination of care and self-management to stem its progression. Population health management strategies hold promise to improve outcomes. Identification of high-risk patients
To achieve better diabetes outcomes at lower cost, the first step involves identifying relevant patients and stratifying them according to clinical risk. The greatest opportunity to lower health care costs is to focus on those at high risk, for example, those with a hemoglobin A1c of greater than 9%. Those who are furthest from evidence-based goals are most likely in the short term to contribute to health care costs through avoidable hospitalizations and emergency visits. Proactively identifying these patients can enable outreach efforts to address their needs. Care management where an individual within a practice focuses on these high-risk patients through outreach, engagement, self-management support, and problem solving has been shown to be one of the most effective quality improvement interventions for glycemic control.8 At-risk population identified from aggregated risk factor data should be screened to avoid delays in diagnosis. Early glycemic control can be achieved only after a timely diagnosis. Automated patient identification systems and surveillance applications that ingest data in near-real time can help health care organizations close this gap and begin intervention at the earliest possible time. In addition to speeding the diagnosis of diabetes, analytics can help to identify prediabetic individuals. Such early identification can prompt assignment to a lifestyle management program to prevent progression to type 2 diabetes. It has been shown in the Diabetes Prevention Program
Diabetes Population Management
that intensive lifestyle intervention, including dietary modification, weight loss, and increases in physical activity, can prevent progression of type 2 diabetes.20 Once the diabetes population is stratified, one can design referral strategies and identify gaps in care that can ensure the right patient is seen in the right setting. One may think of this as a “pyramid of risk,” with the highest risk patients at the top and being most appropriate for endocrinologist care and those at lower risk being cared for primarily in primary care with some guidance and education by endocrinologists (Fig. 1). Coordination of care
Diabetes management involves a range of specialty physicians, dietitians, exercise physiologists, diabetes educators, primary care providers, and behavioral health specialists. Effective diabetes care requires collaboration across the care community to avoid miscommunication among providers and ineffective care transitions. It has been shown that proactive previsit preparation may be a key strategy for primary care practices to improve areas critical for chronic disease management, such as patient engagement, kept appointments, and adherence with recommended screenings, tests, and services.11 Supporting primary care practices in practice redesign, and transforming practices into teams where doctors and other caregivers work to coordinate care for patients, improve both clinical outcomes and patient satisfaction.21 The ultimate goal would be to keep high-risk individuals healthier and lower the overall costs for their care by preventing avoidable hospital visits. Patient engagement
Through a team-based practice and with family support, patients are motivated to change their lifestyle, be adherent with medications, and build a support network. Identifying what team members can most effectively engage patents is a key step. Diabetes educators are well-suited to this role, but ongoing self-management support is critical to achieve optimal outcomes.
CHRONIC CARE DELIVERY
To target fragmentation of our health care delivery system, duplicate services, and lack of clinical information, the chronic care model22 and the patient-centered medical home (PCMH) model21 were developed to provide frameworks for effective care of diabetes and other chronic diseases. By incorporating team care as a vital component
Fig. 1. Pyramid of risk. CVD, cardiovascular disease; PCP, primary care physician.
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of delivery system design, these models will serve as guidance for health care reform initiatives aiming for an integrated health care delivery system. The chronic care model provides patients with self-management skills and tracking systems. It represents a well-rounded approach to restructuring medical care through partnerships between health systems and communities. The model ensures that a prepared proactive practice team has productive interactions with an informed activated patient, and focuses on the domains needed to achieve this goal. It has been shown that the chronic care model is generally effective for managing diabetes in US primary care settings.23 The PCMH is a great example of a new health delivery system that developed out from the principles of the chronic care model framework. Leading primary care organizations introduced the PCMH to address high costs and poor health outcomes, particularly those related to chronic medical conditions, such as hypertension and diabetes. The objective of the PCMH model of care is to have a centralized setting that facilitates partnerships between patients and their personal physicians and, when appropriate, the patient’s family.24 Medically complex patients can be managed through an integrated care management program, which assigns nurse care managers to oversee complicated and chronically ill patients with multiple medical conditions, such as diabetes or heart disease. The PCMH has been shown to be a viable mechanism to improve the quality and costs of diabetes care.25 The basic elements of a PCMH are care coordination, quality and safety, whole person orientation, personal physician, enhanced access, and payment reform. A critical component of a medical home practice is care with coordination and communication among its members and where information technology is essential to improve patient-centered care.26,27 Efforts to transform diabetes care align with the aims of PCMH. In a typical workflow, the patient experience is improved when previous results and past medical records have been collected and merged across health care providers. One of the main goals of the visit is to empower patients enable to manage their own care. In summary, the PCMH has shown promise for improving outcomes through coordinated primary care and better coordination with others outside primary care—sometimes referred to as the medical neighborhood.28 IMPROVING QUALITY THROUGH POPULATION HEALTH
The framework of the PCMH has been the focus of the most recent efforts to drive better diabetes care in the primary care. Some attributes of the PMCH is for practices to assess care quality at the population level uses evidence-based measures, identify high-risk patients for outreach and care management, and enhance patient engagement—all key aspects of population management. Many of the early PCMH pilots focused on diabetes as a target disease and have showed improvements in both process and outcome measures.21 For example, a large multipayer supported PMCH initiative in Pennsylvania had its initial focus on diabetes. More than 100 primary practices across the state were transformed to National Center for Quality Assurance reconfigured PCMHs through practice facilitation, monthly population level reporting of clinical quality measures and implementation of care management for high risk patients. After 1 year, there was a significant improvement in diabetes process measures (annual eye examination, nephropathy screening, foot examinations, pneumonia vaccination, and smoking cessation) and clinical measures of diabetes control.25 These changes were also associated with improvements on health care use.14
Diabetes Population Management
SUMMARY
In an era of accountable care organizations, health care systems need to be redesigned to care for the chronically ill. Diabetes is a great example of a chronic disease that could be partly prevented, but more important most of its complications that are costly and burdensome could be prevented. Population health management, which seeks to decrease health care cost and improve quality of care, can address most of the challenges in diabetes management. However, it cannot be achieved successfully without information technology system in place and a mental shift of provider who has been trained on treating the acutely ill and typically incentivized by reimbursement for every provided service. Stratifying populations based on risk is an important step to ensuring the right patient receives the right care from the right provider. Better measurement tools for assessing diabetes quality continue to evolve, and systems to better coordinate care within a medical neighborhood will be important elements to refine. As has happened so often in the history of health care delivery changes, the field of diabetes care has the opportunity to lead the way in developing this more comprehensive approach to care. Health care organizations, payers, and stakeholders have a big challenge to find the best delivery and payment model to meet populations’ needs. REFERENCES
1. National Center for Health Statistics. Health, United States, 2012: with special feature on emergency care. Hyattsville (MD): 2013. 2. Coleman K, Austin BT, Brach C, et al. Evidence on the chronic care model in the new millennium. Health Aff (Millwood) 2009;28(1):75–85. 3. McColl MA, Shortt S, Gignac M, et al. Disentangling the effects of disability and age on health service utilisation. Disabil Rehabil 2011;33(13–14):1253–61. 4. Dill MJ, Salsberg ES. Association of American Medical Colleges. The complexities of physician supply and demand: Projections through 2025. Available at: https:// members.aamc.org/eweb/upload/The%20Complexities%20of%20Physician%20 Supply.pdf. Accessed March 29, 2016. 5. Yach D, Hawkes C, Gould CL, et al. The global burden of chronic diseases: overcoming impediments to prevention and control. JAMA 2004;291(21): 2616–22. 6. Danaei G, Finucane MM, Lu Y, et al. National, regional, and global trends in fasting plasma glucose and diabetes prevalence since 1980: systematic analysis of health examination surveys and epidemiological studies with 370 country-years and 2.7 million participants. Lancet 2011;378(9785):31–40. 7. American Diabetes Association. Economic costs of diabetes in the U.S. in 2012. Diabetes Care 2013;36:1033–46. 8. Shojania KG, Ranji SR, McDonald KM, et al. Effects of quality improvement strategies for type 2 diabetes on glycemic control: a meta-regression analysis. JAMA 2006;296(4):427–40. 9. OECD. Cardiovascular disease and diabetes: policies for better health and quality of care. Paris: OECD Publishing; 2015. 10. Ali MK, Bullard KM, Saaddine JB, et al. Achievement of goals in U.S. diabetes care, 1999-2010. N Engl J Med 2013;368(17):1613–24. 11. Kindig D, Stoddart G. What is population health? Am J Public Health 2003;93(3): 380–3.
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12. Shortell SM, Zukoski AP, Alexander JA, et al. Evaluating partnerships for community health improvement: tracking the footprints. J Health Polit Policy Law 2002; 27(1):49–91. 13. Burwell SM. Setting value-based payment goals–HHS efforts to improve U.S. health care. N Engl J Med 2015;372(10):897–9. 14. Friedberg MW, Rosenthal MB, Werner RM, et al. Effects of a medical home and shared savings intervention on quality and utilization of care. JAMA Intern Med 2015;175(8):1362–8. 15. O’Connor PJ, Bodkin NL, Fradkin J, et al. Diabetes performance measures: current status and future directions. Diabetes Care 2011;34(7):1651–9. 16. Samuels TA, Cohen D, Brancati FL, et al. Delayed diagnosis of incident type 2 diabetes mellitus in the ARIC study. Am J Manag Care 2006;12(12):717–24. 17. Elhauge E. The Fragmentation of U.S. Health Care: causes and solutions. New York, NY: Oxford University press; 2010. 18. Naylor MD, Kurtzman ET, Grabowski DC, et al. Unintended consequences of steps to cut readmissions and reform payment may threaten care of vulnerable older adults 2012;31(7):1623–32. 19. Norris SL, Lau J, Smith SJ, et al. Self-management education for adults with type 2 diabetes: a meta-analysis of the effect on glycemic control. Diabetes Care 2002;25(7):1159–71. 20. Diabetes Prevention Program Research Group, Knowler WC, Fowler SE, et al. 10year follow-up of diabetes incidence and weight loss in the Diabetes Prevention Program Outcomes Study. Lancet 2009;374(9702):1677–86. 21. Bojadzievski T, Gabbay RA. Patient-centered medical home and diabetes. Diabetes Care 2011;34(4):1047–53. 22. Wagner EH, Austin BT, Von Korff M. Improving outcomes in chronic illness. Manag Care Q 1996;4(2):12–25. 23. Stellefson M, Dipnarine K, Stopka C. The chronic care model and diabetes management in US primary care settings: a systematic review. Prev Chronic Dis 2013; 10:E26. 24. Martsolf GR, Kandrack R, Gabbay RA, et al. Cost of transformation among primary care practices participating in a Medical Home Pilot. J Gen Intern Med 2016;31(7):723–31. 25. Gabbay RA, Bailit MH, Mauger DT, et al. Multipayer patient-centered medical home implementation guided by the chronic care model. Jt Comm J Qual Patient Saf 2011;37(6):265–73. 26. Cohn KH, Berman J, Chaiken B, et al. Engaging physicians to adopt healthcare information technology. J Healthc Manag 2009;54(5):291–300. 27. Weber V, Bloom F, Pierdon S, et al. Employing the electronic health record to improve diabetes care: a multifaceted intervention in an integrated delivery system. J Gen Intern Med 2008;23(4):379–82. 28. Spatz C, Gabbay R. The patient-centered medical neighborhood and diabetes care. Diabetes Spectr 2014;27(2):131–3.
MD, MS*,
Robert Gabbay,
MD, PhD
KEYWORDS Population health Population management Chronic disease Diabetes KEY POINTS Chronic diseases, in particular diabetes, are major drivers of cost in health care. Most of the costs related to diabetes are a result of preventable complications. Population health management’s goals in diabetes are to reduce cost and improve quality of care. Population health can address diabetes management challenges in many ways.
INTRODUCTION
There is a continued increase in the US population. Life expectancy and the proportion of individuals older than 65 year old are increasing.1 Chronic diseases including diabetes are the leading cause of death and constitute 46% of the global disease burden.2 Health care services are costly and complex for individuals with chronic diseases.3 In parallel, there is a shortage of physicians in most medical specialties.4 Specifically, the demand for endocrinologists is expected to increase secondary to the aging population with diabetes and obesity. It has been suggested that this demand will exceed the capacity of the endocrinology workforce. A more coordinated team based approach between endocrinologists, primary care providers, and other key team members will be needed to manage the population of patients with diabetes. The United States health care system is facing quality and cost challenges, a major driver of cost being chronic disease. According to the Centers for Disease Control and Prevention, more than 75% of our nation’s health care spending is on individuals with chronic conditions. Health systems are not oriented toward managing chronic diseases. Chronic disease management is complex and it entails multiple factors over
Disclosures: The authors have nothing to disclose. Joslin Diabetes Center, Lipid Clinic, Adult Diabetes, 1 Joslin Place, Boston, MA 02215, USA * Corresponding author. Joslin Diabetes Center, Lipid Clinic, Adult Diabetes, 1 Joslin Place, #239, Boston, MA 02215. E-mail address: [email protected] Endocrinol Metab Clin N Am - (2016) -–http://dx.doi.org/10.1016/j.ecl.2016.06.006 0889-8529/16/ª 2016 Elsevier Inc. All rights reserved.
endo.theclinics.com
2
Mitri & Gabbay
a lifetime, as well as a more horizontal and integrated approach, with patient, family, and the community being active participants. The increasing global burden of chronic diseases necessitates stronger leadership by policymakers, advocates, and health care professionals. Developing effective strategies to prevent and manage these conditions is a global health priority.5 In an effort to reduce cost and improve quality of care in patients with chronic diseases, population health management has to do with organization of the health care system delivery system in a way that meets these 2 goals. Diabetes has often been an initial target disease for the key principles of chronic disease and population management given its high cost, prevalence, and available evidence-based quality metrics. This type of thinking requires a mental shift from simply focusing on individual patients one at a time to a broader perspective where the quality of care of a population of patients is tracked, and system based efforts are used to shift the health of that overall population of patients toward better quality and lower long-term costs by reducing complications. Herein, we describe several efforts to improve population management for diabetes, outline some of the challenges of measuring quality, and highlight system changes that can facilitate better care of those with chronic diseases such as diabetes. DIABETES, A CHRONIC DISEASE
The worldwide prevalence of diabetes has been increasing over the past few decades.6 The estimated prevalence of diabetes is 12% to 14% among US adults based on the National Health and Nutrition Examination Survey data. Diabetes represents a major threat to public health in many countries of the world. The costs associated with diabetes are sizable and noted to be 245 billion annually in the United States alone.7 Diabetes affects 29 million people—9.3% of the US population.8 Out of these, only 21 million have been officially diagnosed; 8 million remain undiagnosed. More important, an estimated 79 million American adults aged 20 years or older have prediabetes. The leading cause of kidney failure, nontraumatic lower limb amputations, and new cases of blindness remains diabetes, and it remains the major cause of cardiovascular disease. Based on these numbers, there is an urgent need for national plans to improve diabetes prevention and quality of care. International health organizations are also monitoring quality of care indicators at the population level; however, this monitoring remains a challenge for many countries.9 There are large gaps between what guidelines recommend and actual achievement of care goals.10 Individualized glycemic control and multifactorial risk reduction are the cornerstones of high-quality diabetes care. Despite national decline in hemoglobin A1c, 33% to 49% of patients still do not meet targets for glycemic, blood pressure or cholesterol control. Only 14% of patients meet targets for all 3 measures and nonsmoking status.10 It is likely that patient factors play a role in this; however, the persistent variation in quality of diabetes care across providers and practice settings indicate a problem at the system level. The health care system is fragmented and poorly designed to coordinate care management for chronic diseases. There are unmet needs for an increasing number of people who have a chronic disease such as diabetes. Health care reform calls for new approaches to diabetes care delivery and greater emphasis on improving the efficiency and ability of health systems to respond to chronic disease to prevent diabetes and its complications in an equitable manner. Reversing the diabetes epidemic requires remaking of our health care delivery system by focusing on proactive prevention, improved delivery of care, and continuous access to coordinated, evidence-based management of chronic diseases.
Diabetes Population Management
Diabetes management extends beyond blood glucose control. Regulation of metabolic risk factors such as body weight, blood pressure, and lipid profile is needed. In addition, preventative strategies such as annual eye and foot examinations, and lifestyle modifications such as physical activity, dietary modification, and smoking cessation require extensive counseling and coordination. Although there are guidelines for goals in diabetes management, there is a need to individualize care for patients, particularly when it comes to glycemic goals. POPULATION MANAGEMENT
Despite increasing awareness of population health management, the concept remains unclearly defined and even less well-understood. Population health has been defined as the health outcomes of a group of individuals, including the distribution of such outcomes within the group. Whereas medical care is a key factor that affects health outcomes, other factors include public health interventions, social and physical environment, genetics, and individual behavior.11 Based on this concept, there have been some efforts to combine health care with social services to improve population health.12 Population health management is an approach to medicine that improves patient access to care and helps patients to navigate the complex health care system. It facilitates care delivery across the general population and helps patients to make the best possible health care decisions. The goal is to improve care and reduce health care cost by keeping the patient population as healthy as possible and reducing the need for expensive interventions such as emergency department visits, hospitalizations, and procedures. The advent of shared accountability financial arrangements between delivery systems and purchasers has created significant financial incentives to focus on population health management and measuring and reporting its outcomes. Accountable care organizations, at-risk contracting, and value-based payment all involve the continuum of US health care payment models that aim to reward health care systems beyond the traditional fee-for-service model. Fundamentally, these payment models incentivize better population management by rewarding health systems for better quality outcomes, and diabetes fits nicely in this framework because most of the costs associated with diabetes are related to long-term complications, which can be reduced significantly with better management of intermediate outcomes such as hemoglobin A1c, blood pressure, and lipids. Health care systems are shifting from fee-forservice to different types of value-based and shared risk alternative payments models like accountable care organizations. This shift provides an enormous opportunity for the health systems to invest in services that have traditionally been poorly reimbursed (eg, diabetes self-management education and support) to lower overall health care costs. Population health management requires major changes at the system and provider levels. Providers have learned to care for an individual patient seeking care rather than managing an entire population of individuals. In a new era of value-based and shared risk payment, providers will need to learn how to work together by coordinating care and exchanging health information. Health care organizations, on the other hand, need to adapt to a new reimbursement models, change structure and leadership approaches. The Centers for Medicare and Medicaid Services reimbursement is shifting dramatically. The goal is to have 85% of all Medicare fee-for-service payments tied to quality by 2016% and 90% by 2018. Also, 30% of Medicare payments will be tied to quality or value through alternative payment models such as accountable care
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organizations and bundled payment arrangements by the end of 2016, and 50% of payments by the end of 2018. Health care providers will be accountable for the quality and cost of the care they deliver to patient populations under accountable care organizations and bundled payment arrangements (Box 1).13 THE CHALLENGES WITH MEASURING POPULATION HEALTH
Measuring is where successful population health management starts. One of the challenges lies in how to measure success and failure. The most common measures are: 1. Process measures: these measures are the specific steps in a process, ensuring appropriate processes have occurred, like yearly eye examinations. 2. Intermediate measures: these are physiologic or biochemical values, like control of hemoglobin A1c, blood pressure, or low-density lipoprotein cholesterol value. These precede and may lead to longer-range end result outcomes. 3. Finally, true disease outcomes are measures of a reduction of complications, for example, fewer amputations or cases of blindness. The most widely used quality measures in the United States are The Healthcare Effectiveness Data and Information Set measures. These measures are used by more than 90% of America’s health plans to measure performance on important dimensions of care and service. They also form the basis for the Provider Recognition Program by the National Center for Quality Assurance and used for provider recognition. The 81 Healthcare Effectiveness Data and Information Set measures are divided into 5 domains of care: effectiveness of care, access and availability of care, experience of care, utilization and relative resource use, and health plan descriptive information.14 These measures evolve over time but currently for diabetes include the percentage of patients: Testing blood glucose level (hemoglobin A1c test); Controlling hemoglobin A1c level; Screening for serum cholesterol level (low-density lipoprotein cholesterol screening); Controlling serum cholesterol level; Examining eyes for retinal disease; Monitoring for kidney disease; Controlling high blood pressure; and Medical assistance with smoking cessation. Although Healthcare Effectiveness Data and Information Set measures have been reported for many years, there is a need for more refined measures for population
Box 1 Goals of population health management 1. Reduce the frequency of acute and chronic complications of chronic diseases. 2. Lower the cost per service through an integrated delivery of care team approach. 3. Improve the overall patient experience. 4. Promote patient engagement and empower patients to better self-manage their health, and participate in the decision making process.
Diabetes Population Management
health management. A consensus development conference was convened by the American Diabetes Association to discuss the future of performance measurement in diabetes. One of the raised questions was the future of quality measurement in diabetes. Several new opportunities for quality measurement in diabetes were identified, and included clinical action measures, weighted quality measures, personalized riskbased quality measures, measures of overtreatment, and quality measures for primary prevention of diabetes. Additional opportunities involve incorporating measures of adherence into performances measures, incorporating costs into quality measures, and using performance measurement to reduce, not worsen, health disparities.15 Data analysis is an integral part of population health management. Data should report on mortality rates, health status, disease prevalence, and even patient experience. These reports are the basis for quality reporting to payers or outside entities and they serve as a measure of provider’s quality of care and patient outcomes. This only emphasizes the need of programs that can incorporate different types of data, include patient self-reports and be able to reports on different subpopulation. In this way, trends and gaps can be identified. Most of the measures neglect the distribution of outcomes within these subpopulations, which can only inevitably widen health gaps by improving the health of some, while leaving marginalized communities behind. Most health care providers and organizations see the critical importance of population health management; however, they do not have the information technology infrastructure that is required to implement it successfully. To advance population health management, providers also must develop electronic registries with populationwide databases that are not limited to patients with specific diseases. ROLE OF INFORMATION TECHNOLOGY
The current tools used by organizations do not have the ability to store, manage, and distribute comprehensive, timely, and relevant information to the degree needed for population management. There is a need for electronic registries with populationwide databases. Registries capture clinical data, claims data, administrative data, and self-reported patient data to power clinical decisions and identify gaps in care. There is a wealth of information at the disposal of health systems, but typically they are not integrated into a single system that can provide real time data for providers. Using this information will facilitate delivery of information-powered care to patients in real time to advance clinical outcomes, improve quality, and lower costs. Organizations need to identify and invest in physician leaders, who can manage and drive the results. Sharing data on quality of care across provides can spur opportunities for “healthy competition,” as different providers work to improve their outcomes compared with their peers. Appropriate leadership can promote better quality by highlighting those that have achieved better outcomes and spread their approaches to other providers who have been less successful. Ongoing outcome reporting can then ensure that the providers are continuously focused on improved population outcomes. Clinical information professionals are in the midst of the greatest transformation in the history of the US health care system. POPULATION HEALTH AND DIABETES Challenges in Diabetes Timely diagnosis
One of the ongoing challenges in diabetes is timely diagnosis. The median delay from the onset of diabetes to physician diagnosis is 2.4 years, with more than 7% of cases remaining undiagnosed for at least 7.5 years.16 By the time type 2 diabetes is
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diagnosed, many patients have already developed microvascular complications. Population health management tools can be used to identify those at high risk for diabetes and ensure timely screening for diabetes occurs. Transition of care
Diabetes is a complex disease requiring care by multiple specialists and care providers. It has been shown that errors could result from lack of communication and coordination among providers as well as lack of effective data sharing.17 One particularly problematic area where disconnects can play a role is when transitioning from an acute care setting. Hospital readmissions can be reduced by better coordination of care from the inpatient to outpatient settings.18 Patients with diabetes have a significantly higher hospital readmission rate and better coordination of care is key to reducing this trend. Self-management
Behavioral management is a critical element in disease management. Providers face the major challenge of getting patients with chronic diseases to take more responsibility for their own health. Empowering patients is time consuming and cannot be achieved easily in a typically short visit. Engagement plays an important role in adherence to the care plan. Every individual must take responsibility for promoting his or her own health. However, individual’s health behaviors are influenced by many factors, including the patient’s family, culture, environment, socioeconomic status, insurance, care access, and health literacy. Many patients will require support and assistance to improve illness self-management. Diabetes self-management education improves psychosocial and clinical outcomes in patients with diabetes,19 but is typically underused. How Population Health Can Address Diabetes
Being a chronic and progressive illness, diabetes requires early diagnosis, effective coordination of care and self-management to stem its progression. Population health management strategies hold promise to improve outcomes. Identification of high-risk patients
To achieve better diabetes outcomes at lower cost, the first step involves identifying relevant patients and stratifying them according to clinical risk. The greatest opportunity to lower health care costs is to focus on those at high risk, for example, those with a hemoglobin A1c of greater than 9%. Those who are furthest from evidence-based goals are most likely in the short term to contribute to health care costs through avoidable hospitalizations and emergency visits. Proactively identifying these patients can enable outreach efforts to address their needs. Care management where an individual within a practice focuses on these high-risk patients through outreach, engagement, self-management support, and problem solving has been shown to be one of the most effective quality improvement interventions for glycemic control.8 At-risk population identified from aggregated risk factor data should be screened to avoid delays in diagnosis. Early glycemic control can be achieved only after a timely diagnosis. Automated patient identification systems and surveillance applications that ingest data in near-real time can help health care organizations close this gap and begin intervention at the earliest possible time. In addition to speeding the diagnosis of diabetes, analytics can help to identify prediabetic individuals. Such early identification can prompt assignment to a lifestyle management program to prevent progression to type 2 diabetes. It has been shown in the Diabetes Prevention Program
Diabetes Population Management
that intensive lifestyle intervention, including dietary modification, weight loss, and increases in physical activity, can prevent progression of type 2 diabetes.20 Once the diabetes population is stratified, one can design referral strategies and identify gaps in care that can ensure the right patient is seen in the right setting. One may think of this as a “pyramid of risk,” with the highest risk patients at the top and being most appropriate for endocrinologist care and those at lower risk being cared for primarily in primary care with some guidance and education by endocrinologists (Fig. 1). Coordination of care
Diabetes management involves a range of specialty physicians, dietitians, exercise physiologists, diabetes educators, primary care providers, and behavioral health specialists. Effective diabetes care requires collaboration across the care community to avoid miscommunication among providers and ineffective care transitions. It has been shown that proactive previsit preparation may be a key strategy for primary care practices to improve areas critical for chronic disease management, such as patient engagement, kept appointments, and adherence with recommended screenings, tests, and services.11 Supporting primary care practices in practice redesign, and transforming practices into teams where doctors and other caregivers work to coordinate care for patients, improve both clinical outcomes and patient satisfaction.21 The ultimate goal would be to keep high-risk individuals healthier and lower the overall costs for their care by preventing avoidable hospital visits. Patient engagement
Through a team-based practice and with family support, patients are motivated to change their lifestyle, be adherent with medications, and build a support network. Identifying what team members can most effectively engage patents is a key step. Diabetes educators are well-suited to this role, but ongoing self-management support is critical to achieve optimal outcomes.
CHRONIC CARE DELIVERY
To target fragmentation of our health care delivery system, duplicate services, and lack of clinical information, the chronic care model22 and the patient-centered medical home (PCMH) model21 were developed to provide frameworks for effective care of diabetes and other chronic diseases. By incorporating team care as a vital component
Fig. 1. Pyramid of risk. CVD, cardiovascular disease; PCP, primary care physician.
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of delivery system design, these models will serve as guidance for health care reform initiatives aiming for an integrated health care delivery system. The chronic care model provides patients with self-management skills and tracking systems. It represents a well-rounded approach to restructuring medical care through partnerships between health systems and communities. The model ensures that a prepared proactive practice team has productive interactions with an informed activated patient, and focuses on the domains needed to achieve this goal. It has been shown that the chronic care model is generally effective for managing diabetes in US primary care settings.23 The PCMH is a great example of a new health delivery system that developed out from the principles of the chronic care model framework. Leading primary care organizations introduced the PCMH to address high costs and poor health outcomes, particularly those related to chronic medical conditions, such as hypertension and diabetes. The objective of the PCMH model of care is to have a centralized setting that facilitates partnerships between patients and their personal physicians and, when appropriate, the patient’s family.24 Medically complex patients can be managed through an integrated care management program, which assigns nurse care managers to oversee complicated and chronically ill patients with multiple medical conditions, such as diabetes or heart disease. The PCMH has been shown to be a viable mechanism to improve the quality and costs of diabetes care.25 The basic elements of a PCMH are care coordination, quality and safety, whole person orientation, personal physician, enhanced access, and payment reform. A critical component of a medical home practice is care with coordination and communication among its members and where information technology is essential to improve patient-centered care.26,27 Efforts to transform diabetes care align with the aims of PCMH. In a typical workflow, the patient experience is improved when previous results and past medical records have been collected and merged across health care providers. One of the main goals of the visit is to empower patients enable to manage their own care. In summary, the PCMH has shown promise for improving outcomes through coordinated primary care and better coordination with others outside primary care—sometimes referred to as the medical neighborhood.28 IMPROVING QUALITY THROUGH POPULATION HEALTH
The framework of the PCMH has been the focus of the most recent efforts to drive better diabetes care in the primary care. Some attributes of the PMCH is for practices to assess care quality at the population level uses evidence-based measures, identify high-risk patients for outreach and care management, and enhance patient engagement—all key aspects of population management. Many of the early PCMH pilots focused on diabetes as a target disease and have showed improvements in both process and outcome measures.21 For example, a large multipayer supported PMCH initiative in Pennsylvania had its initial focus on diabetes. More than 100 primary practices across the state were transformed to National Center for Quality Assurance reconfigured PCMHs through practice facilitation, monthly population level reporting of clinical quality measures and implementation of care management for high risk patients. After 1 year, there was a significant improvement in diabetes process measures (annual eye examination, nephropathy screening, foot examinations, pneumonia vaccination, and smoking cessation) and clinical measures of diabetes control.25 These changes were also associated with improvements on health care use.14
Diabetes Population Management
SUMMARY
In an era of accountable care organizations, health care systems need to be redesigned to care for the chronically ill. Diabetes is a great example of a chronic disease that could be partly prevented, but more important most of its complications that are costly and burdensome could be prevented. Population health management, which seeks to decrease health care cost and improve quality of care, can address most of the challenges in diabetes management. However, it cannot be achieved successfully without information technology system in place and a mental shift of provider who has been trained on treating the acutely ill and typically incentivized by reimbursement for every provided service. Stratifying populations based on risk is an important step to ensuring the right patient receives the right care from the right provider. Better measurement tools for assessing diabetes quality continue to evolve, and systems to better coordinate care within a medical neighborhood will be important elements to refine. As has happened so often in the history of health care delivery changes, the field of diabetes care has the opportunity to lead the way in developing this more comprehensive approach to care. Health care organizations, payers, and stakeholders have a big challenge to find the best delivery and payment model to meet populations’ needs. REFERENCES
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