Diabetes Care Coordination in Patient-Centered Medical Homes
Posted April 26, 2012 by Kevin A. Peterson, MD, MPH
The patient centered medical home (PCMH) model has been considered a hallmark for high quality health care. Although the concept of coordinated care is fundamental to the principle of the PCMH, and although primary care teams are increasingly integrating patient- and family-centered approaches into their practice workflow for diabetes support,1 primary care physicians still need to develop a better understanding of how to coordinate population-based management of diabetes while maintaining a patient–centered approach. Innovative versions of the patient-centered medical home model that incorporate new tools for assessing patient ”complexity” are beginning to show how this is possible.
Care Coordination and the Patient-Centered Approach
The development of the PCMH model has been driven by the Institute of Health’s Triple Aim.2 The Triple Aim calls for simultaneously improving the individual experience of care, the health of the population, and the affordability of health care. The PMCH model puts patients at the center of the care delivery process by delivering care at the right time, in the right place, and in the most cost-effective manner. It encourages a proactive approach to health promotion, disease prevention, and chronic disease management through the development of care plans and increased care coordination between primary care providers and community resources.
Diabetes care coordination is among the most common focuses of developing PCMHs. Diabetes is well suited as a model for chronic disease care since it provides well recognized, evidence-based guidelines, has expensive treatment options, and has a well-established gap in the quality of care.3 The identification of patient panels and disease specific “registries” has provided an important start by identifying the patient population needing proactive support. Establishing a health care team that uses the registry to provide non-visit care proactively has a proven track record of improving clinical quality measures.4
One good example is the Health Partners Medical Group of Minneapolis, a large integrated health system with fifty clinic locations using “prepared clinical teams,” each consisting of a physician, nurse and receptionist.5 By addressing compliance with five diabetes quality measures (A1C, blood pressure, LDL cholesterol, aspirin use and tobacco cessation), the percentage of patients who met targets for the composite quality measures rose from 4 to 25%.6 Inpatient admissions and readmissions were significantly reduced (−24% and −39% respectively), and clinic costs were 8% lower than average clinic costs in Minnesota (where average costs of health care are already below the national average).
The Need for a More Comprehensive Approach
For care coordination models to continue to improve clinical outcomes while meeting the expectations of patients and families, care coordinators need to step beyond disease-specific management and adopt a more comprehensive approach to health care needs. New evidence suggests that a broader view that includes evaluation of social determinants of health provide important perspectives to improving diabetes quality measures across a population. Although registries help to identify individuals in a PCMH that are not meeting clinical targets, the kind of support that is needed is not always obvious. We still have a limited understanding of what needs to be done with diabetes registries, but we need to remember that an important aspect of patient-centered care is attention to the individual. Although the application of treatment algorithms that add medications and drive more complex treatment regimens provides a tempting panacea for population-based diabetes management, more medicine doesn’t address many of the problems that prevent better diabetes outcomes. Particularly when providing care to an underserved population, social determinants of health play a major role in diabetes care.
Ignoring social determinants of health and sticking to medicines, moreover, too often results in unnecessary medicalization of social or mental health problems, increases costs, and misses opportunities for more integrated and patient-centered approaches that more effectively support prevention and health promotion.7,8 We know that population-based preventive service screening tools that define well-being only in terms of disease can result in “medicalization,” of mental health or social challenges. In other words, as physicians we tend to increase medicine when people really need better food, family, and/or social support. It is easy to overlook the evidence suggesting that social and economic circumstances reduce efficacy and undermine responses to medical treatments.9,10
Broad implementation of population-based diabetes care management tools has the potential to increase the medicalization of social distress, raising costs, reducing efficacy, and undermining care coordination overall. This is especially true among economically disadvantaged populations, where high levels of depression are linked to broader social determinants of mental health, such as housing problems, and financial security.11
In a recently released Scottish study, new patient-centered approaches to care coordination using structured patient interviews systematically integrated biologic, psychological, and social factors into a measure of patient “complexity” that provided caregivers with a broader understanding of a patient’s socioeconomic situation. Use of this “complexity” assessment tool led to better and more consistent identification of community services that could be provided to the participants, and significantly improved the patient experience, clinical process, and medical outcomes, together with less medicine.12 The overall result was less medicine and a more sensible way of addressing the real obstacles to better care. Since self-management is an important aspect of diabetes care, it makes sense that attention to social determinants of health could have an important impact on diabetes outcomes.
Remaining Challenges
Challenges remain of course. We still know very little about which patients in a population would be most likely to medically respond to the provision of social services. In existing PCMH models, reimbursement for care coordination is based on disease control or on the number of associated comorbidities.13,14 However these models miss social and economic factors that are less expensive to fix, and may have an important influence on the success of care coordination.
Another important challenge is that health care providers themselves can find it difficult to respond to broad social determinants of health even when recognized. Some providers express concern about overwhelming limited local social support services. Others believe that as health care providers we can’t address the scale of the potential problems that lead to poor health outcomes.15 Few tools exist that effectively assess and document the impact of broad social and economic influences on diabetes outcomes. However, the introduction of comprehensive assessment measures offer an early glimpse at the promise for better evaluating the complex determinants of health and providing direction for more patient-centered responses to individuals living with diabetes. Further exploration of new methods of providing patient-centered care in real world community settings will continue to be important in improving the care we provide to individuals with diabetes.
Resources
1. Bojadzievski, T and Gabbay RA. Patient-centered medical home and diabetes. Diabetes Care 2011;34(4):1047-1053
2. Improvement IfH. The IHI Triple Aim. 20 University Road, Cambridge, MA 02138: Institute for Healthcare Improvement, 2011. Accessed April 20, 2012.
3. Centers for Disease Control and Prevention. National diabetes fact sheet: national estimates and general information on diabetes and prediabetes in the United States, 2011. Atlanta, GA: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, 2011.
4. Peterson, K. A., Radosevich, D. M., O’Connor, P. J., Nyman, J. A., Prineas, R. J., Smith, S. A., Arneson, T. J., et al. (2008). Improving Diabetes Care in Practice Findings from the TRANSLATE trial. Diabetes Care, 31(12), 4670-4675. doi:10.2337/dc08-2034.
5. McCarthy D, Mueller K, Tillmann I. HealthPartners Uses “BestCare” practices to improve care and outcomes, reduce costs. Cambridge, MA: Institute for Healthcare Improvement.Accessed April 20, 2012.
6. Van Berckelaer A, DiRocco D, Ferguson M, et al. Building a patient-centered medical home: Obtaining the patient's voice. Journal of the American Board of Family Medicine 2012;25(2):192-198.
7. MacDonald S, Morrison J, Maxwell M, et al. A “coal face option”: GPs’ perspectives on the rise in antidepressant prescribing. British Journal of General Practice 2009;59 (566):e299-e307.
8. Maxwell M and Pratt R. Prevention and management of depression in primary care in Europe: A holistic model of care and interventions. Quality in Primary Care 2008;16:187-196.
9. Brown, GW, Harris TO, Kendrick T, et al. Antidepressants, social adversity and outcome of depression in general practice. Journal of Affective Disorders 2010;121:239-246.
10. Gilchrist G and Gunn J. Observational studies of depression in primary care: What do we know? BMC Family Practice 2007;8(28):28.
11. Kinnear PR and Gray CD. SPSS 14 Made Simple. Brighton and Hove: Psychology Press, 2006.
12. Maxwell M, Hibberd C, Pratt R, et al. Development and Initial Validation of the Minnesota Edinburgh Complexity Assessment Method (MECAM) for Use Within the Keep Well Health Check. NHS Health Scotland, 2012.Accessed April 26, 2012.
13. Minnesota State Health Reform Initiative. Accessed April 20, 2012.
14. 2010 State of Minnesota Administrative Rules, Chapter 4764.0010-4764.0070, Health Care Homes. Accessed April 20, 2012.
15. Maxwell, M. General practitioners’ and women’s experiences of depression and its management in primary care: The moral dilemma of care. Chronic Illness 2005;1:61-71.