From the Center for Health Care Knowledge Management, NJ VA Healthcare System (standing, left to right): Chin-Lin Tseng, DrPH, health science specialist/biostatistician, assistant professor, Department of Preventive Medicine and Community Health, UMDNJ-New Jersey Medical School (NJMS); Ranjana Banerjea, PhD, health science specialist, adjunct instructor, School of Social Work, Rutgers; Usha Sambamoorthi, PhD, director, Health Outcomes Research at the Center, adjunct associate professor, Division of Health Systems and Policy, UMDNJ-School of Public Health; and (seated) Leonard Pogach, MD, professor, NJMS, and director of the Center
Understanding Chronic Illness with Complexity
by Leonard Pogach
T
he increasing prevalence of co-occurring multiple chronic conditions (physical and mental) in an aging population has resulted in an increasing need to focus on the individual person, not individual diseases. One important element of this new paradigm, termed Chronic Illness with Complexity (CIC), has been the research focus of how treatment of one condition (e.g., depression) influences care and outcomes associated with another condition (e.g., diabetes). The Veterans Health Administration (VHA), the largest integrated healthcare system in the U.S., has made care coordination for individuals with multiple chronic medical and mental illnesses a priority. Furthermore, it has developed innovative strategies, such as primary care, collaborative care, and tele-health, to integrate treatment for veterans with CIC.
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| Figure 1. Average long term blood sugar control (A1c test) fluctuates through the year: it is highest in late winter, and lowest in late summer in all US climates. This finding has implications for performance measurement. Although current industry standards evaluate the "last" test in a year, clinicians manage persons with diabetes at the time of a visit based upon all previous results (Tseng CL et al. Seasonal Patterns in Monthly Hemoglobin A1c Values Chin-Lin Tseng Am. J. Epidemiol. 2005 161: 565-574). |
In recent years the VHA has developed an international reputation for its use of electronic health care records to improve quality of care while decreasing costs. However, it remains unknown as how to best deliver care and improve outcomes for CIC patients because care of these patients presents enormous challenges due to competing patient priorities, and conflicting and difficult treatment regimens. In addition, for CIC patients, clinical guidelines and quality standards derived from clinical trials may not be relevant because most of the trials exclude CIC patients. Thus, care of the CIC population is an important research priority for both the VHA as well as other healthcare systems.
Evaluation of the quality of care provided to, and outcomes of, CIC patients requires multidisciplinary approaches with expertise from several areas of medicine and public health, behavior, economics, informatics, epidemiology, statistics, as well as other health-related disciplines. The Health Services Research Center for Healthcare Knowledge Management at the VA New Jersey Healthcare System (hereafter referred to as the Center) is in a unique position to accomplish the daunting methodological challenges in providing care to CIC populations. The mission of the Center is to integrate the methodological disciplines of predictive modeling, decision-making, risk communication and risk-adjustment of outcomes with information technology and datasets as the basis for knowledge management in CIC at the levels of policy development, management, and clinical point of service.
Since 2004, the 10 Center investigators have received 21 federal grants for a cumulative total of $14,500,000. In addition to myself, they include: Thomas Findley MD, PhD, associate director, professor of psychiatry, UMDNJ-New Jersey Medical School (NJMS); Usha Sambamoorthi, PhD, director, Health Outcomes of the Center, adjunct associate professor, UMDNJ-School of Public Health; Karen Quigley, PhD, director of research, War Related Illness and Injury Study Center, associate professor of psychiatry, NJMS; Donald Ciconne, PhD, assistant professor of psychiatry, NJMS; David Smelson, Pysch D, associate professor of psychiatry, RWJMS; Chin-Lin Tseng, DrPH, assistant professor of preventive medicine, NJMS; Yujing Shen, PhD, research associate, Institute for Health, Rutgers University; Ranjana Banerjea, PhD, and Victor Chang, MD. Our analytical team consists of Miriam Maney, MA, administrative officer; Mangala Rajan, MBA; Chan Shen, MS; and Anjali Tiwari, MBBS, MS.
The Center has assembled a repository of large databases consisting of merged Medicare/VHA administrative data to analyze care for multiple chronic illnesses with diabetes, heart disease, hypertension, major depression, and spinal cord injury. Initial work focused on using the VA Diabetes Epidemiology Cohort, one of the largest in the U.S., to evaluate trends in amputations and chronic kidney disease care, and cost-effectiveness of depression treatment. Recent work has expanded the database to analyze the interaction between chronic physical illness (diabetes, heart disease, and hypertension) and mental illness in female and male veterans.
Findings from many of our funded studies have gained national and international attention. For example, Dr. Sambamoorthi’s research was the first to establish cost-effectiveness of depression treatment in the VHA. Dr. Chin-lin Tseng’s work on evaluating area variation in major and minor amputations was cited by the Organization for Economic Collaboration and Development. Reuters News Agency carried her work on seasonal variations in HbA1c.We evaluated the need for distinguishing among mental illness and substance abuse clusters and their association with persistent increases in expenditures (led by Dr. Banerjea). Our analysis has also provided directions for policymakers by demonstrating that nephrology care can decrease pre-dialysis mortality (led by Dr. Tseng), and has demonstrated the possible implications of fragmentation of care for dual users of the VHA and Medicare (led by Dr. Shen).
The Center also focuses on innovative methods, and has developed new methodologies to evaluate diabetes outcomes, such as distinguishing initial from repeat amputations (led by Dr. Sambamoorthi), and continuous and weighted measures of intermediate outcomes, such as HbA1c (led by Dr. Pogach). Longitudinal analyses demonstrated that the current industry standard of serial cross sectional measures results in misleading inferences about changes in quality that should be attributed to in- and out-migration of new and established cases of diabetes.
Our investigators have also emphasized the implementation of care coordination in veterans. Dr. Smelson and his research team have developed Time Limited Care-Coordination, which is a transtheoretical approach aimed at reducing the day-to-day situational barriers that impede treatment engagement of those with mental health and co-occurring substance abuse problems.
Dr. Quigley and the HEROES project investigators are examining pre-war psychosocial and physiological factors that may predict post-war unexplained physical symptoms, functional status, healthcare utilization and other mental health outcomes in soldiers deployed to Iraq and Afghanistan. Dr. Ciconne and his research team are funded to evaluate whether tele-medicine is an equally effective alternative to face-to-face visits in managing post-traumatic stress.
The current and future research work by the Center’s investigators will not only advance science in health services research but also aid policy makers in understanding factors that are relevant to the maintenance of CIC patients and improve their healthcare. As we seek to better understand how to manage chronic illnesses with complexity, we look forward to working with colleagues across UMDNJ both to improve care for our patients, and to improve medical knowledge in this exciting area of inquiry.
Leonard Pogach, MD, MBA, FACP, is the director of the Center for Healthcare Knowledge Management at the New Jersey VA Healthcare System and professor of medicine at UMDNJ-New Jersey Medical School. He has an extensive background in evidence-based guidelines and performance measurement development.
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