The chronic kidney disease model: a general purpose model of disease progression and treatment.
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2011-06-16
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Abstract
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Chronic kidney disease (CKD) is the focus of recent national policy efforts; however, decision makers must account for multiple therapeutic options, comorbidities and complications. The objective of the Chronic Kidney Disease model is to provide guidance to decision makers. We describe this model and give an example of how it can inform clinical and policy decisions.Methods
Monte Carlo simulation of CKD natural history and treatment. Health states include myocardial infarction, stroke with and without disability, congestive heart failure, CKD stages 1-5, bone disease, dialysis, transplant and death. Each cycle is 1 month. Projections account for race, age, gender, diabetes, proteinuria, hypertension, cardiac disease, and CKD stage. Treatment strategies include hypertension control, diabetes control, use of HMG-CoA reductase inhibitors, use of angiotensin converting enzyme inhibitors, nephrology specialty care, CKD screening, and a combination of these. The model architecture is flexible permitting updates as new data become available. The primary outcome is quality adjusted life years (QALYs). Secondary outcomes include health state events and CKD progression rate.Results
The model was validated for GFR change/year -3.0 ± 1.9 vs. -1.7 ± 3.4 (in the AASK trial), and annual myocardial infarction and mortality rates 3.6 ± 0.9% and 1.6 ± 0.5% vs. 4.4% and 1.6% in the Go study. To illustrate the model's utility we estimated lifetime impact of a hypothetical treatment for primary prevention of vascular disease. As vascular risk declined, QALY improved but risk of dialysis increased. At baseline, 20% and 60% reduction: QALYs = 17.6, 18.2, and 19.0 and dialysis = 7.7%, 8.1%, and 10.4%, respectively.Conclusions
The CKD Model is a valid, general purpose model intended as a resource to inform clinical and policy decisions improving CKD care. Its value as a tool is illustrated in our example which projects a relationship between decreasing cardiac disease and increasing ESRD.Type
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Orlando, Lori A, Eric J Belasco, Uptal D Patel and David B Matchar (2011). The chronic kidney disease model: a general purpose model of disease progression and treatment. BMC medical informatics and decision making, 11(1). p. 41. 10.1186/1472-6947-11-41 Retrieved from https://hdl.handle.net/10161/22838.
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Lori Ann Orlando
Dr. Lori A. Orlando, MD MHS MMCI is a Professor of Medicine and Director of the Precision Medicine Program in the Center for Applied Genomics and Precision Medicine at Duke University. She attended Tulane Medical Center for both medical school (1994-1998) and Internal Medicine residency (1998-2000). There she finished AOA and received a number of awards for teaching and clinical care from the medical school and the residency programs, including the Musser-Burch-Puschett award in 2000 for academic excellence. After completing her residency, she served as Chief Medical Resident in Internal Medicine (2001) and then completed a Health Services Research Fellowship at Duke University Medical Center (2002-2004). In 2004 she also received her MHS from the Clinical Research Training Program at Duke University and joined the academic faculty at Duke. In 2005 she received the Milton W. Hamolsky Award for Outstanding Junior Faculty by the Society of General Internal Medicine. Her major research interests are decision making and patient preferences, implementation research, risk stratification for targeting preventive health services, and decision modeling. From 2004-2009 she worked with Dr. David Matchar in the Center for Clinical Heath Policy Research (CCHPR), where she specialized in decision modeling, decision making, and technology assessments. In 2009 she began working with Dr. Geoffrey Ginsburg in what is now the Center for Applied Genomics and Precision Medicine (CAGPM) and in 2014 she became the director of the Center’s Precision Medicine Program. Since joining the CAGPM she has been leading the development and implementation of MeTree, a patient-facing family health history based risk assessment and clinical decision support program designed to facilitate the uptake of risk stratified evidence-based guidelines. MeTree was designed to overcome the major barriers to collecting and using high quality family health histories to guide clinical care and has been shown to be highly effective when integrated into primary care practices. This effort started with the Genomic Medicine Model, a multi-institutional project, whose goal was to implement personalized medicine in primary care practices. The success of that project has led to funding as part of NHGRI’s IGNITE (Implementing Genomics in Clinical Practice) network. She is currently testing methods for integrating patient preferences and decision making processes into clinical decision support recommendations for patients and providers to facilitate management of patients’ risk for chronic disease using mHealth and other behavioral interventions.
Uptal Dinesh Patel
Uptal Patel, MD is an Adjunct Professor interested in population health with a broad range of clinical and research experience. As an adult and pediatric nephrologist with training in health services and epidemiology, his work seeks to improve population health for patients with kidney diseases through improvements in prevention, diagnosis and treatment.
Prior efforts focused on four inter-related areas that are essential to improving kidney health: i) reducing the progression of chronic kidney disease by improving its detection and management, particularly by leveraging technology to facilitate engagement and self-management; ii) elucidating the inter-relationships between kidney disease and cardiovascular disease, which together amplify the risk of death; iii) improving the evidence in nephrology through comparative effectiveness research, including clinical trials, observational studies, and meta-analyses; and iv) promoting more optimal clinical health policy for all patients with kidney disease. These inter-disciplinary projects have been funded by a variety of public and private sources including the Robert Wood Johnson Foundation, Veterans Affairs, National Institutes of Health, Agency for Healthcare Research & Quality, Food and Drug Administration, Centers for Medicare & Medicaid Services, Renal Physicians Association, and the American Society of Nephrology.
Current efforts seek to advance novel therapies for kidney diseases through early clinical development that he leads at AstraZeneca.
David Bruce Matchar
My research relates to clinical practice improvement - from the development of clinical policies to their implementation in real world clinical settings. Most recently my major content focus has been cerebrovascular disease. Other major clinical areas in which I work include the range of disabling neurological conditions, cardiovascular disease, and cancer prevention.
Notable features of my work are: (1) reliance on analytic strategies such as meta-analysis, simulation, decision analysis and cost-effectiveness analysis; (2) a balancing of methodological rigor the needs of medical professionals; and (3) dependence on interdisciplinary groups of experts.
This approach is best illustrated by the Stroke Prevention Patient Outcome Research Team (PORT), for which I served as principal investigator. Funded by the AHCPR, the PORT involved 35 investigators at 13 institutions. The Stroke PORT has been highly productive and has led to a stroke prevention project funded as a public/private partnership by the AHCPR and DuPont Pharma, the Managing Anticoagulation Services Trial (MAST). MAST is a practice improvement trial in 6 managed care organizations, focussing on optimizing anticoagulation for individuals with atrial fibrillation.
I serve as consultant in the general area of analytic strategies for clinical policy development, as well as for specific projects related to stroke (e.g., acute stroke treatment, management of atrial fibrillation, and use of carotid endarterectomy.) I have worked with AHCPR (now AHRQ), ACP, AHA, AAN, Robert Wood Johnson Foundation, NSA, WHO, and several pharmaceutical companies.
Key Words: clinical policy, disease management, stroke, decision analysis, clinical guidelines
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