Volume 53 Number 6, 2016
Pages 853 — 862
Abstract — Implementation of a prediabetes identification algorithm for overweight and obese Veterans
Tannaz Moin, MD, MBA, MSHS;1–2* Laura J. Damschroder, MS, MPH;3 Bradley Youles, MPA;3 Fatima Makki, MPH;3 Charles Billington, MD;4 William Yancy, MD, MHSc;5 Matthew L. Maciejewski, PhD;5 Linda S. Kinsinger, MD, MPH;6 Jane E. Weinreb, MD;1 Nanette Steinle, MD;7 Caroline R. Richardson, MD3,8
1Department of Veterans Affairs (VA) Greater Los Angeles Healthcare System, Los Angeles, CA; and David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA; 2Center for the Study of Healthcare Innovation, Implementation and Policy, Health Services Research & Development, VA Greater Los Angeles Healthcare System, Los Angeles, CA; 3VA Center for Clinical Management Research, Ann Arbor, MI; 4Minneapolis VA Health Care System, Minneapolis, MN; and University of Minnesota Medical Center, Minneapolis, MN; 5Durham VA Medical Center (VAMC), Durham, NC; and Duke University School of Medicine, Durham, NC; 6National Center for Health Promotion and Disease Prevention, Veterans Health Administration, Durham, NC; 7Baltimore VAMC, Baltimore, MD; and University of Maryland School of Medicine, Baltimore, MD; 8Department of Family Medicine, University of Michigan, Ann Arbor, MI; and VA Diabetes Quality Enhancement Research Initiative, Ann Arbor, MI
Abstract — Type 2 diabetes prevention is an important national goal for the Veterans Health Administration (VHA): one in four Veterans has diabetes. We implemented a prediabetes identification algorithm to estimate prediabetes prevalence among overweight and obese Veterans at Department of Veterans Affairs (VA) medical centers (VAMCs) in preparation for the launch of a pragmatic study of Diabetes Prevention Program (DPP) delivery to Veterans with prediabetes. This project was embedded within the VA DPP Clinical Demonstration Project conducted from 2012 to 2015. Veterans who attended orientation sessions for an established VHA weight-loss program (MOVE!) were recruited from VAMCs with geographically and racially diverse populations using existing referral processes. Each site implemented and adapted the prediabetes identification algorithm to best fit its local clinical context. Sites relied on an existing referral process in which a prediabetes identification algorithm was implemented in parallel with existing clinical flow; this approach limited the number of overweight and obese Veterans who were assessed and screened. We evaluated 1,830 patients through chart reviews, interviews, and/or laboratory tests. In this cohort, our estimated prevalence rates for normal glycemic status, prediabetes, and diabetes were 29% (n = 530), 28% (n = 504), and 43% (n = 796), respectively. Implementation of targeted prediabetes identification programs requires careful consideration of how prediabetes assessment and screening will occur.
Key words:diabetes, diabetes prevention, guidelines, health services research, implementation research, obesity, prediabetes, screening, Veterans, weight management.
Contents Vol. 53, No. 6
This article and any supplementary material should be cited as follows:
Moin T, Damschroder LJ, Youles B, Makki F, Billington C, Yancy W, Maciejewski ML, Kinsinger LS, Weinreb JE, Steinle N, Richardson CR. Implementation of a prediabetes identification algorithm for overweight and obese Veterans. J Rehabil Res Dev. 2016;53(6):853–62.
ORCID: Tannaz Moin, MD, MBA, MSHS: 0000-0002-5035-6641
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Last Reviewed or Updated Tuesday, January 24, 2017 8:54 AM