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Implementation of a prediabetes identification algorithm for overweight and obese Veterans.

Publication ,  Journal Article
Moin, T; Damschroder, LJ; Youles, B; Makki, F; Billington, C; Yancy, W; Maciejewski, ML; Kinsinger, LS; Weinreb, JE; Steinle, N; Richardson, C
Published in: J Rehabil Res Dev
2016

Type 2 diabetes prevention is an important national goal for the Veteran 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 in 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 their 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.

Duke Scholars

Published In

J Rehabil Res Dev

DOI

EISSN

1938-1352

Publication Date

2016

Volume

53

Issue

6

Start / End Page

853 / 862

Location

United States

Related Subject Headings

  • Veterans
  • United States Department of Veterans Affairs
  • United States
  • Rehabilitation
  • Prevalence
  • Prediabetic State
  • Overweight
  • Obesity
  • Middle Aged
  • Mass Screening
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Moin, T., Damschroder, L. J., Youles, B., Makki, F., Billington, C., Yancy, W., … Richardson, C. (2016). Implementation of a prediabetes identification algorithm for overweight and obese Veterans. J Rehabil Res Dev, 53(6), 853–862. https://doi.org/10.1682/JRRD.2015.06.0104
Moin, Tannaz, Laura J. Damschroder, Bradley Youles, Fatima Makki, Charles Billington, William Yancy, Matthew L. Maciejewski, et al. “Implementation of a prediabetes identification algorithm for overweight and obese Veterans.J Rehabil Res Dev 53, no. 6 (2016): 853–62. https://doi.org/10.1682/JRRD.2015.06.0104.
Moin T, Damschroder LJ, Youles B, Makki F, Billington C, Yancy W, et al. Implementation of a prediabetes identification algorithm for overweight and obese Veterans. J Rehabil Res Dev. 2016;53(6):853–62.
Moin, Tannaz, et al. “Implementation of a prediabetes identification algorithm for overweight and obese Veterans.J Rehabil Res Dev, vol. 53, no. 6, 2016, pp. 853–62. Pubmed, doi:10.1682/JRRD.2015.06.0104.
Moin T, Damschroder LJ, Youles B, Makki F, Billington C, Yancy W, Maciejewski ML, Kinsinger LS, Weinreb JE, Steinle N, Richardson C. Implementation of a prediabetes identification algorithm for overweight and obese Veterans. J Rehabil Res Dev. 2016;53(6):853–862.

Published In

J Rehabil Res Dev

DOI

EISSN

1938-1352

Publication Date

2016

Volume

53

Issue

6

Start / End Page

853 / 862

Location

United States

Related Subject Headings

  • Veterans
  • United States Department of Veterans Affairs
  • United States
  • Rehabilitation
  • Prevalence
  • Prediabetic State
  • Overweight
  • Obesity
  • Middle Aged
  • Mass Screening