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Implementation of a prediabetes identification algorithm for overweight and obese Veterans.
Tannaz Moin1,2, Laura J Damschroder3, Bradley Youles3
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.
A prediabetes identification algorithm estimated prevalence among overweight and obese Veterans. The study found 28% prediabetes prevalence, highlighting the need for careful program implementation in healthcare settings.
Area of Science:
- Public Health
- Endocrinology
- Health Services Research
Background:
- Type 2 diabetes prevention is a key objective for the Veteran Health Administration (VHA), with one in four Veterans affected by diabetes.
- The study addresses the need for effective prediabetes identification strategies within the VHA system.
Purpose of the Study:
- To estimate prediabetes prevalence among overweight and obese Veterans using a prediabetes identification algorithm.
- To inform the implementation of a pragmatic study on Diabetes Prevention Program (DPP) delivery to Veterans with prediabetes.
Main Methods:
- A prediabetes identification algorithm was implemented across diverse Department of Veterans Affairs (VA) medical centers (VAMCs).
- Veterans attending orientation for the VHA weight-loss program (MOVE!) were recruited.
- Data were collected through chart reviews, interviews, and laboratory tests for 1,830 patients.
Main Results:
- The estimated prevalence rates were: normal glycemic status (29%), prediabetes (28%), and diabetes (43%).
- The algorithm was adapted to local clinical contexts, but the parallel implementation with existing clinical flow limited screening reach.
Conclusions:
- Prediabetes affects a significant portion of overweight and obese Veterans within the VHA system.
- Successful implementation of targeted prediabetes identification programs requires careful planning of assessment and screening processes.
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