Evaluation of the HealthImpact Diabetes Risk Model in the Veterans Health Administration.

Linder JR, Waterbury NV, Alexander B, Lund BC. Evaluation of the HealthImpact Diabetes Risk Model in the Veterans Health Administration. Journal of managed care & specialty pharmacy. 2018 Sep 1; 24(9):862-867.

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Abstract:

BACKGROUND: HealthImpact is a novel algorithm using administrative health care data to stratify patients according to risk for incident diabetes. OBJECTIVES: To (a) independently assess the predictive validity of HealthImpact and (b) explore its utility in diabetes screening within a nationally integrated health care system. METHODS: National Veterans Health Administration data were used to create 2 cohorts. The replication cohort included patients without diagnosed diabetes as of October 1, 2012, to determine if HealthImpact scores were significantly associated with diabetes (type 1 or 2) incidence within the subsequent 3 years. The utility cohort included patients without diagnosed diabetes as of August 1, 2015, and assessed diabetes screening rates in the 2 years surrounding this index date, stratified by HealthImpact scores. RESULTS: The 3-year incidence of diabetes in the replication cohort (n = 3,287,240) was 9.1%. Of 100,617 (3.1%) patients with HealthImpact scores > 90, 30,028 developed diabetes, yielding a positive predictive value of 29.8%. These patients accounted for 9.9% of all incident diabetes cases (sensitivity). Sensitivity and negative predictive value improved with descending HealthImpact threshold scores (e.g., > 75, > 50), whereas specificity and positive predictive value declined. Of 3,499,406 patients in the utility cohort, 85.3% received either a blood glucose or hemoglobin A1c test during the 2-year observation period. Among 101,355 patients with a HealthImpact score > 90, nearly all (98.3%) were screened, and 86.3% had an A1c test. CONCLUSIONS: Our independent analysis corroborates the validity of HealthImpact in stratifying patients according to diabetes risk. However, its practical utility to enhance diabetes screening in a real-world clinical environment will be strongly dependent on the pattern and frequency of existing screening practices. DISCLOSURES: This work was supported by the Iowa City VA Health Care System and by the Department of Veterans Affairs, Office of Research and Development, Health Services Research and Development Service (Lund, CIN 13-412). The authors have no conflicts of interest. The views expressed in this article are those of the authors and do not necessarily reflect the position or policy of the Department of Veterans Affairs or the U.S. government.