Evaluation of the health impact diabetes risk model in the Veterans health administration

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.