Effect of discussing personalized estimates of diabetes risk for people with prediabetes
Abstract
BACKGROUND: To assess acceptability, feasibility, and effectiveness of incorporating individualized risk prediction into clinical assessment, decision making, and communication of risk of type 2 diabetes, with and without preventive interventions, in patients with prediabetes.
METHODS: We integrated a prediction model into the clinical workflow at a US health care organization. We conducted patient and provider focus groups and pre- and post-dissemination surveys among 2,500 patients with prediabetes who had primary care visits between May 2018 and December 2019. We compared rates of progression to type 2 diabetes at 3 years between the intervention group and a propensity score matched cohort of patients who received usual care.
RESULTS: Prior to implementing the predictive model, 41.6% of providers and 63.8% of patients felt confident or very confident in their ability to estimate the risk of progression to diabetes for individual patients. After personalized risk information was made available, this increased to 92.8% and 66.9%, for providers and patients, respectively. People with prediabetes who had a discussion with their provider about their personal risk of developing type 2 diabetes, supported by the EHR-based prediction model, were significantly less likely to progress to diabetes in the following 3 years, compared to a propensity-score-matched cohort who received usual care in the same health system without individualized risk estimates (19.5% vs. 27.6%, p =…
How strong is the evidence?
Evidence Hub reads this as a cohort study, done in people. Its evidence level is 3 of 5 (Moderate · trial / cohort / secondary analysis). Trials without a large randomized design, cohorts and secondary analyses give moderate evidence. Reported size: 2,500 participants or records.
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