Effect of discussing personalized estimates of diabetes risk for people with prediabetes

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.

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.

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 = 0.042).

Used at the point of care during a shared decision-making discussion between the patient and provider, the EHR-based diabetes risk calculator helped providers prioritize patients for diabetes prevention interventions, facilitated communication, and improved health outcomes among patients with prediabetes.

One-third of U.S. adults have prediabetes, a condition which carries an increased risk of developing type 2 diabetes, yet few people with prediabetes receive evidence-based preventive intervention such as the Diabetes Prevention Program (DPP) or metformin. A recent study suggests a new category of preventive intervention, GLP-1 and GIP receptor agonist, is highly effective for prevention in people with prediabetes and obesity. Provider organizations need an efficient way to risk-stratify the large population of people with prediabetes, in order to focus prevention efforts toward those who are at greatest risk.A risk calculator integrated in the electronic health record (EHR) equipped physicians to provide an estimate of each patient's individual risk of developing type 2 diabetes and prioritize patients for preventive interventions. DPP referrals and metformin prescribing increased substantially, and patients at high risk were more likely to receive a preventive intervention than those at intermediate or low risk.People with prediabetes for whom use of the diabetes risk prediction tool was documented were significantly less likely to progress to diabetes over 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%).