Increasing SGLT-2 inhibitor prescribing through an integrated case-finding algorithm-guided interdisciplinary intervention.

BACKGROUND: Use of sodium-glucose cotransporter 2 inhibitors (SGLT-2 inhibitors) falls short of their cardiorenal protective benefits. Patient and provider-level barriers hinder the adoption of these life-saving medications. Innovative practices to provide primary care providers (PCPs) with added clinical-decision support via a dedicated remote interdisciplinary diabetes rounds (IDRs) team could promote SGLT-2 inhibitor selection. OBJECTIVE: To evaluate the impact of the IDR's proactive provider outreach on the prescribing rate of SGLT-2 inhibitors and assess the application of an SGLT-2 inhibitor case-finding algorithm to allow targeted intervention in a population-health-based setting. METHODS: This is a quality improvement prospective cohort observational study from October 2021 to May 2022. Patients who met the prespecified criteria for SGLT-2 eligibility were reviewed via IDR with recommendations sent to the PCP via the electronic health record. The primary analysis employed a multivariate logistic regression to assess the difference in SGLT-2 inhibitor prescription rates between reviewed and not reviewed patients, adjusting for variables affecting SGLT-2 inhibitor prescribing. The secondary analysis measured the algorithm's accuracy in identifying patients with compelling indications. RESULTS: The IDR team reviewed a total of 206 patients (mean age, 63 years; 53.9% women; 42.7% Black; mean A1c 8.3%) with a successful PCP appointment. Patients reviewed by the IDR team had an increased prescribing rate within 90 days of the visit (adjusted odds ratio 5.1, 95% CI 3.06-8.47). The algorithm identified 1084 SGLT-2 inhibitor-eligible patients with a sensitivity of 90.4% (95% CI, 86.4%, 94.4%) and specificity of 85.1% (95% CI, 79.9%, 90.4%). CONCLUSION: IDR team's review of eligible patients with recommendations to PCPs was associated with significantly increased SGLT-2 inhibitor prescription rates. Development of an algorithm with high sensitivity and specificity for targeted intervention may provide a pathway for channeling therapy and decreasing clinical inertia in population health management efforts.

Duke Scholars

Author Susan Elizabeth Spratt Medicine, Endocrinology, Metabolism, and Nutrition