Increasing SGLT-2 Inhibitor Prescribing Through an Integrated Case-Finding Algorithm Guided Interdisciplinary Intervention (INSPIRE)

Cindy Leslie A Roberson; Abby F Hoffman; Pamela Cohen; Victoria Lee Jackson; Susan E Spratt

doi:10.1016/j.japh.2024.102320

Increasing SGLT-2 Inhibitor Prescribing Through an Integrated Case-Finding Algorithm Guided Interdisciplinary Intervention (INSPIRE)

J Am Pharm Assoc (2003). 2024 Dec 27:102320. doi: 10.1016/j.japh.2024.102320. Online ahead of print.

Authors

Cindy Leslie A Roberson¹, Abby F Hoffman², Pamela Cohen³, Victoria Lee Jackson⁴, Susan E Spratt⁵

Affiliations

¹ Clinical Pharmacist, Duke Population Health Management Office (PHMO), Durham, NC. Electronic address: Susan.Spratt@duke.edu.
² Senior Population Health Analyst, Duke PHMO, Durham, NC.
³ Program Coordinator, Duke PHMO, Durham, NC.
⁴ Senior Clinical Account Executive, Express Scripts, Durham, NC.
⁵ Endocrinologist, Senior Medical Director, Duke PHMO, Durham, NC; Professor of Medicine, Professor in Family Medicine and Community Health, Division of Endocrinology, Metabolism, Nutrition, Department of Medicine, Duke University School of Medicine, Durham, NC.

PMID: 39733807
DOI: 10.1016/j.japh.2024.102320

Abstract

Background: Use of sodium-glucose co-transporter 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 (PCP) with added clinical-decision support via a dedicated remote interdisciplinary diabetes rounds (IDR) 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 (EHR). 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 [aOR] 5.1, 95% CI 3.06 to 8.47). The algorithm identified 1,084 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.

Keywords: Sodium-glucose co-transporter 2 inhibitor (SGLT-2 inhibitor) prescribing; interdisciplinary team; virtual rounds.