Journal Article

12442 Effectiveness Of An Electronic Decision Support Algorithm To Optimize Recommendation Of SGLT2i And GLP-1RA In Patients With Type 2 Diabetes Upon Discharge From Internal Medicine Wards

El Saleh, R, Shochat, T, Basharim, B, Eliakim-Raz, N, McNeil, R, Jaffe, E, Abo Molhem, M, Ayalon-Dangur, I, Abuhasira, R, Hendel, H, Shitrit, T, Shaked, A, Gitter, L Azulay, Oved, Y, Shimon, I, Grossman, A

2024

Overview

Abstract Disclosure: E. Jaffe: None. I. Ayalon-Dangur: Grant Recipient; Self; Boehringer Ingelheim. A. Grossman: None. H. Hendel: None. Y. Oved: None. A. Shaked: None. I. Shimon: None. B. Basharim: None. M. Abo Molhem: None. R. McNeil: None. R. Abuhasira: None. T. Shitrit: None. L. Azulay Gitter: None. R. El Saleh: None. T. Shochat: None. N. Eliakim-Raz: None. Background: Type 2 diabetes mellitus (T2DM) is a major cause of morbidity and mortality. Current guidelines recommend the use of glucagon-like peptide-1 receptor agonists (GLP-1RA) and sodium-glucose cotransporter-2 inhibitors (SGLT2i) in patients with T2DM with or at high risk for cardiovascular disease to reduce mortality. Despite the established benefit, many studies found low treatment rates with these medications in eligible patients. The aim of our study is to examine the effectiveness of a clinical decision support (CDS) algorithm that was developed in our institution, in improving the recommendation rate of SGLT2i and GLP-1RA upon discharge from hospitalization in internal medicine wards. Methods: Our algorithm was developed to automatically recommend SGLT2i and GLP-1RA for T2DM patients based on current guidelines. Data was collected from electronic medical records of all T2DM patients ≥18 years old who were eligible for SGLT2i or GLP-1RA and hospitalized for any reason in one of five internal medicine wards in Beilinson Hospital. The primary outcome was to evaluate the rate of physician recommendation of SGLT2i or GLP-1RA at hospital discharge for eligible patients pre-algorithm implementation (January 2021-December 2021) versus post-algorithm implementation (April 2023-September 2023). Results: A total of 1318 patients were included in the pre-algorithm group and 970 were included in the post-algorithm group. Median age was 75 and 73 years in the pre- and post-algorithm groups, respectively. In the pre-algorithm group, 62% were males vs 60% in the post-algorithm group. Median length of hospitalization was three days and four days in the pre- and post-algorithm groups, respectively. The rate of SGLT2i and GLP-1RA recommendation for eligible patients was 8.50% (112 of 1318 patients) in the pre-algorithm group and 22.68% (220 of 970 patients) in the post-algorithm group. The odds ratio of the recommendation rate in the post vs pre-algorithm group was 3.151, 95% confidence interval 2.467– 4.025, p<0.0001. Conclusion: The results of this study demonstrate the benefit of an algorithm as part of a CDS system to improve recommendation rates of SGLT2i and GLP-1RA for eligible patients upon discharge from hospitalization. Future studies should assess the impact of the algorithm on prescription rates, patient adherence, and long-term outcomes. Presentation: 6/2/2024

• Publisher: Oxford University Press
• Subject: Abstract / Algorithms / Diabetes / Hospitalization / Internal medicine / Mortality