Factors Associated With Receipt of Diabetes Self-Management Education and Support for Type 2 Diabetes: Potential for a Population Health Management Approach

Author:

Bober Timothy1ORCID,Rothenberger Scott1,Lin Jonathan1,Ng Jason M.2,Zupa Margaret2ORCID

Affiliation:

1. Center for Research on Health Care, Division of General Internal Medicine, University of Pittsburgh, Pittsburgh, PA, USA

2. Division of Endocrinology and Metabolism, University of Pittsburgh, Pittsburgh, PA, USA

Abstract

Background: Population health management approaches can help target diabetes resources like Diabetes Self-Management Education and Support (DSMES) to individuals at the highest risk of complications and poor outcomes. Little is known about patient characteristics associated with DSMES receipt since widespread uptake of telemedicine for diabetes care in 2020. Methods: In this retrospective cohort study, we used electronic medical record (EMR) data to assess patterns of DSMES delivery from May 2020 to May 2022 among adults who used telemedicine for type 2 diabetes (T2D) endocrinology care in a large integrated health system. Multilevel regression models were used to evaluate the association of key patient characteristics with DSMES receipt. Results: Of 3530 patients in the overall cohort, 401 patients (11%) received DSMES. In adjusted multivariable logistic regression, higher baseline HbA1c (odds ratios [OR] 3.10 [95% confidence interval 2.22-4.33] for HbA1c ≥9% vs <7%), insulin regimen complexity (OR 3.53 [2.59-4.80] for multiple daily injections vs no insulin), and number of noninsulin medications (OR 1.17 [1.05-1.30] per 1 additional medication) were significantly associated with receipt of DSMES, whereas rurality and area-level deprivation of patient residence were not. Conclusions: Diabetes Self-Management Education and Support remains underutilized in this cohort of adults using telemedicine to access endocrinology care for T2D. Factors contributing to clinical complexity increased the odds of receiving DSMES. These results support a potential population health management approach using EMR data, which could target DSMES resources to those at higher risk of poor outcomes. This risk-stratified approach may be even more effective now that more people can access DSMES via telemedicine in addition to in-person care.

Funder

National Center for Advancing Translational Sciences

NIH Clinical Center

Publisher

SAGE Publications

Subject

Biomedical Engineering,Bioengineering,Endocrinology, Diabetes and Metabolism,Internal Medicine

Reference47 articles.

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