Patient need and provider referrals to diabetes self-management education

Brittany L. Brown-Podgorski, Yunfeng Shi, Joshua R. Vest

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


OBJECTIVES: This study measured the likelihood of adult patients with diabetes being referred to diabetes selfmanagement education (DSME) when "in need" according to clinical guidelines and identified which types of clinical need predict a greater likelihood of provider referral to DSME. STUDY DESIGN: This repeated cross-sectional analysis utilized patient electronic health records (EHRs) and a statewide health information exchange database to examine a 7-year panel (2010-2016) of adult patients with diabetes. Our analytic sample included 8782 adult patients with diabetes with a total of 356,631 encounters. METHODS: Fixed-effects linear probability models with clustered robust standard errors estimated the association between patients' need for DSME and likelihood of being referred to the service. Models controlled for patients' health status, prior utilization, encounter setting, comorbidity risk scores, the state's expansion of Medicaid, and the count of accredited DSME program sites in the community. RESULTS: Most patient encounters indicated at least 1 type of need for DSME, but less than 7% of those encounters with a documented need resulted in a provider referral. In regression analysis, clinical indicators of need increased the likelihood that patients would be referred to DSME. Patients exhibiting multiple types of need were most likely to be referred to DSME. CONCLUSIONS: Although findings indicate that patient need for DSME does improve the likelihood of being referred, provider referral rates were significantly lower than anticipated. Future research should explore barriers to clinical guideline adherence and whether clinical decision support in EHR systems can facilitate provider referrals.

Original languageEnglish (US)
Pages (from-to)E201-E207
JournalAmerican Journal of Managed Care
Issue number6
StatePublished - Jun 2021

All Science Journal Classification (ASJC) codes

  • Health Policy


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