Implementation of an EHR care gap alert significantly increased ESS screening rates for obstructive sleep apnea from 2.21% to 9.15% (p<0.0001), though referral rates did not significantly change.
Observational
No
Does an EHR care gap alert improve OSA screening rates in adult patients with BMI ≥35 and hypertension?
An EHR care gap alert significantly improved OSA screening rates among high-risk patients with obesity and hypertension, though it did not increase sleep medicine referral rates.
Absolute Event Rate: 9.15% vs 2.21%
p-value: p=<0.0001
Abstract Introduction Obstructive sleep apnea (OSA) is a prevalent sleep disorder affecting an estimated 39% of men and 26% of women in the United States 1. Untreated OSA is linked to cardiovascular and metabolic conditions that increase morbidity, mortality, and reduce quality of life, yet, it remains largely underdiagnosed. The United States Preventative Services Task Force (USPSTF) reports insufficient evidence to assess screening for OSA in asymptomatic adults in the general population 2 . However, those with obesity and hypertension represent a population in whom early detection of OSA may meaningfully alter disease trajectory. In 2021, our internal medicine residency clinic implemented an electronic health record (EHR) “care gap” alert to prompt OSA screening in those with a BMI ≥35 and hypertension. This study investigates whether the care gap improves screening and downstream diagnosis of OSA. Methods We conducted a retrospective chart review of adult patients (≥18 years) at our clinic with BMI ≥35 and hypertension, without an existing OSA diagnosis. Data were extracted from the Virtual Data Warehouse for encounters three years before and after care gap implementation. Primary outcomes were pre-post differences in ESS and STOP-BANG screening rates, and Sleep Medicine referral rates, including BMI-based subgroup analyses. Secondary outcomes examined downstream diagnostic outcomes including referrals to sleep medicine, appointment attendance, completion of a sleep study, and OSA diagnoses. Descriptive statistics, two-proportion z-tests, and chi-square tests were used for analysis. Results ESS screening rates increased from 2.21% pre-intervention (n=16) to 9.15% post-intervention (n=78), a statistically significant difference (95% CI 4.73%–9.16%; Z-test and Chi-square p 0.0001). Referral rates were similar, rising slightly from 13.42% pre-intervention (n=97) to 15.26% post-intervention (n=130), with no significant difference (95% CI –1.62% to 5.31%; Z-test p = 0.30; Chi-square p = 0.2997). The remaining outcomes are in progress. Conclusion Early findings suggest that implementation of this care gap significantly improved OSA screening among high-risk patients, though referral rates did not change. Ongoing analysis will clarify the intervention’s impact on diagnostic follow-through. Understanding long-term screening trends and referral patterns may help health systems optimize digital prompts to screen for under-diagnosed conditions and improve outcomes for vulnerable populations. Support (if any)
Kramer et al. (Fri,) conducted a observational in Obstructive sleep apnea. Electronic health record (EHR) care gap alert vs. Pre-intervention (no alert) was evaluated on ESS screening rates (95% CI 4.73%-9.16%, p=<0.0001). Implementation of an EHR care gap alert significantly increased ESS screening rates for obstructive sleep apnea from 2.21% to 9.15% (p<0.0001), though referral rates did not significantly change.