1087 Transitioning from Paper to Electronic Health Record Collection of Epworth Sleepiness Scale (ESS) for Quality Measures. (27th April 2018)

• Record Type: Journal Article
• Authors: Chang, Y; Staley, B; Simonsen, S; Breen, M; Keenan, B; Schwab, R; Bae, C; Pack, A; Schutte-Rodin, S
• Is Part Of: Sleep. Volume 41(2018)Supplement 1
• Page Start: A403
• Page End: A404
• Publication Date: 2018-04-27
• Subjects: Sleep -- Physiological aspects -- Periodicals; Sleep disorders -- Periodicals; Sommeil -- Aspect physiologique -- Périodiques; Sommeil, Troubles du -- Périodiques; Sleep disorders; Sleep -- Physiological aspects; Sleep -- physiological aspects; Sleep Wake Disorders; Psychophysiology; Electronic journals; Periodicals; 616.8498
• DOI: 10.1093/sleep/zsy061.1086
• Languages: English
• ISSNs: 0161-8105

Abstract

Abstract: Introduction: The shift from volume-based to value-based payment models has increased the emphasis on quality measures (QM) when determining payment. Electronic health records (EHR) enable collection and use of large amounts of QM data, including patient reported outcomes (PRO). Benefits of EHR-based data include availability during individual patient visits and use for group-level data QM. However, efficient PRO collection into the EHR requires integration into the daily clinical workflow. We describe our experience in transitioning from paper-based to EHR-based collection of ESS for individual and group QM documentation. Methods: The ESS was administered with an EHR-based sleep questionnaire (SQ) to all new and returning patients at the Penn Sleep Center. Our goal was to collect ESS for >90% of all visits using the EHR. Originally, patients completed paper questionnaires in the waiting room and providers typed the ESS into EHR notes. Despite creation of an EHR provider digital data entry of ESS in 2010 and the use of PRO entry using the EHR-patient portal SQ in 2013, digital ESS collection remained inconsistent and <50%. In mid-April 2017, we introduced an additional ESS collection method using EHR-based waiting room tablets. Using auto-exported EHR-based ESS data, percent collection of EHR-based ESS were compared before (2014) and after (2017) tablet intervention. Results: De-identified data were analyzed to compare percentages of ESS collection before and after the tablet intervention. EHR-based digital ESS data were collected for 1144 out of 2930 total visits (39.0%) from May-July 2014 (before tablets), and for 1776 out of the 1898 total visits (93.6%) from May-July 2017 (after tablets). Collection was significantly improved after tablets (p<0.0001). Conclusion: EHR-based ESS collection was improved from 2014 to 2017 with integration of tablets into the standard check-in workflow. Integration has enhanced digital EHR-based ESS collection to >90% of all clinic patients. ESS data auto-populate visit notes and save provider documentation time. Data also are available for EHR-based report exports to use for group PRO benchmarks and for AASM and CMS Outcomes QM. Support (If Any): None.