Abstracts

A Real-time Dashboard of Patient-reported Determinants of Health Disparities and Adherence to Epilepsy Quality Metrics in a Large Healthcare System

Abstract number : 1.399
Submission category : 13. Health Services (Delivery of Care, Access to Care, Health Care Models)
Year : 2022
Submission ID : 2204767
Source : www.aesnet.org
Presentation date : 12/3/2022 12:00:00 PM
Published date : Nov 22, 2022, 05:26 AM

Authors :
Lidia Moura, MD, PhD, MPH – Mass General Hospital / Harvard Medical School; Jeffrey Buchhalter, MD, PhD – Epilepsy Learning Healthcare System; Maria Donahue, MD – MGH; Brandy Fureman, PhD – Epilepsy Foundation of America; Marilyn Heng, MD – MGH/HMS; Christopher McGraw, MD, PhD – MGH/HMS; Nicte Mejia, MD – MGH/HMS; Zafar Sahar, MD, Mac – MGH/HMS; Lee Schwamm, MD – MGH/HMS; Rachel Sisodia, MD – MGH/HMS

This abstract has been invited to present during the Broadening Representation Inclusion and Diversity by Growing Equity (BRIDGE) poster session.

Rationale: Quality improvement (QI) learning networks are gaining popularity in healthcare and proving to be effective in improving patient outcomes. Effective models of QI are built on the same components: evidence-based best practices, quality measurement, patient engagement, and real-time performance data. One of the best measures of performance, patient-reported determinants of health (PRDOH) represent the most powerful tool to promote health care equity, but lack of resources and structure to collect this data prevent many networks from thriving. To demonstrate the feasibility of collecting and timely dashboarding PRDOH and clinicians’ adherence to quality measures in a tertiary epilepsy clinic, and to examine whether this dashboard would enable identification of opportunities to reduce healthcare disparities._x000D_
Methods: We offered surveys to 7,484 consecutive adult patients at check-in for in person or virtual epilepsy clinic to collect patient-reported outcome measures (PROMs) using tablets (January 2017 - December 2019) or patient-portal virtual surveys (January 2020 - April 2022). We collected demographic, clinical, and administrative data on all patients from electronic data warehouse and PROMs from respondent patients. We evaluated PROMS completion rates before and after the virtual survey assignment, and stratified the dashboard by race, ethnicity, and preferred language to explore potential inequities in completion rates._x000D_
Results: Of 7,484 patient-encounters in the tertiary epilepsy clinic (2017 - April 2022), 3,987 (53%) patient-encounters had completed surveys (2,196 unique patients). Among respondents, 40% identified as 18-34 years old, 54% female, 85% white, 97% preferred to speak English (1% Spanish, < 2% Other), 49% single (42% married, 4% divorced, 5% other), 41% employed full time (26% unemployed, 15% retired), 13% lived completely alone, and 85% lived at home without community services. 34% reported sometimes/often forgetting to take their medications in the past six months. Among those with epilepsy, 22% (n=607/2,818) reported side effects to anticonvulsants, and 69% (n= 1,369/1,988) had at least one seizure in the last two years. Compared to the pre-virtual survey assignment period (2017-2019), the mean completion rate was greater during the post-virtual survey assignment period of 2020-4/2022 (44% [17-70%] vs. 58% [48-68%]) (Figure 1). People who identified as Black or Latino, particularly those who preferred to speak languages other than English had low completion rates – even after offering the surveys in six languages –but with wide and overlapping confidence intervals (Table 1)._x000D_
Conclusions: Virtual survey assignment and timely dashboarding of patient-reported determinants of health and clinicians’ adherence to quality measures is feasible. The dashboard enabled the visualization of the low diversity, and the potential racial, ethnic, and language differences among survey respondents. It equipped quality improvement teams trying to promote inclusion and equity in epilepsy care._x000D_
Funding: This work was supported by the Department of Neurology of the Massachusetts General Hospital.
Health Services (Delivery of Care, Access to Care, Health Care Models)