29 Shining a light on health inequities and racial disparities – closing the gap with real-world data & SPC methodology. (2nd December 2020)

• Record Type: Journal Article
• Authors: Low, Daniel
• Is Part Of: BMJ open quality. Volume 9:Supplement 1(2020)
• Page Start: A28
• Page End: A29
• Publication Date: 2020-12-02
• Subjects: Medical care -- Quality control -- Periodicals; 362.106805
• DOI: 10.1136/bmjoq-2020-IHI.29
• Languages: English
• ISSNs: 2399-6641

Abstract

Abstract : Background: Health disparities in racial minorities are well documented but few hospitals use real-world data to understand equity. The U.S. has invested over $48 billion in electronic medical records (EMRs), that data can be used to surface and improve these disparities. Objectives: Identify disparities in outcomes for different racial groups across a range of acute care domains - emergency medicine through to peri-operative care. Methods: Using EMR data, a range of clinical metrics for acute care (surgical and emergencies) were surfaced in statistical process control (SPC) charts and then sub-grouped by race to identify disparities in care and opportunities to improve. Results: For stroke patients presenting to the emergency department, looking at time to receive tPA treatment - we detected special cause variation for black patients, 50 min door to treatment time compared to 28 minutes for white patients. Surgical pain following surgery measured in the recovery room (PACU) and the first 24 hours after surgery - we learned American indian patients experience more pain (4.3) than white patients (3.5). Post-operative hospital length of stay - we detected special cause variation for American indian patients who have a longer stay (7.7 days) compared to white patients (3.9 days). 30-day re-operation rate following elective surgeries - we detected special cause variation for American indian patients who have a higher re-operation rate than white patients (17.3% vs 11.4%). 30-day re-admission rates for elective surgeries - we detected special cause variation for American Indian patients and those identifying as multiple races who have a higher rate (11.5% and 10.5%) than white patients (8.1%). Conclusions: SPC methodology allows clinicians to use EMR data to understand how patients' race effects their outcomes across a range of acute care domains. Enabling them to track the effect of system changes to understand if equity improves.