Evaluating Demographic Data to Improve Confidence in Equity Analytics in a Children's Hospital

Abstract

Introduction: Healthcare institutions are placing greater emphasis on equitable care. To accurately track and validate equity metrics, Akron Children's Hospital evaluated how key fields are collected, analyzed, and visualized throughout the organization. Standardized recommendations in this area vary, and this investigation provided specific ways to advance analytics in this field. In addition, the technical infrastructure needed a comprehensive evaluation to increase confidence in using demographic data. Methods: First, we reviewed how staff are trained to collect data at registration. Next, the electronic health record team standardized race and ethnicity fields with federal definitions. We found that fields were not consistently accessible across reporting tools. However, when present, all fields are sourced from the same electronic health record field. Finally, 6 months of encounters were analyzed and validated, with limitations to a seldom-populated Race 2 field. Results: We compared data, including and excluding null values, to provide concise recommendations for standard visualizations. We uncovered many consistencies and a few inconsistencies that informed the next steps. Conclusions: The results informed 7 recommendations to align Akron Children's Hospital's advancement in analytics for health equity data: standardize race and ethnicity fields across all reporting tools, add Child Opportunity Index 2.0 to the enterprise data warehouse, utilize data at the time of the patient's encounter, include null fields (patient refused, unknown, and not specified) in analysis, increase reporting capabilities for social determinants of health (SDOH), standardize multiracial data visualizations, and optimize reliable upstream data collection to increase reliability for all health equity measures.