Using Patient-level Demographic Data to Reduce Health Care Disparities

In 2009, the Institute of Medicine released a report which emphasized that standardized race, ethnicity and language data are needed to detect disparities. Detecting disparities in care requires collecting valid and reliable data on the demographic characteristics of patients receiving care, then stratifying the data by the relevant demographic subgroups to determine if there are differences in care delivery. However, evidence suggests that hospitals, large medical group practices and community health centers often do not collect basic demographic information from their patients at all, or they collect it in non-systematic and unreliable ways.

The American Medical Association (AMA), Chicago Health Information Technology Regional Extension Center (CHITREC), and Alliance of Chicago Community Health Services (Alliance) conducted a quality improvement project aimed at improving the accuracy and reliability of race and ethnicity data collection and internal reporting in ambulatory care clinics.

The presentation will describe the collaborative process used to develop and implement a ‘toolkit’ with practical information aimed at improving the collection of patient-level data on race and ethnicity in the EHR of ambulatory care settings.  The toolkit provides guidance on best practices to implement a systematic and standardized collection of this data. Accurate and reliable data can then be stratified to identify necessary quality improvement interventions and to ensure equity in health care delivery.

Collaborations between a medical care association, regional extension center and community health centers resulted in more relevant and useful resources to implement a process for systematic and standardized collection of patient-level demographic data for detecting disparities in care.