Recommendations for improving national clinical datasets for health equity research.

Health and healthcare disparities continue despite clinical, research, and policy efforts. Large clinical datasets may not contain data relevant to healthcare disparities and leveraging these for research may be crucial to improve health equity. The Health Disparities Collaborative Research Group was commissioned by the Patient-Centered Outcomes Research Institute to examine the data science needs for quality and complete data and provide recommendations for improving data science around health disparities.

Interviews with Patients and Providers on Transgender and Gender Nonconforming Health Data Collection in the Electronic Health Record.

Meaningful use (MU) and Uniform Data Systems (UDSs) are calling for the collection of gender identity (GI) in electronic health record (EHR) systems; however, many transgender and nonconforming (TGNC) patients may not feel safe disclosing their GI and the data collection is not designed to guide care provision. This study explores the complexities surrounding the inclusion of GI in EHR data collection and how it can best serve patients and providers. Using a semistructured interview format, TGNC patients (=7) and providers (=5) who care for TGNC patients were asked about data collection procedures and the use of these data within community health centers in Oregon.