Development and testing of data infrastructure in the American College of Emergency Physicians' Clinical Emergency Data Registry for opioid-related research.

Objective: Prior research has identified gaps in the capacity of electronic health records (EHRs) to capture the intricacies of opioid-related conditions. We sought to enhance the opioid data infrastructure within the American College of Emergency Physicians' Clinical Emergency Data Registry (CEDR), the largest national emergency medicine registry, through data mapping, validity testing, and feasibility assessment. Methods: We compared the CEDR data dictionary to opioid common data elements identified through prior environmental scans of publicly available data systems and dictionaries used in national informatics and quality measurement of policy initiatives. Validity and feasibility assessments of CEDR opioid-related data were conducted through the following steps: (1) electronic extraction of CEDR data meeting criteria for an opioid-related emergency care visit, (2) manual chart review assessing the quality of the extracted data, (3) completion of feasibility scorecards, and (4) qualitative interviews with physician reviewers and informatics personnel. Results: We identified several data gaps in the CEDR data dictionary when compared with prior environmental scans including urine drug testing, opioid medication, and social history data elements. Validity testing demonstrated correct or partially correct data for >90% of most extracted CEDR data elements. Factors affecting validity included lack of standardization, data incorrectness, and poor delimitation between emergency department (ED) versus hospital care. Feasibility testing highlighted low-to-moderate feasibility of date and social history data elements, significant EHR platform variation, and inconsistency in the extraction of common national data standards (eg, Logical Observation Identifiers Names and Codes, International Classification of Diseases, Tenth Revision codes). Conclusions: We found that high-priority data elements needed for opioid-related research and clinical quality measurement, such as demographics, medications, and diagnoses, are both valid and can be feasibly captured in a national clinical quality registry. Future work should focus on implementing structured data collection tools, such as standardized documentation templates and adhering to data standards within the EHR that would better characterize ED-specific care for opioid use disorder and related research.