Data-Related Processes and Challenges at Level I-IV Trauma Centers in Arkansas: Results of a Mixed-Methods Case Study.

Background: Clinical data registries provide a rich source of real-world data that can be leveraged by clinicians, researchers, and public health professionals to address some of the current health challenges faced in society today. The relative usefulness of a registry depends on the ability to gather data and the overall quality of the data. To assess existing datarelated processes, including barriers and facilitators to data collection and submission, we conducted an observational case study to evaluate sites submitting data to a prominent state-based trauma registry. Methods: A mixed-methods approach was undertaken to evaluate existing processes and barriers to data collection for the Arkansas Trauma Registry (ATR). A series of interviews and observations were conducted with trauma registry personnel from level I-IV trauma centers across the state of Arkansas to collect data on current data-related processes. To facilitate observations, a think-aloud protocol was used to gather keystroke-level modeling (KLM) data. Additional observational data (qualitative) were collected regarding site processes and workflows pertaining to the collection and submission of registry data to the ATR. Following the observations, informal, semi-structured interviews were conducted to assess the participants' perspectives on current data-related processes, potential barriers to data collection or submission, and any recommendations for improvement. All sessions were recorded, and de-identified transcripts and session notes were used for analysis. Quantitative analyses were performed on the KLM data derived from observations to determine time spent performing end-to-end registry-related activities. Qualitative data from interviews were reviewed and coded by 2 independent reviewers. The qualitative codings were adjudicated by the reviewers using a consensus-driven approach. Themes were then extrapolated to generate the final set of results. Results: Seven unique staff members (trauma registrars, coordinators, supervisors, and directors) participated in the study, having completed both observation and interview sessions. These participants were from 5 unique trauma centers (one level I, one level II, two level III, and one level IV). Through the observations, we were able to characterize the typical operational flow for level I-IV trauma centers participating in the ATR, confirming a primarily manual process was used across all sites. Furthermore, the KLM analysis demonstrated that, on average, site staff would need close to 26 total hours to identify, abstract, and transcribe a single, relatively complex trauma registry case (meaning all 288 registry data elements were captured). Results from interviews further emphasized the exhaustive nature of the current data collection processes across sites, regardless of trauma level classification. Five common themes were identified across all 7 interviews: data quality; manual processes; resources and technology; site environment and staffing; and training. Across each theme, interviewees provided their perspectives on various activities and procedures at their site, as well as on the overarching trauma registry program. Many positive perspectives were shared, and several negative perspectives and perceived issues were noted. Interviewees also provided recommendations for improving internal site processes and streamlining the way in which data are collected and submitted to the ATR. Discussion: Automation of data entry, improved training resources, and adequate staffing are critical areas of improvement for efficiently abstracting registry data. By streamlining manual inputs into the registry, registrars could minimize time spent consolidating and abstracting recurring data. Conclusion: These results illuminate existing data-related practices of sites participating in the ATR and the outcomes measures for process improvement efforts. These challenges are not unique to the trauma domain and are encountered by registries across a variety of therapeutic areas. Thus, attempts to develop integrated and interoperable solutions to streamline and improve data collection would benefit all registries.