Stats, Stat! Now With QA/QI Applications for Volunteer EMS Agencies
- 2 minsCollegiate EMS agencies face a variety of common operational challenges, from staffing issues to underwhelming recruitment and retention rates. Low call volumes, high member turnover, and non-targeted recruitment strategies often exacerbate these issues. However, solutions are possible with the aid of an untapped organizational resource: data. Agencies often possess an unrealized amount of information, from trends in patient care reports to commonalities among members.
At the 2019 annual conference of the National Collegiate EMS Foundation in Pittsburgh, I presented an evolved version of “Stats, Stat!”, my statistics-based lecture which won the Vomacka Student Speaker competition in 2018. This lecture expands upon previous work by incorporating quality assurance/quality improvement (QA/QI) applications of basic statistical methodology to volunteer EMS agency data. This iteration of the presentation broadened the analytic scope to examine how incorporating data analysis in quality improvement processes additionally benefits patient care, clinical performance, and resource allocation. I overviewed basic statistical analysis which enables agency leaders to effectively recognize members struggling with clinical skills, identify members likely to leave an organization or applicants likely to join the agency, and forecast call volumes to lend quantitative evidence to that well known, anecdotal suspicion that “tonight will be a bad night.” The presentation highlighted the interconnectedness and diverse applications of these easily obtainable metrics, presented the results of these applications at Carnegie Mellon University EMS and the City of Pittsburgh EMS, identified flaws and methodology improvements, and generalized these approaches to enable audience members to identify their own solutions based on agency-specific priorities and needs.
Learning objectives for audience members included identifying useful metrics (primarily from organizational and patient care data), reviewing methodology to obtain these data (including harnessing existing ePCR reporting software), and analyzing real data to provide insight into improving performance in patient care, resource allocation and response operations, and member recruitment and retention. This presentation allowed audiences to see the operational and clinical advantages of integrating straightforward data analysis into their quality improvement processes. Specific examples of these benefits in the presentation included data-driven detection of clinical skills which require improvement or practice, methods for basic call volume prediction, and identification both of strong candidates applying to an agency and of agency members likely to leave an agency. Methodology was generalized to allow audience members to identify their own solutions based on agency-specific priorities and needs.
Header image source: The National Collegiate Emergency Medical Service Foundation.
Tom Goode
Data Scientist & EMS Researcher