Exploring State Data Sources to Monitor Rural Emergency Medical Services Performance Improvement
EMS, Flex Monitoring Team, Data, State programs, policy, MRHRC
In 1981, responsibility for overseeing emergency medical services (EMS) largely shifted to states and localities, contributing to the creation of a fragmented national picture of the state of EMS that is most evident in the resultant data collection and reporting issues that curb the availability of EMS data. These patchwork systems of care disproportionately affect rural areas, where myriad challenges – from a high reliance on a volunteer workforce to low call volumes and inadequate reimbursement – hinder performance. Previous studies by the Flex Monitoring Team (FMT) highlighted how little is known about the administrative, operational, and clinical capacity of rural EMS, which are key to investigate further before considering traditional EMS outcome measures. In this study, the FMT convened an expert panel comprised of representatives from a variety of stakeholders to highlight existing data challenges EMS face, identify data to support rural EMS performance measurement, as well as reassess the FMT’s 2017 rural-relevant EMS performance measures.
Among the themes raised by the panel, experts suggested that improved engagement in oversight by state EMS agencies would increase accountability by local EMS; however, they cited a lack of staff capacity and expertise to analyze data in states, as well as disagreement between states on relevant measures. The FMT created EMS capacity measures to monitor and improve rural EMS capacity, along with the National Highway Traffic Safety Administration’s EMS Compass outcome measures to monitor performance. Potential opportunities identified by the panel to source standardized data for those measures include an assessment tool developed through the Joint Committee of Rural Emergency Care, or for the relevant data to be collected by state EMS agencies through their existing EMS service licensure process, many of which already collect some of the relevant data. Electronic patient care records, the typical source of data to calculate EMS clinical and non-clinical performance measures, can be collected and reported to states through the National EMS Information System (NEMSIS). Though not perfect, targeted efforts to improve the collection of local EMS data provides an opportunity for state EMS agencies and State Flex Programs (SFPs) to train local services in data collection, in addition to educating them on how to access and use their own data for performance improvement. This collaboration can also play a role in supporting improved health information exchange between EMS, hospitals, and other providers, which help improve the quality of pre-hospital care and assist in monitoring the quality and outcomes of care across the system of care.
The importance of reliable, standardized, and timely data from local and state EMS is underscored by the recently launched Medicare Ground Ambulance Data Collection System, a Centers for Medicare and Medicaid Services study that will collect information to evaluate how ground ambulance costs relate to current payment policies. In turn, this will be used to formulate a report to Congress assessing the adequacy of Medicare ground ambulance payment rates and geographic variations in cost. As the data will be used to assess reimbursement rates across urban, rural, and super rural areas, accurate data collection and reporting is vital.
The expert panel also reaffirmed the validity of FMT’s rural-relevant measures and raised questions about monitoring the measures longitudinally or developing measures to assess financial performance and sustainability. Additional work is needed to understand how to best use these measures to track rural EMS capacity over time, as well as identify the relevant financial measures.
Gale, J, Pearson, K, Jonk, Y. Exploring State Data Sources to Monitor Rural Emergency Medical Services Performance Improvement. Portland, ME: University of Southern Maine, Flex Monitoring Team, Maine Rural Health Research Center; March 2020. Briefing Paper #43.