This brief highlights a roundtable discussion that sought to identify ways to improve data about the safety of incident response and emergency services personnel working on the side of the road. Recommendations are made based on information provided by the panel of experts.
Incident response and emergency services personnel, including police, firefighters, emergency medical services, and towing operators, are at risk of being struck by passing motorists while they are working at the roadside. Stakeholders such as AAA and others strive to reduce these professionals’ risk of being injured or killed on the job through advocacy, education, and implementation of other safety measures. However, at present, such efforts are greatly limited by a lack of comprehensive, high-quality data on the incidence, as well as the details, of crashes involving this population and the associated injuries and deaths. Such data are fundamental to the design, tracking, and appraisal of national, state, or regional countermeasures to enhance the safety of these workers.
This Research Brief describes highlights from a roundtable discussion hosted by the AAA Foundation for Traffic Safety that sought to identify ways to improve data about the safety of incident response and emergency services personnel. A panel of experts was convened to discuss issues and efforts surrounding data on crashes involving roadside responders. The overarching aim was to help improve the overall accounting of roadside service providers killed and injured each year while assisting other motorists in order to learn more about the circumstances of these tragic incidents. Toward these ends, the panel was asked to reflect on two main questions:
A number of recommendations have been distilled, based on the rich information provided by the panel of experts. They are not independent of one another, nor is the list exhaustive. Collectively (and ideally), they represent areas where positive steps can be taken towards establishing better estimates of crashes involving roadside responders and gaining better insight into the circumstances surrounding such instances. In the figures below, the recommendations are grouped into three categories, however these are not mutually exclusive.
|Improving Data Quality and Granularity|
|Enhance Current Data Systems||Improve Data Collection Process||Enhance Training of Coders||Standardize Job
Advocate for continued enhancements to current data systems, including improvements to specific variables or elements.
The ultimate goal is to ensure sufficient resolution in the variables that relate to personnel responding to incidents at the roadside.
|Promote or advocate for enhancements in the collection of data to reduce the burden for those charged with collecting data in the field, while ensuring the capture of critical elements.||
Promote or advocate for continued or enhanced training of coders.
This requires a deeper assessment of needs and challenges faced by those in the field.
Promote the standardizing of critical job codes and other related data elements across data sets.
In traffic crash data sets, promote, at minimum, an indicator of whether a crash-involved person was working or on-duty.
|Enabling Data Sharing and Linkage|
|Catalogue Existing Data Sources||Determine Cost-Benefits of Linkage||Establish a Data Coalition||Develop Linkage Strategy|
Develop inventories of what data sources* are available and what information each includes. This will help guide strategies for sharing and linking data.
This includes record-level data that forms the basis of aggregates generated by different organizations.
*Note that “data sources” should be construed broadly to include non-traditional data sources, such as media articles, in addition to traditional sources such as research or actuarial databases.
Determine what information can be gained by linkage of existing data sources beyond that which is available in any of them individually, and how or whether those data sources can be linked.
|Establish a coalition charged with facilitating data sharing and harmonizing, including a universal identifier that would be common across data sources (or, minimally, a feasibility assessment of doing so).||
Determine the following:
• Which existing data sources can be linked deterministically in their current form?
• What steps would need to be taken to enable deterministic linkage where it is not currently possible (e.g., creation of unique identifiers common to all relevant data sources) and what is the feasibility of doing so?
• Whether probabilistic linkage is feasible until unique identifiers are created to enable deterministic linkage?
|Expanding Data Sources|
|Examine Feasibility and Utility of Video Data|
|If data on near misses are desired, carry out a feasibility assessment of a near-miss reporting system for roadside service providers. If promising, this could be conducted as a proof-of-concept with a one or more fleets of roadside service providers.||If in-vehicle video data are desired for risk-management operations and/or for research or educational purposes, a feasibility assessment of using truck-mounted video recorders to capture near misses can be carried out.|
Two 2-hour discussions were held virtually in June 2021. As shown in the table below, a diverse group of nine experts participated in the discussion, representing a mixture of different backgrounds and job roles, including academic researchers, epidemiologists, a crash investigator, a federal program manager, a research statistician, a program analyst, and an insurance risk control professional. Collectively, this group had experience and knowledge of safety and health surveillance programs, work-related injuries, on-site investigations, service providers, EMS and first responder safety, towing safety, worker’s compensation, national- and state-level data, operational strategies for databases, and occupational injury and illness.
The main points of the conversation are summarized in the Brief. Based on this information, several recommendations were subsequently generated.