@article {Taylore007562, author = {Jennifer A Taylor and Andrea L Davis and Brittany Barnes and Alicia V Lacovara and Reema Patel}, title = {Injury risks of EMS responders: evidence from the National Fire Fighter Near-Miss Reporting System}, volume = {5}, number = {6}, elocation-id = {e007562}, year = {2015}, doi = {10.1136/bmjopen-2014-007562}, publisher = {British Medical Journal Publishing Group}, abstract = {Objectives We analysed near-miss and injury events reported to the National Fire Fighter Near-Miss Reporting System (NFFNMRS) to investigate the workplace hazards and safety concerns of Emergency Medical Services (EMS) responders in the USA.Methods We reviewed 769 {\textquoteleft}non-fire emergency event{\textquoteright} reports from the NFFNMRS using a mixed methods approach. We identified 185 emergency medical calls and analysed their narrative text fields. We assigned Mechanism of Near-Miss/Injury and Nature of Injury codes and then tabulated frequencies (quantitative). We coded major themes regarding work hazards and safety concerns reported by the EMS responders (qualitative).Results Of the 185 emergency medical calls, the most commonly identified Mechanisms of Near-Miss/Injury to EMS responders was Assaults, followed by Struck-by Motor Vehicle, and Motor Vehicle Collision. The most commonly identified weapon used in an assault was a firearm. We identified 5 major domains of workplace hazards and safety concerns: Assaults by Patients, Risks from Motor Vehicles, Personal Protective Equipment, Relationships between Emergency Responders, and Policies, Procedures and Practices.Conclusions Narrative text from the NFFNMRS is a rich source of data that can be analysed quantitatively and qualitatively to provide insight into near-misses and injuries sustained by EMS responders. Near-miss reporting systems are critical components for occupational hazard surveillance.}, issn = {2044-6055}, URL = {https://bmjopen.bmj.com/content/5/6/e007562}, eprint = {https://bmjopen.bmj.com/content/5/6/e007562.full.pdf}, journal = {BMJ Open} }