Using Red Lights and Sirens for Emergency Ambulance Response: How Often Are Potentially Life-Saving Interventions Performed?

Effect of urgency level on prehospital emergency transport times: a natural experiment

Accurate estimation of ambulance transport time from the scene of incident to arrival at the emergency department (ED) is important for effective resource management and emergency care system planning. Further, differences in transport times between different urgency levels highlight the benefits of ambulance transports with highest urgency level in a setting where ambulances are allowed to not follow standard traffic rules. The objective of the study is to compare ambulance urgency level on the differences in estimates of ambulance transport times generated by Google Maps and the observed transport times in a prehospital setting where emergency vehicles have their own traffic laws. The study was designed as a natural experiment and register study. Ambulance transports dispatched with different levels of urgency (Level A and B) were included in the Central Denmark Region (a mixed urban and rural area) from March 10 to June 11, 2021. Ambulance transports for highest urgency level were compared to lowest urgency level with Google Maps estimated transport times as reference. We analyzed 1981 highest urgency level and 8.958 lowest urgency level ambulance transports. Google Maps significantly overestimated the duration of transports operating at highest level of urgency (Level A) by 1.9 min/10 km (95% CI 1.8; 2.0) in average and 4.8 min/10 km (95% CI 3.9; 5.6) for the first driven 10 km. Contrary, Google Maps significantly underestimated the duration of transports operating at lowest level of urgency (Level B) by -1.8 min/10 km (95% CI -2.1; -1.5) in average and -4.4 min/10 km (95% CI -5.4; -3.5) for the first driven 10 km. Google Maps systematically overestimates transport times of ambulance transports driven with Level A, the highest level of urgency in a setting where ambulances are allowed to not follow standard traffic rules. The results highlight the benefit of using urgency Level A and provide valuable information for emergency care management.

A National Assessment of EMS Performance at the Response and Agency Level

BACKGROUND

In 2019, the National EMS Quality Alliance (NEMSQA) established a suite of 11 evidence-based EMS quality measures, yet little is known regarding EMS performance on a national level. Our objective was to describe EMS performance at a response and agency level using the National EMS Information System (NEMSIS) dataset.

METHODS

The 2019 NEMSIS research dataset of all EMS 9-1-1 responses in the United States was utilized to calculate 10 of 11 NEMSQA quality measures. Measure criteria and pseudocode was implemented to calculate the proportion meeting measure criteria and 95% confidence intervals across all encounters and for each anonymized agency. We omitted Pediatrics-03b because the NEMSIS national dataset does not report patient weight. Agency level analysis was subsequently stratified by call volume and urbanicity.

RESULTS

Records from 9,679 agencies responding to 26,502,968 9-1-1 events were analyzed. Run-level average performance ranged from 12% for Safety-01 (encounter documented as initial response without the use of lights and siren to 82% for Pediatrics-02 (documented respiratory assessment in pediatric patients with respiratory distress) At the agency level, significant variation in measure performance existed by agency size and by urbanicity. At the individual agency performance analysis, Trauma-04 (trauma patients transported to trauma center) had the lowest agency-level performance with 47% of agencies reporting 0% of eligible runs with documented transport to a trauma center.

CONCLUSION

There is a wide range of performance in key EMS quality measures across the United States that demonstrate a need to identify strategies to improve quality and equity of care in the prehospital environment, system performance and data collection.

Frequency, Type, and Degree of Potential Harm of Adverse Safety Events among Pediatric Emergency Medical Services Encounters

BACKGROUND

Only 5-10% of emergency medical services (EMS) patients are children, and most pediatric encounters are low-acuity. EMS chart review has been used to identify adverse safety events (ASEs) in high-acuity and high-risk pediatric encounters. The objective of this work was to evaluate the frequency, type, and potential harm of ASEs in varied acuity pediatric EMS encounters.

METHODS

This cross-sectional study evaluated pediatric (ages 0-18 years) prehospital records from 15 EMS agencies among three states (Colorado, Connecticut, and Rhode Island) between November 2019 and October 2021. Research associates used a previously validated tool to analyze electronic EMS and hospital records. Adverse safety events were recorded in six care categories, grouped into four levels for analysis: assessment/diagnosis/clinical decision-making, procedures, medication administration (including O2), and fluid administration, and defined across five types of ASEs: Unintended injuries or consequences, Near misses, Suboptimal actions, Errors, and Management complications (UNSEMs). Type and frequency of ASEs in each category were rated in three harm severities: Harm Unlikely, Mild/Temporary, or Permanent/Severe. Three physicians verified ASEs determined by research associates. Frequency of ASEs and harm likelihood are reported.

RESULTS

Records for 508 EMS patients were reviewed, with 63 (12.4%) transported using lights and sirens. At least one clinical intervention beyond assessment/diagnosis/clinical decision-making was documented for 183 (36.1%, 95% CI: 31.8, 40.4) patients. A total of 162 ASEs were identified for 112 patients (22.1%, 95% CI: 18.5, 25.7). Suboptimal actions were the most frequent UNSEM (n = 66, 40.7%; 95% CI: 33.1, 48.3). For ASEs, (n = 162), the most frequent associations were with procedures 39.5% (95% CI: 32.0, 47.0) or assessment/diagnosis/clinical decision making, 32.1%, (95% CI: 24.9, 39.3). Among care categories, fluid administration was associated with significantly more UNSEMs (58.1%, 95% CI:53.8, 62.4). Most ASEs were determined to be 'Harm Unlikely' 62.4% (95% CI: 54.4, 70.4), with assessment/diagnosis/clinical decision making having significantly fewer ASEs with documented harm (22.4%, 95% CI: 10.7, 34.1) compared to other care categories.

CONCLUSION

Over 20% of pediatric EMS encounters had an identified ASE, and most were unlikely to cause harm. Most frequent ASEs were likely to be associated with procedures and assessment/diagnosis/clinical decision-making.

Driving Speeds in Urgent and Non-Urgent Ambulance Missions during Normal and Reduced Winter Speed Limit Periods—A Descriptive Study

Objective: Most traffic research on emergency medical services (EMS) focuses on investigating the time saved with emergency response driving. Evidence regarding driving speed during non-urgent ambulance missions is lacking. In contrast, this descriptive study compared registered driving speeds to the road speed limit in urgent A-missions and non-urgent D-missions. Specifically, the study examined driving speeds during normal speed limits, periods of reduced winter speed limits, and speeding during non-urgent D-missions. Methods: Urgent A-missions and non-urgent D-missions were included. Registered ambulance locations and speed data from Pirkanmaa Hospital District, Finland between 1 January 2018 and 31 December 2018 were used. Ambulance locations were linked to OpenStreetMap digital road network data. The registered driving speed distribution was reported as quartiles by the effective road speed limit. Furthermore, the results during the normal speed limit and reduced winter speed limit periods were reported separately. Driving speeds in non-urgent missions were compared with current Finnish traffic violation legislation. Results: As expected, the urgent A-missions exceeded the speed limits during both the normal speed limit and reduced winter speed limit periods. On the smallest streets with speed limits of 30 km/h, the driving speeds in urgent missions were lower than the speed limit. The driving speeds in non-urgent D-missions were broadly similar throughout the whole year on high-speed roads, and mostly on lower speed limit roads. However, within the 30 km/h speed limits, the mean speed in non-urgent missions appeared to increase during the winter. One-fifth of the registered non-urgent D-missions were speeding. Conclusions: Speeding is common in urgent A-missions and non-urgent D-missions throughout the year. Stricter guidelines for EMS are needed to increase driving safety.