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Does Every Minute Really Count? Road Time as an Indicator for the Economic Value of Emergency Medical Services

Published:November 01, 2021DOI:https://doi.org/10.1016/j.jval.2021.09.009

      Highlights

      • Empirical work on the impact of emergency medical service response time on patient outcomes has provided mixed results.
      • This article displays the endogenous characteristics of response time when estimating its impact on patient outcomes and provides a novel solution to the estimation of this relationship by using “road” time.
      • This article will help healthcare decision makers better understand the relationship between response time and patient outcomes. The results can contribute to more reliable evaluation of policies aimed at optimizing emergency medical service response time.

      Abstract

      Objectives

      This article builds on the literature regarding the association between emergency medical service (EMS) response times and patient outcomes (death and severe injury). Three issues are addressed in this article with respect to the empirical estimation of this relationship: the endogeneity of response time (systematically quicker response for higher degrees of urgency), the nonlinearity of this relationship, and the variation between such estimations for different patient outcomes.

      Methods

      Binomial and multinomial logistic regression models are used to estimate the impact of response time on the probabilities of death and severe injury using data from French Fire and Rescue Services. These models are developed with response time as an explanatory variable and then with road time (dispatch to arrival) hypothesized as representing the exogenous variation within response time. Both models are also applied to data subsets based on response time intervals.

      Results

      The results show that road time yields a higher estimate for the impact of response time on patient outcomes than (total) response time. The impact of road time on patient outcomes is also shown to be nonlinear. These results are of both statistical significance (model coefficients are significant at the 95% confidence level) and economical significance (when taking into account the number of annual interventions performed).

      Conclusions

      When using heterogeneous data on EMS interventions where endogeneity is a clear issue, road time is a more reliable indicator to estimate the impact of EMS response time on patient outcomes than (total) response time.

      Keywords

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