Abstract
AbstractIn this paper, we analyze the Fire Department of New York City’s pre-hospital emergency medical services dispatch data for the period of March 20, 2019–June 13, 2019, and the corresponding Covid lockdown period of March 20, 2020–June 13, 2020. A fixed effects negative binomial model is used to estimate the heterogeneity effects of average ambulance travel or response times on the daily volume of emergency calls, year, day of the week, dispatcher-assigned medical emergency call type, priority rank, ambulance crew response, borough and an offset for missing calls. We also address the limitations of other non-parametric Covid studies or parametric studies that did not properly account for over-dispersion. When our model is estimated and corrected for clustered standard errors, fixed effects, and over-dispersion, we found that Wednesday was the only day of the week that was most likely to increase travel response time with an odd ratio of 6.91%. All grouped call types that were categorized showed significant declines in average travel time, except for call types designated as allergy and an odds ratio of 21.81%. When compared to Manhattan, Staten Island ambulance response times increased with an odds ratio of 19.05% while the Bronx showed a significant decline with an odds ratio of 31.92% advanced life support (ALS) and BLS ambulances showed the biggest declines in travel time with the exception of BLS assigned ambulance types and emergency priority rank of 6. Surprisingly, in terms of capacity utilization, the dispatch system was not as overwhelmed as previously predicted as emergency call volume declined by 8.83% year over year.
Publisher
Springer Science and Business Media LLC
Subject
General Economics, Econometrics and Finance,General Psychology,General Social Sciences,General Arts and Humanities,General Business, Management and Accounting
Reference29 articles.
1. Agresti A (2007) An introduction to categorical data analysis, 2nd edn. John Wiley & Sons, New York.
2. Ahmad FB, Cisewski JA, Miniño A, Anderson RN (2021) Provisional mortality data—United States, 2020. CDC Morb Mortal Wkly Rep 70:1–4
3. Amiry AA, Maguire BJ (2021) Emergency medical services (ems) call during covid-19: early lessons learned for systems planning (a narrative review). Open Access Emerg Med 13:407–414
4. Azbel M, Heinanen M, Laaperi M, Kuisma M (2021) Effects of the covid-19 pandemic on trauma-related emergency medical service calls: a retrospective cohort study. BMC Emerg Med 21:1–10
5. Berge L (2018) Efficient estimation of maximum likelihood models with multiple fixed-effects: the R package FENmlm. Center for Research in Economics and Managment, CREA Discussion Paper 2018-13, pp. 1–38. https://wwwen.uni.lu/content/download/110162/1299525/file/2018_13. Accessed 20 December 2019