Factors affecting the ambulance response times of trauma incidents in Singapore Sean Shao Wei Lam a, *, Francis Ngoc Hoang Long Nguyen a , Yih Yng Ng b , Vanessa Pei-Xuan Lee c , Ting Hway Wong d , Stephanie Man Chung Fook-Chong e , Marcus Eng Hock Ong f a Health Services Research and Biostatistics Unit, Division of Research, Singapore General Hospital, 226 Outram Road, Singapore 169039, Singapore b Medical Department, Singapore Civil Defence Force, 91 Ubi Ave 4, Singapore 408827, Singapore c Health Services Research and Biostatistics Unit, Division of Research, Singapore General Hospital, 226 Outram Road, Singapore 169039, Singapore d Department of General Surgery, Singapore General Hospital; Health Services Research and Biostatistics Unit, Division of Research, Singapore General Hospital, 226 Outram Road, Singapore 169039, Singapore e Health Services Research and Biostatistics Unit, Division of Research, Singapore General Hospital, 226 Outram Road, Singapore 169039, Singapore f Department of Emergency Medicine, Singapore General Hospital; Health Services Research and Biostatistics Unit, Division of Research, Singapore General Hospital; Health Services and Systems Research, Duke-NUS Graduate Medical School, 226 Outram Road, Singapore 169039, Singapore A R T I C L E I N F O Article history: Received 24 February 2015 Received in revised form 7 May 2015 Accepted 7 May 2015 Available online xxx Keywords: Emergency medical services Ambulance response time Trauma Multinomial logistic regression A B S T R A C T Objectives: Time to definitive care is important for trauma outcomes, thus many emergency medical services (EMS) systems in the world adopt response times of ambulances as a key performance indicator. The objective of this study is to examine the underlying risk factors that can affect ambulance response times (ART) for trauma incidents, so as to derive interventional measures that can improve the ART. Material and methods: This was a retrospective study based on two years of trauma data obtained from the national EMS operations centre of Singapore. Trauma patients served by the national EMS provider over the period from 1 January 2011 till 31 December 2012 were included. ART was categorized into “Short” (<4 min), “Intermediate” (4–8 min) and “Long” (>8 min) response times. A modelling framework which leveraged on both multinomial logistic (MNL) regression models and Bayesian networks was proposed for the identification of main and interaction effects. Results: Amongst the process-related risk factors, weather, traffic and place of incident were found to be significant. The traffic conditions on the roads were found to have the largest effect—the odds ratio (OR) of “Long” ART in heavy traffic condition was 12.98 (95% CI: 10.66–15.79) times higher than that under light traffic conditions. In addition, the ORs of “Long ART” under “Heavy Rain” condition were significantly higher (OR 1.58, 95% CI: 1.26–1.97) than calls responded under “Fine” weather. After accounting for confounders, the ORs of “Long” ART for trauma incidents at “Home” or “Commercial” locations were also significantly higher than that for “Road” incidents. Conclusion: Traffic, weather and the place of incident were found to be significant in affecting the ART. The evaluation of factors affecting the ART enables the development of effective interventions for reducing the ART. ã2015 Elsevier Ltd. All rights reserved. 1. Introduction Emergency medical services (EMS) is a critical link in any trauma and emergency care system (Cowley, 1976; Cummins, 1993; I.O.M., 2007). The growing demand for more efficient EMS has sparked off efforts to evaluate and improve the quality of many EMS systems in recent years. The key objective of many successful EMS systems can be operationally defined by the effective and consistent provision of immediate medical care to seriously ill or injured patients, and the expeditious conveyance of patients to advanced resuscitation and Abbreviations: EMS, emergency medical services; OR, odds ratio; PACS, patient acuity category scale; ED, emergency department; MNL, multinomial logistic model; ART, ambulance response time; ITT, ideal travel time; LRT, likelihood ratio test; CI, confidence interval; IQR, interquartile range. * Corresponding author at: Health Services Research and Biostatistics Unit Division of Research, Singapore General Hospital, 226 Outram Road, Blk A Level 2, Singapore 169603, Singapore. Tel.: +65 65762617; fax: +65 64385836. E-mail addresses: lam.shao.wei@sgh.com.sg (S.S.W. Lam), nguyen.ngoc.hoang.long@sgh.com.sg (F.N.H.L. Nguyen), ng_yih_yng@scdf.gov.sg (Y.Y. Ng), vanessalpx@yahoo.com.sg (V.P.-X. Lee), wong.ting.hway@sgh.com.sg (T.H. Wong), stephanie.fook.m.c@sgh.com.sg (S.M.C. Fook-Chong), marcus.ong.e.h@sgh.com.sg (M.E.H. Ong). http://dx.doi.org/10.1016/j.aap.2015.05.007 0001-4575/ ã 2015 Elsevier Ltd. All rights reserved. Accident Analysis and Prevention 82 (2015) 27–35 Contents lists available at ScienceDirect Accident Analysis and Prevention journal homepage: www.else vie r.com/locate /aa p