Improving Lagos State emergency medical services by analysing road traffic accident data, response time, and efficient allocation of ambulances

Sayeed Salam, Avirut Mehta, Dohyeong Kim, Justina Seyi-Olajide, Nicholas Allo, Chenchita Malolan, Fiemu Nwariaku, Latifur Khan

Research output: Contribution to journalArticlepeer-review


BACKGROUND: Emergency medical services (EMS) play a critical role in the response to road traffic accidents (RTAs) by providing critical prehospital care to RTA victims, and thus helping to reduce the severity of injuries and casualties from RTAs. Analysing the efficiency of such systems and optimising the service (often with insufficient resources) would be highly beneficial to inform operating guidelines. In this study, we aimed to assess the ambulance utilisation rate for RTAs and provide insights about the system's efficiency and utilisation metrics in Lagos State, Nigeria. METHODS: We received hospital capacity information (type of hospital [eg, tertiary] and number of beds, nurses, operating rooms, and so on) from hospital survey data in Lagos. Additionally, we received RTA-specific intervention forms from the Lagos State Ambulance Service. With the limited amount of historical data, we highlighted methods to estimate the system parameters (eg, arrival rate, service rate, and so on) of RTA victims at various hospitals in Lagos. We also developed a parametric model and applied approximate dynamic programming approach for ambulance dispatch and location optimisation with a fixed number of base stations. Furthermore, our routing approach was accompanied by directions from OpenRouteService and queue analysis to determine the most appropriate hospital near an RTA for the EMS systems in Lagos. FINDINGS: Using patient-queue based wait-time analysis, we found that in over 80% of cases, one of the nearest three hospitals was the most appropriate recommendation for patient delivery. This exponentially decays with the next closest hospitals. Additionally, we found that optimising the ambulance relocation method, where the ambulance returns to a base selected by our model as opposed to its dedicated base or a random base, can reduce the average response time of the EMS system by 8%, or 3·5 min (from 41 min to 38 min). INTERPRETATION: Appropriate placement of mobile resources (ie, ambulances, health-care booths, and so on) can help to lower the response time of EMS systems in addressing RTAs. Similarly, optimal routing of patients to the most well prepared and nearby hospitals would significantly increase the system's efficacy and improve health outcomes. Our findings can provide valuable insight into this and further inform resource allocation and guidelines for health systems, by identifying those hospitals that have the highest burden of RTA victims and those that provide the most efficient care in a resource-limited setting. FUNDING: National Institutes of Health (1R21TW010991-01A1).

Original languageEnglish (US)
Pages (from-to)S26
JournalThe Lancet Global Health
StatePublished - Mar 1 2022

ASJC Scopus subject areas

  • Medicine(all)


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