We aim to evaluate whether the first National Emergency Medical Service (NEMS) improved access to hospital care for the people of Sierra Leone. We performed an interrupted time-series analysis to assess the effects of NEMS implementation on hospital admissions in 25 facilities. The analysis was also replicated separately for the area of Freetown and the rest of the country. The study population was stratified by the main Free Health Care Initiative (FHCI) categories of pregnant women, children under 5 years of age, and populations excluded from the FHCI. Finally, we calculated direct costs of the service. We report a 43% overall increase in hospital admissions immediately after NEMS inception (RR 1.43; 95% CI 1.2–1.61). Analyses stratified by FHCI categories showed a significant increase among pregnant women (RR 1.54; 95% CI 1.33–1.77) and among individuals excluded from the FHCI (RR 2.95; 95% CI 2.47–3.53). The observed effect was mainly due to the impact of NEMS on the rural districts. The estimated recurrent cost per ambulance ride and NEMS yearly cost per inhabitant were 124 and 0.45 USD, respectively. To our knowledge, this is the first nationwide study documenting the increase in access to healthcare services following the implementation of an ambulance-based medical service in a low-income country. Based on our results, NEMS was able to overcome the existing barriers of geographical accessibility and transport availability, especially in the rural areas of Sierra Leone.

Background: The COVID-19 pandemic has positioned fragile healthcare systems in low-income countries under pressure, leading to critical gaps in service delivery. The pandemic response demands the healthcare system to be resilient and continue provision of healthcare services. This review is aimed at describing the healthcare response challenges during the pandemic in Ethiopia. Methodology: Eligible studies dealing with challenges of the healthcare system in response to the COVID-19 pandemic in Ethiopia were included. The six World Health Organization (WHO) healthcare system building blocks were used to categorize healthcare challenges. PubMed ProQuest, databases were searched, and results were summarized using systematic review synthesis. Results: Financial constraints led to a shortage of mechanical ventilators. Furthermore, the pandemic hindered the capacity to avail full packages of personal protective equipment in health facilities and intensive care capacity. The pandemic also affected the delivery of maternal, child and new-born services, prevention, and treatment of childhood illness, including immunization services. Conclusions: The COVID-19 pandemic posed various challenges to the performance of the healthcare system in Ethiopia. It is recommended that policy makers and stakeholders enhance pandemic preparedness and strengthen response capacity by considering the six WHO healthcare system building blocks.

Electronic simulation (e-simulation)—particularly scenario-based e-simulation (SBES)—is an increasingly used, promising educational strategy for global health education that can address gaps in training access, effectiveness, and cost. However, there is little guidance for educators on how to develop an SBES, and guidance is lacking outside the clinical context. Moreover, literature on medical education rarely uses the theoretical basis for e-simulation design and development, including for SBES. Hence, we aim to differentiate and describe the concept, design elements, and theoretical basis of SBES with examples from different topics in global health. In addition to enhancing the understanding of the potential of SBES for global health education, this manuscript also provides practical recommendations for global health educators in designing and developing SBESs based on the existing literature and authors’ experiences. Overall, this manuscript will be useful for global health educators as well as other medical educators seeking to develop an SBES for similar skill sets.

Stroke is a very time-sensitive pathology, and many new solutions target the optimization of prehospital stroke care to improve the stroke management process. In-ambulance telemedicine, defined by live bidirectional audio-video between a patient and a neurologist in a moving ambulance and the automated transfer of vital parameters, is a promising new approach to speed up and improve the quality of acute stroke care. Currently, no evidence exists on the cost effectiveness of in-ambulance telemedicine. We aim to develop a first cost effectiveness model for in-ambulance telemedicine and use this model to estimate the time savings needed before in-ambulance telemedicine becomes cost effective. Current standard stroke care is compared with current standard stroke care supplemented with in-ambulance telemedicine using a cost-utility model measuring costs and quality-adjusted life-years (QALYs) from a health care perspective. We combine a decision tree with a Markov model. Data from the UZ Brussel Stroke Registry (2282 stroke patients) and linked hospital claims data at individual level are combined with literature data to populate the model. A 2-way sensitivity analysis varying both implementation costs and time gain is performed to map the different cost-effective combinations and identify the time gain needed for cost effectiveness and dominance. For several modeled time gains, the cost-effectiveness acceptability curve is calculated and mapped in 1 figure. Under the base-case scenario (implementation cost of US $159,425) and taking a lifetime horizon into account, in-ambulance telemedicine is a cost-effective strategy compared to standard stroke care alone starting from a time gain of 6 minutes. After 12 minutes, in-ambulance telemedicine becomes dominant, and this results in a mean decrease of costs by US -$30 (95% CI -$32 to -$29) per patient with 0.00456 (95% CI 0.00448 to 0.00463) QALYs on average gained per patient. In over 82% of all probabilistic simulations, in-ambulance telemedicine remains under the cost-effectiveness threshold of US $47,747. Our model suggests that in-ambulance telemedicine can be cost effective starting from a time gain of 6 minutes and becomes a dominant strategy after approximately 15 minutes. This indicates that in-ambulance telemedicine has the potential to become a cost-effective intervention assuming time gains in clinical implementations are realized in the future.