Confronting mobile phone signal coverage and helicopter emergency medical service travel time: A geospatial analysis in the northwest macro-region of Paraná State, Brazil.

OBJECTIVE: The aim of this study was to conduct a detailed geospatial analysis of mobile phone signal coverage in the northwest macro-region of Paraná State, Brazil, seeking to identify areas where limitations in coverage may be related to lengthy travel times of the helicopter emergency medical service (HEMS) for the assistance of victims of road traffic injuries (RTIs). METHODS: An observational study was conducted to examine mobile phone signal coverage and HEMS travel times from 2017 to 2021. HEMS travel times were categorized into four groups: T1 (0-15 min), T2 (16-30 min), T3 (31-45 min), and T4 (over 45 min). Empirical Bayesian Kriging was used to map areas with low mobile signal coverage. The Kruskal-Wallis test and Dwass-Steel-Critchlow-Fligner comparative analyses were performed to explore how mobile signal coverage relates to HEMS travel times to RTI locations. RESULTS: There were 470 occurrences of RTIs attended by HEMS, of which 108 (23%) resulted in on-site fatalities. Among these deaths, 47 (26.85%) occurred in areas with low mobile phone signal coverage ("shadow areas"). Low mobile phone signal coverage identified at 175 (37.24%) RTIs locations, was unevenly distributed across the macro-region. The lowest medians of mobile signal quality were predominantly found in areas with HEMS travel times exceeding 30 min, corresponding to signal strength values of -98.44 (T3) and -100.75 (T4) dBm. This scenario represents a challenge for effective communication to activate HEMS. In the multiple comparison analysis among travel time groups, significant differences were observed between T1 and T2 (p < 0.001), T1 and T3 (p < 0.001), T1 and T4 (p < 0.001), and T2 and T3 (p < 0.001), indicating a potential association between lower mobile phone signal coverage and longer HEMS travel times. CONCLUSION: It can be concluded that poor mobile phone signals in remote areas can hinder HEMS activation, potentially delaying the start of treatment for RTIs. Identification of the shadow areas can help communication and health managers in designing and implementing the necessary changes to improve mobile phone signal coverage and consequently reduce delays in the initial response to RTIs.

Designing, development and validation of an app to reduce the response time of the emergency medical services.

INTRODUCTION: Delays in prehospital care attributable to the call-taking process can often be traced back to miscommunication, including uncertainty around the call location. Geolocation applications have the potential to streamline the call-taking process by accurately identifying the caller's location. OBJECTIVE: To develop and validate an application to geolocate emergency calls and compare the response time of calls made via the application with those of conventional calls made to the Brazilian Medical Emergency System (Serviço de Atendimento Médico de Urgência-SAMU). METHODS: This study was conducted in two stages. First, a geolocating application for SAMU emergency calls (CHAMU192) was developed using a mixed methods approach based on design thinking and subsequently validated using the System Usability Scale (SUS). In the second stage, sending time of the geolocation information of the app was compared with the time taken to process information through conventional calls. For this, a hypothetical case control study was conducted with SAMU in the Maringá, Paraná, Brazil. A control group of 350 audio recordings of emergency calls from 2019 was compared to a set of test calls made through the CHAMU192 app. The CHAMU192 group consisted of 201 test calls in Maringá. In test calls, the location was obtained by GPS and sent to the SAMU communication system. Comparative analysis between groups was performed using the Mann-Whitney test. RESULTS: CHAMU192 had a SUS score of 90, corresponding to a "best imaginable" usability rating. The control group had a median response time of 35.67 seconds (26.00-48.12). The response time of the CHAMU192 group was 0.20 (0.15-0.24). CONCLUSION: The use of the CHAMU192 app by emergency medical services could significantly reduce response time. The results demonstrate the potential of app improving the quality and patient outcomes related to the prehospital emergency care services.

AI-based approach for transcribing and classifying unstructured emergency call data: A methodological proposal.

Emergency care-sensitive conditions (ECSCs) require rapid identification and treatment and are responsible for over half of all deaths worldwide. Prehospital emergency care (PEC) can provide rapid treatment and access to definitive care for many ECSCs and can reduce mortality in several different settings. The objective of this study is to propose a method for using artificial intelligence (AI) and machine learning (ML) to transcribe audio, extract, and classify unstructured emergency call data in the Serviço de Atendimento Móvel de Urgência (SAMU) system in southern Brazil. The study used all "1-9-2" calls received in 2019 by the SAMU Novo Norte Emergency Regulation Center (ERC) call center in Maringá, in the Brazilian state of Paraná. The calls were processed through a pipeline using machine learning algorithms, including Automatic Speech Recognition (ASR) models for transcription of audio calls in Portuguese, and a Natural Language Understanding (NLU) classification model. The pipeline was trained and validated using a dataset of labeled calls, which were manually classified by medical students using LabelStudio. The results showed that the AI model was able to accurately transcribe the audio with a Word Error Rate of 42.12% using Wav2Vec 2.0 for ASR transcription of audio calls in Portuguese. Additionally, the NLU classification model had an accuracy of 73.9% in classifying the calls into different categories in a validation subset. The study found that using AI to categorize emergency calls in low- and middle-income countries is largely unexplored, and the applicability of conventional open-source ML models trained on English language datasets is unclear for non-English speaking countries. The study concludes that AI can be used to transcribe audio and extract and classify unstructured emergency call data in an emergency system in southern Brazil as an initial step towards developing a decision-making support tool.

A qualitative assessment of stakeholder perspectives on barriers and facilitators to emergency care delays in Northern Tanzania through the Three Delays.

Introduction: Emergency conditions cause a significant burden of death and disability, particularly in developing countries. Prehospital and Emergency Medical Services (EMS) are largely nonexistent throughout Tanzania and little is known about the community's barriers to accessing emergency care. The objective of this study was to better understand local community stakeholder perspectives on barriers, facilitators, and potential solutions surrounding emergency care in the Kilimanjaro region through the Three Delays Model framework. Methods: A qualitative assessment of local stakeholders was conducted through semi-structured focus group discussions (FGDs) from February to June 2021 with five separate groups: hospital administrators, emergency hospital workers, police personnel, fire brigade personnel, and community health workers. FGDs were conducted in Kiswahili, audio recorded, and translated to English verbatim. Two research analysts separately coded the first two FGDs using both inductive and deductive thematic analysis. A final codebook was then created to analyze the remaining FGDs. Results: A total of 24 participants were interviewed. Thematic analysis revealed that participants identified significant barriers within the Three Delays Model as well as identified an additional delay centered on community members and first aid provision. Perceived delays in the decision to seek care, the first delay, were financial constraints and the lack of community education on emergency conditions. Limited infrastructure and reduced transportation access were thought to contribute to the second delay. Potential barriers to receiving timely appropriate care, the third delay, included upfront payments required by hospitals and emergency department intake delays. Suggested solutions focused on increasing education and improving communication and infrastructure. Conclusion: The findings outline barriers to accessing emergency care from a stakeholder perspective. These themes can support recommendations for further strengthening of the prehospital and emergency care system. Due to logistical constraints, emergency care workers interviewed were all from one hospital and patients were not included.

Built environment influence on the incidence of elderly pedestrian collisions in a medium-large city in southern Brazil: a spatial analysis.

Trauma disproportionately affects vulnerable road users, especially the elderly. We analyzed the spatial distribution of elderly pedestrians struck by vehicles in the urban area of Maringa city, from 2014 to 2018. Hotspots were obtained by kernel density estimation and wavelet analysis. The relationship between spatial relative risks (RR) of elderly run-overs and the built environment was assessed through Qualitative Comparative Analysis (QCA). Incidents were more frequent in the central and southeast regions of the city, where the RR was up to 2.58 times higher. The QCA test found a significant association between elderly pedestrian victims and the presence of traffic lights, medical centers/hospitals, roundabouts and schools. There is an association between higher risk of elderly pedestrians collisions and specific elements of built environments in Maringa, providing fundamental data to help guide public policies to improve urban mobility aimed at protecting vulnerable road users and planning an age-friendly city.

The association of indoor heat exposure with diabetes and respiratory 9-1-1 calls through emergency medical dispatch and services documentation.

BACKGROUND: People with pre-existing medical conditions, who spend a large proportion of their time indoors, are at risk of emergent morbidities from elevated indoor heat exposures. In this study, indoor heat of structures wherein exposed people received Grady Emergency Services based care in Atlanta, GA, U.S., was measured from May to September 2016. METHOD: ology: In this case-control study, analyses were conducted to investigate the effect of indoor heat on the odds of 9-1-1 calls for diabetic (n = 90 cases) and separately, for respiratory (n = 126 cases), conditions versus heat-insensitive emergencies (n = 698 controls). Generalized Additive Models considered both linear and non-linear indoor heat and health outcome associations using thin-plate regression splines. RESULTS: Hotter and more humid indoor conditions were non-linearly associated with an increasing likelihood of receiving emergency care for complications of diabetes and severe respiratory distress. Higher heat indices were associated with increased odds of a diabetes (odds ratio for change from 30 to 31 °C: 1.12, 95% CI: 1.08-1.16) or respiratory 9-1-1 medical call versus control (odds ratio for change from 34 to 35 °C: 1.18, 95% CI: 1.09-1.28) call. Both diabetic and respiratory distress patients were more likely to be African-American and/or have comorbidities. CONCLUSIONS: In this study, the statistical association of indoor heat exposure with emergency morbidities (diabetic, respiratory) was demonstrated. The study also showcased the value and utility of data gathered by emergency medical dispatch and services from inaccessible private indoor sources (i.e., domiciles) for environmental health.

Barriers to accessing follow up care in post-hospitalized trauma patients in Moshi, Tanzania: A mixed methods study.

Disproportionately high injury rates in Sub-Saharan Africa combined with limited access to care in both the acute injury phase and for injury patients requiring continued care after hospital discharge remains a challenge. We aimed to characterize barriers to transportation and access to care in a cohort of post-hospitalized injury patients in Moshi, Tanzania. This was a mixed-methods study of a prospective cohort of trauma registry patients presenting to Kilimanjaro Christian Medical Center between August 2018 and January 2020. We conducted standardized patient/family surveys and in-depth interviews at a 2-week follow up visit after hospital discharge, and focus groups with healthcare providers. Quantitative results were analyzed using descriptive statistics and multivariable logistic regression using R statistical software. Qualitative results were analyzed using thematic analysis through an iterative process using NVivo software. A total of 1,365 patients were enrolled in the trauma registry, with 169 patients followed up at 2 weeks. Over half of patients at follow-up, 101 (59.8%), reported challenges in traveling. The majority of patients were male (80.3%). Difficulty in traveling since injury was associated with female gender (aOR 5.85 [95% CI 1.20-33.59]) and a need for non-family members escorts for travel (aOR 7.10 [95% CI 1.43-41.66]). Those who reported assault or fall as the mechanism of injury as compared to road traffic injury and had health insurance were less likely to report challenges in traveling (aOR 0.19 [95% CI 0.03-0.90]), 0.11 [95% CI 0.01-0.61], 0.14 [95% 0.02-0.80]). Transportation barriers that emerged from qualitative data included inability to use regular means of transportation, financial challenges, physical barriers, rigid compliance to physician orders, access to healthcare, and social support barriers. Our findings demonstrate several areas to address transportation barriers for post-injury patients in Tanzania. Educational interventions such as clarification of doctors' orders of strict bedrest, provision of vouchers to support financial challenges and alternate means of transportation given physical barriers and reliance on social support may address some of these barriers.

Medical transport-associated infection: Review and commentary making a case for its legitimacy.

The purpose of this article is to summarize existing literature about healthcare-associated infection (HAI) in the medical transport environment and to define the term medical transport-associated infection (MTAI) to unify all previous work under a single umbrella with the objective of providing a standardized definition for future research. A review of the literature yielded 34 relevant articles. These studies show that there are pathogens in the ambulance environment, that emergency medical services (EMS) personnel do not regularly comply with hygiene practices, and that patients are potentially affected by HAI as a direct result of ambulance exposure. Prospective studies must be conducted to truly understand the impact that ambulance exposure has on HAIs. MTAI is a subset of HAI and is defined as any infection acquired as a direct effect of exposure in a medical transport setting.

A hypothetical implementation of 'Termination of Resuscitation' protocol for out-of-hospital cardiac arrest.

BACKGROUND: Out-of-hospital cardiac arrests with negligible chance of survival are routinely transported to hospital and many are pronounced dead thereafter. This leads to some potentially avoidable costs. The 'Termination of Resuscitation' protocol allows paramedics to terminate resuscitation efforts onsite for medically futile cases. This study estimates the changes in frequency of costly events that might occur when the protocol is applied to out-of-hospital cardiac arrests, as compared to existing practice. METHODS: We used Singapore data from the Pan-Asian Resuscitation Outcomes Study, from 1 Jan 2014 to 31 Dec 2017. A Markov model was developed to summarise the events that would occur in two scenarios, existing practice and the implementation of a Termination of Resuscitation protocol. The model was evaluated for 10,000 hypothetical patients with a cycle duration of 30 days after having a cardiac arrest. Probabilistic sensitivity analysis accounted for uncertainties in the outcomes: number of urgent transports and emergency treatments, inpatient bed days, and total number of deaths. RESULTS: For every 10,000 patients, existing practice resulted in 1118 (95% Uncertainty Interval 1117 to 1119) additional urgent transports to hospital and subsequent emergency treatments. There were 93 (95% Uncertainty Interval 66 to 120) extra inpatient bed days used, and 3 fewer deaths (95% Uncertainty Interval 2 to 4) in comparison to using the protocol. CONCLUSION: The findings provide some evidence for adopting the Termination of Resuscitation protocol. This policy could lead to a reduction in costs and non-beneficial hospital admissions, however there may be a small increase in the number of avoidable deaths.

Emergency Care Sensitive Conditions in Brazil: A Geographic Information System Approach to Timely Hospital Access.

Background: The benefits of treatment for many conditions are time dependent. The burden of these emergency care sensitive conditions (ECSCs) is especially high in low- and middle-income countries. Our objective was to analyze geospatial trends in ECSCs and characterize regional disparities in access to emergency care in Brazil. Methods: From publicly available datasets, we extracted data on patients assigned an ECSC-related ICD-10 code and on the country's emergency facilities from 2015-2019. Using ArcGIS, OpenStreetMap, and WorldPop, we created catchment areas corresponding to 180 minutes of driving distance from each hospital. We then used ArcGIS to characterize space-time trends in ECSC admissions and to complete an Origin-Destination analysis to determine the path from household to closest hospital. Findings: There were 1362 municipalities flagged as "hot spots," areas with a high volume of ECSCs. Of those, 69.7% were more than 180 minutes (171 km) from the closest emergency facility. These municipalities were primarily located in the states of Minas Gerais, Bahia, Espiríto Santo, Tocantins, and Amapá. In the North region, only 69.1% of the population resided within 180 minutes of an emergency hospital. Interpretations: Significant geographical barriers to accessing emergency care exist in certain areas of Brazil, especially in peri-urban areas and the North region. One limitation of this approach is that geolocation was not possible in some areas and thus we are likely underestimating the burden of inadequate access. Subsequent work should evaluate ECSC mortality data. Funding: This study was funded by the Duke Global Health Institute Artificial Intelligence Pilot Project.