Trauma Incidence and Care in Tanzania Report of Trauma Cases in a Sample of Health Facilities with a Focus on Road Traffic Crash Injuries (2019–2020) May 2021 ©2021 The World Bank 1818 H Street NW, Washington DC 20433 Telephone: 202-473-1000; Internet: www.worldbank.org Some rights reserved. This work is a product of contributions by staff of The World Bank. The findings, interpretations, and conclusions expressed in this work do not necessarily reflect the views of The World Bank, its Board of Executive Directors, or the governments they represent. The World Bank does not guarantee the accuracy of the data included in this work. The boundaries, colors, denominations, and other information shown on any map in this work do not imply any judgment on the part of The World Bank concerning the legal status of any territory or the endorsement or acceptance of such boundaries. Nothing herein shall constitute or be considered to be a limitation upon or waiver of the privileges and immunities of The World Bank, all of which are specifically reserved. Rights and Permissions This work is available under the Creative Commons Attribution 3.0 IGO license (CC BY 3.0 IGO) http://creativecommons.org/ licenses/by/3.0/igo. Under the Creative Commons Attribution license, you are free to copy, distribute, transmit, and adapt this work, including for commercial purposes, under the following conditions: Attribution – Please cite the work as follows: The World Bank, 2021. “Trauma Incidence and Care in Tanzania: Report of Trauma Cases in a Sample of Health Facilities with a Focus on Road Traffic ” World Bank, Washington, DC. License: Creative Commons Attribution Crashes (2019-2020). CC BY 3.0 IGO Translations – If you create a translation of this work, please add the following disclaimer along with the attribution: This translation was not created by The World Bank and should not be considered an official World Bank translation. The World Bank shall not be liable for any content or error in this translation. Adaptations – If you create an adaptation of this work, please add the following disclaimer along with the attribution: This is an adaptation of an original work by The World Bank. Views and opinions expressed in the adaptation are the sole responsibility of the author or authors of the adaptation and are not endorsed by The World Bank. Graphic Design: Circle Graphics, Inc. Table of Contents Acknowledgements 3 Acronyms 4 Executive Summary 5 Introduction 8 Background 11 Trauma Registry Data Collection Process 16 Data Analysis 20 Data Limitations and Lessons Learned 31 for Trauma Registry Data Collection Discussion, Policy Relevance and Next Steps 33 Bibliography 36 Annexes 38 TRAUMA INCIDENCE AND CARE IN TANZANIA 1 Acknowledgements T he Principal Investigators for this research and report are Sveta Milusheva, Development Impact Evaluation Group (DIME), World Bank; Saahil Karpe, DIME, World Bank; Hendry Sawe, Muhimbili University of Health and Allied Sciences; Juma Mfinanga, Muhimbili National Hospital; and Kevin Croke, Harvard School of Public Health. Additional contributors to this report were Inaam Ul Haq, Health, Nutrition, Population (HNP) Practice Group, World Bank; Peter Okwero, HNP Practice Group, World Bank; Kriti Malhotra, DIME, World Bank; Doreen Shango, DIME, World Bank; and Meyhar Mohammed, DIME, World Bank. The team would like to thank the Government of Tanzania – especially Dr. Elias Kwesi and Ms. Yustina Muhaji from the Ministry of Health, Community Development, Gender, Elderly and Children (MoHCDGEC) and Muhimbili University for Allied Sciences (MUHAS) for supporting the data collection necessary for producing these analyses. Additionally, the team thanks the Ministry of Works, Transport and Communications (MoWTC) and the Ministry of Home Affairs (Traffic Police Division) for their participation in this endeavor. They thank Chiku Simbano, Ramadhani Mashoka, Jonna Margaret Bertfelt, as well as the health facility managers, and Trauma Data Coordinators in the field for their excellent research assistance through the baseline data collection. The team also thanks the World Bank Country Office in Tanzania, especially Mara Warwick (Country Director), Preeti Arora (Operations Manager), and the Health sector team members, including Mariam Ally (Senior Economist) and Chiho Suzuki (Senior Health Specialist), for their support with this project; as well as the World Bank project team leads, Gylfi Palsson (Lead Transport Specialist) and Dominic S. Haazen (Lead Health Policy Specialist), for their inputs throughout the implementation. They also appreciate helpful comments from Sudeshna Mitra (Transport Specialist) and Fatima Barry (Health Specialist). The team is grateful to Arianna Legovini (Head of DIME), Aidan Coville (Research Program Manager Climate and Infrastructure, DIME) and Alice Mortlock (Operations Officer, DIME) for their feedback and support. We also thank Tim Bushell, Infrastructure Advisor for FCDO for his continued support throughout the project. This work is part of the ieConnect for Impact program, which links project teams with researchers to develop rigorous and innovative impact evaluations that both substantially improve the evidence- base for policy making and induce global shifts in transport policy. The ieConnect program is a collaboration between the World Bank’s Development Impact Evaluation (DIME) group and the Transport Global Practice. This research has been funded by the Foreign Commonwealth & Development Office (FCDO) of the United Kingdom Government. This work would not have been possible without their support. TRAUMA INCIDENCE AND CARE IN TANZANIA 3 Acronyms  EMS Emergency Medical Services IE Impact Evaluation MUHAS Muhimbili University of Health and Allied Sciences MoHCDGEC Ministry of Health, Community Development, Gender, Elderly and Children MoWTC Ministry of Works, Transport and Communication FCDO Foreign Commonwealth Office of the Government of United Kingdom TR Trauma Registry GDP Gross Domestic Product  TDC Trauma Data Coordinator FC Field Coordinator RA Research Assistant PI Principal Investigator  GCS Glasgow Coma Score AVPU Alert, Verbal, Pain, Unresponsive RTC Road Traffic Crash RTI Road Traffic Injury ICU Intensive Care Unit 4 TRAUMA INCIDENCE AND CARE IN TANZANIA Executive Summary I njuries due to road traffic crashes (RTCs) are one of the major causes of mortality in developing countries, with higher numbers of fatalities in the Sub-Saharan African region and specifically in Tanzania, where fatalities due to RTCs are almost 1.7 times the global rate (WHO, 2018). This critical problem was at the heart of the Government of Tanzania’s decision to adopt the Road Safety Policy, 2009 with the key aim of reducing mortality and morbidity for crash victims. The outcomes for the crash victims could be improved by strengthening emergency medical services (EMS) and better, reliable trauma data. Yet, survey findings from the report The State of EMS in SSA (Sub Saharan Africa) (World Bank, 2021) reveal that very few countries in the Sub-Saharan Africa region have developed systematic and sustainable Emergency Medical Services (EMS) systems at scale.1 1 The report defines EMS as prehospital care that is formalized and provided by emergency care professionals, whereby there is an established entity, agency or system facilitating the coordinated, timely, and safe provision of emergency care and transportation to the most appropriate healthcare facility. TRAUMA INCIDENCE AND CARE IN TANZANIA 5 To address this important area of post-crash care, the Ministry implemented and operational for a period of time in order to of Health, Community Development, Gender, Elderly and evaluate the impacts. Therefore, the goal of this report is to Children (MoHCDGEC) embarked on a pilot project to test the provide insights into the current situation and overall burden implementation of centralized Emergency Medical Services in a of trauma and RTCs in Tanzania. This report leverages the small number of health facilities, as part of a World Bank funded data collected over one year to produce relevant insights project (Southern Africa Trade and Transport Facilitation Program — focused on trauma cases as well as road traffic injuries. These Phase 1 (SATTFP) in Tanzania). The pilot, being implemented by provide valuable information to improve our understanding of the MoHCDGEC, entailed renovation of the emergency care trauma and road traffic injuries in the country, which can help rooms, training of first responders, and establishing an ambulance in the framing and targeting of future policy in the sector. This dispatch system in a sample of 7 pilot health facilities in the report provides a few key findings and key recommendations: A7 Highway (Dar to Morogoro). As of May 2021, certain components of the Pilot have progressed, including collection of baseline ◾ Trauma is concentrated within the economically productive trauma data, progress in renovation of the emergency care rooms, age groups, especially ages 20–35 in the registry data. and training the first responders; while some aspects, such as Across all age groups, a higher share of patients is male. the centralized ambulance dispatch are yet to be implemented Given the impact on this prime working-age group, this finding (see Annex IV for details on status of implementation). is consistent with estimates that injuries due to road traffic crashes affect 3.4% of Tanzania’s GDP annually (WHO, 2015). Given the importance of understanding the current status of ◾ The most common occupations recorded in the trauma registry trauma and post-crash care in Tanzania, collecting high quality data are small business traders (22%), farmers (20%), students and producing rigorous evidence on these topics was critical. It (15%) and professional drivers (10.5%). was equally important to measure the impacts of this pilot project ◾ Road Traffic Crashes (RTCs) are the main cause of trauma, in order to inform potential scale-up to the rest of the country. accounting for 40% of all the cases recorded in the trauma Therefore, the Development Impact Evaluation Group (DIME) at registry, and about half of these RTCs require admission the World Bank partnered with the MoHCDGEC to conduct an in the health facilities. This represents a key concern for impact evaluation of this EMS pilot project, funded by the Foreign both the health and transport authorities. This reflects the Commonwealth & Development Office of the Government of the need for targeted policy efforts towards reducing RTCs and United Kingdom (FCDO). As part of this work and in collaboration improving emergency care response on major corridors with with MoHCDGEC and Muhimbili University of Health and significant movement of goods and people. Allied Sciences (MUHAS), the team set up high quality trauma ◾ Other significant causes of trauma reported include falls (17%), data collection across 13 health facilities located along major blunt trauma (11%) and stabs (13%). roads, including the A7 Highway between Dar es Salaam and ◾ The most reported injuries across all trauma include lacerations Morogoro. The process of setting up the trauma registries (TR) (21%), fractures (16%), soft tissue injuries (16%), contusion provided crucial learning and may help inform trauma registry (11%) and head injuries (11%). While these are also most implementation endeavors for policy makers in similar contexts. reported for RTC trauma, fractures and head injuries make up the highest percentage in this group. Baseline data was collected over a one-year period from ◾ The share of trauma cases is relatively consistent across the September 2019 to October 2020, from 18,553 trauma cases weekdays and weekends. Non-RTC trauma has a peak attended to in 13 health facilities. It provides detailed data on — between 8:00–14:00. In contrast, we see two peaks for patient demographics, trauma causes, care, medical outcomes, RTCs: in the daytime between 8:00 to 13:00 and in the and road traffic injuries from the 13 health facilities that are evening between 18:00 to 22:00. The two peaks for cyclists representative of the diverse scale of administrative structure in are especially pronounced, signaling that these hours may Tanzania, including regional referral hospitals, district hospitals, be particularly dangerous for them. Additionally, the overall health centers and dispensaries. volume of trauma is very low in the early hours between 4 am–6 am, but the share of RTCs exceeds all other causes The data was initially collected with the goal of acting as a of trauma reported during that time. baseline for the pilot EMS project (also referred to as Treatment ◾ More than half of the incoming trauma cases (62%) are or Intervention) that was planned to be implemented in 7 of the treated and discharged on the day of arrival, 29% of patients health facilities. This pilot has not yet been implemented as a are admitted to the ward, ICU, or operating theatre.2 fully functional system; consequently, the impact evaluation has not been completed since it will require the pilot to be fully 2 Seven out of the thirteen facilities have an ICU. ◾ Motorcycle passengers/drivers make up the highest cases and improving outcomes for trauma cases that percent of RTC victims (33%), followed by pedestrians and come to health facilities cyclists. A higher share of pedestrians (53.9%) experience 2. Given motorcycle passengers/drivers make up the highest more severe trauma requiring admission as compared to percentage of RTC patients and motorcycles are also the other road users. Additionally, the majority of pedestrians most likely to hit cyclists or pedestrians, these data point and cyclists crashed with motorcycles. These data point to to a need to develop better regulation and enforcement in a clear need for policies focused on motorcycles as well as relation to motorcycles. non-motorized road users. 3. Further analysis into the cause of delays in reaching a ◾ The time taken to arrive at the health facility post-crash health facility can help to decrease the time for victims to is considered crucial for emergency care. From this data receive healthcare to below one hour. Different causes, we find that it took the crash victims a median time such as lack of transport options versus congestion on the of 69 minutes (interquartile range: 39 mins, 120 mins) road, will require different approaches for improvement. to arrive at the health facility — thus emphasizing the 4. While trauma registries are useful tools to collect information importance of improving the access to emergency post- on trauma patients entering health facilities, there should crash care. be an investment in other data sources as well. In particular, measuring victims’ disabilities in the long run could provide Recommendations important information to understand the long-term burden of trauma. Also, given the role of motorcycles, there should The goal of this report is to present some of the insights that can be further research on motorcycle ownership, how this is be gained from the one year of detailed trauma data collection changing over time, and the types of policies that will be across 13 health facilities in Tanzania in order to encourage further needed to manage motorcycle injuries. use of these data to help inform policymakers on the current 5. A cross-sectional approach and coordination between the situation and help feed into more data-informed decisions. A few Health, Law Enforcement, and the Transport authorities in recommendations that arise from these analyses: Tanzania is needed to collate data from multiple sources in 1. Investment in systematic data collection on trauma cases order to have a more comprehensive picture of road traffic can provide useful information for Transport and Health crashes (combining data on the circumstances of crashes agencies to monitor the patterns and trends of trauma with the health consequences and outcomes of victims) and to develop more targeted and effective policies, and to also develop a multi-sectoral approach to tackling strategies and actions for reducing number of trauma the burden of RTCs. TRAUMA INCIDENCE AND CARE IN TANZANIA 7 Introduction A s per the World Health Organization, approximately 1.35 million people die annually due to road traffic crashes, and it is the eighth leading cause of death globally. Low- and middle-income countries (LMICs) carry the majority of the burden, accounting for 93% of these fatalities (WHO, 2020). In addition, nearly 10–15% of the road crashes result in long term disability in these countries, yet there remains inadequate investment in emergency medical care and road safety (GRSF, 2015). Further, global data shows that people from low socio-economic backgrounds are more likely to be involved in road crashes, and it is the leading cause of death worldwide among those aged 15–29 years — individuals that represent one of the prime working-age groups, significantly affecting the global economy (Boniface et al., 2016; WHO, 2020). Additionally, more than half of the road traffic deaths are among the vulnerable road users (pedestrians, cyclists, motorcyclists). The differences in road traffic deaths among vulnerable road users are stark — while pedestrians and cyclists represent 26% of the deaths worldwide, they account for 44% of deaths in Africa (World Bank, 2021). Evidence from other developing countries such as Iraq and Cambodia show that 8 TRAUMA INCIDENCE AND CARE IN TANZANIA pre-hospital trauma care systems helped reduce the fatality burden strategies that could reduce this burden using region-focused from 40% to 15% based on data from a five-year intervention. data driven evidence. The Tanzania Health Sector Strategic Plan However, SSA represents the largest group of countries (by (2015–2020) outlines the importance of gathering information on population) with no effective pre-hospital emergency care determinants of health outcomes using impact assessments, systems in place, and more data-driven regional evidence to favoring an evidence-based approach to health sector policy improve mortality and morbidity is needed in this domain (World making. Additionally, the Tanzania Development Vision 2025 Bank, 2021). also emphasizes harnessing the role of ICTs (Information, Communications Technology and Information Management While there are several key aspects that require attention to Systems) for the benefit of the people of Tanzania. Developing comprehensively address the rapidly growing road safety issue, a long-term trauma registry for information management and such as the road infrastructure, legislation, road user behavior, to inform the health planning, especially a robust EMS system, and safer vehicles, an emergency care system lies at the core could be key to reducing mortality and morbidity to trauma and of post-crash care response for road safety management road traffic crashes. (WHO 2016; 2018). The relatively high mortality rate due to RTIs in LMICs points towards a weaker healthcare system and weak With the aim of addressing this specific policy problem, the trauma care systems in these countries that are especially Government of Tanzania, with funding support from the World in need of investments in emergency care (Reynolds et  al., Bank, planned to pilot an EMS system along the corridor from 2017). Improvement in trauma care and post-crash recovery Dar-es-Salaam to Ruaha Mbuyuni, as part of the Southern Africa management has also been one of the key pillars of policy focus Trade and Transport Facilitation Project (SATTFP). This pilot had for the Decade of Action for Road Safety 2011–2020, initiated multiple interlinked Treatment components: (a) renovation of emergency units, (b) establishment of an ambulance dispatch by the United Nations. system and (c) training of health care providers along the corridor. Sub-Saharan Africa has one of the highest road traffic death rates The operational pilot aimed to achieve a few key outcomes: in the world, with 26.6 deaths per 100,000 people. In Tanzania, improving care at the site of crashes (via training of the first the World Health Organization estimates 29.2 fatalities per responders); reducing the time from the occurrence of trauma to 100,000 people per year (WHO 2018). Accelerated urbanization when a patient receives medical treatment at a hospital (via the in developing countries, including Tanzania, has led to an alarming ambulance system); and improving care en route to the hospital increase in the rate of road crashes; contributing to a rapidly and at facilities (via paramedic training, facility renovation and growing burden of trauma due to injuries (Ola, 2013); with equipment upgrades at health facilities). It was expected that injury rates being one of the highest worldwide. Despite these the victims of trauma will receive better and more timely high rates of trauma injuries in Tanzania and across the region, medical care and will have better health outcomes such as detailed trauma data that could potentially inform policymakers lower mortality, and lower morbidity/disability. are sparse (Sawe et al., 2017). Better data on trauma, collected An impact evaluation (IE) was designed to evaluate the through trauma registries is a key tool for identifying gaps in effectiveness of this pilot program. One goal of the evaluation injury prevention and severe outcomes for trauma patients. was to understand the role of the EMS system in reducing Evidence from Tanzania and Malawi (Sawe et al. 2017, Mulwafu adverse health outcomes from road traffic crashes (RTCs) through et al 2017) suggests that healthcare facilities in this context are improved access to emergency medical services. A similar EMS not adequately equipped to meet trauma care needs and that Pilot and Impact Evaluation are being implemented in Malawi; there are gaps in coordinated emergency response. A proportion however, the scope of this report is specific to implementation of the fatalities and disability could potentially be prevented and baseline data from Tanzania. The IE, along with the parallel with a well-coordinated emergency medical system (EMS) that’s IE in Malawi, aim at providing some of the first rigorous evidence functional at all stages of post-crash response. Without data in developing country settings. Annex IV provides additional collection and real-time information management, preventive information on the original EMS pilot intervention and planned strategies have also been difficult to implement. Tanzania does evaluation for further context. As of April 2021, the centralized not have large-scale, well-established trauma care and trauma ambulance dispatch system has not yet been implemented; therefore, the report does not focus on the intervention and its data collection — even though trauma injuries are one of the impacts. Instead, the focus of this report is on the second goal leading causes of mortality in the country (Sawe, 2020). of the study, which was to provide high-quality, rigorous data and The lack of trauma registries has posed a challenge and led analytics on the current state of trauma in Tanzania in order to to a gap in understanding emergency care as well as policy support data-informed health and transport policies. TRAUMA INCIDENCE AND CARE IN TANZANIA 9 As part of this work and in collaboration with MoHCDGEC and collected over the course of one year that provides important Muhimbili University, the IE team has implemented a multi-site insights regarding overall trauma and Road Traffic injuries trauma registry across 13 health facilities. The Trauma Form in Tanzania. The report is organized as follows: used for this purpose (paper and a digitized version) included key variables to inform trauma cases, as well as Road Traffic Crashes (a) Executive summary and Road Traffic Injuries. This includes detailed information on RTI (b) Section I provides introduction to the context of trauma variables such as location of road crash, mode of arrival, vehicle and road traffic injuries in the Sub-Saharan Africa region, type, vehicle crashed with, patient’s role on road, and driver particularly Tanzania. behavior, as well as broader indicators such as injury severity, (c) Section II provides background on healthcare in Tanzania broadly, the EMS Pilot Operations, related challenges, and vital signs and patient demographics. The Baseline data collection the planned research study. commenced in September 2019 and ended in October 2020 (d) Section III explains the trauma registry data collection with 18,553 trauma cases collected, out of which nearly half setup, key trauma data variables, and key variables for are RTCs. Data were collected on all trauma cases that entered the assessing road traffic injuries. 13 health facilities. These detailed data from trauma registries in (e) Section IV describes the baseline data and findings from the main economic corridor where movement of goods and people the trauma registry, focused on demographics of patients, are relatively high is a significant step in obtaining evidence that overall trauma information and analysis of road traffic could support policy makers for informing road safety interventions. crashes and injuries. In this report, we discuss the operationalization of the trauma (f) Section V discusses data limitations and challenges. registries to support the EMS pilot impact evaluation and key (g) Section VI summarizes and discusses the policy relevance findings from the data. The goal is to analyse the rich data of the exercise. 10 TRAUMA INCIDENCE AND CARE IN TANZANIA Background T he DIME ieConnect Health Impacts of Emergency Response and Post-Crash Medical Care in Tanzania impact evaluation project was developed to support a new Emergency Medical Services (EMS) pilot planned in Tanzania under the Southern Africa Trade and Transport Facilitation Program (SATTFP). The primary source of data for this IE is a multi-site Trauma Registry, collecting data on trauma cases and outcomes from a series of public health facilities across the country. This report focuses on analyzing the baseline data collected in order to shed light on the current state of trauma and specifically road traffic injuries and care across a set of government health facilities in Tanzania. In this section, we provide some background on the health system in Tanzania broadly, the operational pilot project focused on Emergency Medical Services, and the impact evaluation planned for this operational project to set the stage for the data collection that was conducted and used for producing this report. TRAUMA INCIDENCE AND CARE IN TANZANIA 11 Tanzania Health System National Hospitals The Government health care system in Tanzania is pyramidical; Zonal Level: structured at several administrative levels targeting differing Referral/Consultant Hospitals geographical catchment areas of the country. For mainland Regional Catchment: Tanzania, while the main three levels are National, Regional, Regional Hospitals and District, each district is bifurcated into wards and villages. District Catchment: District Hospitals The health services serve these different catchment areas (see Figure 1). In each administrative catchment level of government Ward Catchment: Health Centres health system, the health facilities above serve as the referral Village health facilities to the immediate level below (Sawe, 2020). Dispensary However, there are a number of health facilities that are specialized and do not fit this Pyramidical hierarchy. Additionally, there are outpatient clinics, general, specialized, and polyclinics, where Figure 1.  Public Health System Pyramid, Tanzania one can avail both specialized and general outpatient services. The administration of the facilities is managed between the Ministry of Health, Community Development, Gender, Elderly local Government authorities. However, the centralized authorities and Children (MoHCDGEC), the President’s Office – Regional manage the primary pool of allocation of health funds, and Administration and Local Government (PO-RALG) and the resources. Different levels of authorities, both centralized and Military. Based on the Tanzania Health Facility Registry (updated decentralized, continue to coordinate with each other to implement 2021), there are 9,773 operating health facilities. Of these, 3858 and improve the access to health care services for the people are private, including 2549 private for-profit health facilities, of Tanzania. 961 health facilities funded by Faith Based Organizations (FBOs), and 75 health facilities funded by Non-Governmental Prior to the launch of the data collection and set-up of the trauma Organizations (NGOs). A total of 6187 health facilities are public. 3 registries, we conducted field visits along with the MoHCDGEC These public health facilities include 5836 health facilities under colleagues to the health facilities that were part of this IE to Local Government Authorities (LGAs), 281 health facilities directly understand the differences between administrative scale of under MoHCDGEC, and 70 health facilities under the Military. The health facilities and to gather observational data on trauma care breakdown across facility types includes 9 national hospitals, infrastructure and staffing based on the scale. In the facilities we 39 regional hospitals, 13 zonal hospitals, 313 district hospitals, visited, we found that dispensaries were generally much smaller 927 health centers, 6962 dispensaries, 1266 specialized clinics in comparison and would have 50 outpatients or less per day on and labs, and 238 clinics. average, and in terms of staffing had 1 clinical officer available in person. Health centers were bigger than a dispensary and Around two-thirds of Tanzanians live in rural areas and are primarily had a larger staff capacity, receiving over 80 outpatients per dependent on the health centers, and dispensaries run by the day on average (with the exception of the newly established LGAs as the first reach solution for basic health services. health centers that received less patients at the time of our For pressing health concerns, especially ones that require visit). Urban area health centers such as Kimara received more hospitalization, the patients get referred to other district and patients.4 Most district and regional hospitals were larger in regional hospitals. These referral flows are generally bottom-up scale compared to both health centers and dispensaries. Most hierarchical, and the patients get referred to national or con­ regional hospitals also had a separate entrance for Emergency, sultative hospitals when needed, or when there is a need a registry maintained to log incoming patients, as well as a post- for specialized care not available in the district or regional health crash care specialist. facilities. Given the main immediate reliance of the communities on health centers, the health system of Tanzania aimed at Based on a recent study conducted of primary health care decentralized administrative structure, with budget allocation, facilities in Tanzania (health centers and dispensaries), it was managerial and decision-making responsibilities vested in the found that 46% had a good physical status, 33% needed minor 4 See Annex V for a detailed breakdown of average patients per facility in each of 3 http://hfrportal.moh.go.tz/index.php?r=facilities/facilitiesList the facilities that were part of this research. 12 TRAUMA INCIDENCE AND CARE IN TANZANIA renovation and 21% were labeled as C to F, meaning they need on a similar road safety component aimed at addressing post- major renovation (Kapologwe et al 2020). They also find that crash care that is part of the parallel SATTFP II project in Malawi. 8.3% of the primary health facilities had been renovated or constructed between 2015 and 2019 and equipped to offer safe The Emergency Medical Services (EMS) operations pilot (the surgery services. Treatment intervention) was designed to be implemented along the A7 highway between Dar es Salaam and Morogoro at Focusing on EMS services specifically, the recent State of 7 health facilities that include 2 hospitals, 3 health centers and Emergency Medical Services in SSA Report put out by the 2 dispensaries. The pilot has the following components: World Bank provides a profile of what is currently available. 1. Renovation of the emergency room in health facilities Policy frameworks pertaining to EMS are limited in scope in 2. Setting up an ambulance dispatch center and activation of many SSA countries, and in Tanzania currently there are not an emergency access telephone number national level operational policies and protocols applicable 3. Training community first responders to all authorized EMS providers, instead each EMS agency or 4. Training paramedics, fire safety professionals, and drivers provider has its own without needing formal authorization, or based on the curriculum developed by MUHAS; and minimum requirements set out as a standard across the country. 5. Procurement and management of ambulances and EMS There are also not formally approved and standardized dispatch equipment. and response procedures laid out for swiftly addressing mass casualty incidents in Tanzania. There are also currently no EMS All components were planned to be implemented simultaneously, vehicle staff requirements. therefore the goal of the impact evaluation was to be able to evaluate the total effect of this combined intervention.5 In terms of EMS training, relative to the situation in SSA, Tanzania is better prepared. There is accreditation of emergency medicine The main parent project (SATTFP) was approved by the World as a medical specialty, regulations requiring completion of an Bank board of directors in November 2013, and the EMS accredited EMS training program, and there is a register of EMS component was initialized in 2018. The EMS Pilot Operations in professionals. Additionally, the Tanzanian Occupational Safety and Tanzania, including the centralized EMS dispatch, were initially Health Authority (under the Ministry of Labor and Employment) planned to be implemented by 30th June 2019. This operational has been conducting first-aid trainings for emergency care to date was extended to 31st December 2020; however, the EMS enable workers to be able to have a basic response to medical operational pilot component has faced several delays, including emergencies. delays owing to COVID-19. The full operational pilot project is yet to be implemented, thus the intended Impact Evaluation could not be completed. The scope of this report entails the analyses and recommendations gathered from the rich Role of EMS Systems and information via the EMS Baseline Data collection from both Project Overview Treatment and Control facilities under the Pilot. As of early 2021, The World Bank has been financing the Southern Africa Trade the renovation of emergency rooms is underway and ambulances and Transport Facilitation Program — Phase 1 (SATTFP) in have been procured, which are important components of the Tanzania, with the objective of facilitating the movement of pilot. Nevertheless, the dispatch center and new emergency goods and people along the North-South Corridor, while supporting number that would bring together the whole system are still improvements in road safety and health services along the in development. Upon full implementation of the EMS pilot, it corridor. The project includes improvement in the physical, could be possible to use these baseline data, combined with institutional, and social infrastructure and the strengthening of end-line data collection, to measure the impact of the pilot post- the management of the corridor. Improvements in the corridor implementation. are expected to lead to higher speeds and reductions in travel time. Without accompanying attention to road safety, such interventions can result in increases in crashes and fatalities from RTCs. To address this possible negative externality and to address the growing RTCs in Tanzania more broadly, the project team worked with the MoHCDGEC to integrate a road safety 5 Since all treatment facilities would receive all components at the same time, it component into this larger transport program. This was modelled is not possible to disentangle the impacts of specific components. TRAUMA INCIDENCE AND CARE IN TANZANIA 13 Tanzania EMS IE Overview inclusively and adequately. One of the selected pilot facilities, Ruaha Dispensary, required extensive renovations and was and Design closed for the duration of the data collection while the facility To encourage investment in post-crash care, it is important for was being constructed; therefore, data collection was set up in policymakers to utilize evidence on the impact of different post- only 6 treatment facilities. crash interventions in achieving the goals of greater access to emergency transport, improved on-scene primary care, reduced Since this was a pilot in a limited number of facilities, it was delays in accessing specialist medical care, and lower morbidity possible for the research team to design an IE, working with and mortality. An IE research project was launched to help provide a set of identified control facilities that are comparable to the some of the first rigorous evidence in a developing country setting project facilities but did not receive the intervention. The team on the impact that this type of emergency medical services planned to use a difference-in-differences empirical design to program can have on trauma outcomes. An important goal of compare the change over time in key outcome indicators in this exercise was to produce high quality data and evidence on the pilot facilities compared to the set of control facilities. It trauma causes, care, and outcomes — a significant data gap in was therefore important for control facilities to be chosen with this context. The lack of data and evidence affects the design of similar key characteristics in order to ensure that the parallel effective policy interventions and prevents Governments from trends assumption would hold. Control facilities were identified understanding what works best and improving future policies — based on location: they also needed to be close to major transit a cycle that perpetuates less effective programs and that the corridors, and they needed to be far enough away from treatment data collection aimed to target. facilities that they would not experience any spillovers6. They were also chosen based on their operational capacity and The 7 treatment health facilities that would receive the EMS caseload, with the goal of identifying facilities that were similar intervention had been selected at the beginning of the in size and scope to the pilot facilities.7 We conducted a field operational project, before the research study began. The pilot health facilities were selected by the MoHCDGEC, keeping 6 Spillovers could arise if facilities are too close together and patients are brought in mind the requirement for the sites to be located on the using the new ambulance dispatch system to a control facility instead of a treatment one. A7 Highway, which was part of the SATTFP parent project. It 7 While one of the treatment facilities was a dispensary, it was decided not to also was ensured that the health facilities were all government include any dispensaries in the control. This was for two reasons. First, the team wanted to increase power to detect impacts by increasing the number of cases facilities that represent diverse administrative structures in that would come in; therefore, it included larger facilities. Second, the dispensary and some of the health centers in the treatment group are larger than their names Tanzania — i.e., a mix of regional referral hospitals, health centers would suggest; therefore, the control facilities chosen were in line with the size of as well as smaller dispensaries to inform the policy outcomes the facilities in the treatment. 14 TRAUMA INCIDENCE AND CARE IN TANZANIA recce (more information available in Annex V) with MoHCDGEC Table 1.  Treatment and Control Health Facilities for the EMS Impact officials to collect data on a set of possible control facilities, Evaluation Study and to guide the selection of sites and implementation of the Treatment Control TR. In the end there were 13 facilities included in this research project (6 treatment facilities and 7 control facilities). The chosen Kimara Health Centre Mvomero District Hospital facilities are listed in Table 1 and mapped in Figure 2. The team Tumbi Regional Hospital Gairo Health Centre worked closely with the MoHCDGEC and local researchers in Chalinze Health Centre Dodoma Regional Hospital Tanzania to set up trauma registry data collection in each health Fulwe Dispensary Mkata Health Centre facility to collect high frequency data on trauma cases coming Morogoro Regional Hospital Korogwe District Hospital to the treatment and control facilities. Mikumi Health Centre Mawenzi Regional Hospital Same District Hospital As mentioned, the EMS pilot project saw some delays in implementation. Therefore, the full impact evaluation piece will Note: See Annex V for details on field visit data for site selection. not be possible until after the pilot has been fully implemented and functional. Nevertheless, one year of high-frequency trauma data has been collected that provides a baseline for this impact evaluation. These detailed data on 18,553 trauma cases in Tanzania also provide a comprehensive view of trauma along these important corridors of the country. Figure 2. Tanzania EMS Pilot and Control Facilities TRAUMA INCIDENCE AND CARE IN TANZANIA 15 Trauma Registry Data Collection Process T his research has involved setting up trauma registries in 13 health facilities in Tanzania. The goal of the data collection was to collect detailed information on every trauma case entering the facilities of interest. The trauma registry collects a range of demographic, health and accident-cause data including: i. Age, gender, education, and occupation of patients ii. Geographic information including residence, region, district, ward and street of trauma, as well as whether the location is urban or rural iii. Injury related information including primary injury description, cause of trauma, seriousness of injury, pain level, location of injury, number of serious injuries iv. Date and time of injury; date and time of arrival in the health facility; and date and time the patient was attended by a Clinician 16 TRAUMA INCIDENCE AND CARE IN TANZANIA v. Mass casualty — This collects information regarding the supporting buy-in within the facility. The RA was brought on number of victims that were injured during the incident board to work on this research project, in some cases full time, vi. Information on the outcome of the trauma and health care and was selected by the health facility leadership. provided to the patient including vital signs, Glasgow coma scale (GCS), AVPU (Alert, Verbal, Pain, Unresponsive) Data was collected in real-time. The clinicians working in score, treatment provided and final outcome. the emergency department of these health facilities and vii. Information on road traffic injuries (RTIs) responsible for attending the patients, were asked to start viii. Mode of Arrival to the health facilities systematically collecting patient data during the process of seeing the patient using paper trauma books designed by “Road traffic crash” is one of the mechanisms causing injuries the research team to collect data for all trauma patients. as categorized in the data that were collected. There are a set of The form used in this book was based on a variation of the specific questions that are only asked under the RTC category: WHO Standardized Clinical Form that had been tested in Tanzania (WHO 2020; Sawe et al 2020b). 8 Each form in the i. Patient’s role on road — This captures the activity that trauma registry book had a carbon paper which allowed for the patient was doing when the road crash occurred. the copy of the information recorded. One hard copy was The expected roles were that the patient was a driver/ sent by the health facility TDCs to MUHAS and a sample passenger/pedestrian or cyclist of these further shared with the World Bank research team ii. Vehicle of patient — This variable captures information for data verification 9 while the other copy remained with regarding the type of vehicle that the patient was using the health facility. The goal was that these systematic paper when s/he got into the crash. records could then be used in the process of providing iii. Crashed with vehicle/object — This asks about the object/ health care so they would remain with patients if they were vehicle that collided with the patient (or the patient’s transferred to other wards and contained the main pieces of vehicle). information collected by doctors in the process of seeing and iv. Safety equipment — This covers the safety equipment treating a patient. This process serves two purposes: (1)  it that the patient was using during the crash. is more sustainable because it relies on existing clinicians collecting data that they typically ask patients without having In this section, we discuss the process of setting up the trauma to duplicate work and (2) it can potentially help improve the registry in the 13 selected facilities. The life cycle had three main provision of healthcare because it ensures that each patient phases — pre-launch preparation, the launch phase, and quality is systematically asked all the same questions and responses checks and process improvement throughout the project’s life are recorded. cycle. The data collection form with all variables is included in Annex II of the report. As soon as the clinician was done seeing and collecting information from the patient on the trauma form, the RA(s), Phase 1: Preparation and followed up on some detailed variables pertaining to Road Traffic Crashes. The RA was also in charge of entering the data Pre-Launch Phase onto a digital platform — Research Electronic Data Capture The focus of the preparation phase was to ensure buy-in (REDCap) — a web-based software developed to capture data from local partners and to secure necessary permissions and for clinical research. This digital data entry was done the same approvals to begin implementation. Finding a local research day on tablets provided to each of the facilities. TDCs were partner and identifying feasible implementation mechanisms, responsible for verifying all the information that was filled in and subsequently finalizing the trauma tool and training the the paper forms and digital forms. staff for data collection were important pillars of this phase of the process. Specific details are outlined in Table 2. Phase 2: Data Collection Each of the 13 facilities had a Trauma Data Coordinator (TDC) and a Research Assistant (RA) that supported data collection. 8 See Annex II for the full trauma form that was used. 9 We conducted periodic quality checks on a sample of hard copies of these forms. The TDC is an existing clinician in the facility, a strategic choice This process included checking for key errors, as well as cross-tallying information aimed at establishing the project within existing systems and input online with the hard copies of these forms. TRAUMA INCIDENCE AND CARE IN TANZANIA 17 Table 2. Setting Up Trauma Registries and Data Collection Process Activity Timeline Description 1  Workshop with Key November 2018 A design workshop was conducted in Dodoma, Tanzania to launch the research. Feedback was sought from a range Government Stakeholders of stakeholders including the MoHCDGEC, Ministry of Works Transport and Communications, as well as the Police (Ministry of Home Affairs) with a focus on post-crash care infrastructure and road safety. 2 Deployment of Field January 2019 DIME deployed a Coordinator to support operationalization and implementation of the IE. The FC was based in Tanzania Coordinator throughout the life cycle of the project and coordinated all operational components of the research in-country. 3 Ethical Clearances in June 2019 The research proposal received ethical clearances from national agencies: COSTECH, and NIMR (National Institute of Tanzania Medical Research) — a necessary precondition to conducting medical research in Tanzania. 4 Regional and Local June 2019 Some of the dispensaries and smaller health facilities in the study were under the purview of the President’s Office, Governance Liaison — Regional Administration and Local Government Tanzania (PO-RALG). Following concurrence of support for the project PORALG from the Director, PO-RALG, the research team was able to begin liaising with relevant staff in the field. 5 Government (Ministry July 2019 The research team received formal permission from the Permanent Secretary of Ministry of Health, Community of Health) Approval and Development, Gender, Elderly and Children (MoHCDGEC) to set up trauma registries. Permission Letter 6 Procurement, Hiring July–August 2019 Muhimbili University of Health and Allied Sciences (MUHAS) was procured through a competitive process to support implementation of data collection in the 13 selected facilities. The Principal Investigators at MUHAS then commenced the process of identifying and hiring Trauma Data Coordinators (TDCs) for each health facility. These were clinicians already embedded in the health facility. To support the TDCs, additional Research Assistants were deployed in the sites. 7 Field Recce and finalization August 2019 With the support and concurrence of MoH (Ministry of Health) as well as PO-RALG, the team conducted field visits to of health sites all the health facilities to assess the availability of relevant infrastructure, progress of the operational pilot, and state of emergency care to inform the final selection of the sites for a representative sample. 8 Finalization of Trauma September 2019 The Trauma Registry Form was finalized through a consultative process with the Ministry of Health and a separate Registry Tool — Paper book section to collect Road Crash variables was added. This form was then printed as trauma books to be deployed in and Digitization health facilities; as well as digitized on REDCap for digital data entry of the variables. 9 Piloting September 2019 The trauma registry form was piloted in Kimara Health Centre, and Tumbi Regional Hospital. The pilot provided operational feedback on the use of the form in a health facility and allowed the team to improve it prior to deployment. 10 Training September 2019 The first training — targeted at all the TDCs and RAs — was organized in MUHAS, Dar es Salaam. They were trained on (1) the context of impact evaluation, (2) key trauma vocabulary and measurements, and (3) the use of the trauma registry paper form and the REDCap tool via the tablets. All TDC and RAs were also trained on research ethics recommended by the local IRB (Institutional Review Board). MUHAS led the training in Swahili, while the World Bank team supported and trained on other components relevant for RTC (Road Traffic Crash) indicators in the Trauma registry form. 11 Launch of Data Collection October 2019 The trauma registry books and tablets with the REDCap (Research Electronic Data Capture) form were deployed, and data collection began in all 13 facilities. 12 Monitoring and Quality October 2019– A data dashboard was set up and shared with TDCs; weekly calls were organized to discuss progress at the facility Feedback October 2020 level; data reconciliation was carried out to ensure high capture rates; and high frequency checks were implemented to ensure strong data quality. 13 Refresher Training and January 2020 A training was conducted with all TDCs and RAs to introduce changes to the trauma registry book aimed at improving redeployment data quality. The form was adjusted based on lessons learned and data collected using the existing form. 13 COVID19 and NIMR April 2020 RAs transitioned to working from home to minimize risk of COVID-19 transmission. Guideline 14 Closing of Baseline Data October 2020 With 18,586 recorded cases, baseline data collection was closed. In 3 facilities, Mkata, Chalinze and Fulwe, staff Collection elected to continue using the trauma registry books as part of their standard processes. 15 Debrief Process November 2020 Debrief calls were organized with staff from all the health facilities to understand their experience, achievements, and challenges during the life of the project. 18 TRAUMA INCIDENCE AND CARE IN TANZANIA Phase 3: Data Quality Monitoring and emergency and trauma care in their respective health facilities and could support in resource and personnel planning based on Improving Processes Over Time weekly trends. The baseline data collection was conducted for The incoming data were regularly monitored for logical one year, from September 2019 until October 2020. inconsistencies, missing data, outliers, as well as the capture rate per health site. The World Bank team established a system Data collection was affected by COVID-19, which necessitated of weekly checks on incoming data and the most important the RAs to work remotely from home effective from April outliers and inconsistencies were discussed each week with the 2020. This affected the quality and quantity of data received. TDCs and RAs to give them feedback on progress and address The clinicians were unable to enter all the data without the challenges with some of the variables (Figure  3 displays the assistance of the RAs, especially when the number of in-coming communication flow across the research team). Additionally, patients was high. Additionally, more observations for death at a weekly Dashboard (which included completion, number of the crash scene were missing since they would go straight to cases, a few demographic statistics, and missing data) was the mortuary without passing through the Emergency Medical shared with the TDCs and RAs. This Dashboard was electronic; Department. There were also delays in getting data filled on the however, the WB team converted the information into visually digital forms since the books had to be brought to the RAs who easy, readable and accessible PDF files, which were then further entered the data at home. shared with the Trauma Data Coordinators and Clinicians in each health facility on a biweekly basis. The dashboard was a useful Details on timelines and specifics in each step of the process tool for the TDC and health facility manager to understand are outlined in Table 2. The World Bank MUHAS Government Health Facilities Pls + FC Project Coordinator Part Time Trauma Data Coordinators Facility Managers Biweekly Calls Full-Time Research Assistants MUHAS Pls Regional Referral Admin. Figure 3.  Communication Structure for Trauma Registry Baseline Data Collection Note: PIs = Principal Investigators in the impact evaluation study; FC = Field Coordinator deployed by the World Bank. Part Time Trauma Clinicians who were already working in these health facilities and hired by the Government of Tanzania were employed as data coordinators to oversee the trauma data collection in the facility. The Research Assistants were employed in these sites specifically to support the EMS impact evaluation baseline data collection. TRAUMA INCIDENCE AND CARE IN TANZANIA 19 Data Analysis F rom September 2019–October 2020, the trauma registry collected 18,553 trauma cases across all facilities, both treatment and control. Figure 4 shows the distribution of trauma cases across all the months of data collection. It is important to note that the months of September 2019 and October 2020 are excluded from this figure since the data was collected only for 13 and 23 days respectively in these months. The figure also shows the number of RTC cases out of the total each month, as we will focus much of the analysis on these cases, which contribute 40% to the total trauma. The following sections cover analysis of the trauma registry data in terms of demography, causes of trauma, nature of injuries related to trauma, and final trauma outcome of patients. These are important for understanding the current situation of trauma in Tanzania and can support policymakers with identifying policies to prevent trauma as well as to provide insights for how to improve trauma care and outcomes. The analyses do not make a distinction between treatment and control 20 TRAUMA INCIDENCE AND CARE IN TANZANIA Oct-2019 14 554 Demographic Description Nov-2019 6 614 of Trauma Patients Dec-2019 19 710 Jan-2020 11 618 Figure  5a. shows the distribution of all trauma patients by Feb-2020 9 568 age and gender. As is common in many countries, trauma Mar-2020 27 704 is concentrated within the economically productive age Apr-2020 8 408 groups, especially ages 20–35 years. Across all age groups, a May-2020 11 385 higher share of admitted patients are male. Older females (≥ Jun-2020 16 550 50 years), have a higher share of admissions than females in Jul-2020 12 594 other age groups and a comparable share to men ≥ 50 years. Aug-2020 14 596 Looking at the age and gender distribution for RTC, Figure 5b Sep-2020 12 544 demonstrates an even starker gap between men and women. 0 500 1,000 1,500 2,000 Overall, 80% of all RTC victims are males and 20% are females. RTC with fatality RTC All other trauma Not only are males the majority of RTC victims, but they also have a higher probability of being admitted as compared to Figure 4. Trauma Cases per Month female victims (50% as compared to 42%). Males between the Note: Each bar represents the total trauma cases recorded each month of the primary working age group of 20–35 years make up the bulk of data collection. The shaded regions represent the number of RTC cases and the darkest bar represents the fatalities due to RTC each month respectively. RTC cases (54%). One of the other big differences is that the 0–15 age group makes up a large part of all trauma cases, but they are a relatively smaller number of RTC cases. facilities in this report because the focus of this report is not The four most common occupations observed in the trauma on a comparison between these two groups of facilities since registry are farmer, student, business trader and driver. Within all data is collected before there is any intervention. Annex I these, there is heterogeneity in the highest level of education includes some figures breaking down the data by treatment completed (Figure  6). 80% of farmers have completed up and control facilities to demonstrate the patterns across the to primary education and 11% have no education. The most two groups. common occupations recorded for RTC patients are also small 5a: Gender and Age Distribution of All Trauma Patients 5b: Gender and Age Distribution of RTC Patients ≥50 years ≥50 years 45−50 years 45−50 years 40−45 years 40−45 years 35−40 years 35−40 years 30−35 years 30−35 years Age Age 25−30 years 25−30 years 20−25 years 20−25 years 15−20 years 15−20 years 0−15 years 0−15 years 2,000 1,500 1,000 500 0 500 1,000 1,500 2,000 2,500 400 200 0 200 400 600 800 1,000 1,200 1,400 Total trauma: Male Admitted trauma: Male Total RTC: Male Admitted RTC: Male Total trauma: Female Admitted trauma: Female Total RTC: Female Admitted RTC: Female Total males: 13,193 Total RTC from males: 5,862 Total males admitted: 5,219 Total males admitted from RTC: 2,963 Total females: 5,272 Total RTC from females: 1,529 Total females admitted: 1,630 Total females admitted from RTC: 642 Admitted includes admitted/died in ED/referred to other facilities Admitted includes admitted/died in ED/referred to other facilities Figure 5.  Gender and Age Distribution Note: This figure represents the population pyramid of all trauma patients (on the left) and road traffic crash patients (on the right). To the right of zero is the age distribution of males in the trauma registry. The shaded portion represents the number of males from each age group that were admitted to the facility due to trauma and RTC respectively. To the left of zero, is the age distribution of females in the trauma registry, with the shaded portion representing the number of females from each age group that were admitted. TRAUMA INCIDENCE AND CARE IN TANZANIA 21 business or traders (25%), drivers (21%), farmers (18%) and students (11%), with the main difference being the larger Manual laborer 4.74 percent that describe their profession as driver. Office worker 1.20 Military 0.73 Amongst the 31 districts recorded in the trauma registry Farmer 21.45 surrounding the facilities, Ubungo (20%), Moshi urban (10%), Morogoro urban (16%), Kibaha urban (11%) and Same (6%) Mining 0.02 collectively make up 60% of the incoming trauma cases Small Business/trader 23.88 (Figure  7a). Figure  7b shows the percentage share of RTC Driver 10.98 from all reported trauma cases for the districts surrounding Craftsman 1.42 the facilities. Temeke (81%), Kigamboni (77%), Ilala (82%), Health worker 0.25 Kilombero (75%), Kinondoni (70%), Siha (57%), Dodoma (57%), Unemployed 2.78 Rombo (54%), Same (53.08%), Kibaha (50%), and Kisarawe Retired 0.33 (63%) have more than half of their recorded trauma as RTC. It should be noted that for some of these districts, especially Housewife 3.24 those that are further away from one of the health facilities Student 16.44 where data was recorded, the denominator (total number of Other 12.54 trauma cases) can be small (see Annex III for a breakdown of number of trauma cases, RTC cases and number of admitted 0 5 10 15 20 25 Percent cases by district). No formal education Primary school Secondary or higher Figure 6.  Patient Occupation for All Trauma Cases Note: This figure shows the frequency distribution of different occupations as recorded in the trauma registry. The fill within the bar represents the share of patients with no formal education, primary, and secondary or higher education for each occupation. 7a: Trauma Cases by District 7b: RTC Share of Trauma by District Share of Road Traffic Crashes (as % of total trauma) Health Facilities by district Number of trauma cases 80 by district 70 60 2000 50 1500 40 30 1000 500 Health Facilities Figure 7. Trauma and RTC Share by District Note: This map shows the total number of trauma cases recorded at the district Note: This map shows road traffic crashes as a percentage share of total trauma in level. The colored region shows 30 districts surrounding the facilities (represented the trauma registry at the district level. The colored region represents 30 districts by the dots) which were recorded in the trauma registry. Darker shade represents surrounding the facilities (seen in yellow dots) which were recorded in the trauma higher number of recorded cases. The grey portion represents all other districts registry. Darker shade represents a higher share of road traffic crashes recorded in Tanzania which were not recorded in the data. The dashed black lines represent in each district. The grey portion refers to other districts in Tanzania which were major highways and primary roads in Tanzania. not recorded in the trauma registry. The dashed black lines represent the highways and other primary roads in Tanzania. 22 TRAUMA INCIDENCE AND CARE IN TANZANIA Road traffic crash 40.40 Road traffic crash 48.63 Stab/cut 13.14 Fall 24.17 Fall 17.60 Blunt trauma 6.23 Blunt trauma 10.99 Stab/cut 6.84 Bite 4.84 Other 5.10 Other 5.70 Bite 2.24 Hit by falling object 2.96 Hit by falling object 1.51 Unknown 1.97 Unknown 1.23 Burn 2.40 Burn 4.04 0 10 20 30 40 50 60 70 80 90 100 0 10 20 30 40 50 60 70 80 90 100 Percent of trauma cases Percent of trauma cases Discharged Admitted/Died in ED/Referred Discharged Admitted/Died in ED/Referred Other includes: Sexual assault, drowning, suffocation, gunshot, poisoning Other includes: Sexual assault, drowning, suffocation, gunshot, poisoning Figure 8a. Trauma Cause for All Trauma Cases Figure 8b. Trauma Cause for Referred Trauma Cases Note: This figure shows the different causes of trauma for all incoming trauma cases (on the left panel) and only for referral cases (on the right panel). Each bar represents the percentage frequency of the cause of trauma as observed in the trauma registry. The light blue portion represents the share of trauma cases from each cause that led to admission of the patient in the facility. Admission includes patients being admitted to ward, ICU, operating theatre, referred to another hospital, or if the patient died in the emergency department. Causes of Trauma and facility. 85% of cases brought in by ambulance were referrals from other health facilities, demonstrating that currently in our Types of Injury study area ambulances are almost never used for transporting Out of 18,553 trauma cases recorded in the emergency room patients from the scene of the trauma. Figure  9 shows the of facilities, 98.9% (18,357) arrived at a facility alive, and 1.02% share of all the modes of transport used to arrive at the facility (189) died at the scene of trauma and/or in transit to the facility. 10 and the share of cases admitted by each mode. The relative share Road Traffic Crashes (RTCs) make up 40% of all the trauma, about half of which require admission or referral. The other major causes of trauma are stabbing, falls and blunt Motorcycle 38.97 trauma (Figure 8a). 9.67% (1,794) of all the incoming cases were Walk in 14.22 referred from other facilities, 48% of these referrals comprised of road traffic crashes (Figure 8b). 64% (1,150) of the referred Tricycle (bajaj) 15.44 trauma cases were admitted to the facility, demonstrating the Mini bus 10.48 more serious nature of referred cases. 46% of all trauma injuries Car (private or taxi) 16.54 have happened on the road. Over 70% of cases are unintentional or accidental, 9% of trauma cases are reported as intentional Other 3.65 (assault), with 57% of these cases coming from blunt force Ambulance 0.69 trauma and 27% from stabbing cases. 0 10 20 30 40 50 60 70 80 90 100 The most common mode of arrival to the facility was recorded Percent of trauma cases as motorcycles (37%), followed by cars (16%) and tricycle (15%). Discharged Admitted/Died in ED/Referred About 3% of trauma cases used an ambulance to reach the Other includes: bicycle, bus, truck Figure 9.  Mode of Transport for Arrival to Facility for All Trauma Cases Note: This figure shows the different modes of transport (on the vertical axis) and the share of trauma cases for each mode (on the horizontal axis). The light blue 10 It is important to note that the number of cases that were brought in having area represents the share of trauma cases that were sent home the same day died at the scene or in transit is likely higher because many of these cases may and the dark blue represents the share of cases that were admitted. This excludes have been brought directly to a morgue, where trauma data was not collected. cases that were referred from other facilities. TRAUMA INCIDENCE AND CARE IN TANZANIA 23 10a: Mode of Transport 10b: Median Time to Arrival Ambulance Ambulance 1.44 (99 min) Car Car (private/taxi) 34.45 (76 min) Motorcycle Motorcycle 25.81 (69 min) Other Other 6.06 (67 min) Bicycle/tricycle Bicycle/tricycle 23.67 (69 min) Bus/minibus Bus/minibus 8.57 (87 min) 0 5 10 15 20 25 30 35 0 40 80 120 160 200 240 280 320 Percent of admitted/referred/died RTC Duration of arrival (in minutes) to facility after RTC Excludes cases that were referred from other facilities Excludes cases that were referred from other facilities Other includes walking, truck and other unspecified Figure 10.  Mode of Transport and Median Time to Arrival for Admitted/Died in ED/Referred RTC Patients Note: This graph shows the different modes of transport for RTC patients that were admitted/died in ED/referred. All patients that were referrals from other facilities have been excluded. On the left, the bars represent the percentage share of patients using each mode. On the right, the plot shows the distribution of arrival times in minutes with the line in the middle of each box representing the median time taken for each mode of transport to reach the facility. of admitted cases is recorded to be more from cases coming in Figure  11 shows the distribution of trauma across days of by car, motorcycle, and tricycle. Figure 10 demonstrates mode the week and times within a day. Trauma cases are relatively of arrival for RTC patients, whereby, 34% of them arrive at the consistent across days of the week, though there is a slight facility in a car or taxi with a median time of arrival of 76 minutes, decrease on weekends and an analogous increase on Mondays 25% in motorcycle with a median time to arrival of 69 minutes, as potentially less urgent cases that may have occurred over 23% in bicycle with a median time to arrival of 69 minutes. the weekend wait until Monday to go to a facility. RTC cases 8.5 % of patients use public transport (bus and minibus), which are similarly mostly consistent across days of the week with the takes a median time of 87 minutes (1 hour 27 minutes). Fewer main difference being an increase on Sundays, that is not seen patients arrive in an ambulance (1.44%), which has a median time in trauma broadly, as well as slightly higher values on Fridays of arrival of 99 minutes. (Figure 12a). 11a: Day of the Week 11b: Time of the Day 16.01 0.10 14.87 14.91 All other trauma 15 14.10 14.15 13.05 12.91 0.08 Percent of total trauma cases Distribution of hour of trauma 10 0.06 RTC 0.04 5 0.02 0 0 Monday Tuesday Wednesday Thursday Friday Saturday Sunday 0 2 4 6 8 10 12 14 16 18 20 22 24 All other trauma RTC Hour Figure 11.  Day and Time of Trauma Note: This panel shows the distribution of trauma across days of the week and times of the day. On the left, each bar represents the percentage of total trauma cases on the given day (on x-axis). The light portion highlights the share of RTC and the dark area highlights the share of all other causes of trauma. On the right, is the distribution of road traffic crashes (light line) and all other trauma (dark line) across all hours in a day. The x-axis represents hours of the day and y-axis represents the density of trauma cases for every hour of the day. 24 TRAUMA INCIDENCE AND CARE IN TANZANIA 12a: Day of the Week 12b: Time of the Day 16.01 0.08 14.87 14.91 15 14.10 14.15 13.05 12.91 0.06 Density of RTC 10.25 Percent of RTC 10 9.25 9.66 8.81 9.16 0.04 7.89 7.78 0.02 5 0 0 2 4 6 8 10 12 14 16 18 20 22 24 0 Monday Tuesday Wednesday Thursday Friday Saturday Sunday Hour Non-serious RTC Serious RTC Driver Pedestrian Passenger Cyclist Figure 12.  Day and Density of RTC by Hour of the Day Note: This panel shows the distribution of trauma across days of the week and time of day for road traffic crash patients. The figure on the left breaks down the percent of trauma into non-serious (dark portion) and serious (light portion). A road traffic crash is considered serious if the GCS of the patient is at or below 8 or if they are admitted to the facility (includes ward, operation theatre, ICU, died in ED, and referred to another facility). On the right, each line represents the density of RTC for a given road user for different hours of the day. Analyzing the distribution of cases across times in the day, non- RTC trauma cases have a single peak shape, with the majority of cases occurring in the first half of the day, and specifically in the hours between 8:00–14:00. RTC cases, on the other hand, have a two-peak trend, with higher case load between 8:00–13:00 and again between 18:00–22:00. The density of trauma from crashes is also higher than other trauma in the early hours of the day between 4:00–6:00, which could be due to low visibility and speeding among other reasons. Figure 12b breaks down the density of RTC across different times during the day for each type of road user. The two peaks for cyclists are especially pronounced, signaling that rush hours may be particularly dangerous for them. The trauma registry also records details on injuries and severity of injuries by using the Glasgow Coma Scale (GCS), vital signs and Alert Verbal Pain Unresponsive (AVPU) scores. Figure 13a shows the different types of injuries recorded in the trauma registry categorized by serious and non-serious for each type of injury. Serious trauma cases are all admitted trauma (admitted to ICU, admitted to ward, admitted to operating theatre, died in ED) or cases where the GCS of the patient is less than 8. Fractures and head injuries have a higher share of severe trauma relative to other injuries, indicating higher need for hospital care for these types of injuries. Details about the nature of injury are recorded only for one primary injury of the patient (only 4% of trauma patients have two or more serious injuries). Focusing on injuries for RTC patients, Figure 13b shows that fractures, head injuries and soft tissue are the most common. Not only are more of the injuries fractures and head injuries, but these are also more TRAUMA INCIDENCE AND CARE IN TANZANIA 25 13a: All Trauma Cases 13b: Road Traffic Crash Cases Fracture 16.60 Fracture 21.98 Head injury 11.50 Head injury 19.51 Laceration (cut) 21.59 Laceration (cut) 16.38 Other 7.51 Contusion (bruise) 15.48 Soft tissue injury 16.44 Other 7.11 Burn 3.61 Soft tissue injury 16.49 Contusion (bruise) 11.20 Dislocation 1.97 Dislocation 2.41 Penetrating wound/stab 0.73 Bite 6.52 Bite 0.32 Penetrating wound/stab 2.61 Burn 0.03 0 5 10 15 20 0 5 10 15 20 Percent Percent Serious injury Non-serious injury Serious injury Non-serious injury Other includes: drowning, poisoning, spine injury, foreign body, amputation, gunshot wounds Other includes: drowning, poisoning, spine injury, foreign body, amputation, gunshot wounds Figure 13. Type of Injury Note:This bar graph shows the different types of injuries in the trauma registry for all trauma (on the left) and only road traffic crash cases (on the right). The y-axis shows the percentage of the given injury out of all the trauma cases reported in the trauma registry. The dark blue region represents the share of serious trauma for each reported injury category. Serious trauma cases are all admitted trauma (admitted to ICU, admitted to ward, admitted to operating theatre, died) or cases where the GCS of the patient is less than 8. The variable used for recording type of injuries has 9,632/18,553 (51%) observations missing because they were not recorded in a way conducive to analysis. These results displayed are from the remaining observations only. severe with a higher share of injuries requiring admission. Other Figure 15a shows a panel of different road users and vehicles common injuries for RTCs are soft tissue injuries, contusion, and involved in a road traffic crash. Motorcyclist passengers/drivers lacerations. Figure 14a shows the treatment given by means of make up one third of all victims, followed by cyclists (20%) fluids or medication. Analgesia, antibiotics, tetanus and IVF form and pedestrians (22%). A higher share of pedestrians (53.9%) the large majority of the treatment plan. The percent of cases experience more severe trauma requiring admission as compared that receive these four medications/fluids is broken down for the to other road users (Figure 15a). With 50% of RTC coming from five most common injuries in Figure 14b. drivers and passengers, Figure 15b shows the different vehicles 14a: All Injuries 14b: Most Common Treatment for the Top Five Injuries 100 Tetanus 27.39 80 Sedation and paralytics 4.99 Percent of treatment Other 9.96 60 None 5.18 40 IVF 23.54 20 Antibiotics 59.98 Analgesia 90.31 0 Contusion Laceration Fracture Soft tissue Head injury (bruise) (cut) injury 0 20 40 60 80 100 Percent of treatment % Analgesia % Antibiotics % Tetanus % IVF Figure 14. Types of Treatment Note: This panel shows the different types of treatments in terms of fluids and medications provided. The percentages do not sum up to 100% because there were multiple treatments provided to patients. The figures show the percentage of each treatment applied mutually exclusive of other applied treatments. The figure on the left is for all cases. The figure on the right focuses on the five most common injury types and looks at the four main treatments provided. 26 TRAUMA INCIDENCE AND CARE IN TANZANIA 15a: Role on Road 15b: Type of Vehicle Motorcycle (driver-pass) 32.87 Motorcycle 67.91 Cyclist 20.12 Car 15.71 Pedestrian 22.00 Other 10.21 Bus/minibus 15.37 Bus (driver-pass) 7.38 Car (driver-pass) 7.42 Other 1.02 0 10 20 30 0 10 20 30 40 50 60 70 Percent Percent Discharged Admitted/Died in ED/Referred Driver Passenger (driver-pass): Driver and passenger Other includes trucks Figure 15.  Role on Road and Type of Vehicle for RTC Cases Note: This figure displays the role on the road for road traffic crash victims. The Note: This graph shows the different types of vehicle for RTC victims who were vertical axis represents the different road users of vehicles recorded in the trauma drivers or passengers. Each bar shows the percentage of vehicle type observed in registry. The horizontal axis represents the percentage of road users for incoming the trauma registry and the share of drivers and passengers for each vehicle. The RTC. For each road user, the shaded portion shows the share of road users that light blue area represents the share of passengers for each vehicle. were discharged from the facility and sent home the same day. the patient was in, as recorded in the trauma registry. 68% of crashed mostly with other motorcycles, although around a drivers or passengers were reported to be on motorcycles at the quarter crashed with cars. Though drivers and passengers of time of crash, followed by car (15%) and bus (14%). trucks make up a small share of RTC victims, over a third of them Figure 16 shows the different types of crashes for each road have crashed with nothing or a non-moving object. 28% of user. We find that the non-motorized road users (pedestrians pedestrians get a fracture and 20% get a head injury, indicating and cyclists) are hit more by motorcycles than cars. Motorcycle that over 40% suffer from injuries that require long term care drivers and passengers, who make up 33% of RTC victims, (Figure 17). 100 75 Percent 50 25 0 Pedestrian Cyclist Motorcycle Car Bus Truck Other (22%) (20%) (driver-pass) (driver-pass) (driver-pass) (driver-pass) (10%) (33%) (7%) (7%) (0.24%) Car/private vehicle Truck Public transit/bus Bicycle/tricycle Motorcycle Non-moving object Unknown Other Nothing Figure 16.  Crashed With Note: This graph shows the different road users (on the horizontal axis) and percentage frequency of objects they crashed with (on the vertical axis). Next to each road user in parentheses is their percentage representation in the trauma registry data. Each block making a bar represents the share of objects crashed with out of all the road traffic crashes recorded for the given road user. TRAUMA INCIDENCE AND CARE IN TANZANIA 27 100 75 Percent 50 25 0 Pedestrian Cyclist Motorcycle Car Bus Other (22%) (20%) (driver-pass) (driver-pass) (driver-pass) (10%) (32%) (7%) (7%) Contusion Laceration Fracture Soft tissue injury Head injury Other Other includes burn, penetrating wound, dislocation Figure 17.  Injury Type by Road User Note: The above figure shows the different road users (on the horizontal axis) and the share of types of injuries recorded in the trauma registry from each of them (on the vertical axis). The legend shows all the different types of injuries recorded in the trauma registry. The trauma registry also recorded any substance use and shows the share of patients that wore a seatbelt or helmet. There presence of safety equipment for RTC patients. The trauma seems to be a slightly lower rate of admittance for those that registry recorded 17% of drivers and passengers of cars and wore a seatbelt or helmet, though it could also be that those that trucks wore a seatbelt and 37% of motorcyclists had a helmet use safety equipment are also less risky on the road and therefore on. Alcohol was recorded for 2.6% of RTC patients. Figure 18 less likely to be in a serious crash. 18a: Seatbelt 18b: Helmet 100.00 100.00 100.00 100.00 100 100 80 80 Percent of frequency Percent of frequency 60 60 48.14 47.92 49.87 46.12 40 40 20 20 0 0 Seatbelt-No Seatbelt-Yes Helmet-No Helmet-Yes Admitted/Died in ED/Referred Not admitted Admitted/Died in ED/Referred Not admitted Figure 18.  Safety Equipment and Hospital Admission Note: On the left, each bar shows the share of drivers/passengers of cars and trucks that wore a seatbelt or had any safety equipment and those that did not answer the question. No response is assumed to be representing no safety equipment. On the right each bar shows the motorcyclists that had responded to wearing a helmet or any other safety equipment. In both figures, the dark shaded portion represents the share of patients from each category who were admitted/died in ED/referred to a different facility. 17% of drivers and passengers of cars and trucks wore a seatbelt and 37% of motorcyclists had a helmet on. 28 TRAUMA INCIDENCE AND CARE IN TANZANIA Trauma Outcomes Discharged home 62.5 The trauma registry records the final outcome of the hospital Admitted to ward 28.2 visit, following treatment. Over 60% of the trauma patients are Transferred to treated and sent home on the same day they come in (Figure 19). 8.0 another facility 29% of the patients are admitted to ward/OT/ICU, with a small Admitted to OT 0.6 percentage admitted to the ICU (0.1%) and operating theatre (0.62%). RTCs not only make up the largest portion of trauma, Died at ED 0.5 but they also represent more severe trauma. Only 50% (3,708) of Admitted to ICU 0.1 all RTCs were treated and sent home the same day, 36% (2,663) were admitted to ward, 0.16% (12) were admitted to the ICU, 0 10 20 30 40 50 60 1% (80) were admitted to operating theatre, and 10% (785) were Percent transferred to another facility. 1% (73) of RTC cases have died RTA Fall Stab All other trauma in the casualty department. Figure 19.  Outcome of Trauma Figure  20 shows the distributions of AVPU and GCS scores Note: This figure represents the outcome of trauma patients on the day they arrived at the facility. Each bar represents the percentage of reported outcomes out of for RTC patients. For RTC cases where the patient came in as total trauma cases. The colored portion shows shares of RTC, falls, stabs and all unresponsive or responding only to voice, a higher share of those other trauma for each outcome. patients was admitted to the ward, ICU, or operating theatre. The team also collected vital signs and trauma scores while reassessing the patient’s overall condition after spending 24 hours by phone, 572 (5%) had been referred to another facility and in the facility. Figure  21 compares the GCS score for the could be contacted by phone, 100 (1%) had died and 1,315 (13%) patients admitted across the days spent in the hospital. For most patients could not be reached. patients, the score increases, suggesting improvement in health condition over 24 hours. For a 30-day follow up, out of a total of 9,178 patients contacted 7,587 (82%) patients had been discharged and were traceable Based on the trauma outcomes, the team conducted follow up by phone and 1,461 (15%) patients could not be traced. A small phone calls at 24 hours and 30-days intervals since they arrived fraction of 11 (0.1%) patients were still in the facility showing at the facility. For the 24-hour outcomes, a total 9,813 patients the need for prolonged hospital care for severe trauma. The were contacted. 2,190 (22%) of these patients were still in the number of patients that died increased only by 2 patients health facility, 5,636 (57%) were discharged and were reachable between 24-hour and 30-day follow up. TRAUMA INCIDENCE AND CARE IN TANZANIA 29 20a: Percentage GCS scale 20b. AVPU scores 65.63 75.50 14.52 9.87 13.49 8.63 3.95 2.37 0.82 0.31 0.80 1.79 0.97 1.35 ≤6 7 8 9 10 11 12 13 14 15 Alert (A) Responds to voice (V) Responds to pain (P) Unresponsive (U) Not admitted Admitted/Died in ED/Referred Not admitted Admitted/Died in ED/Referred Figure 20.  AVPU and GCS Scores for RTC Patients Note: These figures show the GCS scale and AVPU score of RTC patients. On the left, each bar represents the percentage GCS scale (shown on the horizontal axis) of RTC patients broken down by share of admitted and not admitted. On the right, each bar shows the percentage of AVPU indicators (shown on the horizontal axis) with the share of admitted patients. GCS ≤ 10 GCS ≤ 10 10 < GCS < 15 10 < GCS < 15 GCS = 15 GCS = 15 GCS on arrival GCS 24 hours Figure 21.  GCS on Day of Arrival and Post 24 Hours Note: This graph shows the change in GCS scores over 24 hours for 1,647 patients out of 2,180 patients who were still in the health facility 24 hours after their arrival. The GCS scores on the day of arrival and at 24-hour assessment are represented by the blocks on both the vertical axes. The height of each block represents the percentage of patients whose GCS scores are in each of the categories i.e., GCS score equal to 15, between 10 and 15, or GCS less than or equal to 10. Each stream represents the flow of GCS scores of patients over 24 hours. The height of the stream shows the size of patients within each flow component. 30 TRAUMA INCIDENCE AND CARE IN TANZANIA Data Limitations and Lessons Learned for Trauma Registry Data Collection O ne of the critical and continuous challenges in any data collection effort relates to data quality. There are two dimensions of data quality: (1) data completeness and (2) data accuracy. Within data completeness, we look at completeness of variables collected for each individual trauma case, as well as whether all individual incoming trauma cases were recorded. Both data completeness and accuracy are important for ensuring the analyses produced with the data are unbiased and are an accurate portrayal of the situation for the areas covered by the data collection. Ensuring data quality requires significant investments, and the next subsections outline some of the issues faced by the research team and efforts made to address them. Completeness of the Data Given the level of detail the trauma forms aimed to capture relative to the standard systems in place, the research team provided detailed feedback for the hospital staff. The primary indicators TRAUMA INCIDENCE AND CARE IN TANZANIA 31 of completeness were missing variables and missing cases. Accuracy of the Data From the early stages of implementation, the research team observed missing data across multiple health-related outcome The research team implemented several measures to try and variables including vital signs, Glasgow Coma Scale (GCS) verify accuracy of the data. An “audit” system — comparing entries and Alert Verbal Pain Unresponsive (AVPU) score. In addition, in the trauma book vs the digital forms — allowed the team to recording the location of the incident and capturing date-time identify potential discrepancies. A primary goal was to identify variables posed serious challenges. The research team worked such discrepancies up-stream so that they could be addressed to understand how these gaps might be eliminated across the as close to the entry date as possible. Outcomes that were most facilities. The challenges presented at each facility were unique susceptible to accuracy errors include the date and location of to their infrastructure and capacity constraints. In each case, injury. For example, there were logical inconsistencies such as the research team engaged in a data-informed discussion the date and time the patient was injured were after the date and to prioritize the areas along which data collection could be time s/he reached the facility and was attended by a doctor. These improved for every facility. Solutions included providing staff logical inconsistencies were improved over time with consistent with vital-sign equipment they could use specifically for this flagging of outliers, sharing weekly feedback on data challenges, project; helping implement processes that streamlined data- and additional training to resolve common errors. verification; and refresher training on the importance of some Within the digital system, the research team could leverage the of the more complex health-related outcomes. With each ability to put in consistency checks at data entry, which would measure in place, the team noticed improvements in the data immediately signal a flag to the person entering the data if it completeness. Additionally, the team found that editing the was outside of an acceptable range or inconsistent with other paper form based on the feedback of clinicians made it more variables entered. Moving to a completely digital system that usable by field staff. Coding the digital data tool so that the does not have the intermediate step of paper entry would ensure majority of variables were required helped to further limit some a much higher quality of data for this type of data collection of the completeness challenges. effort because mistakes in data entry would be flagged while In addition to assessing completeness of the data within a given the clinician or data clerk is initially entering the data as they see entry in the trauma registry form, the team put in place a number the patient. This would provide the opportunity to correct such of measures to understand the extent to which the registry was issues while the patient is still being seen. capturing all cases coming into the health facilities. Assessment of capture rate was conducted regularly through different means including tallying hospital registry logs and comparing these Challenges Specific to numbers with the data collected from the project. A tracking sheet Road Traffic Crash Cases was also developed and used to compare cases in the digital data with the ones on paper forms to ensure that all paper forms were In addition to the set of broad data quality issues discussed above, entered in the digital system. The team supplemented this by there are a few challenges specific to RTI cases. There were three comparing administrative data with the trauma data the project main challenges faced. The first was being unable to capture the was collecting. Throughout these assessments, the trauma exact location of injury, i.e. up to the street/village level, this registries proved to be recording a majority of cases coming variable has 20% missing observations, which could be due to the into most of the facilities. Nevertheless, the capture was not patient not knowing the exact name of the street/village where s/ 100%, and there were especially gaps in capturing patients who he experienced the crash. The second challenge was difficulty in were dead on arrival at the facility. These patients did not pass convincing clinicians of the importance of collecting some of the through the emergency medical department at most facilities RTI variables (such as location of crash), given that they are not but were taken directly to the mortuaries. This multiple point-of- immediately relevant to their health care practice for attending entry posed a challenge to capture rate and is a limitation to the the patient. However additional support was provided to the trauma registry. Additionally, when the data collection began, Clinicians wherein the RA (Research Assistant) followed up on there could be a gap in recording the most serious cases i.e., these variables. Finally, there was difficulty and/or unwillingness those admitted in ICU; and the occasional absence of the RA that of the patients to provide some of the information, for example, could support the Clinician in collecting these data slowed down information on substance used within 6 hours of injury i.e., if there the process in a few health facilities. Due to the aforementioned was any alcohol used that might have influenced the crash. We reasons, out of our 13 health facilities Gairo, Morogoro, Kimara, tried resolving some of these issues via weekly feedback calls as and Mkata showed a lower capture rate. well as virtual training conducted in Swahili. 32 TRAUMA INCIDENCE AND CARE IN TANZANIA Discussion, Policy Relevance and Next Steps G iven the paucity of trauma data and evidence in post-crash care outcomes in low-income settings, the trauma registries set up under this project provide a notable example of how the data could feed in relevant insights for informing emergency care in a developing country context such as Tanzania. The initial goal of setting up trauma registries under this project was to estimate the impacts of Tanzania’s EMS Pilot on a series of critical health and road-safety outcomes. The registries were designed to capture all incoming trauma at 13 strategically selected facilities along the A7 highway and comparable highways. Due to factors unrelated to the impact evaluation and research, EMS operations were significantly delayed and as of May 2021, the pilot has not been launched. Consequently, while the trauma registry data cannot yet be utilized to assess the impact of the EMS pilot for post-crash care response outcomes, the data still has policy value given the TRAUMA INCIDENCE AND CARE IN TANZANIA 33 detailed time series data that has been collected over one emergency care in post-crash management (Sawe, 2017), which year — covering critical issues ranging from trauma care to the government aims to address through the EMS pilot project. medical outcomes, as well as road traffic injuries, amongst others. This kind of TR set-up also adds to regional data needed One of the constraints in effectively informing road safety and post-crash care interventions in developing countries is the to design coherent strategies. paucity of data in the sector and the varying nature of There are some key descriptive findings that come out of the available data sources (Thompson et al. 2016). Police records data. Trauma is concentrated in the age groups of 20–35, and are the primary data source for road crashes in most African the majority of victims coming to facilities are men. By far the countries (WHO 2013; 2015). Unfortunately, the traffic police most important cause of trauma is road traffic crashes, of which reports tend to underreport road crash injuries and deaths due around half are serious enough to be admitted. Within this group to poor response and follow ups with injured victims; with a of victims, almost one third were either the driver or passenger lack of uniformity in traffic injury and fatality definitions (WHO of a motorcycle, signaling the importance of focusing road safety Regional Office for Africa, 2010). Even data from some of the policies on motorcycles. Cyclists and pedestrians each make up registry-based systems in the region vary in their quality and in around twenty percent of road crash victims. A larger share of the completeness of data, incomplete breakdown of road traffic pedestrians experiences more severe trauma requiring admission crash estimates by road user type and lack of road traffic fatality as compared to other road users (53.8% of all pedestrians). case appropriate definitions (Adeloye et al. 2016). Additionally, the majority of pedestrians and cyclists were involved High quality and long-term trauma registries are a potentially in motorcycle crashes. These data signal the importance of putting important tool for health planning and post-crash response in road in place policies to reduce crashes among motorcyclists and to safety management. The data from this research project is an improve safety for both pedestrians and cyclists. excellent example of one of the first such rigorous, time-series, The time taken to arrive at the health facility post-crash is multi-site trauma registries set-up in health facilities with a considered crucial for emergency care. From these data we find focus on road crash variables in Tanzania. These high-quality that it took the crash victims a median time of 69 minutes to time series data from the registry could form the basis to estimate arrive at the health facility. There is also a peak of RTCs in the the true burden of road traffic crashes on the public health system daytime between 8:00 to 13:00 and then again in the evening and support prioritization of preventive strategies to address road between 18:00 to 22:00, which coincide with peak rush traffic traffic injuries; and be utilized to evaluate the impact of different times. This is in contrast to other trauma cases, which have a policy interventions focused on post-crash care in the broader single peak around mid-morning. The two peaks for cyclists domain of road safety management. We also see important are especially pronounced, signaling that rush hours may be differences between the data collected in Tanzania and the particularly dangerous for them. data collected in a parallel project in Malawi through a set of similar trauma registries set up in 10 health facilities. In Malawi, Fractures and head injuries make up a large part of the serious only around 17% of road traffic crash victims were the driver or injuries that are seen, demonstrating the importance of ensuring passenger of a motorcycle, which is half the value in Tanzania, training and resources to treat these specific injuries. The main demonstrating that the causes of RTCs are very context specific medications provided for all injuries are tetanus toxoid, antibiotics, and trauma registries can shed light on the particular needs in a and analgesics. The majority of victims are discharged the same given setting to help reduce crashes and save lives. day, and for those that are admitted to the hospital and still in the facility 24 hours later, most see improvement with an increase There are four main benefits of this type of rigorous trauma in their GCS score. registry data collection in Tanzania. First, multi-site trauma registries in Sub-Saharan Africa are very rare. This study Reduction in road crash related mortality and morbidity is a policy provides policymakers with a template for how they can be priority internationally, as well as for the Government of Tanzania, operationalized. It demonstrates that despite the significant following from the significant cost to the government — estimated infrastructure and capacity constraints relative to developed- at 3–4% of its GDP (WHO, 2015). Even though there have been country contexts, adequate planning, capacity building and efforts to prioritize road safety management in the global agenda oversight can feasibly deliver a high-quality trauma registry in such as the UN Decade for Road Safety, RTI related deaths in this setting. Second, relatedly, these data systems can support low-income countries persist. The pattern holds true in Tanzania, health system planning and administration. Findings around spurred by rapid urbanization (WHO, 2018) and lack of centralized seasonality of trauma and/or spikes over the course of the 34 TRAUMA INCIDENCE AND CARE IN TANZANIA day are just two examples of the kind of resource allocation the EMS pilot, including the renovation of emergency rooms decisions the registries can speak to, thereby improving the and the procurement of additional ambulances in the 7 pilot functioning of the health system as a whole. Third, in speaking facilities, the pilot should lead to overall improvements in EMS, to patient outcomes, the data can support the hospital and the data collected can potentially help to measure if these system(s) in designing improved patient care and triage improvements translate into better health outcomes. processes. Fourth, the registries provide data that supports previous estimates that trauma, and road traffic crashes, are a first-order public health concern in Tanzania that will require Recommendations a cross-sectoral approach to resolving. The goal of this report is to present some of the insights that can be gained from the one year of detailed trauma data collection These data from EMS Trauma registries can be fully utilized for the across 13 health facilities in Tanzania in order to encourage further impact evaluation once the EMS Pilot becomes operational. They use of these data to help inform policymakers on the current will support the assessment of a large multi-site emergency post- situation and help feed into more data-informed decisions. A few crash care system in a developing country; especially because recommendations that arise from these analyses: a high-quality baseline and time-series data are imperative to understand and establish trends, adding to policy evidence 1. Investment in systematic data collection on trauma cases for what works to improve outcomes for trauma victims. The can provide useful information for Transport and Health process of stakeholder buy-in, preparation, establishing, agencies to monitor the patterns and trends of trauma and operationalizing, and monitoring of the TR was pivotal to develop more targeted and effective policies, strategies in itself; the lessons learned from the process cycle can be and actions for reducing the number of trauma cases and helpful for policy makers aiming to establish TR in similar improving outcomes for trauma cases that come to health contexts. Additionally, the structure of data collection was such facilities that it primarily relied on the clinicians that were already embedded 2. Given motorcycle passengers/drivers make up the highest in the Government health facilities, an aspect that is crucial for long percentage of RTC patients and motorcycles are also the term sustainability. The fact that three health facilities continue to most likely to hit cyclists or pedestrians, these data point use the TR even after the official closing of baseline speaks to to a need to develop better regulation and enforcement in the usefulness of this type of data collection and the potential of sustainability of such a system. relation to motorcycles. 3. Further analysis into the cause of delays in reaching a health Insights from this report point to the importance of trauma in facility can help to decrease the time for victims to receive Tanzania, and especially the role of road traffic crashes, which healthcare to below one hour. Different causes, such as make up the largest part of the burden. As motorization increases lack of transport options versus congestion on the road, and there are further investments in road infrastructure, RTCs will require different approaches for improvement. are likely to increase. This calls for a targeted policy response and 4. While trauma registries are useful tools to collect information efforts towards a) reducing RTCs and b) improving emergency on trauma patients entering health facilities, there should care response on major corridors with significant movement of be an investment in other data sources as well. In particular, goods and people. This response can be guided by existing policy measuring victims’ disabilities in the long run could provide reports such as the recent GRSF report on what interventions important information to understand the long-term burden work and which ones do not (Turner et al 2021). As most of trauma. Also, given the role of motorcycles, there should recently Tanzania is the first country to begin implementation be further research on motorcycle ownership, how this is of the Ten Step Plan for Safer Road Infrastructure11 that started changing over time, and the types of policies that will be September, 2020, developed by the United Nations Road Safety needed to manage motorcycle injuries. Collaboration partners, it will be important to measure how 5. A cross-sectional approach and coordination between the effective this initiative will be in reducing the burden from RTCs Health, Law Enforcement, and the Transport authorities in seen in health facilities in the country. Additionally, while RTCs Tanzania is needed to collate data from multiple sources are the main cause of trauma, the data points to other important in order to have a more comprehensive picture of road factors as well, such as falls, which are the second leading cause traffic crashes (combining data on the circumstances of of trauma. With the overall improvements in EMS care through crashes with the health consequences and outcomes of victims) and to also develop a multi-sectoral approach to 11 https://www.who.int/roadsafety/publications/20200219-202801-4216-un-rsf- 10-steps-infrastructure.PDF tackling the burden of RTCs. TRAUMA INCIDENCE AND CARE IN TANZANIA 35 Bibliography Boniface, R., Museru, L., Kiloloma, O., & Munthali, V. (2016). Factors associated with road traffic injuries in Tanzania. Pan African medical journal, 23(1). Botchey Jr, I. M., Hung, Y. W., Bachani, A. M., Paruk, F., Mehmood, A., Saidi, H., & Hyder, A. A. (2017). Epidemiology and outcomes of injuries in Kenya: A multisite surveillance study. Surgery, 162(6), S45-S53. Croke, K., Chokotho, L., Milusheva, S., Bertfelt, J., Karpe, S., Mohammed, M., & Mulwafu, W. (2020). Implementation of a multi-center digital trauma registry: Experience in district and central hospitals in Malawi. The International Journal of Health Planning and Management, 35(5), 1157–1172. Kapologwe, N. A., Meara, J. G., Kengia, J. T., Sonda, Y., Gwajima, D., Alidina, S., & Kalolo, A. (2020). Development and upgrading of public primary healthcare facilities with essential surgical services infrastructure: a strategy towards achieving universal health coverage in Tanzania. BMC health services research, 20(1), 1–14. Mulwafu, W., Chokotho, L., Mkandawire, N., Pandit, H., Deckelbaum, D. L., Lavy, C., & Jacobsen, K. H. (2017). Trauma care in Malawi: A call to action. Malawi Medical Journal, 29(2), 198–202. Ola, O. (2013, October 17). Africa’s Trauma Epidemic. The New York Times. 36 TRAUMA INCIDENCE AND CARE IN TANZANIA Reynolds, T. A., Stewart, B., Drewett, I., Salerno, S., Sawe, H. R., URT: Ministry of Transport, Works and Communication. (2009). National Toroyan, T., & Mock, C. (2017). The impact of trauma care systems in Road Safety Policy. low-and middle-income countries. Annual review of public health, 38, World Bank. (2021). The State of Emergency Medical Services in Sub- 507–532. Saharan Africa. Washington, DC., USA: World Bank. Sawe, H. R., Mfinanga, J. A., Mbaya, K. R., Koka, P. M., Kilindimo, S. S., World Health Organization. (2015). Global status report on road safety Runyon, M. S., Mwafongo, V. G., Wallis, L. A. & Reynolds, T. A. (2017). 2015. World Health Organization. Trauma burden in Tanzania: a one-day survey of all district and regional public hospitals. BMC emergency medicine, 17(1), 1–6. World Health Organization. (2018). Global status report on road safety Sawe, H. R., Sirili, N., Weber, E., Coats, T. J., Wallis, L. A., & Reynolds, 2018. Geneva: World Health Organization. T. A. (2020a). Barriers and facilitators to implementing trauma registries in World Health Organization. (2020). Road traffic injuries. low-and middle-income countries: qualitative experiences from Tanzania. African journal of emergency medicine, 10, S23-S28. World Health Organization. (2020) WHO standardized clinical form. Available: https://www.who.int/publications/i/item/who-standardized- Sawe, H. R., Reynolds, T. A., Weber, E. J., Mfinanga, J. A., Coats, T. J., clinical-form & Wallis, L. A. (2020b). Development and pilot implementation of a standardised trauma documentation form to inform a National Trauma World Health Organization: A brochure for World Health Day 7 April 2004 Registry in a low-resource setting: lessons from Tanzania. BMJ open, (No. WHO/NMH/VIP/03.4). (2004). Road safety is no accident. World 10(10), e038022. Health Organization. TRAUMA INCIDENCE AND CARE IN TANZANIA 37 Annexes 38 TRAUMA INCIDENCE AND CARE IN TANZANIA Annex I:  Additional Figures A1.1a: Monthly Cases A1.1b: Percent of Trauma Cases Sep-2019 182 38.51 112 Road traffic crash 41.72 Oct-2019 775 775 17.38 Nov-2019 772 Fall 748 17.45 Dec-2019 81O 3.18 849 Hit by falling object 844 2.62 Jan-2020 671 811 15.84 Feb-2020 Stab/cut 687 9.61 Mar-2020 1006 897 11.19 Blunt trauma 10.50 Apr-2020 624 555 712 2.87 May-2020 Burn 465 1.80 Jun-2020 807 582 3.53 839 Bite Jul-2020 6.28 631 Aug-2020 850 1.06 637 Unknown 3.01 Sep-2020 789 557 5.72 310 Other Oct-2020 5.54 275 0 200 400 600 800 1,000 0 5 10 15 20 25 30 35 40 45 Number of cases Percent of cases EMS Pilot Control EMS Pilot Control Figure A1.1.  Comparison of EMS Pilot and Control Facilities Note: This panel shows the number of cases (on the left) and the percentage of trauma causes (on the right) broken down for treatment and control facilities. The light blue bars represent EMS pilot facilities and the shaded bars represent control facilities in the trauma registry. A1.2a: Rural trauma sites A1.2b: Urban trauma sites Car (private/taxi) 33.04 Car (private/taxi) 26.15 Motorcycle 22.32 Walk in 21.55 Ambulance 21.43 Tricycle (bajaj) 16.09 Walk in 9.82 Motorcycle 15.52 Other 6.25 Mini bus 9.77 Mini bus 5.36 Ambulance 6.03 Tricycle (bajaj) 1.79 Other 4.89 0 10 20 30 40 50 60 70 80 90 100 0 10 20 30 40 50 60 70 80 90 100 Percent of trauma cases Percent of trauma cases Other includes bicycle, bus, truck Other includes bicycle, bus, truck Total number of recorded cases from rural areas = 6,342 Total number of recorded cases from urban areas = 11,228 Total number of severe cases from rural areas = 115 Total number of severe cases from urban areas = 349 Figure A1.2.  Mode of Transfer for Severe Injuries (GCS ≤ 10 or AVPU = ‘Unresponsive’) from Rural and Urban Trauma Sites Note: The above figure shows a subset of severe injuries where the GCS ≤ 10 or the AVPU is unresponsive. In both panels, the bar graph shows the share of each mode of transport (on the vertical axis). The panel on the left represents the severe trauma cases from rural areas and the right panel shows the severe trauma cases from urban areas. TRAUMA INCIDENCE AND CARE IN TANZANIA 39 Annex II:  Trauma Form TRAUMA FORM Hospital Registration Number: Date: DD/MM/YY Time of Arrival: (24h format) Other IDNumber: _ _ Referred from another facility? □Y □N ; Name of facility: Source: Patient Name (Surname, First): Arrival Mode: □Ambulance □Car (Circle Private or Taxi) □Truck □ Walk in □ Motorcycle □Tricycle (Bajaj) □Bus □Minibus □Bicycle Date of Birth: DD/MM/YY □Other Sex: M / F Weight: kg Age: INF / CH / AD Patient Phone Number: Contact Person: Patient Residence: Region_______________ District______________________________ Phone: Relation: Ward Village/Street/Landmark Status of the patient: □Alive-Ambulatory □ Alive-Non Ambulatory Level of Education: □Dead ontransitto facility □Dead onthescene of injury Patient Occupation: Triage Category: □ Emergency □Priority □ Queue CHIEF COMPLAINT: □Contusion (bruise) □Laceration ( Cut) □Abrasion □Fracture □SoftTissueInjury □Bite □Burn □Penetratingwound/stab □Dislocation INITIAL VS: at : (AM/PM) B.P: / □Gun-shotwound □Injury to internal organ □Head Injury □Spine Injury □ Foreign body □Traumatic Amputation □Drowning □Crush Injury □ Unknown HR: RR: SpO2: % on Temp: °C □Other Reason VS not recorded: DETAILS (if any): PAINSCORE: (Out of 10) Date Patient attended by Doctor: Time Patient Attended by Doctor (24h format) Physical findings Interventions done Airway Manipulation: □ Repositioning □Suction A irway □ Angioedema□Stridor □Voicechanges □ Oral/Airway burns Airway: □OralAirway □Nasal Airway □ NORMAL Obstructed by: □ Tongue □Blood □ Laryngeal mask airway □ Endotracheal intubation □Secretions □ Vomit □ Foreign body Cervical collar: □None needed □Placed before arrival □Placed in casualty Spontaneous Respiration: □ Yes □ No GivenOxygen: L Chest needle / tube (circle): B reathing Chest Rise: □Shallow □ Retractions □ Paradoxical □Nasal Cannula □Mask □ L – Size: Depth: cm Trachea: □ Midline □Deviated to □L □R □ Non-Rebreather mask □Bag Valve □ R – Size: Depth: cm □NORMAL Breath Sounds: Abnormal: □ L □R Mask □C PAP □ Not done □Ventilator Skin: □ Warm □ Dry □ Bleeding controlled (bandage, tourniquet, direct pressure) □ Pale □ Cyanotic □ Moist □ Cool Access: □Intravenous Location Cannula Size G Circulation Capillary refill: □ <2 sec □ ≥2 sec □Central line Location □Intraosseous Line Location Size Size G G □ Pulses: □Weak □Asymmetric JugularVenousDistension: □Yes □ No □Intravenous Fluid: mL □ NS □RL □ DNS □Dextrose NORMAL □Blood ordered □Pelvic binder placed Disability Blood glucose: mmol/l □Glucose given Responsiveness: □ A □ V □ P □ U FAST Peritoneum: □ Negative □ Indeterminate □NORMAL □Naloxone GCS: /15 (E V M □ Free Fluid Moves Extremities: □ LUE □RUE □ LLE □RLE Exposure Pupils: L mm→ mm R mm_→ mm □NORMAL □ Chest: □Negative □ Indeterminate □ Pneumothorax (R/L): □NORMAL □NotIndicated □Patient has been Exposed completely □ Pleuralfluid (R/L): □ Pericardial fluid □Not done HISTORY OF PRESENT ILLNESS Date of Injury: DD/MM/YY Time of Injury: (24h format) Place of injury: □On the Road □At Work □ At Home □In School Mechanism of injury: □During Leisure / Sport □ Public Space – Indoor □Road traffic incident □ Public Space– outdoor □Unknown □Other □Fall from: □Hit by fallingobject: Location of Injury: □ Rural □Urban □Semi-Urban □ Unknown □Stab/Cut □Gunshot □Sexual Assault □Other blunt forcetrauma(struck/hit): Patient’s activity at the time of injury__ □Unknown □Suffocation, choking, hanging Hours since last meal: _□Unknown □Drowning: Flotationdevice:Y/ N First Care sought before arrival at the Casualty □Burncausedby: □ None □Layperson first aid □ Health Care provider □Poisoning/Toxic Exposure: □ Bite Care given: □Unknown □Other: LocationoftheTrauma Incident: Region Road Traffic Incident: District Ward Role on road: □Driver □Passenger □ Pedestrian □ Cyclist □ Other Village/Street/Landmark Vehicle of patient: □Car □Truck □Motorcycle □Tricycle □ Bicycle □Bus □ Minibus Intent: □ Unintentional or accidental □ Assault □Self harm □ Other ( Circle Private or Taxi) □Legal process, political unrest or war □ Unknown Crashed with: □Car □Truck □ Motorcycle □Tricycle □Bus □ Minibus □ Bicycle Assaulted by: □Pedestrian □ Animal □ Non-moving object □Nothing (Due to Vehicle failure) Substanceusewithin6hoursofinjury: □Unknown□None □ Nothing (Due to External factors) □ Unknown □ Other (Circle Private or Taxi) □Reported □ Evidence (positive test/clinical findings) Safety Equipment: □Airbag □ Seat belt □Other vehicle restraint □ Helmet □ Alcohol □ Other Substance (if known): Other: □Ejected □Extricated Other Details:□Loss of consciousness □<5min □5–29min □30-24hr Mass Causality: □Y □N 40 TRAUMA INCIDENCE AND CARE IN TANZANIA PAST MEDICAL HISTORY: History Obtainedfrom: Known History of □Hypertension □Diabetes □ COPD □ HIV Pregnant: □Yes □No □Not applicable (N/A) □Other □None □Unknown Last Menstrual Cycle: □N/A G P □N/A Current Medication: □None □Unknown Vaccinations up to date?: □Yes □No Past Surgeries: □None □Unknown Substance User: □Tobacco□ Alcohol □Drug □IV Drugs AnyKnownAllergies: □None □Unknown Safe at home?: PHYSICAL EXAMINATION (SECONDARY SURVEY) Comments Serious (Yes/No) Detail area of injury: General □NORMAL HEENT □Yes □No □NORMAL Neuro □Yes □No □NORMAL Neck □Yes □No □NORMAL Pulm/Chest □Yes □No □NORMAL Cardiac □Yes □No □NORMAL Abdominal □Yes □No □NORMAL Pelvis □Yes □No □NORMAL GU/Rectal □Yes □No □NORMAL Back Exam □Yes □No □NORMAL MSK/Skin □Yes □No PLAN AND INTERVENTIONS: Fluids and Medications Given Procedures done □ IV Fluids: □ NS mL|□RL mL| □ mL□ None given □ Intubation: □ Blood products: □ WB U|□PRBC U| □Other □ None given □ Chest Tube: □ Analgesia: □ Nonegiven □ Splinting: □ SedationandParalytics: □ Nonegiven □ Fracture Reduction: □ Antibiotics: □ Nonegiven □Pelvic Stabilization: □ Tetanustoxoid: □ Nonegiven □ Foreignbody removal: □ Other: □ Simple / Complex Laceration Repair: □ Other: LABORATORY TEST AND RESULTS RADIOLOGICAL / IMAGING INVESTIGATIONS ANDRESULTS □Urine for pregnancy: □Not done □Positive □ Negative □X Rayof: □ Haemoglobin: g/dl □pending □ Notdone □Pneumothorax □ Pleural Fluid □Rib Fracture □Pulmonary Opacity □ Bloodgrouping: _ □ pending □ Not done □C-Spine fracture □ Extremity Fracture □ Pelvic fracture □Other: □Other: _ FINAL CASUALITY DIAGNOSIS: Number of serious injuries (Total No.) CASUALITY CONSULTATION: □None needed □Done to: : Time called : Time arrived Recommendations from consult: _ FINAL CASUALTY REASSESSMENT at : (24h format) BP: / HR: RR: SpO2: % on Temp: °C PATIENT CONDITION: □Same□Changed ADMINTTED TO: □Ward □ ICU □Operating Theatre □DISCHARGE HOME Plan discussed with patient? □ Yes □No REFFERED TO: _ □DIED OF _ □Left without being seen □ Left without complete treatment Name of the attending Clinician Cadre (MD, AMO, CO , Intern) Signature, Date and Time / / Comments TRAUMA INCIDENCE AND CARE IN TANZANIA 41 Annex III:  Trauma and RTC Cases by District Admitted (admitted/died in District ED/referred to other facilty? RTC Total trauma Ubungo 559 800 2861 Morogoro mjini 1212 818 2259 Kibaha mjini 299 787 1567 Moshi mjini 282 590 1395 Same 395 490 923 Gairo 231 215 703 Bagamoyo 99 255 612 Dodoma 531 345 603 Moshi vijijini 124 209 595 Mvomero 178 133 538 Kilosa 100 178 435 Morogoro vijijini 202 129 429 Chamwino 78 33 130 Bahi 91 45 125 Hai 30 34 94 Kibaha vijijini 24 33 68 Kondoa 54 26 59 Ilab 13 43 52 Kinondoni 5 29 41 Mwanga 17 19 40 Kisarawe 7 23 36 Chemba 29 10 35 Mpwapwa 26 14 28 Temeke 5 22 27 Kongwa 23 11 26 Siha 9 8 14 Rombo 5 6 11 Kigamboni 3 7 9 Mikumi 4 1 7 Ulanga 1 2 5 Kilombero 0 3 4 Mkuranga 0 1 2 42 TRAUMA INCIDENCE AND CARE IN TANZANIA Annex IV:  EMS Pilot Impact Evaluation Aim of the Impact In order to encourage investment in post-crash care, it is important for policymakers to have data-driven evidence on how well different post- Evaluation crash interventions work in achieving the goals of greater access to emergency transport, improved on-scene primary care, reduced delays in accessing specialist medical care, and ultimately lower morbidity and mortality. This project aimed to help provide some of the first rigorous evidence in a developing country setting. The key objectives were two-fold: (a) Evaluate the effectiveness of a pilot EMS program aimed at reducing adverse health outcomes from road crashes. The IE would help inform a possible scale-up of the EMS system in a developing country setting like Tanzania depending on the results of the study. (b) Provide real-time data to policymakers, hospital leaders and the doctors and clinicians on the ground that can use this information to improve trauma care and reduce mortality through the set-up of Trauma Registries. Treatment — Components The Emergency Medical Services (EMS) operations pilot was designed to be implemented along the A7 highway between Dar es Salaam and of EMS Pilot Intervention Morogoro at 7 public health facilities that include 2 hospitals, 3 health centers and 2 dispensaries. These were selected by the Ministry of Health, Tanzania to be inclusive of different levels of health facilities in Tanzania, as well as to be coordinated with the Southern Africa Trade and ­ Phase 1 (SATTFP) project area. Transport Facilitation Program — The pilot has the following key Treatment components: a) Renovation of the emergency room in health facilities; b) creation of an ambulance dispatch center and activation of an emergency access telephone number; c) training community first responders; d) training paramedics, fire safety professionals, and drivers based on the curriculum developed by Muhimbili University of Health and Allied Sciences; and e) procurement and management of ambulances and EMS equipment. Outputs expected: new ambulances with trained staff; first responders trained; a centralized dispatch center where people can call during emergencies; facilities with improved EMS infrastructure; facilities with trauma registries to record real-time patient-level data. Status of the Treatment components: The EMS operational pilot component has faced a number of delays — including delays owing to COVID-19 — and the full operational pilot project is yet to be implemented, thus the intended Impact Evaluation could not be completed. As of May 2021, the renovation of emergency rooms is underway and ambulances have been procured, which are important components of the pilot. Nevertheless, the dispatch center and new emergency number that would bring together the whole system are still in development. Outcomes of Interest The operational pilot aimed to achieve a few key outcomes: improving care at the site of crashes (via training of the first responders); reducing the time from the occurrence of trauma to when a patient receives medical treatment at a hospital (via the ambulance system); and improving care en route to the hospital and at facilities (via paramedic training, facility renovation and equipment upgrades at health facilities). The impact evaluation aims to assess whether the pilot intervention improves trauma care and mortality and morbidity in a developing country setting such as Tanzania. Some of the specific outcomes that were going to be measured included: 1.  Time between incidence of trauma and access to medical treatment. 2.  Clinical characteristics for victims of trauma including GCS, AVPU and vital signs. 3.  Discharge status from the hospital for victims of trauma 4.  Mortality for victims of trauma The medium-term outcomes of interest for the IE include improved health conditions — upon arrival at the hospital, and upon leaving the hospital. The long-term outcomes of interest include reducing mortality and morbidity due to road crashes in the catchment areas and improved policy planning in the EMS system. Research Method This IE was designed using a quasi-experimental research design that aims to use a Difference in Differences Strategy with High-Frequency Data. The primary questions for the IE were planned to be answered using a difference-in-differences design that includes high-frequency data collection. Apart from setting up trauma registries in the treatment hospitals, we extended this by setting them up as well in a group of control hospitals. We started these trauma registries before the programs have been implemented in order to have detailed pre-treatment data on health outcomes prior to the intervention. This trauma registry data provides high-frequency information on the trauma cases coming to these health facilities, including the time elapsed between trauma occurrence and arrival in hospital and treatment, the severity of the trauma, vital signs upon entrance, number of days in the hospital, and outcome of the case upon departure from the hospital. These data were going to be used to generate a set of outcome variables and to compare cases in the treatment and control facilities before and after the rollout of the program, using the high-frequency nature of the data to control extensively for pre-trends. For this main analysis of interest focused on health status as measured by the trauma registries in the health facilities, the unit of analysis was planned to be the patient, who is either treated in a treatment or control hospital. The goal of the intervention is that by improving post-crash care through this comprehensive set of policies, both trauma-related morbidity and mortality would decrease. The trauma registries can be used to detect effects on short and medium-term morbidity. Given that trauma-related mortality is a relatively rare event, there is not enough statistical power to detect changes linked to the program in the treatment and control facilities. At this stage, since the intervention did not move forward, data collection in the trauma registries has been stopped after 1 year. Once the intervention is fully implemented and operational, it could be possible to follow the strategy that was initially designed for evaluating the intervention. In particular, collecting 1 year of post-intervention data using the same trauma registry forms in the 13 health facilities would make it possible to compare the main outcomes before and after the intervention across the treatment and control facilities. TRAUMA INCIDENCE AND CARE IN TANZANIA 43 Annex V: Field Recce (Visit) Data, August 2019 *Daily Average varies if it is a Mass Casualty Accident; **No Data Number of outpatient services Number of road accident Health Facility clients on an average day patients on an average day* Kimara Health Centre 300 5 Morogoro Regional Hospital 120 7 Tumbi Regional Hospital 300 20 Chalinze Health Centre 180 5 Fulwe Dispensary 50 2 Mikumi Health Centre 30 2 Mvomero District Hospital 20 1 Gairo Health Centre 100 7 Dodoma Regional Hospital 250 30 Mkata Health Centre 80 1 Korogwe District Hospital 66 2 Mawenzi Regional Hospital 150 50 Same District Hospital 100 ** Note: Three dispensaries that were being considered to be part of the IE and were included in the Field Recce were removed after the field visits due to low volume of patients, and because most patients from these dispensaries got referred to the bigger health center or hospital. One of the goals of the Field Recce was to help in identifying appropriate control facilities and therefore a larger number of facilities were visited and narrowed down to the seven control facilities and 6 treatment facilities included in this table. 44 TRAUMA INCIDENCE AND CARE IN TANZANIA Photo Credits Cover: © FabrikaSimf/Shutterstock.com. Page 1: Photo ”Nurse at Cathlab control room“ courtesy of Irwan Iwe via Unsplash.com. Page 2: © Direct Relief, ”Bugando Medical Center, Tanzania“ October 15, 2008 via Flickr, Creative Commons CC BY-NC-ND 2.0. Page 5: © Hendri Lombard/World Bank, ”Dar es Salaam’s new bus transit system“ January 19, 2017 via Flickr, Creative Commons CC BY-NC-ND 2.0. Page 8: © Tim Brauhn, ”Ambulance” August 28, 2009 via Flickr, Creative Commons CC BY-NC-SA 2.0. Page 11: © Dominic Chavez/World Bank, “A portrait of Dr. Abdoul” June 16, 2015 via Flickr, Creative Commons CC BY-NC-ND 2.0. Page 14: © Jorge Cancela, “Tanzania” September 6, 2015 via Flickr, Creative Commons CC BY 2.0. Page 16: © Arne Hoel/The World Bank, “A doctor conducts an exam” March 12, 2003 via Flickr, Creative Commons CC BY-NC-ND 2.0. Page 20: © Andrey_Popov/Shutterstock.com. Page 25: © R Boed, “Clocktower Circle, Arusha, Tanzania” March 5, 2019 via Flickr, Creative Commons CC BY 2.0. Page 29: © Arne Hoel/The World Bank, “Bike rack” November 27, 2006 via Flickr, Creative Commons CC BY-NC-ND 2.0. Page 31: Photo ”Doctor Holding Cell Phone“ courtesy of National Cancer Institute via Unsplash.com. Page 33: © Dominic Chavez/World Bank, “A portrait of Lucy” June 25, 2015 via Flickr, Creative Commons CC BY-NC-ND 2.0. Page 36: © Arne Hoel/The World Bank, “AH-GH061127_6293 World Bank” November 27, 2006 via Flickr, Creative Commons CC BY-NC-ND 2.0. Page 38: © Direct Relief, ”Bugando Medical Center, Tanzania“ July 26, 2010 via Flickr, Creative Commons CC BY-NC-ND 2.0.