Skip to main content
Download PDF

Traumatic brain injury in Uganda: exploring the use of a hospital based registry for measuring burden and outcomes

BMC Research Notes volume 11, Article number: 299 (2018) Cite this article

Abstract

Objective

Lack of data on traumatic brain injuries (TBI) hinders the appreciation of the true magnitude of the TBI burden. This paper describes a scientific approach for hospital based systematic data collection in a low-income country. The registry is based on the evaluation framework for injury surveillance systems which comprises a four-step approach: (1) identifying characteristics that assess a surveillance system, (2) review of the identified variables based on adopted specific, measurable, assignable, realistic, and time-related criteria, (3) assessment of the proposed variables and system characteristics by an expert panel, and (4) development and application of a rating system.

Results

The electronic hospital-based TBI registry is designed through a collaborative approach to capture comprehensive, yet context specific, information on each TBI case, from the time of injury until death or discharge from the hospital. It includes patients’ demographics, pre-hospital and hospital assessment and care, TBI causes, injury severity, and patient outcomes. The registry in Uganda will open the opportunity to replicate the process in other similar context and contribute to a better understanding of TBI in these settings, and feed into the global agenda of reducing deaths and disabilities from TBI in low-and middle-income countries.

Introduction

Each year over 10 million people globally suffer traumatic brain injury (TBI) [1], which is a leading cause of brain disorders and disability worldwide. Road traffic injuries (RTI), which account for 60% of TBI cases, ranked as 8th leading cause of death in 2015 (1.2 million deaths globally); an increase of about 19.7% since 1990 [2]. Other important contributors to TBI include falls (20–30%), and violence (10%) [2, 3].

TBI incidence in sub-Saharan Africa (150–170/100,000) is much higher than the global incidence (106/100,000) [3]. Similarly, incidence of intracranial short-term injuries due to RTI and violence in sub-Saharan Africa are 1.47 and 3.34 times higher than global rates respectively. Whereas incidence rates of intracranial long-term injuries due to war, violence and other unintentional injuries are 5.44, 3.37 and 1.86 times higher than their respective global incidence rates. Rapid motorization and conflicts have been attributed as important causes of the relatively higher TBI incidence in the region [4].

As with majority of sub-Saharan countries, data on the burden of injury and TBI in Uganda is scarce. According to a Ministry of Health report, the capital city Kampala had an estimated annual injury incidence of 116/1000, an injury mortality rate of 220/100,000, an incidence of injury leading to disability of 23/1000, and incidence of non-fatal injuries of 2.8/1000 [5]. Facility-based studies from Uganda estimated the cumulative incidence of TBI hospital admissions at 89/100,000, with alarming figures for TBI-related mortality between 45.3 and 75% [4, 6,7,8].

The number of deaths from RTI in Uganda has doubled from 3059 in 1990 to nearly 7800 in 2015 [2]. With a growth rate of 3.3%, the population of the capital city Kampala, continues to rise, leading to greater numbers of vehicles and pedestrians on roads, and a resultant increase in road injuries and TBI incidence [9,10,11]. The day commuter population in Kampala is estimated at about 700,000 people, creating a risk pool of over 2 million people each day on the roads. As a result, approximately 9000 crashes are recorded each year in Kampala, which amounts to 25 crashes per day [12].

To better address the growing TBI burden, there are many critical gaps in knowledge that need to be addressed. Lack of good quality data on TBI hinders understanding of the magnitude of the burden and poses a barrier in identifying risks factors, vulnerable groups, and the impact of interventions. This issue was highlighted in a recent hospital-based study on severe TBI cases, that called for a need for systematic and efficient data collection that could have a positive impact on improving patient outcomes [4]. Thus, the overall goal of this paper is to introduce the development of an internet-based TBI registry in Uganda, based on an injury surveillance framework. The paper describes steps and components of the registry, Kampala internet-based Traumatic Brain Injury Registry (KiTBIR), which is the first of its kind in Uganda to understand the hospital-based TBI burden, risk factors in different populations and age groups, documentation of care processes, and indicators for quality of care. It is expected that the evidence generated from KiTBIR will facilitate the development of TBI management guidelines in resource-constraint settings.

Main text

The registry development was guided by the core principles of injury surveillance, and hospital-based context. The evaluation framework for injury surveillance systems (EFISS) presented by Mitchell et al. [13] describes the scope of the surveillance system in a four-step approach: (1) identifying characteristics that assess a surveillance system, (2) a thorough review of identified characteristics/variables based on adapted specific measurable assignable realistic time-related (SMART) criteria, (3) assessment of the proposed variables and system characteristics by an expert panel, and (4) development and application of a rating system [13].

According to EFISS, injury surveillance system should be designed so that it could be evaluated for its data quality, operational characteristics, and practical considerations [13]. These attributes are summarized in Table 1. This paper focuses on the development and implementation of KiTBIR, where EFISS characteristics were adopted from the planning to the development phase of the registry, to be able to systematically monitor and evaluate specific attributes after implementation. Subsequent papers will discuss KiTBIR variables, results, sustainability and scale-up of the registry to other settings.

Table 1 Modified EFISS framework for traumatic brain injury registry in Uganda
Full size table

A multi-pronged approach was sought for finalizing the content and scope of KiTBIR. The approach involved a comprehensive literature review, identification of core variables, expert consensus meeting to shortlist the variables according to the scope and case definition. These steps are described in detail below:

The identification of potential variables in KiTBIR involved three strategies: (1) Literature review using search terms and MESH headings for “Brain injury AND Africa” and “Brain injury AND registry AND low-and-middle-income countries (LMICs)”. Several databases were searched using these terms including PubMed/Medline, EMBASE, Scopus, Cochrane Reviews, System for Information on Grey Literature, and Global Health Ovid. The purpose of this review was to understand the published literature on characteristics and risk factors in the context of LMIC and sub-Saharan Africa between year 2006 and 2015 (Fig. 1). Twenty-four papers were selected and independently reviewed by two members of the research team. The result was development of a candidate list of TBI variables; (2) United States National Institute of Neurological Disorders and Stroke (NINDS) guidelines were reviewed for case definitions, TBI signs and symptoms; and (3) review of the previous work done by the team on development and implementation of injury surveillance tools and trauma registries [14, 15].

Fig. 1
figure1

Summary of literature review for identification of core variable for the traumatic brain injury registry

Full size image

Core variables covered three main areas: risk factors, clinical care, and patient outcomes. These variables provide context-specific details of hospital burden of TBI, care processes and pre-hospital, emergency department (ED) and inpatient interventions. In addition, date/time variables for injury event, hospital presentation, triage and disposition were included to understand potential delays in care provision. Outcomes at discharge from the hospital was based on Glasgow Outcome Scale which has five categories; death, persistent vegetative state, severe disability, moderate disability and good recovery [16]. Scoring systems such as Kampala trauma score (KTS) was also proposed to measure the injury severity, and risk-adjusted outcome comparisons [17,18,19]. The final list of variables is available upon request.

The registry was envisioned to create a foundation for TBI prevention and improving quality of care by embedding indicators and outcomes for injury control, access to hospital care, care processes and outcomes. A multidisciplinary consensus meeting was held to finalize the scope of KiTBIR, core variables, data collection platform, and implementation process. The group consisted of local, regional and international public health practitioners, clinicians including neurosurgeons, injury prevention experts and information technology professionals. Time burden, local healthcare delivery processes, and data collection feasibility was also considered in finalization of the variables. Consensus was developed for the inclusion/exclusion criteria, operational definitions, and key performance indicators. Additionally, approaches to get reliable information, data collection procedures, training needs and ethical considerations were also established.

The final KiTBIR registry consists of six broad sections with 97 variables. Each section covers 5–29 questions, which are illustrated in Table 2 and include patients’ demographics, pre-hospital and hospital assessment and care, external causes of injuries, injury severity measured by KTS and revised trauma score, and patient outcome. KiTBIR provides an opportunity for validation of KTS in TBI population of Uganda.

Table 2 Sections and variables in KiTBIR
Full size table

The registry was digitized using a m-health platform that was developed and pretested according to the local needs and resources available for TBI patients at the tertiary-care hospital in Kampala, Uganda.

In the digital platform, the flow of the information and organization of different sections was based on the usual course of patient in a tertiary-care hospital of Uganda (Additional file 1: Figure S1: patient and data flow for KiTBIR). Patients with TBI typically present to the ED where staff completes initial assessment to assess patient’s condition and injuries, followed by specialty consultation based on the injury severity and need for hospital admission. Patients requiring inpatient admission are moved to neurosurgery ward while patients with less severe injuries are observed and discharged from ED. This patient flow is considered in designing the content and flow of questions in each section of KiTBIR to facilitate data collection.

Several steps were taken to develop a user-friendly and standardized data collection tool. OpenDataKit (https://opendatakit.org), an open source software for mobile data collection, was used and an Aggregate on a cloud server in Uganda was setup. Questionnaires were developed in Microsoft Excel XLSFORM, and uploaded to the Aggregate for data collection. The questionnaires largely consisted of dropdown menus and check boxes, along with mandatory fields such as age, sex, vital signs. The ODK-Collect app was downloaded on the Android tablets, secured through user-specific password, for data collection. Completed data collection forms on the tablet could be uploaded over Wi-Fi or internet connection to the Aggregate on the cloud server. Data quality control measures, confidentiality, and system security were in place. The encryption of the device was supported by elliptic curve cryptography and script; this provided additional security of the data with the ability to remotely activate android device manager to lock or erase information in case of stolen or lost device.

Strengths and limitations

This is one of the first studies designed to collect prospective hospital-based data on TBI patients in a large tertiary-care hospital of a low-income setting, employing electronic data collection methods. KiTBIR demonstrated several advantages: First, it feeds into a surveillance system, documents the hospital-based TBI burden, risk factors, injury mechanisms, outcomes, allows to fill information gaps on the vulnerable populations, and develop strategies for prevention and control [20].

Second, KiTBIR documents care processes and performance indicators in a low-resource setting, that functions with limited infrastructure, human resources, access to care, and efficiency compared to high-income countries [21]. Combining core surveillance measures with hospital-based care processes and outcome, makes KiTBIR a robust tool to perform dual function of surveillance and monitoring quality of care. Development and implementation of clinical management protocols and data-driven policies to improve outcomes of TBI patients in Uganda will be the ultimate impact of the registry.

Third, this hand-held based data collection tool uses innovative approach which could become a foundation for multicenter injury database [22]. Using open-source software and smart electronic devices is the way forward to streamlining data collection in setups lacking electronic medical record systems. The collaborative approach has resulted in understanding local context and developed local capacity for future sustainability and integration of the registry into the current system at the hospital.

Lastly, utilization of the EFISS framework provided the basis of the planning and development of KiTBIR, and ensured that data quality, operational challenges and practical considerations were taken into account. Similar approaches could guide other researchers and clinicians in development of a comprehensive database for injury surveillance and hospital-based registries. The planning and implementation of KiTBIR, based on EFISS provides a proof of concept that low-cost, good quality, reliable injury surveillance systems could be established and help identify targeted strategies to increase the uptake of the system and expand it to other clinical settings.

There are some limitations of this work. First, KiTBIR is designed to collect data on TBI patients from their point of entry to exit from the hospital. In a resource-limited tertiary care setting, tracking patients through their entire course, especially those involving multiple departments and locations, might present a unique challenge. There is lack of centralized information system to update patients’ location or discharge in real time, and this could potentially result in missing information, or loss of patient follow-up after leaving ED.

Second, since this is the first time that tablets are used for data collection in the hospital, there is a risk of loss of data in case of tablet malfunction, theft, etc., if not timely uploaded on the servers. In such instances, the data will not be retrievable. During implementation phase, effort would be made to ensure data submission within 24 h of patient presentation to the ED.

A customized electronic TBI registry will open opportunity to replicate the process in similar settings and contribute to the global agenda of reducing deaths and disabilities from TBI in low-income countries.

Abbreviations

EFISS:

evaluation framework for injury surveillance systems

KiTBIR:

Kampala internet-based Traumatic Brain Injury Registry

LIC:

low-income countries

LMIC:

low-and-middle income country

RTI:

road traffic injury

SMART:

specific measurable assignable realistic time

TBI:

traumatic brain injuries

WHO:

World Health Organization

References

  1. 1.

    World Health Organization. Neurological disorders: public health challenges. Geneva: World Health Organization; 2006.

    Google Scholar 

  2. 2.

    The Global Burden of Disease Study 2015 University of Washington. Seattle: Institute for Health Metrics and Evaluation; 2016. http://www.healthdata.org/gbd. Accessed 30 Jan 2017.

  3. 3.

    Hyder AA, Wunderlich CA, Puvanachandra P, et al. The impact of traumatic brain injuries: a global perspective. NeuroRehabilitation. 2007;22(5):341–53.

    PubMed  Google Scholar 

  4. 4.

    Tran TM, Fuller AT, Kiryabwire J, et al. Distribution and characteristics of severe traumatic brain injury at Mulago National Referral Hospital in Uganda. World Neurosurg. 2015;83(3):269–77.

    Article  PubMed  Google Scholar 

  5. 5.

    Uganda Ministry of Health. Health management information system report. Kampala: Ministry of Health; 2000.

    Google Scholar 

  6. 6.

    Hsia RY, Ozgediz D, Mutto M, et al. Epidemiology of injuries presenting to the national hospital in Kampala, Uganda: implications for research and policy. Int J Emerg Med. 2010;3(3):165–72.

    Article  PubMed  PubMed Central  Google Scholar 

  7. 7.

    Jayaraman S, Ozgediz D, Miyamoto J, et al. Disparities in injury mortality between Uganda and the United States: comparative analysis of a neglected disease. World J Surg. 2011;35(3):505–11.

    Article  PubMed  Google Scholar 

  8. 8.

    Kwizera A, Dunser M, Nakibuuka J. National intensive care unit bed capacity and ICU patient characteristics in a low income country. BMC Res Notes. 2012;5:475.

    Article  PubMed  PubMed Central  Google Scholar 

  9. 9.

    Uganda Bureau of Statistics. Uganda population and housing census analytical report: education and literacy. Kampala: Uganda Bureau of Statistics; 2006.

    Google Scholar 

  10. 10.

    The World Bank Data. Washington DC: The World Bank; 2016.

  11. 11.

    National Population and Housing Census—provisional results. Kampala: Uganda Bureau of Statistic; 2014. http://unstats.un.org/unsd/demographic/sources/census/wphc/Uganda/UGA-2014-11.pdf. Accessed 1 Aug 2017.

  12. 12.

    Nasasira JH. Call for a decade of action for road safety CALL: launch of the second report of the commission for global road safety. Kampala: Uganda Ministry of Works and Transport; 2009.

    Google Scholar 

  13. 13.

    Mitchell RJ, Williamson AM, O’Connor R. The development of an evaluation framework for injury surveillance systems. BMC Public Health. 2009;9:260.

    Article  PubMed  PubMed Central  Google Scholar 

  14. 14.

    Mehmood A, Razzak JA, Kabir S, et al. Development and pilot implementation of a locally developed trauma registry: lessons learnt in a low-income country. BMC Emerg Med. 2013;13:4.

    Article  PubMed  PubMed Central  Google Scholar 

  15. 15.

    Mehmood A, Allen KA, Al-Maniri A, et al. Trauma care in Oman: a call for action. Surgery. 2017;162:S107.

    Article  PubMed  Google Scholar 

  16. 16.

    McMillan TM, Weir CJ, Ireland A, et al. The glasgow outcome at discharge scale: an inpatient assessment of disability after brain injury. J Neurotrauma. 2013;30(11):970–4.

    Article  PubMed  Google Scholar 

  17. 17.

    Kobusingye OC, Lett RR. Hospital-based trauma registries in Uganda. J Trauma. 2000;48(3):498–502.

    Article  PubMed  CAS  Google Scholar 

  18. 18.

    Hung YW, He H, Mehmood A, et al. Exploring injury severity measures and in-hospital mortality: a multi-hospital study in Kenya. Injury. 2017;48:2112–8.

    Article  PubMed  Google Scholar 

  19. 19.

    Weeks SR, Juillard CJ, Monono ME, et al. Is the Kampala trauma score an effective predictor of mortality in low-resource settings? A comparison of multiple trauma severity scores. World J Surg. 2014;38(8):1905–11.

    Article  PubMed  Google Scholar 

  20. 20.

    Krug EG. Injury surveillance is key to preventing injuries. Lancet. 2004;364(9445):1563–6.

    Article  PubMed  Google Scholar 

  21. 21.

    Gruen RL, Gabbe BJ, Stelfox HT, et al. Indicators of the quality of trauma care and the performance of trauma systems. Br J Surg. 2012;99(Suppl 1):97–104.

    Article  PubMed  Google Scholar 

  22. 22.

    Labrique AB, Vasudevan L, Kochi E, et al. mHealth innovations as health system strengthening tools: 12 common applications and a visual framework. Global Health Sci Pract. 2013;1(2):160–71.

    Article  Google Scholar 

  23. 23.

    du Toit-Prinsloo L, Saayman G. Fatal head injuries in children under the age of 5 years in Pretoria. Am J Forensic Med Pathol. 2014;35(3):212–7.

    Article  PubMed  Google Scholar 

  24. 24.

    Maier D, Njoku I Jr, Schmutzhard E, et al. Traumatic brain injury in a rural and an urban Tanzanian hospital–a comparative, retrospective analysis based on computed tomography. World Neurosurg. 2014;81(3–4):478–82.

    Article  PubMed  Google Scholar 

  25. 25.

    Kiboi JG, Kitunguu PK, Angwenyi P, et al. Predictors of functional recovery in African patients with traumatic intracranial hematomas. World Neurosurg. 2011;75(5–6):586–91.

    Article  PubMed  Google Scholar 

  26. 26.

    Hassan NA, Kelany RS, Emara AM, et al. Pattern of craniofacial injuries in patients admitted to Tanta University Hospital-Egypt. J Forensic Leg Med. 2010;17(1):26–32.

    Article  PubMed  Google Scholar 

  27. 27.

    Zulu BM, Mulaudzi TV, Madiba TE, et al. Outcome of head injuries in general surgical units with an off-site neurosurgical service. Injury. 2007;38(5):576–83.

    Article  PubMed  CAS  Google Scholar 

  28. 28.

    Qureshi JS, Ohm R, Rajala H, et al. Head injury triage in a sub Saharan African urban population. Int J Surg. 2013;11(3):265–9.

    Article  PubMed  Google Scholar 

  29. 29.

    Nnadi MON, Bankole OB. Traumatic brain injury patients: direct versus inter-facility transfer time to neurosurgical center and the effects on outcome. East Central Afr J Surg. 2014;19(2):59–65.

    Google Scholar 

  30. 30.

    Winkler AS, Tluway A, Slottje D, et al. The pattern of neurosurgical disorders in rural northern Tanzania: a prospective hospital-based study. World Neurosurg. 2010;73(4):264–9.

    Article  PubMed  Google Scholar 

  31. 31.

    Hitimana J, Perez M, Kinasha A, et al. Clinical presentation and outcome of neurosurgical conditions at Butare Teaching Hospital, Rwanda. East Central Afr J Surg. 2009;14(1):50–6.

    Google Scholar 

  32. 32.

    Kesinger MR, Nagy LR, Sequeira DJ, et al. A standardized trauma care protocol decreased in-hospital mortality of patients with severe traumatic brain injury at a teaching hospital in a middle-income country. Injury. 2014;45(9):1350–4.

    Article  PubMed  Google Scholar 

  33. 33.

    Bahloul M, Chelly H, Ben Hmida M, et al. Prognosis of traumatic head injury in South Tunisia: a multivariate analysis of 437 cases. J Trauma. 2004;57(2):255–61.

    Article  PubMed  Google Scholar 

  34. 34.

    Imen RB, Olfa C, Kamilia C, et al. Factors predicting early outcome in ptients admitted at emergency department with head trauma. J Acute Dis. 2015;4(1):68–72.

    Article  Google Scholar 

  35. 35.

    Morisse E, Favarel-Garrigues JF, Couadau E, et al. Incidence of hospital-admitted severe traumatic brain injury and in-hospital fatality rates in a Pacific Island country: a 5-year retrospective study. Brain Inj. 2014;28(11):1436–40.

    Article  PubMed  Google Scholar 

  36. 36.

    Wu X, Hu J, Zhuo L, et al. Epidemiology of traumatic brain injury in eastern China, 2004: a prospective large case study. J Trauma. 2008;64(5):1313–9.

    Article  PubMed  Google Scholar 

  37. 37.

    Chalya PL, Kanumba ES, Mabula JB, et al. Aetiological spectrum, injury characteristics and treatment outcome of head injury patients at Bugando Medical Centre in north-western Tanzania. Tanzania J Health Res. 2011;13(1):74–81.

    Article  Google Scholar 

  38. 38.

    Idowu OE, Akinbo O. Neurotrauma burden in a tropical urban conurbation level I trauma centre. Injury. 2014;45(11):1717–21.

    Article  PubMed  CAS  Google Scholar 

  39. 39.

    Bahloul M, Ben Hamida C, Chelly H, et al. Severe head injury among children: prognostic factors and outcome. Injury. 2009;40(5):535–40.

    Article  PubMed  Google Scholar 

  40. 40.

    Adeolu AA, Abiona TC, Komolafe EO, et al. Epidemiology of neurotrauma in Ife-Ijesha zone of Nigeria. World Neurosurg. 2013;80(3–4):251–4.

    Article  PubMed  Google Scholar 

  41. 41.

    Okyere-Dede EK, Nkalakata MC, Nkomo T, et al. Paediatric head injuries in the Kwazulu-Natal Province of South Africa: a developing country perspective. Trop Doct. 2013;43(1):1–4.

    Article  PubMed  Google Scholar 

  42. 42.

    Dias C, Rocha J, Pereira E, et al. Traumatic brain injury in Portugal: trends in hospital admissions from 2000 to 2010. Acta Med Port. 2014;27(3):349–56.

    Article  PubMed  Google Scholar 

  43. 43.

    Shao J, Zhu H, Yao H, et al. Characteristics and trends of pediatric traumatic brain injuries treated at a large pediatric medical center in China, 2002–2011. PLoS ONE. 2012;7(12):e51634.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  44. 44.

    Adeleye AO, Olowookere KG, Olayemi OO. Clinicoepidemiological profiles and outcomes during first hospital admission of head injury patients in Ikeja, Nigeria. A prospective cohort study. Neuroepidemiology. 2009;32(2):136–41.

    Article  PubMed  CAS  Google Scholar 

  45. 45.

    Klimo P Jr, Ragel BT, Jones GM, et al. Severe pediatric head injury during the Iraq and Afghanistan conflicts. Neurosurgery. 2015;77(1):1–7 (discussion).

    Article  PubMed  Google Scholar 

  46. 46.

    Udoh DO, Adeyemo AA. Traumatic brain injuries in children: a hospital-based study in Nigeria. Afr J Paediatr Surg. 2013;10(2):154–9.

    Article  PubMed  Google Scholar 

Download references

Authors’ contributions

AM, NZ, CH, OK, HS and AAH were involved in the conception and design of the tool and the study. All authors revised the article critically for important intellectual content. All authors read and approved the final manuscript.

Acknowledgements

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Availability of data and materials

Data sharing is not applicable to this article as no datasets were generated or analyzed during the current study.

Consent for publication

Not applicable.

Ethics approval and consent to participate

Ethical review and approval for this study is taken from the Institutional Review Boards (IRB) of the Johns Hopkins School of Public Health, Makerere University School of Public Health and Uganda National Council. Oral consent will be taken from study participants and will be informed during the consent process that their data will be de-identified and aggregated data will be published in scientific journal and disseminated through community awareness programs. Oral consent is considered instead of written consent to include individuals who are not educated and therefore, unable to read and write. This is mentioned in the IRB applications and is approved by all the three IRBs mentioned above. The data collection of this project is completed and results will be shared in future publications.

Funding

This study was supported by Grant (R21NS085094) to Johns Hopkins University under the Global Brain Disorders Research award of the Fogarty International Center at the US National Institutes of Health (NIH). The funding agency had no role in study design, data collection, data analysis, data interpretation, or decision to submit this manuscript for publication. The corresponding author had full access to all the data in the study, and had final responsibility for the decision to submit for publication.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Author information

Affiliations

  1. Johns Hopkins International Injury Research Unit, Health Systems Program, Department of International Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA

    Amber Mehmood, Nukhba Zia, Connie Hoe & Adnan A. Hyder

  2. Makerere University’s School of Public Health, Kampala, Uganda

    Olive Kobusingye

  3. Department of Neurosurgery, Mulago Hospital, Kampala, Uganda

    Hussein Ssenyojo

Authors
  1. Amber Mehmood
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Nukhba Zia
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Connie Hoe
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Olive Kobusingye
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Hussein Ssenyojo
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Adnan A. Hyder
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Nukhba Zia.

Additional file

Additional file 1.

Patient and data flow for KiTBIR.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Mehmood, A., Zia, N., Hoe, C. et al. Traumatic brain injury in Uganda: exploring the use of a hospital based registry for measuring burden and outcomes. BMC Res Notes 11, 299 (2018). https://doi.org/10.1186/s13104-018-3419-1

Download citation

Keywords

  • Traumatic brain injuries
  • Registry
  • Uganda
  • Injury
  • Low-income country
  • Trauma
  • Surveillance

BMC Research Notes

ISSN: 1756-0500

Contact us