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Developing an Interoperable Framework for Accessing Electronic Health Records by Emergency Medical Services in Uganda: A Case Study of City Ambulance, Kampala

Chapter One
Background of the Study
Electronic Health Records (EHRs) have been widely adopted as a practical solution for managing health data, ensuring its quality and integrity, and making it accessible to healthcare providers and patients when needed (Nowrozy et al., 2024). Globally recognized as a best practice, EHRs support the principles of Findable, Accessible, Interoperable, and Reusable (FAIR) health data, offering a competitive advantage to healthcare institutions (Johnson, Neuss, and Detmer, 2021). In Uganda, the increasing adoption of EHRs across healthcare facilities has the potential to revolutionize patient care by centralizing health information. However, interoperability challenges often prevent Emergency Medical Services (EMS) from accessing critical patient data during emergencies. Despite global advancements, the adoption of EHRs in low-income countries like Uganda is hindered by a lack of standards, insufficient guidelines, and limited support services (Aminabee, 2024).

Globally, the inability to access timely medical histories is a significant contributor to mortality, accounting for 45%–54% of all deaths (National Academies of Sciences, Engineering, and Medicine, 2018). Conditions such as sepsis and myocardial infarction, which require prompt and high-quality emergency care, can rapidly become fatal if untreated. The burden of such deaths is disproportionately higher in low- and middle-income countries (LMICs), where the mortality rate is approximately three times that of high-income countries (Williamson et al., 2020). Despite this urgent need, acute care systems in LMICs have historically been underfunded and under-researched, with a focus instead on disease-specific care. The ability to access EHRs has received limited attention in these regions, resulting in fragmented and underdeveloped systems (Luyckx et al., 2021). This is exacerbated by issues such as data loss, mishandling, misuse, and inaccessibility when needed. Limited access to timely and accurate health records, particularly in emergencies, can compromise the quality and efficiency of care. An interoperable framework for accessing EHRs by EMS providers could significantly improve decision-making, reduce medical errors, and enhance patient outcomes.

In Uganda, 84% of maternal deaths are preventable, yet significant delays in accessing patient health information within healthcare facilities contribute to these fatalities (Namagembe et al., 2022). The absence of standardized protocols and compatible data-sharing systems across healthcare providers has resulted in fragmented EHRs, complicating continuity of care during emergencies. The need for interoperability is further emphasized by the necessity for seamless communication between EMS teams and hospitals to ensure real-time access to medical histories, allergies, medications, and other critical health information. Without access to complete medical records, healthcare providers may lack essential information, leading to delayed treatment, misdiagnoses, or improper care. The World Health Organization (WHO) estimates that medical errors, often caused by miscommunication, missing data, or incomplete records, are a leading cause of death globally (Hossain et al., 2022). While Uganda has made strides in developing health information systems, a comprehensive framework enabling interoperability between EMS and healthcare facilities remains unrealized. Technical, regulatory, and infrastructural challenges, including data security concerns, system incompatibility, and limited digital literacy, have impeded progress. This study seeks to address these challenges by developing a framework that supports EMS in accessing health records efficiently.

Statement of the Problem
The adoption of EHRs has emerged as a promising solution to improve healthcare data management, ensure data integrity, and enhance the accessibility of patient information for healthcare providers and patients. In Uganda, the growing implementation of EHRs in healthcare facilities presents an opportunity to centralize patient health information, potentially transforming patient care, particularly in emergency medical services (EMS). However, the lack of interoperability among EHR systems remains a significant barrier, especially in emergencies where timely access to patient data is critical.

Despite the increasing adoption of EHRs, challenges such as fragmented data systems, the absence of standardized protocols, and insufficient support services continue to hinder their full potential in Uganda (Fuhr, 2019). Accurate and immediate access to patient data is essential, yet delays or gaps in accessing this information, compounded by fragmented and incompatible EHR systems, can lead to misdiagnosis, inappropriate treatment, and preventable deaths. In Uganda, these challenges are particularly evident in maternal healthcare, where 84% of maternal deaths are preventable with timely intervention (Patterton, 2016). There is an urgent need for an interoperable EHR framework that facilitates seamless data exchange between EMS providers and healthcare institutions. Such a system would enhance decision-making, reduce medical errors, and improve the efficiency and quality of emergency care, potentially saving lives. This study aims to explore the development of an interoperable framework for accessing EHRs by EMS in Uganda, using City Ambulance in Kampala as a case study.

Purpose of the Study
The purpose of this study is to develop an interoperable framework for accessing electronic health records by emergency medical services in Uganda, with a focus on City Ambulance in Kampala as a case study.

Objectives of the Study

• To examine the influence of software integration on accessing electronic health records by emergency medical services.
• To determine the influence of healthcare provider collaboration on accessing electronic health records by emergency medical services.
• To assess the relationship between user training and capacity building on accessing electronic health records by emergency medical services.

Research Questions

• What is the influence of software integration on accessing electronic health records by emergency medical services?
• What is the influence of healthcare provider collaboration on accessing electronic health records by emergency medical services?
• What is the relationship between user training and capacity building on accessing electronic health records by emergency medical services?

Conceptual Background
Interoperable Framework for Accessing Electronic Health Records by Emergency Medical Services
Interoperable Framework | Electronic Health Records

Literature Review
2.1 Software Integration
According to the U.S. Department of Health and Human Services (2019), EHR systems help reduce medication errors, improve clinical decision-making, and streamline communication between EMS, hospitals, and primary care providers. However, one of the most significant barriers to integrating EMS with EHRs is the lack of interoperability between various healthcare IT systems. EHRs are often maintained on disparate platforms with different standards, making it difficult for EMS systems to access and exchange data seamlessly. Over 40% of hospitals use different EHR systems, which impedes communication between pre-hospital providers and healthcare facilities. Ensuring the privacy and security of patient data is another critical concern (Rasmi et al., 2020).

2.2 Healthcare Provider Collaboration
One of the most significant challenges in collaborative EHR access is the issue of interoperability. Different healthcare institutions often use different EHR systems, which may not communicate effectively with one another. As a result, EMS providers may struggle to access up-to-date, accurate patient information, particularly in systems where data is fragmented or stored in incompatible formats. EMS providers report difficulties accessing EHR data due to technical barriers such as lack of system compatibility and inconsistent data exchange standards (Wu, Zeng, and Wang, 2020).

2.3 User Training and Capacity Building
Another major challenge for EMS teams is the time constraints imposed by the nature of their work. EMS personnel work in high-pressure environments, often with little downtime. Additionally, shift work and frequent interruptions can hinder the opportunity for training sessions, making it difficult to ensure consistent and adequate training for all team members. Despite the implementation of EHR systems, a lack of dedicated training time often leads to gaps in knowledge among EMS providers. Training sessions that are too short or not well-integrated into the daily work schedule may fail to equip EMS personnel with the skills necessary to use EHR systems effectively under emergency conditions (McLeod and Lomas, 2023).

Methodology
Research Design
A descriptive cross-sectional survey will be conducted, employing both qualitative and quantitative approaches.

Area of the Study
The study will be carried out at City Ambulance in Kampala.

Target Population
The study will involve employees from various departments at City Ambulance.

Sample Size, Techniques, and Selection
Using Krejcie and Morgan’s (1970) table for sample size determination, a sample size of 196 employees will be selected from a total population of 401 employees.

Research Instrument
Questionnaires will be used to collect primary data necessary to answer the research questions and achieve the study objectives.

Interviewing
Interviews will also be conducted with management staff at City Ambulance to gather additional insights.

Data Sources
Data will be collected from both primary and secondary sources.

References
Aminabee, S., 2024. The future of healthcare and patient-centric care: Digital innovations, trends, and predictions. In Emerging Technologies for Health Literacy and Medical Practice (pp. 240-262). IGI Global.
Hossain, M.S., Karuniawati, H., Jairoun, A.A., Urbi, Z., Ooi, D.J., John, A., Lim, Y.C., Kibria, K.K., Mohiuddin, A.K.M., Ming, L.C., and Goh, K.W., 2022. Colorectal cancer: a review of carcinogenesis, global epidemiology, current challenges, risk factors, preventive and treatment strategies. Cancers, 14(7), p.1732.
Johnson, K.B., Neuss, M.J., and Detmer, D.E., 2021. Electronic health records and clinician burnout: a story of three eras. Journal of the American Medical Informatics Association, 28(5), pp.967-973.
Luyckx, V.A., Al-Aly, Z., Bello, A.K., Bellorin-Font, E., Carlini, R.G., Fabian, J., Garcia-Garcia, G., Iyengar, A., Sekkarie, M., Van Biesen, W., and Ulasi, I., 2021. Sustainable development goals relevant to kidney health: an update on progress. Nature Reviews Nephrology, 17(1), pp.15-32.
McLeod, J., and Lomas, E., 2023. Record DNA: reconceptualising digital records as the future evidence base. Archival Science, 23(3), pp.411-446.
Namagembe, I., Kiwanuka, N., Byamugisha, J.K., Ononge, S., Beyeza-Kashesya, J., Kaye, D.K., Moffett, A., Aiken, C.E., and Nakimuli, A., 2022. Why mothers die at a busy tertiary urban hospital in Kampala, Uganda: a comprehensive review of maternal deaths 2016-2018 and implications for quality improvement to reduce deaths. African Health Sciences, 22(2), pp.489-499.
National Academies of Sciences, Engineering, and Medicine, 2018. Crossing the global quality chasm: improving health care worldwide.
Nowrozy, R., Ahmed, K., Kayes, A.S.M., Wang, H., and McIntosh, T.R., 2024. Privacy preservation of electronic health records in the modern era: A systematic survey. ACM Computing Surveys, 56(8), pp.1-37.
Rasmi, M., Alazzam, M.B., Alsmadi, M.K., Almarashdeh, I.A., Alkhasawneh, R.A., and Alsmadi, S., 2020. Healthcare professionals’ acceptance of Electronic Health Records system: Critical literature review (Jordan case study). International Journal of Healthcare Management.
Williamson, Elizabeth J., Alex J. Walker, Krishnan Bhaskaran, Seb Bacon, Chris Bates, Caroline E. Morton, Helen J. Curtis et al. “OpenSAFELY: factors associated with COVID-19 death in 17 million patients.” Nature 584, no. 7821 (2020): 430.
Wu, P., Zeng, D., and Wang, Y., 2020. Matched learning for optimizing individualized treatment strategies using electronic health records. Journal of the American Statistical Association.