LEVEL AND SOCIO-DEMOGRAPHIC PREDICTORS OF ELECTRONIC MEDICAL RECORDS UTILIZATION AMONG HEALTHCARE WORKERS AT MBAGATHI COUNTY REFERRAL HOSPITAL, KENYA
Abstract
Purpose of the Study: This study sought to assess the level of Electronic Medical Records (EMR) utilization and determine how socio-demographic characteristics influenced utilization patterns among healthcare workers at Mbagathi County Referral Hospital, Nairobi, Kenya.
Statement of the Problem: Despite over a decade of EMR implementation in Kenyan public hospitals, utilization gaps continue to persist, especially in public healthcare facilities. These gaps are linked to challenges such as unreliable internet connectivity, insufficient hardware, low uptake among some healthcare workers, and data inconsistencies between electronic and paper-based records.
Methodology: The study adopted an analytical cross-sectional design integrating quantitative and qualitative approaches. A sample of 210 healthcare workers was drawn from a target population of 449 using stratified random sampling proportional to cadre size. Data were collected using a semi-structured self-administered questionnaire and a focus group discussion involving eight purposively selected participants. EMR utilization was measured through self-reported frequency of use. Quantitative data were analyzed using descriptive statistics, Chi-square tests, and binary logistic regression in SPSS Version 24, while qualitative data were analyzed thematically.
Findings: The findings revealed that the majority of respondents, 72.1%, reported full EMR utilization, while 27.9% were classified as partial utilizers. Age was significantly associated with EMR utilization, χ² = 18.691, p = 0.001, with the highest full utilization recorded among healthcare workers aged 26–35 years at 50.7%. Education level was also significantly associated with EMR utilization, χ² = 13.900, p = 0.003, with diploma holders recording the highest full utilization at 70.7%.
Conclusion: The study concluded that the majority of healthcare workers at Mbagathi County Referral Hospital were utilizing EMRs. Age and education level were significant socio-demographic predictors of EMR utilization, while gender did not significantly influence utilization patterns.
Recommendation: The study recommends targeted practical EMR training and refresher programs, particularly for older healthcare workers and partial utilizers, to bridge existing utilization gaps and strengthen effective EMR use in routine healthcare service delivery.
Keywords: Socio-Demographic, Predictors, Electronic, Medical Records, Healthcare Workers
References
Adeniyi, A. O., Arowoogun, J. O., Chidi, R., Okolo, C. A., & Babawarun, O. (2024). The impact of electronic health records on patient care and outcomes: A comprehensive review. World Journal of Advanced Research and Reviews, 21(2), 1446-1455.
Ajwang, B., Komen, A., Ngaira, D., & Wanjala, P. (2019). Policy Brief: Enhancing health information system for evidence based decision making in the health sector. Retrieved from: https://www.health.go.ke/wp-content/uploads/2019/01/HIS-POLICY-BRIEF-.pdf
Alhur, A. (2024). Overcoming electronic medical records adoption challenges in Saudi Arabia. Cureus, 16(2), 1-7.
Allen, O. S., Fields, L. S., Sweeney, M. J., Als, S. L., Seiple, W. H., & Shrivastava, A. (2025). The impact of workflow modifications in an electronic medical record on tertiary service referrals for patients with visual impairment in New York city. Clinical Ophthalmology, 5(2), 3693-3702.
Alrasheeday, A. M., Alshammari, B., Alkubati, S. A., Pasay-An, E., Albloushi, M., & Alshammari, A. M. (2023). Nurses' attitudes and factors affecting use of electronic health record in Saudi Arabia. In Healthcare (Vol. 11, No. 17, p. 2393). MDPI.
Bagherian, H., & Sattari, M. (2022). Health information system in developing countries: a review on the challenges and causes of success and failure. Medical Journal of the Islamic Republic of Iran, 36(2), 111.
Bostan, S., Johnson, O. A., Jaspersen, L. J., & Randell, R. (2024). Contextual barriers to implementing open-source electronic health record systems for low-and lower-middle-income countries: scoping review. Journal of Medical Internet Research, 26, e45242.
Chatta, H. P., Thrigulla, S. R., Mane, S., & Prasad, G. P. (2024). Development of Medical Record Science in India and Transition from Paper-based Record to Electronic Medical Records: A Historical Account Focusing on the Ayush Sector. Journal of Indian Medical Heritage, 3(1), 15-26.
Chepkirui, M., Dellicour, S., Musuva, R., Odero, I., Omondi, B., Omondi, B., & Taegtmeyer, M. (2025). Missed opportunities for digital health data use in healthcare decision-making: A cross-sectional digital health landscape assessment in Homa Bay county, Kenya. PLOS Digital Health, 4(6), e0000870.
Essuman, L. R., Apaak, D., Ansah, E. W., Sambah, F., Ansah, J. E., Opare, M., & Ahinkorah, B. O. (2020). Factors associated with the utilization of electronic medical records in the Eastern Region of Ghana. Health Policy and Technology, 9(3), 362-367.
Feldacker, C., Mugwanya, R., Irongo, D., Kathumba, D., Chiwoko, J., Kitsao, E., & Tweya, H. (2023). A community-based, mobile electronic medical record system app for high-quality, integrated antiretroviral therapy in Lilongwe, Malawi: design process and pilot implementation. JMIR Formative Research, 7, e48671.
González-Anleo, J. M., Delbello, L., Martínez-Gonzálo, J. M., & Gómez, A. (2024). Sociodemographic impact on the adoption of emerging technologies. Journal of Small Business Strategy, 34(2), 42-50.
Ifinedo, P. (2020). The moderating effects of demographic and individual characteristics on nurses' acceptance of information systems: A Canadian study. International Journal of Medical Informatics, 87, 27-35.
Jagannath, S., Sarcevic, A., Multak, N., & Myers, S. (2021). Understanding paper-based documentation practices in medical resuscitations to inform the design of electronic documentation tools. Pediatric Emergency Care, 37(8), e436-e442.
Jimma, B. L., & Enyew, D. B. (2022). Barriers to the acceptance of electronic medical records from the perspective of physicians and nurses: A scoping review. Informatics in Medicine Unlocked, 31, 100991.
Kessy, E. C., Kibusi, S. M., & Ntwenya, J. E. (2024). Electronic medical record systems data use in decision-making and associated factors among health managers at public primary health facilities, Dodoma region: a cross-sectional analytical study. Frontiers in Digital Health, 5, 1-13.
Liang, J., Li, Y., Zhang, Z., Shen, D., Xu, J., Zheng, X., & Zhang, J. (2021). Adoption of electronic health records (EHRs) in China during the past 10 years: consecutive survey data analysis and comparison of Sino American challenges and experiences. Journal of Medical Internet Research, 23(2), e24813.
Malacon, K., Touponse, G., Yoseph, E., Li, G., Wei, P. J., Kicielinski, K., & Zygourakis, C. (2024). Gender differences in electronic health record usage among surgeons. JAMA Network Open, 7(7), e2421717-e2421717.
Mudavadi, O. M., Nyaberi, J. M., & Nyamai, J. (2023). Health system factors contributing to the utilization of EMR among health workers in selected level III and IV hospitals in Siaya County, Kenya. International Academic Journal of Health, Medicine and Nursing, 2(1), 363-379.
Ndemi, C. K. B. (2025). Uptake of electronic medical record system by health workers in selected public hospitals in Kiambu county, Kenya (Doctoral dissertation, Kenyatta University).
Onyeaka, H. K., Romero, P., Healy, B. C., & Celano, C. M. (2021). Age differences in the use of health information technology among adults in the United States: An analysis of the Health Information National Trends Survey. Journal of Aging and Health, 33(1-2), 147-154.
Oumer, A. (2020). Utilization of Electronic Medical Record and Associated Factors Among Health Professionals in Public Health Facilities with Service Delivery, Eastern Ethiopia.
Rahal, R. M., Mercer, J., Kuziemsky, C., & Yaya, S. (2021). Factors affecting the mature use of electronic medical records by primary care physicians: a systematic review. BMC Medical Informatics and Decision Making, 21(1), 67-82.
Senishaw, A. F., Tilahun, B. C., Nigatu, A. M., Mengiste, S. A., & Standal, K. (2023). Willingness to use electronic medical record (EMR) system and its associated factors among health professionals working in Amhara region Private Hospitals 2021, Ethiopia. PLoS One, 18(5), e0282044.
Sezis, C. (2023). An Academic Review About Human Psychology Demographics Features. Collaborate, Current Science, 5(5-9), 238-260.
Singh, A., Jadhav, S., & Roopashree, M. R. (2020). Factors to overcoming barriers affecting electronic medical record usage by physicians. Indian Journal of Community Medicine: Official Publication of Indian Association of Preventive & Social Medicine, 45(2), 168.
Thacharodi, A., Singh, P., Meenatchi, R., Tawfeeq Ahmed, Z. H., Kumar, R. R., V, N., & Hassan, S. (2024). Revolutionizing healthcare and medicine: The impact of modern technologies for a healthier future: A comprehensive review. Health Care Science, 3(5), 329-349.
Uslu, A., & Stausberg, J. (2021). Value of the electronic medical record for hospital care: update from the literature. Journal of Medical Internet Research, 23(12), e26323.
Walsh, B., Mac Domhnaill, C., & Mohan, G. (2021). Developments in healthcare information systems in Ireland and internationally. Dublin: The Economic and Social Research Institute, 1-81.
