Determinants of The Willingness to Adopt Telehealth Technology Among Health Professionals in a Tertiary Hospital
DOI:
https://doi.org/10.30953/thmt.v10.621Keywords:
digital healthcare, electronic health records, Ghana, healthcare professionals, telehealth adoption, telehealth technologyAbstract
Background: Digitalization in healthcare, particularly through electronic health records and telehealth, is transforming healthcare delivery globally. However, challenges in adoption persist, particularly in resource-limited settings.
Aim: This study aimed to determine the factors influencing the willingness to adopt telehealth technology among health professionals in a tertiary hospital in Ghana.
Methods: A cross-sectional study was conducted from September 2021 to May 2022 at Korle Bu Teaching Hospital, targeting departments that had transitioned to the use of electronic health records. Stratified random sampling was used to recruit 223 doctors and nurses. Data were collected electronically and analyzed using SPSS version 26. Chisquare tests and multivariate logistic regression were applied to determine the relationship between variables.
Results: Of the 223 participants, 217 were included in the analysis. Among the 217 participants, 48% were willing to adopt telehealth technology. Factors associated with willingness to adopt telehealth included sex, qualification, profession, department, years in healthcare, work experience, knowledge and training in information technologies (IT), high IT proficiency, familiarity with telemedicine apps, and familiarity with telemedicine tools. These factors were significantly associated with willingness to adopt telehealth technology. From the logistic regression analysis, age group, familiarity with telehealth, and working years were significant predictors.
Conclusion: Demography and organizational factors impacted telehealth adoption at Korle-bu Teaching Hospital. To ensure successful integration into routine clinical practice, it is essential to implement hands-on training, tailor departmental strategies, and institute supportive policies, including digital infrastructure and literacy initiatives in the health facilities
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References
WHO WHO. Telemedicine and Digital Health Strategy. Published online 2019.
Allison CO, Prucka SK, Fitzgerald-Butt SM, et al. Characterization of adults concerning the use of a hypothetical mHealth application addressing stress-overeating: an online survey. Int J Environ Res Public Health. 2024;8 1):1-11. doi:10.1371/journal.pone.0309119
Putteeraj M, Bhungee N, Somanah J, Moty N. Assessing E-Health adoption readiness using diffusion of innovation theory and the role mediated by each adopter’s category in a Mauritian context. Int Health. 2022;14 3):236-249. doi:10.1093/inthealth/ihab035
Owoyemi A, Owoyemi J, Osiyemi A, Boyd A. Artificial Intelligence for Healthcare in Africa. Front Digit Heal. 2020;2 July). doi:10.3389/fdgth.2020.00006
Bee P, Lovell K, Airnes Z, Pruszynska A. Embedding telephone therapy in statutory mental health services: A qualitative, theory-driven analysis. BMC Psychiatry. 2016;16 1):1-11. doi:10.1186/s12888-016-0761-5
Shaarani I, Jounblat M, Jounblat H, Ghanem A, Mansour R, Taleb R. Developing and Validating a Tool to Assess Telemedicine Acceptance Among Physicians During Pandemic Using a Technology Acceptance Model. Telemed e-Health. 2023;29 6):903-911. doi:10.1089/tmj.2022.0348
Feroz A, Kadir MM, Saleem S. Health systems readiness for adopting mhealth interventions for addressing non-communicable diseases in low- and middle-income countries: a current debate. Glob Health Action. 2018;11 1). doi:10.1080/16549716.2018.1496887
Kim MO, Coiera E, Magrabi F. Problems with health information technology and their effects on care delivery and patient outcomes: A systematic review. J Am Med Informatics Assoc. 2017;24 2):246-260. doi:10.1093/jamia/ocw154
Su XV, Sutiman I, Suut SKWM, et al. Perception of primary care doctors towards telemedicine in Kuching, Sarawak: A cross-sectional study. Malaysian Fam Physician. 2024;19. doi:10.51866/oa.505
Sin DYE, Guo X, Yong DWW, et al. Assessment of willingness to Tele-monitoring interventions in patients with type 2 diabetes and/or hypertension in the public primary healthcare setting. BMC Med Inform Decis Mak. 2020;20 1):1-11. doi:10.1186/s12911-020-1024-4
Shi J, Guo Y, Yang F, Kulkarni S. Telehealth use and work stress among Chinese health care providers during the COVID-19 pandemic. Decis Mak Anal. 2023;2 1):1-10. doi:10.55976/dma.2202411881-10
Onsongo S, Kamotho C, Rinke De Wit TF, Lowrie K. Experiences on the Utility and Barriers of Telemedicine in Healthcare Delivery in Kenya. Int J Telemed Appl. 2023;2023. doi:10.1155/2023/1487245
Kyei KA, Onajah GN, Daniels J. The emergence of telemedicine in a low-middle-income country: challenges and opportunities. Ecancermedicalscience. 2024;18:1-9. doi:10.3332/ecancer.2024.1679
Mensah NK, Adzakpah G, Kissi J, et al. Health professional’s readiness and factors associated with telemedicine implementation and use in selected health facilities in Ghana. Heliyon. 2023;9 3):e14501. doi:10.1016/j.heliyon.2023.e14501
Gbolahan O, Kokori E, Osaghae O, Lawal ZD, Olaogun T. Telehealth in Africa: evolution and transformative impact before, during and after COVID-19: a narrative review. J Glob Heal Sci. 2023;5 2):1-11. doi:10.35500/jghs.2023.5.e14
Stuijt DG, van Doeveren EEM, Kos M, et al. Remote Patient Monitoring Using Mobile Health Technology in Cancer Care and Research: Patients’ Views and Preferences. JCO Clin Cancer Informatics. 2024;8. doi:10.1200/CCI.24.00092
Schürmann F, Westmattelmann D, Schewe G. Factors Influencing Telemedicine Adoption Among Health Care Professionals: Qualitative Interview Study. JMIR Form Res. 2025;9. doi:10.2196/54777
Yan M, Sun W, Tan C, Wu Y, Liu Y. Analysis of Factors Influencing the Willingness of Chinese Older Adults to Use mHealth Devices: Nationwide Cross-Sectional Survey Study. J Med Internet Res. 2025;27. doi:10.2196/66804
Rouidi M, Elouadi A, Hamdoune A. Acceptance and use of telemedicine technology by health professionals: Development of a conceptual model. Digit Heal. 2022;8. doi:10.1177/20552076221081693
Ojo JO, Ipinnimo TM, Afolayan AC, et al. Factors associated with willingness to use mHealth interventions for medication adherence among people living with HIV attending a tertiary hospital in sub-Saharan Africa. PLoS One. 2024;19 8). doi:10.1371/journal.pone.0309119
Mensah M. Health Professionals ’ Preference and Use of Electronic Health Records in a Tertiary Care Hospital in Ghana : A Cross-Sectional Study.
Knop M, Mueller M, Niehaves B. Investigating the use of telemedicine for digitally mediated delegation in team-based primary care: Mixed methods study. J Med Internet Res. 2021;23 8). doi:10.2196/28151
Xiong S, Lu H, Peoples N, et al. Digital health interventions for non-communicable disease management in primary health care in low-and middle-income countries. npj Digit Med. 2023;6 1). doi:10.1038/s41746-023-00764-4
Kung LH, Yan YH, Kung CM. Exploring Telemedicine Usage Intention Using Technology Acceptance Model and Social Capital Theory. Healthc. 2024;12 13):1-9. doi:10.3390/healthcare12131267
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Copyright (c) 2026 Michael Mensah, MSc, Sampson Opoku, PhD, Annabel Anum, MA, Theophilus Brocke, MPH, Enoch Makafui Mensah, BSc, Ernest Obeng Nsiah, BSc, Yaa Adutwumwaa Owusu-Ansah, FGCNM, Ernest Asamoa, PhD(c)
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