A comparative review of mobile health and electronic health utilization in sub-Saharan African countries
Abstract
This study distinguished between the application of e-health and m-health technologies in sub-Saharan African (SSA) countries based on the dimensions of use, targeted diseases or health conditions, locations of use, and beneficiaries (types of patients or health workers) in a country specific context. It further characterized the main opportunities and challenges associated with these dimensions across the sub-region. A systematic review of the literature was conducted on 66 published peer reviewed articles. The review followed the scientific process of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines of identification, selection, assessment, synthesis and interpretation of findings. The results of the study showed that m-health was prevalent in usage for promoting information for treatment and prevention of diseases as well as serving as an effective technology for reminders towards adherence. For e-health, the uniqueness lay in data acquisition and patients' records management; diagnosis; training and recruitment. While m-health was never used for monitoring or training and recruitment, e-health on the other hand could not serve the purpose of reminders or for reporting cases from the field. Both technologies were however useful for adherence, diagnosis, disease control mechanisms, information provision, and decision-making/referrals. HIV/AIDS, malaria, and maternal (postnatal and antenatal) healthcare were important in both m-healt…
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Osterberg, L., & Blaschke, T. (2005) · New England Journal of Medicine · doi:10.1056/nejmra050100 · Cited by 7,974 · see citing works
Lester, R. T., Ritvo, P., Mills, E. J., Kariri, A., Karanja, S., Chung, M. H., Jack, W., Habyarimana, J., Sadatsafavi, M., Najafzadeh, M., et al. (2010) · The Lancet · doi:10.1016/s0140-6736(10)61997-6 · Cited by 1,278 · cited 4× · see citing works
“We found that most studies on HIV were mostly related to adherence and reminders of ART treatment, patients’ records keeping and counselling sessions [21, 40, 88].”
BackgroundInfluentialPop-Eleches, C., Thirumurthy, H., Habyarimana, J. P., Zivin, J. G., Goldstein, M. P., de Walque, D., MacKeen, L., Haberer, J., Kimaiyo, S., Sidle, J., et al. (2011) · AIDS · doi:10.1097/qad.0b013e32834380c1 · Cited by 982 · see citing works
Healthcare via Cell Phones: A Systematic Review
Krishna, S., Boren, S. A., & Balas, E. A. (2009) · Telemedicine and e-Health · doi:10.1089/tmj.2008.0099 · Cited by 882 · see citing works
Free, C., Phillips, G., Felix, L., Galli, L., Patel, V., & Edwards, P. (2010) · BMC Research Notes · doi:10.1186/1756-0500-3-250 · Cited by 539 · see citing works
Zurovac, D., Sudoi, R. K., Akhwale, W. S., Ndiritu, M., Hamer, D. H., Rowe, A. K., & Snow, R. W. (2011) · The Lancet · doi:10.1016/s0140-6736(11)60783-6 · Cited by 403 · see citing works
E-health in low- and middle-income countries: findings from the Center for Health Market Innovations
Lewis, T., Synowiec, C., Lagomarsino, G., & Schweitzer, J. (2012) · Bulletin of the World Health Organization · doi:10.2471/blt.11.099820 · Cited by 319 · see citing works
Mobile phones improve antenatal care attendance in Zanzibar: a cluster randomized controlled trial
Lund, S., Nielsen, B. B., Hemed, M., Boas, I. M., Said, A., Said, K., Makungu, M. H., & Rasch, V. (2014) · BMC Pregnancy and Childbirth · doi:10.1186/1471-2393-14-29 · Cited by 301 · see citing works
Leon, N., Schneider, H., & Daviaud, E. (2012) · BMC Medical Informatics and Decision Making · doi:10.1186/1472-6947-12-123 · Cited by 200 · see citing works
Douglas, G. P., Gadabu, O. J., Joukes, S., Mumba, S., McKay, M. V., Ben-Smith, A., Jahn, A., Schouten, E. J., Landis Lewis, Z., van Oosterhout, J. J., et al. (2010) · PLoS Medicine · doi:10.1371/journal.pmed.1000319 · Cited by 149 · see citing works
Kiberu, V. M., Mars, M., & Scott, R. E. (2017) · African Journal of Primary Health Care & Family Medicine · doi:10.4102/phcfm.v9i1.1277 · Cited by 147 · cited 1× · see citing works
“[5] highlighted that factors related to the excessive burden of disease in Africa (for instance; the shortage of health professionals; a rapidly growing population; the low median age of people), are the reasons for this expansion.”
BackgroundLeon, N., Surender, R., Bobrow, K., Muller, J., & Farmer, A. (2015) · BMC Family Practice · doi:10.1186/s12875-015-0289-7 · Cited by 126 · cited 3× · see citing works
“Only a case [23] reported using mobile phone text messaging to improve adherence to clinic visits mainly by adults, and subsequent treatment for this health condition.”
BackgroundCrankshaw, T., Corless, I. B., Giddy, J., Nicholas, P. K., Eichbaum, Q., & Butler, L. M. (2010) · AIDS Patient Care and STDs · doi:10.1089/apc.2010.0146 · Cited by 119 · see citing works
Using cell phones to collect postpartum hemorrhage outcome data in rural Ghana
Andreatta, P., Debpuur, D., Danquah, A., & Perosky, J. (2011) · International Journal of Gynecology & Obstetrics · doi:10.1016/j.ijgo.2010.11.020 · Cited by 88 · see citing works
Mangwi Ayiasi, R., Kolsteren, P., Batwala, V., Criel, B., & Orach, C. G. (2016) · PLOS ONE · doi:10.1371/journal.pone.0153051 · Cited by 84 · see citing works
Evans, G. F., Shirk, A., Muturi, P., & Soliman, E. Z. (2017) · Global Heart · doi:10.1016/j.gheart.2016.12.003 · Cited by 54 · see citing works
Colven, R., Shim, M.-H. M., Brock, D., & Todd, G. (2011) · Telemedicine and e-Health · doi:10.1089/tmj.2010.0163 · Cited by 52 · cited 2× · see citing works
“The educational benefit of webconferencing by way of referring primary care physicians could be sustainable and would ultimately enhance the quality of dermatological care [59].”
BackgroundTsang, M. W., & Kovarik, C. L. (2011) · International Journal of Dermatology · doi:10.1111/j.1365-4632.2010.04790.x · Cited by 50 · see citing works
Odero, W., Rotich, J., Yiannoutsos, C. T., Ouna, T., & Tierney, W. M. (2007) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2006.12.007 · Cited by 37 · see citing works
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Telemedicine in middle eastern countries: progress, barriers, and policy recommendations
Al-Samarraie, H., Ghazal, S., Alzahrani, A. I., & Moody, L. (2020) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2020.104232 · Cited by 179 · see citing works
Self-citationTelemedicine use in Sub-Saharan Africa: Barriers and policy recommendations for Covid-19 and beyond
Dodoo, J. E., Al-Samarraie, H., & Alzahrani, A. I. (2021) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2021.104467 · Cited by 125 · see citing works
“Sub-Saharan African (SSA) countries have witnessed some improvement in healthcare provision through the use of telemedicine [1].”
BackgroundSelf-citation
- Authors
- Bervell, B., & Al-Samarraie, H.
- Affiliations
- University of Cape Coast (GH)
- Venue
- Social Science & Medicine
- Publisher
- Elsevier BV
- Published
- 2019-07
- Volume
- 232
- Pages
- 1-16
- ISSN
- 0277-9536 (ISSN-L)
- OpenAlex
- W2940642480
- Cited by
- 74
- References
- 19
- Citations by year
- 2026: 6 · 2025: 11 · 2024: 17 · 2023: 18 · 2022: 3 · 2021: 9 · 2020: 8 · 2019: 2
- FWCI
- 1.01
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Social Science & Medicine (publishedVersion)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (acceptedVersion)
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Physical Sciences › Computer Science › Information Systems › ICT in Developing Communities
- Health Sciences › Health Professions › Health Information Management › Health, Technology, Consumer Behavior
- Keywords
- mobile health, e-health, sub-Saharan Africa, health technology utilization, HIV/AIDS, malaria, maternal health, health information provision, medical records management, rural health care
- MeSH terms
- Clinical Decision-Making, Smartphone, Communicable Disease Control, Health Workforce, Health Promotion, Humans, Inservice Training, Patient Compliance, Preventive Health Services, Referral and Consultation, Telemedicine, Africa South of the Sahara, Electronic Health Records
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