The DOI matches its Crossref record; 112 of the 112 references it cites were found in a registry or an index.
The potential use of digital health technologies in the African context: a systematic review of evidence from Ethiopia
Open accessPublished version of a preprint
Abstract
The World Health Organization (WHO) recently put forth a Global Strategy on Digital Health 2020–2025 with several countries having already achieved key milestones. We aimed to understand whether and how digital health technologies (DHTs) are absorbed in Africa, tracking Ethiopia as a key node. We conducted a systematic review, searching PubMed-MEDLINE, Embase, ScienceDirect, African Journals Online, Cochrane Central Registry of Controlled Trials, ClinicalTrials.gov, and the WHO International Clinical Trials Registry Platform databases from inception to 02 February 2021 for studies of any design that investigated the potential of DHTs in clinical or public health practices in Ethiopia. This review was registered with PROSPERO ( CRD42021240645 ) and it was designed to inform our ongoing DHT-enabled randomized controlled trial (RCT) (ClinicalTrials.gov ID: NCT04216420 ). We found 27,493 potentially relevant citations, among which 52 studies met the inclusion criteria, comprising a total of 596,128 patients, healthy individuals, and healthcare professionals. The studies involved six DHTs: mHealth (29 studies, 574,649 participants); electronic health records (13 studies, 4534 participants); telemedicine (4 studies, 465 participants); cloud-based application (2 studies, 2382 participants); information communication technology (3 studies, 681 participants), and artificial intelligence (1 study, 13,417 participants). The studies targeted six health conditions: maternal and child health (15), infectious diseases (14), non-communicable diseases (3), dermatitis (1), surgery (4), and general health conditions (15). The outcomes of interest were feasibility, usability, willingness or readiness, effectiveness, quality improvement, and knowledge or attitude toward DHTs. Five studies involved RCTs. The analysis showed that although DHTs are a relatively recent phenomenon in Ethiopia, their potential harnessing clinical and public health practices are highly visible. Their adoption and implementation in full capacity require more training, access to better devices such as smartphones, and infrastructure. DHTs hold much promise tackling major clinical and public health backlogs and strengthening the healthcare ecosystem in Ethiopia. More RCTs are needed on emerging DHTs including artificial intelligence, big data, cloud, cybersecurity, telemedicine, and wearable devices to provide robust evidence of their potential use in such settings and to materialize the WHO’s Global Strategy on Digital Health.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Figures
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“This infrastructure gap hinders the development and deployment of practical systems such as health chatbot applications in resource-constrained regions like Ethiopia, despite their strong potential to reduce pressure on overstretched services and lower operational costs (Manyazewal et al., 2021;Bank, 2023).”
From Improving Amharic Information Retrieval with Translative and Multi-Agent Debate Retrieval Augmented Generation (2026) · cites this paper as Manyazewal et al., 2021
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“People living in LMICs, such as many countries in Africa, are at high risk of many health conditions compared to those living in high-income countries while having the most limited access to health innovations such as digital health intervention.”
From Effectiveness of digital health interventions on blood pressure control, lifestyle behaviours and adherence to medication in patients with hypertension in low-income and middle-income countries: a systematic review and meta-analysis of randomised controlled trials (2024) · cites this paper as [20]
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Human-computer collaboration for skin cancer recognition
Tschandl, P., Rinner, C., Apalla, Z., Argenziano, G., Codella, N., Halpern, A., Janda, M., Lallas, A., Longo, C., Malvehy, J., et al. (2020) · Nature Medicine · doi:10.1038/s41591-020-0942-0 · Cited by 1,024
Artificial intelligence powers digital medicine
Fogel, A. L., & Kvedar, J. C. (2018) · npj Digital Medicine · doi:10.1038/s41746-017-0012-2 · Cited by 473
Daly, A. C., Prendergast, M. E., Hughes, A. J., & Burdick, J. A. (2021) · Cell · doi:10.1016/j.cell.2020.12.002 · Cited by 354
Technology approaches to digital health literacy.
Dunn, P., & Hazzard, E. (2019) · International Journal of Cardiology · doi:10.1016/j.ijcard.2019.06.039 · Cited by 232
The Future of Wearable Technologies and Remote Monitoring in Health Care
Liao, Y., Thompson, C. A., Peterson, S. K., Mandrola, J. M., & Beg, M. S. (2019) · American Society of Clinical Oncology Educational Book · doi:10.1200/edbk_238919 · Cited by 195
Kalayou, M. H., Endehabtu, B. F., & Tilahun, B. C. (2020) · Journal of Multidisciplinary Healthcare · doi:10.2147/jmdh.s284973 · Cited by 179
Comparing machine learning algorithms for predicting ICU admission and mortality in COVID-19
Subudhi, S., Verma, A., Patel, A. B., Hardin, C., Khandekar, M. J., Lee, H., McEvoy, D. S., Stylianopoulos, T., Munn, L. L., Dutta, S., et al. (2021) · npj Digital Medicine · doi:10.1038/s41746-021-00456-x · Cited by 171
Wiljer, D., & Hakim, Z. (2019) · Journal of Medical Imaging and Radiation Sciences · doi:10.1016/j.jmir.2019.09.010 · Cited by 170
Biruk, S., Yilma, T. M., Andualem, M., & Tilahun, B. C. (2014) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-014-0115-5 · Cited by 164
Shiferaw, F., & Zolfo, M. (2012) · Global Health Action · doi:10.3402/gha.v5i0.15638 · Cited by 161
Investing in health R&D: where we are, what limits us, and how to make progress in Africa
Simpkin, V. L., Namubiru-Mwaura, E., Clarke, L., & Mossialos, E. A. (2019) · BMJ Global Health · doi:10.1136/bmjgh-2018-001047 · Cited by 133
Containment of COVID-19 in Ethiopia and implications for tuberculosis care and research
Mohammed, H., Oljira, L., Roba, K. T., Yimer, G., Fekadu, A., & Manyazewal, T. (2020) · Infectious Diseases of Poverty · doi:10.1186/s40249-020-00753-9 · Cited by 125
Self-citationBiruk, K., & Abetu, E. (2018) · Journal of Healthcare Engineering · doi:10.1155/2018/2389268 · Cited by 125
Brown, E. L., Ruggiano, N., Li, J., Clarke, P., Kay, E. S., & Hristidis, V. (2017) · Journal of Applied Gerontology · doi:10.1177/0733464817723088 · Cited by 123
The Determinants of M-Health Adoption in Developing Countries: An Empirical Investigation
Alaiad, A., Alsharo, M., & Alnsour, Y. (2019) · Applied Clinical Informatics · doi:10.1055/s-0039-1697906 · Cited by 115
Medhanyie, A. A., Little, A., Yebyo, H., Spigt, M., Tadesse, K., Blanco, R., & Dinant, G.-J. (2015) · Human Resources for Health · doi:10.1186/1478-4491-13-2 · Cited by 114
Tilahun, B. C., & Fritz, F. (2015) · JMIR Medical Informatics · doi:10.2196/medinform.4106 · Cited by 109
Little, A., Medhanyie, A., Yebyo, H., Spigt, M., Dinant, G.-J., & Blanco, R. (2013) · PLoS ONE · doi:10.1371/journal.pone.0077563 · Cited by 107
Ahmed, M. H., Bogale, A. D., Tilahun, B. C., Kalayou, M. H., Klein, J., Mengiste, S. A., & Endehabtu, B. F. (2020) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-020-01222-x · Cited by 104
A Novel Electronic Data Collection System for Large-Scale Surveys of Neglected Tropical Diseases
King, J. D., Buolamwini, J., Cromwell, E. A., Panfel, A., Teferi, T., Zerihun, M., Melak, B., Watson, J., Tadesse, Z., Vienneau, D., et al. (2013) · PLoS ONE · doi:10.1371/journal.pone.0074570 · Cited by 99
Randhawa, G. K., & Jackson, M. (2020) · Healthcare Management Forum · doi:10.1177/0840470419869032 · Cited by 96
Digital public health surveillance: a systematic scoping review
Abad, Z. S. H., Kline, A. S., Sultana, M., Noaeen, M., Nurmambetova, E., Lucini, F. R., Al-Jefri, M. M., & Lee, J. (2021) · npj Digital Medicine · doi:10.1038/s41746-021-00407-6 · Cited by 92
Lehoux, P., Roncarolo, F., da Silva, H. P., Boivin, A., Denis, J., & Hébert, R. (2018) · International Journal of Health Policy and Management · doi:10.15171/ijhpm.2018.110 · Cited by 91
Shiferaw, S., Spigt, M., Tekie, M., Abdullah, M., Fantahun, M., & Dinant, G.-J. (2016) · PLOS ONE · doi:10.1371/journal.pone.0158600 · Cited by 90
Association Between the Safe Delivery App and Quality of Care and Perinatal Survival in Ethiopia
Lund, S. B., Boas, I. M., Bedesa, T., Fekede, W., Nielsen, H. S., & Sørensen, B. L. (2016) · Archives of Pediatrics and Adolescent Medicine · doi:10.1001/jamapediatrics.2016.0687 · Cited by 88
Atnafu, A., Otto, K., & Herbst, C. H. (2017) · mHealth · doi:10.21037/mhealth.2017.08.04 · Cited by 85
Deep learning of pharmacogenomics resources: moving towards precision oncology
Chiu, Y., Chen, H.-I. H., Gorthi, A., Mostavi, M., Zheng, S., Huang, Y., & Chen, Y. (2019) · Briefings in Bioinformatics · doi:10.1093/bib/bbz144 · Cited by 80
Johnson, D. S., Juras, R., Riley, P., Chatterji, M., Sloane, P., Choi, S. K., & Johns, B. (2016) · Contraception · doi:10.1016/j.contraception.2016.07.009 · Cited by 75
Kebede, M., Adeba, E., & Cheme, M. C. (2020) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-020-01148-4 · Cited by 73
Harrington, E. K., Drake, A. L., Matemo, D., Ronen, K., Osoti, A. O., John-Stewart, G., Kinuthia, J., & Unger, J. A. (2019) · American Journal of Public Health · doi:10.2105/ajph.2019.305051 · Cited by 70
Healthcare providers’ digital competency: a cross-sectional survey in a low-income country setting
Shiferaw, K. B., Tilahun, B. C., & Endehabtu, B. F. (2020) · BMC Health Services Research · doi:10.1186/s12913-020-05848-5 · Cited by 69
Implementing mHealth Interventions in a Resource-Constrained Setting: Case Study From Uganda
Meyer, A. J., Armstrong-Hough, M. J., Babirye, D., Mark, D., Turimumahoro, P., Ayakaka, I., Haberer, J. E., Katamba, A., & Davis, J. L. (2020) · JMIR mhealth and uhealth · doi:10.2196/19552 · Cited by 67
Kazi, A. M., Carmichael, J.-L., Hapanna, G. W., Wangoo, P. G., Karanja, S., Wanyama, D., Muhula, S. O., Kyomuhangi, L. B., Loolpapit, M., Wangalwa, G. B., et al. (2017) · JMIR Public Health and Surveillance · doi:10.2196/publichealth.5386 · Cited by 67
Seto, E., Smith, D., Jacques, M., & Morita, P. P. (2019) · JMIR Medical Informatics · doi:10.2196/11353 · Cited by 60
Investigating the resistance to telemedicine in Ethiopia
Xue, Y., Liang, H., Mbarika, V., Hauser, R., Schwager, P., & Kassa Getahun, M. (2015) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2015.04.005 · Cited by 59
Smartphone-based symbol-digit modalities test reliably captures brain damage in multiple sclerosis
Pham, L., Harris, T., Varosanec, M., Morgan, V., Kosa, P. F., & Bielekova, B. (2021) · npj Digital Medicine · doi:10.1038/s41746-021-00401-y · Cited by 57
EPHA7 mutation as a predictive biomarker for immune checkpoint inhibitors in multiple cancers
Zhang, Z., Wu, H., Lin, W., Wang, Z., Yang, L.-P., Zeng, Z.-L., & Luo, H. (2021) · BMC Medicine · doi:10.1186/s12916-020-01899-x · Cited by 56
Young, A. T., Fernandez, K., Pfau, J., Reddy, R., Cao, N. A., von Franque, M., Johal, A., Wu, B., Wu, R. R., Chen, J. Y., et al. (2021) · npj Digital Medicine · doi:10.1038/s41746-020-00380-6 · Cited by 54
Klingberg, A., Sawe, H. R., Hammar, U., Wallis, L. A., & Hasselberg, M. (2019) · Telemedicine Journal and e-Health · doi:10.1089/tmj.2019.0048 · Cited by 53
Awol, S. M., Birhanu, A. Y., Mekonnen, Z. A., Gashu, K. D., Shiferaw, A. M., Endehabtu, B. F., Kalayou, M. H., Guadie, H. A., & Tilahun, B. C. (2020) · Advances in Medical Education and Practice · doi:10.2147/amep.s233368 · Cited by 52
Abiy, R., Gashu, K. D., Asemaw, T., Reta, M. M., Fekadie, B., Mekonnen, Z. A., Mamuye, A. L., Tazebew, A., Toni, A. T., Nurhussien, F., et al. (2018) · Online Journal of Public Health Informatics · doi:10.5210/ojphi.v10i2.8309 · Cited by 50
Jemere, A. T., Yeneneh, Y. E., Tilahun, B. C., Fritz, F., Alemu, S., & Kebede, M. M. (2019) · BMJ Open · doi:10.1136/bmjopen-2018-021766 · Cited by 48
Kebede, M. M., Zeleke, A. A., Asemahagn, M. A., & Fritz, F. (2015) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-015-0193-z · Cited by 47
Zeleke, A. A., Worku, A. G., Bogale, A. D., Otto‐Sobotka, F., Wilken, M., Lipprandt, M., Tilahun, B. C., & Röhrig, R. (2018) · JMIR mhealth and uhealth · doi:10.2196/10995 · Cited by 46
Thomsen, C. F., Barrie, A. M. F., Boas, I. M., Lund, S. B., Sørensen, B. L., Oljira, F. G., & Tersbøl, B. P. (2019) · Reproductive Health · doi:10.1186/s12978-019-0725-6 · Cited by 46
Barrenho, E., Miraldo, M., & Smith, P. (2018) · Health Economics · doi:10.1002/hec.3833 · Cited by 45
Manyazewal, T., Woldeamanuel, Y., Holland, D. P., Fekadu, A., Blumberg, H. M., & Marconi, V. C. (2020) · Trials · doi:10.1186/s13063-020-04324-z · Cited by 44
Self-citationThe fight to end tuberculosis must not be forgotten in the COVID-19 outbreak
Manyazewal, T., Woldeamanuel, Y., Blumberg, H. M., Fekadu, A., & Marconi, V. C. (2020) · Nature Medicine · doi:10.1038/s41591-020-0917-1 · Cited by 43
Self-citationBerihun, B., Atnafu, D. D., & Sitotaw, G. (2020) · BioMed Research International · doi:10.1155/2020/3827328 · Cited by 39
Félix, I. B., Guerreiro, M. P., Cavaco, A. M. D. N., Cláudio, A. P., Mendes, A., Balsa, J., Carmo, M. B., Pimenta, N. M., & Henriques, M. A. (2019) · Frontiers in Pharmacology · doi:10.3389/fphar.2019.00680 · Cited by 38
Mengesha, W., Steege, R., Kea, A. Z., Theobald, S., & Datiko, D. G. (2018) · Journal of Public Health · doi:10.1093/pubmed/fdy200 · Cited by 37
Quamme, G. A., & Dirks, J. H. (1983) · Reviews of physiology, biochemistry and pharmacology · doi:10.1007/bfb0035346 · Cited by 37
Development and Validation of a Smartphone-based Contrast Sensitivity Test
Habtamu, E., Bastawrous, A., Bolster, N. M., Tadesse, Z., Callahan, E. K., Gashaw, B., Macleod, D., & Burton, M. J. (2019) · Translational Vision Science & Technology · doi:10.1167/tvst.8.5.13 · Cited by 36
Ngongo, B. P., Ochola, P. O., Ndegwa, J., & Katuse, P. (2019) · PLoS ONE · doi:10.1371/journal.pone.0225167 · Cited by 35
Delaigue, S., Morand, J.-J., Olson, D., Wootton, R., & Bonnardot, L. (2014) · Frontiers in Public Health · doi:10.3389/fpubh.2014.00233 · Cited by 35
Thobias, J., & Kiwanuka, A. (2018) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-018-0622-x · Cited by 33
Endehabtu, B. F., Weldeab, A. N., Were, M. C., Lester, R. T., Worku, A., & Tilahun, B. C. (2018) · JMIR Pediatrics and Parenting · doi:10.2196/pediatrics.9618 · Cited by 33
Toward an Effective Innovation Agenda
Schulman, K. A., & Richman, B. D. (2019) · New England Journal of Medicine · doi:10.1056/nejmp1812460 · Cited by 32
Medhanyie, A. A., Spigt, M., Yebyo, H. G., Little, A., Gebremariam, K. T., Dinant, G., & Blanco, R. (2017) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2017.01.016 · Cited by 31
Telemedicine: An Evolving Field in Hepatology
Piao, C., Terrault, N. A., & Sarkar, S. (2019) · Hepatology Communications · doi:10.1002/hep4.1340 · Cited by 31
Shiferaw, S., Workneh, A., Yirgu, R., Dinant, G.-J., & Spigt, M. (2018) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-018-0704-9 · Cited by 31
Advances in clinical trial design for development of new TB treatments: A call for innovation
Lienhardt, C., & Nahid, P. (2019) · PLoS Medicine · doi:10.1371/journal.pmed.1002769 · Cited by 30
Dusabe-Richards, J., Tesfaye, H. T., Mekonnen, J., Kea, A. Z., Theobald, S., & Datiko, D. G. (2016) · Canadian Journal of Public Health · doi:10.17269/cjph.107.5569 · Cited by 29
Seboka, B. T., Yilma, T. M., & Birhanu, A. Y. (2021) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-021-01398-w · Cited by 29
MACKINTOSH, M. M., Mugwagwa, J., Banda, G., Tibandebage, P., Tunguhole, J., Wangwe, S. M., & Njeru, M. K. (2018) · Health Policy and Planning · doi:10.1093/heapol/czy022 · Cited by 27
Steege, R., Waldman, L., Datiko, D. G., Kea, A. Z., Taegtmeyer, M., & Theobald, S. (2018) · Journal of Public Health · doi:10.1093/pubmed/fdy199 · Cited by 26
Kebede, A. S., Ajayi, I. O., & Arowojolu, A. O. (2019) · Global Health Action · doi:10.1080/16549716.2019.1609297 · Cited by 25
Network for Peri‐operative Critical care (N4PCc)* (2021) · Anaesthesia · doi:10.1111/anae.15394 · Cited by 25
Comparison of Smartphone Photography, Single-Lens Reflex Photography, and Field-Grading for Trachoma
Nesemann, J. M., Seider, M. I., Snyder, B. M., Maamari, R. N., Fletcher, D. A., Ayele, B., Tadesse, Z., Varnado, N. E., Cotter, S. Y., Callahan, E. K., et al. (2020) · American Journal of Tropical Medicine and Hygiene · doi:10.4269/ajtmh.20-0386 · Cited by 25
Challenges and Silver Linings of COVID-19 in Ethiopia –Short Review
Wondimu, W., & Girma, B. (2020) · Journal of Multidisciplinary Healthcare · doi:10.2147/jmdh.s269359 · Cited by 24
Jede, F., Brandt, T., Gedefaw, M., Wubneh, S. B., Abebe, T., Teka, B., Alemu, K., Tilahun, B. C., Yitayew, T. A., Worku, A. G., et al. (2020) · Papillomavirus Research · doi:10.1016/j.pvr.2020.100198 · Cited by 24
Desta, B. F., Mohammed, H. A., Barry, D., Frew, A. H., Hepburn, K. W., & Claypoole, C. (2014) · Journal of Midwifery & Women s Health · doi:10.1111/jmwh.12111 · Cited by 23
Jadhav, A., & Weis, J. (2019) · Contraception · doi:10.1016/j.contraception.2019.10.004 · Cited by 21
Lee, S., Begley, C. E., Morgan, R. O., Chan, W., & Kim, S. (2018) · International Health · doi:10.1093/inthealth/ihy092 · Cited by 21
Aw, M. J., Ochieng, B. O., Attambo, D., Opot, D., Aw, J., Francis, S., & Hawkes, M. (2020) · Pathogens and Global Health · doi:10.1080/20477724.2020.1816286 · Cited by 21
New Opportunities for Digital Health to Thrive
Klonoff, D. C., King, F., & Kerr, D. E. (2019) · Journal of Diabetes Science and Technology · doi:10.1177/1932296818822215 · Cited by 20
Digital Entrepreneurship in Sub-Saharan Africa
(2019) · Palgrave studies of entrepreneurship in Africa · doi:10.1007/978-3-030-04924-9 · Cited by 20
Revisiting aid dependency for HIV programs in Sub-Saharan Africa
Olakunde, B. O., Adeyinka, D. A., Ozigbu, C. E., Ogundipe, T., Menson, W. N. A., Olawepo, J. O., Olakunde, O. A., & Ezeanolue, E. E. (2019) · Public Health · doi:10.1016/j.puhe.2019.02.016 · Cited by 19
Estifanos, A. S., Alemu, G., Negussie, S., Ero, D., Mengistu, Y. T., Addissie, A., Gebrehiwot, Y., Yifter, H., Melkie, A., Gebrekiros, D. H., et al. (2020) · BMJ Global Health · doi:10.1136/bmjgh-2020-003204 · Cited by 19
Endehabtu, B. F., Endehabtu, B. F., Tadesse, Y., Gelagay, A. A., Tilahun, B. C., Mekonnen, Z. A., & Gashu, K. D. (2019) · Online Journal of Public Health Informatics · doi:10.5210/ojphi.v11i2.9468 · Cited by 18
Nabyonga‐Orem, J., Nabukalu, J. B., & Okuonzi, S. A. (2019) · BMJ Global Health · doi:10.1136/bmjgh-2018-001193 · Cited by 18
Endebu, T., Deksisa, A., Dugasa, W., Kebede, E. M., & Bogale, T. (2019) · BMC Public Health · doi:10.1186/s12889-019-7687-z · Cited by 18
Thomas, D. S. K., Daly, K., Nyanza, E. C., Ngallaba, S. E., & Bull, S. S. (2020) · Digital Health · doi:10.1177/2055207620905409 · Cited by 17
mHealth advances clinical research, bit by bit
Kvedar, J. C., & Fogel, A. L. (2017) · Nature Biotechnology · doi:10.1038/nbt.3851 · Cited by 16
Ngowi, K. M., Lyamuya, F., Mmbaga, B. T., Muro, E. P., Hillu, Z., Shirima, M., Aarnoutse, R. E., Sprangers, M. A. G., Nieuwkerk, P. T., Reiss, P., et al. (2020) · JMIR Formative Research · doi:10.2196/14649 · Cited by 16
Mobile Phone Based Strategies for Preconception Education in Rural Africa
Kassa, Z. Y., Tenaw, Z., Astatkie, A., Siyoum, M., Bekele, G., Taye, K., Mekonnen, S., & Kassaye, Z. (2019) · Annals of Global Health · doi:10.5334/aogh.2566 · Cited by 15
Gebremariam, K. T., Zelenko, O., Hadush, Z., Mulugeta, A., & Gallegos, D. (2020) · Health Informatics Journal · doi:10.1177/1460458220911779 · Cited by 15
Karlyn, A. S., Odindo, S., Onyango, R. O., Mbindyo, C., Mberi, T., Too, G., Dalley, J., Holeman, I., & Wasunna, B. (2020) · mHealth · doi:10.21037/mhealth-19-261 · Cited by 15
Value and Feasibility of Telephone Follow-Up in Ethiopian Surgical Patients
Starr, N. E., Gebeyehu, N., Tesfaye, A., Forrester, J. A., Bekele, A., Alemu, S. B., Wayessa, E., Weiser, T. G., & Mammo, T. N. (2020) · Surgical Infections · doi:10.1089/sur.2020.054 · Cited by 14
Mableson, H. E., Martindale, S., Stanton, M. C., Mackenzie, C. D., & Kelly‐Hope, L. A. (2017) · mHealth · doi:10.21037/mhealth.2017.06.06 · Cited by 14
Public Health–Driven Research and Innovation for Next-Generation Influenza Vaccines, European Union
Navarro-Torné, A., Hanrahan, F., Kerstiëns, B., Aguar, P., & Matthiessen, L. (2019) · Emerging infectious diseases · doi:10.3201/eid2502.180359 · Cited by 13
Yigezu, A., Alemayehu, S., Hamusse, S. D., Ergeta, G. T., Mariam, D. H., & Hailu, A. (2020) · Cost Effectiveness and Resource Allocation · doi:10.1186/s12962-020-00231-x · Cited by 13
Brant, A. R., Hinkle, J. W., Shi, S., Hess, O. M., Zubair, T., Pershing, S., & Tabin, G. C. (2020) · Journal of Cataract & Refractive Surgery · doi:10.1097/j.jcrs.0000000000000407 · Cited by 12
Martindale, S., Mableson, H. E., Kebede, B. A., Kiros, F. H., Tamiru, A., Mengistu, B., Krueger, A., Mackenzie, C. D., & Kelly‐Hope, L. A. (2018) · mHealth · doi:10.21037/mhealth.2018.09.12 · Cited by 12
Translational Bioinformatics: Biobanks in the Precision Medicine Era
Ritchie, M. D., Moore, J. H., & Kim, J. H. (2019) · Pacific Symposium on Biocomputing (PSB) · doi:10.1142/9789811215636_0067 · Cited by 11
Developing countries in the digital revolution
Burki, T. K. (2018) · The Lancet · doi:10.1016/s0140-6736(18)30191-0 · Cited by 10
Little, A., Medhanyie, A. A., Yebyo, H. G., Spigt, M., Dinant, G., & Blanco, R. (2014) · PLoS ONE · doi:10.1371/annotation/fedf94d2-cf4e-494c-8828-85861ce282a5 · Cited by 10
Introducing medical genetics services in Ethiopia using the MiGene Family History App
Quinonez, S. C., Weldetsadik, A. Y., Lourie, M. A., Bekele, D., Asfaw, Y. M., Nigatu, B., Metaferia, G., & Deribessa, S. J. (2018) · Genetics in Medicine · doi:10.1038/s41436-018-0069-6 · Cited by 9
Webster, P. C. (2019) · The Lancet Digital Health · doi:10.1016/s2589-7500(19)30202-x · Cited by 9
A novel digital approach to describe real world outcomes among patients with constipation
Shapiro, A. D., Bradshaw, B., Landes, S., Kammann, P., Fer, B. B. D., Lee, W.-N., & Lange, R. (2021) · npj Digital Medicine · doi:10.1038/s41746-021-00391-x · Cited by 9
Mugambe, R. K., Mselle, J. S., Ssekamatte, T., Ntanda, M., Isunju, J. B., Wafula, S. T., Kansiime, W. K., Isubikalu, P., Ssemwanga, D. K., Yakubu, H., et al. (2021) · BMC Health Services Research · doi:10.1186/s12913-021-06082-3 · Cited by 9
Bramo, S. S., Bayissa, G., Asaminewu, S., & Alaro, T. (2016) · Ethiopian Journal of Health Sciences · doi:10.4314/ejhs.v26i4.6 · Cited by 8
Overcoming Barriers to Accessing Obstetric Care in Underserved Communities
Burlone, S., Moore, L., & Johnson, W. (2019) · Obstetrics and Gynecology · doi:10.1097/aog.0000000000003364 · Cited by 8
The Patient‐Centered Future of Clinical Pharmacology
Shahin, M. H., Abdel‐Rahman, S. M., Hartman, D., Johnson, J. A., Mitchell, D. Y., Reynolds, K. S., Wagner, J. A., & Morrissey, K. M. (2019) · Clinical Pharmacology & Therapeutics · doi:10.1002/cpt.1681 · Cited by 8
Bradley, D., Honeyman, C. S., Patel, V., Zeolla, J., Lester, L., Eshete, M. A., Demissie, Y., Martin, D., & McGurk, M. (2020) · Journal of Plastic Reconstructive & Aesthetic Surgery · doi:10.1016/j.bjps.2020.10.025 · Cited by 8
The Current Status of Cyber Security in EthiopiaPreprint
Adane, K. (2020) · SSRN Electronic Journal · doi:10.2139/ssrn.3545189 · Cited by 8
A mobile-based telepathology system for a low resource setting in Ethiopia
Abate, A., Kifle, M., Okuboyejo, S. R., & Mbarika, V. W. A. (2017) · Applied Computing and Informatics · doi:10.1016/j.aci.2017.08.002 · Cited by 7
Whitney, R. E., Riera, A., & Chen, L. (2019) · Pediatric Emergency Care · doi:10.1097/pec.0000000000001948 · Cited by 6
Innovation, Regional Integration, and Development in Africa
(2018) · Advances in African economic, social and political development · doi:10.1007/978-3-319-92180-8 · Cited by 6
Targeted health innovation for global health
Røttingen, J., & Farrar, J. (2019) · BMJ · doi:10.1136/bmj.l5601 · Cited by 5
Bramo, S. S., & Alaro, T. (2017) · Ethiopian Journal of Health Sciences · doi:10.4314/ejhs.v27i5.9 · Cited by 4
Adamu, Y. (2019) · Ethiopian Journal of Health Development · Cited by 1
Research works printed but not linked: 2
- United Nations Conference on Trade and Development (UNCTED). Selected sustainable development trends in the least developed countries—2019. https://unctad.org/en/PublicationsLibrary/aldc2019d1_en.pdf (Geneva, 2019).
- United Nations Conference on Trade and Development (UNCTED). Technology and innovation report—2018: Harnessing Frontier Technologies for Sustainable Development. https://unctad.org/en/PublicationsLibrary/tir2018_en.pdf (Geneve, 2018).
Cited by
Sorted by citations
Roppelt, J. S., Kanbach, D. K., & Kraus, S. (2023) · Technology in Society · doi:10.1016/j.techsoc.2023.102443 · Cited by 193
Acceptance of telemedicine technology among physicians: A systematic review
Garavand, A., Aslani, N., Nadri, H., Abedini, S., & Dehghan, S. (2022) · Informatics in Medicine Unlocked · doi:10.1016/j.imu.2022.100943 · Cited by 136
Digital health in the era of COVID-19: Reshaping the next generation of healthcare
Getachew, E., Adebeta, T., Muzazu, S. G. Y., Charlie, L., Said, B., Tesfahunei, H. A., Wanjiru, C. L., Acam, J., Kajogoo, V. D., Solomon, S., et al. (2023) · Frontiers in Public Health · doi:10.3389/fpubh.2023.942703 · Cited by 100
Self-citationHunde, M. K., Demsash, A. W., & Walle, A. D. (2022) · Informatics in Medicine Unlocked · doi:10.1016/j.imu.2022.101154 · Cited by 84
Metadata
- Authors
- Manyazewal, T., Woldeamanuel, Y., Blumberg, H. M., Fekadu, A., & Marconi, V. C.
- Affiliations
- Addis Ababa University (ET)
- Emory University (US)
- Corresponding author
- Manyazewal, Tsegahun
- ORCID
- Venue
- npj Digital Medicine
- Published
- 2021-08-17
- Volume
- 4
- Issue
- 1
- Pages
- 125-125
- ISSN
- 2398-6352 (ISSN-L)
- PMC
- PMC8371011
- OpenAlex
- W3194185186
- Cited by
- 177
- References
- 112
- Citations by year
- 2026: 33 · 2025: 43 · 2024: 42 · 2023: 27 · 2022: 28 · 2021: 4
- FWCI
- 5.22
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- npj Digital Medicine (publishedVersion, cc-by)
- medRxiv (acceptedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Figshare (submittedVersion, cc-by)
- Funders
- U.S. Department of Health & Human Services | NIH | Fogarty International Center (D43TW009127)
- Emory University | Center for AIDS Research, Emory University (P30 AI050409)
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Telemedicine and Telehealth Implementation
- Physical Sciences › Computer Science › Information Systems › ICT in Developing Communities
- Keywords
- digital health technologies, Ethiopia, mobile health, electronic health records, telemedicine, cloud applications, information and communication technologies, artificial intelligence in healthcare, maternal and child health, infectious diseases, non-communicable diseases, technology adoption, feasibility and usability, health infrastructure, digital health implementation, smartphone access
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
