TELERADIOLOGY AS A TOOL FOR REDUCING DIAGNOSTIC INEQUALITY: LITERATURE REVIEW OF EVIDENCE FROM RESOURCE-CONSTRAINED HEALTHCARE SYSTEMS
DOI:
https://doi.org/10.31435/ijitss.2(50).2026.5846Keywords:
Teleradiology, Health Care Disparities, Diagnostic Imaging, Low-Resource Settings, Artificial Intelligence, Mobile Imaging Systems, Telemedicine, Radiology Workforce ShortageAbstract
Background: In many regions of the world where healthcare resources are limited, access to radiologists and the infrastructure necessary for diagnostic imaging is significantly restricted. The uneven distribution of resources leads to delayed diagnosis and, as a result, poorer treatment outcomes. In response to these challenges, teleradiology enables the remote transmission and interpretation of imaging studies, which can help reduce disparities in access to diagnostic imaging. Such solutions are particularly significant in rural and hard-to-reach areas. Despite the growing trend in the number and scope of telemedicine system implementations, the effectiveness of teleradiology in the context of systematically reducing diagnostic inequalities requires further analysis.
Methods: A comprehensive PubMed and Cochrane Library search was performed using broad terms not specified to subtypes of medical imaging devices, including cohort studies, systematic reviews and meta-analyses from January 2020 to April 2026. Then, the articles were reviewed manually and selected based on the relevance for the review.
Results: The available evidence suggests that the use of teleradiology and artificial intelligence models, in conjunction with mobile imaging systems, can effectively help address the shortage of radiologists, thereby increasing access to diagnostic imaging in healthcare and strengthening screening programs. It also facilitates multidisciplinary collaboration among specialists, leading to more accurate diagnoses and targeted treatment.
Conclusions: In many low-resource regions, limited access to radiologists and diagnostic imaging infrastructure contributes to delayed diagnoses and poorer treatment outcomes. Teleradiology, by enabling remote image interpretation, may help reduce these disparities, particularly in rural and underserved areas. However, its effectiveness in systematically reducing diagnostic inequalities still requires further evaluation.
References
Adams, S., Burbridge, B., Chatterson, L., Babyn, P., & Mendez, I. (2022). A telerobotic ultrasound clinic model of ultrasound service delivery to improve access to imaging in rural and remote communities. Journal of the American College of Radiology, 19(1 Pt B), 162–171. https://doi.org/10.1016/j.jacr.2021.07.023
Ain, H., Tahir, M., Farooq, F., Eljack, M., & Yousaf, Z. (2023). Teleradiology: Legislations and ethical issues in low- and middle-income countries. Academic Radiology. https://doi.org/10.1016/j.acra.2023.02.036
Alhasan, M., & Alhasan, A. (2025). Technical requirements and optimization strategies for home-based teleradiology workstations: A review article. Insights into Imaging, 16. https://doi.org/10.1186/s13244-025-02081-8
Alqarni, M., Alharbi, F., Daghriri, A., Tohari, M., Awaji, M., Gharawi, A., Altukhais, I., Amri, A., Almutairi, F., Alanbari, F., & Alshaibani, M. (2025). Impact of telemedicine and teleradiology on interprofessional collaborative care among nurses, pharmacists, and radiologists: A systematic review. Saudi Journal of Medicine and Public Health. https://doi.org/10.64483/jmph-84
Alruwaili, A., Alshammari, A., Alsalhi, F., Aldamen, S., & Alamri, H. (2024). Teleradiology in Saudi Arabia: A national survey and retrospective review of associated MRI reports. BMC Health Services Research, 24. https://doi.org/10.1186/s12913-024-11706-5
Arjuna, S., Mathur, N., Rawath, M., & Kalyanpur, A. (2025). Utilization of teleradiology services for healthcare delivery in Saudi Arabia. Advances in Radiotherapy & Nuclear Medicine. https://doi.org/10.36922/arnm025270033
Bashshur, R., Krupinski, E., Thrall, J., & Bashshur, N. (2016). The empirical foundations of teleradiology and related applications: A review of the evidence. Telemedicine and e-Health, 22, 868–898. https://doi.org/10.1089/tmj.2016.0149
Britton, N., Miller, M., Safadi, S., Siegel, A., Levine, A., & McCurdy, M. (2019). Tele-ultrasound in resource-limited settings: A systematic review. Frontiers in Public Health, 7. https://doi.org/10.3389/fpubh.2019.00244
Chandramohan, A., Krothapalli, V., Augustin, A., Kandagaddala, M., Thomas, H., Sudarsanam, T., Jagirdar, A., Govil, S., & Kalyanpur, A. (2023). Teleradiology and technology innovations in radiology: Status in India and its role in increasing access to primary health care. The Lancet Regional Health – Southeast Asia, 23. https://doi.org/10.1016/j.lansea.2023.100195
Chikarmane, S., Thimm, E., Plaxco, J., Chung, S., Harvey, J., & Slanetz, P. (2025). Remote diagnostic breast imaging: An implementation guide. American Journal of Roentgenology. https://doi.org/10.2214/AJR.25.33537
Coulborn, R., Panunzi, I., Spijker, S., Brant, W., Duran, L., Kosack, C., & Murowa, M. (2012). Feasibility of using teleradiology to improve tuberculosis screening and case management in a district hospital in Malawi. Bulletin of the World Health Organization, 90(9), 705–711. https://doi.org/10.2471/BLT.11.099473
Crumley, I., Halton, J., Greig, J., Kahunga, L., Mwanga, J., Chua, A., & Kosack, C. (2020). The impact of computed radiography and teleradiology on patients’ diagnosis and treatment in Mweso, the Democratic Republic of Congo. PLOS ONE, 15. https://doi.org/10.1371/journal.pone.0227773
Diala, O., Njoku, C., Onwe, I., Onyeibor, C., & Ekanem, C. (2025). Integrating artificial intelligence and data analytics in imaging for early cancer detection: Optimizing workforce efficiency and healthcare resource allocation. International Journal of Scientific Research Updates. https://doi.org/10.53430/ijsru.2025.9.1.0026
Ewing, B., & Holmes, D. (2022). Evaluation of current and former teleradiology systems in Africa: A review. Annals of Global Health, 88. https://doi.org/10.5334/aogh.3711
Forkuo, A., Chianumba, E., Mustapha, A., Osamika, D., & Komi, L. (2022). Advances in digital diagnostics and virtual care platforms for primary healthcare delivery in West Africa. International Journal of Multidisciplinary Research and Growth Evaluation. https://doi.org/10.54660/.ijmrge.2022.3.1.1034-1047
Hanna, T., Steenburg, S., Rosenkrantz, A., Pyatt, R., Duszak, R., & Friedberg, E. (2020). Emerging challenges and opportunities in the evolution of teleradiology. American Journal of Roentgenology, 1–6. https://doi.org/10.2214/AJR.20.23007
Harahap, V., Purba, J., & Pitriani, P. (2024). The role of tele-radiology technology in supporting health services in remote areas of North Sumatera. Jurnal Ilmiah Metadata. https://doi.org/10.47652/metadata.v6i1.865
Johnston, K., Smith, D., Preston, R., Evans, R., Carlisle, K., Lengren, J., Naess, H., Phillips, E., Shephard, G., Lydiard, L., Lattimore, D., & Larkins, S. (2020). “From the technology came the idea”: Safe implementation and operation of a high-quality teleradiology model increasing access to timely breast cancer assessment services for women in rural Australia. BMC Health Services Research, 20. https://doi.org/10.1186/s12913-020-05922-y
Kalyanpur, A., Meka, S., Joshi, K., Nair, H., & Mathur, N. (2022). Teleradiology in Tripura: Effectiveness of a telehealth model for the rural health sector. International Journal of Health Technology and Innovation. https://doi.org/10.60142/ijhti.v1i02.36
Khan, A., Galea, S., & Mendez, I. (2025). Standardizing virtual healthcare deployment: Insights from the implementation of telerobotic ultrasound to bridge healthcare inequities in rural and remote communities across Canada. Journal of Primary Care & Community Health, 16. https://doi.org/10.1177/21501319251329314
Kumar, P., A., Lionis, C., Andoko, D., Rahman, Z., Anastasaki, M., & Awankem, B. (2025). Evaluation of diagnostic services in rural and remote areas: Bottlenecks, success stories, and solutions. Journal of Surgical Specialties and Rural Practice. https://doi.org/10.4103/jssrp.jssrp_8_25
Marini, T., Oppenheimer, D., Baran, T., Rubens, D., Dozier, A., Garra, B., Egoavil, M., Quinn, R., Kan, J., Ortega, R., Zhao, Y., Tamayo, L., Carlotto, C., & Castañeda, B. (2021). Testing telediagnostic right upper quadrant abdominal ultrasound in Peru: A new horizon in expanding access to imaging in rural and underserved areas. PLOS ONE, 16. https://doi.org/10.1371/journal.pone.0255919
Marini, T., Weiss, S., Gupta, A., Zhao, Y., Baran, T., Garra, B., Shafiq, I., Oppenheimer, D., Egoavil, M., Ortega, R., Quinn, R., Kan, J., Dozier, A., Tamayo, L., Carlotto, C., & Castañeda, B. (2021). Testing telediagnostic thyroid ultrasound in Peru: A new horizon in expanding access to imaging in rural and underserved areas. Journal of Endocrinological Investigation, 44, 2699–2708. https://doi.org/10.1007/s40618-021-01584-7
Marini, T., Oppenheimer, D., Baran, T., Rubens, D., Toscano, M., Drennan, K., Garra, B., Miele, F., Garra, G., Noone, S., Tamayo, L., Carlotto, C., Trujillo, L., Waks, E., Garra, K., Egoavil, M., Berrospi, J., & Castañeda, B. (2020). New ultrasound telediagnostic system for low-resource areas. Journal of Ultrasound in Medicine, 40. https://doi.org/10.1002/jum.15420
Martadipura, B., & Martadipura, R. (2025). A systematic review of diagnostic radiology access, barriers, and novel interventions in low-income countries. The International Journal of Medical Science and Health Research. https://doi.org/10.70070/z08s4k08
Monsky, W., Seslar, S., & James, R. (2025). Remote telerobotics in interventional radiology: Development, procedures, and challenges. Journal of Vascular and Interventional Radiology, 36(12), 1917–1921.e1. https://doi.org/10.1016/j.jvir.2025.09.011
Muñoz, J. (2024). Aproximación a la capacidad instalada de equipos de tomografía computarizada en Colombia. Revista CIFE: Lecturas de Economía Social. https://doi.org/10.15332/22484914.10545
Murali, S., Ding, H., Adedeji, F., Qin, C., Obungoloch, J., Asllani, I., Anazodo, U., Ntusi, N., Mammen, R., Niendorf, T., & Adeleke, S. (2023). Bringing MRI to low- and middle-income countries: Directions, challenges, and potential solutions. NMR in Biomedicine, 37. https://doi.org/10.1002/nbm.4992
Nigatu, A., Yilma, T., Gezie, L., Gebrewold, Y., Gullslett, M., Mengiste, S., & Tilahun, B. (2025). Effect of teleradiology on patient waiting time and service satisfaction in public hospitals, Northwest Ethiopia: A quasi-experimental study. BMC Health Services Research, 25. https://doi.org/10.1186/s12913-025-12545-8
Nigatu, A., Yilma, T., Gezie, L., Gebrewold, Y., Gullslett, M., Mengiste, S., & Tilahun, B. (2024). Barriers and facilitators experienced during the implementation of a web-based teleradiology system in public hospitals of Northwest Ethiopia: An interpretive description study. International Journal of Telemedicine and Applications, 2024. https://doi.org/10.1155/2024/5578056
Nortey, J., Osei, E., Suleiman, R., Agbotsigah, L., Adabo, A., & Gborgblah, M. (2023). Review of teleradiology applications in some selected African countries [Preprint]. medRxiv. https://doi.org/10.1101/2023.10.07.23296691
Osonuga, A., Osonuga, A., Fidelis, S., Osonuga, G., Juckes, J., & Olawade, D. (2025). Bridging the digital divide: Artificial intelligence as a catalyst for health equity in primary care settings. International Journal of Medical Informatics, 204, 106051. https://doi.org/10.1016/j.ijmedinf.2025.106051
Palozzi, G., Schettini, I., & Chirico, A. (2020). Enhancing the sustainable goal of access to healthcare: Findings from a literature review on telemedicine employment in rural areas. Sustainability. https://doi.org/10.3390/su12083318
Perez, K., Wisniewski, D., Arı, A., Lee, K., Lieneck, C., & Ramamonjiarivelo, Z. (2025). Investigation into application of AI and telemedicine in rural communities: A systematic literature review. Healthcare, 13. https://doi.org/10.3390/healthcare13030324
Pesapane, F., Tantrige, P., Rotili, A., Nicosia, L., Penco, S., Bozzini, A., Raimondi, S., Corso, G., Grasso, R., Pravettoni, G., Gandini, S., & Cassano, E. (2023). Disparities in breast cancer diagnostics: How radiologists can level the inequalities. Cancers, 16. https://doi.org/10.3390/cancers16010130
Rackimuthu, S., Hasan, M., Ray, I., Sahito, A., Chawla, P., & Ghosh, D. (2022). Teleradiology in India during the COVID-19 pandemic: Merits, pitfalls, and a future perspective. Health Policy and Planning. https://doi.org/10.1093/heapol/czac045
Rao, P., Mathur, N., & Kalyanpur, A. (2023). Utilization of teleradiology by intensive care units: A cohort study. Indian Journal of Critical Care Medicine, 28, 20–25. https://doi.org/10.5005/jp-journals-10071-24593
Ren, J., Lei, Y., Lei, B., Peng, Y., Pan, X., Ye, H., & Cui, X. (2023). The feasibility and satisfaction study of a 5G-based robotic teleultrasound diagnostic system in health check-ups. Frontiers in Public Health, 11. https://doi.org/10.3389/fpubh.2023.1149964
Reschke, P., Gruenewald, L., Koch, V., Gotta, J., Booz, C., Mahmoudi, S., Bernatz, S., Gökduman, A., Höhne, E., Eichler, K., Schlüchtermann, J., Vogl, T., & Yel, I. (2025). Radiology access in rural Germany: A nationwide survey on outpatient imaging and teleradiology. Diagnostics, 15. https://doi.org/10.3390/diagnostics15080962
Rosenkrantz, A., Hanna, T., Steenburg, S., Tarrant, M., Pyatt, R., & Friedberg, E. (2019). The current state of teleradiology across the United States: A national survey of radiologists’ habits, attitudes, and perceptions on teleradiology practice. Journal of the American College of Radiology. https://doi.org/10.1016/j.jacr.2019.05.053
Rudisill, K., Mathur, N., & Kalyanpur, A. (2024). A teleradiology network for the improvement of healthcare and patient management in the developing countries of the African continent. Clinical Imaging, 111, 110188. https://doi.org/10.1016/j.clinimag.2024.110188
Samuels-Kalow, M., Jaffe, T., & Zachrison, K. (2021). Digital disparities: Designing telemedicine systems with a health equity aim. Emergency Medicine Journal, 38, 474–476. https://doi.org/10.1136/emermed-2020-210896
Sangare, M., Tanner, L., Voss, S., Laureys, F., Hollow, D., & Toure, M. (2015). A national teleradiology programme in Mali: Implementation and results. Journal of Telemedicine and Telecare, 21, 131–138. https://doi.org/10.1177/1357633X15569966
Sharma, A., Choudhury, R., & Shahi, A. (2025). OP25 teleradiology public-private partnership models: Informing health technology assessment findings in India. International Journal of Technology Assessment in Health Care, 41, S12–S12. https://doi.org/10.1017/S0266462325100834
Suji, T., Sullivan, R., & Bowsher, G. (2024). Radiology in conflict: Scoping review. Conflict and Health, 18. https://doi.org/10.1186/s13031-023-00550-9
Tahir, M., Mars, M., & Scott, R. (2022). A review of teleradiology in Africa—Towards mobile teleradiology in Nigeria. SA Journal of Radiology, 26. https://doi.org/10.4102/sajr.v26i1.2257
Toscano, M., Marini, T., Drennan, K., Baran, T., Kan, J., Garra, B., Dozier, A., Ortega, R., Quinn, R., Zhao, Y., Egoavil, M., Tamayo, L., Carlotto, C., & Castañeda, B. (2021). Testing telediagnostic obstetric ultrasound in Peru: A new horizon in expanding access to prenatal ultrasound. BMC Pregnancy and Childbirth, 21. https://doi.org/10.1186/s12884-021-03720-w
Tran, A., Grant, G., Akande, O., & Sadigh, G. (2025). Disparities in imaging and management of multiple sclerosis: A review. The British Journal of Radiology. https://doi.org/10.1093/bjr/tqaf233
Turkar, G., & Bagdey, P. (2020). Role of utilization of teleradiology services in rural India: A cross-sectional study. Journal of Population Therapeutics and Clinical Pharmacology. https://doi.org/10.53555/7bvgfq15
Unanah, O., & Mbanugo, O. (2025). Telemedicine and mobile health imaging technologies: Business models for expanding U.S. healthcare access. International Journal of Science and Research Archive. https://doi.org/10.30574/ijsra.2025.14.2.0398
Yemeshev, Y., Nurmashev, B., Zimba, O., & Koçyiğit, B. (2025). Clinical implications of teleradiology in rheumatic and musculoskeletal diseases: Improving rheumatic care. Rheumatology International, 45. https://doi.org/10.1007/s00296-025-05810-w
Zhou, Y., Guo, L., Bo, X., Sun, L., Zhang, Y., Chai, H., Ye, R., Peng, C., Qin, C., & Xu, H. (2023). Tele-mentored handheld ultrasound system for general practitioners: A prospective, descriptive study in remote and rural communities. Diagnostics, 13. https://doi.org/10.3390/diagnostics13182932
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Arnold Borowiec, Natalia Ostruszka, Julia Pilecka, Sabina Kolawa, Jędrzej Wojciechowski, Maria Marusińska, Michał Karpiński, Wiktoria Czyż, Wojciech Markiewicz, Michał Parzniewski
This work is licensed under a Creative Commons Attribution 4.0 International License.
All articles are published in open-access and licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). Hence, authors retain copyright to the content of the articles.
CC BY 4.0 License allows content to be copied, adapted, displayed, distributed, re-published or otherwise re-used for any purpose including for adaptation and commercial use provided the content is attributed.
How to Cite
