The effectiveness of telemedicine in improving the timeliness and quality of referrals for non-communicable diseases in the archipelagic settings: A scoping review
DOI: https://doi.org/10.33024/minh.v9i4.2738
Island Regions Non-communicable Diseases Referral Telemedicine Tele-triage
Abstract
Background: Referral systems in island regions often experience delays and inaccuracies in non-communicable disease (NCD) cases due to geographic barriers and limited resources. Telemedicine (tele-triage/teleconsultation) has the potential to accelerate referral decisions and improve the quality of clinical information between facilities.
Purpose: To map the evidence related to telemedicine in supporting the referral process for non-communicable disease cases in areas with limited access. Outcomes and supporting implementation are reported.
Method: A scoping review was employed based on the PCC (Population, Concept, Context) framework. A literature search was conducted on PubMed, Scopus, ScienceDirect, and Google Scholar for Indonesian or English-language articles published in the period 2019–2025. The selection process followed the PRISMA-ScR guidelines through screening stages of titles, abstracts, and full texts. Source quality assessment was carried out descriptively in accordance with the objectives of the scoping review without excluding studies based on risk of bias. The selection and assessment process were carried out by two reviewers independently, with differences resolved through discussion. Data synthesis was carried out narratively.
Results: Of the 354 articles identified, 10 studies met the inclusion criteria. Telemedicine was reported to expedite the referral process through triage and remote specialist consultation. Key findings include 81.8% of patients recommended for referral were referred within ≤48 hours after a tele-ECG consultation, a mean specialist response time of 4 days for the eConsult service, and a 25.4-day reduction in outpatient waiting time in the quantitative study. Improved referral quality was primarily related to the completeness of clinical data and the accuracy of referral decisions. However, effectiveness is influenced by infrastructure readiness, coordination between facilities, and human resource competency.
Conclusion: Telemedicine has been used in various forms to support the referral process, but evidence remains limited and scattered across specific settings.
Downloads
References
Capodici, A., Noci, F., Nuti, S., Emdin, M., Dalmiani, S., Passino, C., & Giannoni, A. (2025). Reducing outpatient wait times through telemedicine: a systematic review and quantitative analysis. BMJ open, 15(1), e088153.
Dewi, A. (2023). Telemedicine: Health Care Facilities Readiness to Change. Martabe: Jurnal Pengabdian Masyarakat, 6(1), 1–11.
Hasifah, H., Maliga, I., Lestari, A., & Hamdin, H. (2024). Case Study on the Implementation of Telemedicine in Health Administration at Lopok Health Center: Challenges and Opportunities. Jurnal EduHealth, 15(03), 597-602.
Jat, A. S., Grønli, T., & Ghinea, G. (2024). Technological Utilization in Remote Healthcare : Factors Influencing Healthcare Professionals ’ Adoption and Use. Journal of Health Informatics in Developing Countries 18(1), 1–22.
Job, J., Nicholson, C., Calleja, Z., Jackson, C., & Donald, M. (2022). Implementing a general practitioner-to-general physician eConsult service (eConsultant) in Australia. BMC health services research, 22(1), 1278.
Kruse, C. S., Karem, P., Shifflett, K., Vegi, L., Ravi, K., & Brooks, M. (2018). Evaluating barriers to adopting telemedicine worldwide: a systematic review. Journal of telemedicine and telecare, 24(1), 4-12.
Laudanski, K., Huffenberger, A. M., Scott, M. J., Wain, J., Ghani, D., & Hanson III, C. W. (2022). Pilot of rapid implementation of the advanced practice provider in the workflow of an existing tele-critical care program. BMC Health Services Research, 22(1), 855.
Mappangara, I., Qanitha, A., Uiterwaal, C. S., Henriques, J. P., & de Mol, B. A. (2020). Tele-ECG consulting and outcomes on primary care patients in a low-to-middle income population: the first experience from Makassar telemedicine program, Indonesia. BMC family practice, 21(1), 247.
Nabelsi, V., Lévesque-Chouinard, A., Liddy, C., & Pilon, M. D. (2019). Improving the referral process, timeliness, effectiveness, and equity of access to specialist medical services through electronic consultation: pilot study. JMIR medical informatics, 7(3), e13354.
Nataliansyah, M. M., Merchant, K. A., Croker, J. A., Zhu, X., Mohr, N. M., Marcin, J. P., & Ward, M. M. (2022). Managing innovation: a qualitative study on the implementation of telehealth services in rural emergency departments. BMC health services research, 22(1), 852.
Otto, L., Schlieter, H., Harst, L., Whitehouse, D., & Maeder, A. (2023). The telemedicine community readiness model—successful telemedicine implementation and scale-up. Frontiers in digital health, 5, 1057347.
Sebo, P., de Lucia, S., & Vernaz, N. (2021). Scientific publications in internal medicine and family medicine: a comparative cross-sectional study in Swiss university hospitals. Family practice, 38(3), 299-305.
Setianingsih, L. E. (2023). Perceptions Of Telehealth Among Healthcare Professionals During The Covid-19 Pandemic Era In X Hospital. Jurnal eduhealth, 14(01), 389-395.
Sutrisnawati, N. N. D., & Suandari, P. V. L. (2023). Analysis of Factors Influencing the Implementation of an Integrated Referral System (SISRUTE) in an Effort to Improve the Quality of Health Service Facilities. Indonesian Journal of Global Health Research, 5(4), 1043–1058. Retrieved from: https://jurnal.globalhealthsciencegroup.com/index.php/IJGHR/article/view/3341
Totten, A. M., Womack, D. M., & Eden, K. B. (2020). Telehealth: Mapping the Evidence for Patient Outcomes from Systematic Reviews. Technical brief no. 26. Rockville, MD: Agency for Healthcare Research and Quality; 2016. Retrieved from: https://www.ncbi.nlm.nih.gov/books/NBK379320/
Volpato, L., Carral, M. D. R., Senn, N., & Delefosse, M. S. (2021). General practitioners' perceptions of the use of wearable electronic health monitoring devices: qualitative analysis of risks and benefits. JMIR mHealth and uHealth, 9(8), e23896.
Wang, M., Huang, K., Li, X., Zhao, X., Downey, L., Hassounah, S., & Ren, M. (2024). Health workers’ adoption of digital health technology in low-and middle-income countries: a systematic review and meta-analysis. Bulletin of the World Health Organization, 103(2), 126.
Weik, L., Fehring, L., Mortsiefer, A., & Meister, S. (2024). Understanding inherent influencing factors to digital health adoption in general practices through a mixed-methods analysis. NPJ Digital Medicine, 7(1), 47.
World Health Organization. (2017). Monitoring the Building Blocks of Health Systems: A Handbook of Indicators and Their Measurement Strategies. World Health Organization. Retrieved from: https://www.who.int/publications/b/31426
World Health Organization. (2025). Noncommunicable diseases (NCDs). Retrieved from: https://www.who.int/news-room/fact-sheets/detail/noncommunicable-diseases.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Diana Yulias, Arlina Dewi
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
