Experiencing Telemedicine: Insights into Elderly Patients’ Telehealth Interactions in Remote Indonesian Communities

Main Article Content

Ai Lela Kurnia

Abstract

Telemedicine, a key advancement in medical informatics, is reshaping healthcare delivery by enabling remote consultations, particularly in underserved regions. While the technology promises greater accessibility, few studies have explored how elderly patients in remote areas personally experience these digital interactions. Despite its growing implementation, limited knowledge exists about the emotional and cognitive responses of older adults to such systems, especially outside urban areas. This study seeks to answer the following question: What are the lived experiences of elderly patients using telemedicine in remote settings?


Using a descriptive phenomenological approach, this study uncovers how elderly individuals construct meaning around their use of telemedicine platforms. In-depth semi-structured interviews were conducted with ten elderly participants from remote regions of Indonesia, and data were analyzed thematically. The results revealed three key themes: initial technological anxiety and gradual adaptation, emotional distance and trust issues in remote consultations, and ambivalence regarding the perceived quality and accessibility of digital care. These findings illustrate that elderly patients' adoption of telemedicine is influenced not only by digital literacy but also by emotional readiness and relational expectations.


This study broadens our understanding of how telemedicine is experienced by vulnerable users and highlights the need for empathetic, culturally sensitive telehealth design in policy and practice.

Article Details

Section
Articles

References

Amoon et al., (2020). Internet of things sensor assisted security and quality analysis for health care data sets using artificial intelligent based heuristic health management system. Measurement: Journal of the International Measurement Confederation, 161. Scopus. https://doi.org/10.1016/j.measurement.2020.107861

Baldassano, S. N., Roberson, S. W., Balu, R., Scheid, B., Bernabei, J. M., Pathmanathan, J., Oommen, B., Leri, D., Echauz, J., Gelfand, M., Bhalla, P. K., Hill, C. E., Christini, A., Wagenaar, J. B., & Litt, B. (2020). IRIS: A modular platform for continuous monitoring and caretaker notification in the intensive care unit. IEEE Journal of Biomedical and Health Informatics, 24(8), 2389–2397. Scopus. https://doi.org/10.1109/JBHI.2020.2965858

Blonigen, D., Hyde, J., McInnes, D. K., Yoon, J., Byrne, T., Ngo, T., & Smelson, D. (2023). Integrating data analytics, peer support, and whole health coaching to improve the health outcomes of homeless veterans: Study protocol for an effectiveness-implementation trial. Contemporary Clinical Trials, 125. Scopus. https://doi.org/10.1016/j.cct.2022.107065

Fahlevi, H., Irsyadillah, I., Indriani, M., & Oktari, R. S. (2022). DRG-based payment system and management accounting changes in an Indonesian public hospital: Exploring potential roles of big data analytics. Journal of Accounting and Organizational Change, 18(2), 325–345. Scopus. https://doi.org/10.1108/JAOC-10-2020-0179

Fleming, M. D., Safaeinili, N., Knox, M., & Brewster, A. L. (2024). Organizational and community resilience for COVID-19 and beyond: Leveraging a system for health and social services integration. Health Services Research, 59(S1). Scopus. https://doi.org/10.1111/1475-6773.14250

Gous, N., Nyaruhirira, A. U., Cunningham, B., & Macek, C. (2020). Driving the usage of tuberculosis diagnostic data through capacity building in low- And middle-income countries. African Journal of Laboratory Medicine, 9(2). Scopus. https://doi.org/10.4102/AJLM.V9I2.1092

Gramaje, A., Thabtah, F., Abdelhamid, N., & Ray, S. K. (2021). Patient Discharge Classification Using Machine Learning Techniques. Annals of Data Science, 8(4), 755–767. Scopus. https://doi.org/10.1007/s40745-019-00223-6

Harb, H., Mansour, A., Nasser, A., Cruz, E. M., & De La Torre Diez, I. (2021). A Sensor-Based Data Analytics for Patient Monitoring in Connected Healthcare Applications. IEEE Sensors Journal, 21(2), 974–984. Scopus. https://doi.org/10.1109/JSEN.2020.2977352

Harb, H., Mroue, H., Mansour, A., Nasser, A., & Cruz, E. M. (2020). A hadoop-based platform for patient classification and disease diagnosis in healthcare applications. Sensors (Switzerland), 20(7). Scopus. https://doi.org/10.3390/s20071931

Ho, A. F. W., To, B. Z. Y. S., Koh, J. M., & Cheong, K. H. (2019). Forecasting Hospital Emergency Department Patient Volume Using Internet Search Data. IEEE Access, 7, 93387–93395. Scopus. https://doi.org/10.1109/ACCESS.2019.2928122

Maddeh, M., Hajjej, F., Alazzam, M. B., Otaibi, S. A., Turki, N. A., & Ayouni, S. (2023). Spatio-Temporal Cluster Mapping System in Smart Beds for Patient Monitoring. Sensors, 23(10). Scopus. https://doi.org/10.3390/s23104614

Mahajan, A., Madhani, P., Chitikeshi, S., Selvaganesan, P., Russell, A., & Mahajan, P. (2019). Advanced Data Analytics for Improved Decision-Making at a Veterans Affairs Medical Center. Journal of Healthcare Management, 64(1), 54–62. Scopus. https://doi.org/10.1097/JHM-D-17-00164

Metz, M., Smith, R., Mitchell, R., Duong, Y. T., Brown, K., Kinchen, S., Lee, K., Ogollah, F. M., Dzinamarira, T., Maliwa, V., Moore, C., Patel, H., Chung, H., Mtengo, H., & Saito, S. (2021). Data Architecture to Support Real-Time Data Analytics for the Population-Based HIV Impact Assessments. Journal of Acquired Immune Deficiency Syndromes, 87, S28–S35. Scopus. https://doi.org/10.1097/QAI.0000000000002703

Minopoulos, G. M., Memos, V. A., Stergiou, C. L., Stergiou, K. D., Plageras, A. P., Koidou, M. P., & Psannis, K. E. (2022). Exploitation of Emerging Technologies and Advanced Networks for a Smart Healthcare System. Applied Sciences (Switzerland), 12(12). Scopus. https://doi.org/10.3390/app12125859

Mulrooney, M., Smith, M., Lewis, K., Vuernick, E., Anderson, D., Channamsetty, V., & Giannotti, T. (2022). Practical implementation insights from 2 population health pharmacist project approaches to improve blood pressure control. Journal of the American Pharmacists Association, 62(1), 270–280. Scopus. https://doi.org/10.1016/j.japh.2021.07.012