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The E-Health is used to support information technology to maximize the tasks and medical services in the hospital. However, the hospitalâ??s management still have some issues due to E-Health implementation, particularly in the interaction with the system. This study identifies significant factors affecting the implementation of E-Health. Testing a model has been done, to identify factors affecting E-Health acceptance. Quantitative Research methods has been done is implemented in this research, by conducting a survey of 150 respondents on health practitioners in the District Hospital of Gunung Mas Province of Central Kalimantan. Random Sampling Method has been done is performed by doctors, nurses, medical record officers, and midwives. Meanwhile, model testing has been done with Structural Equation Model (SEM) analysis technique. The results of this study show that computer self-efficacy factor is the most powerful factor influencing user's opinion about perceived ease of use and perceived the usefulness of E-Health (significant p <0.05), followed by compatibility, top management support, information quality, system quality, facilitating condition, service quality, complexity, and adaptability. Hospital management needs to work together as a team effort to medical practitioners to apply E-Health in hospitals. Supports and awareness from various parties, such as government, IT support, and resources are expected to help implement E-Health in rural areas. The result of this study could be a decision in taking steps to implement E-Health in the future, in order to improve services of people in rural areas.
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 A. E. Amalia, G. Airlangga, and A. N. A. Thohari, “Breast Cancer Image Segmentation Using K-Means Clustering Based on GPU Cuda Parallel Computing,” J. INFOTEL, vol. 10, no. 1, Feb. 2018.
 A. R. Ahlan and B. Isma, “User Acceptance of Health Information Technology ( HIT ) in Developing Countries?: A Conceptual Model,” Procedia Technol., vol. 16, pp. 1287–1296, 2014.
 S. Saravanan and P. Sudhakar, “Telemedicine communication system in Mobile units,” in 2017 International Conference on Computer Communication and Informatics (ICCCI), 2017, pp. 1–4.
 M. C. Paul, S. Sarkar, M. M. Rahman, S. M. Reza, and M. S. Kaiser, “Low cost and portable patient monitoring system for E-Health services in Bangladesh,” in 2016 International Conference on Computer Communication and Informatics (ICCCI), 2016, pp. 1–4.
 P. Wicks, J. Stamford, M. A. Grootenhuis, L. Haverman, and S. Ahmed, “Innovations in E-Health ,” Quality of Life Research. 2014.
 J. P. Weiner, S. Yeh, and D. Blumenthal, “The Impact Of Health Information Technology And E-Health On The Future Demand For Physician Services,” Health Aff., vol. 32, no. 11, pp. 1998–2004, Nov. 2013.
 C. Thuemmler and C. Bai, “E-Health in China,” in Health 4.0: How Virtualization and Big Data are Revolutionizing Healthcare, Springer, Cham, 2017, pp. 155–185.
 P. Kierkegaard, “eHealth in Denmark: A Case Study,” J Med Syst, vol. 37, no. 6, p. 9991, 2013.
 E. Hage, J. P. Roo, M. A. G. Van Offenbeek, and A. Boonstra, “Implementation factors and their effect on E-Health service adoption in rural communities: A systematic literature review,” BMC Health Serv. Res., vol. 13, no. 1, p. 19, 2013.
 P. W. Handayani, A. N. Hidayanto, A. A. Pinem, I. C. Hapsari, P. I. Sandhyaduhita, and I. Budi, “Acceptance Model of a Hospital Information System,” Int. J. Med. Inform., 2016.
 K. Cresswell and A. Sheikh, “Organizational issues in the implementation and adoption of health information technology innovations: An interpretative review,” Int. J. Med. Inform., vol. 82, no. 5, pp. e73–e86, 2013.
 F. Davis, “Perceived Usefulness, Perceived East of Use, and User Acceptance of Information Technology,” MIS Q., vol. 13, no. 3, pp. 319–340, 1989.
 M. Fishbein and I. Ajzen, Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research. 1975.
 J.-L. Hsiao and R.-F. Chen, “Critical factors influencing physicians’ intention to use computerized clinical practice guidelines: an integrative model of activity theory and the technology acceptance model,” BMC Med. Inform. Decis. Mak., vol. 16, no. 1, p. 3, Dec. 2015.
 C.-H. Hsiao and K.-Y. Tang, “Examining a Model of Mobile Healthcare Technology Acceptance by the Elderly in Taiwan,” J. Glob. Inf. Technol. Manag., vol. 18, no. 4, pp. 292–311, Oct. 2015.
 T. P. Borges Jr, Uirassu MSc; Kubiak, “Continuous Glucose Monitoring in Type 1 Diabetes: Human Factors and Usage,” J. Diabetes Sci. Technol., vol. 10, no. 3, pp. 633–639, 2016.
 J.-L. Hsiao, W.-C. Wu, and R.-F. Chen, “Factors of accepting pain management decision support systems by nurse anesthetists,” BMC Med. Inform. Decis. Mak., vol. 13, no. 1, p. 16, 2013.
 C.-F. Liu, Y.-C. Tsai, and F.-L. Jang, “Patients’ Acceptance towards a Web-Based Personal Health Record System: An Empirical Study in Taiwan,” Int. J. Environ. Res. Public Health, vol. 10, no. 12, pp. 5191–5208, Oct. 2013.
 R. Gajanayake, R. Iannella, and T. Sahama, “An Insight into the Adoption of Accountable-eHealth Systems – An Empirical Research Model Based on the Australian Context,” IRBM, vol. 37, no. 4, pp. 219–231, Aug. 2016.
 F. D. . D. Viswanath Venkatesh , Michael G . Morris , Gordon B . Davis, V. Venkatesh, M. G. Morris, G. B. Davis, and F. D. Davis, “User acceptance of information technology: Toward a unified view,” MIS Q., vol. 27, no. 3, pp. 425–478, 2003.
 I. Ajzen, “The theory of planned behavior,” Organ. Behav. Hum. Decis. Process., vol. 50, no. 2, pp. 179–211, Dec. 1991.
 F. D. Davis, R. P. Bagozzi, and P. R. Warshaw, “Extrinsic and Intrinsic Motivation to Use Computers in the Workplace1,” J. Appl. Soc. Psychol., vol. 22, no. 14, pp. 1111–1132, Jul. 1992.
 L. Lazuras and A. Dokou, “Mental health professionals’ acceptance of online counseling,” Technol. Soc., vol. 44, pp. 10–14, 2016.
 M.-P. Gagnon, É.-R. Nsangou, J. Payne-Gagnon, S. Grenier, and C. Sicotte, “Barriers and facilitators to implementing electronic prescription: a systematic review of user groups’ perceptions,” J. Am. Med. Informatics Assoc., vol. 21, no. 3, pp. 535–541, May 2014.
 J. Ross, F. Stevenson, R. Lau, and E. Murray, “Factors that influence the implementation of E-Health : A systematic review of systematic reviews (an update),” Implement. Sci., vol. 11, no. 1, pp. 1–12, 2016.
 S. Benavides-Vaello, A. Strode, and B. C. Sheeran, “Using Technology in the Delivery of Mental Health and Substance Abuse Treatment in Rural Communities: A Review,” J. Behav. Health Serv. Res., vol. 40, no. 1, pp. 111–120, Jan. 2013.
 M. Duplaga, “Searching for a Role of Nursing Personnel in Developing Landscape of Ehealth: Factors Determining Attitudes toward Key Patient Empowering Applications,” PLoS One, vol. 11, no. 4, 2016.
 S. Jaros?awski and G. Saberwal, “In eHealth in India today, the nature of work, the challenges and the finances: an interview-based study,” BMC Med. Inform. Decis. Mak., vol. 14, no. 1, 2014.
 G. T. Olok, W. O. Yagos, and E. Ovuga, “Knowledge and attitudes of doctors towards E-Health use in healthcare delivery in government and private hospitals in Northern Uganda: A cross-sectional study,” BMC Med. Inform. Decis. Mak., 2015.
 W. Wang et al., “Renal transplant patient acceptance of a self-management support system,” 2017.
 J. Li, A. Talaei-Khoei, H. Seale, P. Ray, and C. R. Macintyre, “Health Care Provider Adoption of eHealth: Systematic Literature Review.,” Interact. J. Med. Res., vol. 2, no. 1, p. e7, Apr. 2013.
 T. M. Waters et al., “Effect of Medicare’s Nonpayment for Hospital-Acquired Conditions,” JAMA Intern. Med., vol. 175, no. 3, p. 347, Mar. 2015.
 I. Cho, I. Park, E. Kim, E. Lee, and D. W. Bates, “Using EHR data to predict hospital-acquired pressure ulcers: A prospective study of a Bayesian Network model,” Int. J. Med. Inform., vol. 82, no. 11, pp. 1059–1067, Nov. 2013.
 A. Naghieh and M. Parvizi, “Exercising soft closure on lay health knowledge? Harnessing the declining power of the medical profession to improve online health information,” Soc. Theory Heal., vol. 14, no. 3, pp. 332–350, 2016.
 F. Cabitza and C. Batini, “Information Quality in Healthcare,” in Data and Information Quality, Springer, Cham, 2016, pp. 403–419.
 L. Nguyen, E. Bellucci, and L. T. Nguyen, “Electronic health records implementation: An evaluation of information system impact and contingency factors,” Int. J. Med. Inform., vol. 83, no. 11, pp. 779–796, 2014.
 M. Y. Chang, C. Pang, J. Michael Tarn, T. S. Liu, and D. C. Yen, “Exploring user acceptance of an e-hospital service: An empirical study in Taiwan,” Comput. Stand. Interfaces, vol. 38, pp. 35–43, 2015.
 A. Eslami Andargoli, H. Scheepers, D. Rajendran, and A. Sohal, “Health information systems evaluation frameworks: A systematic review,” Int. J. Med. Inform., vol. 97, pp. 195–209, 2017.
 S. A. O’Neill et al., “Development of a technology adoption and usage prediction tool for assistive technology for people with dementia,” Interact. Comput., vol. 26, no. 2, pp. 169–176, 2014.
 T. L. M. Suryanto, D. B. Setyohadi, and A. Faroqi, “Analysis of the effect of information system quality to intention to reuse of employee management information system (Simpeg) based on information systems success model,” vol. 58, 2016.
 S. Faber, M. van Geenhuizen, and M. de Reuver, “eHealth adoption factors in medical hospitals: A focus on the Netherlands,” Int. J. Med. Inform., vol. 100, pp. 77–89, Apr. 2017.
 P. Ifinedo, “Empirical Study of Nova Scotia Nurses’ Adoption of Healthcare Information Systems: Implications for Management and Policy-Making,” Kerman Univ. Med. Sci., vol. 7, no. 74, pp. 317–327, 2018.
 C. Fornell and D. F. Larcker, “Evaluating Structural Equation Models with Unobservable Variables and Measurement Error,” J. Mark. Res., vol. 18, no. 1, p. 39, 1981.
 M. Tenenhaus, V. E. Vinzi, Y.-M. Chatelin, and C. Lauro, “PLS path modeling,” Comput. Stat. Data Anal., vol. 48, pp. 159–205, 2005.
 Wetzels, Odekerken-Schröder, and van Oppen, “Using PLS Path Modeling for Assessing Hierarchical Construct Models: Guidelines and Empirical Illustration,” MIS Q., vol. 33, no. 1, p. 177, 2009.
 P. W. Handayani, A. N. Hidayanto, D. Ayuningtyas, and I. Budi, “Hospital information system institutionalization processes in indonesian public, government-owned and privately owned hospitals,” Int. J. Med. Inform., vol. 95, pp. 17–34, 2016.
 A. R. Ahlan and B. I. Ahmad, “User Acceptance of Health Information Technology (HIT) in Developing Countries: A Conceptual Model,” Procedia Technol., vol. 16, pp. 1287–1296, Jan. 2014.