Acceptance Analysis of the Electronic Kohort Information System for Maternal and Child Health Using the Technology Acceptance Model at the Bima City Health Center
Keywords:
Acceptance, Health Information System, Electronic Kohort. Maternal and Child Health, Technology Acceptance Model
Abstract
The Maternal and Child Health (MCH) Program in Indonesia is faced with a diversity of achievements between regions caused by disparities in the capacity of the health system and exacerbated by the Covid-19 pandemic which has caused a decrease in service activities and reporting quality so that digitalization of services is needed. This type of research is qualitative research with the design of phenomenological studies using thematic analysis with the help of the Nvivo 12 application. Primary data collection was carried out by means of observation and in-depth interviews with research informants by purposive sampling. To increase the credibility of the data use source triangulation. The research informants consisted of the head of the family health services section, the head of the health centers and the midwife as the user of the e-cohort. Thirteen informants (11 women and 2 men) participated in the study. Most informants can use the core functions of the e-cohort app navigation menu. The study proposes that the perceived perception of ease of use may not be in line with the perceived expediency of explaining variations in the successful acceptance of MCH e-cohort applications. The study also found that there were differences in outcomes between user perceptions at the operational level and policy makers at the managerial level. In general, the analysis collects several types of obstacles and potentially problems that negatively affect the usefulness of the e-cohort application : not being able to make the work of midwives easier and faster, ineffective and not so much to increase the productivity of performance. With regard to ease of use, users feel that the e-cohort can be easily learned and used. The e-cohort is considered to have value as a system that makes the work of midwives more difficult and hinders the work, however, the appearance, elements, features and design are perceived to be quite easy to use. In addition, users also highlight the need to consider how the system can be implemented in order to minimize the impact and optimize usability
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References
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Hardiana, D., Nugraha, N., Dewi, F. P., Supriyatna, Y., & Lhutfi, I. (2022). The Effectiveness of Using Online Learning Media during the Covid-19 Pandemic Study in Students of the Accounting Education Study Program, Universitas Pendidikan Indonesia (UPI). JPAK (Journal of Accounting and Financial Education), 10(1).
Holden, R. J., & Karsh, B. T. (2010). The Technology Acceptance Model: Its past and its future in health care. Journal of Biomedical Informatics, 43(1), 159–172. https://doi.org/10.1016/j.jbi.2009.07.002
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Jo, H. S., Song, T. M., & Kim, B. G. (2017). Analysis of the factors affecting consumer acceptance of accredited online health information. Journal of Korean Medical Science, 32(11), 1757–1763. https://doi.org/10.3346/jkms.2017.32.11.1757
Joo, Y. J., Park, S., & Lim, E. (2018). Factors influencing preservice teachers’ intention to use technology: TPACK, teacher self efficacy, and technology acceptance model. Journal of Educational Technology & Society, 3, 48–59.
Kabbiri, R., Dora, M., Kumar, V., Elepu, G., & Gellynck, X. (2018). Mobile phone adoption in agri-food sector: Are farmers in Sub-Saharan Africa connected? Technological Forecasting and Social Change, 131(December), 253–261. https://doi.org/10.1016/j.techfore.2017.12.010
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Kinanti, F. S., & Pertiwi, A. A. P. (2019). Evaluation of the Use of Nursing Management Information System at Grhasia Mental Hospital, Yogyakarta Special Region. Journal of Information Systems for Public Health, 4(1), 16–27.
Kowitlawakul, Y. (2011). The technology acceptance model: Predicting nurses’ intention to use telemedicine technology (eICU). CIN - Computers Informatics Nursing, 29(7), 411–418. https://doi.org/10.1097/NCN.0b013e3181f9dd4a
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Kurahashi, A. M., Stinson, J. N., van Wyk, M., Luca, S., Jamieson, T., Weinstein, P., Cafazzo, J. A., Lokuge, B., Cohen, E., Rapoport, A., & Husain, A. (2018). The perceived ease of use and usefulness of loop: evaluation and content analysis of a web-based clinical collaboration system. JMIR Human Factors, 5(1). https://doi.org/10.2196/humanfactors.7882
Laksmi, N. M. D. P. (2021). Socialization Meeting on Recording and Reporting of Maternal and Child Health E-Cohorts. Directorate of Family Health of the Ministry of Health of the Republic of Indonesia.
Lazuardi, L., Sanjaya, G. Y., Ali, P. B., Siahaan, R. G. M., Achmad, L., & Wulandari, H. (2021). Interoperability of Health Digitalization: Case Study on Use of Information Technology for Maternal and Child Health Services in Indonesia. Business Information Systems, July, 317–327.
Legris, P., Ingham, J., & Collerette, P. (2003). Why do people use information technology? A critical review of the technology acceptance model. Information and Management, 40(3), 191–204. https://doi.org/10.1016/S0378-7206(01)00143-4
Marangunić, N., & Granić, A. (2015). Technology acceptance model: a literature review from 1986 to 2013. Universal Access in the Information Society, 14(1), 81–95. https://doi.org/10.1007/s10209-014-0348-1
Mardiana, S., Tjakraatmadja, J. H., & Aprianingsih, A. (2015). Validating the Conceptual Model for Predicting Intention to Use as Part of Information System Success Model: The Case of an Indonesian Government Agency. Procedia Computer Science, 72, 353–360. https://doi.org/10.1016/j.procs.2015.12.150
Mikarsih, A., Wardah, S., & Hidayat, S. (2020). Factors Affecting the Implementation of a Computer-Based Accounting Information System at the East Mataram Primary Tax Service Office. Scientific Journal of Accounting And Finance, 9(1), 1–11. https://doi.org/10.32639/jiak.v9i1.372
Nadal, C., Sas, C., & Doherty, G. (2020). Technology acceptance in mobile health: Scoping review of definitions, models, and measurement. Journal of Medical Internet Research, 22(7), 1–17. https://doi.org/10.2196/17256
Nugroho, H. ., Supriyanto, S., & Notobroto, H. . (2016). The role of perceived organizational support, personal characteristics and perceived enjoyment in the maternal and child health information system acceptance model (The role of perceived organizational support, personal characteristics, and perceived enjoyment da. Universitas Airlangga.
Nugroho, H. S. W., Notobroto, H. B., & Rosyanti, L. (2021). Acceptance model of a mandatory health information system in Indonesia. Healthcare Informatics Research, 27(2), 127–136. https://doi.org/10.4258/HIR.2021.27.2.127
Payne, T. H., Lovis, C., Gutteridge, C., Pagliari, C., Natarajan, S., Yong, C., & Zhao, L.-P. (2019). Status of health information exchange: a comparison of six countries. Journal of Global Health.
Rachmawati, A. I., Puspitasari, R. D., & Cania, E. (2017). Factors Affecting Antenatal Care (ANC) Visits of Pregnant Women. Majority, 7(November), 72–76.
Rush, B., Celi, L. A., & Stone, D. J. (2019). Applying machine learning to continuously monitored physiological data. Journal of Clinical Monitoring and Computing, 33(5), 887–893. https://doi.org/10.1007/s10877-018-0219-z
Sadoughi, F., & Erfannia, L. (2017). Health information system in a cloud computing context. Studies in Health Technology and Informatics, 236(6), 290–297. https://doi.org/10.3233/978-1-61499-759-7-290
Shachak, A., Domb, S., Borycki, E., Fong, N., Skyrme, A., Kushniruk, A., Reis, S., & Ziv, A. (2015). A Pilot Study of Computer-Based Simulation Training for Enhancing Family Medicine Residents’ Competence in Computerized Settings. Studies in Health Technology and Informatics, 216(Figure 1), 506–510. https://doi.org/10.3233/978-1-61499-564-7-506
Sharifian, R., Askarian, F., Nematolahi, M., & Farhadi, P. (2014). Factors influencing nurses’ acceptance of hospital information systems in Iran: application of the Unified Theory of Acceptance and Use of Technology. Health Information Management Journal, 43(3), 23–28. https://doi.org/10.12826/18333575.2014.0001.Sharifian
Sigilipu, S. (2013). The Effect of The Application of Management Accounting Information and Performance Measurement Systems on Managerial Performance. EMBA Journal : Journal of Economic Research, Management, Business And Accounting, 1(3), 239–247.
Sijariemas Technology Innovation. (2021). Submission of MCH E-Cohort Application to the Ministry of Health of the Republic of Indonesia. Sijarimas.Co.Id. https://www.sijariemas.co.id/penyerahan-aplikasi-e-kohort-kia-kepada-kementrian-kesehatan/
Smeru. (2020). COVID-19 Impacts on Nutrition and Maternal Child Health Services: Case Studyin Five Regions in Indonesia (p. 5). Smeru.
Susanto, R., & Haryati, T. (2019). Product Distribution Data Warehouse Modeling in PT. X. INTENSIVE: Scientific Journal of Research and Application of Information Systems Technology, 3(2), 196. https://doi.org/10.29407/intensif.v3i2.12769
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Published
2023-04-05
How to Cite
Hizriansyah, Prawitasari, S., & Lazuardi, L. (2023). Acceptance Analysis of the Electronic Kohort Information System for Maternal and Child Health Using the Technology Acceptance Model at the Bima City Health Center. Jurnal Sistem Informasi, 19(1), 62-78. https://doi.org/10.21609/jsi.v19i1.1207
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