Analysis of Information Management System Utilization at Pelengkap Medical Center Hospital, Jombang, East Java
Abstract
Background: Hospital Management Information System (SIMRS) is an information technology system that integrates the entire flow of hospital services in the form of a network of coordination, reporting, and administrative procedures to obtain precise and accurate information. The successful implementation of SIMRS depends on the use of the system by staff working in health care facilities. The model used in analyzing the use of SIMRS is the Technology Acceptance Model (TAM). The purpose of this study was to determine the effect of the TAM construct variable on the use of SIMRS.
Subjects and Method: This was an analytical observational study with a cross-sectional design. The study was conducted in Pelengkap Medical Center Hospital, Jombang, East Java, in April 2022. A sample of 73 staff was selected by random sampling. The sampled staff are active users of SIMRS for at least 1 year. The dependent variable was the use of SIMRS. The independent variables observed were profession and training education. The data were collected by questionnaire and analzed by path analysis.
Results: MIS utilization was directly affected by positive attitude (b= 3.12; 95% CI= 1.67 to 4.58; p<0.001) and perceived ease of use (b= 2.07; 95% CI= 0.63 to 3.50; p= 0.005). It was indirectly affected by education/ trining, profession, and perceived benefit.
Conclusion: MIS utilization is directly affected by positive attitude and perceived ease of use. It is indirectly affected by education/ trining, profession, and perceived benefit.
Keywords: SIMRS, Technology Acceptance Model
Correspondence:Rendi Adiansa. Masters Program in Public Health, Universitas Sebelas Maret. Jl. Ir. Sutami 36A, Surakarta 57126, Central Java. Email: adiansarendi@gmail.com. Mobile : 08816008735
Journal of Health Policy and Management, (2022), 07(02): 166-175
https://doi.org/10.26911/thejhpm.2022.07.02.08
References
Abdekhoda M, Ahmadi M, Gohari M, Noruzi A (2015). The effects of organizational contextual factors on physicians’ attitude toward adoption of Electronic Medical Records. J Biomed Inform. 53: 174–179. doi: 10.1016 /j.jbi.2014.10.008.
Ahlan AR, Ahmad BI (2014). User Acceptance of Health Information Technology (HIT) in Developing Countries: A Conceptual Model. Procedia Technol. 16, 1287–1296. doi: 10.1016/j.protcy.2014.10.145.
Ahmadi H, Nilashi M, Ibrahim O (2015). Organizational decision to adopt hospital information system: An empirical investigation in the case of Malaysian public hospitals. Int J Med Inform. 84(3), 166–188. doi: 10.1016/j.ijmedinf.2014.12.004.
Wolff J, Pauling J, Keck A, Baumbach J. Success Factors of Artificial Intelligence Implementation in Healthcare. Front Digit Health. 2021 Jun 16;3:594971. doi: 10.3389/fdgth.2021.594971.
Ammenwerth E (2019). Technology Acceptance Models in ealth nformatics: TAM and UTAUT. Stud Health Technol Inform. 263, 64–71. doi: 10.3233/SHTI190111.
Cline GB, Luiz JM (2013). Information technology systems in public sector health facilities in developing countries: The case of South Africa. BMC Med Inform Decis Mak. 13(1). doi: 10.1186/147269471313.
Daerina SRF, Mursityo YT, Rokhmawati RI (2018). Evaluasi Peranan Persepsi Kegunaan dan Sikap Terhadap Penerimaan Sistem Informasi Manajemen Rumah Sakit (SIMRS) di Rumah Sakit Daerah Kalisat (Evaluation of the Role of Perceived Usefulness and Attitudes towards Acceptance of Hospital Management Information Systems (SIMRS) at the Kalisat Regional Hospital). J Pengemb Teknol Inf dan Ilmu Komput. 2(11), 5950–5959. http://jptiik.ub.ac.id/index.php/jptiik/article/view/3473.
Dinev T, Albano V, Xu H, D’Atri A, Hart P (2016). Individuals’ attitudes towards electronic health records: A privacy calculus perspective. doi: 10.1007/9783319232942_2.
Furi FNA, Sandra C, Witcahyo E (2021). Faktor yang Mempengaruhi Persepsi Kemudahan dan Kemanfaatan Penggunaan Sistem Informasi Manajemen RSU Kaliwates Jember Tahun 2019 (Factors Affecting Perceptions of the Ease and Benefit of Using Management Information Systems at RSU Kaliwates Jember in 2019). Pustaka Kesehat. 9(1), 34. doi: 10.19184/pk.v9i1.21025.
Handayani PW, Hidayanto AN, Pinem AA, Hapsari IC, Sandhyaduhita PI, Budi I (2017). Acceptance model of a Hospital Information System. Int J Med Inform. 99: 11–28. doi: 10.1016/j.ijmedinf.2016.12.004.
Holden RJ, Asan O, Wozniak EM, Flynn KE, Scanlon MC (2016). Nurses’ perceptions, acceptance, and use of a novel inroom pediatric ICU technology: testing an expanded technology acceptance model. BMC Med Inform Decis Mak. 16(1), 1–10. doi: 10.1186/s129110160388y.
Hsieh PJ (2015). Healthcare professionals’ use of health clouds: Integrating technology acceptance and status quo bias perspectives. Int J Med Inform. 84(7), 512–523. doi: 10.1016/j.ijmedinf.2015.03.004.
Kamal SA, Shafiq M, Kakria P (2020). Investigating acceptance of telemedicine services through an extended technology acceptance model (TAM). Technol Soc. 60: 101212. doi: 10.1016/j.techsoc.2019.101212.
Khalifa M (2013). Barriers to health information systems and electronic medical records implementation a field study of Saudi Arabian hospitals. Procedia Comput Sci. 21, 335–342. doi: 10.1016/j.procs.2013.09.044.
Kim S, Lee KH, Hwang H, Yoo S (2015). Analysis of the factors influencing healthcare professionals’ adoption of mobile electronic medical record (EMR) using the unified theory of acceptance and use of technology (UTAUT) in a tertiary hospital. BMC
Med Inform Decis Mak, 16(1), 1–12. doi: 10.1186/s1291101602498.
Maillet E, Mathieu L, Sicotte C (2015). Modeling factors explaining the acceptance, actual use and satisfaction of nurses using an Electronic Patient Record in acute care settings: An extension of the UTAUT. Int J Med Inform. 84(1), 36–47. doi: 10.1016/j.ijmedinf.2014.09.004.
Nadri H, Rahimi B, Afshar HL, Samadbeik M, Garavand A (2018). Factors affecting acceptance of hospital information systems based on extended technology acceptance model: A case study in three paraclinical departments. Appl Clin Inform. 9(2), 238–247. doi: 10.1055/s00381641595.
Nguyen M, Fujioka J, Wentlandt K, Onabajo N, Wong I, Bhatia RS, Bhattacharyya O (2020). Using the technology acceptance model to explore health provider and administrator perceptions of the usefulness and ease of using technology in palliative care.BMC Palliat Care, 19(1), 1–9. doi: 10.1186/s12904020006448.
Ojo AI (2017). Validation of the delone and mclean information systems success model. Healthc Inform Res, 23(1), 60–66. doi: 10.4258/hir.2017.23.
Puhan MA, Chandra D, Mosenifar Z (2017). Trust, perceived risk, perceived ease of use and perceived usefulness as factors related to mHealth technology use. Study Heal Technol Inf. 37(4): 784790.
Rho MJ, Choi I young, Lee J (2014) Predictive factors of telemedicine service acceptance and behavioral intention of physicians. Int J Med Inform. 83(8):559571. doi:10.1016/j.ijmedinf.2014.05.005.
Sombat P (2018) The Acceptance Model of Hospital Information Systems in Thailand: A Conceptual Framework Extending TAM2018 5th Int Conf Ind Eng Appl. 8994.
Supriyati (2017). Aplikasi technology acceptance model pada sistem informasi manajemen Rumah Sakit (Application of Technology Acceptance Model in Hospital Management Information System). J Bisnis Manaj. 2017;17(1):81102. doi: 10.20961/jbm.v17i1.12308.
Tubaishat A (2018) Perceived usefulness and perceived ease of use of electronic health records among nurses: Application of Technology Acceptance Model. Informatics Heal Soc Care. 2018;43(4):379389. doi:10.1080 /17538157.2017.1363761.
Pemerintah Republik Indonesia (2009). Undang Undang Tentang Rumah Sakit. No.442019. https://jdihn.go.id/files/4/2009uu044.pdf.
Zhao Y, Ni Q, Zhou R (2018)What factors influence the mobile health service adoption? A metaanalysis and the moderating role of age. Int J Inf Manage. 342350. doi:10.1016 /j.ijinfomgt.2017.08.006
