FAKTOR YANG MEMPENGARUHI PENERIMAAN SISTEM INFORMASI MANAJEMEN RUMAH SAKIT

Muhammad Ade Armansyah Siregar, Prastuti Soewondo

Abstract


Latar Belakang: SIMRS adalah alat informasi yang kuat yang dapat membantu manajer rumah sakit untuk memperbaiki proses pengambilan keputusan dan untuk meningkatkan fungsi positif rumah sakit. Keberhasilan implementasi SIMRS tergantung pada kepuasan pengguna, kebutuhan akan persepsi sistem, kepercayaan dan rasa kepemilikan pengguna terhadap sistem, serta partisipasi pengguna dalam pengembangan sistem.

Tujuan: Penelitian ini bertujuan untuk Menganalisis Faktor yang Mempengaruhi Penerimaan Sistem Informasi Manajemen Kesehatan Rumah Sakit.

Metode: Scoping Review menggunakan database seperti Pubmed, Wiley Online Library, dan ScienceDirect. Hasil pencarian yang memenuhi kriteria kemudian di analisis menggunakan PRISMA Flowchart, ekstraksi data, dan Mapping Tema.

Hasil:  Hasil penelitian dari 148 artikel yang terkait dengan judul dan abstrak, 7 artikel memenuhi kriteria inklusi dan eksklusi. Ditemukan tiga faktor yaitu faktor manusia, faktor teknologi, dan faktor organisasi.

Kesimpulan: Menyederhanakan penggunaan sistem melalui pendidikan bagi pengguna dan menyediakan komprehensif dan pedoman khusus yang sesuai dengan spesialisasi atau departemen pengguna, termasuk kebutuhan kerja pengguna dalam kemampuan penerimaan  SIMRS. Melibatkan pengguna dalam pengembangan, implementasi, dan pendidikan langkah-langkah perangkat lunak SIMRS sangat penting untuk ditingkatkan ke tingkat yang ideal, meningkatkan kepuasan pengguna, dan meningkatkan penerimaan sistem ke tingkat yang optimal.

Keywords


Faktor Penerimaan; Sistem Informasi Manajemen Rumah Sakit

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References


Mohamadali NA, Ab Aziz NF. The Technology Factors as Barriers for Sustainable Health Information Systems (HIS) – A Review. Procedia Computer Science. 2017;124:370–8.

Lulin Z, Owusu-Marfo J, Antwi HA, Xu X. The Contributing Factors to Nurses’ Behavioral Intention to Use Hospital Information Technologies in Ghana. SAGE Open Nursing. 2020 Jan;6:237796082092202.

Chen RF, Hsiao JL. An investigation on physicians’ acceptance of hospital information systems: A case study. International Journal of Medical Informatics. 2012 Dec;81(12):810–20.

Farzandipur M, jeddi F, Azimi E. Factors Affecting Successful Implementation of Hospital Information Systems. Acta Inform Med. 2016;24(1):51.

Hosein B, Luo J, Karami M. Adoption of Hospital Information System Among Nurses: a Technology Acceptance Model Approach. Acta Inform Med. 2019;27(5):305.

Darby AB, Su Y, Reynolds RB, Madlock-Brown C. A Survey-based Study of Pharmacist Acceptance and Resistance to Health Information Technology. 2019;22.

Khalifa M. Barriers to Health Information Systems and Electronic Medical Records Implementation. A Field Study of Saudi Arabian Hospitals. Procedia Computer Science. 2013;21:335–42.

Alsalman D, Alumran A, Alrayes S, Althumairi A, Almubarak S, Alrawiai S, et al. Implementation status of health information systems in hospitals in the eastern province of Saudi Arabia. Informatics in Medicine Unlocked. 2021;22:100499.

Handayani PW, Saladdin IR, Pinem AA, Azzahro F, Hidayanto AN, Ayuningtyas D. Health referral system user acceptance model in Indonesia. Heliyon. 2018 Dec;4(12):e01048.

Alipour J, Mehdipour Y, Karimi A. Factors Affecting Acceptance of Hospital Information Systems in Public Hospitals of Zahedan University of Medical Sciences: A Cross-Sectional Study. 2019;12(4):8.

Nadri H, Rahimi B, Lotfnezhad Afshar H, Samadbeik M, Garavand A. Factors Affecting Acceptance of Hospital Information Systems Based on Extended Technology Acceptance Model: A Case Study in Three Paraclinical Departments. Appl Clin Inform. 2018 Apr;09(02):238–47.

Barzegari S, Ghazisaeedi M, Askarian F, Jesmi A, Gandomani H, Hasani A. Hospital information system acceptance among the educational hospitals. J Nurs Midwifery Sci. 2020;7(3):186.

Gomer S, Hasyim ., Kusumapradja R. Acceptance Model of Hospital Information Management System: Case of Study in Indonesia. EJBMR [Internet]. 2020 Sep 10 [cited 2022 Oct 2];5(5). Available from: https://ejbmr.org/index.php/ejbmr/article/view/505

Prasanna R, Huggins TJ. Factors affecting the acceptance of information systems supporting emergency operations centres. Computers in Human Behavior. 2016 Apr;57:168–81.

Cheng YM. The Effects of Information Systems Quality on Nurses’ Acceptance of the Electronic Learning System. Journal of Nursing Research. 2012 Mar;20(1):19–31.

Carvalho JV, Rocha Á, Vasconcelos J, Abreu A. A health data analytics maturity model for hospitals information systems. International Journal of Information Management. 2019 Jun;46:278–85.

Hsu HH, Wu YH. Investigation of the Effects of a Nursing Information System by Using the Technology Acceptance Model. CIN: Computers, Informatics, Nursing. 2017 Jun;35(6):315–22.

Alanazi A, Al Rabiah F, Gadi H, Househ M, Al Dosari B. Factors influencing pharmacists’ intentions to use Pharmacy Information Systems. Informatics in Medicine Unlocked. 2018;11:1–8.

Santo S, Ayres-de-Campos D. Human factors affecting the interpretation of fetal heart rate tracings: an update. Current Opinion in Obstetrics & Gynecology. 2012 Mar;24(2):84–8.

Meri A, Hasan M, Danaee M, Jaber M, Jarrar M, Safei N, et al. Modelling the utilization of cloud health information systems in the Iraqi public healthcare sector. Telematics and Informatics. 2019 Mar;36:132–46.

Ismail NI, Abdullah NH, Shamsuddin A. Adoption of Hospital Information System (HIS) in Malaysian Public Hospitals. Procedia - Social and Behavioral Sciences. 2015 Jan;172:336–43.

Sharma A, Rana NP, Nunkoo R. Fifty years of information management research: A conceptual structure analysis using structural topic modeling. International Journal of Information Management. 2021 Jun;58:102316.

Wu W, Wu YJ, Wang H. Perceived city smartness level and technical information transparency: The acceptance intention of health information technology during a lockdown. Computers in Human Behavior. 2021 Sep;122:106840.

Ifinedo P. The moderating effects of demographic and individual characteristics on nurses’ acceptance of information systems: A canadian study. International Journal of Medical Informatics. 2016 Mar;87:27–35.

Rahman NAA, Mohamad B, Rahman NAA. Factors Influencing the Quality of e-Services on Hospital Information System (HIS) in Malaysia. Procedia - Social and Behavioral Sciences. 2014 Nov;155:507–12.

Chen C fei, Nelson H, Xu X, Bonilla G, Jones N. Beyond technology adoption: Examining home energy management systems, energy burdens and climate change perceptions during COVID-19 pandemic. Renewable and Sustainable Energy Reviews. 2021 Jul;145:111066.

Handayani PW, Hidayanto AN, Pinem AA, Hapsari IC, Sandhyaduhita PI, Budi I. Acceptance model of a Hospital Information System. International Journal of Medical Informatics. 2017 Mar;99:11–28.

Karimi F, Poo DCC, Tan YM. Clinical information systems end user satisfaction: The expectations and needs congruencies effects. Journal of Biomedical Informatics. 2015 Feb;53:342–54.

Xyrichis A, Iliopoulou K, Mackintosh NJ, Bench S, Terblanche M, Philippou J, et al. Healthcare stakeholders’ perceptions and experiences of factors affecting the implementation of critical care telemedicine (CCT): qualitative evidence synthesis. Cochrane Effective Practice and Organisation of Care Group, editor. Cochrane Database of Systematic Reviews [Internet]. 2021 Feb 18 [cited 2022 Oct 2];2021(2). Available from: http://doi.wiley.com/10.1002/14651858.CD012876.pub2

Hadji B, Martin G, Dupuis I, Campoy E, Degoulet P. 14 Years longitudinal evaluation of clinical information systems acceptance: The HEGP case. International Journal of Medical Informatics. 2016 Feb;86:20–9.

Ciliberti MG, Albenzio M, Annicchiarico G, Sevi A, Muscio A, Caroprese M. Alterations in sheep peripheral blood mononuclear cell proliferation and cytokine release by polyunsaturated fatty acid supplementation in the diet under high ambient temperature. Journal of Dairy Science. 2015 Feb;98(2):872–9.

Hsieh PJ, Lai HM. Exploring people’s intentions to use the health passbook in self-management: An extension of the technology acceptance and health behavior theoretical perspectives in health literacy. Technological Forecasting and Social Change. 2020 Dec;161:120328.

Okumus B, Ali F, Bilgihan A, Ozturk AB. Psychological factors influencing customers’ acceptance of smartphone diet apps when ordering food at restaurants. International Journal of Hospitality Management. 2018 Jun;72:67–77.

Mohamadali NA, Ab Aziz NF. The Technology Factors as Barriers for Sustainable Health Information Systems (HIS) – A Review. Procedia Computer Science. 2017;124:370–8.




DOI: https://doi.org/10.35730/jk.v13i3.848

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