Rizky Taufik , Akhmad
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Model of Improving The Utilization of Hospital Management Information System (SIMRS) Based On Human, Organization Technology-Fit (Hot-Fit) Method at RSPI Prof. Dr. Sulianti Saroso Suryana, Anang; Adikara, Fransiskus; Arrozi , MF; Rizky Taufik , Akhmad
Journal of Public Health Education Vol. 1 No. 2 (2022): Journal of Public Health Education
Publisher : MPI Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53801/jphe.v1i02.26

Abstract

Introduction: Hospital management requires fast and accurate data management to create quality services. As a result, an assessment is required, particularly utilizing the HOT-Fit method, which was established with knowledge and regulation in mind, to assess the information system in this study. Objectives: This study aims to analyze the influence of humans, organizations, technology, knowledge, and regulation on benefits either simultaneously or partially. Method: This study uses quantitative research methods with the type of research that is causality explanatory. The analytical method used is multiple linear regression analysis. Respondents in this study were the respondents of RSPI Prof. Dr. Sulianti Saroso who operates SIMRS directly with as many as 154 employees. Result: The results of this study showed that there is a significant influence from Humans, Organizations, Technology, Knowledge, and Regulations that affect the benefits of 80.9%. Human, Organization, Technology, Knowledge, and Regulation partially affect the benefit, with the provisions of the regulation being the variable that has the highest influence on the benefit. Conclusion: Regulation is the most dominant variable affecting the benefits of using SIMRS. Follow-up in this case, especially regulations is that the hospital is expected not to replace the developer and use a qualified developer who understands all business processes in the hospital. For further researchers, it can analyze the influence of other variables on benefits and analyze how the influence of knowledge and regulation variables if they become mediating variables.