Critical Success Factors Influencing the Acceptance of a Casemix-Based Hospital Information System: Cross-Sectional Study

Abstract

Background: The Ministry of Health Malaysia integrated the Casemix System into the Total Hospital Information System (THIS) to improve care delivery, resource efficiency, and cost-effectiveness. Casemix, a patient classification tool, supports clinical documentation, hospital financing, and management by grouping patients according to diagnoses and resource use. Within THIS, it enables automated coding, streamlined workflows, and better hospital performance. Its success, however, relies on acceptance by medical doctors who ensure accurate documentation and coding. Despite its importance, limited empirical research has examined factors influencing Casemix acceptance in Malaysia’s hospital information system context. Understanding these factors is critical for effective implementation and sustained use. Objective: This study aims to investigate the interrelationships between critical success factors namely system quality (SY), information quality (IQ), service quality (SQ), organizational characteristic (ORG), perceived ease of use (PEOU), perceived usefulness (PU), and intention to use (ITU) on user acceptance of the Casemix system in hospitals equipped with THIS. Methods: This study used a cross-sectional design, using a self-administered digital questionnaire that was developed by adopting and adapting previously validated instruments, grounded in the Human-Organization-Technology Fit and Technology Acceptance Model (TAM) frameworks. The instrument underwent rigorous validation and reliability procedures, including content and criterion validation through expert review, exploratory factor analysis to assess item appropriateness, and confirmatory factor analysis to establish construct, convergent, and discriminant validity. Proportionate stratified random sampling was used to ensure equitable representation of medical doctors across 5 Ministry of Health hospitals, each representing 1 of Malaysia’s geographical zones. The minimum required sample size of 375 was proportionally distributed across 4 categories of medical doctors within these hospitals. Based on structural equation modeling standards, a total of 343 valid responses were obtained, yielding a response rate of 91.5%. Path analysis was conducted using covariance-based structural equation modeling with SPSS Amos (version 24.0; IBM Corp) to assess the direct relationships among the constructs in this study. Results: Path analysis revealed that SY (β=–0.262, P=.043) and IQ (β=0.307, P=.01) significantly influenced PEOU. PEOU (β=0.105, P=.02) and PU (β=0.580, P