Ranking and selecting hospital information systems: A multi-criteria decision making approach using TOPSIS in Hamadan, Iran

This study evaluated and ranked Hospital Information Systems (HIS) in teaching hospitals affiliated with Hamadan University of Medical Sciences, Iran. A cross-sectional design was employed, evaluating three HIS systems (PARDAZESHGARAN, SAYAN, and RAYAVARAN). Eight key criteria—technical quality, software quality, support quality, workflow support quality, output quality, cost, user satisfaction, and interdepartmental communication quality—were considered. Criterion weights were determined through expert consultation. The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method was used to rank the HIS systems. Results indicated that cost and output quality were assigned the highest weights. The PARDAZESHGARAN system was ranked first, followed by SAYAN and RAYAVARAN. While this study provides insights into HIS evaluation in this context, limitations related to the sample size should be considered.Author summary: In this study, we aimed to evaluate and rank the Hospital Information Systems (HIS) used in teaching hospitals affiliated with Hamadan University of Medical Sciences in Iran. Recognizing the crucial role HIS plays in modern healthcare, we sought to provide a systematic and objective assessment to aid decision-makers in selecting and improving these systems. We employed a cross-sectional study design, focusing on three prominent HIS systems: PARDAZESHGARAN, SAYAN, and RAYAVARAN. Our evaluation considered eight key criteria: technical quality, software quality, support quality, workflow support quality, output quality, cost, user satisfaction, and interdepartmental communication quality. We gathered data from expert panels, including hospital staff and university faculty, to determine the weights of these criteria and evaluate the performance of each HIS. Using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), a multi-criteria decision-making method, we ranked the systems. Our findings revealed that cost and output quality were considered the most important factors. The TOPSIS analysis ranked PARDAZESHGARAN as the top-performing system, followed by SAYAN and then RAYAVARAN. This research provides valuable insights into HIS evaluation in the Iranian healthcare context, highlighting the key factors to consider when selecting and implementing these systems. While our study offers a valuable contribution, we acknowledge limitations related to the sample size and expert selection, which could influence the generalizability of our findings. Future research could expand on this work by including a larger sample size, exploring additional evaluation criteria, and investigating the long-term impact of HIS on healthcare quality and patient outcomes.