ArticleBMC medical informatics and decision making2020
A combination of two methods for evaluating the usability of a hospital information system.
Article in BMC medical informatics and decision making, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.
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Who cites it
15 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Usability evaluation methods for hospital information systems: a systematic review.BMC health services research · 2025Pooled it
- Optimizing HIV Care Engagement: Usability of a mHealth App for Identifying and Retaining Individuals with Nonviral Suppression in Digital Cohort.Applied clinical informatics · 2026Article
- Comprehensive usability evaluation of electronic prescription systems: integrating expert and user perspectives.BMC medical informatics and decision making · 2025Article
- Do explainable AI (XAI) methods improve the acceptance of AI in clinical practice? An evaluation of XAI methods on Gleason grading.The journal of pathology. Clinical research · 2025Article
- Optimization of a Web-Based Self-Assessment Tool for Preconception Health in People of Reproductive Age in Australia: User Feedback and User-Experience Testing Study.JMIR human factors · 2024Article
- Evaluating the usability of Iran's national comprehensive health information system: a think-aloud study to uncover usability problems in the recording of childcare data.BMC medical informatics and decision making · 2024Article
- Evaluation of a digital patient education programme in patients with coronary artery disease, a survey-based study.BMC health services research · 2024Article
- Usability of Standards for Scaffolding in a Health Sciences Programme: A feasibility Study.BMC nursing · 2024Article
- Usability of an Automated System for Real-Time Monitoring of Shared Decision-Making for Surgery: Mixed Methods Evaluation.JMIR human factors · 2024Article
- Designing Electronic Data Capture Systems for Sustainability in Low-Resource Settings: Viewpoint With Lessons Learned From Ethiopia and Myanmar.JMIR public health and surveillance · 2024Article
- Article
- Inpatient EHR User Experience and Hospital EHR Safety Performance.JAMA network open · 2023Article
- Comparison of usability evaluation methods for a health information system: heuristic evaluation versus cognitive walkthrough method.BMC medical informatics and decision making · 2022Article
- Investigating the Impact of Usability on Energy Efficiency of Web-based Personal Health Records.Journal of medical systems · 2021Article
- User testing of a diagnostic decision support system with machine-assisted chart review to facilitate clinical genomic diagnosis.BMJ health & care informatics · 2021Article
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2 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundNone of the evaluation methods can identify all the usability problems of information systems. So far, no study has sufficiently investigated the potential of a combination of these methods to identify usability problems. The present study aimed at examining the potential for combining two commonly utilized user-based and expert-based methods to evaluate the usability of a hospital information system.
methodsThink aloud (TA) and Heuristic evaluation (HE) methods were used to identify the usability problems of two subsystems of the Social Security Electronic System in Iran. To this end, the problems were categorized into five groups based on ISO-Nielsen usability attributes. The Chi-square test was applied to compare the intended methods based on the total number of problems and the number of problems within each group, followed by utilizing the Mann-Whitney U test to compare the mean severity scores of these methods.
resultsThe evaluation by combining these methods yielded 423 problems of which 75% varied between the methods. The two methods were significantly different in terms of the total number of problems, the number of problems in each usability group, and the mean severity of two satisfaction and efficiency attributes (P < 0.05). However, no significant difference was observed between the two methods based on the mean severity of problems and severity scores related to three usability attributes i.e., effectiveness, learnability, and error prevention (P > 0.05). In addition, the mean severity of problems identified by each method was at the "Major" level.
conclusionBased on the results, although the mean severity scores of the identified problems were not significantly different, these methods identify heterogeneous problems. HE mainly identifies problems related to satisfaction, learnability, and error prevention while TA detects problems related to effectiveness and efficiency attributes. Therefore, using a combination of these two methods can identify a wider range of usability problems.
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