A combination of two methods for evaluating the usability of a hospital information system

Abstract

Abstract Background None 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. Methods Think 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. Results The 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. Conclusion Based 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.