Evaluation of CDSS for Drug Prescriptions Based on Success Measures

Abstract

Objective The Clinical Decision Support System (CDSS) for drug prescriptions was developed by integrating the computerized physician order entry (CPOE) system to support doctors and pharmacists in making correct decisions on prescribing drugs in line with the prescription guidelines by the Health Insurance Review Agency (HIRA). The objective of this study was to evaluate the performance of the CDSS with respect to system quality, information quality, and user satisfaction in reducing prescription errors. Methods The study was based on survey data from 38 hospitals that were using the CDSS for drug prescriptions. To identify factors influencing the performance of CDSS, multiple linear regression and chi-square analyses were performed. Results Regression analysis showed that the variables for system quality and information quality significantly influenced the overall system performance. Specifically, ease of understanding the results and terminology assystem quality measures significantly influenced user satisfaction. Furthermore, based on chi-square analysis, two independent variables (ease of understanding results and decision support functions) were statistically significant with respect to all four dependent variables (information satisfaction, system satisfaction, willingness to recommend to other hospitals, and drug safety). Conclusion Based on this study, users should be educated to improve their understanding of the system,and system and information quality should be continuously monitored to improve user satisfaction. We examined the effects of two quality measures on the overall system performance by combining user satisfaction and improvement in drug safety. The results of the multiple regression analysis showed that both system quality and information quality significantly influenced the system performance. System quality was slightly more significant than information quality measure ( ). The overall R-square was 0.244. Of the three system quality measures, ease of understanding results and ease of understanding terminology significantly influenced user satisfaction, but ease of system use did not. The R-square of this model was 0.391 ( ). Of five information quality measures, however, only decision supporting function significantly influenced user satisfaction, with an R-square of 0.455 ( ). This implies that decision supporting is the most important function for CDSS, whereas timeliness or other factors may be more important functions for CPOE. While all system quality measures were significantly associated with information satisfaction, ease of terminology understandability was not positively (or consistently) associated with information satisfaction ( ). That is, of the highly satisfied respondents on information, 66.7% of the respondents did not understand terminology; 28.2% of them slightly understood terminology; and 80% of them highly understood terminology. All information quality measures were significantly associated with information satisfaction and highly satisfied respondents on information also positively responded to information quality. However, only the decision supporting function had higher percentage of positive respondents (55.8%) than in-between respondents (41.6%). All quality measures except ease of the system use were significantly associated with the overall satisfaction ( ). Specifically, ease of understanding results received a positive response from 45 respondents (58.4%), of whom 66.7% also gave a positive response to the overall satisfaction with the system. Of the information quality measures, decision making support functions obtained a positive response from 43 (55.8%), of whom 65.1% also gave a positive response to the overall satisfaction. This analysis showed that ease of understanding results for system quality and decision supporting function for information quality were the two biggest contributors to the increase in overall satisfaction. All quality measures except information accuracy were significantly associated with the willingness to recommend it to others ( ). Specifically, of the system quality measures, ease of understanding results obtained a positive response from 45 respondents (58.4%), of whom 97.8% also gave a positive response (average or higher) to the willingness to recommend to others. Of the information quality measures, decision supporting function obtained a positive response from 43 respondents (55.8%), of whom 97.7% also gave a positive response (average or higher) to the willingness to recommend to others ( ). This analysis showed that ease of understanding results and the decision supporting function were also the two biggest contributors to willingness to recommend to others.