Assessing and comparing the usability of Chinese EHRs used in two Peking University hospitals to EHRs used in the US: A method of RUA.

Abstract

The objective of this study was to investigate the usability level of Chinese hospital Electronic Health Records (EHRs) by assessing the completion times of EHRs for seven "meaningful use (MU)" relevant tasks conducted at two Chinese tertiary hospitals and comparing the results to those of relevant research conducted in US EHRs. Using Rapid Usability Assessment (RUA) developed by the National Center for Cognitive Informatics and Decision Making (NCCD), the usability of EHRs from two Peking University hospitals was assessed using a three-step Keystroke Level Model (KLM) in a laboratory environment. (1) The total EHR task completion time for 7 MU relevant test tasks showed no significant differences between the two Chinese EHRs and their US counterparts, in which the time for thinking was relatively large and comprised 35.6% of the total time. The time for the electronic physician order was the largest. (2) For specific tasks, the mean completion times of the 2 hospital EHR systems spent on recording, modifying and searching (RMS) the medication orders were similar to those for the RMS radioactive tests; the mean time spent on the RMS laboratory test orders were much less. (3) There were 85 usability problems identified in the 2 hospital EHR systems. In Chinese EHRs, a substantial amount of time is required to complete tasks relevant to MU targets and many preventable usability problems can be discovered. The task completion time of the 2 Chinese EHR systems was a little shorter than in the 5 reported US EHR systems, while the differences in smoking status and CPOE tasks were obvious; one main reason for these differences was the use of structured data entry. The efficiency of Chinese and US EHRs was not significantly different. The key to improving the efficiency of both systems lies in expediting the Computerized physician order entry (CPOE) task. Many usability problems can be identified using heuristic assessments and improved by corresponding actions.