Background: Many hospitals have adopted mobile nursing carts that can be easily rolled up to a patient’s bedside to access charts and help nurses perform their rounds. However, few papers have reported data regarding the use of wireless computers on wheels (COW) at patients’ bedsides to collect questionnaire-based information of their perception of hospitalization on discharge from the hospital. Objective: The purpose of this study was to evaluate the relative efficiency of computerized adaptive testing (CAT) and the precision of CAT-based measures of perceptions of hospitalized patients, as compared with those of nonadaptive testing (NAT). An Excel module of our CAT multicategory assessment is provided as an example. Method: A total of 200 patients who were discharged from the hospital responded to the CAT-based 18-item inpatient perception questionnaire on COW. The numbers of question administrated were recorded and the responses were calibrated using the Rasch model. They were compared with those from NAT to show the advantage of CAT over NAT. Results: Patient measures derived from CAT and NAT were highly correlated (r = 0.98) and their measurement precisions were not statistically different (P = .14). CAT required fewer questions than NAT (an efficiency gain of 42%), suggesting a reduced burden for patients. There were no significant differences between groups in terms of gender and other demographic characteristics. Conclusions: CAT-based administration of surveys of patient perception substantially reduced patient burden without compromising the precision of measuring patients’ perceptions of hospitalization. The Excel module of animation-CAT on the wireless COW that we developed is recommended for use in hospitals. Copyright © 2011 Tsair-Wei Chien, Wen-Chung Wang, Sheng-Yun Huang, Wen-Pin Lai, Julie Chi Chow.
CitationChien, T.-W., Wang, W.-C., Huang, S.-Y., Lai, W.-P., & Chow, J. C. (2011). A web-based computerized adaptive testing (CAT) to assess patient perception in hospitalization. Journal of Medical Internet Research, 13(3), e61.
- Computer on wheels
- Computerized adaptive testing
- Nonadaptive testing
- Item response theory (IRT)
- Classic test theory