Information system design for a hospital emergency department: a usability analysis of software prototypes.

STUDY OBJECTIVE: The purpose of this study is to evaluate the usability of emergency department (ED) software prototypes developed for Tablet personal computers (Tablet PCs) in order to keep electronic health records (EHRs) of patients errorless and accessible through mobile technologies. In order to serve this purpose, two alternative prototypes were developed for Tablet PCs: Mobile Emergency Department Software (MEDS) and Mobile Emergency Department Software Iconic (MEDSI) among which the user might choose the more appropriate one for ED operations based on a usability analysis involving the target users. METHODS: The study is based on a case study of 32 potential users of our prototypes at the ED of Kadikoy-AHG in Istanbul, Turkey. We examined usability of the prototypes for medical information systems by means of Nielsen's heuristic evaluation and cognitive walkthrough methods relying on 7-point scales, and scenario completion success rate and average scenario completion time, respectively. RESULTS: The implementation of MEDSI in our case study confirmed the view that the usability evaluation results of iconic GUIs were better than those of non-iconic GUIs in terms of Nielsen's heuristic evaluation, effectiveness and user satisfaction. For the whole sample, paired t-test scores indicated that there was a significant difference (p<0.01) between mean values of Nielsen's usability scores toward MEDS and MEDSI indicating that MEDSI was evaluated more favorably than MEDS. As for effectiveness of the prototypes, significant differences (p<0.01) were noted between MEDS and MEDSI in terms of both overall scenario completion success rate and average scenario completion time. Similarly, for the full sample of users independent sample t-test scores indicated that MEDSI was perceived significantly more favorable (p<0.01) than MEDS in terms of overall user satisfaction. CONCLUSION: The study provides two important contributions to the extant literature. First, it addresses a topic and methodology that serves potentially interesting to the biomedical informatics community. Drawing on good background information and appropriate context, it involves various aspects of usability testing. Another contribution of the study lies in its examination of two different prototypes during the design phase involving the target users.

Prediction of cyclosporine A blood levels: an application of the adaptive-network-based fuzzy inference system (ANFIS) in assisting drug therapy.

OBJECTIVE: Therapeutic drug monitoring (TDM) is a procedure in which the levels of drugs are assayed in various body fluids with the aim of individualizing the dose of critical drugs, such as cyclosporine A. Cyclosporine A assays are performed in blood. METHODS: We proposed the use of the Takagi and Sugeno-type "adaptive-network-based fuzzy inference system" (ANFIS) to predict the concentration of cyclosporine A in blood samples taken from renal transplantation patients. We implemented the ANFIS model using TDM data collected from 138 patients and 20 input parameters. Input parameters for the model consisted of concurrent use of drugs, blood levels, sampling time, age, gender, and dosing intervals. RESULTS: Fuzzy modeling produced eight rules. The developed ANFIS model exhibited a root mean square error (RMSE) of 0.045 with respect to the training data and an error of 0.057 with respect to the checking data in the MATLAB: environment. CONCLUSION: ANFIS can effectively assist physicians in choosing best therapeutic drug dose in the clinical setting.