Information processing in electronic medical records: A survey validation
Objective: The purpose of this study was to validate the Clinical Information Processing Instrument. This instrument attempts to examine information processing in electronic medical records (EMRs). We drew upon the theory of swift and even flow to guide survey development and construction. Materials and Methods: We used a mixed-methods approach to gather data from registered nurses. Nurses were invited to participate in focus groups, an expert panel, and the survey validation process. A semi-structured questionnaire addressed the following themes: method of communication, quality of information, and usability of the system. Results: We conducted a confirmatory factor analysis using structural equation modelling. The Kaiser-Meyer-Olkin measure was greater than 0.7 (0.90), and the Bartlett's test of sphericity was significant (X2 = 1519.03, df = 105, P < 0.001). The proposed structural equation model was analysed and revised to a final model that was statistically significant. The final survey, Clinical Information Processing Instrument, contained 18 Likert scale questions that supported the tenets of the theory of swift and even flow. Discussion: The nurses perceived EMRs as efficient for medication management, time management, and communication. The Clinical Information Processing Instrument is a validated survey tool that assesses information flow in EMRs. Conclusions: The Clinical Information Processing Instrument was validated as an approach to analyse the utility of EMR in disseminating information among clinical staff. To increase the utility and meaningful use of EMR systems, it is important to consider factors that affect the distribution of information among clinicians.
Journal of Evaluation in Clinical Practice
Digital Object Identifier (DOI)
Williams, Cynthia; Hamadi, Hanadi; Cummings, Cynthia; and Zakari, Nazik M.A., "Information processing in electronic medical records: A survey validation" (2019). UNF Faculty Research and Scholarship. 967.