Development of a Measure of Clinical Information Systems Expectations and Experiences

验证性因素分析 比例(比率) 可靠性(半导体) 心理干预 结构方程建模 心理测量学 心理学 应用心理学 医学 护理部 计算机科学 临床心理学 量子力学 机器学习 物理 功率(物理)
作者
Douglas S. Wakefield,Jonathon R. B. Halbesleben,Marcia M. Ward,Qian Qiu,Jane M. Brokel,Donald K. Crandall
出处
期刊:Medical Care [Lippincott Williams & Wilkins]
卷期号:45 (9): 884-890 被引量:63
标识
DOI:10.1097/mlr.0b013e3180653625
摘要

BACKGROUND/OBJECTIVES: The purpose of this study is to describe the development and initial psychometric properties of a measure of expectations and experiences regarding the impact of clinical information systems on work process and outcomes. RESEARCH DESIGN: Basic item analysis, confirmatory factor analysis, cross-validation factor analyses, and reliability analysis were used to assess the psychometric properties of the scale. SUBJECTS: The initial validation sample included registered nurses from a large Midwestern rural referral hospital that implemented electronic medical records and computerized provider order entry systems. Nurses from 3 other hospitals were used to cross-validate the factor structure of the scale. MEASURES: The scale assesses respondents' perceptions related to communication changes, changes in selected work behaviors, perceptions of the implementation strategy, and the impact on quality of patient care. The instrument can be used to assess perceptions before and after implementation. RESULTS: Confirmatory factor analysis generally supported the a priori factor structure for both expectations and experiences regarding the clinical information system. The consistency of the fit to the factor models was also high across the cross-validation samples. The scales demonstrated acceptable internal consistency in all the samples. CONCLUSIONS: Our findings suggest that the measure of clinical information systems expectations and experiences offers a valid and reliable tool for assessing the perceived impact of new clinical technology on work process and outcomes. This instrument can be useful before and after technology implementation by assisting in the identification of staff perceptions and concerns, thus allowing for targeted interventions to address these issues.

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