Literature DB >> 16501392

Clinical information technology capabilities in four U.S. hospitals: testing a new structural performance measure.

Ruben Amarasingham1, Marie Diener-West, Michael Weiner, Harold Lehmann, Jerome E Herbers, Neil R Powe.   

Abstract

BACKGROUND: Few tools exist to quantify the performance of a hospital's information system from a user perspective.
OBJECTIVES: Our objective was to develop and evaluate a survey-based metric that assesses the automation and usability of a hospital's information system. RESEARCH DESIGN AND METHODS: This is a cross-sectional study of 117 physicians and 3 chief information officers (CIOs) working in 2 community hospitals with historically low investment in IT (Hospitals A and B), an academic hospital with an advanced IT system (Hospital C), or a major Veterans Affairs hospital (Hospital D). Respondents completed a survey assessing their institution's information system. The mean of 90 summed responses yields the clinical information technology (CIT) index, a global measure of a hospital's information system performance on a 100-point scale.
RESULTS: On the global CIT index, mean physician scores were significantly higher for hospitals with advanced IT (61.1 and 64.3 for C and D) compared with those with low investment in IT (32.6 and 29.4 for A and B, P < 0.001). These differences also were observed for each of 7 separate subdomains. The CIO scores, 74.7, 78.0 for Hospitals C and D, and 44.5 for Hospitals A and B, paralleled the mean physician scores for these hospitals. All measures exhibited low variance for each hospital (eg, standard deviations for the CIT index ranged from 5.9 to 8.1) and intraclass correlation was high (Chronbach's alpha >.70).
CONCLUSIONS: This assessment tool demonstrates initial evidence of validity and reliability.

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Year:  2006        PMID: 16501392     DOI: 10.1097/01.mlr.0000199648.06513.22

Source DB:  PubMed          Journal:  Med Care        ISSN: 0025-7079            Impact factor:   2.983


  5 in total

1.  Measuring clinical information technology in the ICU setting: application in a quality improvement collaborative.

Authors:  Ruben Amarasingham; Peter J Pronovost; Marie Diener-West; Christine Goeschel; Todd Dorman; David R Thiemann; Neil R Powe
Journal:  J Am Med Inform Assoc       Date:  2007-02-28       Impact factor: 4.497

2.  Using High-Fidelity Simulation and Eye Tracking to Characterize EHR Workflow Patterns among Hospital Physicians.

Authors:  Julie W Doberne; Ze He; Vishnu Mohan; Jeffrey A Gold; Jenna Marquard; Michael F Chiang
Journal:  AMIA Annu Symp Proc       Date:  2015-11-05

3.  How is the electronic health record being used? Use of EHR data to assess physician-level variability in technology use.

Authors:  Jessica S Ancker; Lisa M Kern; Alison Edwards; Sarah Nosal; Daniel M Stein; Diane Hauser; Rainu Kaushal
Journal:  J Am Med Inform Assoc       Date:  2014-06-09       Impact factor: 4.497

Review 4.  Care coordination gaps due to lack of interoperability in the United States: a qualitative study and literature review.

Authors:  Lipika Samal; Patricia C Dykes; Jeffrey O Greenberg; Omar Hasan; Arjun K Venkatesh; Lynn A Volk; David W Bates
Journal:  BMC Health Serv Res       Date:  2016-04-22       Impact factor: 2.655

5.  Hospital characteristics associated with highly automated and usable clinical information systems in Texas, United States.

Authors:  Ruben Amarasingham; Marie Diener-West; Laura Plantinga; Aaron C Cunningham; Darrell J Gaskin; Neil R Powe
Journal:  BMC Med Inform Decis Mak       Date:  2008-09-15       Impact factor: 2.796

  5 in total

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