Quantifying the Impact of Health IT Implementations on Clinical Workflow: a New Methodological Perspective

Overview

Journal J Am Med Inform Assoc

Publisher Oxford University Press

Specialty Medical Informatics

Date 2010 Jul 3

PMID 20595314

Citations 60

Authors

Kai Zheng

Hilary M Haftel

Ronald B Hirschl

Michael OReilly

David A Hanauer

Affiliations

Soon will be listed here.

Abstract

Health IT implementations often introduce radical changes to clinical work processes and workflow. Prior research investigating this effect has shown conflicting results. Recent time and motion studies have consistently found that this impact is negligible; whereas qualitative studies have repeatedly revealed negative end-user perceptions suggesting decreased efficiency and disrupted workflow. We speculate that this discrepancy may be due in part to the design of the time and motion studies, which is focused on measuring clinicians' 'time expenditures' among different clinical activities rather than inspecting clinical 'workflow' from the true 'flow of the work' perspective. In this paper, we present a set of new analytical methods consisting of workflow fragmentation assessments, pattern recognition, and data visualization, which are accordingly designed to uncover hidden regularities embedded in the flow of the work. Through an empirical study, we demonstrate the potential value of these new methods in enriching workflow analysis in clinical settings.

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References

Tierney W, Miller M, Overhage J, McDonald C . Physician inpatient order writing on microcomputer workstations. Effects on resource utilization. JAMA. 1993; 269(3):379-83. View

Guss D, Chan T, Killeen J . The impact of a pneumatic tube and computerized physician order management on laboratory turnaround time. Ann Emerg Med. 2007; 51(2):181-5. DOI: 10.1016/j.annemergmed.2007.03.010. View

Wong D, Gallegos Y, Weinger M, Clack S, Slagle J, Anderson C . Changes in intensive care unit nurse task activity after installation of a third-generation intensive care unit information system. Crit Care Med. 2003; 31(10):2488-94. DOI: 10.1097/01.CCM.0000089637.53301.EF. View

Chaudhry B, Wang J, Wu S, Maglione M, Mojica W, Roth E . Systematic review: impact of health information technology on quality, efficiency, and costs of medical care. Ann Intern Med. 2006; 144(10):742-52. DOI: 10.7326/0003-4819-144-10-200605160-00125. View

Pratt W, Reddy M, McDonald D, Tarczy-Hornoch P, Gennari J . Incorporating ideas from computer-supported cooperative work. J Biomed Inform. 2004; 37(2):128-37. DOI: 10.1016/j.jbi.2004.04.001. View

Kushniruk A, Patel V . Cognitive and usability engineering methods for the evaluation of clinical information systems. J Biomed Inform. 2004; 37(1):56-76. DOI: 10.1016/j.jbi.2004.01.003. View

Ammenwerth E, Schnell-Inderst P, Machan C, Siebert U . The effect of electronic prescribing on medication errors and adverse drug events: a systematic review. J Am Med Inform Assoc. 2008; 15(5):585-600. PMC: 2528040. DOI: 10.1197/jamia.M2667. View

Ash J, Sittig D, Poon E, Guappone K, Campbell E, Dykstra R . The extent and importance of unintended consequences related to computerized provider order entry. J Am Med Inform Assoc. 2007; 14(4):415-23. PMC: 2244906. DOI: 10.1197/jamia.M2373. View

Bates D, Boyle D, Teich J . Impact of computerized physician order entry on physician time. Proc Annu Symp Comput Appl Med Care. 1994; :996. PMC: 2247898. View

10.

Kirmeyer S . Coping with competing demands: interruption and the type A pattern. J Appl Psychol. 1988; 73(4):621-9. DOI: 10.1037/0021-9010.73.4.621. View

11.

Weingart S . House officer education and organizational obstacles to quality improvement. Jt Comm J Qual Improv. 1996; 22(9):640-6. DOI: 10.1016/s1070-3241(16)30271-1. View

12.

Taylor J, Loan L, Kamara J, Blackburn S, Whitney D . Medication administration variances before and after implementation of computerized physician order entry in a neonatal intensive care unit. Pediatrics. 2008; 121(1):123-8. DOI: 10.1542/peds.2007-0919. View

13.

Shu K, Boyle D, SPURR C, Horsky J, HEIMAN H, OConnor P . Comparison of time spent writing orders on paper with computerized physician order entry. Stud Health Technol Inform. 2001; 84(Pt 2):1207-11. View

14.

Campbell E, Sittig D, Ash J, Guappone K, Dykstra R . Types of unintended consequences related to computerized provider order entry. J Am Med Inform Assoc. 2006; 13(5):547-56. PMC: 1561794. DOI: 10.1197/jamia.M2042. View

15.

Campbell E, Guappone K, Sittig D, Dykstra R, Ash J . Computerized provider order entry adoption: implications for clinical workflow. J Gen Intern Med. 2008; 24(1):21-6. PMC: 2607519. DOI: 10.1007/s11606-008-0857-9. View

16.

Zheng K, Padman R, Johnson M, Diamond H . An interface-driven analysis of user interactions with an electronic health records system. J Am Med Inform Assoc. 2008; 16(2):228-37. PMC: 2649313. DOI: 10.1197/jamia.M2852. View

17.

Mudunuri U, Stephens R, Bruining D, Liu D, Lebeda F . botXminer: mining biomedical literature with a new web-based application. Nucleic Acids Res. 2006; 34(Web Server issue):W748-52. PMC: 1538892. DOI: 10.1093/nar/gkl194. View

18.

Koppel R, Metlay J, Cohen A, Abaluck B, Russell Localio A, Kimmel S . Role of computerized physician order entry systems in facilitating medication errors. JAMA. 2005; 293(10):1197-203. DOI: 10.1001/jama.293.10.1197. View

19.

Mekhjian H, Kumar R, Kuehn L, Bentley T, Teater P, Thomas A . Immediate benefits realized following implementation of physician order entry at an academic medical center. J Am Med Inform Assoc. 2002; 9(5):529-39. PMC: 346640. DOI: 10.1197/jamia.m1038. View

20.

Bonnabry P, Despont-Gros C, Grauser D, Casez P, Despond M, Pugin D . A risk analysis method to evaluate the impact of a computerized provider order entry system on patient safety. J Am Med Inform Assoc. 2008; 15(4):453-60. PMC: 2442261. DOI: 10.1197/jamia.M2677. View