Abstract
Background
Clinicians in ambulatory care settings are increasingly called upon to use health information technology (health IT) to improve practice efficiency and performance. Successful adoption of health IT requires an understanding of how clinical tasks and workflows will be affected; yet this has not been well described.
Objective
To describe how health IT functions within a clinical context.
Design
Qualitative study, using in-depth, semi-structured interviews.
Participants
Executives and staff at 4 community health centers, 3 health center networks, and 1 large primary care organization.
Approach
Transcribed audio-recorded interviews, analyzed using the constant comparative method.
Results
Systematic characterization of clinical context identified 6 primary clinical domains. These included results management, intra-clinic communication, patient education and outreach, inter-clinic coordination, medication management, and provider education and feedback. We generated clinical process diagrams to characterize these domains. Participants suggested that underlying workflows for these domains must be fully operational to ensure successful deployment of health IT.
Conclusions
Understanding the clinical context is a necessary precursor to successful deployment of health IT. Process diagrams can serve as the basis for EHR certification, to identify challenges, to measure health IT adoption, or to develop curricular content regarding the role of health IT in clinical practice.
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References
Institute of Medicine. Crossing the Quality Chasm: A New Health System for the 21st Century. Washington, DC: The National Academies Press; 2001.
Simon S, Kaushal R, Cleary PD, et al. Correlates of electronic health record adoption in office practices: a statewide survey. J Am Med Inform Assoc. 2007;14:110–17.
Shields A, Shin P, Leu M, et al. Adoption of health information technology in community health centers: results of a national survey. Health Aff. 2007;26:1373–83.
Bates DW. Physicians and ambulatory electronic health records. Health Aff. 2005;24:1180–9.
Jha AK, Ferris TG, Donelan K, et al. How common are electronic health records in the United States? A summary of the evidence. Health Aff. 2006;25:w496–507.
Institute of Medicine. Key Capabilities of an Electronic Health Record System. Washington, DC: The National Academies Press; 2003.
HL7 2007 EHR-S Functional Model. Ann Arbor, MI: Health Level Seven, Inc. Available at: http://www.hl7.org/documentcenter/public/standards/EHR_Functional_Model/R1/EHR_Functional_Model_R1_Final.zip. Accessed April 3, 2007.
Ambulatory EHR Functionality 2007 Final Criteria. Chicago, IL: Certification Commission for Healthcare Information Technology. Available at: http://www.cchit.org/work/criteria.htm. Accessed April 3, 2007.
Osheroff JA, Teich JM, Middleton BF, Steen EB, Wright A, Detmer DE. A Roadmap for National Action on Clinical Decision Support. Bethesda, MD: American Medical Informatics Association, 2006. Available at: http://www.amia.org/inside/initiatives/cds/cdsroadmap.pdf. Accessed April 28, 2007.
Bell DS, Cretin S, Marken RS, Landman AB. A conceptual framework for evaluating outpatient electronic prescribing systems based on their functional capabilities. J Am Med Inform Assoc. 2004;11:60–70.
Institute of Medicine. Preventing Medication Errors: Quality Chasm Series. Washington, DC: The National Academies Press; 2006.
Findings from the Evaluation of E-Prescribing Pilot Sites. Rockville, MD: AHRQ Publication No. 07-0047-EF, 2007.
Rogers EM. Diffusion of Innovations, 5th ed. New York, NY: Free Press (Simon & Schuster, Inc.); 2003.
Sofaer S. Qualitative methods: what are they and why use them. Health Serv Res. 1999;34:1101–18.
Patton M. Qualitative Evaluation and Research Methods, 3rd ed. Thousand Oaks, CA: Sage; 2002.
Morse JM. The significance of saturation. Qual Health Res. 1995;5:147–9.
Landon BE, Hicks LS, O’Malley AJ, Lieu TA, Keegan T, BcNeil BJ, Guadagnoli E. Improving the management of chronic disease at community health centers. N Engl J Med. 2007;356:921–34.
Health Disparities Collaboratives. Rockville, MD: HRSA. Available at: http://www.healthdisparities.net/hdc/html/home.aspx. Accessed April 20, 2007.
Pope C, Mays N. Reaching the parts other methods cannot reach: an introduction to qualitative methods in health and health services research. BMJ. 1995;311:42–45.
Giacomini M, Cook D. Users’ guides to the medical literature: XXIII. Qualitative research in health care A. Are the results of the study valid. JAMA. 2000;284:357–62.
Bradley E, Curry L, Devers K. Qualitative Data Analysis for Health Services Research: Developing Taxonomy, Themes, and Theory. Health Serv Res. 2007; 42(4):1758–72. doi 10.1111/j.1475-6773.2006.00684.x
Glaser BG, Strauss AL. The Discovery of Grounded Theory: Strategies for Qualitative Research. Chicago, IL: Aldine; 1967.
Lincoln YS, Guba EG. Naturalistic Inquiry. Beverly Hills, CA: Sage Publications; 1985.
Armstrong D, Gosling A, Weinman J, Marteau T. The place of inter-rater reliability in qualitative research: an empirical study. Sociology. 1997;31:597–606.
Morse JM. Designing funded qualitative research. In: Denzin NK, Lincoln YS, eds. Handbook of Qualitative Research. London, UK: Sage Publications; 1994:220–35.
Miles MB, Huberman AM. Qualitative Data Analysis: An Expanded Sourcebook, 2nd ed. Thousand Oaks, CA: Sage Publications; 1994.
U.S. Preventive Services Task Force Screening for Cervical Cancer. Rockville, MD: AHRQ. Available at: http://www.ahrq.gov/clinic/uspstf/uspscerv.htm. Accessed April 20, 2007.
AHRQ Conference on Health Care Data Collection and Reporting. Rockville, MD: AHRQ Publication No. 07-0033-EF, 2007.
Acknowledgments
We would like to thank the Ethel Donaghue Center for Translating Research Into Practice and Policy for research support, and the Robert Wood Johnson Foundation for funding Dr. Leu and Ms. Webster’s time through the Clinical Scholars Program at Yale University. Dr. Bradley is supported by a Patrick and Catherine Weldon Donaghue Medical Research Foundation Investigator Award. We would also like to thank Community Health Center, Inc. for Mr. Cheung’s time.
The funding organizations, except authors, had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; or preparation, review, or approval of the manuscript. Dr. Leu, Dr. Curry, and Dr. Burstin have had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
We would like to acknowledge Dr. Harlan Krumholz for providing administrative oversight and for supporting this project, and would like to thank Saurish Bhattacharjee and the Human Investigative Committee for their support. We would like to thank our collaborators that helped us with selecting sites to visit, our interviewees at participating organizations, our reviewers, and our families for their ongoing support.
This research has been presented as a poster at the National Association of Community Health Center’s Community Health Institute and Expo, in Dallas, Texas, on August 28, 2007.
Conflict of Interest
None disclosed.
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Leu, M.G., Cheung, M., Webster, T.R. et al. Centers Speak Up: The Clinical Context for Health Information Technology in the Ambulatory Care Setting. J GEN INTERN MED 23, 372–378 (2008). https://doi.org/10.1007/s11606-007-0488-6
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DOI: https://doi.org/10.1007/s11606-007-0488-6