Appl Clin Inform 2013; 04(01): 12-24
DOI: 10.4338/ACI-2012-09-RA-0033
Research Article
Schattauer GmbH

Predictors of success for electronic health record implementation in small physician practices

J.S. Ancker
1   Weill Cornell Medical College, Center for Healthcare Informatics and Policy, Departments of Pediatrics and of Public Health, New York, NY 10034
2   Health Information Technology Evaluation Collaborative (HITEC)
,
M.P. Singh
3   New York City Department of Health and Mental Hygiene, New York, NY
,
R. Thomas
1   Weill Cornell Medical College, Center for Healthcare Informatics and Policy, Departments of Pediatrics and of Public Health, New York, NY 10034
2   Health Information Technology Evaluation Collaborative (HITEC)
,
A. Edwards
1   Weill Cornell Medical College, Center for Healthcare Informatics and Policy, Departments of Pediatrics and of Public Health, New York, NY 10034
2   Health Information Technology Evaluation Collaborative (HITEC)
,
A. Snyder
3   New York City Department of Health and Mental Hygiene, New York, NY
,
A. Kashyap
4   eClinicalWorks, New York, NY
,
R. Kaushal
1   Weill Cornell Medical College, Center for Healthcare Informatics and Policy, Departments of Pediatrics and of Public Health, New York, NY 10034
2   Health Information Technology Evaluation Collaborative (HITEC)
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Publikationsverlauf

received: 17. September 2012

accepted: 19. Januar 2012

Publikationsdatum:
19. Dezember 2017 (online)

Summary

Background: The federal government is promoting adoption of electronic health records (EHRs) through financial incentives for EHR use and implementation support provided by regional extension centers. Small practices have been slow to adopt EHRs.

Objectives: Our objective was to measure time to EHR implementation and identify factors associated with successful implementation in small practices receiving financial incentives and implementation support. This study is unique in exploiting quantitative implementation time data collected prospectively as part of routine project management.

Methods: This mixed-methods study includes interviews of key informants and a cohort study of 544 practices that had worked with the Primary Care Information Project (PCIP), a publicly funded organization that since 2007 has subsidized EHRs and provided implementation support similar to that supplied by the new regional extension centers. Data from a project management database were used for a cohort study to assess time to implementation and predictors of implementation success.

Results: Four hundred and thirty practices (79%) implemented EHRs within the analysis period, with a median project time of 24.7 weeks (95% CI: 23.3 – 26.4). Factors associated with implementation success were: fewer providers, practice sites, and patients; fewer Medicaid and uninsured patients; having previous experience with scheduling software; enrolling in 2010 rather than earlier; and selecting an integrated EHR plus practice management product rather than two products. Interviews identified positive attitude toward EHRs, resources, and centralized leadership as additional practice-level predictors of success.

Conclusions: A local initiative similar to current federal programs successfully implemented EHRs in primary care practices by offsetting software costs and providing implementation assistance. Nevertheless, implementation success was affected by practice size and other characteristics, suggesting that the federal programs can reduce barriers to EHR implementation but may not eliminate them.

Citation: Ancker JS, Singh MP, Thomas R, Edwards A, Snyder A, Kashyap A, Kaushal R. Predictors of success for electronic health record implementation in small physician practices. Appl Clin Inf 2013; 4: 12–24

http://dx.doi.org/10.4338/ACI-2012-09-RA-0033

 
  • References

  • 1 DesRoches CM, Campbell EG, Rao SR, Donelan K, Ferris TG, Jha A. et al. Electronic health records in ambulatory care: A national survey of physicians. New England Journal of Medicine 2008; 359 (01) 50-60.
  • 2 Bramble JD, Galt KA, Siracuse MV, Abbott AA, Drincic A, Paschal KA. et al. The relationship between physician practice characteristics and physician adoption of electronic health records. Health Care Management Review 2010; 35 (01) 55-64.
  • 3 Rao SR, DesRoches C, Donelan K, Campbell E, Miralles P, Jha A. Electronic health records in small physician practices: Availability, use, and perceived benefits. JAMIA 2011; 18: 271-275.
  • 4 Jha AK, DesRoches CM, Campbell EG, Donelan K, Rao SR, Ferris TG. et al. Use of electronic health records in U. S. hospitals. The New England journal of medicine 2009 Apr 16 360 (16) 1628-38. PubMed PMID: 19321858. Epub 2009/03/27.
  • 5 Gans D, Kralewski J, Hammons T, Dowd B. Medical groups’ adoption of electronic health records and information systems. Health Affairs (Millwood) 2005; 24 (05) 1323-1333.
  • 6 Simon SR, Kaushal R, Cleary PD, Jenter CA, Volk LA, Poon EG. et al. Correlates of electronic health record adoption in office practices: a statewide survey. J Am Med Inform Assoc 2007; 14 (01) 110-117. PubMed PMID: 17068351.
  • 7 Simon SR, Kaushal R, Cleary PD, Jenter CA, Volk LA, Orav EJ. et al. Physicians and electronic health records: a statewide survey. Arch Intern Med 2007; 167 (05) 507-512. PubMed PMID: 17353500.
  • 8 Maxson E, Jane S, Kendall M, Mostashari F, Blumenthal D. The regional extension center program: helping physicians meaningfully use health information technology. Annals of Internal Medicine 2010; 153: 666-670.
  • 9 Blumenthal D, Tavenner M. The "meaningful use" regulation for electronic health records. New England Journal of Medicine 2010; 363: 501-504.
  • 10 Medicare and Medicaid Programs.. Electronic Health Record Incentive Program, Final Rule. 75 Federal Register 144 (28 July 2010) 2010
  • 11 Scott J, Rundall T, Vogt T, Hsu J. Kaiser Permanente’s experience of implementing an electronic medical record: A qualitative study. British Medical Journal 2005; 331: 1313-1316.
  • 12 McAlaerney A, Song P, Robbins J. Moving from good to great in ambulatory electronic health record implementation. Journal of Healthcare Quality 2010; 32 (05) 41-50.
  • 13 Yoon-Flannery K, Zandieh S, Kuperman GJ, Langsam D, Hyman D, Kaushal R. A qualitative analysis of an electronic health record (EHR) implementation in an academic ambulatory setting. Informatics in Primary Care 2008; 16: 277-284.
  • 14 Fullerton C, Aponte P, Hopkins R, Bragg D, Ballard DJ. Lessons learned from pilot site implementation of an ambulatory electronic health record. Proceedings of the Baylor University Medical Center 2006; 19: 303-310.
  • 15 Baron RJ, Fabens EL, Schiffman M, Wolf E. Electronic health records: Just around the corner?. Or over the Cliff? Annals of Internal Medicine 2005; 143 (03) 222-226.
  • 16 Miller RH, Sim I, Newman J. Electronic medical records: Lessons from small physician practices. Oakland, CA: California HealthCare Foundation,; 2003
  • 17 Ludwick D, Manca D, Doucette J. Primary care physicians’ experiences with electronic medical records: Implementation experience in community, urban, hospital, and academic family medicine. Canadian Family Physician 2010; 56: 40-47.
  • 18 Lorenzi NM, Kouroubali A, Detmer DE, Bloomrosen M. How to successfully select and implement electronic health records (EHR) in small ambulatory practice settings. BMC Medical Informatics and Decision Making. 2010 9:(15)
  • 19 Torda P, Han ES, Scholle SH. Easing the adoption and use of electronic health records in small practices. Health Affairs (Millwood) 2010; 29 (04) 668-675.
  • 20 Fleurant M, Kell R, Jenter C, Volk LA, Zhang F, Bates DW. et al. Factors associated with difficult electronic health record implementation in office practice. Journal of the American Medical Informatics Association. 2012
  • 21 Mostashari F, Tripathi M, Kendall M. A tale of two large community electronic health record extension projects. Health Aff (Millwood) 2009; 28 (02) 345-356. PubMed PMID: 19275989.
  • 22 Safran C, Bloomrosen M, Hammond WE, Labkoff S, Markel-Fox S, Tang PC. et al. Toward a national framework for the secondary use of health data: An American Medical Informatics Association white paper. JAMIA 2007; 14 (01) 1-9.
  • 23 Strauss A, Corbin J. Basics of Qualitative Research: Techniques and Procedures for Developing Grounded Theory. 2nd ed. Thousand Oaks, CA: Sage; 1998
  • 24 Lincoln YS, Guba EG. Naturalistic Inquiry. Newbury Park, CA: Sage Publications, Inc.; 1985
  • 25 Crabtree BF, Miller WL. Doing Qualitative Research. 2nd ed. Thousand Oaks, CA: Sage Publications; 1999
  • 26 Ancker JS, Shih S, Singh MP, Snyder A, Edwards A, Kaushal R. et al. Root causes underlying challenges to secondary use of data. Proceedings / AMIA Annual Fall Symposium 2011; 2011: 57-62.
  • 27 Akaike H. A new look at the statistical model identification. IEEE Transactions on Automatic Control 1974; 19 (06) 716-723.
  • 28 Dennehy P, White MP, Hamilton A, Pohl JM, Tanner C, Onifade TJ. et al. A partnership model for implementing electronic health records in resource-limited primary care settings: experiences from two nurse-managed health centers. Journal of the American Medical Informatics Association 2011; 18 (06) 820-826.
  • 29 Goldberg DG, Kuzel AJ, Feng LB, DeShazo JP, Love LE. EHRs in primary care practices: benefits, challenges, and successful strategies. American Journal of Managed Care 2012; 18 (02) e48-e54.
  • 30 Rogers EM. Diffusion of innovations. New York Free Press; 1962/2003.
  • 31 Lorenzi NM, Riley RT. Managing change: an overview. Journal of the American Medical Informatics Association 2000; 7: 116-124.
  • 32 Prokosch H-U, Ganslandt T. Reusing the electronic medical record for clinical research. Methods of Information in Medicine 2009; 48: 38-44.