Predicting the Adoption of Electronic Health Records by Physicians: When Will Health Care be Paperless?
- Affiliations of the authors: Center for Healthcare Leadership and Strategy, Texas Tech University, Lubbock, TX (EWF); Center on Patient Safety, Florida State University, Tallahassee, FL (NM); Department of Clinical Information Systems, University of South Alabama Hospitals, Mobile, AL (MTP)
- Correspondence and reprints: Eric W. Ford, PhD, Area of Management, MS 2101, Texas Tech University, Lubbock, TX 79409; e-mail: <eford{at}ttu.edu>.
- Received 18 July 2005
- Accepted 13 September 2005
Abstract
Objectives The purpose of this study was threefold. First, we gathered and synthesized the historic literature regarding electronic health record (EHR) adoption rates among physicians in small practices (ten or fewer members). Next, we constructed models to project estimated future EHR adoption trends and timelines. We then determined the likelihood of achieving universal EHR adoption in the near future and articulate how barriers can be overcome in the small and solo practice medical environment.
Design This study used EHR adoption data from six previous surveys of small practices to estimate historic market penetration rates. Applying technology diffusion theory, three future adoption scenarios, optimistic, best estimate, and conservative, are empirically derived.
Measurement EHR adoption parameters, external and internal coefficients of influence, are estimated using Bass diffusion models.
Results All three EHR scenarios display the characteristic diffusion S curve that is indicative that the technology is likely to achieve significant market penetration, given enough time. Under current conditions, EHR adoption will reach its maximum market share in 2024 in the small practice setting.
Conclusion The promise of improved care quality and cost control has prompted a call for universal EHR adoption by 2014. The EHR products now available are unlikely to achieve full diffusion in a critical market segment within the time frame being targeted by policy makers.
