A paradigm in the field of Heath Informatics which has been taken for granted up until this point may be disappearing and a new paradigm may begin to take shape as paper-based medical record (PMR) systems are changing to the electronic health record (EHR) systems. Although the PMR has played a critical role in recording patient's clinical information, now many studies report that EHR systems improve quality of care beyond PMRs. For this reason, the governments across the world have initiated various approaches accelerating EHR adoption, use, and interoperability. However, there has been a paucity of studies explaining which factors affect EHR adoption, use, and interoperability in hospitals. The objective of this study is to predict and investigate those factors.
This study used a non-experimental, retrospective, cross-sectional study design to measure hospitals' internal features. Specifically, this study conducted a nationwide EHR survey with the IT departments in South Korean hospitals by using online surveys from April 10 to August 3, 2009. It used Generalized Estimating Equations, an extension of the Generalized Linear Model, to interpret EHR system adoption and interoperability, and General Linear Mixed Model for the use of EHR systems.
With respect to EHR system adoption, this study found that 1) the likelihood of EHR adoption increases as a hospital's task complexity - measured by the number of medical specialties - IT infrastructure, and organic structural characteristics, and environmental complexity - measured by the number of hospitals within the local area - increases and 2) there were significant interaction effects between task complexity and structural features. Assuming that a hospital adds additional medical specialties, the likelihood of adopting an EHR system of the hospital increases under the decentralized decision-making system, but decreases under the centralized decision-making system. The likelihood decreases under a high level of IT infrastructure, but increases under a lower level of IT infrastructure. For the hospitals' EHR use, there was not any relationship between EHR use and proposed hospital's internal features. Thus, alternative measures of EHR use and internal features were suggested. For EHR interoperability, this study found that 1) the likelihood of having EHR interoperability increases as task complexity and organic managerial features increases, and 2) two interaction effects were reported. Assuming that a hospital adds additional medical specialties, the likelihood of having EHR interoperability of the hospital increases at a high level of IT staff specialization, but decreases at a lower level of IT staff specialization. At a high level of environmental complexity with more than average number of hospitals within the local area, the likelihood of having EHR interoperability of the hospitals located in the area increases as IT staff specialization increases. However, the likelihood decreases as IT staff specialization increases at a lower level of environmental complexity with less than average number of hospitals within the local area.
In conclusion, this study verified that hospitals' task, structure, and environmental features were critical factors affecting the EHR system adoption and interoperability. However, these factors did not affect EHR use. Different approaches measuring EHR use and hospitals' various internal features were recommended. This study's results can provide health informaticians, hospital IT managers, and health politicians with new information about EHR system adoption, use, and interoperability for their innovative decision-making.
University of Minnesota Ph.D. dissertation. June 2010. Major: Health Informatics. Advisor: Stuart M. Speedie, PhD. 1 computer file (PDF); x, 148 pages, appendices 1-6. Ill. (some col.)
Park, Young-Taek, M.P.H..
Impact of task, structure, and environment on electronic health record adoption, use, and interoperability in hospitals..
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