Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Introduction to Bayesian Networks
Introduction to Bayesian Networks
Organizational and Environmental Determinants of Hospital EMR Adoption: A National Study
Journal of Medical Systems
Methods to Evaluate Health information Systems in Healthcare Settings: A Literature Review
Journal of Medical Systems
Determining Patient Preferences for Remote Monitoring
Journal of Medical Systems
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Return on investment (ROI) concerns related to Electronic Health Records (EHRs) are a major barrier to the technology's adoption. Physicians generally rely upon early adopters to vet new technologies prior to putting them into widespread use. Therefore, early adopters' experiences with EHRs play a major role in determining future adoption patterns. The paper's purposes are: (1) to map the EHR value streams that define the ROI calculation; and (2) to compare Current Users' and Intended Adopters' perceived value streams to identify similarities, differences and governing constructs. Primary data was collected by the Texas Medical Association, which surveyed 1,772 physicians on their use and perceptions of practice gains from EHR adoption. Using Bayesian Belief Network Modeling, value streams are constructed for both current EHR users and Intended Adopters. Current Users and Intended Adopters differ significantly in their perceptions of the EHR value stream. Intended Adopters' value stream displays complex relationships among the potential gains compared to the simpler, linear relationship that Current Users identified. The Current Users identify "Reduced Medical Records Costs" as the gain that governs the value stream while Intended Adopters believe "Reduced Charge Capture Costs" define the value stream's starting point. Current Users' versus Intended Adopters' assessments of EHR benefits differ significantly and qualitatively from one another.