Background Wide adoption of electronic medical records (EMR) systems in the United States can lead to better-quality medical care at lower cost. Despite the laws and financial subsidies by the United States government for service providers and suppliers, interoperability still lags. An understanding of the drivers of EMR adoption for physicians and the role of policy-making can translate into increased adoption and enhanced information sharing between medical care providers. Methods Physicians across the United States were surveyed to gather primary data on their psychological, social and technical perceptions towards EMR systems. This quantitative study builds on the theory of planned behaviour, the technology acceptance model and the diffusion of innovation theory to propose, test and validate an innovation adoption model for the healthcare industry. A total of 382 responses were collected, and data were analysed via linear regression to uncover the effects of 12 variables on the intention to adopt EMR systems. Results Regression model testing uncovered that government policy-making or mandates and other social factors have little or negligible effect on physicians’ intention to adopt an innovation. Rather, physicians are directly driven by their attitudes and ability to control, and indirectly motivated by their knowledge of the innovation, the financial ability to acquire the system, the holistic benefits to their industry and the relative advancement of the system compared to others. Conclusions Identifying physicians’ needs regarding EMR systems and providing programmes that meet them can increase the potential for reaching the goal of nationwide interoperable medical records. Government, healthcare associations and EMR system vendors can benefit from our findings by working towards increasing physicians’ knowledge of the proposed innovation, socializing how medical care providers and the overall industry can benefit from EMR system adoption, and solving for the financial burden of system implementation and sustainment.

the aim of this research is to explore the motives behind the adoption or rejection of Electronic Health Records (EHR) systems in the USA by medical offices. The current health care system in the United States suffers from high expenditures and poor quality. The Patient Protection and Affordable Care Act, passed in 2010, attempts to save costs and improve quality of care by offering incentives to use Electronic Health Records systems. Part of the reform by this law is dependent on the use of technology in managing patient medical and health records. The objective is to reduce redundancy and increase quality by sharing medical information amongst different health organizations like hospitals, physician offices, laboratories and clinical institutions. The success of such reform requires the participation and collaboration of all these entities and their patients. Prior research shows that adoption of Electronic Medical Records systems by hospitals and physician offices has been evident but at a rate that is slower than in other countries. Aside from financial barriers, technical, psychological, social/legal and organizational barriers exist. In order to understand the impact of those barriers on the adoption of Electronic Health Records management by small physician offices better, a five-level adoption model is presented to define the stages of diffusion of EHR systems. Fifteen consolidated barriers are mapped to each adoption level. This research concentrates on smaller physician offices because hospitals and larger institutions are more ready and capable of adoption, according to previous research. The Diffusion of Technology Model by Rogers, the Theory of Planned Behavior by Ajzen and Fishbein, and Davis' Technology Acceptance Model are combined and extended. This model will be used to empirically measure physicians' attitudes, knowledge, social and legal influences, subjective norm and systems' ease of use and usefulness amongst other variables. These variables are applied as mediators or moderators of the intention and decision to adopt or move into subsequent levels of adoption with the goal of seeing what drives those decisions.

Abstract Background: Wide adoption of electronic medical records (EMR) systems in the United States can lead to better quality medical care at a lower cost. Despite the laws and financial subsidies by the U.S. government for service providers and suppliers, the adoption has been slow. Understanding the EMR adoption drivers for physicians and the role of policymaking can translate into increased adoption rate and enhanced information sharing between medical care providers. Methods: Physicians across the United States were surveyed to gather primary data on their psychological, social, and technical perceptions toward EMR systems. This quantitative study builds on the Theory of Planned Behavior, the Technology Acceptance Model, and the Diffusion of Innovation theory to propose, test, and validate an innovation adoption model for the health care industry. 382 responses were collected and data were analyzed via linear regression to uncover the effects of 12 variables on the intention to adopt EMR systems.Results: Regression model testing uncovers that government policymaking or mandates and other social factors have little or negligible effect on physicians’ intention to adopt an innovation. Rather, physicians are directly driven by their attitudes and ability to control, and indirectly motivated by their knowledge of the innovation, the financial ability to acquire the system, the holistic benefits to their industry, and the relative advancement of the system compared to others.Conclusions: A unidirectional mandate from the government is not sufficient for physicians to adopt an innovation. Government, health care associations, and EMR system vendors can benefit from our findings by working toward increasing the physicians’ knowledge of the proposed innovation, socializing how medical care providers and the overall industry can benefit from EMR system adoption, and solving for the financial burden of system implementation and sustainment.

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