Organizational and environmental correlates of electronic health records implementation and performance in acute care hospitals in the United States

Electronic health record (EHR) systems have the potential to transform the health care system from a mostly paper-based industry to one that utilizes clinical and other electronic information to assist providers in delivering higher quality of care to their patients. However the complexity of the healthcare delivery setting, characterized by both the need for standardization and the necessity for sensitivity to variation in local conditions, only magnifies both the intricacy and importance of effective EHR implementation. Studies of implementation of EMRs are relatively few, mostly case studies, without controls, with most data from informants' self-reports and often lack generalizability. The purpose of this study is to examine the organizational and environmental factors associated with the level of implementation of electronic health records in U.S. acute care hospitals. Additionally the study also examines the impact of EHR implementation on acute care hospitals' performance, more specifically the operating efficiency of these hospitals. The study employed an observational, non-experimental, retrospective nonequivalent control group design with lagged independent variables. Data form the 2007-2009 American Hospital Association (AHA) and 2007-2008 Area Resource Files were used. Multinomial logistic regression was used to model the relationship between the organizational and environmental con-elates and the levels of EHR implementation. Generalized Estimating Equation model was used to examine the relationship between EHR implementation and operating expense. The findings from the multivariate analyses suggested that FP ownership status, degree of competition and size of the hospitals were significantly associated with higher levels of EHR implementation. System affiliation, size, per capita income, diffusion of EHR and the geographic location of the hospital were significantly associated with higher levels of the patient information and data functionality implementation. Similarly size, per capita income, diffusion of EHR and location were also significantly associated with higher levels of results management, order entry management and decision support implementation. The findings of the multivariate analysis assessing the relationship between higher levels of EHR implementation and efficiency showed that size, per capita income, Medicare payer mix, teaching status of the hospitals were all significantly associated with efficiency. Two interaction terms were also observed between EHLTH and ownership status and size, which were both, significantly associated with lower costs and hence increased efficiency. The findings of this study offer practical implications for hospital decision makers and raise an important issue regarding national efforts imbedded in the HITECH Act. This study is likely to be of interest to not only the policy makers but also health services organizations that are looking to understand the determinants of higher levels of EHR implementation.