Medical Records System Adoption in European Hospitals

Abstract

Health Care system has had an ongoing focus on improving access to and quality of care, and more recently on cost reduction. The primary mean to achieve these goals has been to change health care policy, as exemplified by the adoption of health information technology in particular the adoption of patient centred information, characterized by the ability to manage comprehensive patience information such as: medical records; appointments scheduling; theatre management and ward reporting. Different terms are used to refer to these systems including the most common: electronic patient record; electronic medical record; computer based patient record and medical records system (MRS). Despite the importance of these systems in health care, little is known about the adoption. This study addresses the existent research gap by analyzing the adoption of MRS in European hospitals. Study data source is the e‑Business W@tch 2006 decision maker survey, covering 448 hospitals in the European Union. Additional information related to country wealth indicators, was extracted from the EU official statistics and opinion polls website. Variable choice is based on a derivation from the recently introduced framework know as Human, Organization and Technology fit (HOT‑fit) and Technology, Organization and Environment (TOE) framework. Adding the environmental context into the HOT‑fit framework, the Human, Organization, Technology and Environment (HOTE) framework is derivate. HOTE framework identifies four contexts that influence information and communication technologies (ICT) adoption: Technology characteristics including equipment but also processes; Organizational context as size, localization and even managerial structure; Human context relating to ‘User Involvement’; and Environmental context that incorporate the cultural environment of the country and regulatory influence. In order to reduce the number of variables available, a factor analysis (FA) is performed, using the principal component technique with varimax rotation. Three eigen‑value, greater than one are extracted, explaining 69.68% of the variance contained in the data. The three contexts found are: country wealth, competition and technology readiness. To determine the correlation between HOTE framework characteristics and MRS adoption a Logit model is used. For that were used variables obtained from the FA and other variables such as hospital size, education level and research level, gathered directly from the e‑business watch survey. MRS adoption is significantly associated with Education Level, Technology Readiness and Country Wealth. Since MRS adoption may be an organization survival strategy for hospitals to improve quality and efficiency while reducing costs, hospitals that are at risk of missing the wave of implementation should be offered incentives that enable them to implement and maintain patient centred information systems.