Combining Ontologies and Open Standards to Derive a Middle Layer Information Model for Interoperability of Personal and Electronic Health Records.

The aim of our study was to enable better interoperability between Personal Health Record (PHR) and Electronic Health Record (EHR) systems and vice versa. A multi-layer architectural model that resides between a PHR and EHR system has been developed. The model consists of an ontology-driven information model and a set of transformation rules that work in conjunction to process data exported from a PHR or EHR system and prepare it accordingly for the receiving system. The model was evaluated by executing a set of case study scenarios containing data from both a PHR and an EHR system. This allowed various challenges to emerge and revealed gaps in current standards in use. The proposed information model offers a number of advantages. Altering only the information model can incorporate modifications to either a PHR or EHR system. The model uses classes and attributes to define how data is captured which allows greater flexibility in how data can be manipulated by receiving systems.

Assessing the motivation of MDs to use computer-based support at the point-of-care in the Emergency Department.

A significant body of research investigates the acceptance of computer-based support (including devices and applications ranging from e-mail to specialized clinical systems, like PACS) among clinicians. Much of this research has focused on measuring the usability of systems using characteristics related to the clarity of interactions and ease of use. We propose that an important attribute of any clinical computer-based support tool is the intrinsic motivation of the end-user (i.e. a clinician) to use the system in practice. In this paper we present the results of a study that investigated factors motivating medical doctors (MDs) to use computer-based support. Our results demonstrate that MDs value computer-based support, find it useful and easy to use, however, uptake is hindered by perceived incompetence, and pressure and tension associated with using technology.

Automatic indexing and retrieval of encounter-specific evidence for point-of-care support.

Evidence-based medicine relies on repositories of empirical research evidence that can be used to support clinical decision making for improved patient care. However, retrieving evidence from such repositories at local sites presents many challenges. This paper describes a methodological framework for automatically indexing and retrieving empirical research evidence in the form of the systematic reviews and associated studies from The Cochrane Library, where retrieved documents are specific to a patient-physician encounter and thus can be used to support evidence-based decision making at the point of care. Such an encounter is defined by three pertinent groups of concepts - diagnosis, treatment, and patient, and the framework relies on these three groups to steer indexing and retrieval of reviews and associated studies. An evaluation of the indexing and retrieval components of the proposed framework was performed using documents relevant for the pediatric asthma domain. Precision and recall values for automatic indexing of systematic reviews and associated studies were 0.93 and 0.87, and 0.81 and 0.56, respectively. Moreover, precision and recall for the retrieval of relevant systematic reviews and associated studies were 0.89 and 0.81, and 0.92 and 0.89, respectively. With minor modifications, the proposed methodological framework can be customized for other evidence repositories.