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Medication reconciliation is an essential, but resource-intensive process without a "gold standard" to measure medication adherence. Medication reconciliation applications that focus on facilitating clinicians' decision-making are needed. Since no single available source of medication information is adequate, combining data sources may improve usefulness and outcomes.

Health Risk Appraisals (HRAs) have been implemented in a variety of settings, however few studies have examined the impact of computerized HRAs systematically in primary care. The study aimed at the development and pilot testing of a novel, comprehensive HRA tool in primary care practices.

There are problems of quality in maternity services at primary health care level in South Africa. Many of these problems can be traced to non-adherence to the maternity care guidelines and lack of tools to support clinic staff and managers in their roles.

In a previous study, we reported on a successful clinical decision support (CDS) intervention designed to improve electronic problem list accuracy, but did not study variability of provider response to the intervention or provider attitudes towards it. The alert system accurately predicted missing problem list items based on health data captured in a patient's electronic medical record.

In a prior study, we developed methods for automatically identifying associations between medications and problems using association rule mining on a large clinical data warehouse and validated these methods at a single site which used a self-developed electronic health record.

The objective of this study was to investigate and improve the use of automated data collection procedures for nursing research and quality assurance.

The federal government is promoting adoption of electronic health records (EHRs) through financial incentives for EHR use and implementation support provided by regional extension centers. Small practices have been slow to adopt EHRs.

Clinical pathways are evidence-based recommendations for treating a diagnosis. Although implementations of clinical pathways have reduced medical errors, lowered costs, and improved patient outcomes, monitoring whether a patient is following the intended pathway is problematic. Implementing a variance reporting program is impeded by the lack of a reliable source of electronic data and automatic retrieval methods.

We previously demonstrated that a general purpose text mining system, the Vaccine adverse event Text Mining (VaeTM) system, could be used to automatically classify reports of an-aphylaxis for post-marketing safety surveillance of vaccines.

The rapidly growing industry for mobile medical applications provides numerous smartphone resources designed for healthcare professionals. However, not all applications are equally useful in addressing the questions of early medical trainees.