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While the secondary use of medical data has gained attention, its adoption has been constrained due to protection of patient privacy. Making medical data secure by de-identification can be problematic, especially when the data concerns rare diseases. We require rigorous security management measures.

The Secretary of Health and Human Services (HHS) acting through the Food and Drug Administration (FDA), and in collaboration with the Federal Communications Commission (FCC) and Office of the National Coordinator for Health IT (ONC) was tasked with delivering a report on an appropriate, risk-based regulatory framework for health information technology (IT). An expert stakeholder group was established under the auspices of the Health IT Policy Committee to help provide [...]

This paper describes Health Level 7 (HL7) V.3 Care Transfer, Care Record Query, and Care Record messages. This is the core of the Care Provision Domain in the HL7 standard which became normative at the end of 2012 and is an American National Standards Institute (ANSI)-approved HL7 standard.

The objective of this investigation is to evaluate binary prediction methods for predicting disease status using high-dimensional genomic data. The central hypothesis is that the Bayesian network (BN)-based method called efficient Bayesian multivariate classifier (EBMC) will do well at this task because EBMC builds on BN-based methods that have performed well at learning epistatic interactions.

To evaluate attitudes regarding privacy of genomic data in a sample of patients with breast cancer.

Evidence indicates that users incur significant physical and cognitive costs in the use of order sets, a core feature of computerized provider order entry systems. This paper develops data-driven approaches for automating the construction of order sets that match closely with user preferences and workflow while minimizing physical and cognitive workload.

Clinical decision support has the potential to improve prevention of venous thromboembolism (VTE). The purpose of this prospective study was to analyze the effect of electronic reminders on thromboprophylaxis rates in wards to which patients were admitted and transferred. The latter was of particular interest since patient handoffs are considered to be critical safety issues.

To apply human factors engineering principles to improve alert interface design. We hypothesized that incorporating human factors principles into alerts would improve usability, reduce workload for prescribers, and reduce prescribing errors.

Doc'CISMeF (DC) is a semantic search engine used to find resources in CISMeF-BP, a quality controlled health gateway, which gathers guidelines available on the internet in French. Visualization of Concepts in Medicine (VCM) is an iconic language that may ease information retrieval tasks. This study aimed to describe the creation and evaluation of an interface integrating VCM in DC in order to make this search engine much easier to use.

Drug-drug interactions (DDIs) are an important consideration in both drug development and clinical application, especially for co-administered medications. While it is necessary to identify all possible DDIs during clinical trials, DDIs are frequently reported after the drugs are approved for clinical use, and they are a common cause of adverse drug reactions (ADR) and increasing healthcare costs. Computational prediction may assist in identifying potential DDIs during clinical trials.