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The aim of this paper is to summarize concerns with the de-identification standard and methodologies established under the Health Insurance Portability and Accountability Act (HIPAA) regulations, and report some potential policies to address those concerns that were discussed at a recent workshop attended by industry, consumer, academic and research stakeholders.

To review the methods and dimensions of data quality assessment in the context of electronic health record (EHR) data reuse for research.

We explore relationships between health information seeking activities and engagement with healthcare professionals via a privacy-sensitive analysis of geo-tagged data from mobile devices.

This study assessed the effectiveness of a fully automated surveillance system for the detection of healthcare-associated infections (HCAIs) in intensive care units. Manual ward surveillance (MS) and electronic surveillance (ES) were performed for two intensive care units of the Vienna General Hospital. All patients admitted for a period longer than 48 h between 13 November 2006 and 7 February 2007 were evaluated according to HELICS-defined rules for HCAI. The sensitivity [...]

To identify key principles for establishing a national clinical decision support (CDS) knowledge sharing framework.

Breakthroughs in molecular profiling technologies are enabling a new data-intensive approach to biomedical research, with the potential to revolutionize how we study, manage, and treat complex diseases. The next great challenge for clinical applications of these innovations will be to create scalable computational solutions for intelligently linking complex biomedical patient data to clinically actionable knowledge. Traditional database management systems (DBMS) are not well suited to representing complex syntactic and semantic [...]

To provide a set of high-quality time-series physiologic and event data from anesthetic cases formatted in an easy-to-use structure.

(1) To evaluate a state-of-the-art natural language processing (NLP)-based approach to automatically de-identify a large set of diverse clinical notes. (2) To measure the impact of de-identification on the performance of information extraction algorithms on the de-identified documents.

To try to lower patient re-identification risks for biomedical research databases containing laboratory test results while also minimizing changes in clinical data interpretation.

To determine what, if any, opportunity exists in using administrative medical claims data for supplemental reporting to the state infectious disease registry system.