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De-identification allows faster and more collaborative clinical research while protecting patient confidentiality. Clinical narrative de-identification is a tedious process that can be alleviated by automated natural language processing methods. The goal of this research is the development of an automated text de-identification system for Veterans Health Administration (VHA) clinical documents.

To review the literature on clinical decision support (CDS) for genetically guided personalized medicine (GPM).

(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 examine information flow, a vital component of a patient's care and outcomes, in a sample of multiple hospital nursing units to uncover potential sources of error and opportunities for systematic improvement.

Logical Observation Identifiers Names and Codes (LOINC) mapping of laboratory data is often a question of the effort of mapping compared with the benefits of the structure achieved. The new LOINC mapping assistant RELMA (version 2011) has the potential to reduce the effort required for semi-automated mapping. We examined quality, time effort, and sustainability of such mapping.

At the 2011 American College of Medical Informatics (ACMI) Winter Symposium we studied the overlap between health IT and economics and what leading healthcare delivery organizations are achieving today using IT that might offer paths for the nation to follow for using health IT in healthcare reform. We recognized that health IT by itself can improve health value, but its main contribution to health value may be that it can [...]

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 [...]

Electronic health records (EHR) are becoming more common because of the federal EHR incentive programme, which is also promoting electronic health information exchange (HIE). To determine whether consumers' attitudes toward EHR and HIE are associated with experience with doctors using EHR, a nationwide random-digit-dial survey was conducted in December 2011. Of 1603 eligible people contacted, 1000 (63%) participated. Most believed EHR and HIE would improve healthcare quality (66% and 79% [...]

Significant limitations exist in the timely and complete identification of primary and recurrent cancers for clinical and epidemiologic research. A SAS-based coding, extraction, and nomenclature tool (SCENT) was developed to address this problem.

The use of the internet as a source of health information and link to healthcare services has raised concerns about the ability of consumers, especially vulnerable populations such as older adults, to access these applications. This study examined the influence of training on the ability of adults (aged 45+ years) to use the Medicare.gov website to solve problems related to health management. The influence of computer experience and cognitive abilities [...]