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The Clinical Language Understanding group at Nuance Communications has developed a medical information extraction system that combines a rule-based extraction engine with machine learning algorithms to identify and categorize references to patient smoking in clinical reports. The extraction engine identifies smoking references; documents that contain no smoking references are classified as UNKNOWN. For the remaining documents, the extraction engine uses linguistic analysis to associate features such as status and time [...]

Patients, policymakers, providers, payers, employers, and others have increasing interest in using personal health records (PHRs) to improve healthcare costs, quality, and efficiency. While organizations now invest millions of dollars in PHRs, the best PHR architectures, value propositions, and descriptions are not universally agreed upon. Despite widespread interest and activity, little PHR research has been done to date, and targeted research investment in PHRs appears inadequate. The authors reviewed the [...]

Infobuttons are decision support tools that provide links within electronic medical record systems to relevant content in online information resources. The aim of infobuttons is to help clinicians promptly meet their information needs. The objective of this study was to determine whether infobutton links that direct to specific content topics ("topic links") are more effective than links that point to general overview content ("nonspecific links").

To externally validate EPICON, a computerized system for grouping diagnoses from EMRs in general practice into episodes of care. These episodes can be used for estimating morbidity rates.

There has been major progress both in description logics and ontology design since SNOMED was originally developed. The emergence of the standard Web Ontology language in its latest revision, OWL 1.1 is leading to a rapid proliferation of tools. Combined with the increase in computing power in the past two decades, these developments mean that many of the restrictions that limited SNOMED's original formulation no longer need apply. We argue [...]

The American Medical Informatics Association (AMIA) recently augmented the scope of its activities to encompass translational bioinformatics as a third major domain of informatics. The AMIA has defined translational bioinformatics as "... the development of storage, analytic, and interpretive methods to optimize the transformation of increasingly voluminous biomedical data into proactive, predictive, preventative, and participatory health." In this perspective, I will list eight reasons why this is an excellent time [...]

OBJECTIVES This study sought to examine the differences between ignoring (naïve) and incorporating dependency (nonnaïve) among linkage variables on the outcome of a probabilistic record linkage study. DESIGN AND MEASUREMENTS We used the outcomes of a previously developed probabilistic linkage procedure for different registries in perinatal care assuming independence among linkage variables. We estimated the impact of ignoring dependency by re-estimating the linkage weights after constructing a variable that combines [...]

Innovative approaches can strengthen patient-caregiver-clinician information exchange and more effectively address the physical and psychosocial challenges of advanced disease. This study reports initial findings from implementation of the Clinician Report (CR)-a patient and caregiver status report tool accessible by the oncology clinic team.

Computerized monitors can effectively detect and potentially prevent adverse drug events (ADEs). Most monitors have been developed in large academic hospitals and are not readily usable in other settings. We assessed the ability of a commercial program to identify and prevent ADEs in a community hospital.

There is increasing pressure to share health information and even make it publicly available. However, such disclosures of personal health information raise serious privacy concerns. To alleviate such concerns, it is possible to anonymize the data before disclosure. One popular anonymization approach is k-anonymity. There have been no evaluations of the actual re-identification probability of k-anonymized data sets.