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Despite at least 40 years of promising empirical performance, very few clinical natural language processing (NLP) or information extraction systems currently contribute to medical science or care. The authors address this gap by reducing the need for custom software and rules development with a graphical user interface-driven, highly generalizable approach to concept-level retrieval.

The 2010 i2b2/VA Workshop on Natural Language Processing Challenges for Clinical Records presented three tasks: a concept extraction task focused on the extraction of medical concepts from patient reports; an assertion classification task focused on assigning assertion types for medical problem concepts; and a relation classification task focused on assigning relation types that hold between medical problems, tests, and treatments. i2b2 and the VA provided an annotated reference standard corpus [...]

The BT-Nurse system uses data-to-text technology to automatically generate a natural language nursing shift summary in a neonatal intensive care unit (NICU). The summary is solely based on data held in an electronic patient record system, no additional data-entry is required. BT-Nurse was tested for two months in the Royal Infirmary of Edinburgh NICU. Nurses were asked to rate the understandability, accuracy, and helpfulness of the computer-generated summaries; they were [...]

The US Vaccine Adverse Event Reporting System (VAERS) collects spontaneous reports of adverse events following vaccination. Medical officers review the reports and often apply standardized case definitions, such as those developed by the Brighton Collaboration. Our objective was to demonstrate a multi-level text mining approach for automated text classification of VAERS reports that could potentially reduce human workload.

To evaluate the benefit of a health information exchange (HIE) between hospitals, we examine the rate of crossover among neurosurgical inpatients treated at Emory University Hospital (EUH) and Grady Memorial Hospital (GMH) in Atlanta, Georgia. To inform decisions regarding investment in HIE, we develop a methodology analyzing crossover behavior for application to larger more general patient populations.

Clinical Queries filters were developed to improve the retrieval of high-quality studies in searches on clinical matters. The study objective was to determine the yield of relevant citations and physician satisfaction while searching for diagnostic and treatment studies using the Clinical Queries page of PubMed compared with searching PubMed without these filters.

To assess whether a low level of decision support within a hospital computerized provider order entry system has an observable influence on the medication ordering process on ward-rounds and to assess prescribers' views of the decision support features.

Electronic personal health record systems (PHRs) support patient centered healthcare by making medical records and other relevant information accessible to patients, thus assisting patients in health self-management. We reviewed the literature on PHRs including design, functionality, implementation, applications, outcomes, and benefits. We found that, because primary care physicians play a key role in patient health, PHRs are likely to be linked to physician electronic medical record systems, so PHR adoption [...]

To understand how the source of information affects different adverse event (AE) surveillance methods.