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An analysis of the timing of events is critical for a deeper understanding of the course of events within a patient record. The 2012 i2b2 NLP challenge focused on the extraction of temporal relationships between concepts within textual hospital discharge summaries.

Electronic health records (EHRs) are increasingly useful for health services research. For relatively uncommon conditions, such as multiple myeloma (MM) and its treatment-related complications, a combination of multiple EHR sources is essential for such research. The Shared Health Research Information Network (SHRINE) enables queries for aggregate results across participating institutions. Development of a rational search strategy in SHRINE may be augmented through analysis of pre-existing databases. We developed a SHRINE [...]

Prognostic studies of breast cancer survivability have been aided by machine learning algorithms, which can predict the survival of a particular patient based on historical patient data. However, it is not easy to collect labeled patient records. It takes at least 5 years to label a patient record as 'survived' or 'not survived'. Unguided trials of numerous types of oncology therapies are also very expensive. Confidentiality agreements with doctors and [...]

Detecting complex patterns of association between genetic or environmental risk factors and disease risk has become an important target for epidemiological research. In particular, strategies that provide multifactor interactions or heterogeneous patterns of association can offer new insights into association studies for which traditional analytic tools have had limited success.

To explore how key components of economic evaluations have been included in evaluations of health information systems (HIS), to determine the state of knowledge on value for money for HIS, and provide guidance for future evaluations.

Allergy documentation and exchange are vital to ensuring patient safety. This study aims to analyze and compare various existing standard terminologies for representing allergy information.

An enduring challenge in personalized medicine lies in selecting the right drug for each individual patient. While testing of drugs on patients in large trials is the only way to assess their clinical efficacy and toxicity, we dramatically lack resources to test the hundreds of drugs currently under development. Therefore the use of preclinical model systems has been intensively investigated as this approach enables response to hundreds of drugs to [...]

Effective clinical communication is critical to providing high-quality patient care. Hospitals have used different types of interventions to improve communication between care teams, but there have been few studies of their effectiveness.

The goal of this work was to evaluate machine learning methods, binary classification and sequence labeling, for medication-attribute linkage detection in two clinical corpora.