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The constant progress in computational linguistic methods provides amazing opportunities for discovering information in clinical text and enables the clinical scientist to explore novel approaches to care. However, these new approaches need evaluation. We describe an automated system to compare descriptions of epilepsy patients at three different organizations: Cincinnati Children's Hospital, the Children's Hospital Colorado, and the Children's Hospital of Philadelphia. To our knowledge, there have been no similar previous [...]

This study describes the implementation and impact of an electronic test result acknowledgement (RA) system in the Mater Mothers' Hospital in Brisbane, Australia. The Verdi application electronically records clinicians' acknowledgement of the review of results. Hospital data (August 2011-August 2012) were extracted to measure clinicians' acknowledgement practices. There were 27,354 inpatient test results for 6855 patients. All test results were acknowledged. 60% (95% CI 59% to 61%) of laboratory and [...]

To compare the agreement of electronic health record (EHR) data versus Medicaid claims data in documenting adult preventive care. Insurance claims are commonly used to measure care quality. EHR data could serve this purpose, but little information exists about how this source compares in service documentation. For 13 101 Medicaid-insured adult patients attending 43 Oregon community health centers, we compared documentation of 11 preventive services, based on EHR versus Medicaid claims [...]

Data-driven risk stratification models built using data from a single hospital often have a paucity of training data. However, leveraging data from other hospitals can be challenging owing to institutional differences with patients and with data coding and capture.

Although electronic health records (EHRs) have the potential to provide a foundation for quality and safety algorithms, few studies have measured their impact on automated adverse event (AE) and medical error (ME) detection within the neonatal intensive care unit (NICU) environment.

Children are a vulnerable population in the operating room, and are particularly at risk of complications from unanticipated hemorrhage. The decision to prepare blood products prior to surgery varies depending on the personal experience of the clinician caring for the patient. We present the first application of a data visualization technique to study large datasets in the context of blood product transfusions at a tertiary pediatric hospital. The visual analytical [...]

Named entity recognition (NER) is one of the fundamental tasks in natural language processing. In the medical domain, there have been a number of studies on NER in English clinical notes; however, very limited NER research has been carried out on clinical notes written in Chinese. The goal of this study was to systematically investigate features and machine learning algorithms for NER in Chinese clinical text.

Adverse drug reaction (ADR) can have dire consequences. However, our current understanding of the causes of drug-induced toxicity is still limited. Hence it is of paramount importance to determine molecular factors of adverse drug responses so that safer therapies can be designed.

There is currently limited information on best practices for the development of governance requirements for distributed research networks (DRNs), an emerging model that promotes clinical data reuse and improves timeliness of comparative effectiveness research. Much of the existing information is based on a single type of stakeholder such as researchers or administrators. This paper reports on a triangulated approach to developing DRN data governance requirements based on a combination of [...]