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Cohort definition is a bottleneck for conducting clinical research and depends on subjective decisions by domain experts. Data-driven cohort definition is appealing but requires substantial knowledge of terminologies and clinical data models. Criteria2Query is a natural language interface that facilitates human-computer collaboration for cohort definition and execution using clinical databases.

Clinical research data warehouses are largely populated from information extracted from electronic health records (EHRs). While these data provide information about a patient's medications, laboratory results, diagnoses, and history, her social, economic, and environmental determinants of health are also major contributing factors in readmission, morbidity, and mortality and are often absent or unstructured in the EHR. Details about a patient's socioeconomic status may be found in the U.S. census. To [...]

The study sought to describe patient-entered supplemental information on symptomatic adverse events (AEs) in cancer clinical research reported via a National Cancer Institute software system and examine the feasibility of mapping these entries to established terminologies.

Health information technology (HIT) interventions include electronic patient records, prescribing, and ordering systems. Clinical pathways are multidisciplinary plans of care that enable the delivery of evidence-based healthcare. Our objective was to systematically review the effects of implementing HIT-supported clinical pathways.

Effective communication is critical to the safe delivery of care but is characterized by outdated technologies. Mobile technology has the potential to transform communication and teamwork but the evidence is currently uncertain. The objective of this systematic review was to summarize the quality and breadth of evidence for the impact of mobile technologies on communication and teamwork in hospitals.

Electronic health record (EHR) data are increasingly used for biomedical discoveries. The nature of the data, however, requires expertise in both data science and EHR structure. The Observational Medical Out-comes Partnership (OMOP) common data model (CDM) standardizes the language and structure of EHR data to promote interoperability of EHR data for research. While the OMOP CDM is valuable and more attuned to research purposes, it still requires extensive domain knowledge [...]

Immune checkpoint inhibitors (ICIs) have dramatically improved outcomes in cancer patients. However, ICIs are associated with significant immune-related adverse events (irAEs) and the underlying biological mechanisms are not well-understood. To ensure safe cancer treatment, research efforts are needed to comprehensively detect and understand irAEs.

Acute kidney injury (AKI) in hospitalized patients puts them at much higher risk for developing future health problems such as chronic kidney disease, stroke, and heart disease. Accurate AKI prediction would allow timely prevention and intervention. However, current AKI prediction researches pay less attention to model building strategies that meet complex clinical application scenario. This study aims to build and evaluate AKI prediction models from multiple perspectives that reflect different [...]

To identify factors impacting physician use of information charted by others.

Integrating patient-reported outcomes (PROs) into electronic health records (EHRs) can improve patient-provider communication and delivery of care. However, new system implementation in health-care institutions is often accompanied by a change in clinical workflow and organizational culture. This study examines how well an EHR-integrated PRO system fits clinical workflows and individual needs of different provider groups within 2 clinics.