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We propose a system, quEHRy, to retrieve precise, interpretable answers to natural language questions from structured data in electronic health records (EHRs).

Severe infection can lead to organ dysfunction and sepsis. Identifying subphenotypes of infected patients is essential for personalized management. It is unknown how different time series clustering algorithms compare in identifying these subphenotypes.

The study tests a community- and data-driven approach to homelessness prevention. Federal policies call for efficient and equitable local responses to homelessness. However, the overwhelming demand for limited homeless assistance is challenging without empirically supported decision-making tools and raises questions of whom to serve with scarce resources.

Hospital acquired infections (HAIs) are one of the top 10 leading causes of death within the United States. While current standard of HAI risk prediction utilizes only a narrow set of predefined clinical variables, we propose a graph convolutional neural network (GNN)-based model which incorporates a wide variety of clinical features.

Sustainable investment in computerized decision support systems (CDSS) requires robust evaluation of their economic impacts compared with current clinical workflows. We reviewed current approaches used to evaluate the costs and consequences of CDSS in hospital settings and presented recommendations to improve the generalizability of future evaluations.

Observational studies of diabetic retinopathy (DR) using electronic health record data often determine disease severity using International Classification of Disease (ICD) codes. We investigated the mechanism of missingness for DR severity based on ICD coding using the American Academy of Ophthalmology IRIS® Registry. We included all patient encounters in the registry with a DR ICD-9 or ICD-10 code between January 1, 2014 and June 30, 2021. Demographic, clinical, and practice-level [...]

The objective was to develop a dataset definition, information model, and FHIR® specification for key data elements contained in a German molecular genomics (MolGen) report to facilitate genomic and phenotype integration in electronic health records.

To study the coverage and challenges in mapping 3 national and international procedure coding systems to the International Classification of Health Interventions (ICHI).

Compared to natural language processing research investigating suicide risk prediction with social media (SM) data, research utilizing data from clinical settings are scarce. However, the utility of models trained on SM data in text from clinical settings remains unclear. In addition, commonly used performance metrics do not directly translate to operational value in a real-world deployment. The objectives of this study were to evaluate the utility of SM-derived training data [...]