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To evaluate the phenotyping performance of three major electronic health record (EHR) components: International Classification of Disease (ICD) diagnosis codes, primary notes, and specific medications.

Numerous articles have reported on the development of patient portals, including development problems and solutions. We review these articles to inform future patient portal development efforts and to provide a summary of the evidence base that can guide future research.

Online patient portals are being widely implemented; however, no studies have examined whether portals influence health behaviors or outcomes similarly across patient racial/ethnic subgroups. We evaluated longitudinal changes in statin adherence to determine whether racial/ethnic minorities initiating use of the online refill function in patient portals had similar changes over time compared with Whites.

Enormous amounts of healthcare data are becoming increasingly accessible through the large-scale adoption of electronic health records. In this work, structured and unstructured (textual) data are combined to assign clinical diagnostic and procedural codes (specifically ICD-9-CM) to patient stays. We investigate whether integrating these heterogeneous data types improves prediction strength compared to using the data types in isolation.

Hospitals are challenged to provide timely patient care while maintaining high resource utilization. This has prompted hospital initiatives to increase patient flow and minimize nonvalue added care time. Real-time demand capacity management (RTDC) is one such initiative whereby clinicians convene each morning to predict patients able to leave the same day and prioritize their remaining tasks for early discharge. Our objective is to automate and improve these discharge predictions by [...]

This study focused on patient portal use and investigated whether aesthetic evaluations of patient portals function are antecedent variables to variables in the Technology Acceptance Model.

To test the vulnerabilities of a wide range of computerized physician order entry (CPOE) systems to different types of medication errors, and develop a more comprehensive qualitative understanding of how their design could be improved.

To develop an open-source temporal relation discovery system for the clinical domain. The system is capable of automatically inferring temporal relations between events and time expressions using a multilayered modeling strategy. It can operate at different levels of granularity--from rough temporality expressed as event relations to the document creation time (DCT) to temporal containment to fine-grained classic Allen-style relations.

Develop a device-agnostic cloud platform to host diabetes device data and catalyze an ecosystem of software innovation for type 1 diabetes (T1D) management.