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To determine if IndiGO individualized clinical guidelines could be implemented in routine practice and assess their effects on care and care experience.

To understand the factors that influence success in scrubbing personal names from narrative text.

An innovative web-based system was developed to allow patient-reported outcome measures (PROMs) to be easily administered. Stakeholders guided the design and implementation. The software gives patients access to their current and previous scores. This pilot study focused on patients undergoing arthroscopic subacromial decompression, evaluated using the Oxford shoulder score (OSS). Patients showing good improvement in their OSS were offered the choice to return for routine follow-up clinic appointments, or continue [...]

Annotations to physical workspaces such as signs and notes are ubiquitous. When densely annotated, work areas become communication spaces. This study aims to characterize the types and purpose of such annotations.

To study the relation between electronic health record (EHR) variables and healthcare process events.

Mental illness is the leading cause of disability in the USA, but boundaries between different mental illnesses are notoriously difficult to define. Electronic medical records (EMRs) have recently emerged as a powerful new source of information for defining the phenotypic signatures of specific diseases. We investigated how EMR-based text mining and statistical analysis could elucidate the phenotypic boundaries of three important neuropsychiatric illnesses-autism, bipolar disorder, and schizophrenia.

Many cancer interventional clinical trials are not completed because the required number of eligible patients are not enrolled.

To describe a collaborative approach for developing an electronic health record (EHR) phenotyping algorithm for drug-induced liver injury (DILI).

Celiac disease (CD) is a lifelong immune-mediated disease with excess mortality. Early diagnosis is important to minimize disease symptoms, complications, and consumption of healthcare resources. Most patients remain undiagnosed. We developed two electronic medical record (EMR)-based algorithms to identify patients at high risk of CD and in need of CD screening.