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Develop a tool to disseminate integrated laboratory, clinical, and demographic case data necessary for improved contact tracing and outbreak detection of tuberculosis (TB).

Despite the widespread adoption of electronic health records (EHRs), usability of many EHRs continues to be suboptimal, with some vendors failing to meet usability standards, resulting in clinician frustration and patient safety hazards. In an effort to increase EHR vendor competition on usability, recommendations have been made and legislation drafted to develop comparison tools that would allow purchasers to better understand the usability of EHR products prior to purchase. Usability [...]

This paper describes a new congestive heart failure (CHF) treatment performance measure information extraction system - CHIEF - developed as part of the Automated Data Acquisition for Heart Failure project, a Veterans Health Administration project aiming at improving the detection of patients not receiving recommended care for CHF.

Access to online patient portals is key to improving care, but we have limited understanding of patient perceptions of online portals and the characteristics of people who use them.

With the rapid rise in the adoption of patient portals, many patients are gaining access to their personal health information online for the first time. The objective of this study was to examine specific usability barriers to patient portal engagement among a diverse group of patients and caregivers.

We describe how electronic health record (EHR) audit files can be used to understand how time is spent in primary care (PC).

Routine health information systems (RHISs) provide data that are vital for planning and monitoring individual health. Data from RHISs could also be used for purposes for which they were not originally intended, provided that the data are of sufficient quality. For example, morbidity data could be used to inform burden of disease estimations, which serve as important evidence to prioritize interventions and promote health. The objective of this study was [...]

Phenotyping algorithms are capable of accurately identifying patients with specific phenotypes from within electronic medical records systems. However, developing phenotyping algorithms in a scalable way remains a challenge due to the extensive human resources required. This paper introduces a high-throughput unsupervised feature selection method, which improves the robustness and scalability of electronic medical record phenotyping without compromising its accuracy.

The goal of this investigation was to determine whether automated approaches can learn patient-oriented care teams via utilization of an electronic medical record (EMR) system.

To determine the effect of availability of clinical information from an integrated electronic health record system on pregnancy outcomes at the point of care.