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An increasing number of healthcare providers are adopting patient safety event reporting systems, yet leveraging these data to improve safety remains a challenge, particularly with large datasets composed of thousands of event reports. A MedStar Health research team, with expertise in data analytics and human factors, developed intuitive visualization dashboards to facilitate data exploration and trend analysis. Dashboards were developed using an iterative design and development process that was end-user [...]

To analyze the completeness, computability, and accuracy of specifications for five National Quality Forum-specified (NQF) eMeasures spanning ambulatory, post-discharge, and emergency care within a comprehensive, integrated electronic health record (EHR) environment.

To develop and evaluate an electronic dashboard of hospital-wide electronic health record medication alerts for an alert fatigue reduction quality improvement project.

To examine the financial impact of electronic health record (EHR) implementation on ambulatory practices.

To visualize and describe collaborative electronic health record (EHR) usage for hospitalized patients with heart failure.

Develop and evaluate an automated case detection and response triggering system to monitor patients every 5 min and identify early signs of physiologic deterioration.

Hospital readmissions are common, costly, and offer opportunities for utilization reduction. Electronic health information exchange (HIE) systems may help prevent readmissions by improving access to clinical data by ambulatory providers after discharge from the hospital.

The effects of electronic health records (EHRs) on doctor-patient communication are unclear.

Electronic medical records with encoded entries should enhance the semantic interoperability of document exchange. However, it remains a challenge to encode the narrative concept and to transform the coded concepts into a standard entry-level document. This study aimed to use a novel approach for the generation of entry-level interoperable clinical documents.

The ShARe/CLEF eHealth 2013 Evaluation Lab Task 1 was organized to evaluate the state of the art on the clinical text in (i) disorder mention identification/recognition based on Unified Medical Language System (UMLS) definition (Task 1a) and (ii) disorder mention normalization to an ontology (Task 1b). Such a community evaluation has not been previously executed. Task 1a included a total of 22 system submissions, and Task 1b included 17. Most [...]