The Southeastern Minnesota Beacon Project for Community-driven Health Information Technology: Origins, Achievements, and Legacy.

Introduction: The Southeastern (SE) Minnesota Beacon organized all the health care providers, county public health organizations, and school districts in the deployment and integration of health information exchange (HIE) and targeted health communication around childhood asthma and diabetes. The community cooperated to establish a clinical data repository for all residents in the 11-county region. Through this community of practice approach that involved traditional and nontraditional providers, the SE Minnesota Beacon was able to realize unique applications of this technology.

A brief Patient-Reported Outcomes Quality of Life (PROQOL) instrument to improve patient care.

Jeff Sloan and colleagues describe the development of the Patient-Reported Outcomes Quality of Life (PROQOL) instrument, which captures and stores patient-recorded outcomes in the medical record for patients with diabetes. Please see later in the article for the Editors' Summary.

Normalization and standardization of electronic health records for high-throughput phenotyping: the SHARPn consortium.

Research Objective: To develop scalable informatics infrastructure for normalization of both structured and unstructured electronic health record (EHR) data into a unified, concept-based model for high-throughput phenotype extraction.

Materials And Methods: Software tools and applications were developed to extract information from EHRs. Representative and convenience samples of both structured and unstructured data from two EHR systems-Mayo Clinic and Intermountain Healthcare-were used for development and validation.

The SHARPn project on secondary use of Electronic Medical Record data: progress, plans, and possibilities.

SHARPn is a collaboration among 16 academic and industry partners committed to the production and distribution of high-quality software artifacts that support the secondary use of EMR data. Areas of emphasis are data normalization, natural language processing, high-throughput phenotyping, and data quality metrics. Our work avails the industrial scalability afforded by the Unstructured Information Management Architecture (UIMA) from IBM Watson Research labs, the same framework which underpins the Watson Jeopardy demonstration.