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This article presents and describes our methods in developing a novel strategy for recruitment of underrepresented, community-based participants, for pragmatic research studies leveraging routinely collected electronic health record (EHR) data.

Previous research developed a new method for locating prescribing errors in rapidly discontinued electronic medication orders. Although effective, the prospective design of that research hinders its feasibility for regular use.

Hospitals use antibiograms to guide optimal empiric antibiotic therapy, reduce inappropriate antibiotic usage, and identify areas requiring intervention by antimicrobial stewardship programs. Creating a hospital antibiogram is a time-consuming manual process that is typically performed annually.

Simple measures of electronic health record (EHR) adoption may be inadequate to evaluate EHR use; and positive outcomes associated with EHRs may be better gauged when varying degrees of EHR use are taken into account. In this article, we aim to assess the current state of the literature regarding measuring EHR use.

The increased emphasis on patient satisfaction has coincided with the growing adoption of electronic health records (EHRs) throughout the U.S. The 2001 Institute of Medicine Report, “Crossing the Quality Chasm,” identified patient-centered care as a key element of quality health care.[1] In response to this call, the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey was developed to assess patients' health care experiences in the inpatient setting. Simultaneously [...]

While evidence generally supports the use of medication management technology, systems are typically implemented and evaluated piecemeal rather than as part of a comprehensive model for medication management. Systems to support drug therapy optimization, increasingly a key role of pharmacists in our healthcare system, have not yet been reported.

Allergies are increasing, but the reasons for this are unclear. Although environmental factors are thought to be important, there is a lack of data on how they contribute to symptom development. To understand this relationship better, we need accurate data about both symptoms and environmental factors. Our objective here is to ascertain whether experience sampling is a reliable approach for collecting allergy symptom data in the general population, allowing us [...]

The DAta Tag Suite (DATS) is a model supporting dataset description, indexing, and discovery. It is available as an annotated serialization with schema.org, a vocabulary used by major search engines, thus making the datasets discoverable on the web. DATS underlies DataMed, the National Institutes of Health Big Data to Knowledge Data Discovery Index prototype, which aims to provide a "PubMed for datasets." The experience gained while indexing a heterogeneous range [...]