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The gap between domain experts and natural language processing expertise is a barrier to extracting understanding from clinical text. We describe a prototype tool for interactive review and revision of natural language processing models of binary concepts extracted from clinical notes. We evaluated our prototype in a user study involving 9 physicians, who used our tool to build and revise models for 2 colonoscopy quality variables. We report changes in [...]

The International Classification of Functioning, Disability and Health (ICF) is the World Health Organization's standard for describing health and health-related states. Examples of how the ICF has been used in Electronic Health Records (EHRs) have not been systematically summarized and described yet.

While most hospitals have adopted electronic health records (EHRs), we know little about whether hospitals use EHRs in advanced ways that are critical to improving outcomes, and whether hospitals with fewer resources - small, rural, safety-net - are keeping up.

Improved methods to identify nonmedical opioid use can help direct health care resources to individuals who need them. Automated algorithms that use large databases of electronic health care claims or records for surveillance are a potential means to achieve this goal. In this systematic review, we reviewed the utility, attempts at validation, and application of such algorithms to detect nonmedical opioid use.

To determine the effect of health information exchange (HIE) on medication prescribing for hospital inpatients in a cluster-randomized controlled trial, and to examine the prescribing effect of availability of information from a large pharmacy insurance plan in a natural experiment.

To develop an open-source information extraction system called Eligibility Criteria Information Extraction (EliIE) for parsing and formalizing free-text clinical research eligibility criteria (EC) following Observational Medical Outcomes Partnership Common Data Model (OMOP CDM) version 5.0.

One promise of nationwide adoption of electronic health records (EHRs) is the availability of data for large-scale clinical research studies. However, because the same patient could be treated at multiple health care institutions, data from only a single site might not contain the complete medical history for that patient, meaning that critical events could be missing. In this study, we evaluate how simple heuristic checks for data "completeness" affect the [...]

Clinical decision support tools for risk prediction are readily available, but typically require workflow interruptions and manual data entry so are rarely used. Due to new data interoperability standards for electronic health records (EHRs), other options are available. As a clinical case study, we sought to build a scalable, web-based system that would automate calculation of kidney failure risk and display clinical decision support to users in primary care practices.

To systematically review the literature pertaining to asynchronous automated electronic notifications of laboratory results to clinicians.