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To develop and test a parsimonious and actionable model of effective technology use (ETU).

Develop and test web services to retrieve and identify the most precise ICD-10-CM code(s) for a given clinical encounter. Facilitate creation of user interfaces that 1) provide an initial shortlist of candidate codes, ideally visible on a single screen; and 2) enable code refinement.

Markers of illness severity are increasingly captured in emergency department (ED) electronic systems, but their value for surveillance is not known. We assessed the value of age, triage score, and disposition data from ED electronic records for predicting influenza-related hospitalizations.

In the United States, International Classification of Disease Clinical Modification (ICD-9-CM, the ninth revision) diagnosis codes are commonly used to identify patient cohorts and to conduct financial analyses related to disease. In October 2015, the healthcare system of the United States will transition to ICD-10-CM (the tenth revision) diagnosis codes. One challenge posed to clinical researchers and other analysts is conducting diagnosis-related queries across datasets containing both coding schemes. Further [...]

To evaluate the utility of applying the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) across multiple observational databases within an organization and to apply standardized analytics tools for conducting observational research.

Currently, the processes for harmonizing and extending standards by leveraging the knowledge within local documentation artifacts are not well described. We describe a collaborative project to develop common information models, terminology bindings, and term definitions based on nursing documentation systems, and carry the findings through to the adoption in standards development organizations (SDOs) and technical implementations in clinical applications.

For many literature review tasks, including systematic review (SR) and other aspects of evidence-based medicine, it is important to know whether an article describes a randomized controlled trial (RCT). Current manual annotation is not complete or flexible enough for the SR process. In this work, highly accurate machine learning predictive models were built that include confidence predictions of whether an article is an RCT.

Standards terminologies may be large and complex, making their quality assurance challenging. Some terminology quality assurance (TQA) methodologies are based on abstraction networks (AbNs), compact terminology summaries. We have tested AbNs and the performance of related TQA methodologies on small terminology hierarchies. However, some standards terminologies, for example, SNOMED, are composed of very large hierarchies. Scaling AbN TQA techniques to such hierarchies poses a significant challenge. We present a scalable [...]

Large and complex terminologies, such as Systematized Nomenclature of Medicine-Clinical Terms (SNOMED CT), are prone to errors and inconsistencies. Abstraction networks are compact summarizations of the content and structure of a terminology. Abstraction networks have been shown to support terminology quality assurance. In this paper, we introduce an abstraction network derivation methodology which can be applied to SNOMED CT target hierarchies whose classes are defined using only hierarchical relationships (ie [...]