Comparison of Specialty Medication Use for Common Chronic Inflammatory Diseases Among Health Exchange and Other Commercially Insured Members.

Background: The Affordable Care Act of 2010 allows the purchase of health insurance through special marketplaces called "health exchanges." The majority of individuals enrolling in the exchanges were previously uninsured, older, and sicker than other commercially insured members. Early evidence also suggests that exchange plan members use more costly specialty drugs compared with other commercially insured members.

Intravenous Versus Subcutaneous Anti-TNF-Alpha Agents for Crohn's Disease: A Comparison of Effectiveness and Safety.

Background: In recent years, there have been a number of pharmacological innovations for Crohn's disease (CD), a difficult-to-treat condition, including new treatment philosophies (e.g., top-down therapy) and new therapeutic options in terms of the agent and the route of administration.

Considering patient preferences when selecting anti-tumor necrosis factor therapeutic options.

Background: Anti-tumor necrosis factor (TNF) medications for the treatment of chronic inflammatory conditions represent a large and growing expenditure for health plans. Over the past few years, there has been an increase in options for patients receiving anti-TNFs, including choice of agent, route of administration, and location for receiving the medication.

Objective: To examine patient preferences regarding available anti-TNF agents and mode of administration options.

Towards a framework for developing semantic relatedness reference standards.

Our objective is to develop a framework for creating reference standards for functional testing of computerized measures of semantic relatedness. Currently, research on computerized approaches to semantic relatedness between biomedical concepts relies on reference standards created for specific purposes using a variety of methods for their analysis. In most cases, these reference standards are not publicly available and the published information provided in manuscripts that evaluate computerized semantic relatedness measurement approaches is not sufficient to reproduce the results.

A corpus driven approach applying the "frame semantic" method for modeling functional status terminology.

In an effort to unearth semantic models that could prove fruitful to functional-status terminology development we applied the "frame semantic" method, derived from the linguistic theory of thematic roles currently exemplified in the Berkeley "FrameNet" Project. Full descriptive sentences with functional-status conceptual meaning were derived from structured content within a corpus of questionnaire assessment instruments commonly used in clinical practice for functional-status assessment. Syntactic components in those sentences were delineated through manual annotation and mark-up.

From clinical records to regulatory reporting: formal terminologies as foundation.

Achieving goals of healthy people and populations is dependent on available and relevant data for health care decisions. New technologies enable reuse of data for decisions, however it is clear that uniform data standards and in particular standards around terminological data will be required to achieve reuse. Terminological data related to functioning and disability presents unique challenges because of the conceptual ambiguity within the field.

Maximum entropy modeling for mining patient medication status from free text.

Using a classification scheme of patient medication status we sought to recognize and categorize medications mentioned in the unrestricted text of clinical documents generated in clinical practice. The categories refer to the patient's status with respect to the medication such as discontinuation, start or initiation, and continuation of a given medication. This categorization is performed with a machine learning technique, Maximum Entropy (ME), that is well suited to incorporating heterogeneous sources of information necessary for classifying patient's medication status.