A Framework to Support the Sharing and Reuse of Computable Phenotype Definitions Across Health Care Delivery and Clinical Research Applications.

INTRODUCTION: The ability to reproducibly identify clinically equivalent patient populations is critical to the vision of learning health care systems that implement and evaluate evidence-based treatments. The use of common or semantically equivalent phenotype definitions across research and health care use cases will support this aim. Currently, there is no single consolidated repository for computable phenotype definitions, making it difficult to find all definitions that already exist, and also hindering the sharing of definitions between user groups. METHOD: Drawing from our experience in an academic medical center that supports a number of multisite research projects and quality improvement studies, we articulate a framework that will support the sharing of phenotype definitions across research and health care use cases, and highlight gaps and areas that need attention and collaborative solutions. FRAMEWORK: An infrastructure for re-using computable phenotype definitions and sharing experience across health care delivery and clinical research applications includes: access to a collection of existing phenotype definitions, information to evaluate their appropriateness for particular applications, a knowledge base of implementation guidance, supporting tools that are user-friendly and intuitive, and a willingness to use them. NEXT STEPS: We encourage prospective researchers and health administrators to re-use existing EHR-based condition definitions where appropriate and share their results with others to support a national culture of learning health care. There are a number of federally funded resources to support these activities, and research sponsors should encourage their use.

Medical education as moral formation: an Aristotelian account of medical professionalsim.

The medical professionalism movement, bolstered by many influential medical organizations and institutions, has in the last decade produced a number of conceptual definitions of professionalism and a number of concrete proposals for its measurement and teaching. These projects, however laudable, are misguided when they treat professionalism as a unitary descriptive concept rather than as a contested and therefore primarily evaluative one; when they conceive professionalism as a domain of medical practice separable in principle from other domains; and when they treat professionalism as, in principle, a specifiable goal or product of sufficiently well designed educational curricula. The logic of professionalism-as-product corresponds to the logic of techne (art or practical skill) in Aristotle's Nicomachean Ethics. Aristotle provides a cogent argument, however, that the moral excellences denoted by "professionalism" cannot be "produced" or even prespecified in the concrete; rather, they must be acquired through long practice under the careful concrete guidance of teachers who themselves embody these moral excellences. Phronesis (practical wisdom) rather than techne must therefore be the guiding logic of educational initiatives in medical professional formation, with particular emphasis on close mentorship and on the moral character both of students and of those who teach them.

Qualitative analysis of the interdisciplinary interaction between data analysis specialists and novice clinical researchers.

BACKGROUND: The inherent complexity of statistical methods and clinical phenomena compel researchers with diverse domains of expertise to work in interdisciplinary teams, where none of them have a complete knowledge in their counterpart's field. As a result, knowledge exchange may often be characterized by miscommunication leading to misinterpretation, ultimately resulting in errors in research and even clinical practice. Though communication has a central role in interdisciplinary collaboration and since miscommunication can have a negative impact on research processes, to the best of our knowledge, no study has yet explored how data analysis specialists and clinical researchers communicate over time. METHODS/PRINCIPAL FINDINGS: We conducted qualitative analysis of encounters between clinical researchers and data analysis specialists (epidemiologist, clinical epidemiologist, and data mining specialist). These encounters were recorded and systematically analyzed using a grounded theory methodology for extraction of emerging themes, followed by data triangulation and analysis of negative cases for validation. A policy analysis was then performed using a system dynamics methodology looking for potential interventions to improve this process. Four major emerging themes were found. Definitions using lay language were frequently employed as a way to bridge the language gap between the specialties. Thought experiments presented a series of "what if" situations that helped clarify how the method or information from the other field would behave, if exposed to alternative situations, ultimately aiding in explaining their main objective. Metaphors and analogies were used to translate concepts across fields, from the unfamiliar to the familiar. Prolepsis was used to anticipate study outcomes, thus helping specialists understand the current context based on an understanding of their final goal. CONCLUSION/SIGNIFICANCE: The communication between clinical researchers and data analysis specialists presents multiple challenges that can lead to errors.

The Toronto Word Pool: Norms for imagery, concreteness, orthographic variables, and grammatical usage for 1,080 words

Imagery and concreteness norms and percentage noun usage were obtained on the 1,080 verbal items from the Toronto Word Pool. Imagery was defined as the rated ease with which a word aroused a mental image, and concreteness was defined in relation to level of abstraction. The degree to which a word was functionally a noun was estimated in a sentence generation task. The mean and standard deviation of the imagery and concreteness ratings for each item are reported together with letter and printed frequency counts for the words and indications of sex differences in the ratings. Additional data in the norms include a grammatical function code derived from dictionary definitions, a percent noun judgment, indexes of statistical approximation to English, and an orthographic neighbor ratio. Validity estimates for the imagery and concreteness ratings are derived from comparisons with scale values drawn from the Paivio, Yuille, and Madigan (1968) noun pool and the Toglia and Battig (1978) norms. © 1982 Psychonomic Society, Inc.

RCN4GSC Workshop Report: Managing Data at the Interface of Biodiversity and (Meta)Genomics, March 2011.

Building on the planning efforts of the RCN4GSC project, a workshop was convened in San Diego to bring together experts from genomics and metagenomics, biodiversity, ecology, and bioinformatics with the charge to identify potential for positive interactions and progress, especially building on successes at establishing data standards by the GSC and by the biodiversity and ecological communities. Until recently, the contribution of microbial life to the biomass and biodiversity of the biosphere was largely overlooked (because it was resistant to systematic study). Now, emerging genomic and metagenomic tools are making investigation possible. Initial research findings suggest that major advances are in the offing. Although different research communities share some overlapping concepts and traditions, they differ significantly in sampling approaches, vocabularies and workflows. Likewise, their definitions of 'fitness for use' for data differ significantly, as this concept stems from the specific research questions of most importance in the different fields. Nevertheless, there is little doubt that there is much to be gained from greater coordination and integration. As a first step toward interoperability of the information systems used by the different communities, participants agreed to conduct a case study on two of the leading data standards from the two formerly disparate fields: (a) GSC's standard checklists for genomics and metagenomics and (b) TDWG's Darwin Core standard, used primarily in taxonomy and systematic biology.