Terminological Systems for Representing Patient Status

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DESCRIPTION (provided by applicant): Health care is a profoundly information intensive industry, existing in an environment where the development and deployment of computer based technologies to support information processing is proceeding at an unprecedented pace. Unfortunately, the lack of consistent and comparable terminological data remains a significant barrier to fully realizing the potential of these new technologies. Concept based terminologies terminology systems offer solutions, emphasizing concept based approaches to terminology rather than lexical based approaches. The overall focus of this proposal is on the underlying concept systems that are required for the machine processing of terminological data related to the subject field of "patient status". We use the term patient status to refer to the dimensions of physical, social, and cognitive functioning within the context of health, disease, and the environment in which one lives. The specific aims of this project are to 1) identify and evaluate terms and terminology systems relevant to patient status, 2) describe a terminology system specific to the subject field of patient status identify and evaluate, and 3) compare a terminology system to formally represent patient status to reference terminology and information models. In accomplishing this, we will leverage nearly a decade of work at the Mayo Clinic that is emphasized concept based terminology systems in support of automated indexing of clinical records, and considerable pilot work specific to indexing the domain of patient status. In contrast to terminology developments that have emphasized disciplinary and business perspectives in modeling initiatives, we are employing a "bottom-up" perspective, emphasizing the subject field perspective of patient status through the assembly of rich textual corpora. At the end of this study, we intend to make available a scalable resource for this field. This work does not duplicate any existing work in terminology and information modeling work, rather extensively builds on existing work.