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Title Building Decision Support Systems: Development of an Instrument for Data Extraction from the Literature
Author(s) Renee D. Feuerbach and T. Panniers
Source Proceedings of the 2001 AMIA Annual Symposium, Pages 905-905
ISBN 1-56053-536-9
Publisher Hanley and Belfus, Inc.
Publication Date November 2001
Abstract Decision support systems (DSS) assist caregivers to make decisions that can lead to positive health outcomes. In order to build a DSS that will be acceptable to clinicians in their practice, it is imperative that the knowledge engineer identifies, defines, and describes a clinical problem precisely. This precision facilitates effective communication when modeling decisions. Clinical problems can be subjectively identified, defined, and described by clinicians in the practice setting and objectively defined by clinicians reviewing the scientific literature. The present study demonstrates a method for examining the scientific literature in a systematic way to define and delineate boundaries for clinical problems. An instrument that extracts definitions of terminology from the literature surrounding the concept of oral feeding in premature infants in a neonatal intensive care unit (NICU) is presented. Premature infants are defined as neonates regardless of birth weight, born before 37 weeks of gestation [1]. Initially, a sample of health care sources that include the relevant terminology surrounding the concept of oral feeding in premature infants in the NICU were systematically identified. Non-random sampling was used to choose sources judged to be typical of the literature. Three published lists of books and journals compiled by health science librarians [2,3,4] and four electronic databases of key indices in the health sciences were searched. Next, a list of readings, recommended to prospective examinees in preparation for certification, was obtained from the board certification agencies of pediatric nurse practitioners and neonatal nurse practitioners, respectively. After redundancy between lists was corrected and the reference list was assessed for content validity a non-random sample size of 43 sources was obtained. Next, a source rating form was designed to systematically assist in the selection of appropriate sources from the reference list. The development of this form was guided by a review of previously used instruments for data extraction from the literature aimed at defining nursing interventions [5]. Scoring criteria were based on comprehensiveness and specificity. Subsequently, a coding system was developed to extract the data from each source with a score of 2 or above. Finally, a pilot study was conducted after stratified random sampling. The results indicated the need for an additional step in the systematic search for each premature infant feeding term. For example, the definition of nipple feeding may be indexed under bottle feeding or feeding, bottle or feeding, nipple. A template form was designed to address this problem. After completion of the systematic scoring of each sample source, information analysis will begin. In consultation with a methodologist, a coding system for premature infant feeding terms will be developed and piloted. In summary, an instrument to systematically extract data from the literature was developed to assist researchers and practitioners to communicate effectively when building a DSS. This novel method of information analysis can also be applied to other clinical problems that are deemed appropriate for decision support system development, effectively addressing an important measurement issue in informatics research.

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