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Clinical Data Mining in the Age of Evidence-Based Practice: Recent Exemplars and Future Challenges

Clinical Data Mining in the Age of Evidence-Based Practice: Recent Exemplars and Future Challenges
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Author(s): Irwin Epstein (City University of New York, USA) and Lynette Joubert (University of Melbourne, Australia)
Copyright: 2010
Pages: 21
Source title: Data Mining in Public and Private Sectors: Organizational and Government Applications
Source Author(s)/Editor(s): Antti Syvajarvi (University of Lapland, Finland) and Jari Stenvall (Tampere University, Finland)
DOI: 10.4018/978-1-60566-906-9.ch016

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Abstract

Clinical Data Mining (CDM) is a paradigm of practice-based research that engages practitioners in analyzing and evaluating routinely recorded material to explore, evaluate and reflect on their practice. The rationale for, and benefits of this research methodology are discussed with multiple exemplars from health and human service settings. While CDM was conceived as a quantitative methodology evaluating the process, intervention and outcomes of practice, it can support qualitative studies encouraging reflectiveness. CDM was originally employed as a practice based research (PBR) consultation strategy with practitioners in clinical settings, but the methodology has been increasingly used by doctoral students as a dissertation research strategy either by itself or in combination with other research methods. CDM has gained international recognition by both social workers and allied health professionals. The authors present CDM as a knowledge-generating paradigm contributing to “evidence-informed” practice rather than “evidence based practice.”

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