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Three visions of doctoring: a Gadamerian dialogue.

Benjamin Chin-YeeAtara MessingerL Trevor Young
Published in: Advances in health sciences education : theory and practice (2018)
Medicine in the twenty-first century faces an 'identity crisis,' as it grapples with the emergence of various 'ways of knowing,' from evidence-based and translational medicine, to narrative-based and personalized medicine. While each of these approaches has uniquely contributed to the advancement of patient care, this pluralism is not without tension. Evidence-based medicine is not necessary individualized; personalized medicine may be individualized but is not necessarily person-centered. As novel technologies and big data continue to proliferate today, the focus of medical practice is shifting away from the dialogic encounter between doctor and patient, threatening the loss of humanism that many view as integral to medicine's identity. As medical trainees, we struggle to synthesize medicine's diverse and evolving 'ways of knowing' and to create a vision of doctoring that integrates new forms of medical knowledge into the provision of person-centered care. In search of answers, we turned to twentieth-century philosopher Hans-Georg Gadamer, whose unique outlook on "health" and "healing," we believe, offers a way forward in navigating medicine's 'messy pluralism.' Drawing inspiration from Gadamer's emphasis on dialogue and 'practical wisdom' (phronesis), we initiated a dialogue with the dean of our medical school to address the question of how medical trainees and practicing clinicians alike can work to create a more harmonious pluralism in medicine today. We propose that implementing a pluralistic approach ultimately entails 'bridging' the current divide between scientific theory and the practical art of healing, and involves an iterative and dialogic process of asking questions and seeking answers.
Keyphrases
  • healthcare
  • big data
  • public health
  • mental health
  • machine learning
  • primary care
  • quality improvement
  • artificial intelligence
  • risk assessment
  • deep learning
  • pain management
  • climate change