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Priority setting for new technologies in medicine: a transdisciplinary study.

Jennifer L Gibson1, Douglas K Martin, Peter A Singer

  • 1University of Toronto Joint Centre for Bioethics, 88 College St, Toronto, Canada M5G-1L4. jegibson@chass.utoronto.ca

BMC Health Services Research
|July 20, 2002
PubMed
Summary

Healthcare leaders face challenges prioritizing new medical technologies. This study integrates ethical and empirical findings into a practical, transdisciplinary model for effective technology priority setting.

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Area of Science:

  • Health Services Research
  • Medical Technology Assessment
  • Healthcare Management

Background:

  • Healthcare organizations face significant challenges in prioritizing the adoption of new medical technologies.
  • Existing methods for technology priority setting are often inadequate, lacking a universally accepted framework.
  • Decision-makers require robust models to navigate complex choices regarding medical innovations.

Purpose of the Study:

  • To develop a comprehensive model for priority setting of new medical technologies.
  • To integrate ethical considerations with empirical observations of current practices.
  • To provide an operationalizable framework for healthcare decision-makers.

Main Methods:

  • Integration of an ethically-based account (Daniels and Sabin) with an empirically-based account of priority setting.

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  • Development of a transdisciplinary model synthesizing theoretical and practical perspectives.
  • Focus on real-world application and operationalization within healthcare institutions.

    • Main Results:

    • A novel transdisciplinary model for medical technology priority setting has been established.
    • The model successfully integrates ethical principles with empirical data on decision-making processes.
    • The framework is designed to be actionable for healthcare organizations.

    Conclusions:

    • The developed transdisciplinary model offers a practical approach to medical technology priority setting.
    • This ethically and empirically grounded model provides essential guidance for healthcare decision-makers.
    • Operationalizing this model can help institutions address challenges in adopting new medical technologies.