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Development and pilot of a multicriteria decision analysis (MCDA) tool for health services administrators
  1. Robin Blythe1,
  2. Shamesh Naidoo2,
  3. Cameron Abbott2,
  4. Geoffrey Bryant2,
  5. Amanda Dines2,
  6. Nicholas Graves1
  1. 1 Australian Centre for Health Services Innovation, Institute of Health and Biomedical Innovation, School of Public Health and Social Work, Queensland University of Technology, Brisbane, Queensland, Australia
  2. 2 Administration, Royal Brisbane and Women’s Hospital, Herston, Queensland, Australia
  1. Correspondence to Robin Blythe; robin.blythe{at}qut.edu.au

Abstract

Introduction Health administration is complex and serves many masters. Value, quality, infrastructure and reimbursement are just a sample of the competing interests influencing executive decision-making. This creates a need for decision processes that are rational and holistic.

Methods We created a multicriteria decision analysis tool to evaluate six fields of healthcare provision: return on investment, capacity, outcomes, safety, training and risk. The tool was designed for prospective use, at the beginning of each funding round for competing projects. Administrators were asked to rank their criteria in order of preference. Each field was assigned a representative weight determined from the rankings. Project data were then entered into the tool for each of the six fields. The score for each field was scaled as a proportion of the highest scoring project, then weighted by preference. We then plotted findings on a cost-effectiveness plane. The project was piloted and developed over successive uses by the hospital’s executive board.

Results Twelve projects competing for funding at the Royal Brisbane and Women’s Hospital were scored by the tool. It created a priority ranking for each initiative based on the weights assigned to each field by the executive board. Projects were plotted on a cost-effectiveness plane with score as the x-axis and cost of implementation as the y-axis. Projects to the bottom right were considered dominant over projects above and to the left, indicating that they provided greater benefit at a lower cost. Projects below the x-axis were cost-saving and recommended provided they did not harm patients. All remaining projects above the x-axis were then recommended in order of lowest to highest cost-per-point scored.

Conclusion This tool provides a transparent, objective method of decision analysis using accessible software. It would serve health services delivery organisations that seek to achieve value in healthcare.

  • health economics
  • organisation of health services
  • quality in health care
  • health economics

This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/.

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Footnotes

  • Contributors RB: Conceptualisation, analysis, investigation, methodology, visualisation, writing, review. SN: Conceptualisation, analysis, investigation, methodology, visualisation, writing, review. CA: Analysis, investigation, methodology, review. GB: Conceptualisation, methodology, visualisation. AD: Conceptualisation, writing, review. NG: Conceptualisation, analysis, investigation, methodology, writing, review.

  • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

  • Competing interests None declared.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data sharing statement Data on the specific projects evaluated in the tool have been obtained from the RBWH hospital in Brisbane, Australia. If desired, please contact the RBWH for further information.

  • Patient consent for publication Not required.