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  • Murray Krahn (a1), Fiona Miller (a2), Ahmed Bayoumi (a3) (a4), Ann-Sylvia Brooker (a5), Frank Wagner (a6), Shawn Winsor (a7), Mita Giacomini (a8), Ron Goeree (a5), Holger Schünemann (a9), Gabrielle van der Velde (a2), Stephen Petersen (a10), Nancy Sikich (a10) and Irfan Dhalla (a10)...

In 2007, the Ontario Health Technology Advisory Committee (OHTAC) developed a decision framework to guide decision making around nondrug health technologies. In 2012, OHTAC commissioned a revision of this framework to enhance its usability and deepen its conceptual and theoretical foundations.


The committee overseeing this work used several methods: (a) a priori consensus on guiding principles, (b) a scoping review of decision attributes and processes used globally in health technology assessment (HTA), (c) presentations by methods experts and members of review committees, and (d) committee deliberations over a period of 3 years.


The committee adopted a multi-criteria decision-making approach, but rejected the formal use of multi-criteria decision analysis. Three broad categories of attributes were identified: (I) context criteria attributes included factors such as stakeholders, adoption pressures from neighboring jurisdictions, and potential conflicts of interest; (II) primary appraisal criteria attributes included (i) benefits and harms, (ii) economics, and (iii) patient-centered care; (III) feasibility criteria attributes included budget impact and organizational feasibility.


The revised Ontario Decision Framework is similar in some respects to frameworks used in HTA worldwide. Its distinctive characteristics are that: it is based on an explicit set of social values; HTA paradigms (evidence based medicine, economics, and bioethics/social science) are used to aggregate decision attributes; and that it is rooted in a theoretical framework of optimal decision making, rather than one related to broad social goals, such as health or welfare maximization.

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1.Johnson, AP, Sikich, NJ, Evans, G, et al. Health technology assessment: A comprehensive framework for evidence-based recommendations in Ontario. Int J Technol Assess Health Care. 2009;25:141-50.
2.Health Quality Ontario. Health technology assessments: Methods and process guide. Toronto, Ontario: Health Quality Ontario; 2017 p. 57
3.CADTH. pCODR Expert Review Committee: Deliberative Framework. 2016 March [16 pp.]. (accessed April 11, 2018).
4.Department of Health Clinical Access and Redesign Unit. The Queensland Policy and Advisory Committee on New Technology (QPACT): Decision making criteria. 2013:1. (accessed April 11, 2018).
5.Alonso-Coello, P, Oxman, AD, Moberg, J, et al. GRADE Evidence to Decision (EtD) frameworks: A systematic and transparent approach to making well informed healthcare choices. 2: Clinical practice guidelines. BMJ. 2016;353:i2089.
6.Goetghebeur, MM, Wagner, M, Khoury, H, et al. Evidence and Value: Impact on DEcisionMaking: The EVIDEM framework and potential applications. BMC Health Serv Res. 2008;8:270.
7.Anderson, JL, Heidenreich, PA, Barnett, PG, et al. ACC/AHA statement on cost/value methodology in clinical practice guidelines and performance measures: A report of the American College of Cardiology/American Heart Association Task Force on Performance Measures and Task Force on Practice Guidelines. J Am Coll Cardiol. 2014;63:2304-2322.
8.Schnipper, LE, Davidson, NE, Wollins, DS, et al. American Society of Clinical Oncology Statement: A conceptual framework to assess the value of cancer treatment options. J Clin Oncol. 2015;33:2563-2577.
9.Abelson, J, Wagner, F, DeJean, D, et al. Public and patient involvement in health technology assessment: A framework for action. Int J Technol Assess Health Care. 2016;32:256-264.
10.National Institute for Health Care Excellence (NICE). NICE process and methods guides. Social value judgements: Principles for the development of NICE guidance. London: National Institute for Health and Care Excellence (NICE); 2008.
11.Stafinski, T, Menon, D, Marshall, D, et al. Societal values in the allocation of healthcare resources: Is it all about the health gain? Patient. 2011;4:207-225.
12.Whitty, JA, Littlejohns, P. Social values and health priority setting in Australia: An analysis applied to the context of health technology assessment. Health Policy. 2015;119:127-136.
13.Giacomini, M, Wagner, F, Krahn, M, et al. Social and ethical values for health technology assessment in Ontario. Health Quality Transformation 2012; Toronto, Ontario, 2012.
14.Miller, F. Improving the appraisal of non-drug technologies: Revising the Ontario Decision Framework Ethics & Social Values: Patient centred care. [Internet]. Saskatoon, SK: CADTH Symposium; 2015 [updated April 14, 2015; cited October 2, 2017]. (accessed April 11, 2018).
15.Miller, GA. The magical number seven plus or minus two: Some limits on our capacity for processing information. Psychol Rev. 1956;63:81-97.
16.Redelmeier, DA, Rozin, P, Kahneman, D. Understanding patients' decisions. Cognitive and emotional perspectives. JAMA. 1993;270:72-76.
17.Abelson, J, Forest, PG, Eyles, J, et al. Deliberations about deliberative methods: Issues in the design and evaluation of public participation processes. Soc Sci Med. 2003;57:239-251.
18.Kuhn, TS. The structure of scientific revolutions. Chicago: University of Chicago Press; 1996.
19.Dogan, M. Paradigms in the Social Sciences. In: Smelser, NJ, Baltes, PB, eds. International encyclopedia of the social & behavioral sciences. Oxford: Pergamon; 2001. p. 11023-11027.
20.Devlin, N, Sussex, J. Incorporating multiple criteria in HTA: Methods and processes. London, UK: Office of Health Economics; 2011.
21.Claxton, K, Martin, S, Soares, M, et al. House of Commons, Parliamentary publication: Written Evidence (NICE 61). London, UK: Health Select Committee, 2012 October.
22.Keeney, RL. Utility functions for multiattributed consequences. Manage Sci. 1972;18(Pt-1):276-287.
23.Schoemaker, PJH. The expected utility model: Its variants, purposes, evidence and limitations. J Econ Lit. 1982;20:529-563.
24.von Neumann, J, Morgenstern, O, Kuhn, HW, et al. Theory of games and economic behavior (60th Anniversary Commemorative Edition). Princeton, NJ: Princeton University Press; 1944.
25.National Institute for Health and Care Excellence (NICE). Guide to the processes of technology appraisal: Foreword. London, UK: The National Institute for Health and Care Excellence (NICE); 2014
26.Brouwer, WB, Culyer, AJ, van Exel, NJ, et al. Welfarism vs. extra-welfarism. J Health Econ. 2008;27:325-338.
27.Institute for Clinical and Economic Review (ICER). Overview of the ICER value framework and proposals for an update for 2017–2018. Boston, MA: ICER; 2017. p. 1-24.
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International Journal of Technology Assessment in Health Care
  • ISSN: 0266-4623
  • EISSN: 1471-6348
  • URL: /core/journals/international-journal-of-technology-assessment-in-health-care
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