Prioritize pharmaceuticals, medical devices, equipment, procedures and other health technologies.
Health decision-makers have to grapple with how best to allocate new funding as it becomes available. They must choose from entirely new technologies as well as, potentially, how much more to spend on existing technologies.
Such choices involves confronting trade-offs between multiple objectives or criteria, and so methods based on Multi-Criteria Decision-Making (MCDM, also known as Multi-Criteria Decision Analysis, MCDA) are increasingly popular.
About the use of 1000minds for health technology prioritization.
- J Chua, P Hansen, A Briggs, & J Abbott (2019), abstract, 2019 OARSI World Congress on Osteoarthritis: Promoting Clinical and Basic Research in Osteoarthritis, Toronto, Canada, 2019, “What attributes of interventions for osteoarthritis drive preferences? A discrete choice experiment involving cross-sectoral and multi-disciplinary stakeholder groups”, Osteoarthritis and Cartilage 27, S302
- J Chua, P Hansen, A Briggs, R Wilson, D Gwynne-Jones & J Abbott (2019), abstract, 2019 OARSI World Congress on Osteoarthritis: Promoting Clinical and Basic Research in Osteoarthritis, Toronto, Canada, 2019, “Integrating values and preferences with the best available evidence: a multi-criteria decision analysis approach”, Osteoarthritis and Cartilage 27, S308-S309
- J Eyles, D Hunter, K Bennell et al (2019), “Priorities for the effective implementation of osteoarthritis management programs: an OARSI international consensus exercise”, Osteoarthritis and Cartilage, early online version
- J Eyles, K Bennell, K Dziedzic et al (2019), abstract, 2019 OARSI World Congress on Osteoarthritis: Promoting Clinical and Basic Research in Osteoarthritis, Toronto, Canada, 2019, “Implementation priorities for osteoarthritis management programs”, Osteoarthritis and Cartilage 27, S307-S308
- P Hansen & N Devlin (2019), “Multi-Criteria Decision Analysis (MCDA) in health care decision making”, In: Oxford Research Encyclopedia of Economics and Finance, Oxford University Press
- F Ombler, M Albert & P Hansen (2018), “How significant are ‘high’ correlations between EQ-5D value sets?”, Medical Decision Making 38, 635-45
- I Lasorsa, E Padoano, S Marceglia & A Accardo (2018), “Multi-criteria decision analysis for the assessment of non-clinical hospital services: Methodology and case study”, Operations Research for Health Care, early online version
- M Espinoza, R Rojas & H de Patiño (2018), “Knowledge translation in practice: Exploring the potential use of MCDA in Central America and the Caribbean”, Value in Health Regional Issues 17, 148-9
- S Howard, I Scott, H Ju, L McQueen & P Scuffham (2018), “Multicriteria decision analysis (MCDA) for health technology assessment: the Queensland Health experience”, Australian Health Review, early online version
- A Shmueli (2017), “Do the equity-efficiency preferences of the Israeli Basket Committee match those of Israeli health policy makers?”, Israel Journal of Health Policy Research 6, 20
- A Shmueli, O Golan, F Paolucci & E Mentzakis (2017), “Efficiency and equity considerations in the preferences of health policymakers in Israel”, Israel Journal of Health Policy Research 6, 18
- J Drake, J Carlos T de Hart, C Monleón, W Toro & J Valentim (2017), “Utilization of multiple-criteria decision analysis (MCDA) to support healthcare decision-making FIFARMA, 2016”, Journal of Market Access & Health Policy 5, 1360545
- T Sullivan & P Hansen (2017), “Determining criteria and weights for prioritizing health technologies based on the preferences of the general population: A New Zealand pilot study”, Value in Health 20, 679-86
- N Martelli, P Hansen, H van den Brink et al (2016), “Combining multi-criteria decision analysis and mini-health technology assessment: A funding decision-support tool for medical devices in a university hospital setting”, Journal of Biomedical Informatics 59, 201-08
- I Lasorsa, G Abis, B Podda & A Accardo (2015), “Multi-criteria decision analysis to redesign an Italian Clinical Engineering Service under specific needs and regulation requirements”, In: D Jaffray (editor), World Congress on Medical Physics and Biomedical Engineering, 2015, Toronto, Canada, IFMBE Proceedings 51, Springer International Publishing, 1562-5
- T Sullivan & P Hansen (2015), “Which drugs, medical procedures and equipment should be funded?”, EcoNZ@Otago 34, 8-12
- T Sullivan & P Hansen (2014), “Determining benefits-related criteria and weights for prioritizing health technologies”, Occasional Report, 14/01, Centre for Health Systems, University of Otago
- O Golan & P Hansen (2012), “Which health technologies should be funded? A prioritization framework based explicitly on value for money”, Israel Journal of Health Policy Research 1, 44 News »
- N Devlin & J Sussex (2011), “Incorporating multiple criteria in HTA. Methods and processes”, OHE Report, Office of Health Economics
- O Golan, P Hansen, G Kaplan & O Tal (2011), “Health technology prioritization: Which criteria for prioritizing new technologies and what are their relative weights?” Health Policy 102, 126-35
- T Sullivan, F Ombler, N Devlin, S Derrett & P Hansen, “A new tool for creating personal and social EQ-5D-5L value sets: provisional results for New Zealand”, conference paper, 35th EuroQol Group Plenary Meeting, Lisbon, Portugal, 2018 (forthcoming)
- T Sullivan, J Ward, P Hansen et al, “A new approach for creating personal and social EQ-5D-5L value sets: provisional results from development and pilot-testing in New Zealand”, poster presentation and ‘brief pitch’, 3rd EuroQol Group Academy Meeting 2018, Budapest, Hungary, 2018 News »