Beyond cost-effectiveness: A five-step framework for appraising the value of health technologies in Asia-Pacific.
cost-benefit analysis
health economics
health technology assessment
resource allocation
Journal
The International journal of health planning and management
ISSN: 1099-1751
Titre abrégé: Int J Health Plann Manage
Pays: England
ID NLM: 8605825
Informations de publication
Date de publication:
Jan 2020
Jan 2020
Historique:
received:
06
06
2019
accepted:
07
06
2019
pubmed:
11
7
2019
medline:
20
11
2020
entrez:
11
7
2019
Statut:
ppublish
Résumé
Given resource constraints and the potential for increasingly high-cost, cost-effective medicines to become available, policymakers require strategies that go beyond cost-effectiveness when making resource allocation decisions. This manuscript presents a five-step framework that complements traditional health technology assessment (HTA) guidance documents that policymakers in Asia-Pacific and elsewhere may consider when setting up HTA guidelines and/or evaluating whether or not to subsidize a medicine or other health innovations. The framework recommends that subsidy decisions be based on five criteria: the relative burden of the condition as compared with other conditions (step 1), comparative and cost-effectiveness of the medicine (steps 2 and 3), the short-term impact on the budget (step 4), and other considerations including patient and societal preferences (step 5). Our approach, which is a complement to traditional HTA guidance documents, is not prescriptive but provides an evidence-based framework that HTA agencies in Asia-Pacific can follow as they aim to deliver value-based medicines to their constituents.
Types de publication
Journal Article
Langues
eng
Pagination
397-408Subventions
Organisme : Duke-NUS Medical School
Informations de copyright
© 2019 John Wiley & Sons, Ltd.
Références
OECD/WHO. Health at a Glance: Asia/Pacific 2016. Paris: OECD Publishing; 2016.
OECD/WHO. Health at a Glance: Asia/Pacific 2014. Paris: OECD Publishing; 2014.
Sivalal S. Health technology assessment in Malaysia. Int J Technol Assess Health Care. 2009;25(Suppl 1):224-230.
Tuan QK. Health technology and its application in Vietnam. News Across Asia. 2017.
De Rosas-Valera M. Health technology assessment in the Philippines. Int J Technol Assess Health Care. 2009;25(Suppl 1):231-233.
Kennedy-Martin T, Mitchell BD, Boye KS, et al. The health technology assessment environment in Mainland China, Japan, South Korea, and Taiwan-implications for the evaluation of diabetes mellitus therapies. Value Health Reg Issues. 2014;3(Supplement C):108-116.
Prinja S, Downey LE, Gauba VK, Swaminathan S. Health technology assessment for policy making in India: current scenario and way forward. PharmacoEcon - Open. 2018;2(1):1-3.
Murray CJ. Quantifying the burden of disease: the technical basis for disability-adjusted life years. Bull World Health Organ. 1994;72(3):429-445.
GBD results tool [internet]. IHME, University of Washington. 2016 [cited 9 Sep 2017]. Available from: http://ghdx.healthdata.org/gbd-results-tool.
Youn SW, Tsai TF, Theng C, et al. The MARCOPOLO study of Ustekinumab utilization and efficacy in a real-world setting: treatment of patients with plaque psoriasis in Asia-Pacific countries. Annals Dermatol. 2016;28(2):222-231.
The Cochrane Collaboration. A network meta-analysis (NMA) toolkit 2018 [Available from: http://training.cochrane.org/resource/network-meta-analysis-nma-toolkit.
Wang K-L, Lip GYH, Lin S-J, Chiang C-E. Non-vitamin K antagonist oral anticoagulants for stroke prevention in Asian patients with nonvalvular atrial fibrillation. Stroke. 2015;46(9):2555-2561.
Tangamornsuksan W, Chaiyakunapruk N, Somkrua R, Lohitnavy M, Tassaneeyakul W. Relationship between the hla-b*1502 allele and carbamazepine-induced Stevens-Johnson syndrome and toxic epidermal necrolysis: a systematic review and meta-analysis. JAMA Dermatol. 2013;149(9):1025-1032.
Finkelstein EA, Kruger E. Meta- and cost-effectiveness analysis of commercial weight loss strategies. Obesity (Silver Spring, Md). 2014;22(9):1942-1951.
Kularatna S, Whitty JA, Johnson NW, Scuffham PA. Health state valuation in low- and middle-income countries: a systematic review of the literature. Value Health. 2013;16(6):1091-1099.
Xie F, Gaebel K, Perampaladas K, Doble B, Pullenayegum E. Comparing EQ-5D valuation studies: a systematic review and methodological reporting checklist. Med Decis Making. 2014;34(1):8-20.
Wong ELY, Ramos-Goni JM, Cheung AWL, Wong AYK, Rivero-Arias O. Assessing the use of a feedback module to model EQ-5D-5L health states values in Hong Kong. Patient. 2018;11(2):235-247.
Yusof FA, Goh A, Azmi S. Estimating an EQ-5D value set for Malaysia using time trade-off and visual analogue scale methods. Value Health. 2012;15(1 Suppl):S85-S90.
Liu GG, Wu H, Li M, Gao C, Luo N. Chinese time trade-off values for EQ-5D health states. Value Health. 2014;17(5):597-604.
Luo N, Liu G, Li M, Guan H, Jin X, Rand-Hendriksen K. Estimating an EQ-5D-5L value set for China. Value Health. 2017;20(4):662-669.
Purba FD, Hunfeld JAM, Iskandarsyah A, et al. The Indonesian EQ-5D-5L value set. Pharmacoeconomics. 2017;35(11):1153-1165.
Lee HY, Hung MC, Hu FC, Chang YY, Hsieh CL, Wang JD. Estimating quality weights for EQ-5D (EuroQol-5 dimensions) health states with the time trade-off method in Taiwan. J Formos Med Assoc. 2013;112(11):699-706.
Ramsey S, Willke R, Briggs A, et al. Good research practices for cost-effectiveness analysis alongside clinical trials: the ISPOR RCT-CEA task force report. Value Health. 2005;8(5):521-533.
World Health Organization. Health financing strategy for the Asia Pacific region (2010-2015): WHO Regional Office for South-East Asia. 2009.
Praditsitthikorn N, Teerawattananon Y, Tantivess S, et al. Economic evaluation of policy options for prevention and control of cervical cancer in Thailand. Pharmacoeconomics. 2011;29(9):781-806.
Zhang S, Bastian ND, Griffin PM. Cost-effectiveness of sofosbuvir-based treatments for chronic hepatitis C in the US. BMC Gastroenterol. 2015;15(1):98.
Stahmeyer JT, Rossol S, Liersch S, Guerra I, Krauth C. Cost-effectiveness of treating hepatitis C with sofosbuvir/ledipasvir in Germany. PLoS ONE. 2017;12(1):e0169401.
Aggarwal R, Chen Q, Goel A, et al. Cost-effectiveness of hepatitis C treatment using generic direct-acting antivirals available in India. PLoS ONE. 2017;12(5):e0176503.
Anothaisintawee T, Attia J, Nickel JC, et al. Management of chronic prostatitis/chronic pelvic pain syndrome: a systematic review and network meta-analysis. JAMA. 2011;305(1):78-86.
Downey L, Rao N, Guinness L, et al. Identification of publicly available data sources to inform the conduct of health technology assessment in India. F1000Research. 2018;7:245.
Koh L, Glaetzer C, Chuen Li S, Zhang M. Health technology assessment, international reference pricing, and budget control tools from China's perspective: what are the current developments and future considerations? Value Health Reg Issues. 2016;9:15-21.
Agency for Care Effectiveness. Drug Evaluation Methods and Process Guide. Singapore: Ministry of Health, Singapore; 2018 Feb 5, 2018.
Riewpaiboon A. Measurement of costs for health economic evaluation. J Med Assoc Thai. 2014;97(Suppl 5):S17-S26.
Torrance GW, Thomas WH, Sackett DL. A utility maximization model for evaluation of health care programs. Health Serv Res. 1972;7(2):118-133.
Torrance GW. Social preferences for health states: an empirical evaluation of three measurement techniques. Socioecon Plann Sci. 1976;10(3):129-136.
Brooks R. EuroQol: the current state of play. Health Policy. 1996;37(1):53-72.
Brazier JE, Roberts J. The estimation of a preference-based measure of health from the SF-12. Med Care. 2004;42(9):851-859.
Feeny D, Furlong W, Torrance GW, et al. Multiattribute and single-attribute utility functions for the health utilities index mark 3 system. Med Care. 2002;40(2):113-128.
Lorgelly PK, Doble B, Rowen D, Brazier J. Condition-specific or generic preference-based measures in oncology? A comparison of the EORTC-8D and the EQ-5D-3L. Qual Life Res. 2017;26(5):1163-1176.
Permsuwan U, Guntawongwan KPB. Handling time in economic evaluation studies. J Med Assoc Thai. 2014;97(5):50-58.
Gold MR, Siegel JE, Russell LB, Weinstein MC. Cost-Effectiveness in Health and Medicine: Report of the Panel on Cost-Effectiveness in Health and Medicine. 2nd ed. New York: Oxford University Press; 1996.
Neumann PJ, Sanders GD, Russell LB, Siegel JE, Ganiats TG. Cost-Effectiveness in Health and Medicine. 2nd ed. New York: Oxford University Press; 2016.
Schwarzer R, Rochau U, Saverno K, et al. Systematic overview of cost-effectiveness thresholds in ten countries across four continents. J Comp Eff Res. 2015;4(5):485-504.
McCabe C, Claxton K, Culyer AJ. The NICE cost-effectiveness threshold: what it is and what that means. Pharmacoeconomics. 2008;26(9):733-744.
Vallejo-Torres L, Garcia-Lorenzo B, Castilla I, et al. On the estimation of the cost-effectiveness threshold: why, what, how? Value Health. 2016;19(5):558-566.
Claxton K, Sculpher M, Palmer S, Culyer AJ. Causes for concern: is NICE failing to uphold its responsibilities to all NHS patients? Health Econ. 2015;24(1):1-7.
World Health Organization. Choosing interventions that are cost-effective Geneva 2018 [Available from: http://www.who.int/choice/en/].
Bae EY, Lee EK. Pharmacoeconomic guidelines and their implementation in the positive list system in South Korea. Value Health. 2009;12:S36-S41.
Cole A, Marsden G, Devlin N, Grainger D, Lee EK, Oortwijn W, editors. “New age” decision making in HTA: is it applicable in Asia? HTAi conference panel session; 2016; Tokyo.
Sullivan SD, Mauskopf JA, Augustovski F, et al. Budget impact analysis-principles of good practice: report of the ISPOR 2012 Budget Impact Analysis Good Practice II Task Force. Value Health. 2014;17(1):5-14.
Wang H, Sun Q, Vitry A, Nguyen TA. Availability, price, and affordability of selected essential medicines for chronic diseases in 11 countries of the Asia Pacific region: a secondary analysis. Asia Pac J Public Health. 2017;29(4):268-277.
NICE, England N. Proposals for changes to the arrangements for evaluating and funding drugs and other health technologies appraised through NICE's technology appraisal and highly specialised technologies programmes. London; 2016 13 Oct.
Ciarametaro M, Abedi S, Sohn A, Ge CF, Odedara N, Dubois R. Concerns around budget impact thresholds: not all drugs are the same. Value Health. 2017;20(2):230-233.
Guimarães C, Marra CA, Gill S, et al. A discrete choice experiment evaluation of patients' preferences for different risk, benefit, and delivery attributes of insulin therapy for diabetes management. Patient Prefer Adherence. 2010;4:433-440.
Ozdemir S, Wong TT, Allingham RR, Finkelstein EA. Predicted patient demand for a new delivery system for glaucoma medicine. Medicine. 2017;96(15):e6626.
Johnson FR, Özdemir S, Manjunath R, Hauber AB, Burch SP, Thompson TR. Factors that affect adherence to bipolar disorder treatments: a stated-preference approach. Med Care. 2007;45(6):545-552.
Johnson FR, Van Houtven G, Özdemir S, et al. Multiple sclerosis patients-benefit-risk preferences: serious adverse event risks versus treatment efficacy. J Neurol. 2009;256(4):554-562.
Center for Devices and Radiological Health. Patient preference information-voluntary submission, review in premarket approval applications, humanitarian device exemption applications, and de novo requests, and inclusion in decision summaries and device labeling. US Food Drug Admin. 2016 24 August [Available from: https://www.fda.gov/media/92593/download].
NICE Given Grant to Research Patient Preference [Press Release]. London: Cancer Research UK; 2016.
HITAP. Patient involvement on HTA. HITAP; 2017.
Chim L, Salkeld G, Kelly P, Lipworth W, Hughes DA, Stockler MR. Societal perspective on access to publicly subsidised medicines: a cross sectional survey of 3080 adults in Australia. PLoS ONE. 2017;12(3):e0172971.
Shiroiwa T, Saito S, Shimozuma K, Kodama S, Noto S, Fukuda T. Societal preferences for interventions with the same efficiency: assessment and application to decision making. Appl Health Econ Health Policy. 2016;14(3):375-385.
Green C. Investigating public preferences on ‘severity of health' as a relevant condition for setting healthcare priorities. Soc Sci Med. 2009;68(12):2247-2255.