Value elements and methods of value-based pricing for drugs in Japan: a systematic review

Figures & data

Table 1. Study selection criteria.

Component	Inclusion criteria	Exclusion criteria
Population	Any	NA
Interventions/Comparator	Drugs	Diagnostic agent, vaccine, surgical procedure, medical devices
Outcomes	Estimated price of VBP, value elements, and pricing method	Outcomes are dedicated to decision making of reimbursement and insurance payment Articles that do not describe the details of the pricing method Outcomes estimated only by QALYs and costs in a conventional cost effectiveness analysis approach
Study design	Any (any study related to VBP)	NA
Publication type	Original articles	Review articles, conference report
Publication language	English or Japanese	NA
Publish date	1/1/2017 to 4/30/2022	NA
Country	Any	NA
Publication status	Published	NA

NA, not applicable; QALY, quality-adjusted life year; VBP, value-based pricing.

Figure 1. Flow diagram of the literature selection process.

Table 2. Value elements, method used to quantify value elements and pricing method of the included studies.

Article ID	Value elements	Method used to quantify value elements	Pricing method
Ma et al. [66]	Conventional values elements (cost, care giver time cost, productivity loss, QALYs [patient, caregiver])	-	CEA approach with Markov model was performed for each state of CMT against chemotherapy alone to obtain QALY and cost. NMB of the drug was calculated as (QALY gain x WTP) − cost. *WTP: $100,000/QALY
	Real option value	Real option value was defined as health gains by living longer because of use of the new technology. The value was implemented as mortality data, which included potential mortality reduction from future advances in technologies. In addition, mortality because of increased risk of heart disease or new cancers from the initial cancer treatment were assumed to be reduced because of future technological advances, and the trends in annual incidence-based mortality improvement for lung cancer was used.
	Value of hope	Value of hope was defined as WTP for patient’s life-years because of the prospect of living for an extended period. By referring to a previous study, WTP was estimated as $36,300 for a 1-year increase in survival.
Ten Ham et al. [67]	Conventional values elements (cost, productivity loss, outcomes [LYs, QALYs, Petterson score, bleeds])	–	The CEA approach with a Markov model to simulate different bleeding conditions in hemophilia A was used to obtain QALYs and cost. The marginal value of cost at which Vallox was regarded as cost-effective was calculated as the maximum value-based price. *WTP: €80,000/QALY
Prados et al. [68]	Conventional values elements (cost, productivity loss [patient, caregiver], QALYs)	-	A Markov model was used to simulate the following: 1) prediction of the annual number of people diagnosed with MCI due to AD in the United States; 2) modeling of the progression from MCI to the three stages (mild, moderate, and severe) for both treated and untreated patients (treatment effect was incorporated as a 30% reduction in progression from MCI to mild or mild to moderate); and 3) calculation of the difference in outcomes between the treated and untreated groups. To estimate societal value, the societal monetary value of the drug was estimated by simulated QALYs and cost.
	Severity of disease	Severity of disease severity was embedded in the QALY with the concept that the health gain is more valuable to a patient with a low level of health. It was considered by applying a severity multiplier, which was the ratio of marginal utility of health improvement with respect to base health proposed by Lakdawalla and Phelps [77].
	Insurance value	Financial insurance value was considered by applying the premium load estimated by Brown and Finkelstein [78] to the out-of-pocket components of medical and long-term care costs.Insurance value to the unafflicted was defined as the expected improvement in well-being of the currently unafflicted before the realization of the uncertain health state by calculating the combined future probability of survival and developing MCI due to AD for unafflicted individuals between the ages of 18 and 85. The value was calculated as the lifetime value of the actuarially fair expected private benefit conditional on surviving to that stage and developing the disease and quantified by using the simulation results for forecasted benefits of treatment in terms of increased earnings, value of gains in QALYs adjusted for severity of disease, financial insurance value, and reduced out-of-pocket spending on medical and social care, assuming no costs for the treatment itself.
Reed et al. [69]	Value of hope	Value of hope was defined as dollar-equivalent values of percentage chances of long-term survival. A discrete choice experiment was conducted in cancer patients by using a questionnaire that included questions on the probability of achieving 10-year survival, expected survival rate, health status, and out-of-pocket costs. The experimental results were used for a random utility maximization framework in which the utility value was expressed as the sum of the product of each component and its probability. A mixed logit model was used to analyze the results, and the coefficients of each element were estimated. The price of the value of hope was estimated as the cost of offsetting the utility value at 5%, 10%, and 20% probability of achieving 10-year survival against a 0% probability of achieving 10-year survival.	-
Berkowitz et al. [70]	Conventional values elements (cost [cash flow])	-	A discount cash flow analysis was used to estimate the current value of genetic therapy in nAMD, taking into account the discounted rate and total costs for lifetime treatment with the anti-VEGF drugs aflibercept, ranibizumab, or bevacizumab.
Levaggi et al. [71]	Effectiveness	Effectiveness was defined as the marginal effectiveness in the last patient in the population in the framework; article included an example real-world case study with LYs.	MVBP: In a reimbursement policy where only subgroups with ICER below WTP are treated, firms determine the price to maximize the number of people x profit. The optimal solution that maximizes the company’s profit under such assumptions was estimated as MVBP. AVBP: In a reimbursement policy where the price is determined by multiplying the mean benefit in the treated subgroup by the value per unit, companies determine the population to be treated by maximizing the number of people x profit. Under such assumptions, the optimal solution that maximizes the company’s profit was estimated as AVBP.
Lanitis et al. [72]	Efficacy	Difference in median OS in years multiplied by adjustment factor	A Drug Abacus tool was used to obtain prices by summing the product of each value with a weight representing the importance of that element to the drug price.
	Toxicity	Difference in percentage of grade 3 to 4 adverse events Difference in percentage discontinuing because of adverse events
	Novelty	Mechanism of action relative to current therapy
	Research & Development cost	The number of patients enrolled in approval trial.
	Rarity	Projected incidence of the disease
	Population health burden	Years of life lost annually
	Unmet needs	Existence of licensed treatments
	Prognosis	Median OS in absence of intervention
Lipton et al. [73]	Conventional values elements (cost, productivity loss, QOL [QALYs])	-	CEA approach consisting of the health states of ‘on preventive treatment,’ ‘off preventive treatment,’ and ‘dead’ over a 10-year time horizon was performed with a Markov model. The maximum price at which the drug is considered to be cost-effective relative to its comparators was considered as VBP. *WTP: $100,000–$200,000/QALY

AD, Alzheimer disease; AVBP, average value-based pricing; CEA, cost-effectiveness analysis; CMT, combined modality treatment; LYs, life years; MCC, Merkel cell cancer; MCI, mild cognitive impairment; MVBP, marginal value-based pricing; nAMD; neovascular age-related macular degeneration; NMB, net monetary benefit; OS, overall survival; QALYs, quality-adjusted life years; QOL, quality of life; RCT, randomized controlled trial; VBP, value-based pricing VEGF, vascular endothelial growth factor; WPT, willingness to pay.

Note: Methods used for quantifying broader value elements except quality-adjusted life years, costs and productivity loss were summarized because their methods were already established.

Ma S, Olchanski N, Cohen JT, et al. The impact of broader value elements on cost-effectiveness analysis: two case studies. Value Health. 2022;25(8):1336–1343. doi:10.1016/j.jval.2022.01.025.

 PubMedGoogle Scholar

Ten Ham RMT, Walker SM, Soares MO, et al. Modeling benefits, costs, and affordability of a novel gene therapy in hemophilia a. Hemasphere. 2022;6(2):e679. . doi:10.1097/HS9.0000000000000679

 PubMed Web of Science ®Google Scholar

Prados MJ, Liu Y, Jun H, et al. Projecting the long-term societal value of a disease-modifying treatment for Alzheimer’s disease in the United States. Alzheimers Dement. 2022;18(1):142–151. . doi:10.1002/alz.12578

 PubMed Web of Science ®Google Scholar

Lakdawalla DN, Phelps CE. Health technology assessment with risk aversion in health. J Health Econ. 2020;72:102346. doi: 10.1016/j.jhealeco.2020.102346

 PubMed Web of Science ®Google Scholar

Brown J, Finkelstein A. Insuring long-term care in the United States. J Econ Perspect. 2011;25(4):119–142. doi:10.1257/jep.25.4.119.

 Web of Science ®Google Scholar

Reed SD, Yang JC, Gonzalez JM, et al. Quantifying value of hope. Value Health. 2021;24(10):1511–1519. doi:10.1016/j.jval.2021.04.1284

 PubMed Web of Science ®Google Scholar

Berkowitz ST, Patel S. Value of anti–vascular endothelial growth factor gene therapy for neovascular age-related macular degeneration. Ophthalmology Retina. 2021;5(4):357–364. doi:10.1016/j.oret.2020.08.005.

 PubMedGoogle Scholar

Levaggi R, Pertile P. Which valued-based price when patients are heterogeneous? Health Econ. 2020;29(8):923–935. doi:10.1002/hec.4033.

 PubMed Web of Science ®Google Scholar

Lanitis T, Ambavane A, Zheng Y, et al. Value assessment of immuno-oncology in the treatment of rare tumors in the era of accelerated conditional approvals. Future Oncol. 2019;15(35):4057–4067. doi:10.2217/fon-2019-0456.

 PubMed Web of Science ®Google Scholar

Lipton RB, Brennan A, Palmer S, et al. Estimating the clinical effectiveness and value-based price range of erenumab for the prevention of migraine in patients with prior treatment failures: a US societal perspective. J Med Econ. 2018;21(7):666–675. doi:10.1080/13696998.2018.1457533.

 PubMed Web of Science ®Google Scholar