The impacts of government reimbursement negotiation on targeted anticancer medication price, volume and spending in China

IntroductionNew targeted therapies have changed cancer treatment in the past decades. However, high prices of targeted anticancer medications have increased economic burden for both patients and health insurance systems. In July 2017, China implemented combined medication price negotiation and mandatory reimbursement policies for 15 targeted anticancer medications. This study assesses effects of the policy on hospital procurement prices, volumes and spending.MethodsUsing a quasi-experimental interrupted time series design, we analysed procurement data from the Chinese Medical Economic Information of 789 public hospitals in 30 provinces between January 2016 and September 2018. The intervention group consisted of 15 targeted anticancer medications with negotiated prices in 2017. The comparison group consisted of six targeted anticancer medications without negotiated prices by 2018. The effective date of the policy was September 2017.ResultsAfter the implementation of the 2017 medication price negotiation and reimbursement policy, cost per defined daily dose (DDD) of the 15 targeted anticancer medications dropped US$71.21 on average from an average US$169.24/DDD before (p=0.000). Compared with what would have happened without the intervention, cost/DDD of price-negotiated medications decreased by 48.9% (p=0.000), procurement volumes increased by 143.0% (p=0.000) and hospital medication spending decreased by 6.9% (p=0.146).ConclusionsThe 2017 medication price negotiation and reimbursement policy decreased targeted medication procurement costs per DDD, increased volumes procured and at least temporarily contained spending. These changes should result in better access to and affordability of targeted anticancer medications in China.

The Profitability of Revenue-Based Quotas Under Price Negotiation

We study how the presence of a monthly revenue-based quota impacts a retailer’s profits when prices are negotiated by a salesperson. Using transaction level data for refrigerators, we first provide reduced-form evidence that prices are impacted by the quota: the negotiated discounts are approximately 3.8% higher if the salesperson is 10% closer to reaching the quota in the final week of the month. Guided by this result, we specify and estimate a demand model that identifies the impact of the quota through two forces: the effort salespeople expend in order to sell the product and their bargaining position. Results indicate that, as salespeople get closer to reaching their quota, their effort increases regardless of the week, and their bargaining position weakens (i.e., they offer lower prices), but only in the final week of the month. We use these results to analyze the impact of the quota and find that, holding salespeoples’ total compensation fixed, eliminating quotas results in 8% lower profit for the retailer. This decrease stems primarily from the reduction in effort that outweighs any benefit from strengthening the salespeoples’ bargaining position. The change in profit is economically meaningful because eliminating both price negotiation (i.e., moving to fixed pricing) and the quota results in an up to 36% reduction in profit. This paper was accepted by Matthew Shum, marketing.

Price Negotiation with Merchant Heterogeneity in the Payment Card Industry

We examine price negotiation in the payment card industry by exploiting a unique merchant-, industry-, and city-level dataset. Motivated by the substantial variation in acquirer fees and the heterogeneous merchant card transactions, we use Nash bargaining to model the negotiation over the acquirer fee between an acquirer and a merchant. We find that the merchants secure a larger incremental surplus than the acquirer on average. Moreover, merchants might face upward pressure on acquirer fees as the card penetration rate rises over time, and policies that weaken the acquirer's bargaining power could relieve the upward fee pressure.

Supplier Replacement Model in a One-Level Assembly System under Lead-Time Uncertainty

Supplier selection/replacement strategies, purchasing price negotiation and optimized replenishment policies play a key role in efficient supply chain management in today’s dynamic market. Their importance increases even more in Industry 4.0. In this paper, we propose a joint model of replenishment planning and purchasing price negotiation in the context of supplier replacement in a one-level assembly system (OLAS) producing one type of finished product. The real component lead times are stochastic. There is consequently a non-negligible risk that the assembly process may be stopped if all components for assembly are not delivered on the due date. This incurs inventory-related costs, holding and backlogging, which should be minimized. We consider a set of suppliers characterized by their prices and the probability distributions of their lead-times, and we present a model and an approach that optimize not only replenishment policy, but also purchasing prices. For a given unit, it is possible to model several alternative suppliers with alternative pricing and lead-time uncertainties, and evaluate their impacts on the total cost: composed of holding, backlogging and purchasing costs for the assembly system. The findings of this study indicate that it can be beneficial to pay suppliers an additional purchase cost in order to reduce the holding and backlogging costs related to uncertainty. In consequence, decision makers can use the proposed approach to negotiate prices and delivery delays or to select suppliers.