The Impact of Reference Pricing of Nonsteroidal Anti-Inflammatory Agents on the Use and Costs of Analgesic Drugs

Objective. To estimate the effect of reference pricing (RP) of nonsteroidal anti-inflammatory drugs (NSAIDs) on drug subsidy program and beneficiary expenditures on analgesic drugs.
Data Sources/Study Setting. Monthly claims data from Pharmacare, the public drug subsidy program for seniors in British Columbia, Canada, over the period of February 1993 to June 2001.
Study Design. RP limits drug plan reimbursement of interchangeable medicines to a reference price, which is typically equal to the price of the lowest cost interchangeable drug; any cost above that is borne by the patient. Pharmacare introduced two different forms of RP to the NSAIDs, Type 1 in April 1994 and Type 2 in November 1995. Under Type 1 RP, generic and brand versions of the same NSAID are considered interchangeable, whereas under Type 2 RP different NSAIDs are considered interchangeable. We extrapolated average reimbursement per day of NSAID therapy over the months before RP to estimate what expenditures would have been without the policies. These counterfactual predictions were compared with actual values to estimate the impact of the policies; the estimated impacts on reimbursement rates were multiplied by the postpolicy volume of NSAIDS dispensed, which appeared unaffected by the policies, to estimate expenditure changes.
Principal Findings. After Type 2 RP, program expenditures declined by $22.7 million (CAN), or $4 million (CAN), annually cutting expenditure by about half. Most savings accrued from the substitution of low-cost NSAIDs for more costly alternatives. About 20 percent of savings represented expenditures by seniors who elected to pay for partially reimbursed drugs. Type 1 RP produced one-quarter the savings of type 2 RP.
Conclusions. Type 2 RP of NSAIDs achieved its goal of reducing drug expenditures and was more effective than Type 1 RP. The effects of RP on patient health and associated health care costs remain to be investigated.     

The Role of Indication-Based Pricing in Future Pricing and Reimbursement Policies: A Systematic Review

ObjectivesIndication-based pricing (IBP) has received growing attention because of the expected increase in the number of new medicines with multiple indications. In our systematic review, we assess the potential benefits, barriers, current experiences, and future perspectives of different IBP mechanisms.MethodsWe searched publications in English, Spanish, or French assessing the impact, international experience, and future context of IBP systems on PubMed, Scopus, Cochrane, EconLit, American Society of Clinical Oncology, and National Institute for Health Research Health Technology Assessment from 2000 to 2020. This was complemented by a gray literature search in Google Scholar.ResultsA total of 29 publications that specifically addressed the topic of IBP were retained. The most commonly reported benefits of IBP were a better alignment of medicines’ value and price, optimization of research and development incentives and increase of competition, and improvement of patients’ access to treatments. Data collection and proper infrastructures, and the risk of high administrative burden and associated costs, were seen as the main barriers for proper IBP implementation. International experience lacks concrete examples of IBP. A single weighted average price according to volume, value, or a combination of both, appears to be the most used methodology, followed by different confidential net prices per indication. Different brands with distinct price per indication are less common, although it is considered a pure IBP system.ConclusionsEvidence of IBP impact is still scarce, and there is a need for pilot projects and experiences to monitor its real consequences. An appropriate price and reimbursement model for multi-indication medicines should be a priority, but political will and proper data collection systems remain crucial.     

Affordability Challenges to Value-Based Pricing: Mass Diseases,Orphan Diseases,and Cures

Objectives

To analyze how value-based pricing (VBP), which grounds the price paid for pharmaceuticals in their value, can manage “affordability” challenges, defined as drugs that meet cost-effectiveness thresholds but are “unaffordable” within the short-run budget.

Pricing and reimbursement of generic pharmaceuticals in Turkey: Evaluation of hypertension drugs from 2007 to 2013

Purpose

This study was designed to examine the effects of drug pricing and reimbursement politics on drug expenditures from January 2007 to September 2013, with a focus on internal reference pricing in Turkey.

Time Series Analysis on the Impact of Generic Substitution and Reference Pricing on Antipsychotic Costs in Finland

ObjectivesTo analyze the medium- to long-term impact of generic substitution and the reference price system on the daily cost of antipsychotics in Finland. The additional impact of reference pricing over and above previously implemented generic substitution was also assessed.MethodsAn interrupted time series design with a control group and segmented regression analysis was used to estimate the effect of the implementation of generic substitution and the reference price system on the daily cost of antipsychotics. The data have 69 monthly values of the average daily cost for each of the studied antipsychotics: 39 months before and 30 months after the introduction of reference pricing. For one of the studied antipsychotic, the time before the introduction of reference pricing could be further divided into time before and after the introduction of generic substitution.ResultsAccording to the model, 2.5 years after the implementation of reference pricing, the daily cost of the studied antipsychotics was 24.6% to 50.6% lower than it would have been if reference pricing had not been implemented. Two and a half years after the implementation of the reference price system, however, the additional impact of reference pricing over and above previously implemented generic substitution was modest, less than 1 percentage point.ConclusionsAlthough the price competition induced by reference pricing decreased the prices of antipsychotics in Finland in the short-term, the prices had a tendency to stagnate or even to turn in an upward direction in the medium- to long-term. Furthermore, the additional impact of reference pricing over and above previously implemented generic substitution remained quite modest.     

Modeling Clinical Outcomes in Prostate Cancer: Application and Validation of the Discrete Event Simulation Approach

Objectives

Treatment landscape in prostate cancer has changed dramatically with the emergence of new medicines in the past few years. The traditional survival partition model (SPM) cannot accurately predict long-term clinical outcomes because it is limited by its ability to capture the key consequences associated with this changing treatment paradigm. The objective of this study was to introduce and validate a discrete-event simulation (DES) model for prostate cancer.

Mathematical Modeling and Pharmaceutical Pricing: Analyses Used to Inform In-Licensing and Developmental Go/No-Go Decisions

In the face of significant real healthcare cost inflation, pressured budgets, and ongoing launches of myriad technology of uncertain value, payers have formalized new valuation techniques that represent a barrier to entry for drugs. Cost-effectiveness analysis predominates among these methods, which involves differencing a new technological interventions marginal costs and benefits with a comparators, and comparing the resulting ratio to a payers willingness-to-pay threshold. In this paper we describe how firms are able to model the feasible range of future product prices when making in-licensing and developmental Go/No-Go decisions by considering payers use of the cost-effectiveness method. We illustrate this analytic method with a simple deterministic example and then incorporate stochastic assumptions using both analytic and simulation methods. Using this strategic approach, firms may reduce product development and in-licensing risk.The FDA in the United States or the EMEA in Europe. Coverage and reimbursement decision making for new technology entering European markets occurs at the country-level     

Predicting Potential Prevention Effects on Hospital Burden of Nosocomial Infections: A Multistate Modeling Approach

ObjectivesHospital-acquired infections (HAIs) place a substantial burden on health systems. Tools are required to quantify the change in this burden as a result of a preventive intervention. We aim to estimate how much a reduction in the rate of hospital-acquired infections translates into a change in hospital mortality and length of stay.MethodsUsing multistate modelling and competing risks methodology, we created a tool to estimate the reduction in burden after the introduction of a preventive effect on the infection rate. The tool requires as inputs the patients’ length of hospital stay, patients’ infection information (status, time), patients’ final outcome (discharged alive, dead), and a preventive effect. We demonstrated the methods on both simulated data and 3 published data sets from Germany, France, and Spain.ResultsA hypothetical prevention that cuts the infection rate in half would result in 21 lives and 2212 patient-days saved in French ventilator-associated pneumonia data, 61 lives and 3125 patient-days saved in Spanish nosocomial infection data, and 20 lives and 1585 patient-days saved in German nosocomial pneumonia data.ConclusionsOur tool provides a quick and easy means of acquiring an impression of the impact a preventive measure would have on the burden of an infection. The tool requires quantities routinely collected and computation can be done with a calculator. R code is provided for researchers to determine the burden in various settings with various effects. Furthermore, cost data can be used to get the financial benefit of the reduction in burden.     

Value‐Based Differential Pricing: Efficient Prices for Drugs in a Global Context

This paper analyzes pharmaceutical pricing between and within countries to achieve second‐best static and dynamic efficiency. We distinguish countries with and without universal insurance, because insurance undermines patients' price sensitivity, potentially leading to prices above second‐best efficient levels. In countries with universal insurance, if each payer unilaterally sets an incremental cost‐effectiveness ratio (ICER) threshold based on its citizens' willingness‐to‐pay for health; manufacturers price to that ICER threshold; and payers limit reimbursement to patients for whom a drug is cost‐effective at that price and ICER, then the resulting price levels and use within each country and price differentials across countries are roughly consistent with second‐best static and dynamic efficiency. These value‐based prices are expected to differ cross‐nationally with per capita income and be broadly consistent with Ramsey optimal prices. Countries without comprehensive insurance avoid its distorting effects on prices but also lack financial protection and affordability for the poor. Improving pricing efficiency in these self‐pay countries includes improving regulation and consumer information about product quality and enabling firms to price discriminate within and between countries. © 2013 The Authors. Health Economics published by John Wiley & Sons Ltd.     

Budget Impact Analysis of Thrombolysis for Stroke in Spain: A Discrete Event Simulation Model

Objective:  Thrombolysis within the first 3 hours after the onset of symptoms of a stroke has been shown to be a cost-effective treatment because treated patients are 30% more likely than nontreated patients to have no residual disability. The objective of this study was to calculate by means of a discrete event simulation model the budget impact of thrombolysis in Spain.
Methods:  The budget impact analysis was based on stroke incidence rates and the estimation of the prevalence of stroke-related disability in Spain and its translation to hospital and social costs. A discrete event simulation model was constructed to represent the flow of patients with stroke in Spain.
Results:  If 10% of patients with stroke from 2000 to 2015 would receive thrombolytic treatment, the prevalence of dependent patients in 2015 would decrease from 149,953 to 145,922. For the first 6 years, the cost of intervention would surpass the savings. Nevertheless, the number of cases in which patient dependency was avoided would steadily increase, and after 2006 the cost savings would be greater, with a widening difference between the cost of intervention and the cost of nonintervention, until 2015.
Conclusion:  The impact of thrombolysis on society's health and social budget indicates a net benefit after 6 years, and the improvement in health grows continuously. The validation of the model demonstrates the adequacy of the discrete event simulation approach in representing the epidemiology of stroke to calculate the budget impact.     

Congestion Pricing Policies and Safety Implications: a Scoping Review

Congestion pricing policies (CPPs) are a common strategy for addressing urban traffic congestion. Research has explored several impacts of these policies (e.g., air quality, equity, congestion relief). The purpose of this review was to synthesize findings from publications examining CPP impacts on road user safety outcomes. We conducted a systematic search of relevant literature in four large research databases (Transport Research International Documentation, Web of Science, PubMed, and Scopus), searching from database inception through January 2021. We identified 18 eligible publications. Safety-related outcomes included overall crashes and injury crashes with stratification by injury severity and road user type (e.g., bicyclist, pedestrian). A majority of the publications examined zone-based CPPs (n = 13) and used observed data involving real policies (n = 10), as compared to a predicted or simulated analysis. Decreases in overall crashes and injuries for some road users were observed (e.g., car occupants). While some studies estimated short-term increases in injuries and crashes for bicyclists and motorcyclists (likely due to shifts from personal vehicle use to other transportation modes and increased exposure), most analyses focused on longer-term impacts and generally found a reversal and eventual decrease in injuries and crashes after a few years. The relative scarcity of safety outcomes in published literature, along with the wide breadth of CPP types, implementation contexts, and outcomes measured, demonstrates that more research on safety outcomes is needed. Cities and regions planning to implement CPPs should consider potential mode shifts and safety supports for all road users (e.g., bicycle and pedestrian infrastructure).Supplementary InformationThe online version contains supplementary material available at 10.1007/s11524-021-00578-3.     

Economic Evaluation in Opioid Modeling: Systematic Review

ObjectivesThe rapid increase in opioid overdose and opioid use disorder (OUD) over the past 20 years is a complex problem associated with significant economic costs for healthcare systems and society. Simulation models have been developed to capture and identify ways to manage this complexity and to evaluate the potential costs of different strategies to reduce overdoses and OUD. A review of simulation-based economic evaluations is warranted to fully characterize this set of literature.MethodsA systematic review of simulation-based economic evaluation (SBEE) studies in opioid research was initiated by searches in PubMed, EMBASE, and EbscoHOST. Extraction of a predefined set of items and a quality assessment were performed for each study.ResultsThe screening process resulted in 23 SBEE studies ranging by year of publication from 1999 to 2019. Methodological quality of the cost analyses was moderately high. The most frequently evaluated strategies were methadone and buprenorphine maintenance treatments; the only harm reduction strategy explored was naloxone distribution. These strategies were consistently found to be cost-effective, especially naloxone distribution and methadone maintenance. Prevention strategies were limited to abuse-deterrent opioid formulations. Less than half (39%) of analyses adopted a societal perspective in their estimation of costs and effects from an opioid-related intervention. Prevention strategies and studies’ accounting for patient and physician preference, changing costs, or result stratification were largely ignored in these SBEEs.ConclusionThe review shows consistently favorable cost analysis findings for naloxone distribution strategies and opioid agonist treatments and identifies major gaps for future research.     

系统动力学模型在卫生总费用推算中的应用研究

目的:探索系统动力学仿真模型在卫生总费用推算中的应用.方法:依据系统动力学建模原理.采用VensimPLE 5.8b仿真模拟软件建立卫生总费用的系统仿真模型,推算2005-2009年卫生总费用水平并与核算报告值进行对比.结果:系统动力学模型的推算结果优于其他推算方法,非常接近报告值,推算值与报告值的相对平均误差为0.71%.结论:系统动力学模型应用于卫生总费用推算效果良好,可为卫生总费用仿真研究增添一个新工具.     

Modeling the age-of-onset function in segregation analysis: a causal scheme for leprosy

Several methods have been proposed to take into account the variable age of onset of a disease in genetic analysis. A different approach is presented from an etiological point of view. To illustrate the method, we used leprosy, an infectious disease with a variable age of onset depending on both the time of contamination with the bacillus and the latency of the disease; the role of a major gene in the susceptibility to this disease has been recently detected. The age-of-onset function was modeled to account for the two temporal processes: contamination event and incubation period. For genetic analysis, this function was combined with the probability of being susceptible to the disease, which was expressed by the use of regressive models. To test this new approach, ten sets of 500 nuclear families were simulated considering different hypotheses of contamination risks, which were either constant or dependent on contacts with contagious leprosy patients, and varying the extent to which the disease is heritable. Analyses of these data using two versions of the model indicate that the model can detect familial correlations in variable age of onset and discriminate between the different simulated effects.