Inform Reimbursement Decisions Research Articles

MT10 Coverage With Evidence Development as a Potential Solution for the Reimbursement of Digital Therapeutics (DTx)? A Systematic Review of Pathways to Inform Reimbursement Decisions in Major European Healthcare Systems

MT10 Coverage With Evidence Development as a Potential Solution for the Reimbursement of Digital Therapeutics (DTx)? A Systematic Review of Pathways to Inform Reimbursement Decisions in Major European Healthcare Systems

Healthcare resource utilisation and direct medical cost for individuals with 5q spinal muscular atrophy in Sweden.

Spinal muscular atrophy (SMA) is a rare, progressive, neuromuscular disorder. Recent advances in treatment require an updated assessment of burden to inform reimbursement decisions. To quantify healthcare resource utilisation (HCRU) and cost of care for patients with SMA. Cohort study of patients with SMA identified in the Swedish National Patient Registry (2007-2018), matched to a reference cohort grouped into four SMA types (1, 2, 3, unspecified adult onset [UAO]). HCRU included inpatient admissions, outpatient visits, procedures, and dispensed medications. Direct medical costs were estimated by multiplying HCRU by respective unit costs. Average annual HCRU and medical costs were modelled for SMA versus reference cohorts to estimate differences attributable to the disease (i.e., average treatment effect estimand). The trajectory of direct costs over time were assessed using synthetic cohorts. We identified 290 SMA patients. Annualised HCRU was higher in SMA patients compared with reference cohorts. Highest risk ratios were observed for inpatient overnight stays for type 1 (risk ratio [RR]: 29.2; 95% confidence interval [CI]: 16.0, 53.5) and type 2 (RR: 23.3; 95% CI: 16.4,33.1). Mean annual direct medical costs per patient for each year since first diagnosis were greatest for type 1 (€114,185 and SMA-attributable: €113,380), type 2 (€61,876 and SMA-attributable: €61,237), type 3 (€45,518 and SMA-attributable: €44,556), and UAO (€4046 and SMA-attributable: €2098). Costs were greatest in the 2-3years after the first diagnosis for all types. The economic burden attributable to SMA is significant. Further research is needed to understand the burden in other European countries and the impact of new treatments.

Drivers and recent trends of hospitalisation costs related to acute pulmonary embolism.

The socio-economic burden imposed by acute pulmonary embolism (PE) on European healthcare systems is largely unknown. We sought to determine temporal trends and identify cost drivers of hospitalisation for PE in Germany. We analysed the totality of reimbursed hospitalisation costs in Germany (G-DRG system) in the years 2016-2020. Overall, 484 884 PE hospitalisations were coded in this period. Direct hospital costs amounted to a median of 3572 (IQR, 2804 to 5869) euros, resulting in average total reimbursements of 710 million euros annually. Age, PE severity, comorbidities and in-hospital (particularly bleeding) complications were identified by multivariable logistic regression as significant cost drivers. Use of catheter-directed therapy (CDT) constantly increased (annual change in the absolute proportion of hospitalisations with CDT + 0.40% [95% CI + 0.32% to + 0.47%]; P < 0.001), and it more than doubled in the group of patients with severe PE (28% of the entire population) over time. Although CDT use was overall associated with increased hospitalisation costs, this association was no longer present (adjusted OR 1.02 [0.80-1.31]) in patients with severe PE and shock; this was related, at least in part, to a reduction in the median length of hospital stay (for 14.0 to 8.0days). We identified current and emerging cost drivers of hospitalisation for PE, focusing on severe disease and intermediate/high risk of an adverse early outcome. The present study may inform reimbursement decisions by policymakers and help to guide future health economic analysis of advanced treatment options for patients with PE.

Modelling costs of interventional pulmonary embolism treatment: implications of US trends for a European healthcare system.

Catheter-directed treatment (CDT) of acute pulmonary embolism (PE) is entering a growth phase in Europe following a steady increase in the USA in the past decade, but the potential economic impact on European healthcare systems remains unknown. We built two statistical models for the monthly trend of proportion of CDT among patients with severe (intermediate- or high-risk) PE in the USA. The conservative model was based on admission data from the National Inpatient Sample (NIS) 2016-20 and the model reflecting increasing access to advanced treatment from the PERT™ national quality assurance database registry 2018-21. By applying these models to the forecast of annual PE-related hospitalizations in Germany, we calculated the annual number of severe PE cases and the expected increase in CDT use for the period 2025-30. The NIS-based model yielded a slow increase, reaching 3.1% (95% confidence interval 3.0-3.2%) among all hospitalizations with PE in 2030; in the PERT-based model, increase would be steeper, reaching 8.7% (8.3-9.2%). Based on current reimbursement rates, we estimated an increase of annual costs for PE-related hospitalizations in Germany ranging from 15.3 to 49.8 million euros by 2030. This calculation does not account for potential cost savings, including those from reduced length of hospital stay. Our approach and results, which may be adapted to other European healthcare systems, provide a benchmark for healthcare costs expected to result from CDT. Data from ongoing trials on clinical benefits and cost savings are needed to determine cost-effectiveness and inform reimbursement decisions.

HTA5 Variation in Health Technology Assessments for Nivolumab Plus Chemotherapy Vs Chemotherapy in First-Line Gastric Cancer

Health technology assessments (HTAs) inform reimbursement decisions. International differences in HTA processes lead to international differences in patient access to new treatments. Using HTAs for nivolumab plus chemotherapy in first-line gastric cancer as an example, we quantified the variation in time to patient access and in the evaluation of benefits between different HTA agencies.

EE40 Identifying and Quantifying Elements of Value for Nivolumab and Ipilimumab in First-Line Non-Small Cell Lung Cancer

Cost-effectiveness analyses are often used by health technology appraisal agencies to inform reimbursement decisions for new therapies. These evaluations, however, are often performed adopting a payer’s perspective that does not include important elements of value that treatments may generate (e.g., increased productivity, reduced caregiving costs, patients’ hope, option value, or insurance value). There is currently limited evidence quantifying condition-specific novel value elements.

Comprehensive Review of Methods to Assess Uncertainty in Health Economic Evaluations

Uncertainty assessment is a cornerstone in model-based health economic evaluations (HEEs) that inform reimbursement decisions. No comprehensive overview of available uncertainty assessment methods currently exists. We aimed to review methods for uncertainty assessment for use in model-based HEEs, by conducting a snowballing review. We categorised all methods according to their stage of use relating to uncertainty assessment (identification, analysis, communication). Additionally, we classified identification methods according to sources of uncertainty, and subdivided analysis and communication methods according to their purpose. The review identified a total of 80 uncertainty methods: 30 identification, 28 analysis, and 22 communication methods. Uncertainty identification methods exist to address uncertainty from different sources. Most identification methods were developed with the objective to assess related concepts such as validity, model quality, and relevance. Almost all uncertainty analysis and communication methods required uncertainty to be quantified and inclusion of uncertainties in probabilistic analysis. Our review can help analysts and decision makers in selecting uncertainty assessment methods according to their aim and purpose of the assessment. We noted a need for further clarification of terminology and guidance on the use of (combinations of) methods to identify uncertainty and related concepts such as validity and quality. A key finding is that uncertainty assessment relies heavily on quantification, which may necessitate increased use of expert elicitation and/or the development of methods to assess unquantified uncertainty.

Best practices in designing preapproval information engagements for US health care decision makers.

As high-cost and innovative therapies continue to enter the market, health care decision makers (HCDMs) are expressing a need for early information on a product's clinical and economic impacts. Preapproval information exchange (PIE) fulfills these data needs by allowing manufacturers to share drug information with HCDMs prior to US Food and Drug Administration approval. With recent regulatory milestones, such as the Pre-approval Information Exchange Act of 2022, HCDMs look to leverage PIE to forecast budgets and inform reimbursement decisions. However, a lack of stakeholder alignment has challenged the evolving applications of PIE. In addition, manufacturers are still seeking regulatory clarity regarding best practices, and many are developing their own policies for content dissemination. Varying practices have led to heterogeneity of preapproval communications across manufacturers, which may not fully align with HCDM needs and interests. However, recently collected survey data from FormularyDecisions, which focused on HCDM perceptions of both PIE webinars and other formats of PIE (eg, PIE decks and dossiers), indicate that HCDMs have strong preferences regarding the timing and content shared in preapproval engagements. Additionally, product indication and clinical trial information are highly valued, and although desired by HCDMs in other studies, in FormularyDecisions survey data, exact pricing data do not currently appear to be a critical component of PIE. Preapproval communications are expected less than 1 year before anticipated product approval, and PIE webinars, specifically, should prioritize therapeutic areas and products anticipated to have a significant impact on organizational budgets. Although HCDMs prefer nonmanufacturer representatives for PIE webinars and virtual presentations, health outcome liaisons or medical science liaisons are ideal among manufacturer representatives for in-person preapproval engagements. The expectations of HCDMs should be considered as manufacturers establish PIE practices to ensure the exchange of quality and relevant information. DISCLOSURES: This study was funded by Xcenda. Dr Dodda, Dr Bannister, Dr Hydery, Ms Gorey, Ms Dunlap, and Dr Mody report personal fees from Xcenda during the conduct of the study.

EE488 How Is Real-World Data Used in Health Technology Assessments to Inform Reimbursement Decisions for Multiple Sclerosis Drugs? A European Perspective

EE488 How Is Real-World Data Used in Health Technology Assessments to Inform Reimbursement Decisions for Multiple Sclerosis Drugs? A European Perspective

Two-stage matching-adjusted indirect comparison

BackgroundAnchored covariate-adjusted indirect comparisons inform reimbursement decisions where there are no head-to-head trials between the treatments of interest, there is a common comparator arm shared by the studies, and there are patient-level data limitations. Matching-adjusted indirect comparison (MAIC), based on propensity score weighting, is the most widely used covariate-adjusted indirect comparison method in health technology assessment. MAIC has poor precision and is inefficient when the effective sample size after weighting is small.MethodsA modular extension to MAIC, termed two-stage matching-adjusted indirect comparison (2SMAIC), is proposed. This uses two parametric models. One estimates the treatment assignment mechanism in the study with individual patient data (IPD), the other estimates the trial assignment mechanism. The first model produces inverse probability weights that are combined with the odds weights produced by the second model. The resulting weights seek to balance covariates between treatment arms and across studies. A simulation study provides proof-of-principle in an indirect comparison performed across two randomized trials. Nevertheless, 2SMAIC can be applied in situations where the IPD trial is observational, by including potential confounders in the treatment assignment model. The simulation study also explores the use of weight truncation in combination with MAIC for the first time.ResultsDespite enforcing randomization and knowing the true treatment assignment mechanism in the IPD trial, 2SMAIC yields improved precision and efficiency with respect to MAIC in all scenarios, while maintaining similarly low levels of bias. The two-stage approach is effective when sample sizes in the IPD trial are low, as it controls for chance imbalances in prognostic baseline covariates between study arms. It is not as effective when overlap between the trials’ target populations is poor and the extremity of the weights is high. In these scenarios, truncation leads to substantial precision and efficiency gains but induces considerable bias. The combination of a two-stage approach with truncation produces the highest precision and efficiency improvements.ConclusionsTwo-stage approaches to MAIC can increase precision and efficiency with respect to the standard approach by adjusting for empirical imbalances in prognostic covariates in the IPD trial. Further modules could be incorporated for additional variance reduction or to account for missingness and non-compliance in the IPD trial.

P69 Enabling Data Privacy in Health Economic Microsimulation Models by Using Subject-Level Synthetic Data

Health economic microsimulation models, that directly utilize subject-level data to inform reimbursement decisions, are increasingly replacing the more traditional cohort models that utilize summary data only. Sharing such microsimulation with, for example, HTA bodies requires careful attention to data privacy and security in order to protect personal information. This study aimed to explore the potential of an alternative solution which minimizes privacy risk: synthetic subject-level data, which mimics actual data, but holds no sensitive subject information.

POSA95 Exploring the Role of Response to Treatment in Oncology Technology Appraisals

Expedited access programmes for new anticancer medicines have increased the reliance on early-phase clinical trials to inform reimbursement decisions in HTA bodies such as the National Institute for Health and Care Excellence (NICE). Early-phase trials lack mature data on overall survival (OS) and other time-to-event endpoints commonly used to inform economic modelling. The result is increased uncertainty in cost-effectiveness estimates. Early-phase oncology trials are often powered on response endpoints however, therefore the Objectives: of this study are to assess the prevalence of response in clinical trials used in NICE cancer technology appraisals (TAs), and how response is incorporated in economic modelling.

1165P Modelling long-term survival outcomes in patients with stage (stg) IB–IIIA EGFR-mutated NSCLC from the ADAURA trial

∼30% of patients (pts) with NSCLC present with resectable disease. In the ADAURA trial (NCT02511106), there was a significant disease-free survival (DFS) benefit with osimertinib vs placebo (PBO) in pts with completely resected stg IB–IIIA EGFRm NSCLC (hazard ratio [HR] 0.20 [adjusted 99.12% CI 0.14, 0.30], p<0.001; 11% and 46% maturity for osimertinib and PBO, respectively); overall survival (OS) data were immature (29 pts died: osimertinib n=9/339, PBO n=20/343). Payers require estimates on survival benefits of novel oncology treatments to inform reimbursement decisions.

Real-world outcomes associated with new cancer medicines approved by the Food and Drug Administration and European Medicines Agency: A retrospective cohort study

PurposeReal-World Data (RWD) studies are increasingly used to support regulatory approvals, reimbursement decisions, and changes in clinical practice for novel cancer drugs. However, few studies have systematically appraised their quality or compared outcomes to pivotal trials. MethodsAll RWD studies (2010–2019) for drugs approved by the Food and Drug Administration (FDA) and European Medicines Agency (EMA) from 2010 to 2015 for solid organ tumours in the non-curative setting were identified. Quality assessment was undertaken using the Newcastle Ottawa Scale. Survival differences between each RWD study and the pivotal trial were determined using a related sample Wilcoxon signed-rank test. Results293 RWD studies for 45 of the 57 drug indications approved by the FDA/EMA were identified. The most common tumour types were prostate cancer (29%, n = 86) and melanoma (15%, n = 43). A quarter of the studies had industry funding. No high-quality studies were identified, and 78% were low quality. Comparative survival analysis between RWD and pivotal trials was possible for 224 studies (37 drug indications). Differences in median survival between the RWD studies and their corresponding trial ranged from −32 months to 21 months (IQR –4·2 months to 1·6 months). Low-quality studies were more likely to report superior survival outcomes (23%) compared to higher quality studies (8%) (p = 0.02). ConclusionRWD study quality for novel cancer drugs is low and of insufficient rigour to inform reimbursement decisions and clinical practice. RWD studies seeking publication should provide a completed quality assessment tool on submission. Greater investment in properly designed RWD studies is required.

PCN181 Real-World Evidence (RWE) in Reimbursement, Pricing, and Health Technology Assessment (HTA) in ASIA. How CAN Rwe Supplement Trial DATA in Oncology Indications in a Premarketing Setting?

RWE is commonly used for postmarketing purposes and has established guidance in many Asian countries, particularly to examine budget impact and long-term safety. Using RWE in a premarketing setting is less established and this study investigates the use of RWE alongside clinical development to inform reimbursement decisions for oncology indications in Asia.

A Review of Web-Based Tools for Value-of-Information Analysis.

Value-of-information analysis (VOI) is a decision-theoretic approach that is used to inform reimbursement decisions, optimise trial design and set research priorities. The application of VOI analysis for informing policy decisions in practice has been limited due, in part, to the perceived complexity associated with the calculation of VOI measures. Recent efforts have resulted in the development of efficient methods to estimate VOI measures and the development of user-friendly web-based tools to facilitate VOI calculations. We review the existing web-based tools including Sheffield Accelerated Value of Information (SAVI), the web interface to the BCEA (Bayesian Cost-Effectiveness Analysis) R package (BCEAweb), Rapid Assessment of Need for Evidence (RANE), and Value of Information for Cardiovascular Trials and Other Comparative Research (VICTOR). We describe what each tool is designed to do, the inputs they require, and the outputs they produce. Finally, we discuss how tools for VOI calculations might be improved in the future to facilitate the use of VOI analysis in practice.

Prevalence of Immature Survival Data for Anti-Cancer Drugs Presented to the National Institute for Health and Care Excellence and Impact on Decision Making

ObjectivesThis research aims to explore how often the National Institute for Health and Care Excellence (NICE) uses immature overall survival data to inform reimbursement decisions on cancer treatments, and the implications of this for resource allocation decisions. MethodsNICE cancer technology appraisals published between 2015 and 2017 were reviewed to determine the prevalence of using immature survival data. A case study was used to demonstrate the potential impact of basing decisions on immature data. The economic model submitted by the company was reconstructed and was populated first using survival data available at the time of the appraisal, and then using data from an updated data cut published after the appraisal concluded. The incremental cost-effectiveness ratios (ICERs) obtained using the different data cuts were compared. Probabilistic sensitivity analysis was undertaken and expected value of perfect information estimated. ResultsForty-one percent of NICE cancer technology appraisals used immature data to inform reimbursement decisions. In the case study, NICE gave a positive recommendation for a limited patient subgroup, with ICERs too high in the complete patient population. ICERs were dramatically lower when the final data cut was used, irrespective of the parametric model used to model survival. Probabilistic sensitivity analysis and expected value of perfect information may not have fully characterized uncertainty, because as they did not account for structural uncertainty. ConclusionAnalyses of cancer treatments using immature survival data may result in incorrect estimates of survival benefit and cost-effectiveness, potentially leading to inappropriate funding decisions. This research highlights the importance of revisiting past decisions when updated data cuts become available.

PPM5 Health Technology Assessment and Companion Diagnostics: A Review of Submissions to the Ncpe from 2012-2019

Health Technology Assessment (HTA) involves the evaluation of all relevant aspects of a health technology and can be used to inform reimbursement decisions. A companion diagnostic (CDx) is an in-vitro diagnostic test that is essential for the safe and effective use of a corresponding medicinal product. Aspects of the CDx’s performance, such as specificity, can impact the outcome of a HTA and should be investigated as part of an evaluation. However, in Ireland little is known about the proportion of HTAs for drugs that are associated with CDx. Our aim is to evaluate submissions to a national HTA agency that are associated with CDx use, and analyse trends over time. We conducted a retrospective analysis of all Rapid Reviews (RRs) commissioned at the National Centre for Pharmacoeconomics (NCPE) from 2012 to 2019, inclusive. For each RR, data was collected on the licensed indication under assessment and if a CDx, as defined by EU regulation, was required. For those associated with CDx use, additional information was collected to further characterize the submissions. A total of 392 RRs were submitted to the NCPE between 2012 and 2019. Of these, 20.7% were associated with a CDx. Over time, the proportion of RRs associated with a CDx increased from 18.5% in 2012 to 32.8% in 2019. The majority of RRs associated with CDX were for cancer drugs (67.9%). These results indicate that the number of submissions for drugs associated with CDx has increased over the last number of years, with the majority of these drugs relating to cancer. Further research is required to investigate if the additional complexity associated with these HTAs is addressed appropriately.

Partitioned Survival and State Transition Models for Healthcare Decision Making in Oncology: Where Are We Now?

Partitioned survival models (PSMs) are routinely used to inform reimbursement decisions for oncology drugs. We discuss the appropriateness of PSMs compared to the most common alternative, state transition models (STMs). In 2017, we published a National Institute for Health and Care Excellence (NICE) Technical Support Document (TSD 19) describing and critically reviewing PSMs. This article summarizes findings from TSD 19, reviews new evidence comparing PSMs and STMs, and reviews recent NICE appraisals to understand current practice. PSMs evaluate state membership differently from STMs and do not include a structural link between intermediate clinical endpoints (eg, disease progression) and survival. PSMs directly consider clinical trial endpoints and can be developed without access to individual patient data, but limit the scope for sensitivity analyses to explore clinical uncertainties in the extrapolation period. STMs facilitate these sensitivity analyses but require development of robust survival models for individual health-state transitions. Recent work has shown PSMs and STMs can produce substantively different survival extrapolations and that extrapolations from STMs are heavily influenced by specification of the underlying survival models. Recent NICE appraisals have not generally included both model types, reviewed individual clinical event data, or scrutinized life-years accrued in individual health states. The credibility of survival predictions from PSMs and STMs, including life-years accrued in individual health states, should be assessed using trial data on individual clinical events, external data, and expert opinion. STMs should be used alongside PSMs to support assessment of clinical uncertainties in the extrapolation period, such as uncertainty in post-progression survival.

Informing a Cost-Effectiveness Threshold for Health Technology Assessment in China: A Marginal Productivity Approach

Health technology assessment has been increasingly used in China, having been legally mandated in 2019, to inform reimbursement decisions and price negotiations between the National Healthcare Security Administration and pharmaceutical companies around the price of new pharmaceuticals. The criteria currently used to judge cost effectiveness and inform pricing negotiations, 3 × GDP per capita, is based on the rule of thumb previously recommended by the World Health Organization rather than an estimate based on an empirical assessment of health opportunity costs. The objective of this study was to inform a cost-effectiveness threshold for health technology assessment in China that accounts for health opportunity cost. The elasticity of health outcomes with respect to health expenditure was estimated using variations across 30 provincial-level administrative divisions in 2017 controlling for a range of other factors and using an instrumental variable approach to account for endogeneity to assess robustness of results. The estimated elasticity was then used to calculate the cost per disability-adjusted life-year (DALY) averted by variations in Chinese health expenditure at the margin. The range estimated from this study, 27,923-52,247 (2017 RMB) (central estimate 37,446) per DALY averted or 47-88% of GDP per capita (central estimate 63%), shows that a cost per DALY averted cost-effectiveness threshold that reflects health opportunity costs is below 1 × GDP per capita. Our results suggest that the current cost-effectiveness threshold used in China is too high; continuing to use it risks decisions that reduce overall population health.