A retrospective analysis of budget impact models submitted to the National Centre for Pharmacoeconomics in Ireland

Utilization, Expenditure, and Treatment Patterns Associated With Calcitonin Gene-Related Peptide Monoclonal Antibodies Reimbursed Subject to a Managed Access Protocol in Ireland

OBJECTIVES

Calcitonin gene-related peptide monoclonal antibodies (CGRP mAbs) are novel high-cost treatments for the prevention of migraine. This study presents data on utilization, expenditure, and treatment patterns with CGRP mAbs available under a managed access protocol in Ireland, to a cohort of treatment refractory patients (failed 3 or more previous treatments) with chronic migraine.

METHODS

Data were extracted from the Primary Care Reimbursement Service High Tech claims database and special drug request online system and analyzed using Microsoft Excel and SAS. Treatment persistence was evaluated by refill patterns, and adherence was evaluated using the proportion of days covered method. Expenditure data were extracted directly from the database.

RESULTS

Between September 1, 2021 and April 30, 2023, 1517 applications for reimbursement approval for a CGRP mAb were received; 1458 (96.1%) were approved for reimbursement. Total expenditure on CGRP mAbs in year 1 (September 1, 2021 to August 31, 2022) was €3.2 million. The majority of patients initiated treatment with fremanezumab (60.8%) or erenumab (37.1%). Almost 90% of patients were considered adherent, and treatment persistence was high, with more than 75% of patients receiving more than 12 months of treatment in our 18-month study time frame.

CONCLUSIONS

This study demonstrates the importance of active health technology management, after reimbursement, in enabling cost-effective use of high-cost treatments while providing budget certainty for the healthcare payer. High levels of adherence and persistence suggest that treatment is successfully targeted in situations which unmet clinical need is greatest.

Cost-effectiveness evidence on approved cancer drugs in Ireland: the limits of data availability and implications for public accountability

BACKGROUND

We surveyed evidence published by Ireland's National Centre for Pharmacoeconomics (NCPE) on the cost-effectiveness of cancer drugs approved for funding within the Irish public healthcare system. The purpose is threefold: to assess the completeness and clarity of publicly available cost-effectiveness data of such therapies; to provide summary estimates of that data; to consider the implications of constraints on data availability for accountability regarding healthcare resource allocation.

METHODS

The National Cancer Control Programme lists 91 drug-indication pairs approved between June 2012 and July 2020. Records were retrieved from the NCPE website for each drug-indication pair, including, where available, health technology assessment (HTA) summary reports. We assessed what cost-effectiveness data regarding approved interventions is available, aggregated it and considered the consequences of reporting constraints.

RESULTS

Among the 91 drug-indication pairs 61 were reimbursed following full HTA, 22 after a rapid review process and 8 have no corresponding NCPE record. Of the 61 where an HTA report was available, 41 presented costs and quality-adjusted life-year (QALY) estimates of the interventions compared. Cost estimates and corresponding incremental cost-effectiveness ratios (ICERs) are based on prices on application for reimbursement. Reimbursed prices are not published. Aggregating over the drug-indication pairs for which data is available, we find a mean incremental health gain of 0.85 QALY and an aggregate ICER of €100,295/QALY, which exceeds Ireland's cost-effectiveness threshold of €45,000/QALY.

CONCLUSION

Reimbursement applications by pharmaceutical manufacturers for cancer drugs typically exceed Ireland's cost-effectiveness threshold, often by a considerable margin. On aggregate, the additional total net cost of new drugs relative to current treatments needs to be more than halved for the prices sought on application to be justified for reimbursement. Commercial confidentiality regarding prices and cost-effectiveness upon reimbursement compromises accountability regarding the fair and efficient allocation of scarce healthcare resources.

Increasing the impact of budget impact analysis: incorporating uncertainty for decision-makers in small markets

For decision-makers considering new medicines for reimbursement and public use, both value for money and affordability are important considerations. Whereas a cost-effectiveness model provides information about value for money, a budget impact assessment (BIA) is customized to a specific context and estimates the total investment needed; one part of affordability. Both analytic approaches have parameter uncertainty within them, yet comparatively little attention is given to parameter uncertainty in BIA. Currently, within BIA, uncertainty exploration is limited to point estimates for plausible scenarios, prompting the question: can a decision-maker be confident in point estimates? Within this paper, our intent is to revitalize the discussion of uncertainty in BIA. In the context of health technology assessments submitted to support reimbursement decision-making, we propose reliance on probabilistic sensitivity analysis conducted in the cost-effectiveness model. If assumptions made in a cost-effectiveness model are valid, probabilistic cost estimates from the model, with the same perspective adopted as the BIA, should also inform BIA. Mean and variance of population outcomes, given parameter uncertainty in model inputs, are estimable from model outputs. As sufficiently large random samples are drawn from a population, the distribution of sample means will follow an approximately normal distribution. Therefore, when drawing samples from the model to inform estimates of budget impact, the assumption of an approximately normal distribution for costs is reasonable. We propose that the variance in mean costs from the cost-effectiveness model also reflects the variance in budget impact estimates and should be used to estimate budget impact confidence intervals.

Budget impact analysis of medicines: estimated values versus real-world evidence and the implications

Objectives: Budget Impact Analyses (BIA) of medicines helps managers in promoting health systems' sustainability when assessing the role and value of new medicines. However, it is not clear whether BIAs typically underestimate or overestimate the impact on real-world budgets. This retroactive analysis seeks to compare estimated values obtained by a BIA and Real-World Evidence (RWE) to guide discussions.Methods: The estimated values were obtained through a BIA concerning the incorporation of adalimumab for the treatment of Rheumatoid Arthritis into the Brazilian Unified Health System (SUS) carried out retroactively and per international guidelines. RWE data was extracted from SUS computerized systems. We subsequently compared the number of treatments, costs, and Incremental Budget Impact (IBI).Results - The total number of treatments was underestimated by 10% (6,243) and the total expenditure was overestimated by 463% (US$ 4.7 billion). In five years, the total difference between the estimated values and real IBI reached US$ 1.1 billion. A current expenditure of US$ 1.0 was observed for every US$ 5.60 of estimated expenditure.Conclusion - The higher estimates from the BIA might cause decision makers to be more cautious with the introduction of a new medicine to reduce the opportunity costs for other interventions.