Applied Health Economics and Health Policy最新文献

There is currently deep uncertainty about the clinical benefits and cost effectiveness of highly specialised technologies (HSTs), like gene and cell therapies. These treatments are novel, typically have high upfront costs, the patient populations are small and heterogenous, there is minimal information on their long-term safety and effectiveness, and data are limited and often of poor quality. With the increasing number of these technologies and their high cost burden on governments and health care providers, policy makers are currently walking a decision tightrope. On the one hand, an unfavourable funding decision could potentially limit patient access to life-saving treatments, while on the other, a favourable decision could result in unsustainable budget impacts and perhaps poorer patient health outcomes. Health technology assessment (HTA) is meant to determine the value of a health technology in order to promote an equitable, efficient, and high-quality health system. However, standard HTA processes have failed to mitigate the deep uncertainties associated with these technologies. In this paper, we propose a Living HTA framework to address these challenges. This framework includes a one-off process for making explicit the societal values associated with HSTs. These would inform the decision-making approach, data collection and the development of disease-specific reference models to be used by industry sponsors as the basis for their submissions for public funding. Coverage with an evidence development mechanism is also proposed by which data can be collected in real time to update the reference model on a rolling basis, thereby allowing re-assessment of the clinical and cost effectiveness of individual HSTs. The HTA would be ‘live’ until the results indicate there is sufficient certainty for the funding decision to be confirmed, the price changed or the funding removed.

Background

Generic instruments such as the Pediatric Quality of Life Inventory™ v4.0 Generic Core Scales (PedsQL GCS) and Child Health Utility 9D (CHU9D) are widely used to assess health-related quality of life (HRQOL) of the general childhood population, but there is a paucity of information about their psychometric properties in children with specific health conditions. This study assessed psychometric properties, including acceptability, reliability, validity, and responsiveness, of the PedsQL GCS and the CHU9D in children and adolescents with a range of common chronic health problems.

Methods

We used data from the Longitudinal Study of Australian Children (LSAC), for children aged 10–17 years with at least one of the following six parent-reported health conditions: asthma, anxiety/depression, attention deficit hyperactivity disorder (ADHD), autism/Asperger’s, epilepsy, and type 1 diabetes mellitus. The LSAC used parent proxy-reported PedsQL GCS and child self-reported CHU9D assessments. The performance of each instrument (PedsQL GCS and CHU9D) for each psychometric property (acceptability, reliability, validity, and responsiveness) was assessed against established criteria.

Results

The study sample included 7201 children and adolescents (mean age = 14 years; range 10.1–17.9 years; 49% female) with 15,568 longitudinal observations available for analyses. Across the six health conditions, acceptability of the PedsQL GCS was high, while acceptability for the CHU9D was mixed. Both the PedsQL GCS and CHU9D showed strong internal consistency (Cronbach’s alpha range: PedsQL GCS = 0.70–0.95, CHU9D = 0.76–0.84; item-total correlations range: PedsQL GCS = 0.35–0.84, CHU9D = 0.32–0.70). However, convergent validity for both the PedsQL GCS and CHU9D was generally weak (Spearman’s correlations ≤ 0.3). Known group validity was strong for the PedsQL GCS (HRQOL differences were detected for children with and without asthma, anxiety/depression, ADHD, autism/Asperger’s, and epilepsy). CHU9D was only able to discriminate between children with and without anxiety/depression, ADHD, and autism/Asperger’s. The responsiveness of both the PedsQL GCS and CHU9D was variable across the six conditions, and most of the estimated effect sizes were relatively small (< 0.5).

Conclusion

This study expands the evidence base of psychometric performance of the PedsQL GCS and CHU9D and can aid in appropriate HRQOL instrument selection for the required context by researchers and clinicians.

Background

Prevention programmes typically incur short-term costs and uncertain long-term benefits. We use the National Health Service (NHS) England Diabetes Prevention Programme (NHS-DPP) to investigate whether behaviour change programmes may be cost-effective even within the short-term participation period.

Methods

We analysed 384,611 referrals between June 2016 and March 2019. We estimated NHS costs using implementation costs and provider payments. We used linear regressions to relate utility changes to the number of sessions attended, based on responses to the five-level EQ-5D (EQ-5D-5L) at baseline and final session for 18,959 participants. We then calculated the corresponding quality-adjusted life year (QALY) change for all 384,611 referrals by combining the estimated regression coefficients with the observed level of attendance, with individuals that did not attend any programme sessions being assumed to experience zero benefit. In secondary analysis, we added weight change, recorded for 18,105 participants to the regression and applied predicted values to all referrals with missing weight change values estimated using multiple imputation with chained equations. We then estimated the cost-per-QALY generated.

Results

Average cost per referral was £119 (standard deviation: £118; 2020 price year, UK £ Sterling). Each session attended was associated with a 0.0042 increase in utility (95% confidence interval (CI): 0.0025–0.0059). This generated 1,773 QALYs across all referrals (95% CI: 889–2,656). Cost-per-QALY was £24,929 (95% CI: £16,635–49,720) when implementation costs were excluded. Secondary analysis showed each session attended and kilogram of weight lost were associated with 0.0034 (95% CI: 0.0016–0.0051) and 0.0025 (95% CI: 0.0020–0.0031) increases in utility, respectively. These generated 1,542 QALYs, at a cost-per-QALY of £28,661 when implementation costs were excluded.

Conclusion

Participants experienced small utility gains from session attendance and weight loss during their programme participation. These benefits alone made this low-cost behaviour change programme potentially cost-effective in the short-term.

Objective

This study examined the inter-rater agreement between child-self and parental proxy health-related quality of life (HRQoL) ratings (overall and domain level) using two different generic child-specific measures, the Child Health Utility 9D (CHU9D) and the Pediatric Quality of Life Inventory (PedsQL^TM), in a community-based sample of Australian children. A secondary objective was to investigate the impact of age on child–parent agreement across the dimensions of the two measures.

Methods

A total of 85 child–parent dyads (children aged 6–12 years) recruited from the community completed the self and proxy versions of the CHU9D and the PedsQL^TM, respectively. The inter-rater agreement was estimated using Concordance Correlation Coefficients (CCC) and Gwet’s Agreement Coefficient (AC₁) for the overall sample and across age-groups.

Results

Agreement was low for overall HRQoL for both the CHU9D (CCC = 0.28) and the PedsQL^TM (CCC = 0.39). Across the CHU9D dimensions, agreement was the highest for ‘sad’ (AC₁ = 0.83) and lowest for ‘tired’ (AC₁ = 0.31). The PedsQL^TM demonstrated stronger agreement (AC₁ = 0.41–0.6) for the physical health dimension but weaker for the psychosocial dimensions (AC₁ < 0.4). Except for the ‘tired’ dimension, agreement was consistent across age-groups with the CHU9D, whilst the PedsQL^TM showed poor agreement for most of the psychosocial health items among the older age-groups only (8–10 and 11–12 years).

Conclusion

This study highlights that the agreement between child and parent proxy reported HRQoL may be influenced by both the measure used and the age of the child. These findings may have implications for the economic evaluation of healthcare interventions and services in child populations when both child and proxy perspectives are considered in the assessment of child HRQoL.

Background

Increasing pharmaceutical expenditure challenges the sustainability and accessibility of healthcare systems across Europe. Confidentiality restraints hinder assessment of actual prices of Orphan Medicinal Products (OMPs). Hence, we assessed the real prices of brand-name OMPs around market exclusivity expiry (MEE).

Objective

We aimed to explore developments in published list prices (LPs) and confidential hospital purchase prices (PPs) of brand-name OMPs relative to their market exclusivity status in Western European countries with similar GDPs.

Methods

We analyzed LPs and PPs of 13 selected OMPs purchased by university hospitals in Western European countries between 2000 and 2020. For confidentially reasons, proportions were used, with the Dutch LPs of the selected OMPs at the year of MEE serving as reference values. PPs included pre-purchase discounts. Rebates were not considered.

Results

Data were analyzed from hospitals in Denmark (DK) (n = 1), France (FR) (n = 1), Germany (DE) (n = 2), and the Netherlands (NL) (n = 1). Average LPs and PPs of included OMPs dropped gradually but limited over time, with no explicit price drop after MEE. LP levels differed more per country than PP levels: LP range before MEE was 164% (DE)–101% (FR) and after MEE was 135% (DE)–82% (FR); PP range before MEE was 150% (DE)–102% (FR) and after MEE was 107% (DE)–80% (FR). Overall differences between LPs and PPs were < 3% in all countries, except for Denmark.

Conclusion

No evident price drops of included brand-name OMPs were observed around MEE and differences in purchase prices are modest in the selected Western European countries. Results were not subject to significance testing. More robust data are needed to strengthen negotiations with suppliers.

Introduction

There is a boom in imaging biomarker-driven companion and complementary diagnostics (CDx) for cancer, which brings opportunity for personalized medicine. Whether adoption of these technologies is likely to be cost-effective is a relevant question, and studies on this topic are emerging. Despite the growing number of economic evaluations, no review of the methods used, quality of reporting, and potential risk of bias has been done. We report a systematic review to identify, summarize, and critique the cost-effectiveness evidence for the use of biomarker-driven and imaging-based CDx to inform cancer treatments.

Methods

The Preferred Reporting Items of Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. Systematic literature searches until 30 December 2022 were performed in PubMed, Web of Science, Medline, Embase, and Scopus for economic evaluations of imaging biomarker-based CDx for cancer. The inclusion and exclusion of studies were determined by pre-specified eligibility criteria informed by the ‘Patient, Intervention, Comparison, Outcome’ (PICO) framework. The Consolidated Health Economic Evaluation Reporting Standards (CHEERS) was used to assess the quality of reporting, and the Bias in Economic Evaluation (ECOBIAS) was used to examine the potential risk of bias of included studies.

Results

A total of 12 papers were included, with eight model-based and four trial-based studies. Implementing biomarker-driven, imaging-based CDx was reported to be cost-effective, cost saving, or dominant (cost saving and more effective) in ten papers. Inconsistent methods were found in the studies, and the quality of reporting was lacking against the CHEERS reporting guideline. Several potential sources of ‘risk of bias’ were identified. These should be acknowledged and carefully considered by researchers planning future health economic evaluations.

Conclusion

Despite favorable results towards the implementation of imaging biomarker-based CDx for cancer, there is room for improvement regarding the quantity and quality of economic evaluations, and that is expected as the awareness of current study limitations increases and more clinical data become available in the future.