Applied Health Economics and Health Policy最新文献

Background: This study aimed to assess the cost-effectiveness of non-vitamin K antagonist oral anticoagulants (NOACs) in comparison with warfarin using data from real practice based on the perspective of the health care system in Thailand.

Methods: A four-state Markov model encompassing well-controlled atrial fibrillation (AF), stroke and systemic embolism, major bleeding and death was utilised to forecast clinical and economic outcomes. Transitional probabilities, direct medical costs and utilities were derived from the real-world data of the 'COOL-AF Thailand' registry, Thailand's largest nationwide registry spanning 27 hospitals. The cohort comprised AF patients. The primary outcomes assessed were total costs, life years, quality-adjusted life years (QALYs) and the incremental cost-effectiveness ratio. All costs and outcomes were subject to an annual discount rate of 3.0%. A spectrum of sensitivity analyses was conducted.

Results: The mean age of the cohort was 68.8 ± 10.7 years. The NOACs group incurred a marginally lower total lifetime cost than the warfarin group (247,857 Thai baht [THB] vs 253,654 THB or 7137 USD vs 7304 USD) and experienced gains of 0.045 life years and 0.043 QALYs over the warfarin group. Given the lower cost and higher benefits associated with NOACs, this implies that NOAC treatment is a dominant strategy compared to warfarin for AF patients. At a ceiling ratio of 160,000 THB (4607 USD) per QALY, NOACs presented a 61.2% probability of being cost effective.

Conclusions: Non-vitamin K antagonist oral anticoagulants represent a cost-saving alternative to warfarin in the real clinical practice. However, with a probability of being cost effective below 65%, it suggests some parameter uncertainty regarding their overall cost effectiveness compared to warfarin.

It is well accepted that medical devices (MDs) and procedures have several unique characteristics compared with pharmaceuticals, such as learning curve (LC), incremental innovation (II), dynamic pricing (DP), and organizational impact (OI). The objective of this study was to determine the extent to which these MD characteristics are routinely assessed by health technology assessment (HTA) agencies and incorporated in their guidelines and reports. Three approaches were taken. First, a review of the most recent HTA methods guidelines from 14 selected HTA agencies and 5 HTA networks was undertaken. Next, HTA reports from these agencies were reviewed for inclusion of MD-specific characteristics for 16 selected MDs. Finally, a narrative literature review on this topic was conducted. A total of 13 of the included HTA organizations, and some HTA networks (2/5), have published either general or MD-specific method guidelines, whilst several addressed MD-specific characteristics. NICE included all four MD characteristics in their guidelines, but this did not equate to their inclusion in published HTA evaluations. European Network HTA (EUnetHTA) described the inclusion of LC (within patient safety) and OI within their guidance. The results highlight a lack of consistency. For the narrative review, 10/149 articles identified were reviewed. Most provided recommendations on challenges faced by HTAs, proposed steps to address uncertainties around MD characteristics and reported a lack of methodological guidance for evaluating MDs. A lack of inclusion of MD characteristics in HTA is a complex interplay of several important factors. For these characteristics to become a formal part of HTA of MDs in the future, clear guidance and frameworks are required to enable manufacturers to develop appropriate evidence, and HTA practitioners to assess their impact more broadly.

Improving efficiency and productivity are key aspects to ensure that general practices in England can meet the needs of a growing population with increasingly demanding and costly healthcare needs. However, current evidence on the efficiency and productivity of general practices is weak, partly due to suboptimal approaches to measure their 'valued' output. To overcome this limitation, this paper presents a multi-dimensional framework and indicators of valued output from the healthcare decision-maker's perspective. We identified existing primary care performance frameworks through a targeted literature review. We reviewed the frameworks and selected the dimensions relating to the impact on patients' health outcomes, corresponding with the definition of 'valued' output from the healthcare decision-maker perspective. For each dimension, we reviewed the National Institute for Health and Care Excellence (NICE) evidence base and guidance on best practice to develop indicators of valued output. Clinical experts and representatives of the main primary care stakeholders reviewed and validated the framework's comprehensiveness and development process. Based on a review of three existing frameworks, we synthesised a multi-dimensional output framework comprising 13 dimensions for significant primary care-related conditions and services and 51 indicators of valued output. Each indicator of valued output measures a healthcare episode and the resulting impact on patient's health. The multi-dimensional framework and indicators provide a theoretical tool to improve the measurement of primary care output in economic efficiency and productivity studies. Future research should explore the measurability of the indicators through available datasets and the implementation of the framework through analytical approaches for efficiency measurement.

Background: High healthcare costs could arise from unmet needs. This study used random forest (RF) and regression methods to identify predictors of high costs from a US payer perspective in patients newly diagnosed with generalized myasthenia gravis (gMG).

Methods: Adults with gMG (first diagnosis = index) were selected from the IQVIA PharMetrics^® Plus database (2017-2021). Predictors of high healthcare costs were measured 12 months pre-index (main cohort) and during both the 12 months pre- and post-index (subgroup). Top 50 predictors of high costs [≥ $9404 (main cohort) and ≥ $9159 (subgroup) per-patient-per-month] were identified with RF models; the magnitude and direction of association were estimated with multivariable modified Poisson regression models.

Results: The main cohort and subgroup included 2739 and 1638 patients, respectively. In RF analysis, the most important predictors of high costs before/on the index date were index MG exacerbation, all-cause inpatient admission, and number of days with corticosteroids. After the index date, these were immunoglobulin and monoclonal antibody use and number of all-cause outpatient visits and MG-related encounters. Adjusting for the top 50 predictors, post-index immunoglobulin use increased the risk of high costs by 261%, monoclonal antibody use by 135%, index MG exacerbation by 78%, and pre-index all-cause inpatient admission by 27% (all p < 0.05).

Conclusions: This analysis links patient characteristics both before the formal MG diagnosis and in the first year to high future healthcare costs. Findings may help inform payers on cost-saving strategies, and providers can potentially shift to targeted treatment approaches to reduce the clinical and economic burden of gMG.

Objective: Preventing the onset of skin malignancies is feasible by reducing exposure to ultraviolet radiation. We reviewed published economic evaluations of primary prevention initiatives in the past decade, to support investment decisions for skin cancer prevention.

Methods: We assessed cost-effectiveness, cost-utility and benefit-cost analyses published from 1 September 2013. Seven databases were searched on 18 July 2023 and updated on 15 November 2023. Studies must have reported outcomes in terms of monetary costs, life years, quality-adjusted life years or variant thereof. A narrative synthesis was undertaken and reporting quality was assessed by three reviewers using the Consolidated Health Economic Evaluation Reporting Standards checklist.

Results: In total, 12 studies were included with five studies located in Australia; three in North America and the remaining four in Europe. Interventions included restricting the use of indoor tanning devices (7 studies), television advertising, multi-component sun safety campaigns, shade structures plus protective clothing provision for outdoor workers and provision of melanoma genomic risk information to individuals. Most studies constructed Markov cohort models and adopted a societal cost perspective. Overall, the reporting quality of the studies was high. Studies found highly favourable returns on investment ranging from US$0.35 for every $1 spent on prevention, up to €3.60 for every €1 spent. Other studies showed substantial skin cancers avoided, gains in life years, quality-adjusted survival, and societal cost savings.

Conclusions: From both population health and economic perspectives, allocating limited health care resources to primary prevention of skin cancer is highly favourable.

The characteristics and relative strengths and weaknesses of partitioned survival models (PSMs) and state transition models (STMs) for three state oncology cost-effectiveness models have previously been studied. Despite clear and longstanding economic modeling guidelines, more than one structure is rarely presented, and the choice of structure appears correlated more with audience or precedent than disease, decision problem, or available data. One reason may be a lack of guidance and tools available to readily compare measures of internal validity such as the model fit and efficiency of different structures, or sensitivity of results to those choices. To address this gap, methods are presented to evaluate the fit and efficiency of three structures, with an accompanying R software package, psm3mkv. The methods are illustrated by analyzing interim and final analysis datasets of the KEYNOTE-826 randomized controlled trial. At both interim and final analyses, the STM Clock Reset structure provided the best and most efficient fit. Structural uncertainties had been reduced from interim to final analysis. Beyond measures of internal validity, guidelines highlight the importance of reflecting all available data, avoiding model selection purely on the basis of goodness of fit and strongly considering external validity. The method and software allow modelers to more easily evaluate and report model fit and efficiency, examine implicit assumptions, and reveal sensitivities to structural choices.

Background: Fostering market entry of novel antibiotics and enhanced use of diagnostics to improve the quality of antibiotic prescribing are avenues to tackle antimicrobial resistance (AMR), which is a major public health threat. Pricing, procurement and reimbursement policies may work as AMR 'pull incentives' to support these objectives. This paper studies pull incentives in pricing, procurement and reimbursement policies (e.g., additions to, modifications of, and exemptions from standard policies) for novel antibiotics, diagnostics and health products with a similar profile in 10 study countries. It also explores whether incentives for non-AMR health products could be transferred to AMR health products.

Methods: This research included a review of policies in 10 G20 countries based on literature and unpublished documents, and the production of country fact sheets that were validated by country experts. Initial research was conducted in 2020 and updated in 2023.

Results: Identified pull incentives in pricing policies include free pricing, higher prices at launch and price increases over time, managed-entry agreements, and waiving or reducing mandatory discounts. Incentives in procurement comprise value-based procurement, pooled procurement and models that delink prices from volumes (subscription-based schemes), whereas incentives in reimbursement include lower evidence requirements for inclusion in the reimbursement scheme, accelerated reimbursement processes, separate budgets that offer add-on funding, and adapted prescribing conditions.

Conclusions: While a few pull incentives have been piloted or implemented for antibiotics in recent years, these mechanisms have been mainly used to incentivize launch of certain non-AMR health products, such as orphan medicines. Given similarities in their product characteristics, transferability of some of these pull incentives appears to be possible; however, it would be essential to conduct impact assessments of these incentives. Trade-offs between incentives to foster market entry and thus potentially improve access and the financial sustainability for payers need to be addressed.

Economic evaluations aim to compare the costs and the results of health strategies to guide the public decision-making process. Cost estimation is, thus, a cornerstone of this approach. At present, few national evaluation agencies recommend incorporating the cost of greenhouse gas (GHG) emissions from healthcare actions into the calculation of healthcare costs. Our main goal is to describe and discuss the methodology for integrating the cost of GHG emissions into the field of applied economic evaluations. To estimate this cost, three steps are required: (1) identifying and quantifying the physical flows linked to the production and management of the outputs of healthcare interventions, (2) estimating the quantity of GHG that can be attributed to each physical flow, and (3) valuing these GHG emissions in monetary terms. Integrating the cost of GHG emissions into the calculation of the costs of healthcare interventions is both useful and relevant from a perspective of collective intergenerational well-being. This approach has been made possible thanks to the existence of accounting and monetary valuation methods for emissions. Agencies specialized in health economic evaluations could take up this issue to resolve ongoing questions, thus providing researchers with a methodological framework and public decision-makers with some key insights.

Background and objective: Globally, emergency medical services (EMSs) report that their demand is dominated by non-emergency (such as urgent and primary care) requests. Appropriately managing these is a major challenge for EMSs, with one mechanism employed being specialist community paramedics. This review guides policy by evaluating the economic impact of specialist community paramedic models from a healthcare system perspective.

Methods: A multidisciplinary team (health economics, emergency care, paramedicine, nursing) was formed, and a protocol registered on PROSPERO (CRD42023397840) and published open access. Eligible studies included experimental and analytical observational study designs of economic evaluation outcomes of patients requesting EMSs via an emergency telephone line ('000', '111', '999', '911' or equivalent) responded to by specialist community paramedics, compared to patients attended by usual care (i.e. standard paramedics). A three-stage systematic search was performed, including Peer Review of Electronic Search Strategies (PRESS) and Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA). Two independent reviewers extracted and verified 51 unique characteristics from 11 studies, costs were inflated and converted, and outcomes were synthesised with comparisons by model, population, education and reliability of findings.

Results: Eleven studies (n = 7136 intervention group) met the criteria. These included one cost-utility analysis (measuring both costs and consequences), four costing studies (measuring cost only) and six cohort studies (measuring consequences only). Quality was measured using Joanna Briggs Institute tools, and was moderate for ten studies, and low for one. Models included autonomous paramedics (six studies, n = 4132 intervention), physician oversight (three studies, n = 932 intervention) and/or special populations (five studies, n = 3004 intervention). Twenty-one outcomes were reported. Models unanimously reduced emergency department (ED) transportation by 14-78% (higher quality studies reduced emergency department transportation by 50-54%, n = 2639 intervention, p < 0.001), and costs were reduced by AU$338-1227 per attendance in four studies (n = 2962). One study performed an economic evaluation (n = 1549), finding both that the costs were reduced by AU$454 per attendance (although not statistically significant), and consequently that the intervention dominated with a > 95% chance of the model being cost effective at the UK incremental cost-effectiveness ratio threshold.

Conclusions: Community paramedic roles within EMSs reduced ED transportation by approximately half. However, the rate was highly variable owing to structural (such as local policies) and stochastic (such as the patient's medical condition) factors. As models unanimously reduced ED transportation-a major contributor to costs-they in t

Background: With advances in health state valuation methods, new value sets may be developed for some countries. Quantifying the impact of moving between existing and new value sets is critical for guiding decisions around utility score interpretation, reporting and comparison with published scores.

Objectives: The aim of this study is to examine, using large-scale national registry data, how the new Australian EQ-5D-5L value set impacts utility scores for patients undergoing joint replacement.

Methods: Data from the Australian Orthopaedic Association National Joint Replacement Registry were used for this analysis. All primary total hip (THR), knee (TKR), and shoulder replacement (TSR) procedures between 2018 and 2022 with pre-operative and 6-month post-operative EQ-5D-5L data were included. Utility scores were generated using the 2013 and 2023 Australian value sets ('previous' and 'new' value sets, respectively) and analysed descriptively for each joint replacement cohort. Agreement between the two utility score sets was evaluated using concordance correlation coefficients and Bland-Altman plots.

Results: EQ-5D-5L data were available for 17,576 THR, 23,010 TKR, and 1667 TSR procedures. The new value set produced a lowest possible EQ-5D-5L utility score of -0.30 (compared with -0.68 previously) and fewer patients had 'worse-than-dead' quality of life (score < 0.00) before surgery. Mean pre-operative scores were 0.21 (THR), 0.19 (TKR), and 0.17 (TSR) units higher with the new value set, and mean post-operative scores were 0.11-0.14 units higher. The new value set resulted in smaller effect sizes for the THR (1.08 versus 1.23) and TKR cohorts (0.86 versus 0.92). There was moderate-to-good overall agreement (coefficients: 0.70-0.80), but concordance varied by time point.

Conclusion: Although acceptable agreement was evident, the new Australian value set produces less extreme negative utility scores and markedly higher group-level scores. Transition to reporting new EQ-5D-5L utility scores will require accompanying explanation to signal measurement modifications rather than better quality of life.