European Journal of Health Economics最新文献

Financial incentives are a promising intervention to promote healthier behaviours and potentially reduce health inequalities. Despite robust evidence supporting their effectiveness in encouraging actions such as smoking cessation, increased physical activity, and improved diet, large-scale implementation of financial incentives in Europe remains limited. This perspective identifies three key challenges impeding their broader use: (1) difficulties in reaching the populations most in need, (2) short-lived behavioural effects after removal of the incentives, and (3) uncertainty about sustainable and equitable funding. Drawing on interdisciplinary evidence, we explore potential solutions such as tailored incentive design, strategies to prolong behavioural change (e.g. intermittent reinforcement or dynamic phase-outs), and the development of public or private funding models. We argue that while financial incentives should not replace structural health policy interventions, they can be a powerful complementary tool. A coordinated research agenda is needed to inform scalable and effective implementation.

Introduction: To ensure fair competition and prevent risk selection by sickness funds, Germany employs a morbidity-based risk-adjustment scheme, primarily using diagnostic data to record insured persons' morbidity. However, concerns about the manipulability and quality of diagnostic coding have sparked discussions. This study proposes and evaluates an alternative risk-adjustment model based on pharmaceutical data, assessing its potential as an extension or an alternative to the diagnosis-based status quo.

Methods: We adapted an existing pharmacy-based model to German conditions and simulated various models. In order to create comparability to the status quo, we constructed a representative sample for the German statutory health insurance (SHI), using claims data of about 4.5 million insured persons. We evaluated the sample by assessing the standardized differences of the weighted means of the relevant covariates. For a quantitative assessment of the models we used the coefficients of determination (R²), Cumming's Predictive Measure (CPM), and the mean absolute prediction error (MAPE). Under- and overcompensation within different risk groups were also analysed.

Results: The sample closely matched SHI data (overall effect size after matching < 0.0001). Substituting diagnostic data with pharmacy cost groups (PCGs) showed comparable model quality, but worsened under- and overcompensation for groups vulnerable to risk selection. Conversely, integrating PCGs into the status quo improved nearly all performance measures.

Conclusion: Introducing pharmacy-based models into the German risk compensation scheme demonstrates significant potential. Extending the current model with PCGs enhances statistical performance, improves morbidity measurement, and offers a viable approach to mitigate coding manipulation incentives.

Background: Evidence for the long-term costs of cancer is limited, particularly in the Scottish population. Our aim was to better understand the long-term healthcare use and associated costs of cancer in Scotland, and their relationship with cancer survival.

Methods: This was a retrospective study using routine healthcare data to measure inpatient, outpatient, community prescription use and their costs from a national health service perspective. Per-episode incidence costs were assigned using reference costs and charted over eight years during the period 2009 to 2018 by year and phase of care. Risk factors for survival and costs were analysed using Cox regression and generalised linear model regression.

Results: In total, 55,807 adults with cancer were followed over eight years after their diagnosis. Trajectories indicated a complex relationship with survival. Mean cumulative per-patient costs for all cancers were £29,460 at 2017/18 price levels (95% CI £29,199 to £29,720). Considerable variation was observed between cancer types with the highest costs in non-Hodgkin lymphoma at £47,672 (95%CI £45,500 to £49,843) and the lowest in malignant melanoma of skin at £19,217, (95%CI £18,251 to £20,184). Variables negatively associated with costs tended to be positively associated with hazard of death. Only screening was significantly associated with both lower costs (adjusted cost ratio 0.85, p < 0.001) and lower hazard of death (adjusted hazard ratio 0.30, p < 0.001).

Conclusions: Substantial costs were observed in all cancer types studied, with the highest costs measured in the year following diagnosis. Screening was associated with both lower costs and better survival, supporting the focus on early detection.

Background: Non-inferiority and clinical equivalence clinical trials can be used to determine whether a health technology is no worse than an existing treatment. This study identified international guidance for conducting non-inferiority and clinical equivalence trials and investigated the current practices in conducting and reporting such trials, especially in the context of Health Technology Assessment (HTA).

Methods: A pragmatic approach was used to identify international guidelines and published literature reporting approaches for the conduct and reporting of non-inferiority or clinical equivalence studies. Guidelines from both HTA and regulatory bodies were considered, and literature reviews from 2010 to 2023 were identified. The results of the reviews were supplemented by stakeholder interviews and synthesised to form a series of recommendations for the UK National Institute for Health and Care Excellence in the appraisal of non-inferiority and equivalence trials.

Results and conclusion: The majority of guidelines (13/15) discussed methods to determine the non-inferiority margin and how the analysis should be conducted. Despite this, the quality of reporting in non-inferiority and clinical equivalence trials is consistently poor. Prior to presentation of trial evidence, HTA submissions that claim non-inferiority or equivalence should present the technical, biological and/or pharmacokinetic reasonings that support the claim.

Objective: We assessed the cost effectiveness of onasemnogene abeparvovec (OA) for presymptomatic infants with two or three copies of the survival motor neuron 2 (SMN2) gene (diagnosed/treated ≤ 6 weeks old) who lack functional SMN1 gene (biallelic SMN1 mutations). This cost-utility model compared three disease-modifying treatments and best supportive care (BSC) (scenario analysis) in an Italian setting.

Methods: For a cohort of 1000 children, a Markov model simulated costs and benefits of OA (a one-time treatment), nusinersen and risdiplam (continuous lifelong treatments), and BSC. A lifetime time horizon (up to age 100 years) was applied, and the perspective of the Italian National Health Service was considered. Results are reported as incremental cost-effectiveness ratios (ICERs). Deterministic and probabilistic sensitivity analyses were conducted to assess the robustness of the model and validity of results.

Results: In the full cohort, OA was dominant (less costly, more effective) compared with nusinersen or risdiplam (ICERs,-€4,562,815 and-€718,640), and cost effective (more costly, more effective) compared with BSC (ICER, €65,894). Similar results were found for patients with two SMN2 copies. For patients with three SMN2 copies, OA was less costly, with a similar efficacy profile compared with nusinersen, dominant versus risdiplam, and cost effective compared with BSC. Probabilistic sensitivity analysis demonstrated the robustness of the model and validated deterministic sensitivity analysis results for the full cohort.

Conclusions: OA for the treatment of presymptomatic newborns was dominant or cost effective compared with other treatments or BSC in the full patient cohort within the Italian context.

Despite evidence of changes in age-specific incidence and prevalence rates for chronic conditions and disease, future health resource planning is often based on historical age- and gender-specific service use, neglecting changes in the need for care within age groups between generations. This paper studies differences in health needs by age and gender across birth cohorts in Australia and considers the implications for future health service planning. Whilst controlling for age and period effects, we find that more recent-born female birth cohorts have higher prevalence rates of long-term health conditions than earlier-born cohorts, whereas we don't find an effect for males. The increase for females corresponds with an increase in probable mental disorders, and while we also find an increase in probable mental disorders among males, decreases in physical impairment rates among both genders offset the overall rates of long-term health conditions among males but not among females, where increases in probable mental disorders are larger. Comparing projections of mental health service requirements that integrate cohort effects, as opposed to those that do not, shows that traditional planning models may underestimate health service requirements for the future. Our findings suggest that health service planners should relax assumptions about constant age-specific use.

Background: Two million people in the UK suffer from Long COVID (LC), imposing substantial health economic impacts. This study aimed to: 1) assess longitudinal changes in health utility scores and economic costs of LC, and number of services received at LC specialist clinics and clinic region to capture care intensity; 2) assess whether volume of services received responded to health needs; and 3) estimate the national economic impact of LC.

Methods: LC patients from 10 specialist clinics participated in the LOCOMOTION study. Patient-reported outcomes measures (EQ-5D-5L, C19-YRS and Health Economics Questionnaire) were completed on a digital platform. Associations were assessed between changes in economic outcomes (EQ-5D-3L utility, health economic costs) and number/type of LC specialist services received and region. Per-person values of quality-adjusted life-year losses, public sector costs, productivity losses and informal care costs were multiplied by LC prevalence to estimate national economic impacts.

Results: There was a statistically significant reduction in public sector costs over time. There was no significant association between the number of specialist services received and change in health utility scores. LC specialist clinic and outpatient service utilisation corresponded to health need and had significant regional variation after controlling for health need. LC is associated with a substantial economic impact nationally, estimated at £8.1 billion annually and £24.2 billion since its emergence, comparable to the annual cost of £9.4 billion for stroke.

Conclusion: The effectiveness of LC specialist clinic services warrants further research. The substantial national economic impact of LC warrants a nationwide LC care strategy.

Taylor and colleagues presented a very informative and comprehensive overview on the current practice of performing non-inferiority analysis in HTA. We would like to point out that HTA of potentially non-inferior technologies should be based on balancing potential advantages against potential deficits exactly as for potentially superior technologies.