European Journal of Health Economics最新文献

Objective: The objective of this study was to create a mapping algorithm by utilizing traditional regression analyses and a machine learning approach to estimate EQ-5D-5 L values based on EORTC QLQ-LC43 data in the absence of direct EQ-5D-5 L measurements.

Methods: Data for EQ-5D-5 L and EORTC QLQ-LC43 were collected from patients with lung cancer at the Departments of Thoracic Surgery, Medical Oncology, and Radiation Oncology at Sichuan Cancer Hospital. Mapping algorithms were applied using the ordinary least squares model (OLS), Tobit model, Beta mixture regression (BM), the adjusted limited dependent variable mixture model (ALDVMM), and ridge regression (RR) as a machine learning model to map QLQ-LC43 results based on EQ-5D-5 L scores. To develop these models, dimension scores, squared items, and interaction items were incorporated. Performance metrics, including R², root mean square error (RMSE), and mean absolute error (MAE), were used to identify the optimal model. The stability of the models was assessed using five-fold cross-validation (CV).

Results: The Beta mixture regression model (BETAMIX M1A), incorporating all dimensions of QLQ-C30 and QLQ-LC13 as covariates, exhibited the best mapping performance. The final prediction metrics were R²=0.816, RMSE = 0.125, MAE = 0.083, AIC=-717.810, and BIC=-482.609. The BM model has good explanatory ability and low prediction error. Five-fold cross-validation (CV) results also demonstrated that the BM model had the best mapping power.

Conclusions: This study developed an optimized mapping algorithm to predict the utility index from the QLQ-LC43 to the EQ-5D-5 L, offering an effective alternative for estimating EQ-5D-5 L values when preference-based health utility data are unavailable.

Background: Next generation sequencing (NGS) can decrease the diagnostic odyssey for patients with rare diseases. However, valuing the combination of health and non-health outcomes associated with NGS is challenging. While stated preference methods can be used for monetary valuation of outcomes, frameworks that jointly account for both costs and benefits to determine cost-acceptability are limited. Insights into cost-acceptability can help inform pricing and access decisions where competition among NGS alternatives is imperfect or diagnostics are provided as a public good.

Methods: We used stated preference data to estimate the cost-acceptability of exome sequencing (ES) (i.e., cost at which ES provides value and users are willing-to-pay) in a user-based valuation. We estimated the benefit of ES as an alternative to all other diagnostic tests using a compensating variation model. Based on estimated net-benefit, we determined the proportion of users with positive expected net-benefit for varying cost (CAD$0-$15,000) and chance of diagnosis (10%-90%). We created a cost-acceptability frontier of costs and chance of diagnosis for a range of scenarios. Expected net-benefit and cost-acceptability were estimated for low-cost (CAD$1,600) and high-cost (CAD$11,660) ES scenarios.

Results: We find that at least half of users consider costs of up to CAD$10,000 acceptable if the chance of obtaining a diagnosis of ES is at least 50%. However, at least some users are willing to accept a chance of diagnosis below 50%, even if the associated cost are high.

Conclusion: Our proposed valuation framework suggests that many potential users of ES are willing to accept various combinations of cost and chance of diagnosis. Cost-acceptability is especially high if the chance of diagnosis is larger the 50%.

Biologic therapies are increasingly used in multiple sclerosis (MS), but often provoke anti-drug antibodies, potentially leading to treatment failure. Testing for anti-drug antibodies to guide treatment switching could improve clinical- and cost- effectiveness of MS treatment. We assess the value of testing for anti-drug antibodies to alemtuzumab, an effective but immunogenic MS therapy. We developed a microsimulation model to project disease progression, quality of life, and cost outcomes in people with relapsing-remitting MS initiating alemtuzumab treatment without and with alemtuzumab anti-body testing. Risk of anti-drug antibody development was informed by a UK cohort study of alemtuzumab-treated people with MS. UK guidance informed MS treatment strategies. Alemtuzumab anti-drug antibody test-directed treatment switching resulted in 0.02 fewer MS relapses per person; prolonged time to secondary progressive disease by 0.06 years; and yielded 0.02 additional years of life (0.06 Quality-Adjusted Life Years (QALY)). At £25/test, incremental cost per QALY gained was £47,861, with the additional cost arising from increased time on disease-modifying therapies (DMTs). Cost-effectiveness of anti-drug antibody testing was sensitive to anti-drug antibody development risk, their impact on drug efficacy, and costs of disease-modifying therapies (DMTs). Anti-drug antibody testing to inform MS treatment switching could improve clinical outcomes, but its cost-effectiveness depends on anti-drug antibody risk, its impact on drug efficacy, and costs of DMTs.

Background: Interstitial lung disease (ILD) consists of many subtypes, with idiopathic pulmonary fibrosis (IPF) and subtypes that manifest as progressive pulmonary fibrosis (PPF) exhibit faster progression and poorer prognosis. Recent updates in the definition of PPF and expanded approval of antifibrotic treatments warrant a comprehensive review to understand the economic impact and key cost drivers.

Objective: This systematic review aims to summarize published studies on the economic burden of ILD on patients, the healthcare system, and society, and to identify the prevailing cost drivers.

Method: A literature search was conducted using PubMed, Scopus and Web of Science to identify full-length publications in English on the ILD economic burden, cost of illness, or cost-effectiveness studies, from inception until January 2024. The review protocol was registered with PROSPERO (CRD42024504116) and followed Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guideline. This review compares the direct, indirect, and overall costs across ILD subtypes and countries.

Results: Forty studies fulfilled the inclusion criteria. Annual direct costs of ILD ranged from $1,593 (South Korea) to $177,526 (United States) per patient, while indirect costs ranged from $45 to $19,507. Hospitalisation costs ranged from $1,500 to $18,792 per admission, and end-of-life care costs were $52,614 annually per patient. Inpatient (40%-89%) and medication costs (36%-82%) were identified as the major cost drivers. The predictors of increasing costs include disease severity, presence of comorbidities, and antifibrotic use. Additionally, regional disparities and healthcare system differences influenced the economic burden.

Conclusion: Interstitial lung disease imposes a substantial economic impact. Early diagnosis, effective treatments targeting ILD and comorbidities, appropriate social support, and an optimized health delivery system may reduce the overall cost and improve health outcomes.

This study explores the educational inequality in a workplace in Japan in relation to the physiological risk factors. It investigates the difference in the prevalence rates of being overweight, hypertensive, dyslipidemic or diabetic between male employees who have undergone university education and those who have not. Combining the mandatory annual health check-up data, annual stress check survey data and personnel data (total sample size=7,428), this study conducts a decomposition analysis to identify the major contributing factors to the inequality and it measures the extent to which the observed between-group disparity is associated with the differences in observable characteristics. For all four conditions, significant disparities are observed between the groups. Between-group differences pertaining to alcohol consumption, smoking behaviours, job positions, psychological stress and family structure are the major significant contributing factors behind the between-group disparities in health. The results indicate that, along with a universal health-promoting approach, additional efforts to support less educated employees should be initiated to mitigate the health inequality.

Objective: This study aimed to develop a value set for the European Organization for Research and Treatment of Cancer (EORTC) Quality of Life Utility-Core 10 Dimensions (QLU-C10D) based on the preferences of Chinese cancer patients, and to compare results with the Chinese general population value set.

Methods: Patients with mixed cancer diagnoses were recruited from two hospitals in China between September and November 2024. Patients completed the EORTC Core Quality of Life Questionnaire (QLQ-C30) followed by a discrete choice experiment (DCE) valuation survey consisting of 16 choice sets through face-to-face interviews. A conditional logit model was applied to analyze patient preferences. The characteristics and sensitivity of the derived QLU-C10D value set were compared with those of the Chinese general population QLU-C10D value set. Sensitivity was evaluated by ability to discriminate cancer stage and performance status, and effect sizes (ES) were estimated.

Results: Data from 659 cancer patients were analyzed. The cancer patients' value set showed a broader utility range (-0.092 to 1.0) compared to the general population's value set (0.083 to 1). The mean utility score for the cancer patient sample (0.656) was significantly lower than that for the general population (0.738, P < 0.01). Both value sets demonstrated good sensitivity, but the cancer patients' value set was more effective in distinguishing clinical subgroup differences (ES = 2.76-4.46 vs. ES = 2.47-3.48).

Conclusion: Differences in value sets between cancer patients and the general population underscore the importance of more comprehensively integrating patient perspectives into existing evaluation frameworks.

The spread of the COVID-19 pandemic, along with government interventions, significantly reshaped economic activity, leading to abrupt shifts in household consumption behavior. This paper offers an empirical analysis of how the rollout of COVID-19 vaccines influenced consumer spending, using high-frequency debit and credit card transaction data from three European countries. The findings indicate that vaccinations, in conjunction with other policy measures, helped mitigate the pandemic's severe economic impact and supported a recovery in consumer spending. First, the deployment of vaccines had a statistically and economically significant positive effect on private consumption. Second, additional policy responses-aimed at containing the virus and providing financial support to households and businesses-also had notable effects on both the volume and composition of card-based transactions. Third, the stimulative impact of vaccinations on consumer spending was more pronounced in contact-intensive sectors, such as services, compared to goods.

Objectives: To compare health state preferences elicited using composite time trade-off (cTTO) and discrete choice experiment with duration (DCE_TTO) between urban and rural respondents.

Methods: Respondents from the general population were recruited in urban and rural areas across China. Responses of 8 cTTO tasks and 10 DCE_TTO tasks for valuing SF-6Dv2 health states and socio-demographic characteristics were collected through face-to-face interviews. Random-effects regression was used to evaluate the effect of residence area on the cTTO values after adjusting for socio-demographic characteristics. The utility value sets developed based on the urban and rural data for cTTO and DCE_TTO were compared using mean absolute difference (MAD).

Results: Of 3,320 respondents (50.3% male, age range 18-90 years) included, 1,980 (59.6%) resided in urban areas. The mean cTTO value was significantly different between urban and rural respondents across all 295 evaluated states, with the mean (SD) difference of 0.014 (0.119) (range: -0.283 to 0.375). After adjustment, urban respondents assigned significantly higher cTTO values (Coef. = 0.021, p = 0.034). In cTTO value set, the MAD between urban and rural was 0.0276 for states with mean value > 0.5, 0.0327 for states with mean value 0-0.5, and 0.0300 for those states with negative values. For DCE_TTO value set, the MAD was 0.0359 for states with mean value > 0.5, 0.0409 for states with mean value 0-0.5, and 0.0686 for those states with negative values.

Conclusion: Rural respondents tended to assign a lower utility value than urban respondents when evaluating the same state, reflecting an observable urban-rural preference gap.

Objective: As European healthcare systems struggle with increasing workload and sustainability issues, it is estimated that 20% of their production is ineffective. One potential strategy to reduce this excess is by minimizing the use of unnecessary laboratory tests. The aim of this review was to investigate the effect of presenting physicians in Europe with the cost of laboratory tests at the time of ordering on the quantities and expense of laboratory tests as well as to identify knowledge gaps on this matter.

Methods: Following PRISMA guidelines, a systematic search in PubMed and EMBASE was conducted in February 2025. Studies were included if written in English and conducted in Europe. There were no restrictions on year of publication. Study quality was evaluated using a modified Downs and Black checklist.

Results: Of the 2185 publications identified, five met the inclusion criteria. All included studies were published 2002-2021 and found a reduction in order cost and/or volume of laboratory test, following price display (four with statistically significant results). The reduction in order costs were greater than the reduction in order volume. Additionally, the impact of price display diminished over time as the intervention period continued. None of the studies included patient safety measures.

Conclusions: Price display is a simple yet potentially impactful intervention as it is likely to reduce both the cost and volume of tests, thereby decreasing the workload and enhancing the sustainability of the healthcare systems. Further high-quality studies are needed to determine if price display is a patient-safe intervention.

Objective: To identify and synthesize available evidence on the economic burden for myelodysplastic syndromes (MDS).

Methods: A systematic search was conducted in EMBASE and MEDLINE on July 13, 2021 to identify studies that report original data on the economic burden of MDS. Included studies were reviewed independently and in duplicate by two reviewers. Data on study design, patient characteristics and economic burden were extracted using a standardized form developed by the team. All costs were converted to 2023 USD and then a descriptive analysis was conducted.

Results: 77 publications from 61 unique studies reporting the economic burden of MDS were identified. Most were database studies (n = 34, 55.7%) and were conducted in the United States (n = 34, 55.7%). The most common outcome considered was total costs for MDS (n = 32, 52.5%). Total annual costs ranged from $6777 to $521,141 and differed according to treatment modality [best supportive care versus hypomethylating agents (HMAs)] and patient status (risk status and transfusion dependent). Broadly, costs were greater among patients with high-risk MDS compared to low-risk patients as well as those receiving HMAs and transfusions. Other costs and resource use outcomes (outpatient, inpatient costs, etc.) were not directly comparable across studies due to heterogeneity and lack of reporting of cost components.

Conclusion: This systematic literature review provides insight into the economic burden of MDS, which can be substantial. More research is needed to explore specific cost components as well as economic outcomes among subgroups of patients, such as newly diagnosed patients or patients classified as high risk.