Value in Health最新文献

Objectives: This study aimed to generate mapping algorithms from the Patient-Reported Outcomes Measurement Information System Pediatric-25 Profile (PROMIS-25) to both EQ-5D-Y-3L responses (indirect mapping) and EQ-5D-Y-3L utilities (direct mapping).

Methods: A subset of data from the Australian Paediatric Multi-Instrument Comparison study data set was used, including participants aged 5 to 18 years who completed both the EQ-5D-Y-3L and PROMIS-25 (n = 1830). Both direct and indirect mapping approaches were used, exploring a range of regression models and predictor variables for each approach. For the direct mapping approach, the EQ-5D-Y-3L Australian value set was used, and sensitivity analyses were conducted using the EQ-5D-Y-3L Dutch value set. Five-fold internal cross-validation was used to select the optimal mapping models based on goodness-of-fit indicators, including the root mean square error (RMSE), mean absolute error (MAE), and concordance correlation coefficient. The final mapping algorithms reported are based on the full sample.

Results: The generalized ordered logit model using the PROMIS-25 raw domain scores as predictors was selected for predicting EQ-5D-Y-3L responses in the indirect mapping (RMSE, 0.1098; MAE, 0.0724). The Tobit model, also using the PROMIS-25 raw item scores as predictors, was the optimal direct mapping model for predicting Australian EQ-5D-Y-3L utilities (RMSE, 0.0994; MAE, 0.0712). The same models performed similarly well in sensitivity analyses using Dutch utilities.

Conclusions: The mapping algorithms provide a pathway for PROMIS-25 data to be converted directly to either an Australian or Dutch EQ-5D-Y-3L utility or EQ-5D-Y-3L responses where local value sets can be applied. This broadens the usability of PROMIS-25, enabling calculation of utilities for use in economic evaluation.

Economic evaluations of interventions that target or include children require health state utilities (HSUs). Despite the availability of preference-weighted measures for children, methods for valuing child health states and estimating child utilities are not as well established as those for adult HSUs. The objective of this task force was to develop emerging good practice recommendations for valuing child and adolescent health to generate HSUs for use in economic evaluation. This task force identified and described the interrelated methodological choices regarding the valuation of child health to generate HSUs. The task force considered available evidence related to 4 key issues: (1) whose preferences should be sought, (2) whose health is imagined, (3) which method should be used, and (4) the comparability between adult and child utilities. Best practices may vary depending on the modeling context, characteristics of the health states, and the health technology assessment setting in which the HSUs will be used. For any individual study, methods will be informed by empirical evidence, value judgments, and recommendations from healthcare decision makers. Rather than recommending an approach that would apply to every study, this task force presents options to consider when determining the preference elicitation approach to generate utilities for child health states, along with the strengths and limitations of each. Given that child HSUs can affect the outcomes of a cost-utility analysis and subsequent decisions about healthcare resource allocation, this task force recommends that researchers be transparent about methodological choices and their impact on HSUs.

Objectives: Cancer imposes a significant economic burden on the US healthcare system and its patients. We quantified changes in price levels and variation for oncologic services after federal price transparency regulations and evaluated whether the prevalence and granularity of disclosures were associated with these changes.

Methods: This retrospective longitudinal study used nationwide hospital price transparency data from December 2021 to June 2024. The data set included billing codes across 4 oncology service categories (inpatient, chemotherapy administration, radiation, and surgery). A linear mixed-effects model evaluated the annualized real rate change (ARRC) as a function of local market-specific percentile price rank, transparency measures, service category, payer, market structure, and health system.

Results: Data were extracted for 89 billing codes from 228 hospitals, yielding 11 290 negotiated rate groups and 349 990 monthly observations. Each 10-percentage-point increase in code-level transparency was associated with a 0.82-percentage-point decrease in ARRC (P < .001). Within local markets, hospitals in initially low- or high-price deciles demonstrated inflation-adjusted price increases and decreases, respectively, with a -21.2 percentage point ARRC differential between the lowest and highest rates (P < .001). Price changes and convergence varied by service category, payer, and hospital size (P < .05). Price dispersion declined over time (P < .01).

Conclusions: After federal price transparency regulations, markets with greater code-level transparency experienced larger price reductions, and prices converged as variation between high- and low-priced hospitals declined. These findings suggest transparency may promote more efficient and affordable cancer care, although the overall impact on spending and access remains uncertain.

Objectives: Colombia and the Dominican Republic are funding high-cost medicines (HCMs) whose effectiveness is uncertain or, in some cases, limited, whereas essential health services remain underfunded. Public financing of each HCM entails an opportunity cost because these resources could yield greater health benefits if used elsewhere. This study quantifies the population-health impact of funding HCMs in both Latin American countries.

Methods: We selected 10 publicly financed HCMs in each country based on their substantial budgetary impact or high per-case treatment cost. We applied the net health benefit methodology to estimate the population-health impact associated with funding these medicines.

Results: The selected HCMs primarily treat chronic conditions and yield incremental health gains of less than 2 years of life in full health per patient. In Colombia, allocating resources to these HCMs instead of better alternatives required an additional spending of $642 million to treat 22 155 patients, resulting in a net health loss of approximately 122 507 quality-adjusted life-years (QALYs). In the Dominican Republic, the $154 million directed to 1807 patients generated a net population-health loss of 35 221 QALYs.

Conclusions: Public financing of HCMs with limited effectiveness can entail significant population-health losses. These losses must be explicitly accounted for in resource allocation decisions because they reflect missed opportunities to advance universal health coverage.

Objectives: This study aimed to explore the impact of recall period on the measurement properties of the EuroQol 5-Dimension 5-Level (EQ-5D-5L) and EuroQol Health and Well-Being 9 items (EQ-HWB-9) instruments.

Methods: An online cross-sectional survey was conducted with a general population sample in Hong Kong (n = 1262). Respondents completed both a "today (TD)" and a "last week (LW)" version of both the EQ-5D-5L and EQ-HWB-9. Psychometric properties (eg, distributional characteristics, ceiling, informativity, convergent validity with conceptually related items, or domains of ReQoL-10 and Patient-Reported Outcomes Measurement Information System - 29 + 2, known-group and structural validity) were assessed for both recall period versions of both instruments.

Results: Considering all measurement properties, differences between LW and TD versions were small but slightly larger for the EQ-HWB-9 than for the EQ-5D-5L. LW versions showed lower ceilings, captured more problems, and demonstrated greater informativity. They had comparable or stronger correlations with ReQoL-10 and Patient-Reported Outcomes Measurement Information System - 29 + 2 items or domains than TD, especially for EQ-HWB-9. Known-group validity was slightly better for LW versions, particularly in mental health subgroups, whereas structural validity of both measures was largely consistent across recall periods.

Conclusions: In this general population sample, although the LW recall versions exhibited slightly superior measurement properties compared with the TD versions, our findings overall support the original recall periods for the EQ-5D-5L and EQ-HWB-9. Future research should evaluate the impacts of varying recall periods across populations and cultural contexts to further refine guidelines for instrument selection in the intended areas of use for each instrument.

Objectives: To evaluate methodological challenges and regulatory considerations of indirect treatment comparisons (ITCs) with the analysis of French Transparency Committee (TC) decisions and international health technology assessment guidelines.

Methods: We conducted a pragmatic review of ITC guidelines from major health technology assessment bodies and analyzed 138 TC opinions containing 195 ITCs published between 2021 and 2023. We extracted data on ITC methodology, therapeutic areas, acceptability, and limitations expressed by the TC.

Results: ITC submissions increased by 44.7% over the study period, but only 13.3% of these comparisons influenced TC decision making. ITCs were more frequently accepted in genetic diseases (34.4%) compared with oncology (10.0%) and autoimmune diseases (11.1%). Methods using individual patient data showed higher acceptance rates (23.1%) than network meta-analyses (4.2%). Main limitations included heterogeneity/bias risk (59%), lack of data (48%), statistical methodology issues (29%), study design concerns (27%), small sample size (25%), and outcome definition variability (20%). When ITCs were the primary source of evidence, the proportion of important clinical benefit was lower (60.9% vs 73.4%) than when randomized controlled trials were available.

Conclusions: Although ITCs are increasingly submitted, particularly in situations in which direct evidence is impractical, their influence on reimbursement decisions remains limited. There is a need for clear and accessible guides so that manufacturers can produce clearer and more robust ITCs that follow regulatory guidelines, from the planning phase to execution.

Objectives: Many health systems aim to reduce health inequalities. Reimbursement mechanisms for healthcare providers, including pay-for-performance, are common policy levers to align provider behavior with health systems objectives. We develop a methodology to incorporate equity concerns into value-based pricing in the English National Health Service. We focus on socioeconomic inequalities in health measured by deprivation quintiles. We show how changes in the design of a national pay-for-performance scheme in primary care, the Quality Outcome Framework, can be evaluated in terms of their effects on the level and distribution of health across socioeconomic status.

Methods: After developing our theoretical framework, which is based on Distributional Cost-Effectiveness Analysis and contract theory, we calibrate a model of physician behavior using information on costs and health benefits of different incentivized activities, achievement rates, and supply responsiveness to prices. We evaluate the effect of hypothetical 20% increases in price of 1 incentivized activity, which is financed by a reduction in another price to retain budget neutrality. Trade-offs between efficiency and socioeconomic inequalities in health are evaluated using the Equally Distributed Equivalent level of health.

Results: We illustrate our methodology using 3 scenarios: changes in prices for 2 incentivized activities for the same health condition (diabetes), different health conditions (diabetes and chronic obstructive pulmonary disease), and across socioeconomic groups within the same activity (flu vaccination for diabetes patients).

Conclusions: Our analysis illustrates how inequality aversion can be incorporated into value-based pricing when assessing the effect of financial incentives on the health distribution across socioeconomic groups.