Value in Health最新文献

Objectives: Predictive models in medicine help make decisions about which individual to treat with a given therapeutic or preventive intervention. Before being tested in large field studies and recommended for clinical adoption, it is important to evaluate not only their statistical accuracy but also the impact they may have when used to inform health intervention policies. We aim to provide simple methods for the potential impact assessment of health intervention policies based on predictive models.

Methods: We propose an analytic framework based on Qini curves wherein prediction-based policies are analyzed on 2 impact endpoints: (1) the fraction of the population that would be selected for the intervention (coverage) and (2) the effect on the clinical outcomes of interest (disutility). The drivers of values are the disease prevalence, the predictive performance of the model, and the effectiveness of the intervention.

Results: We present simple formulas for calculating coverage and disutility from either observational or randomized controlled data. We illustrate possible value measures arising from geometrical properties on the Qini plane: delta coverage and disutility, number needed to treat, and integrated difference between Qini curves. We show the applicability of the Qini analysis by providing examples about the prevention of falls in older adults and prevention of secondary cardiovascular events with pioglitazone.

Conclusions: Coverage and disutility capture key value components of prediction-based policies. The method can be used for comparing models or tuning risk thresholds for managing trade-offs between conflicting objectives (eg, clinical benefits, side effects, and healthcare resources).

Objectives: Internet-based psychological interventions hold promise for cost-effectiveness; yet, their evaluation lacks standardization, potentially leading to methodological discrepancies and inconclusive results. This study aims to conduct a scoping review of economic methods used when evaluating these interventions.

Methods: Articles published between January 2015 and December 2020 were retrieved from PubMed, Embase, Cochrane Library, CINAHL, ECONLIT, and PsychINFO. Two reviewers independently screened titles, abstracts, and full texts of relevant publications and extracted prespecified data. Outcomes related to intervention characteristics, comparators, perspective, time horizon, costs, benefits, economic endpoints, and uncertainty analysis methods were retrieved and synthetized narratively.

Results: We identified 703 references and included 85. Seventy-four of them included a cost-utility analysis and 58 a cost-effectiveness analysis, with 47 carrying out both. The comparator was treatment as usual in 52 studies (61.2%) but varied widely across studies. A societal perspective was adopted in 60 studies, supplemented by a healthcare perspective in half. Time horizon was 1 year or less in 68 articles (80.0%). Intervention costs (71/85 studies) predominantly covered delivery costs (45/71 studies), whereas development and promotional costs were infrequently considered (respectively, 14 and 5/71 studies). Interventions' reach, opportunity costs, user engagement, and equity issues were rarely addressed. Key factors influencing cost-effectiveness included perspective, time horizon, costs included, and methods for handling missing data.

Conclusions: Assessment of cost-effectiveness in internet-based psychological interventions shows variability, potentially affecting efficiency evidence. Conventional methods are often favored overlooking digital tools' specificities. Tailored guidelines for such evaluations could be helpful for standardized and reliable evidence.

Objectives: This study evaluated the impact of a mobile health (mHealth) cardiovascular disease (CVD) self-management program on medical spending, healthcare utilization, and clinical outcomes.

Methods: We conducted a retrospective cohort, pre-post observational analysis of medical claims data from February 2018 to September 2023. Participants enrolled in the mHealth CVD self-management program were compared with matched nonparticipants to assess changes in medical spending and utilization, using a difference-in-differences (DiD) approach. Moderation analyses tested whether the effect of participation on medical costs differed according to participants' demographic and employer characteristics. Linear mixed models were also used to evaluate changes in participant blood pressure.

Results: There were 7112 participants and an equal number of matched nonparticipants from 14 employers included in the cost-savings analysis. Participation in the mHealth CVD self-management program was associated with an annualized per member savings of $1709 as compared with matched nonparticipants. Although savings were consistent across participant sex and employer type, older participants experienced greater savings. Program participation was associated with fewer inpatient hospital days and increased primary care utilization after enrollment. Program participants experienced significant reductions in blood pressure, with the largest reductions seen among those with stage 2 hypertension at baseline.

Conclusions: Participation in an mHealth CVD self-management program was associated with significant cost savings and clinical improvements across diverse populations, highlighting its effectiveness as a cost-efficient tool for managing CVD and improving health outcomes. Further research is needed to explore the long-term benefits and cost-effectiveness of mHealth programs to support broader adoption.

Objectives: The healthcare sector contributes significantly to global warming; yet, strategies for reducing its impact are not well integrated into health policy. This scoping review aimed to identify the range of effective interventions that can reduce the environmental footprint of healthcare and to provide an overview of their impact.

Methods: We searched for peer-reviewed articles published in English, French, or Swedish between 2010 and September 2024 in Medline and Web of Science, following the Joanna Briggs Institute guidelines and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews. Publications were selected by 2 researchers and a documentalist. Data from included studies were extracted and synthesized in tables and described in a narrative synthesis.

Results: We identified 7 systematic reviews and 44 original research articles. Most of the effective interventions targeted hospitals and varied from energy saving practices and reducing potent anesthetic gases to changing care protocols and improving waste management. The measured impact of interventions was context specific and depended on national energy sources. Only a few studies reported on the impact of structural and strategic changes in healthcare provision across care settings.

Conclusions: There is an urgent need for better understanding the costs and benefits of diffusing effective green interventions across care providers and developing more systemic approaches for optimizing care provision and utilisation to achieve a meaningful impact.

Objectives: We conducted a systematic literature review to summarize the application of statistical methods for analyzing treatment effect on EQ-5D in randomized clinical trials (RCTs).

Method: We searched 2 electronic databases (MEDLINE and EMBASE, from inception through 2021) and www.

Clinicaltrial: gov. Eligible studies were RCTs that analyzed postbaseline EQ-5D data by treatment group. Information on trial characteristics, EQ-5D data characteristics, and statistical methods were extracted. Descriptive statistics were used to summarize results by dimension response, EQ visual analog scale (EQ VAS), and EQ-5D utility.

Results: A total of 2125 trials met the eligibility criteria. EQ-5D was commonly considered a secondary (n = 1219, 57.4%) or exploratory (n = 775, 36.5%) endpoint in RCTs. EQ-5D utilities were the most analyzed. Both utilities and EQ VAS were primarily analyzed in numerical format. The most common statistical models for analyzing utilities were the linear fixed-effect model for single postbaseline (192/589, 32.6%) and the linear mixed-effect model for multiple post-baselines (338/984, 34.3%). Of the 2054 studies that analyzed numerical EQ-5D, 221 (10.8%) examined model assumptions and 438 (21.3%) adjusted for the baseline score. Missing data were explicitly assessed in 661 trials, among which 347 (52.5% of 661) applied imputations, with the 2 most used imputation methods being multiple imputations (n = 200, 57.6% of 347) and last observation carried forward (n = 106, 30.5% of 347).

Conclusions: This review found that health utilities are the most frequently analyzed EQ-5D data collected in clinical trials, followed by EQ VAS. Significant variation was observed in the selection of models, with most trials lacking adjustments for baseline data and appropriate methods for handling missing data.

Objectives: Health economic models are crucial for health technology assessments to evaluate the value of medical interventions. Open-source models (OSMs), in which source code and calculations are publicly accessible, enhance transparency, efficiency, credibility, and reproducibility. This study systematically reviewed databases to map the landscape of available OSMs in health economics.

Methods: A systematic database review was conducted, informed by guidance from ISPOR's OSM Special Interest Group. Eleven databases and specific OSM repositories were searched using predefined terms. Identified models were screened and duplicates were removed.

Results: The search yielded 8664 hits, resulting in 182 unique OSMs. GitHub hosted the majority (74%), followed by Zenodo (11%). R was the predominant software platform (64%). Infectious disease was the most common application domain (29%). Markov models were the most frequent model type (49%). Licensing with Creative Commons was typical. Government and academic institutions were the primary sponsors, although many models lacked clear sponsorship.

Conclusions: This review highlights the diversity and availability of open-source models (OSMs) in health economics, predominantly hosted on GitHub and developed using R. The models span various medical fields, with a strong focus on infectious diseases, oncology, and neurology. Ensuring clear licensing and standardized reporting is crucial to maximizing their impact. A combined approach of repository searches and traditional literature reviews provides a comprehensive method for identifying OSMs. Future efforts should enhance search strategies, improve reporting standards, and leverage OSMs to inform health policy decisions.

Objectives: The population-level impact of newer glucagon-like peptide-1 receptor agonist (GLP-1 RA) treatments on patients with type 2 diabetes remains unclear. Therefore, this study investigated the association of newer GLP-1 RAs with population-level diabetes-related outcomes in US adults with type 2 diabetes.

Methods: This was a noninterventional, retrospective analysis of administrative insurance claims data obtained from Optum's deidentified Clinformatics® Data Mart Database between January 2004 and December 2022. Individual patient data were aggregated into monthly time series at the population level. Associations between the proportion of patients on newer GLP-1 RAs of interest (dulaglutide, once-weekly or oral semaglutide, and tirzepatide) and average hemoglobin A1c (HbA1c), HbA1c <7.0%, and HbA1c <8.0% were assessed using time series regressions. Time-based trends in population-level outcomes were assessed using interrupted time series analyses. All analyses were adjusted for potential confounders.

Results: Time series regression analyses demonstrated that a higher proportion of patients taking newer GLP-1 RAs was associated with a lower average HbA1c and a higher proportion of patients with HbA1c <7.0% (after 5 months of treatment) and <8.0% (after 2 months of treatment). Results from the interrupted time series analyses demonstrated that population-level glycemic control has been improving since the first newer GLP-1 RA (dulaglutide) was approved. This trend has persisted, even after the COVID-19 emergency declaration.

Conclusions: A higher percentage of patients receiving newer GLP-1 RAs was associated with significantly improved population-level glycemic control. The newer GLP-1 RA period displayed improved population-level glycemic control compared with the older GLP-1 RA period.

Objectives: This landscape analysis aimed to summarize the role of health equity in the health technology assessment (HTA) process (topic nomination, topic prioritization, assessment, appraisal, and decision making) in Asia.

Methods: A comprehensive literature review was conducted, followed by in-depth interviews with key informants. Content analysis was performed to summarize the role of health equity in HTA in 13 health systems in Asia, including Brunei Darussalam, Cambodia, China, Indonesia, Japan, Malaysia, Myanmar, Philippines, Singapore, South Korea, Taiwan, Thailand, and Vietnam.

Results: Health equity was reported to be considered in most health systems' HTA processes, except for Cambodia and Myanmar, which do not have an established HTA process. Interviews revealed that health equity has been more frequently considered to address the unmet medical needs of specific diseases (eg, high disease burden or severity, rare diseases, cancer, and diseases affecting children and the elderly) in Brunei Darussalam, China, Japan, Malaysia, Singapore, South Korea, Taiwan, Thailand, and Vietnam or inequities in socially disadvantaged groups (eg, socioeconomic status and geographical location) in Indonesia and the Philippines. Equity-informative economic evaluation was still in the early stages, with only 3 health systems reporting their use.

Conclusions: Health equity is considered in the HTA process in most Asian health systems. However, quantitative evaluation of health equity impact is still in its infancy because few health systems have just begun to perform equity-informative economic evaluations.

Objectives: In the absence of EQ-5D utility data, the National Institute for Health and Care Excellence recommends sourcing utility values from a proxy health condition, provided that data indicate that the health-related quality of life (HRQoL) impact of the conditions is similar. Given that there is no standard practice for identifying proxy conditions, this study presents a patient-centered approach for selecting a proxy condition, using alopecia areata (AA) as an example.

Methods: A structured electronic search was conducted to identify conceptual models for conditions similar to AA with overlapping HRQoL domains. Conceptual models were compared to determine the most suitable proxy condition, defined as the condition with the most overlapping domains and reported similarities between patient HRQoL. A search and comparison of utility data between AA and the selected proxy condition was conducted to validate their comparability in HRQoL impact.

Results: Seven conditions with overlapping HRQoL domains with AA were identified using conceptual models. Atopic dermatitis (AD) had the most overlapping domains (n = 6) and the greatest evidence of similarities between patient HRQoL; thus, it was selected as the proxy condition. Conceptual models indicated that both conditions affected patients' physical, emotional, and functional well-being. Furthermore, AD and AA utilities were comparable, supporting the choice of AD as the proxy condition.

Conclusions: Given the correlation observed between AA and the selected proxy condition using this methodology, this study presents a potential approach to identify proxy conditions for diseases that may be underrepresented in terms of HRQoL data.

Objectives: To examine the cost-effectiveness of a digitally supported care management system (CMS) for caregivers of people with dementia (PwD) compared with usual care.

Methods: The analysis was based on 192 caregivers (n = 96 CMS, n = 96 usual care) of PwD in a cluster-randomized controlled trial testing a digitally supported CMS, aiming to identify and address caregivers' unmet needs and develop and implement an individualized support and care plan over 6 months. Incremental costs from the public-payer and societal perspectives, quality-adjusted life years (QALY), and the incremental cost-effectiveness ratio 6 months after baseline were calculated using multivariate regression models. We assessed the probability of cost-effectiveness using a range of willingness-to-pay thresholds.

Results: Caregivers in the intervention group gained QALYs (+0.004 [95% CI -0.003 to 0.012], P value = .225) and had lower costs from the public payer (-378€ [1926-1168], P value = .630), but higher costs from the societal perspective (+1324 [-3634 to 6284], P value = .599). The intervention dominated usual care from the payer perspective, whereas the incremental cost-effectiveness ratio was €331 000/QALY from a societal perspective. The probability of cost-effectiveness was 72% and 79% from the public payer and 33% and 35% from a societal perspective at the willingness-to-pay thresholds threshold of €40 000 and €80 000/QALY gained.

Conclusions: CMS was likely cost-effective from the payer but not from a societal perspective, underlining the importance of informal care. The gain in QALY was marginal and could be due to the short observation period. Focusing on both the caregiver and the PwD, rather than assessing the PwD needs through the caregiver, could improve the cost-effectiveness results.