Value in HealthPub Date : 2025-10-21DOI: 10.1016/j.jval.2025.09.3069
Carolina Moreno-López, Ramon Castano, Pamela Góngora-Salazar, Úrsula Giedion, Ginna P Saavedra, Andrés I Vecino-Ortiz
{"title":"Disinvestment and Health Spending Efficiency in Latin America and the Caribbean: A Case Study of Colombia.","authors":"Carolina Moreno-López, Ramon Castano, Pamela Góngora-Salazar, Úrsula Giedion, Ginna P Saavedra, Andrés I Vecino-Ortiz","doi":"10.1016/j.jval.2025.09.3069","DOIUrl":"https://doi.org/10.1016/j.jval.2025.09.3069","url":null,"abstract":"<p><strong>Introduction: </strong>Health systems in Latin America and the Caribbean (LAC) face financial pressures from rising healthcare costs, inflation, and limited economic growth. Rationalizing inappropriate or unnecessary uses of technologies can enhance efficiency and sustainability, especially when those technologies yield limited benefits or can even lead to potential harm. Strategic disinvestment can contribute to more sustainable health systems by rationalizing spending and improving health outcomes in Latin America and the Caribbean; however, its effects remain largely unexamined in the region.</p><p><strong>Objective: </strong>This study aims to measure and quantify the potential financial and health (opportunity cost) impact of disinvestment in six candidate health technologies in Colombia (cesarean section, preoperative chest x-ray, CT scan for headaches with no warning signs, extended use of proton-pump inhibitors, antibiotics, and antihistamines in cold), identified by previous research.</p><p><strong>Methods: </strong>We carried out a micro-costing approach. involving four steps: identifying required data, defining the baseline case for evaluation, estimating waste for each prioritized technology along with the potential financial impact of disinvestment , and quantifying the opportunity cost of reallocating these resources to selected cost-effective alternatives (best- buys), using different methodologies.</p><p><strong>Results: </strong>Among the six technologies, inappropriate use of CT scans generated the highest level of waste. If reallocated, these resources could enable 9,029 additional women to receive four prenatal care visits, reducing the existing coverage gap by approximately 6.4%. Similar results are presented for other technologies.</p><p><strong>Conclusion: </strong>We showed the potential health effect of redirecting resources from wasteful or ineffective technologies to highly cost-effective interventions offering a practical pathway to narrow coverage gaps and improve health outcomes in the region.</p>","PeriodicalId":23508,"journal":{"name":"Value in Health","volume":" ","pages":""},"PeriodicalIF":6.0,"publicationDate":"2025-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145356106","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Value in HealthPub Date : 2025-10-18DOI: 10.1016/j.jval.2025.10.001
Ying Zhang, Zhaoyan Chen, Xi Chen, Fangyuan Tian
{"title":"Economic evaluation of deprescribing in older adults: A systematic review.","authors":"Ying Zhang, Zhaoyan Chen, Xi Chen, Fangyuan Tian","doi":"10.1016/j.jval.2025.10.001","DOIUrl":"https://doi.org/10.1016/j.jval.2025.10.001","url":null,"abstract":"<p><strong>Objective: </strong>This study aims to synthesize economic evaluation evidence on deprescribing in older adults across settings.</p><p><strong>Methods: </strong>A comprehensive search was conducted across the PubMed, Embase, and Web of Science databases from inception through June 18, 2025, to identify studies evaluating the economic impact of deprescribing in older adults. Two independent reviewers selected relevant articles, extracted data, and assessed study quality according to the Consolidated Health Economic Evaluation Reporting Standards 2022.</p><p><strong>Results: </strong>57 studies were included, covering multiple settings such as communities, outpatient clinics, hospitals, geriatric care facilities, nursing homes, primary care, home, and online platforms. Medication review was the most frequently employed deprescribing strategy, supplemented by education, pharmaceutical care, rounds, and pharmacist independent prescriber. Multiple deprescribing tools were used, including general and custom criteria. Physicians and pharmacists were the primary implementers of deprescribing interventions. Economic evaluation methods included cost, cost-utility, cost-benefit, cost-effectiveness, cost-consequence, and return-on-investment analysis, with various outcome indicators. Quality assessment revealed that the quality of the studies was good or very good, except for three studies that were of poor quality. Most studies (44 of 57) indicated that deprescribing led to cost-saving, medication cost reduction, or improved cost-effectiveness/benefit/utility.</p><p><strong>Conclusion: </strong>The majority of studies support the economic benefit of deprescribing, although some report negative or inconclusive results. However, this review has some limitations in database retrieval, data abstraction and risk of bias assessment, potentially affecting the findings. The contradiction in economic results stems from a variety of factors, which requires further optimization studies in the future.</p>","PeriodicalId":23508,"journal":{"name":"Value in Health","volume":" ","pages":""},"PeriodicalIF":6.0,"publicationDate":"2025-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145337714","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Value in HealthPub Date : 2025-10-15DOI: 10.1016/j.jval.2025.09.3068
Quan Zhang
{"title":"Operationalizing Distributional Cost-Effectiveness in Genomic Medicine: A US-Focused Comment on Smith et al. (2025).","authors":"Quan Zhang","doi":"10.1016/j.jval.2025.09.3068","DOIUrl":"https://doi.org/10.1016/j.jval.2025.09.3068","url":null,"abstract":"","PeriodicalId":23508,"journal":{"name":"Value in Health","volume":" ","pages":""},"PeriodicalIF":6.0,"publicationDate":"2025-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145313833","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Value in HealthPub Date : 2025-10-15DOI: 10.1016/j.jval.2025.09.3067
Dylan A Mordaunt, Zornitza Stark, Adam G Elshaug, Chris Schilling
{"title":"Genomic Testing in Australia: A Budget Impact Analysis Using Diffusion Modelling from a Healthcare System Perspective.","authors":"Dylan A Mordaunt, Zornitza Stark, Adam G Elshaug, Chris Schilling","doi":"10.1016/j.jval.2025.09.3067","DOIUrl":"https://doi.org/10.1016/j.jval.2025.09.3067","url":null,"abstract":"<p><strong>Background: </strong>Genomic testing can shorten the diagnostic odyssey for people with rare diseases, yet clinical uptake has lagged funding policy in Australia. We evaluated the 10-year budget impact of alternative implementation strategies for publicly funded genomic testing using national claims data and diffusion modelling.</p><p><strong>Methods: </strong>Monthly Medicare Benefits Schedule (MBS) claims (1993-2025) were analyzed for chromosomal microarray analysis (CMA), Fragile X (FMR1) testing, and genomic tests across seven rare-disease groups (syndromic and non-syndromic intellectual disability, neuromuscular, inherited cardiac, renal ciliopathies/tubulopathies, congenital hearing loss, mitochondrial). Logistic, Gompertz, and Bass diffusion functions and SARIMA were fitted to uptake and used to forecast 2025-2034 volumes. Scenarios included: status quo; broadened second-line eligibility; and first-line ES/GS replacing CMA/FMR1 (60:40 ES:GS). Costs used 1 July 2024 MBS schedule fees; results are in AUD.</p><p><strong>Results: </strong>Observed genomic testing volumes were below diffusion-implied trajectories. Ten-year cumulative spending was: status quo AUD 1.1m; broadened second-line AUD 7.5m (incremental +6.4m vs status quo); and first-line ES/GS AUD 6.2m (incremental +5.1m). In 2028, status quo AUD 0.23m, second-line AUD 1.21m, first-line AUD 0.97m. ES/GS achieved lower cumulative spend than broadened second-line despite higher per-test fees, reflecting substitution from CMA/FMR1 and efficient diagnostic pathways.</p><p><strong>Conclusions: </strong>Indication-by-indication funding has yielded slower-than-expected uptake and likely under-budgeting. A first-line genomic testing pathway, aligned with CMA criteria, could better match clinical need while constraining spend vs expanding second-line eligibility. Harmonized eligibility and streamlined implementation would improve access and planning.</p>","PeriodicalId":23508,"journal":{"name":"Value in Health","volume":" ","pages":""},"PeriodicalIF":6.0,"publicationDate":"2025-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145313765","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Value in HealthPub Date : 2025-10-15DOI: 10.1016/j.jval.2025.09.3066
Sara Khor, Anirban Basu, Veena Shankaran, Kyueun Lee, Eric C Haupt, Erin E Hahn, Josh J Carlson, Aasthaa Bansal
{"title":"Evaluating Long-term Health Disparity Impacts of Clinical Algorithms Using a Patient-level Simulation Framework.","authors":"Sara Khor, Anirban Basu, Veena Shankaran, Kyueun Lee, Eric C Haupt, Erin E Hahn, Josh J Carlson, Aasthaa Bansal","doi":"10.1016/j.jval.2025.09.3066","DOIUrl":"https://doi.org/10.1016/j.jval.2025.09.3066","url":null,"abstract":"<p><strong>Objective: </strong>This study applies a simulation framework to evaluate the long-term effects of omitting race from a colon cancer decision algorithm for adjuvant chemotherapy, assessing impacts on health outcomes, costs, and disparities while accounting for measurement errors across racial groups.</p><p><strong>Methods: </strong>We developed a patient-level state-transition model using electronic health records from a large Southern California health system to project outcomes for 4,839 adults with stage II and III colon cancer post-surgery. We compared 30-year quality-adjusted life-years (QALYs), healthcare costs, and QALY distribution among racial groups under three chemotherapy treatment scenarios: 1) current practice, 2) treatment guided by an algorithm that includes race, and 3) the same algorithm with race omitted. An additional health state addressed racial bias in cancer recurrence ascertainment, and probabilistic sensitivity analysis (PSA) assessed uncertainty.</p><p><strong>Results: </strong>The clinical algorithm, compared to current practice, could improve average health by 0.048 QALYs and reduce racial health disparity by 0.20 QALYs at an incremental cost of $3,221, with the disparity gap decreasing in 96% of PSA iterations. Omitting race showed minimal effects on overall health or costs but resulted in 13% fewer Black patients receiving treatment, decreasing their QALYs by 0.07 and widening the disparity gap by 0.13 QALY. Health disparity increased in 94% of PSA iterations.</p><p><strong>Conclusions: </strong>A cancer decision algorithm can improve population health and reduce health disparities, but omitting race may harm disadvantaged groups and limit reductions in disparities. Patient-level simulations can be routinely used to evaluate the potential health disparity impacts of algorithms before implementation.</p>","PeriodicalId":23508,"journal":{"name":"Value in Health","volume":" ","pages":""},"PeriodicalIF":6.0,"publicationDate":"2025-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145313785","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Value in HealthPub Date : 2025-10-14DOI: 10.1016/j.jval.2025.09.3063
Elizabeth Goodwin, Amy Heather, Nia Morrish, Jenny Freeman, Kate Boddy, Sarah Thomas, Jeremy Chataway, Rod Middleton, Annie Hawton
{"title":"Comparative Responsiveness of Preference-Based Health-Related Quality of Life, Social Care and Wellbeing Measures in the Context of Multiple Sclerosis.","authors":"Elizabeth Goodwin, Amy Heather, Nia Morrish, Jenny Freeman, Kate Boddy, Sarah Thomas, Jeremy Chataway, Rod Middleton, Annie Hawton","doi":"10.1016/j.jval.2025.09.3063","DOIUrl":"https://doi.org/10.1016/j.jval.2025.09.3063","url":null,"abstract":"<p><strong>Objectives: </strong>To provide evidence on the responsiveness of social care and wellbeing preference-based measures (PBMs) compared to health-related quality of life PBMs in the context of multiple sclerosis (MS).</p><p><strong>Methods: </strong>The ICEpop CAPability measure for Adults (ICECAP-A) and Adult Social Care Outcomes Toolkit (ASCOT) were completed online in September 2019, March 2020, September 2020, via the UK MS Register. Responses were linked to EQ-5D-3L and MS Impact Scale-Eight Dimensions (MSIS-8D) values, and to MS Walking Scale-12 (MSWS-12), Hospital Anxiety and Depression Scale (HADS) and Fatigue Severity Scale (FSS) scores. Responsiveness was assessed in relation to minimal important differences on MSWS-12, HADS and FSS between timepoints, using mean change scores, t-tests, standardised effect sizes, standardised response means and multivariable regression analyses.</p><p><strong>Results: </strong>Data from 1,742 people with MS were available for analysis. When using standardised values, MSIS-8D showed the greatest responsiveness and EQ-5D-3L the least. In contrast, when absolute utility values were used, EQ-5D-3L performed similarly to MSIS-8D and better than ICECAP-A and ASCOT. Standardised regression analyses indicated the MSIS-8Ds to be the most responsive, followed by the ASCOT, ICECAP-A, and EQ-5D-3L.</p><p><strong>Conclusions: </strong>The ICECAP-A, ASCOT and MSIS-8D were more responsive than the EQ-5D-3L in the context of MS when compared using standardised scores. The increased responsiveness of EQ-5D-3L when absolute values were used seems an artefact of the wide-ranging scale of this measure. This illustrates how the maximum potential range of values for a given PBM tariff could influence whether an intervention is found to be cost-effective.</p>","PeriodicalId":23508,"journal":{"name":"Value in Health","volume":" ","pages":""},"PeriodicalIF":6.0,"publicationDate":"2025-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145309425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Value in HealthPub Date : 2025-10-14DOI: 10.1016/j.jval.2025.09.3062
Nilmini Wijemunige, Pieter van Baal, Ravindra P Rannan-Eliya, Owen O'Donnell
{"title":"Dominance-based distributional cost-effectiveness analysis of cardiovascular disease risk screening in Sri Lanka.","authors":"Nilmini Wijemunige, Pieter van Baal, Ravindra P Rannan-Eliya, Owen O'Donnell","doi":"10.1016/j.jval.2025.09.3062","DOIUrl":"https://doi.org/10.1016/j.jval.2025.09.3062","url":null,"abstract":"<p><strong>Objectives: </strong>Screening for cardiovascular disease (CVD) risk is potentially cost-effective but its net health impact by socioeconomic status (SES) likely depends on a) who is screened, b) the socioeconomic profile of risk factors, and c) the criteria for prescribing preventive medication. We conducted a dominance-based distributional cost-effectiveness analysis (DCEA) of CVD risk screening strategies in Sri Lanka to compare their equity-efficiency trade-offs.</p><p><strong>Methods: </strong>Using nationally representative data, we modelled four strategies of opportunistic CVD risk screening at public outpatient clinics and the current screening program (comparator). We measured SES with an assets index. For each strategy, we simulated costs, quality-adjusted life years (QALYs) and the distribution of QALYs net of health opportunity costs by SES. Assuming aversion to pro-rich inequality, we used generalized concentration curve dominance to rank these distributions and calculated equally distributed equivalent (EDE) net QALYs for each.</p><p><strong>Results: </strong>The most cost-effective (lowest ICER) strategy was opportunistic (vs invited) screening at age ≥ 40 (vs ≥ 35) with statins prescribed at CVD risk ≥ 10% (vs ≥ 20%) and antihypertensives at blood pressure ≥ 130/80 mm Hg (vs ≥ 140/90) for those risks and diabetics. Given net QALYs generated by SES and aversion to pro-rich inequality, this strategy dominated all others (except one), and it generated more EDE net QALYs. This strategy dominated another with a similar ICER that added statins for people with diabetes.</p><p><strong>Conclusions: </strong>Dominance-based DCEA identified modifications to CVD risk screening in Sri Lanka that would likely improve equity while remaining efficient.</p>","PeriodicalId":23508,"journal":{"name":"Value in Health","volume":" ","pages":""},"PeriodicalIF":6.0,"publicationDate":"2025-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145309431","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Value in HealthPub Date : 2025-10-13DOI: 10.1016/j.jval.2025.09.3064
Ankur Pandya, Jinyi Zhu, Andrea Luviano, Lyndon P James, George Goshua
{"title":"A threshold inequality aversion parameter (TIAP) approach to interpret distributional cost-effectiveness analysis results.","authors":"Ankur Pandya, Jinyi Zhu, Andrea Luviano, Lyndon P James, George Goshua","doi":"10.1016/j.jval.2025.09.3064","DOIUrl":"https://doi.org/10.1016/j.jval.2025.09.3064","url":null,"abstract":"<p><strong>Objectives: </strong>Distributional cost-effectiveness analysis (DCEA) requires an inequality aversion parameter to calculate the equally distributed equivalent (EDE). The DCEA decision rule is to choose the strategy with the highest EDE. However, the exact value of the inequality aversion parameter is unknown for most health disparities and settings, hindering the use of DCEA in practice. We therefore propose calculating threshold inequality aversion parameter (TIAP) values in DCEAs that can be interpreted using existing data and conventions.</p><p><strong>Methods: </strong>We provide the rationale and methods for calculating the TIAP for pairwise and multi-strategy DCEAs. TIAPs can be estimated by finding the inequality aversion parameter that sets the EDEs of two competing strategies equal to each other. The interpretation of TIAPs requires a lower and upper bound of an inequality aversion parameter value range (LBIAR and UBAIR, respectively).</p><p><strong>Results: </strong>In a pairwise DCEA, a TIAP that is lower than the LBIAR can be interpreted as favoring the equity-improving strategy, whereas a TIAP that is higher than the UBIAR would favor the more cost-effective strategy. TIAPs between the LBIAR and UBIAR require additional context to determine the optimal strategy.</p><p><strong>Conclusions: </strong>The interpretation of TIAPs is analogous in some ways to how incremental cost-effectiveness ratios (ICERs) are used in conventional cost-effectiveness analysis; ICERs can be calculated without knowing the specific cost-effectiveness threshold, and are then interpreted using empirical estimates or conventions for the setting-specific cost-effectiveness threshold. Although further empirical data and attention toward inequality aversion parameters is needed, reporting TIAPs could enable widespread use of DCEA.</p>","PeriodicalId":23508,"journal":{"name":"Value in Health","volume":" ","pages":""},"PeriodicalIF":6.0,"publicationDate":"2025-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145303547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}