Applied Health Economics and Health Policy最新文献

{"title":"A Head-On Comparison of EQ-VT- and Crosswalk-Based EQ-5D-5L Value Sets.","authors":"Henry Bailey, Bram Roudijk","doi":"10.1007/s40258-025-00954-z","DOIUrl":"https://doi.org/10.1007/s40258-025-00954-z","url":null,"abstract":"<p><strong>Background: </strong>No systematic country-level comparison has been undertaken between crosswalk- and EQ-VT-derived EQ-5D-5L value sets. Crosswalk values can differ from EQ-VT-based EQ-5D-5L value sets owing to valuation protocols, changes in societal preferences over time, and a change in the label of the highest level on mobility in moving from EQ-5D-3L to EQ-5D-5L. This study aimed to compare the five-level (5L) crosswalk and EQ-VT value sets to explore differences between them at the country level.</p><p><strong>Methods: </strong>From the countries with both time trade-off (TTO)- or discrete choice experiment (DCE) + TTO-based EQ-5D-3L value sets and EQ-VT-based EQ-5D-5L value sets, 19 pairs of EQ-5D-3L/EQ-5D-5L sets were found. For each of these EQ-5D-3L value sets, 5L crosswalk sets were developed and compared with the corresponding national EQ-5D-5L valuation set using correlation analysis, ranges, values of specific states, Bland-Altman plots, and scatter plots. Three of the countries have EQ-5D-3L and EQ-5D-5L valuation data for the same set of respondents. These three cases were analyzed separately, as they provide a \"true\" test of the differences between the two value sets.</p><p><strong>Results: </strong>Spearman correlation between the crosswalk and valuation sets ranged from 0.831 to 0.989, being below 0.9 in 11 pairs of value sets. The difference in the percentage of negative values ranged from +22.5 to -18.8%, and the difference in the ranges within each pair of value sets ranged from +42.7 to -18.4%. The average mean absolute difference of values (crosswalk versus EQ-VT) was 0.149. This was below 0.1 in only 5 of the 19 EQ-VT/crosswalk set pairs. For the states comprising one level 5 and four level 1s, no country preserved its ranking of importance of the five dimensions in moving from crosswalk to EQ-VT values. Most of the Bland-Altman plots and scatterplots revealed a pattern that placed states with the highest level on mobility as a separate band from other states.</p><p><strong>Discussion: </strong>All of the criteria showed poor agreement between the crosswalk- and EQ-VT-based value sets. The differences in labels for the most extreme response option for the mobility dimension leads to substantial differences in values between these value sets.</p><p><strong>Conclusions: </strong>Crosswalk and EQ-VT value sets should not be used interchangeably, except under circumstances where it is not possible or feasible to conduct a direct EQ-5D-5L valuation study.</p>","PeriodicalId":8065,"journal":{"name":"Applied Health Economics and Health Policy","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143603668","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"GaitSmart Rehabilitation Exercise Programme for Gait and Mobility Issues: A NICE Medical Technologies Guidance.","authors":"Huey Yi Chong, Michal Pruski, Megan Dale, Rhys Morris","doi":"10.1007/s40258-025-00955-y","DOIUrl":"https://doi.org/10.1007/s40258-025-00955-y","url":null,"abstract":"<p><p>GaitSmart (Dynamic Metrics Ltd) is a class I CE-marked sensor-based digital technology designed to measure lower limb movement via sensors placed on the body. GaitSmart aims to identify any problems with gait, and provide a personalised rehabilitation programme via the integrated vGym app. The company identified people referred for knee or hip replacement and people at risk of falling as potentially being able to benefit from GaitSmart. The clinical evidence identified was limited in its applicability to the scope of the assessment, and there was large variability in the comparators used in these studies and in the current care pathways, especially for people at risk of falls. There is some limited evidence that patients like the report generated by the technology and found it helpful in understanding their condition. Clinical experts thought GaitSmart had the potential to improve outcomes for patients and could be used in the community setting by a range of healthcare professionals. Economic modelling over a 1-year time horizon from a UK National Health Service (NHS) perspective for the falls model and a 17-week horizon for the rehabilitation model indicate that GaitSmart is cost saving; however, this is dependent on the model of standard care. Where GaitSmart is delivered by trained healthcare assistants, it would lead to a reduction in staff time costs compared to most alternative standard care options. Uncertainty is greater in the falls model given the high variability in standard care. In April 2024, the National Institute for Health and Care Excellence recommended that GaitSmart can be used to treat gait and mobility issues in adults at risk of falls, while more evidence is gathered. For adults having hip or knee replacements, access to GaitSmart should be via the company, research or non-core NHS funding, with appropriate management of any risks.</p>","PeriodicalId":8065,"journal":{"name":"Applied Health Economics and Health Policy","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143596037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"New Horizons? Assessing General Public Preferences for a Wellbeing Economy in the Post-COVID-19 World.","authors":"Rachel Milte, Matthew Crocker, Gang Chen, Gordon Duff, Julie Ratcliffe","doi":"10.1007/s40258-025-00951-2","DOIUrl":"https://doi.org/10.1007/s40258-025-00951-2","url":null,"abstract":"<p><strong>Objective: </strong>As societies emerge from the COVID-19 pandemic, governments are increasingly moving away from a focus on economic growth at any cost towards the principles of a wellbeing economy, focused on achieving a more equitable distribution of wealth and wellbeing. This study aimed to assess the relative importance to the Australian general public of the key principles of a wellbeing economy and to investigate heterogeneity in preferences between demographic subgroups.</p><p><strong>Methods: </strong>An online survey was developed and delivered to a general public sample of 2042 Australian adults (aged 18 years and above). Respondents were invited to rank the key principles of a wellbeing economy (dignity, nature and climate, social connection, fairness and participation) plus two additional traditional economic indicators of societal success ('economic growth' and 'economic prosperity') in order of their relative importance for informing future policy directions. Data analysis was conducted using simple summative scoring, which involved the use of a point system allocated to rankings as a dependent variable. In addition, a rank-ordered logit model was used to explore preferences for the entire sample and subgroups defined by key socio-demographic characteristics.</p><p><strong>Results: </strong>'Dignity' (people have enough to live in comfort, safety and happiness) and 'fairness' (equal opportunity for all Australians and the gap between richest and poorest greatly reduced) were ranked as the most important priorities for the total sample and for key socio-demographic subgroups differentiated by age, level of education and level of socio-economic advantage. Traditional economic indicators of societal success including 'economic prosperity' and 'economic growth' were considered important but generally ranked below the principles of 'dignity' and 'fairness'.</p><p><strong>Conclusions: </strong>The findings indicate that government movements away from traditional economic indicators and towards new broader wellbeing economy measures of societal success are likely to be supported by the general public.</p>","PeriodicalId":8065,"journal":{"name":"Applied Health Economics and Health Policy","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143536409","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Is the Use of Unanchored Matching-Adjusted Indirect Comparison Always Superior to Naïve Indirect Comparison on Survival Outcomes? A Simulation Study.","authors":"Ying Liu, Xiaoning He, Jia Liu, Jing Wu","doi":"10.1007/s40258-025-00952-1","DOIUrl":"https://doi.org/10.1007/s40258-025-00952-1","url":null,"abstract":"<p><strong>Objective: </strong>To compare the performance of matching-adjusted indirect comparison (MAIC) and naïve indirect comparison (NIC) under a wide range of data scenarios on survival outcome.</p><p><strong>Methods: </strong>A simulation study included 729 (3⁶) single-arm trial data scenarios, which were created by performing a three-level full factorial arrangement of six situational variables, including individual patient data (IPD) sample size, aggregate data (AgD) sample size, covariate strength, covariate correlation, covariate overlap, and relative treatment effect. In each scenario, 1000 repetitions of simulated datasets were generated using the Monte Carlo approach. MAIC and NIC methods were used to estimate the relative treatment effect of each simulated dataset. The performance was evaluated in terms of bias, empirical standard error (ESE), mean squared error (MSE), and confidence interval coverage, respectively.</p><p><strong>Results: </strong>MAIC yielded relatively unbiased estimates of relative treatment effect compared with NIC in most scenarios, with better coverage and MSE but higher ESE. None of the situational variables had a significant impact on the bias and coverage of MAIC. However, increasing IPD sample size and covariate overlap significantly reduced the ESE and MSE of MAIC. In scenarios with low covariate overlap and high covariate strength, the bias of MAIC was larger and even greater than that of NIC.</p><p><strong>Conclusions: </strong>The performance of MAIC consistently demonstrates advantage over NIC across various scenarios. MAIC often provides more unbiased estimates and achieves confidence interval coverage close to nominal values compared with NIC. While MAIC may exhibit higher ESE in specific scenarios, this additional uncertainty can offer a more accurate reflection of variability, enhancing the robustness of the results. Researchers should thoroughly comprehend the influencing factors and interactions affecting the performance of these methods and judiciously apply research findings.</p>","PeriodicalId":8065,"journal":{"name":"Applied Health Economics and Health Policy","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2025-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143482011","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cost-Utility Analysis of Genomic Profiling in Directing Targeted Therapy in Advanced NSCLC in Thailand.","authors":"Saowalak Turongkaravee, Surakit Nathisuwan, Thanyanan Baisamut, Jennis Meanwatthana","doi":"10.1007/s40258-025-00950-3","DOIUrl":"https://doi.org/10.1007/s40258-025-00950-3","url":null,"abstract":"<p><strong>Background: </strong>Sequential next-generation sequencing (NGS) testing has demonstrated cost-effectiveness in guiding targeted therapy with tyrosine kinase inhibitors (TKIs) for advanced non-small cell lung cancer (aNSCLC) in developed countries. However, its cost-effectiveness in developing countries remains uncertain.</p><p><strong>Objective: </strong>The aim was to conduct a cost-utility analysis comparing sequential NGS testing with the current approach of single epidermal growth factor receptor (EGFR) testing combined with first-line targeted therapy, as implemented under Thailand's Universal Health Coverage scheme for aNSCLC.</p><p><strong>Method: </strong>Hybrid decision tree and Markov models were developed to estimate the lifetime costs and quality-adjusted life years (QALYs) associated with each strategy. The models simulate cohorts of aNSCLC patients who receive platinum-based chemotherapy or TKIs based on identified gene alterations. Patients enter the model at 60 years of age. The incremental cost-effectiveness ratio (ICER) was computed from a societal perspective. The analysis employed a lifetime horizon and discounted costs and outcomes at a rate of 3%. Furthermore, uncertainty and scenario analyses were conducted.</p><p><strong>Findings: </strong>A sequential NGS testing strategy could identify an additional 19% of patients with biomarker-positive findings who subsequently received biomarker-driven targeted therapy compared to a single EGFR testing strategy. The number needed to screen to identify a single gene mutation and administer first-line TKI was six for the sequential NGS testing strategy. Compared to the single EGFR testing, the ICER of the sequential NGS testing strategy was 1,851,150 THB/QALY (US$51,335). At a willingness-to-pay threshold of 160,000 THB/QALY (US$4437), the single EGFR testing strategy demonstrated 100% cost-effectiveness. In contrast, the sequential NGS testing was not deemed cost-effective. The sensitivity of the ICER was influenced by the overall survival rates associated with anaplastic lymphoma kinase (ALK) inhibitors and platinum-based chemotherapy.</p><p><strong>Interpretation: </strong>Sequential NGS testing identified a greater number of patients with aNSCLC eligible for targeted therapies, resulting in improved survival rates and enhanced QALYs compared to single EGFR testing. However, in the context of Thailand, sequential NGS testing was not cost-effective. The single EGFR testing strategy emerged as the most cost-effective option for guiding first-line targeted therapy.</p>","PeriodicalId":8065,"journal":{"name":"Applied Health Economics and Health Policy","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143363317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting Health Utilities Using Health Administrative Data: Leveraging Survey-linked Health Administrative Data from Ontario, Canada.","authors":"Yue Niu, Nazire Begen, Guangyong Zou, Sisira Sarma","doi":"10.1007/s40258-025-00947-y","DOIUrl":"https://doi.org/10.1007/s40258-025-00947-y","url":null,"abstract":"<p><strong>Background: </strong>The quality-adjusted life year (QALY) is widely used to measure health outcome that combines the length of life and health-related quality of life (HRQoL). To be a reliable QALY measure, HRQoL measurements with a preference-based scoring algorithm need to be converted into health utilities on a scale from zero (dead) to one (perfect health). However, preference-based health utility data are often not available. We address this gap by developing a predictive model for health utilities.</p><p><strong>Objectives: </strong>To develop a predictive model for health utilities using available demographic and morbidity variables in a health administrative dataset for non-institutionalised populations in Ontario, Canada.</p><p><strong>Methods: </strong>The data were obtained from the 2009 to 2010 Canadian Community Health Survey containing Health Utilities Index Mark3 (HUI3), a generic multi-attribute preference-based health utility instrument linked with Ontario health administrative (OHA) data that were collected for administrative or billing purposes for patient encounters with the health care system. We employed four regression models (linear, Tobit, single-part beta mixture, and two-part beta mixture) and a calibration technique to identify the best-fit regression model.</p><p><strong>Results: </strong>Our findings indicate that the two-part beta mixture model is the best-fit for predicting health utilities in the OHA data. The proposed predictive model reflects the original distribution of HUI3 in the population.</p><p><strong>Conclusion: </strong>Our proposed predictive model generates reasonably accurate health utility predictions from OHA data. Our model-based prediction approach is a useful strategy for real-world applications, particularly when preference-based utility data are unavailable.</p>","PeriodicalId":8065,"journal":{"name":"Applied Health Economics and Health Policy","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143254528","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Health Economic Evaluations of Obesity Interventions: Expert Views on How We Can Identify, Interpret, Analyse and Translate Effects","authors":"Samira B. Jabakhanji,&nbsp;Gintare Valentelyte,&nbsp;Fabian Manke-Reimers,&nbsp;Vidar Halsteinli,&nbsp;Rønnaug Ødegård,&nbsp;Adam Martin,&nbsp;Grace O’Malley,&nbsp;Jan Sorensen,&nbsp;Emilia Hagman","doi":"10.1007/s40258-025-00946-z","DOIUrl":"10.1007/s40258-025-00946-z","url":null,"abstract":"<div><p>Economic evaluations of obesity interventions are critical to informing policymakers and clinical practitioners about best-value prevention and treatment interventions. However, existing studies often fail to measure appropriate outcomes over sufficient time periods and to adequately address the complexity of data, environments and outcomes. An international, multidisciplinary workshop in Ireland (May 2023) addressed these issues through scientific presentations on obesity modelling, group discussions and interactive small-group exercises. Nineteen presenters and participants co-created a list of research needs, priorities and strategies for the long-term study of obesity and its complications. To support availability of relevant outcome and cost data for health economic analyses, participants highlighted a need to define standards for data collection, data sharing, modelling, and integrating a systems perspective. For example, regarding data collection, careful consideration must be given to selecting valid and relevant health-related outcomes for determining future health risk. Although these issues have been previously highlighted, they remain critical barriers to comprehensive economic obesity studies. To identify best-value obesity interventions, researchers should prioritise strategies to overcome these barriers. This includes early engagement with multidisciplinary stakeholders to integrate diverse perspectives. Developing infrastructure to support international collaborations between researchers, policymakers and patient representatives was also recommended. Additionally, establishing best-practice guidelines could help researchers navigate the complexities of obesity data, environments and outcomes, particularly in data-scarce research environments. The creation of a core outcomes set for obesity would standardise measures for economic evaluations, thereby facilitating more robust cross-country comparisons of intervention effects and improving the evidence base and overall quality of future obesity research.</p></div>","PeriodicalId":8065,"journal":{"name":"Applied Health Economics and Health Policy","volume":"23 2","pages":"161 - 169"},"PeriodicalIF":3.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s40258-025-00946-z.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143073496","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Contextual Factors that Influence Antibiotic Prescribing: A Discrete Choice Experiment of GP Registrars","authors":"Gregory Merlo,&nbsp;Lisa Hall,&nbsp;Parker Magin,&nbsp;Amanda Tapley,&nbsp;Katie J. Mulquiney,&nbsp;Alison Fielding,&nbsp;Andrew Davey,&nbsp;Joshua Davies,&nbsp;Mieke van Driel","doi":"10.1007/s40258-025-00944-1","DOIUrl":"10.1007/s40258-025-00944-1","url":null,"abstract":"<div><h3>Introduction</h3><p>Antimicrobial resistance is a global emergency related to overprescribing of antibiotics. Few studies have explored how prescribing behaviours may change as the consequence of changing resistance. Understanding how contextual factors influence antibiotic prescribing will facilitate improved communication strategies to promote appropriate antibiotic prescribing. We aimed to develop and conduct a discrete choice experiment (DCE) to measure how contextual factors influence intended antibiotic prescribing of general practitioner (GP) registrars.</p><h3>Methods</h3><p>Factors included as attributes in the DCE were level of antibiotic resistance, requirement for an authority to prescribe, existence of a Practice Incentives Program (PIP) for low prescribing and supervisor support for low prescribing. The survey was administered in an online format for GP registrars undergoing training between 2020 and 2021. Regression analysis using a conditional logit model with interaction effects was used on the basis of the assumptions of independence of irrelevant alternatives, independence of error terms and no preference heterogeneity.</p><h3>Results</h3><p>In total, 617 unique respondents answered at least one choice set question. Respondents showed significant preference for avoiding prescribing antibiotics when antibiotic resistance was 25–35% or 40–60% compared with 5–8%. There was also a significant preference for avoiding prescribing when an authority to prescribe was required, or when there was supervisory support of low antibiotic prescribing. In the main effects analysis, respondents were significantly less likely to choose a prescribing option if there was a PIP; however, when interaction effects were included in the regression analysis there was a significant interaction between PIP and resistance rates, but the preference weights for PIP was no longer significant.</p><h3>Conclusions</h3><p>Knowledge about community resistance impacts the stated intention of GP registrars to prescribe antibiotics. The use of the DCE may have made it possible to determine factors influencing prescribing that would not be detected using other survey methods. These findings provide guidance for producing, explaining and communicating issues regarding antibiotic prescribing to GP registrars.</p></div>","PeriodicalId":8065,"journal":{"name":"Applied Health Economics and Health Policy","volume":"23 2","pages":"311 - 317"},"PeriodicalIF":3.1,"publicationDate":"2025-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s40258-025-00944-1.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143031649","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Approaches to Incorporation of Preferences into Health Economic Models of Genomic Medicine: A Critical Interpretive Synthesis and Conceptual Framework.","authors":"Hadley Stevens Smith, Dean A Regier, Ilias Goranitis, Mackenzie Bourke, Maarten J IJzerman, Koen Degeling, Taylor Montgomery, Kathryn A Phillips, Sarah Wordsworth, James Buchanan, Deborah A Marshall","doi":"10.1007/s40258-025-00945-0","DOIUrl":"https://doi.org/10.1007/s40258-025-00945-0","url":null,"abstract":"<p><strong>Introduction: </strong>Genomic medicine has features that make it preference sensitive and amenable to model-based health economic evaluation. Preferences of patients, caregivers, and clinicians related to the uptake and delivery of genomic medicine technologies and services that are not captured in health state utility weights can affect the intervention's cost-effectiveness and budget impact. However, there is currently no established or agreed-on approach for integrating preference information into economic evaluations. The objective of this study was to explore approaches for incorporating preferences into model-based economic evaluations of genomic medicine and to develop a conceptual framework to consider preferences in health economic models.</p><p><strong>Methods: </strong>We conducted a critical interpretive synthesis of published literature guided by the following question: how have preferences been incorporated into model-based economic evaluations of genomic medicine interventions? We integrated findings from the literature and expert opinion to develop a conceptual framework of ways in which preferences influence economic value in the context of genomic medicine.</p><p><strong>Results: </strong>Our synthesis included 14 articles. Revealed and stated preference data were used to estimate choice probabilities and to value outcomes. Our conceptual framework situates preference data in the context of health system, patient, clinician, and family characteristics. Preference data were sourced from clinicians, patients and families impacted by a condition or intervention, and the general public. Evaluations employed various types of models, including discrete event simulation, microsimulation, Markov, and decision tree models.</p><p><strong>Conclusion: </strong>When evaluating the broad benefits and costs of implementing new interventions, sufficiently accounting for preferences in the form of model inputs and valuation of outcomes in economic evaluations is important to avoid biased implementation decisions. Incorporation of preference data may improve alignment between predicted and real-world uptake and more accurately estimate welfare impacts, and this study provides critical insights to support researchers who seek to incorporate preference information into model-based health economic evaluations.</p>","PeriodicalId":8065,"journal":{"name":"Applied Health Economics and Health Policy","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142998897","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Productivity Losses due to Health Problems Arising from COVID-19 Pandemic: A Systematic Review of Population-Level Studies Worldwide","authors":"Paweł Niewiadomski,&nbsp;Marta Ortega-Ortega,&nbsp;Błażej Łyszczarz","doi":"10.1007/s40258-024-00935-8","DOIUrl":"10.1007/s40258-024-00935-8","url":null,"abstract":"<div><h3>Aim</h3><p>To systematically review the evidence on productivity losses due to health problems arising from the COVID-19 pandemic based on evidence from population-level studies.</p><h3>Methods</h3><p>Following PRISMA statement, we conducted a systematic review using Medline, Embase, Scopus, Web of Science, EconLit, WHO COVID-19 Research and EuropePMC databases and a grey literature search. We included population-level studies using secondary data and qualitatively assessed eligible studies. For a quantitative cross-study comparison, we calculated losses in 2020 international dollars and as a share of gross domestic product. PROSPERO registration number: CRD42023478059.</p><h3>Results</h3><p>Thirty-eight studies were eligible for review, most of which reported losses in high-income countries and the European region. COVID-19 was a focus of 33 studies while 3 studies investigated losses from both long COVID and excess mortality. The Human Capital Approach dominated (30 studies) and no study used the Friction Cost Approach. Most studies (84%) reported on premature mortality losses and a quarter provided estimates of losses due to absenteeism. Of the 33 studies eligible for quantitative comparison, we found that the productivity losses ranged from 0 to 2.1% of gross domestic product; the greatest losses were in the high-income countries and for those aged 40–59 years; and losses among men contributed to around 3/4 of the total burden.</p><h3>Conclusion</h3><p>The available evidence on the topic is limited, particularly considering the methodological approaches used. Thus, more research is needed to reach a more comprehensive understanding of economy-level productivity losses resulting from the recent COVID-19 pandemic.</p></div>","PeriodicalId":8065,"journal":{"name":"Applied Health Economics and Health Policy","volume":"23 2","pages":"231 - 251"},"PeriodicalIF":3.1,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142998959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}