Value in Health最新文献

{"title":"Optimizing Monte Carlo Sampling in Health-Economic Modeling: Underlying Concepts and Parameter Definitions","authors":"Stéphane Roze MSc","doi":"10.1016/j.jval.2025.02.020","DOIUrl":"10.1016/j.jval.2025.02.020","url":null,"abstract":"","PeriodicalId":23508,"journal":{"name":"Value in Health","volume":"28 9","pages":"Pages 1454-1455"},"PeriodicalIF":6.0,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144668584","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}

{"title":"Measuring Aversion to Income-Related Health Inequality in Canada: An Equity-Efficiency Trade-Off Experiment.","authors":"Nicolas Iragorri, Shehzad Ali, Sharmistha Mishra, Beate H Sander","doi":"10.1016/j.jval.2025.06.021","DOIUrl":"10.1016/j.jval.2025.06.021","url":null,"abstract":"<p><strong>Objectives: </strong>To estimate the extent to which people living in Canada are averse to income-related health inequalities, a critical component for equity-informative economic evaluations but lacking in the Canadian context.</p><p><strong>Methods: </strong>We conducted 3 experiments among a sample of adults living in Canada to elicit value judgements about reducing income-related health inequality versus improving population health. Each experiment compared 2 programs: (experiment 1) universal and tailored vaccination, (experiment 2) nonspecific prevention programs, and (experiment 3) generic healthcare programs. The programs varied in terms of efficiency (additional life-years), and health inequality across income groups. Preferences were elicited using benefit trade-off analysis and were classified as follows: pro-rich (maximizing the health of individuals with the highest income), health maximizer (maximizing total health), weighted prioritarian (willing to trade some health to reduce inequalities), maximin (only improving the health of the individuals with the lowest income), and egalitarian (minimizing health inequalities at all costs).</p><p><strong>Results: </strong>We recruited 1000 participants per experiment. Preferences for the vaccination, prevention, and generic experiments were distributed as follows: pro-rich (aversion parameter <0): 31%, 22%, and 16%, respectively; health maximizers (aversion parameter = 0): 2%, 3%, and 2%, respectively; weighted prioritarians (aversion parameter > 0): 13%, 19%, and 22%, respectively; maximins (aversion parameter = ∞): 0%, 1%, and 3%, respectively; and egalitarian (aversion parameter undefined): 54%, 55%, and 57%, respectively. The median responses reflected a preference for minimizing income-related health inequalities across the 3 experiments.</p><p><strong>Conclusions: </strong>Our findings suggest a strong aversion to income-related health inequality among the respondents with more than half being classified as egalitarians.</p>","PeriodicalId":23508,"journal":{"name":"Value in Health","volume":" ","pages":""},"PeriodicalIF":6.0,"publicationDate":"2025-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144660315","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}

{"title":"Estimated True Out-of-Pocket Cost Changes From the Inflation Reduction Act on Medicare Part D Beneficiaries With Cancer.","authors":"Aryana Sepassi, Nico Gabriel, Sean D Sullivan, A Mark Fendrick, Jason A Zell, Dana B Mukamel","doi":"10.1016/j.jval.2025.07.003","DOIUrl":"10.1016/j.jval.2025.07.003","url":null,"abstract":"<p><strong>Objectives: </strong>To estimate changes in true out-of-pocket (TrOOP) spend from implementation of a $2000 cap for outpatient prescriptions as authorized by the 2022 Inflation Reduction Act (IRA) among Medicare Part D beneficiaries who received a diagnosis of cancer.</p><p><strong>Methods: </strong>Medicare beneficiaries who received a diagnosis of cancer and at least one Part D claim for a prescription drug to treat cancer in 2021 were identified from a 5% random sample of beneficiaries. Part D drug expenditures were extracted and adjusted to 2025 expenditures using previously published methods. Total annual TrOOP spend per beneficiary was estimated under 2 scenarios: (1) 2025 Part D design expected without any IRA policies implemented and (2) IRA design with a $2000 TrOOP cap. We reported the proportion of beneficiaries who would experience TrOOP spend changes with the cap and estimated differences in TrOOP spend for these individuals.</p><p><strong>Results: </strong>An estimated 42% of Part D beneficiaries with a diagnosis of cancer were predicted to have annual TrOOP spend of more than $2000 without the Part D cap. With the cap, these beneficiaries were expected to experience an average annual reduction of $8486 in TrOOP spend. Among these beneficiaries, with the TrOOP cap, those with hematologic cancers were expected to experience the greatest reduction ($10 846/beneficiary).</p><p><strong>Conclusions: </strong>Implementation of a Part D $2000 cap is expected to generate meaningful reduction in TrOOP spend for high-cost Medicare Part D beneficiaries who received a diagnosis of cancer.</p>","PeriodicalId":23508,"journal":{"name":"Value in Health","volume":" ","pages":""},"PeriodicalIF":6.0,"publicationDate":"2025-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144660314","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}

{"title":"Addressing Limitations in the Cost-Effectiveness Analysis of Digitally Supported Care Management for Dementia Caregivers","authors":"Danyang Liu MD","doi":"10.1016/j.jval.2025.03.022","DOIUrl":"10.1016/j.jval.2025.03.022","url":null,"abstract":"","PeriodicalId":23508,"journal":{"name":"Value in Health","volume":"28 9","pages":"Page 1457"},"PeriodicalIF":6.0,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144650694","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}

{"title":"Medicare Drug Price Negotiation Under the Inflation Reduction Act: Ensuring the Continuity of Critical Real-World Pharmaceutical Studies.","authors":"Abolfazl Sadeghi, Tyler J Varisco","doi":"10.1016/j.jval.2024.12.012","DOIUrl":"10.1016/j.jval.2024.12.012","url":null,"abstract":"","PeriodicalId":23508,"journal":{"name":"Value in Health","volume":" ","pages":""},"PeriodicalIF":6.0,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144650695","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}

{"title":"ELEVATE-GenAI: Reporting Guidelines for the Use of Large Language Models in Health Economics and Outcomes Research: An ISPOR Working Group Report.","authors":"Rachael L Fleurence, Dalia Dawoud, Jiang Bian, Mitchell K Higashi, Xiaoyan Wang, Hua Xu, Jagpreet Chhatwal, Turgay Ayer","doi":"10.1016/j.jval.2025.06.018","DOIUrl":"10.1016/j.jval.2025.06.018","url":null,"abstract":"<p><strong>Objectives: </strong>Generative artificial intelligence (AI), particularly large language models (LLMs), holds significant promise for health economics and outcomes research (HEOR). However, standardized reporting guidance for LLM-assisted research is lacking. This article introduces the ELEVATE-GenAI framework and checklist-reporting guidelines specifically designed for HEOR studies involving LLMs.</p><p><strong>Methods: </strong>The framework was developed through a targeted literature review of existing reporting guidelines, AI evaluation frameworks, and expert input from the ISPOR Working Group on Generative AI. It comprises 10 domains-including model characteristics, accuracy, reproducibility, and fairness and bias. The accompanying checklist translates the framework into actionable reporting items. To illustrate its use, the framework was applied to 2 published HEOR studies: one focused on a systematic literature review tasks and the other on economic modeling.</p><p><strong>Results: </strong>The ELEVATE-GenAI framework offers a comprehensive structure for reporting LLM-assisted HEOR research, while the checklist facilitates practical implementation. Its application to the 2 case studies demonstrates its relevance and usability across different HEOR contexts.</p><p><strong>Conclusions: </strong>Although the framework provides robust reporting guidance, further empirical testing is needed to assess its validity, completeness, usability, and generalizability across diverse HEOR use cases. The ELEVATE-GenAI framework and checklist address a critical gap by offering structured guidance for transparent, accurate, and reproducible reporting of LLM-assisted HEOR research. Future work will focus on extensive testing and validation to support broader adoption and refinement.</p>","PeriodicalId":23508,"journal":{"name":"Value in Health","volume":" ","pages":""},"PeriodicalIF":6.0,"publicationDate":"2025-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144627139","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}

{"title":"Provider Differences in Costs, Utilization, and Quality of Primary Care for Traumatic Brain Injury in the Military.","authors":"Patrick Richard, Daniel Gedeon, Jangho Yoon, Nilam Gibson, Marie-Rachelle Narcisse, Khalilhah McCants, Samya Ligonde, Taj Keshav, Thomas DeGraba","doi":"10.1016/j.jval.2025.06.016","DOIUrl":"10.1016/j.jval.2025.06.016","url":null,"abstract":"<p><strong>Objectives: </strong>Differences in costs, utilization, and quality of care provided by primary care physicians (PCPs) versus nurse practitioners (NPs) and physician assistants (PAs) for mild traumatic brain injury (mTBI) were examined to determine savings and address PCPs shortage.</p><p><strong>Methods: </strong>The Military Data Repository, which includes claims records for beneficiaries in the Military Health System, was used. Active-duty service members, retirees, and military dependents diagnosed with mTBI from 2011 to 2021 were included. Total cost, relative value units, and quality indicators of primary visits were dependent variables. The sample was stratified into patient-risk categories (high, low) and evaluation and management services (new and established patients).</p><p><strong>Results: </strong>Per military patient, PAs and NPs provided care at a lower cost than PCPs, with savings of $53.2 to $99.9 and $72.0 to $275.5, respectively. Per dependent patient, PAs provided care at a lower cost than PCPs, with savings of $64.3 to $91.1; NPs provided care at a lower cost than PCPs, with savings of $71.4 and $81.6. For quality for military patients, PAs ordered fewer brain and spine imaging (4.2%) and conducted fewer depression assessments (6%) than PCPs for patients with \"new/high\" risk. NPs conducted a higher proportion of neuropsychological testing (1.6%) for patients with \"existing/high\" risk compared with PCPs. For dependents, PAs conducted more health risk assessments and physical exams (2.5%) for patients with \"existing/low\" risk compared with PCPs. A total of 7.5% of patients with \"new/low\" risk treated by NPs compared to PCPs experienced fewer readmissions.</p><p><strong>Conclusions: </strong>NPs and PAs provide services for mTBI at lower costs than PCPs, with mixed results for quality.</p>","PeriodicalId":23508,"journal":{"name":"Value in Health","volume":" ","pages":""},"PeriodicalIF":6.0,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144609716","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}

{"title":"Poor Patient Care Outcomes and Nurse Job Outcomes Associated With Unfavorable Intensive Care Unit and Emergency Department Nurse Work Environments: Implications for Critical Care Medicine.","authors":"Kathryn Jane Muir, Daniela Golinelli, Kathryn Connell, Karen B Lasater, Matthew D McHugh","doi":"10.1016/j.jval.2025.06.017","DOIUrl":"10.1016/j.jval.2025.06.017","url":null,"abstract":"<p><strong>Objectives: </strong>Efforts to improve critical care outcomes are traditionally focused on intensive care unit (ICU) work environments, despite the reality that nurses in emergency departments (EDs) also deliver critical care. EDs and ICUs in the same hospitals tend to be differently resourced and may have different work environments as assessed by nurses. The objective of this study was to assess similarities in ED and ICU nurse work environment evaluations and associations with patient care and nurse job outcomes.</p><p><strong>Methods: </strong>Cross-sectional evaluation of ED and ICU nurses in 169 hospitals from a study of nurses licensed to work in New York and Illinois hospitals in the United States, the 2021 RN4CAST-New York/Illinois (NY/IL) survey, was administered electronically. K-means clustering classified hospitals into profiles on the basis of similarities in ED and ICU nurse work environment reports. Hospital-level regression models determined the association between the profiles and the following hospital-level outcomes, namely, patient care quality and safety, nurse burnout, job dissatisfaction, and intent to leave.</p><p><strong>Results: </strong>Three hospital profiles characterized similarities and differences in nurses' favorable and unfavorable work environments: \"ED and ICU nurse-favorable\" (n = 67 hospitals), and \"ED and ICU nurse-unfavorable\" (n = 42); and \"ED nurse-unfavorable\" (n = 60) indicating less favorable environments for ED than ICU nurses. Hospitals that were unfavorable for both ED and ICU nurses, or unfavorable for ED nurses only were associated with higher percentages of poorer outcomes, as compared to hospitals in which nurses in both settings reported favorable environments.</p><p><strong>Conclusions: </strong>To optimize critical care, better nurse work environments are needed in both ICUs and EDs.</p>","PeriodicalId":23508,"journal":{"name":"Value in Health","volume":" ","pages":""},"PeriodicalIF":6.0,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12372961/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144609715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Strong Preferences or Simplifying Heuristics? Using Internal Validity Tests and Latent Class Analysis to Better Understand Stated Preference Survey Results. A Case Example in Health Preferences Research.","authors":"Karen V MacDonald, Juan Marcos Gonzalez Sepulveda, F Reed Johnson, Deborah A Marshall","doi":"10.1016/j.jval.2025.06.015","DOIUrl":"10.1016/j.jval.2025.06.015","url":null,"abstract":"<p><strong>Objectives: </strong>Internal-validity tests (IVTs) are used in discrete choice experiments (DCEs) to check decision heuristics, choice logic, response consistency, and tradeoffs. There is no standard for how many IVT failures classify respondents as having unacceptable data quality or how to account for failures in choice models. We assessed IVT failures and used latent class analysis to identify choice patterns consistent with statistically informative DCE data.</p><p><strong>Methods: </strong>We conducted a DCE with 4 attributes (3 ordered), 12 experimental choice tasks, and 2 constructed IVT choice tasks. Respondents with IVT failures were asked questions about their choices. We evaluated preference heterogeneity controlling for attribute dominance using a 4-class latent class model with attribute-specific alternative-specific constants and compared with a 1-class model without attribute-specific alternative-specific constants.</p><p><strong>Results: </strong>Of the 201 respondents, 34 had IVT failures of which 38% to 42% provided reasons other than nonattendance or simplifying heuristics. Comparing the 4-class latent class model no-dominance class with the 1-class model, the coefficients of 2 ordered attributes were significantly different, illustrating potential bias due to simplifying heuristics. Attribute-specific dominance class probability varied by number of choice tasks respondents exhibited attribute dominance on, ranging from 8 to 10 for a class-membership probability of 50%.</p><p><strong>Conclusions: </strong>IVT \"failures\" should be interpreted as unexpected responses warranting further inquiry. Including understanding questions could yield insights about stated preferences; however, these increase respondent burden and may not explain simplifying heuristics. Single subjective \"rules of thumb\" for attribute dominance thresholds may not be adequate. Latent class models controlling for attribute dominance are a data-driven approach that should be considered to assess simplifying heuristics and attribute dominance thresholds.</p>","PeriodicalId":23508,"journal":{"name":"Value in Health","volume":" ","pages":""},"PeriodicalIF":6.0,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144601670","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}

{"title":"Achieving Patient-Centered Value/Health Technology Assessment: Recommendations From a Multistakeholder eDelphi Panel.","authors":"Julia F Slejko, Tara A Lavelle, Joe Vandigo, Omar A Escontrías, Silke C Schoch, Elisabeth M Oehrlein","doi":"10.1016/j.jval.2025.06.014","DOIUrl":"10.1016/j.jval.2025.06.014","url":null,"abstract":"<p><strong>Objectives: </strong>Current methodological guidelines for value/health technology assessment (V/HTA) and cost-effectiveness analysis describe traditional approaches not originally created to be patient centered. The objective of this study was to identify opportunities for guidance and develop a set of consensus recommendations on methods and needs for patient-centered V/HTA, including identifying and collecting data inputs, results reporting, and future priority topics.</p><p><strong>Methods: </strong>This study included multiple phases: (1) listening sessions with 10 patient group representatives to elicit priorities for patient-centered data elements for V/HTA; (2) leverage findings from step 1 to inform qualitative interviews with 10 health economists to guide the development of an eDelphi instrument; and (3) use the findings from step 1 and 2 to conduct an eDelphi exercise with multistakeholder participants to develop consensus recommendations that guide patient-centered V/HTA.</p><p><strong>Results: </strong>After 2 Delphi rounds, 28 statements achieved consensus (≥80% agreement); 2 statements did not achieve consensus (<80% agreement). The recommendations included a need for data that more broadly reflect the impacts, both inside and outside the healthcare sector, relevant to patients and more accurately reflect the real-world natural history of disease. There was consensus on the need for patient input throughout the assessment process, including plain-language reporting that improves inclusion of patient audiences.</p><p><strong>Conclusions: </strong>Multistakeholder consensus on the recommendations presented serve as a basis for future work toward progressing patient-centered V/HTA.</p>","PeriodicalId":23508,"journal":{"name":"Value in Health","volume":" ","pages":""},"PeriodicalIF":6.0,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144601668","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}