Pub Date : 2025-02-01DOI: 10.1016/j.jval.2024.11.010
Nancy J. Devlin PhD , Giselle Abangma MSc , Andrew Lloyd DPhil , David Parkin DPhil , Andrew Briggs DPhil
Objectives
Articles reporting value sets typically only report the standard errors (SEs) around each estimated coefficient in value set models. This is important information but does not help those building cost-effectiveness models, who need to know the uncertainty around the values of health states to conduct sensitivity analyses. This report’s aim is to demonstrate how SEs around health-related quality of life values can be calculated, using the example of the UK EQ-5D-3L value set.
Methods
We show how information from a model’s variance/covariance matrix can be used to estimate SEs for every health-state value, whether it is part of the modeling data set or not. Data from the Measurement and Valuation of Health study were used to replicate the original UK value set and the variance/covariance matrix and to produce SEs around the values for all 243 EQ-5D-3L states.
Results
The range of the SEs is small compared with the range of the health-state values but is conditional on a correct model specification and may be sensitive to alternative specifications.
Conclusions
Reporting these SEs should become routine practice in reporting value sets, to ensure that users are provided with information on parameter uncertainty. These SEs only capture one specific aspect of the sources of uncertainty around health-related quality of life values but represent a first step toward a more complete account of uncertainty in the preference weights used to estimate quality-adjusted life-years.
{"title":"Reporting Uncertainty Around Health-State Values: A Standard Method and Worked Example","authors":"Nancy J. Devlin PhD , Giselle Abangma MSc , Andrew Lloyd DPhil , David Parkin DPhil , Andrew Briggs DPhil","doi":"10.1016/j.jval.2024.11.010","DOIUrl":"10.1016/j.jval.2024.11.010","url":null,"abstract":"<div><h3>Objectives</h3><div>Articles reporting value sets typically only report the standard errors (SEs) around each estimated coefficient in value set models. This is important information but does not help those building cost-effectiveness models, who need to know the uncertainty around the values of health states to conduct sensitivity analyses. This report’s aim is to demonstrate how SEs around health-related quality of life values can be calculated, using the example of the UK EQ-5D-3L value set.</div></div><div><h3>Methods</h3><div>We show how information from a model’s variance/covariance matrix can be used to estimate SEs for every health-state value, whether it is part of the modeling data set or not. Data from the Measurement and Valuation of Health study were used to replicate the original UK value set and the variance/covariance matrix and to produce SEs around the values for all 243 EQ-5D-3L states.</div></div><div><h3>Results</h3><div>The range of the SEs is small compared with the range of the health-state values but is conditional on a correct model specification and may be sensitive to alternative specifications.</div></div><div><h3>Conclusions</h3><div>Reporting these SEs should become routine practice in reporting value sets, to ensure that users are provided with information on parameter uncertainty. These SEs only capture one specific aspect of the sources of uncertainty around health-related quality of life values but represent a first step toward a more complete account of uncertainty in the preference weights used to estimate quality-adjusted life-years.</div></div>","PeriodicalId":23508,"journal":{"name":"Value in Health","volume":"28 2","pages":"Pages 191-196"},"PeriodicalIF":4.9,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142855266","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}
Pub Date : 2025-02-01DOI: 10.1016/j.jval.2024.12.005
Sanne J.J.P.M. Metsemakers MSc , Rosella P.M.G. Hermens PhD , Geneviève I.C.G. Ector PhD , Nicole M.A. Blijlevens PhD , Tim M. Govers PhD
Objectives
The management of chronic myeloid leukemia (CML) now includes dose reduction (DR) and treatment-free remission (TFR). Evaluating the cost-effectiveness of lifelong-prescribed expensive tyrosine kinase inhibitors (TKIs) for CML is crucial. Prior cost-effectiveness evaluations state that imatinib is the favorable frontline TKI. Some of these evaluations address TFR, but not DR, nor aging and second-generation (2G)-TKIs upcoming patent expirations. This study evaluates the cost-effectiveness of frontline TKIs for CML patients including these factors.
Methods
This Markov model evaluates the cost-effectiveness of frontline TKIs for newly diagnosed patients with CML using 17 health states. Transition probabilities, costs, and utilities were derived from literature data. Incremental cost-effectiveness ratios were calculated. Sensitivity analysis and model validation were conducted.
Results
Nilotinib is most effective (20.13 quality-adjusted life-years [QALYs]) and imatinib is least effective (17.25 QALYs) for the model including TFR and DR. Imatinib was favored over dasatinib (89.80%), nilotinib (62.70%), and bosutinib (78.40%), at a willingness-to-pay threshold of €80 000 per QALY. Without TFR and DR, fewer QALYs were generated. For patients at the age of 70 years, imatinib has a high probability of being more cost-effective than dasatinib, nilotinib, and bosutinib. With 50% 2GTKI cost reductions, nilotinib is considered more cost-effective compared with imatinib (98.40%), dasatinib (94.80%), and bosutinib (68.90%).
Conclusions
The findings indicate that 2GTKIs are more effective in generating QALYs, including for older (age >70 years) patients. Given the current TKI prices, imatinib remains cost-effective. Including DR and TFR in CML management generates more QALYs. Cost reductions from expected 2GTKIs patent expirations will greatly increase their cost-effectiveness. Results may inform 2GTKIs cost discussions after patent expiration, potentially broadening global availability. The findings also emphasize the importance of aiming for TFR and DR in CML management.
{"title":"The Cost-Effectiveness of Frontline Tyrosine Kinase Inhibitors for Patients With Chronic Myeloid Leukemia: In Pursuit of Treatment-Free Remission and Dose Reduction","authors":"Sanne J.J.P.M. Metsemakers MSc , Rosella P.M.G. Hermens PhD , Geneviève I.C.G. Ector PhD , Nicole M.A. Blijlevens PhD , Tim M. Govers PhD","doi":"10.1016/j.jval.2024.12.005","DOIUrl":"10.1016/j.jval.2024.12.005","url":null,"abstract":"<div><h3>Objectives</h3><div>The management of chronic myeloid leukemia (CML) now includes dose reduction (DR) and treatment-free remission (TFR). Evaluating the cost-effectiveness of lifelong-prescribed expensive tyrosine kinase inhibitors (TKIs) for CML is crucial. Prior cost-effectiveness evaluations state that imatinib is the favorable frontline TKI. Some of these evaluations address TFR, but not DR, nor aging and second-generation (2G)-TKIs upcoming patent expirations. This study evaluates the cost-effectiveness of frontline TKIs for CML patients including these factors.</div></div><div><h3>Methods</h3><div>This Markov model evaluates the cost-effectiveness of frontline TKIs for newly diagnosed patients with CML using 17 health states. Transition probabilities, costs, and utilities were derived from literature data. Incremental cost-effectiveness ratios were calculated. Sensitivity analysis and model validation were conducted.</div></div><div><h3>Results</h3><div>Nilotinib is most effective (20.13 quality-adjusted life-years [QALYs]) and imatinib is least effective (17.25 QALYs) for the model including TFR and DR. Imatinib was favored over dasatinib (89.80%), nilotinib (62.70%), and bosutinib (78.40%), at a willingness-to-pay threshold of €80 000 per QALY. Without TFR and DR, fewer QALYs were generated. For patients at the age of 70 years, imatinib has a high probability of being more cost-effective than dasatinib, nilotinib, and bosutinib. With 50% 2GTKI cost reductions, nilotinib is considered more cost-effective compared with imatinib (98.40%), dasatinib (94.80%), and bosutinib (68.90%).</div></div><div><h3>Conclusions</h3><div>The findings indicate that 2GTKIs are more effective in generating QALYs, including for older (age >70 years) patients. Given the current TKI prices, imatinib remains cost-effective. Including DR and TFR in CML management generates more QALYs. Cost reductions from expected 2GTKIs patent expirations will greatly increase their cost-effectiveness. Results may inform 2GTKIs cost discussions after patent expiration, potentially broadening global availability. The findings also emphasize the importance of aiming for TFR and DR in CML management.</div></div>","PeriodicalId":23508,"journal":{"name":"Value in Health","volume":"28 2","pages":"Pages 224-232"},"PeriodicalIF":4.9,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142898558","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}
Pub Date : 2025-02-01DOI: 10.1016/j.jval.2024.09.008
Dawn Lee MMath, MSc , Zain Ahmad , Caroline Farmer PhD , Maxwell S. Barnish PhD , Alan Lovell PhD , G.J. Melendez-Torres DPhil, MPH, RN
Objectives
This study examines the impact of slippage in hazard ratios (tending toward the null over subsequent datacuts) for overall survival for combination treatment with a PD-(L)-1 inhibitor and a tyrosine kinase inhibitor in advanced renal cell carcinoma.
Methods
Four trials’ Kaplan-Meier curves were digitized over several datacuts and fitted with standard parametric curves. Accuracy and consistency of early data projections were calculated versus observed restricted mean survival time and fitted lifetime survival from the longest follow-up datacut. The change in economically justifiable price (eJP) was calculated fitting the same curve to both arms, using an assumed average utility of 0.7 and willingness-to-pay threshold of £30 000 per quality-adjusted life-year. The eJP represents the lifetime justifiable price increment for the new treatment, including differences in drug-, administration-, and disease-related costs.
Results
Slippage in hazard ratios was observed in trials with longer follow-up, potentially influenced by subsequent PD-(L)-1 use after tyrosine kinase inhibitor monotherapy, early stoppage of PD-(L)-1, and development of resistance. Lognormal and log-logistic curves were more likely to overpredict the observed result; Gompertz and gamma underpredicted. Statistical measures of goodness of fit did not select the curves that resulted in the RMST closest to what was observed in the final data cut. Large differences in incremental mean life-years were observed between even the penultimate and final datacuts for most of the fitted curves, meaningfully affecting the eJP.
Conclusions
This work demonstrates the challenge in predicting treatment benefits with novel therapies using immature data. Incorporating information on the impact of subsequent treatment is likely to play a key role in improving predictions.
{"title":"Slipping Away: Slippage in Hazard Ratios Over Datacuts and Its Impact on Immuno-oncology Combination Economic Evaluations","authors":"Dawn Lee MMath, MSc , Zain Ahmad , Caroline Farmer PhD , Maxwell S. Barnish PhD , Alan Lovell PhD , G.J. Melendez-Torres DPhil, MPH, RN","doi":"10.1016/j.jval.2024.09.008","DOIUrl":"10.1016/j.jval.2024.09.008","url":null,"abstract":"<div><h3>Objectives</h3><div>This study examines the impact of slippage in hazard ratios (tending toward the null over subsequent datacuts) for overall survival for combination treatment with a PD-(L)-1 inhibitor and a tyrosine kinase inhibitor in advanced renal cell carcinoma.</div></div><div><h3>Methods</h3><div>Four trials’ Kaplan-Meier curves were digitized over several datacuts and fitted with standard parametric curves. Accuracy and consistency of early data projections were calculated versus observed restricted mean survival time and fitted lifetime survival from the longest follow-up datacut. The change in economically justifiable price (eJP) was calculated fitting the same curve to both arms, using an assumed average utility of 0.7 and willingness-to-pay threshold of £30 000 per quality-adjusted life-year. The eJP represents the lifetime justifiable price increment for the new treatment, including differences in drug-, administration-, and disease-related costs.</div></div><div><h3>Results</h3><div>Slippage in hazard ratios was observed in trials with longer follow-up, potentially influenced by subsequent PD-(L)-1 use after tyrosine kinase inhibitor monotherapy, early stoppage of PD-(L)-1, and development of resistance. Lognormal and log-logistic curves were more likely to overpredict the observed result; Gompertz and gamma underpredicted. Statistical measures of goodness of fit did not select the curves that resulted in the RMST closest to what was observed in the final data cut. Large differences in incremental mean life-years were observed between even the penultimate and final datacuts for most of the fitted curves, meaningfully affecting the eJP.</div></div><div><h3>Conclusions</h3><div>This work demonstrates the challenge in predicting treatment benefits with novel therapies using immature data. Incorporating information on the impact of subsequent treatment is likely to play a key role in improving predictions.</div></div>","PeriodicalId":23508,"journal":{"name":"Value in Health","volume":"28 2","pages":"Pages 260-268"},"PeriodicalIF":4.9,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142401462","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}
Pub Date : 2025-02-01DOI: 10.1016/j.jval.2024.11.005
Sabina Sanghera PhD , Joanna Coast PhD , Axel Walther PhD , Tim J. Peters PhD
Objectives
When health fluctuates recurrently, estimating quality of life (QOL) is challenging, risking over-/underestimation due to measures’ recall periods and timing. To inform how/when to capture QOL, we compared responses using different recall periods and assessment timings.
Methods
For one 3-week chemotherapy cycle, cancer patients were randomly assigned to complete EQ-5D-5L or SF-12v2 (daily with a daily recall, weekly with a weekly recall, and at 3 weeks with a 3-week recall); a third group completed SF-12v2 daily with a 3-week recall. EQ-5D-5L and SF-6D utilities (anchored at 1 [full health] and 0 [dead]) were generated and repeated measures analysis of variance, t tests, and effect sizes were calculated to compare recall.
Results
A total of 503 patients consented; all 21 daily questionnaires were completed by 84 (50%), 67 (40%), and 72 (43%) in the groups. Both measures captured fluctuations in QOL suggesting differences are due to recall effects. Mean daily scores were greater than scores for the past week on days 7, 14, and 21 (P < .0001). Utility was underestimated (by 0.0782, 0.0374, and 0.0437) for EQ-5D-5L and (0.0387, 0.0266, and 0.0304) for SF-6D, with the EQ-5D-5L comparison on day 7 reaching a minimally important difference. The “past 3 weeks” generated the lowest scores (P < .0001), with utility underestimated by 0.0746 (EQ-5D-5L) and 0.0310 (SF-6D), heavily skewed by the first treatment week.
Conclusions
The current practice of using a single estimate at the beginning or end of a cycle with a daily (EQ-5D-5L) or longer (SF-12/SF-36) recall could bias cost-effectiveness estimates. QOL should be captured frequently with short recall when fluctuations are likely and less frequently with longer recall in stable periods.
{"title":"The Influence of Recall and Timing of Assessment on the Estimation of Quality-Adjusted Life-Years When Health Fluctuates Recurrently","authors":"Sabina Sanghera PhD , Joanna Coast PhD , Axel Walther PhD , Tim J. Peters PhD","doi":"10.1016/j.jval.2024.11.005","DOIUrl":"10.1016/j.jval.2024.11.005","url":null,"abstract":"<div><h3>Objectives</h3><div>When health fluctuates recurrently, estimating quality of life (QOL) is challenging, risking over-/underestimation due to measures’ recall periods and timing. To inform how/when to capture QOL, we compared responses using different recall periods and assessment timings.</div></div><div><h3>Methods</h3><div>For one 3-week chemotherapy cycle, cancer patients were randomly assigned to complete EQ-5D-5L or SF-12v2 (daily with a daily recall, weekly with a weekly recall, and at 3 weeks with a 3-week recall); a third group completed SF-12v2 daily with a 3-week recall. EQ-5D-5L and SF-6D utilities (anchored at 1 [full health] and 0 [dead]) were generated and repeated measures analysis of variance, <em>t</em> tests, and effect sizes were calculated to compare recall.</div></div><div><h3>Results</h3><div>A total of 503 patients consented; all 21 daily questionnaires were completed by 84 (50%), 67 (40%), and 72 (43%) in the groups. Both measures captured fluctuations in QOL suggesting differences are due to recall effects. Mean daily scores were greater than scores for the past week on days 7, 14, and 21 (<em>P</em> < .0001). Utility was underestimated (by 0.0782, 0.0374, and 0.0437) for EQ-5D-5L and (0.0387, 0.0266, and 0.0304) for SF-6D, with the EQ-5D-5L comparison on day 7 reaching a minimally important difference. The “past 3 weeks” generated the lowest scores (<em>P</em> < .0001), with utility underestimated by 0.0746 (EQ-5D-5L) and 0.0310 (SF-6D), heavily skewed by the first treatment week.</div></div><div><h3>Conclusions</h3><div>The current practice of using a single estimate at the beginning or end of a cycle with a daily (EQ-5D-5L) or longer (SF-12/SF-36) recall could bias cost-effectiveness estimates. QOL should be captured frequently with short recall when fluctuations are likely and less frequently with longer recall in stable periods.</div></div>","PeriodicalId":23508,"journal":{"name":"Value in Health","volume":"28 2","pages":"Pages 275-284"},"PeriodicalIF":4.9,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142781223","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}
Pub Date : 2025-02-01DOI: 10.1016/j.jval.2024.10.3846
Rachael L. Fleurence PhD , Jiang Bian PhD , Xiaoyan Wang PhD , Hua Xu PhD , Dalia Dawoud PhD , Mitchell Higashi PhD , Jagpreet Chhatwal PhD , ISPOR Working Group on Generative AI
Objectives
To provide an introduction to the uses of generative artificial intelligence (AI) and foundation models, including large language models, in the field of health technology assessment (HTA).
Methods
We reviewed applications of generative AI in 3 areas: systematic literature reviews, real-world evidence, and health economic modeling.
Results
(1) Literature reviews: generative AI has the potential to assist in automating aspects of systematic literature reviews by proposing search terms, screening abstracts, extracting data, and generating code for meta-analyses; (2) real-world evidence: generative AI can facilitate automating processes and analyze large collections of real-world data, including unstructured clinical notes and imaging; (3) health economic modeling: generative AI can aid in the development of health economic models, from conceptualization to validation. Limitations in the use of foundation models and large language models include challenges surrounding their scientific rigor and reliability, the potential for bias, implications for equity, as well as nontrivial concerns regarding adherence to regulatory and ethical standards, particularly in terms of data privacy and security. Additionally, we survey the current policy landscape and provide suggestions for HTA agencies on responsibly integrating generative AI into their workflows, emphasizing the importance of human oversight and the fast-evolving nature of these tools.
Conclusions
Although generative AI technology holds promise with respect to HTA applications, it is still undergoing rapid developments and improvements. Continued careful evaluation of their applications to HTA is required. Both developers and users of research incorporating these tools, should familiarize themselves with their current capabilities and limitations.
{"title":"Generative Artificial Intelligence for Health Technology Assessment: Opportunities, Challenges, and Policy Considerations: An ISPOR Working Group Report","authors":"Rachael L. Fleurence PhD , Jiang Bian PhD , Xiaoyan Wang PhD , Hua Xu PhD , Dalia Dawoud PhD , Mitchell Higashi PhD , Jagpreet Chhatwal PhD , ISPOR Working Group on Generative AI","doi":"10.1016/j.jval.2024.10.3846","DOIUrl":"10.1016/j.jval.2024.10.3846","url":null,"abstract":"<div><h3>Objectives</h3><div>To provide an introduction to the uses of generative artificial intelligence (AI) and foundation models, including large language models, in the field of health technology assessment (HTA).</div></div><div><h3>Methods</h3><div>We reviewed applications of generative AI in 3 areas: systematic literature reviews, real-world evidence, and health economic modeling.</div></div><div><h3>Results</h3><div>(1) Literature reviews: generative AI has the potential to assist in automating aspects of systematic literature reviews by proposing search terms, screening abstracts, extracting data, and generating code for meta-analyses; (2) real-world evidence: generative AI can facilitate automating processes and analyze large collections of real-world data, including unstructured clinical notes and imaging; (3) health economic modeling: generative AI can aid in the development of health economic models, from conceptualization to validation. Limitations in the use of foundation models and large language models include challenges surrounding their scientific rigor and reliability, the potential for bias, implications for equity, as well as nontrivial concerns regarding adherence to regulatory and ethical standards, particularly in terms of data privacy and security. Additionally, we survey the current policy landscape and provide suggestions for HTA agencies on responsibly integrating generative AI into their workflows, emphasizing the importance of human oversight and the fast-evolving nature of these tools.</div></div><div><h3>Conclusions</h3><div>Although generative AI technology holds promise with respect to HTA applications, it is still undergoing rapid developments and improvements. Continued careful evaluation of their applications to HTA is required. Both developers and users of research incorporating these tools, should familiarize themselves with their current capabilities and limitations.</div></div>","PeriodicalId":23508,"journal":{"name":"Value in Health","volume":"28 2","pages":"Pages 175-183"},"PeriodicalIF":4.9,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142628806","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}
Pub Date : 2025-02-01DOI: 10.1016/j.jval.2024.11.001
Becky Field PhD , Katherine E. Smith PhD , Clementine Hill O’Connor PhD , Nyantara Wickramasekera MSc , Aki Tsuchiya PhD
Objectives
Increasingly, discrete choice experiments (DCEs) are conducted online, with little consideration of the digitally excluded, who are unable to participate. Policy makers or others considering online research data need clarity about how views might differ across this “digital divide.” We took tasks from an existing online DCE designed to elicit social preferences for health and well-being outcomes. We aimed to explore (1) how telephone interview participants answered a series of choice tasks taken from an online DCE and (2) whether and how decision making for these tasks differed between digitally excluded and nonexcluded participants.
Methods
We conducted semistructured telephone interviews with members of the public (n = 27), recruited via an existing social research panel. Data were analyzed thematically to identify key approaches to decision making.
Results
Twelve participants were classed as “digitally excluded,” and 15 as “digitally nonexcluded.” Responses were similar between the 2 samples for most choice tasks. We identified 3 approaches used to reach decisions: (1) simplifying, (2) creating explanatory narratives, and (3) personalizing. Although these approaches were common across both samples, understanding the exercise seemed more challenging for the digitally excluded sample.
Conclusions
This novel study provides some assurance that the participants’ views over the choice tasks used are similar across the digital divide. The challenges we identified with understanding highlight the need to carefully examine the views held by the digitally excluded. If online data are to inform policy making, it is essential to explore the views of those who cannot participate in online DCEs.
{"title":"Exploring Social Preferences for Health and Well-Being Across the Digital Divide: A Qualitative Investigation Based on Tasks Taken From an Online Discrete Choice Experiment","authors":"Becky Field PhD , Katherine E. Smith PhD , Clementine Hill O’Connor PhD , Nyantara Wickramasekera MSc , Aki Tsuchiya PhD","doi":"10.1016/j.jval.2024.11.001","DOIUrl":"10.1016/j.jval.2024.11.001","url":null,"abstract":"<div><h3>Objectives</h3><div>Increasingly, discrete choice experiments (DCEs) are conducted online, with little consideration of the digitally excluded, who are unable to participate. Policy makers or others considering online research data need clarity about how views might differ across this “digital divide.” We took tasks from an existing online DCE designed to elicit social preferences for health and well-being outcomes. We aimed to explore (1) how telephone interview participants answered a series of choice tasks taken from an online DCE and (2) whether and how decision making for these tasks differed between digitally excluded and nonexcluded participants.</div></div><div><h3>Methods</h3><div>We conducted semistructured telephone interviews with members of the public (n = 27), recruited via an existing social research panel. Data were analyzed thematically to identify key approaches to decision making.</div></div><div><h3>Results</h3><div>Twelve participants were classed as “digitally excluded,” and 15 as “digitally nonexcluded.” Responses were similar between the 2 samples for most choice tasks. We identified 3 approaches used to reach decisions: (1) simplifying, (2) creating explanatory narratives, and (3) personalizing. Although these approaches were common across both samples, understanding the exercise seemed more challenging for the digitally excluded sample.</div></div><div><h3>Conclusions</h3><div>This novel study provides some assurance that the participants’ views over the choice tasks used are similar across the digital divide. The challenges we identified with understanding highlight the need to carefully examine the views held by the digitally excluded. If online data are to inform policy making, it is essential to explore the views of those who cannot participate in online DCEs.</div></div>","PeriodicalId":23508,"journal":{"name":"Value in Health","volume":"28 2","pages":"Pages 285-293"},"PeriodicalIF":4.9,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142695953","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}
Pub Date : 2025-02-01DOI: 10.1016/j.jval.2024.07.028
Takashi Yoshioka MD, PhD
{"title":"Potential Biases in Post-Stroke Health Utility Estimates by Modified Rankin Scale Scores","authors":"Takashi Yoshioka MD, PhD","doi":"10.1016/j.jval.2024.07.028","DOIUrl":"10.1016/j.jval.2024.07.028","url":null,"abstract":"","PeriodicalId":23508,"journal":{"name":"Value in Health","volume":"28 2","pages":"Pages 319-320"},"PeriodicalIF":4.9,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142772581","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}
Pub Date : 2025-02-01DOI: 10.1016/j.jval.2024.11.012
Harshith Thyagaturu MD , Karthik Seetharam MD , Nicholas Roma MD , Neel Patel MD , Jordan Lacoste PharmD , Vikram Padala BS , Karthik Gonuguntla MD , Muhammad Bilal Munir MD , Sudarshan Balla MD
Objectives
To study the national trends of anticoagulants, antiarrhythmic drugs (AADs), and expenditures in the civilian noninstitutionalized atrial fibrillation (AF) population.
Methods
The Medical Expenditure Panel Survey was queried from January 2016 to December 2021 to identify adults (age ≥18 years) with a diagnosis of AF utilizing the International Classification of Diseases, Tenth Revision, Clinical Modification code I48. Prevalence of anticoagulants (AAD) and its expenditure and AF expenditure across clinical settings in the United States were estimated. The predictors of anticoagulant use were identified utilizing multivariate logistic regression analysis.
Results
A total of 17.3 million AF adults were identified, of which 46.5% were female, 89.6% were White, and ∼70% were middle/high income with prevalent comorbidities of hypertension (75.3%) and coronary heart disease (30%). The mean CHA2DS2 VASc score was 3.2, and 40% had a score of ≥4. In the United States, an average of $26 103 (2021 inflation adjusted) was spent per year per adult with AF for health-related expenditures. The prevalence of direct oral anticoagulants (DOACs) and class I AAD use has increased; in contrast, vitamin K antagonists use has declined. DOAC-related per person annual expenses increased from $849 in 2016 to $1929 in 2021. In those with a CHA2DS2 VASc score of ≥2, female sex and the presence of coronary heart disease were associated with a lower likelihood of anticoagulant use.
Conclusions
AF is a costly condition in which prescription medication use, such as DOACs and class III AADs, are significant contributors.
{"title":"Prescription Medication Use and Expenditure for Atrial Fibrillation in the United States","authors":"Harshith Thyagaturu MD , Karthik Seetharam MD , Nicholas Roma MD , Neel Patel MD , Jordan Lacoste PharmD , Vikram Padala BS , Karthik Gonuguntla MD , Muhammad Bilal Munir MD , Sudarshan Balla MD","doi":"10.1016/j.jval.2024.11.012","DOIUrl":"10.1016/j.jval.2024.11.012","url":null,"abstract":"<div><h3>Objectives</h3><div>To study the national trends of anticoagulants, antiarrhythmic drugs (AADs), and expenditures in the civilian noninstitutionalized atrial fibrillation (AF) population.</div></div><div><h3>Methods</h3><div>The Medical Expenditure Panel Survey was queried from January 2016 to December 2021 to identify adults (age ≥18 years) with a diagnosis of AF utilizing the International Classification of Diseases, Tenth Revision, Clinical Modification code I48. Prevalence of anticoagulants (AAD) and its expenditure and AF expenditure across clinical settings in the United States were estimated. The predictors of anticoagulant use were identified utilizing multivariate logistic regression analysis.</div></div><div><h3>Results</h3><div>A total of 17.3 million AF adults were identified, of which 46.5% were female, 89.6% were White, and ∼70% were middle/high income with prevalent comorbidities of hypertension (75.3%) and coronary heart disease (30%). The mean CHA<sub>2</sub>DS<sub>2</sub> VASc score was 3.2, and 40% had a score of ≥4. In the United States, an average of $26 103 (2021 inflation adjusted) was spent per year per adult with AF for health-related expenditures. The prevalence of direct oral anticoagulants (DOACs) and class I AAD use has increased; in contrast, vitamin K antagonists use has declined. DOAC-related per person annual expenses increased from $849 in 2016 to $1929 in 2021. In those with a CHA<sub>2</sub>DS<sub>2</sub> VASc score of ≥2, female sex and the presence of coronary heart disease were associated with a lower likelihood of anticoagulant use.</div></div><div><h3>Conclusions</h3><div>AF is a costly condition in which prescription medication use, such as DOACs and class III AADs, are significant contributors.</div></div>","PeriodicalId":23508,"journal":{"name":"Value in Health","volume":"28 2","pages":"Pages 197-205"},"PeriodicalIF":4.9,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142855260","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}
Pub Date : 2025-02-01DOI: 10.1016/j.jval.2024.11.009
Thi Thuy Dung Nguyen MS , Yu-Hsuan Lee MPH , Yu-Jr Lin MS , Shu-Chen Chang PhD , Fei-Yuan Hsiao PhD , Chee-Jen Chang PhD , Huang-Tz Ou PhD
Objectives
Given the lack of a value framework for assessing health technologies in Asian settings, a value framework incorporating multiple-criteria decision analysis for new drugs under universal healthcare coverage in Taiwan was established.
Methods
The development process included (1) the adoption of 5 value domains (ie, Overall clinical benefit, Disease burden, Alignment with patient concerns, Economic value, and Feasibility of adoption into the health system) and 26 corresponding indicators, derived from the literature and expert discussions; (2) the creation of separate weighting schemes for 3 drug types—new oncology, new orphan, and other new drugs—based on inputs from multiple stakeholders (n = 86) using various weighting methods; and (3) the application of the value framework to cases of new oncology drugs.
Results
Overall clinical benefit had the highest preference weight, irrespective of drug type, (ie, mean values [95% CIs] for new oncology, new orphan, and other new drugs: 32.5 [30.4–34.6], 30.6 [28.1–33.1], and 30.6 [28.7–32.6], respectively), weighting method, and stakeholder type. The 5 domain-derived weights (from the point allocation method) were comparable to the 26 indicator-derived weights (from the direct rating method), suggesting that the value framework with a short-form (domain-derived) weighting scheme is sufficient to support decision making under time and resource constraints.
Conclusions
A country-specific value framework incorporating multiple-criteria decision analysis for new drugs was developed in an Asian setting under universal healthcare coverage. It allows multiple stakeholders to systematically appraise all drug value attributes and provides a structured process for adapting and refining value assessments.
{"title":"Value Framework Based on Multiple-Criteria Decision Analysis for Assessment of New Health Technologies Under Universal Healthcare Coverage System in Taiwan","authors":"Thi Thuy Dung Nguyen MS , Yu-Hsuan Lee MPH , Yu-Jr Lin MS , Shu-Chen Chang PhD , Fei-Yuan Hsiao PhD , Chee-Jen Chang PhD , Huang-Tz Ou PhD","doi":"10.1016/j.jval.2024.11.009","DOIUrl":"10.1016/j.jval.2024.11.009","url":null,"abstract":"<div><h3>Objectives</h3><div>Given the lack of a value framework for assessing health technologies in Asian settings, a value framework incorporating multiple-criteria decision analysis for new drugs under universal healthcare coverage in Taiwan was established.</div></div><div><h3>Methods</h3><div>The development process included (1) the adoption of 5 value domains (ie, Overall clinical benefit, Disease burden, Alignment with patient concerns, Economic value, and Feasibility of adoption into the health system) and 26 corresponding indicators, derived from the literature and expert discussions; (2) the creation of separate weighting schemes for 3 drug types—new oncology, new orphan, and other new drugs—based on inputs from multiple stakeholders (n = 86) using various weighting methods; and (3) the application of the value framework to cases of new oncology drugs.</div></div><div><h3>Results</h3><div>Overall clinical benefit had the highest preference weight, irrespective of drug type, (ie, mean values [95% CIs] for new oncology, new orphan, and other new drugs: 32.5 [30.4–34.6], 30.6 [28.1–33.1], and 30.6 [28.7–32.6], respectively), weighting method, and stakeholder type. The 5 domain-derived weights (from the point allocation method) were comparable to the 26 indicator-derived weights (from the direct rating method), suggesting that the value framework with a short-form (domain-derived) weighting scheme is sufficient to support decision making under time and resource constraints.</div></div><div><h3>Conclusions</h3><div>A country-specific value framework incorporating multiple-criteria decision analysis for new drugs was developed in an Asian setting under universal healthcare coverage. It allows multiple stakeholders to systematically appraise all drug value attributes and provides a structured process for adapting and refining value assessments.</div></div>","PeriodicalId":23508,"journal":{"name":"Value in Health","volume":"28 2","pages":"Pages 241-249"},"PeriodicalIF":4.9,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142872973","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}
Pub Date : 2025-02-01DOI: 10.1016/j.jval.2024.10.3848
Anirban Basu PhD
Objectives
This study aims to understand the role of alternative pricing and financing mechanisms on the budget impact for payers and the risks and returns of manufacturers for gene therapies.
Methods
This article uses fundamental economic principles to interpret the implications of alternative pricing mechanisms in terms of the share of value appropriated by the manufacturer and how alternative financing mechanisms alter it. It demonstrates these concepts by studying the financial impacts for a payer and the manufacturer across alternative pricing and financing mechanisms that could be used by the US Centers for Medicare and Medicaid Services to pay for gene therapy for sickle cell disease.
Results
Unlike value-based and manufacturer-set monopoly prices, an effective monopoly price can be derived to guarantee monopoly profits for manufacturers during their exclusivity period, thereby providing a high appropriation share and substantially lowering price and budget impact for a payer. For sickle cell disease gene therapy, the 10-year budget impact for the US Centers for Medicare and Medicaid Services would range from US dollar $8.6 billion to $12.8 billion under a value-based price, to $10.2 billion to $15.2 billion under a monopoly price, but reduce to $7.7 billion under an effective monopoly price. The latter price would still fetch over 50% of the total surplus to the manufacturer while mitigating their risk of sales volume.
Conclusions
Significant budget impacts for funding gene therapy are not mitigated across alternative financing mechanisms at any given price. The price determines most of the budget impact. The option of a patent buyout may help negotiate down prices to effective monopoly prices.
{"title":"Financial Impacts of Paying for Gene Therapy for Sickle Cell Disease Under Alternative Pricing and Financing Mechanisms","authors":"Anirban Basu PhD","doi":"10.1016/j.jval.2024.10.3848","DOIUrl":"10.1016/j.jval.2024.10.3848","url":null,"abstract":"<div><h3>Objectives</h3><div>This study aims to understand the role of alternative pricing and financing mechanisms on the budget impact for payers and the risks and returns of manufacturers for gene therapies.</div></div><div><h3>Methods</h3><div>This article uses fundamental economic principles to interpret the implications of alternative pricing mechanisms in terms of the share of value appropriated by the manufacturer and how alternative financing mechanisms alter it. It demonstrates these concepts by studying the financial impacts for a payer and the manufacturer across alternative pricing and financing mechanisms that could be used by the US Centers for Medicare and Medicaid Services to pay for gene therapy for sickle cell disease.</div></div><div><h3>Results</h3><div>Unlike value-based and manufacturer-set monopoly prices, an effective monopoly price can be derived to guarantee monopoly profits for manufacturers during their exclusivity period, thereby providing a high appropriation share and substantially lowering price and budget impact for a payer. For sickle cell disease gene therapy, the 10-year budget impact for the US Centers for Medicare and Medicaid Services would range from US dollar $8.6 billion to $12.8 billion under a value-based price, to $10.2 billion to $15.2 billion under a monopoly price, but reduce to $7.7 billion under an effective monopoly price. The latter price would still fetch over 50% of the total surplus to the manufacturer while mitigating their risk of sales volume.</div></div><div><h3>Conclusions</h3><div>Significant budget impacts for funding gene therapy are not mitigated across alternative financing mechanisms at any given price. The price determines most of the budget impact. The option of a patent buyout may help negotiate down prices to effective monopoly prices.</div></div>","PeriodicalId":23508,"journal":{"name":"Value in Health","volume":"28 2","pages":"Pages 233-240"},"PeriodicalIF":4.9,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142628784","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}
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