Estimating Long-Term Health Utility Scores and Expenditures for Cardiovascular Disease From the Medical Expenditure Panel Survey.
cardiovascular diseases
cost-benefit analysis
health expenditures
myocardial infarction
quality of life
stroke
Journal
Circulation. Cardiovascular quality and outcomes
ISSN: 1941-7705
Titre abrégé: Circ Cardiovasc Qual Outcomes
Pays: United States
ID NLM: 101489148
Informations de publication
Date de publication:
04 2021
04 2021
Historique:
pubmed:
26
3
2021
medline:
16
10
2021
entrez:
25
3
2021
Statut:
ppublish
Résumé
Long-term health utility scores and costs used in cost-effectiveness analyses of cardiovascular disease prevention and management can be inconsistent, outdated, or invalid for the diverse population of the United States. Our aim was to develop a user friendly, standardized, publicly available code and catalog to derive more valid long-term values for health utility and expenditures following cardiovascular disease events. Individual-level Short Form-12 version 2 health-related quality of life and expenditure data were obtained from the pooled 2011 to 2016 Medical Expenditure Panel Surveys. We developed code using the R programming language to estimate preference-weighted Short Form-6D utility scores from the Short Form-12 for quality-adjusted life year calculations and predict annual health care expenditures. Result predictors included cardiovascular disease diagnosis (myocardial infarction, ischemic stroke, heart failure, cardiac dysrhythmias, angina pectoris, and peripheral artery disease), sociodemographic factors, and comorbidity variables. The cardiovascular disease diagnoses with the lowest utility scores were heart failure (0.635 [95% CI, 0.615-0.655]), angina pectoris (0.649 [95% CI, 0.630-0.667]), and ischemic stroke (0.649 [95% CI, 0.635-0.663]). The highest annual expenditures were for heart failure ($20 764 [95% CI, $17 500-$24 027]), angina pectoris ($18 428 [95% CI, $16 102-$20 754]), and ischemic stroke ($16 925 [95% CI, $15 672-$20 616]). The developed code and catalog may improve the quality and comparability of cost-effectiveness analyses by providing standardized methods for extracting long-term health utility scores and expenditures from Medical Expenditure Panel Survey data, which are more current and representative of the US population than previous sources.
Sections du résumé
BACKGROUND
Long-term health utility scores and costs used in cost-effectiveness analyses of cardiovascular disease prevention and management can be inconsistent, outdated, or invalid for the diverse population of the United States. Our aim was to develop a user friendly, standardized, publicly available code and catalog to derive more valid long-term values for health utility and expenditures following cardiovascular disease events.
METHODS
Individual-level Short Form-12 version 2 health-related quality of life and expenditure data were obtained from the pooled 2011 to 2016 Medical Expenditure Panel Surveys. We developed code using the R programming language to estimate preference-weighted Short Form-6D utility scores from the Short Form-12 for quality-adjusted life year calculations and predict annual health care expenditures. Result predictors included cardiovascular disease diagnosis (myocardial infarction, ischemic stroke, heart failure, cardiac dysrhythmias, angina pectoris, and peripheral artery disease), sociodemographic factors, and comorbidity variables.
RESULTS
The cardiovascular disease diagnoses with the lowest utility scores were heart failure (0.635 [95% CI, 0.615-0.655]), angina pectoris (0.649 [95% CI, 0.630-0.667]), and ischemic stroke (0.649 [95% CI, 0.635-0.663]). The highest annual expenditures were for heart failure ($20 764 [95% CI, $17 500-$24 027]), angina pectoris ($18 428 [95% CI, $16 102-$20 754]), and ischemic stroke ($16 925 [95% CI, $15 672-$20 616]).
CONCLUSIONS
The developed code and catalog may improve the quality and comparability of cost-effectiveness analyses by providing standardized methods for extracting long-term health utility scores and expenditures from Medical Expenditure Panel Survey data, which are more current and representative of the US population than previous sources.
Identifiants
pubmed: 33761758
doi: 10.1161/CIRCOUTCOMES.120.006769
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM