Markov modeling for cost-effectiveness using federated health data network
Objective
To introduce 2 R-packages that facilitate conducting health economics research on OMOP-based data networks, aiming to standardize and improve the reproducibility, transparency, and transferability of health economic models.
Materials and Methods
We developed the software tools and demonstrated their utility by replicating a UK-based heart failure data analysis across 5 different international databases from Estonia, Spain, Serbia, and the United States.
Results
We examined treatment trajectories of 47 163 patients. The overall incremental cost-effectiveness ratio (ICER) for telemonitoring relative to standard of care was 57 472 €/QALY. Country-specific ICERs were 60 312 €/QALY in Estonia, 58 096 €/QALY in Spain, 40 372 €/QALY in Serbia, and 90 893 €/QALY in the US, which surpassed the established willingness-to-pay thresholds.
Discussion
Currently, the cost-effectiveness analysis lacks standard tools, is performed in ad-hoc manner, and relies heavily on published information that might not be specific for local circumstances. Published results often exhibit a narrow focus, central to a single site, and provide only partial decision criteria, limiting their generalizability and comprehensive utility.
Conclusion
We created 2 R-packages to pioneer cost-effectiveness analysis in OMOP CDM data networks. The first manages state definitions and database interaction, while the second focuses on Markov model learning and profile synthesis. We demonstrated their utility in a multisite heart failure study, comparing telemonitoring and standard care, finding telemonitoring not cost-effective.
Топ-30
Журналы
|
1
2
|
|
|
medRxiv
2 публикации, 25%
|
|
|
Informatics in Medicine Unlocked
2 публикации, 25%
|
|
|
Journal of Biomedical Informatics
1 публикация, 12.5%
|
|
|
SN Social Sciences
1 публикация, 12.5%
|
|
|
Current Medical Research and Opinion
1 публикация, 12.5%
|
|
|
1
2
|
Издатели
|
1
2
3
|
|
|
Elsevier
3 публикации, 37.5%
|
|
|
openRxiv
2 публикации, 25%
|
|
|
Springer Nature
2 публикации, 25%
|
|
|
Taylor & Francis
1 публикация, 12.5%
|
|
|
1
2
3
|
- Мы не учитываем публикации, у которых нет DOI.
- Статистика публикаций обновляется еженедельно.