Health-Analytics Data to Evidence Suite (HADES): Open-Source Software for Observational Research.
Observational research
epidemiology
machine learning
open-source
software
Journal
Studies in health technology and informatics
ISSN: 1879-8365
Titre abrégé: Stud Health Technol Inform
Pays: Netherlands
ID NLM: 9214582
Informations de publication
Date de publication:
25 Jan 2024
25 Jan 2024
Historique:
medline:
25
1
2024
pubmed:
25
1
2024
entrez:
25
1
2024
Statut:
ppublish
Résumé
The Health-Analytics Data to Evidence Suite (HADES) is an open-source software collection developed by Observational Health Data Sciences and Informatics (OHDSI). It executes directly against healthcare data such as electronic health records and administrative claims, that have been converted to the Observational Medical Outcomes Partnership (OMOP) Common Data Model. Using advanced analytics, HADES performs characterization, population-level causal effect estimation, and patient-level prediction, potentially across a federated data network, allowing patient-level data to remain locally while only aggregated statistics are shared. Designed to run across a wide array of technical environments, including different operating systems and database platforms, HADES uses continuous integration with a large set of unit tests to maintain reliability. HADES implements OHDSI best practices, and is used in almost all published OHDSI studies, including some that have directly informed regulatory decisions.
Identifiants
pubmed: 38269952
pii: SHTI231108
doi: 10.3233/SHTI231108
doi:
Types de publication
Journal Article
Langues
eng