Health-Analytics Data to Evidence Suite (HADES): Open-Source Software for Observational Research

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...

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Bibliographic Details
Published inStudies in health technology and informatics Vol. 310; p. 966
Main Authors Schuemie, Martijn, Reps, Jenna, Black, Adam, Defalco, Frank, Evans, Lee, Fridgeirsson, Egill, Gilbert, James P, Knoll, Chris, Lavallee, Martin, Rao, Gowtham A, Rijnbeek, Peter, Sadowski, Katy, Sena, Anthony, Swerdel, Joel, Williams, Ross D, Suchard, Marc
Format Journal Article
LanguageEnglish
Published Netherlands 25.01.2024
Subjects
Data Science
Databases, Factual
Electronic Health Records
Humans
Observational Studies as Topic
Reproducibility of Results
Software
epidemiology
Observational research
open-source
software
machine learning
Online AccessGet more information
ISSN1879-8365
DOI10.3233/SHTI231108

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Summary: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.
ISSN:1879-8365
DOI:10.3233/SHTI231108