Results 31 to 40 of about 1,082 (160)

Austin Health OMOP Dataset

open access: yes, 2023
The Austin Health Dataset is an OMOP dataset based on records held at Austin Health.The data is derived from an Electronic Medical Records System held in Cerner.While the data is not open access, researchers can enquire about access subject to ethics and
ROGER WARD (1151036)   +1 more
core   +1 more source

Transforming Anesthesia Data Into the Observational Medical Outcomes Partnership Common Data Model: Development and Usability Study

open access: yesJournal of Medical Internet Research, 2021
BackgroundElectronic health records (EHRs, such as those created by an anesthesia management system) generate a large amount of data that can notably be reused for clinical audits and scientific research. The sharing of these data
Antoine Lamer   +7 more
doaj   +1 more source

MIMIC in the OMOP Common Data Model [PDF]

open access: yes, 2020
Objectives In the era of big data, the intensive care unit (ICU) is very likely to benefit from real-time computer analysis and modeling based on close patient monitoring and Electronic Health Record data. MIMIC is the first open access database in the ICU domain.
Nicolas Paris, Adrien Parrot
openaire   +1 more source

Semi-Automated Mapping of German Study Data Concepts to an English Common Data Model

open access: yesApplied Sciences, 2023
The standardization of data from medical studies and hospital information systems to a common data model such as the Observational Medical Outcomes Partnership (OMOP) model can help make large datasets available for analysis using artificial intelligence
Anna Chechulina   +8 more
doaj   +1 more source

Source to OMOP YAML file structure.

open access: yes, 2022
Rules for mapping from the CERNER PERSON table to the OMOP PERSON table, with rules defined for two columns of the OMOP PERSON table: year_of_birth and death_datetime. For each target table, the mapping rules are defined on a column-by-column basis using
Juan C. Quiroz (12400890)   +5 more
core   +1 more source

A Causal Perspective on OSIM2 Data Generation, with Implications for Simulation Study Design and Interpretation

open access: yesJournal of Causal Inference, 2015
Research by the Observational Medical Outcomes Partnership (OMOP) has focused on developing and evaluating strategies to exploit observational electronic data to improve post-market prescription drug surveillance.
Gruber Susan
doaj   +1 more source

Cancer Prediction on OMOP CDM – A Rapid Review / Study Registration

open access: yes, 2022
In this review, we evaluate the current potential of the OMOP to be applicable in cancer prediction and how comprehensively the genomic vocabulary extension of OMOP can serve current needs within the ...
Markus Wolfien   +4 more
core   +1 more source

FAIRifying a Quality Registry Using OMOP CDM: Challenges and Solutions

open access: yes, 2022
The need for health data to be internationally Findable, Accessible, Interoperable and Reusable (FAIR) and thereby support integrative analysis with other datasets has become crystal clear in the ongoing pandemic. The Dutch National Intensive Care Evaluation (NICE) quality registry adopted the Observational Medical Outcomes Partnership Common Database ...
Puttmann, Daniel   +4 more
openaire   +3 more sources

Preserving Privacy when Querying OMOP CDM Databases

open access: yes, 2022
Anonymisation is currently one of the biggest challenges when sharing sensitive personal information. Its importance depends largely on the application domain, but when dealing with health information, this becomes a more serious issue. A simpler approach to avoid inadequate disclosure is to ensure that all data that can be associated directly with an ...
João Rafael Almeida   +2 more
openaire   +3 more sources

Development and validation of the SickKids Enterprise-wide Data in Azure Repository (SEDAR)

open access: yesHeliyon, 2023
Objectives: To describe the processes developed by The Hospital for Sick Children (SickKids) to enable utilization of electronic health record (EHR) data by creating sequentially transformed schemas for use across multiple user types.
Lin Lawrence Guo   +12 more
doaj   +1 more source

Home - About - Disclaimer - Privacy