Document Type
Poster
Publication Date
4-30-2020
Institution/Department
Maine Medical Center, Medical Education, Maine Medical Center Research Institute, Center for Outcomes Research & Evaluation
MeSH Headings
Data Science, Medicine, Medical Informatics
Abstract
Clinical trial evidence is considered the gold standard source of evidence for medical decision-making. However clinical trial evidence is expensive, time consuming to generate and sometimes does not translate to “real world” settings. Large amounts of clinical data are routinely collected every day during the delivery of health care services that represent a potential valuable resource for evidence generation. The Observational Health Data Sciences and Informatics (OHDSI) community is leading the way in developing open source software tools and validated methodology to turn routinely collected observational data into evidence. Over the past year MMCRI has implemented the OHDSI tool stack using MaineHealth Epic data. This poster will update the audience on the progress of this infrastructure setup as well as demonstrate some of the capabilities of the infrastructure. Starting in Jan 2019 MMCRI applied for and received funding from Tufts University to build a research data warehouse built on top of the OHDSI Common Data Model (CDM). The CDM was built using an Extract Transform, and Load (ETL) process that extracted data from Epic and mapped it into the CDM. The new database will make it easier for researchers to build cohorts, design studies, and collaborate with other institutions with data in the same format.
Recommended Citation
Black, Adam; Denton, Dave; DiPalazzo, John; and Santangelo, Susan, "Observational Health Data Sciences and Informatics (OHDSI) Infrastructure at MMC" (2020). Costas T. Lambrew Research Retreat 2020. 70.
https://knowledgeconnection.mainehealth.org/lambrew-retreat-2020/70
Comments
2020 Costas T. Lambrew Research Retreat