OHDSI MEETINGS THIS WEEK
OHDSI Community Call - Tuesday at 12pm EThttps://meetings.webex.com/collabs/#/meetings/detail?uuid=M59X2V1U61WC9ASID2Z5N3UT95-D1JL&rnd=811649.9868221
Patient-level prediction (Eastern hemisphere) workgroup meeting - Wednesday at 3pm Hong Kong/Taiwan timehttps://global.gotomeeting.com/join/9729176611
GIS working group meeting - Monday (November 27th) at 10am EThttps://tufts.webex.com/mw3200/mywebex/default.do?service=1&siteurl=tufts&nomenu=true&main_url=%2Fmc3200%2Fe.do%3Fsiteurl%3Dtufts%26AT%3DMI%26EventID%3D562301137%26UID%3D528546812%26Host%3DQUhTSwAAAAT_EHuT3Ok-zHVhY1-kVGh78TH62dPsFk0x99qz1E9039sh_Eiepw8CoZeIF2SfnopQ8oAZaLN9PkzIZovRf2kV0%26FrameSet%3D2%26MTID%3Dm243d8e9a9c6c2d42d5182aeb5d30efdb1
ANNOUNCEMENTS
2017 OHDSI Symposium Materials: Presentation slides from this year’s symposium and tutorials have been uploaded here: https://www.ohdsi.org/past-events/
Symposium Videos: Recordings from the symposium are now available here: https://www.ohdsi.org/past-events/2017-ohdsi-symposium-materials/2017-ohdsi-sympoium-videos/
Tutorial videos: https://www.ohdsi.org/past-events/2017-tutorials-omop-common-data-model-and-standardized-vocabularies/ https://www.ohdsi.org/past-events/2017-tutorials-population-level-estimation/ https://www.ohdsi.org/past-events/2017-tutorials-ohdsi-development-architecture/ https://www.ohdsi.org/past-events/2017-tutorials-patient-level-prediction/
No duty is more urgent than that of returning thanks.
COMMUNITY PUBLICATIONS
Systematic data ingratiation of clinical trial recruitment locations for geographic-based query and visualization.
J Luo, W Chen, M Wu and C Weng,
International journal of medical informatics , 2017 12
Prior studies of clinical trial planning indicate that it is crucial to search and screen recruitment sites before starting to enroll participants. However, currently there is no systematic method developed to support clinical investigators to search candidate recruitment sites according to their interested clinical trial factors.In this study, we aim at developing a new approach to integrating the location data of over one million heterogeneous recruitment sites that are stored in clinical trial documents. The integrated recruitment location data can be searched and visualized using a map-based information retrieval method. The method enables systematic search and analysis of recruitment sites across a large amount of clinical trials.The location data of more than 1.4 million recruitment sites of over 183,000 clinical trials was normalized and integrated using a geocoding method. The integrated data can be used to support geographic information retrieval of recruitment sites. Additionally, the information of over 6000 clinical trial target disease conditions and close to 4000 interventions was also integrated into the system and linked to the recruitment locations. Such data integration enabled the construction of a novel map-based query system. The system will allow clinical investigators to search and visualize candidate recruitment sites for clinical trials based on target conditions and interventions.The evaluation results showed that the coverage of the geographic location mapping for the 1.4 million recruitment sites was 99.8%. The evaluation of 200 randomly retrieved recruitment sites showed that the correctness of geographic information mapping was 96.5%. The recruitment intensities of the top 30 countries were also retrieved and analyzed. The data analysis results indicated that the recruitment intensity varied significantly across different countries and geographic areas.This study contributed a new data processing framework to extract and integrate the location data of heterogeneous recruitment sites from clinical trial documents. The developed system can support effective retrieval and analysis of potential recruitment sites using target clinical trial factors.
Electronic Health Records-Based Phenotyping
Electronic Health Records-Based Phenotyping Contributors Rachel Richesson, PhD, MPH Michelle Smerek Shelley Rusincovitch Meredith Nahm Zozus, PhD Paramita Saha Chaudhuri, PhD W. Ed Hammond, PhD Robert M. Califf, MD Greg Simon, MD Beverly Green, MD,...
A Data Quality Assessment Guideline for Electronic Health Record Data Reusehttps://egems.academyhealth.org/articles/abstract/10.13063/egems.1280/
Toward multimodal signal detection of adverse drug reactions
