OHDSI Israel

Background 

In recent years, there has been a remarkable increase in interest within Israel regarding the OMOP Common Data Model (CDM) and the Observational Health Data Sciences and Informatics (OHDSI) program. The OHDSI Israel Node, founded in summer 2023, strives to become a meeting point to all interested parties, expand OHDSI adoption within the Israeli healthcare system, and generate reliable, meaningful, and actionable evidence that promotes better health decisions and better care.

Objectives 

• Promote OHDSI mission, vision, and values in Israel; engage with the European and global OHDSI community.
  
  
• Drive further standardization of Israeli data to the OMOP CDM and encourage the use of OHDSI analytics tools.
  
  
• Facilitate training programs and workshops to generate accurate and reproducible evidence generation from observational data; involve clinicians and researchers from the academia, government, healthcare organizations, and industry.
  
  
• Foster collaboration in national research initiatives; communicate with national policymakers to raise awareness and showcase the value of OMOP CDM and OHDSI analytics.

Leading Organisation(s)

Chen Yanover, KI Research Institute, This email address is being protected from spambots. You need JavaScript enabled to view it. 

Publications

• El-Hay T, Yanover C. Estimating Model Performance on External Samples from Their Limited Statistical Characteristics. In: Proceedings of the Conference on Health, Inference, and Learning. PMLR; 2022:48-62.
• Abbou B, Tal O, Frenkel G, Rubin R, Rappoport N. Optimizing Operation Room Utilization—A Prediction Model. Big Data and Cognitive Computing. 2022 Sep;6(3):76. 
• Elkan M, Kofman N, Minha S, Rappoport N, Zaidenstein R, Koren R. Does the “Obesity Paradox” Have an Expiration Date? A Retrospective Cohort Study. Journal of Clinical Medicine. 2023 Jan;12(21):6765.
• Ostropolets A, Albogami Y, Conover M, Banda JM, Baumgartner WA Jr, Blacketer C, et al. Reproducible variability: assessing investigator discordance across 9 research teams attempting to reproduce the same observational study. Journal of the American Medical Informatics Association. 2023 May 1;30(5):859–68. 
• Naderalvojoud B, Curtin CM, Yanover C, El-Hay T, Choi B, Park RW, et al. Towards global model generalizability: independent cross-site feature evaluation for patient-level risk prediction models using the OHDSI network. Journal of the American Medical Informatics Association. 2024 Feb 27;ocae028. 
• Azriel D, Rinott Y, Tal O, Abbou B, Rappoport N. Surgery Duration Prediction using Multitask Feature Selection. IEEE Journal of Biomedical and Health Informatics. 2024;1–9.

How to contribute?

• To join OHDSI Israel, fill out the following Google Form
  
  
• Optional: To get an OHDSI MSTeams account use this link; and here you can sign up for Working Groups.