JeffreyWajdaDOMS, FACEP
Emergency Medicine • Sacramento, CAClinical Informatics
Chief Health Information Officer, University of California Davis - Clinical Informatics Fellowship Director, Clinical Professor - Emergency Medicine
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Office
2315 Stockton Blvd
Sacramento, CA 95817Phone+1 916-734-2011Fax+1 916-734-8080- Is this information wrong?
Summary
- Dr. Jeff Wajda serves the University of California, Davis Health System as the Chief Health Information Officer. He received his medical degree from Chicago College of Osteopathic Medicine and completed Residency training at Rush University / Cook County Hospital. He is experienced in ambulatory / inpatient population health, health technology/informatics, healthcare administration, clinical and biomedical informatics, and clinical transformation.
Education & Training
Cook County Health and Hospitals SystemResidency, Emergency Medicine, 1990 - 1993
Chicago College of Osteopathic Medicine at Midwestern UniversityClass of 1989
Oregon Health & Science University HospitalFellowship, Clinical Informatics (Internal Medicine)
University of Michigan MS
Certifications & Licensure
OR State License 2010 - Present
CA State License 2014 - 2025
WA State License 1993 - 2012
IL State License 1989 - 1993- American Board of Emergency Medicine Emergency Medicine
- American Board of Preventive Medicine Clinical Informatics
Publications & Presentations
PubMed
- 1 citationsPrediction of Tuberculosis Using an Automated Machine Learning Platform for Models Trained on Synthetic Data.Hooman H Rashidi, Imran H Khan, Luke T Dang, Samer Albahra, Ujjwal Ratan, Nihir Chadderwala, Wilson To, Prathima Srinivas, Jeffery Wajda, Nam K Tran> ;Journal of Pathology Informatics. 2022 Jan 1
- 23 citationsNovel application of an automated-machine learning development tool for predicting burn sepsis: proof of concept.Nam K. Tran, Samer Albahra, Tam N. Pham, James H. Holmes, David G. Greenhalgh, Tina L Palmieri, Jeffery Wajda, Hooman H. Rashidi> ;Scientific Reports. 2020 Jul 23
- 34 citationsEarly Recognition of Burn- and Trauma-Related Acute Kidney Injury: A Pilot Comparison of Machine Learning Techniques.Hooman H. Rashidi, Soman Sen, Tina L Palmieri, Thomas Blackmon, Jeffery Wajda, Nam K. Tran> ;Scientific Reports. 2020 Jan 14
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Journal Articles
- Artificial intelligence and machine learning for predicting acute kidney injury in severely burned patients: A proof of concept. Burns. 2019 Jun 20.Tran NK, Sen S, Palmieri TL, Lima K, Falwell S, Wajda J, Rashidi HH., pii: S0305-4179(18)31129-X. doi: 10.1016/j.burns.2019.03.021., 6/2019
Hospital Affiliations
UC Davis Medical CenterSacramento, California
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