Population-Wide Modelling of Immunologic Risk and Infection Susceptibility

Needs Statement

Physician informaticists, nurse informaticists, data analysts, data programmers, developers of health information technology, informatics technicians, and healthcare practitioners and trainees need to receive regular updates on the role of informatics in healthcare and recent advances in the field. The series aims to review current methods for using large sets of healthcare data to solve clinical problems and to support quality patient care. The series also aims to demonstrate how to integrate findings across health systems, synthesize proposed plans for quality improvements, and use such tools as geomapping to better delineate health problems within communities.

Target Audience

Physicians, fellows, residents, medical students, nurses, and other health professionals.

Learning Objectives

At the conclusion of the session, the participants should be able to:

  • Discuss how claims and HER data are being used to improve outcomes for patients with inborn errors of immunity.

  • Describe the role that computational methods can play in detecting patients with a rare disease.

  • Differentiate research artificial intelligence and machine learning from that which is embedded into a clinical workflow for care coordination.

Course summary
Available credit: 
  • 1.00 AMA PRA Category 1 Credit™
  • 1.00 Participation
Course opens: 
Course expires: 

Baylor College of Medicine is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to provide continuing medical education for physicians.

Baylor College of Medicine designates this enduring material activity for a maximum of 1.00 AMA PRA Category 1 Credit(s)™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.

Available Credit

  • 1.00 AMA PRA Category 1 Credit™
  • 1.00 Participation
Please login or register to take this course.