Format: E-course
Duration: Approx 60 min
Instructors: CORAL MED
Learning Credits: 0.1 CEU
*This course was updated on Aug 18, 2025.
This Course introduces analytics tools, predictive modeling, and data visualization to improve healthcare quality and organizational decision-making.
By the end of this course the learner will be able to apply data analytics, create predictive models, implement decision support systems, and evaluate outcomes of data-driven strategies.
Learners will be able to apply advanced analytics tools to improve healthcare quality and make evidence-based organizational decisions.
Recommended: CMED_HDMI_102 or equivalent experience.
Follow Coral Plus LMS policies: participation, integrity, respectful conduct, HIPAA/privacy adherence, timely completion of assessments. 1. Participants should register in advance to receive access details. 2. Access links and passwords, if applicable, should be provided securely to registered participants. 3. Participants are encouraged to join the webinar a few minutes early to resolve any technical issues 4. Participants are responsible for ensuring a stable internet connection, compatible devices (computer, tablet, or smartphone), and recommended browsers. 5. A microphone and webcam may be required for interactive sessions. Please test your audio and video settings in advance. 6. The webinar may be recorded for educational purposes. 7. Recorded sessions may be shared with registered participants after the webinar. 8. Please be mindful not to share personal or confidential information during the webinar. 9. A detailed agenda will be provided, and each session will adhere to the schedule to cover all planned topics. 10. Time will be allocated for Q&A sessions and discussions. 11. A helpdesk or contact information for technical support will be provided during the webinar. 12. Common technical issues will be addressed at the beginning of the session. 13. Relevant resources, such as presentation slides or additional reading materials, will be shared after the webinar.
Data analysts, informaticians, health IT staff, program managers