AI processes to improve tobacco use treatment in outpatient and inpatient care
This continuing education webinar will examine the use of artificial intelligence (AI) to enhance tobacco use treatment in both outpatient and inpatient care settings. Participants will explore current AI applications that support the identification, engagement, and monitoring of patients who use tobacco, with a focus on tools such as predictive risk modeling, clinical decision support, and automated follow-up. The session will review evidence on the effectiveness and limitations of these technologies in improving treatment outcomes. Attendees will also learn strategies for integrating AI-supported processes into clinical workflows to promote patient-centered counseling, initiate pharmacotherapy, and ensure continuity of care across settings.
Target Audience
- Nurses
- Nurse Practitioners
- Physicians
- Physician Assistants
- Pharmacists
Learning Objectives
- Describe current applications of artificial intelligence in identifying, engaging, and monitoring patients who use tobacco in both outpatient and inpatient settings. --
- Evaluate evidence on the effectiveness and limitations of AI-driven tools—such as predictive risk modeling, clinical decision support, and automated follow-up—in improving tobacco treatment outcomes. --
- Develop strategies to integrate AI-supported processes into clinical workflows that enhance patient-centered counseling, pharmacotherapy initiation, and continuity of care across care settings.
ACPE - Pharmacist
AMA PRA Category 1 Credit(s)
ANCC
Attendance
IACET CEU
JA Credit - AH
Available Credit
- 1.00 ACPE - Pharmacist
- 1.00 AMA PRA Category 1 Credit(s)™
- 1.00 ANCC
- 1.00 Attendance
- 1.00 JA Credit - AH
- 1.00 Approved for AMA PRA Category 1 Credit(s)™

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