Accreditation Statement: The activity has been planned and implemented in accordance with the Essential Areas and policies of the Accreditation Council for Continuing Medical Education (ACCME) through the joint sponsorship of the University of Massachusetts Medical School Office of Continuing Medical Education (UMMS-OCME) and the Institute for Healthcare Optimization (IHO). The UMMS-OCME is accredited by the ACCME to provide continuing medical education for physicians.
CME Credit Statement: The University of Massachusetts Medical School designates this live activity for a maximum of 7 AMA PRA Category 1 Credits™. Physicians should only claim credit commensurate with the extent of their participation in the activity.
Other: Other professionals will be eligible for 7 continuing education hours from the University of Massachusetts Medical School.
Certification: All those who sign in on each day attended and complete a course evaluation will receive a certificate of credit. Each person should claim only those hours of credit that he/she actually spent in the educational activity.
CME Inquiries: For all CME certificate inquiries, please contact the UMMS-OCME register at (508) 856-1671 or (877) 234-1673
Intended Audience: Physicians, nurses, performance improvement specialists and hospital administration
Course Objectives: At the conclusion of the conference, the participant will be able to:
- Understand the different types of variability in healthcare delivery (patient flow variability, clinical variability, provider variability, etc.) and how to manage each.
- Identify the appropriate queuing theory model to use in different situations.
- Collect accurate data needed for different queuing models.
- Perform various mathematical calculations to determine resources (e.g. staff) and service levels (e.g. waiting times), as well as to implement changes in their operational service areas.
- Work collaboratively with other performance improvement staff with queuing theory expertise to provide them with accurate input data and clinical perspective, and to understand the outcomes of queuing analyses performed by others.