This course will enable learners to apply descriptive statistical theory for continuous and categorical healthcare data including central tendency measures, and hospital statistics. Learners will employ commonly used statistical software systems. Relevant sources of data such as DAD, NACRS, RAI, MIS, etc. will be utilized. The course will introduce common principles and practices to create performance indicators, standards, benchmarks, metrics, reports, etc. including methodology, definitions, and visualization. Graphical and tabular presentation of healthcare data to facilitate decision making will be explored. Learners will examine business intelligence (BI) tools used to locate, store, retrieve, analyze, and present data and information from multiple sources and policies and processes for those BI tools. The course will summarize how BI can be utilized for personal information need and information-seeking behaviour. Principles and practices for applying machine learning, artificial intelligence, predictive analytics, data modelling, patient flow modelling, and dataflow diagrams will be discussed.
No Scheduled Class Meetings, February 12 - April 21 (Online)
Location:
ONLINE
Instructor:
Karen Pietrangelo
Notes:
This course will include 2-3 non-mandatory webinars throughout the term. Dates of the Webinars will be posted in the course schedule in the Learning Management System. All webinars will be recorded. Please note registering after the course start date may delay course access and does not permit exceptions to coursework due dates, late textbook purchases, or the refund policy
