Lecture: 4 hours/week
or
Hybrid: 2 hours/week in class and 2 hours/week online
In this course, students engage in a variety of learning activities such as lectures, case study analysis, independent research, exercises, training on data classification technology, participant presentations, classroom discussions and guest speakers.
- Population grouping methodology
- Case mix groups (CMG+) methodology
- Resource intensity weights (RIW) and expected length of stay (ELOS)
- Acute ambulatory care grouping methodology - Comprehensive Ambulatory Classification Systems (CACS)
- Analysis of quality, risk, utilization and financial management of healthcare using data from population, inpatient and ambulatory care grouping methodologies
- Concepts of ethics, equity, diversity and inclusivity supported by data management
At the end of the course, the successful student will be able to:
- apply case mix groups methodologies to analyze health outcomes from the quality, risk, utilization and financial management perspectives;
- apply population grouping methodologies to analyze health outcomes within various sectors;
- apply CACS methodologies to analyze health outcomes provided by ambulatory care services;
- create geographical information visualization using ArcGIS software (ESRI Canada) to facilitate monitoring and trending of health outcomes across the care continuum on a regional, territorial, provincial, and national level;
- determine methods to address concepts of ethics, equity, diversity and inclusivity supported by health data.
The course evaluation is consistent with the ÌÇÐÄvlog´«Ã½Evaluation Policy. An evaluation schedule is presented at the beginning of the course. This is a graded course. All assignments must be completed to pass the course.
A list of required and optional textbooks, materials and electronic applications is provided for students at the beginning of each semester.