Statistics & Analytics
Description
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.
Note: Check with the institution regarding start/end dates, prices, and delivery method. These may vary according to program, section, and/or semester.
Note: Check with the institution regarding start/end dates, prices, and delivery method. These may vary according to program, section, and/or semester.
Overview
- Institution: McMaster University
- Level: University
- Language: English
- Course Code: HIF106
- Delivery Method: Entièrement en ligne/à distance
Disclaimer:
Check with the institution regarding start/end dates, prices, and delivery method. These may vary according to program, section, and/or semester.
Check with the institution regarding start/end dates, prices, and delivery method. These may vary according to program, section, and/or semester.