HIT 103 - Healthcare Statistics & Data Mining
Credits: 4
2 Lecture Hours 4 Lab Hours
Prerequisites: HIT 100 , MAT 108
Co-requisites: MAT 161 or MAT 165
Description
This course presents students with an introduction to healthcare statistics and data manipulation in multiple environments. Students explore topics such as spreadsheets, case-mix index, basic epidemiology, data mining, calculating statistics for healthcare operations, data visualization, research methodologies in healthcare and data management.
Learning Outcomes
Upon successful completion of the course, the student will:
- Generate statistical reports using latest industry tools such as R programming language.
- Create spreadsheets for business operations.
- Prepare data for visualization and mining.
- Design data visualizations utilizing Tableau and Excel.
- Describe Python’s role in data mining.
- Interpret data for hospital and community disease control.
- Analyze the role of case-mix in hospital planning.
- Apply research methodologies.
Listed Topics
- Excel workbook functions and formulas
- Programming languages
- Data cleaning
- Healthcare statistics
- Data manipulation
- Data presentation
- Case-mix
Reference Materials
Textbook, software packages, various internet sites, etc.
Students who successfully complete this course acquire general knowledge, skills and abilities that align with CCAC’s definition of an educated person. Specifically, this course fulfills these General Education Goals: - Quantitative & Scientific Reasoning
- Technological Competence
Approved By: Dr. Quintin B. Bullock Date Approved: 12/15/2023
Last Reviewed: 12/15/2023
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