HIT 216 - Healthcare Data Analytics

Credits: 3
1 Lecture Hours 4 Lab Hours

Prerequisites: HIT 103, HIT 210 and MAT 165

Description
In this course, students manage, analyze, interpret and transform data. Basic concepts for machine learning are introduced. Commonly used languages and tools for data are introduced including Python and Java. Students are prepared for the competencies addressed in the Certified Healthcare Data Analyst (CHDA), including cleaning and organizing data for transformation, visualizations and validation.

Learning Outcomes
Upon successful completion of the course, students will:

Examine trends, applications, benefits and risks of Artificial Intelligence (AI) and machine learning.
Determine analytical methods.
Describe automation processes in electronic health records.
Extract healthcare data from various sources using Python.
Analyze healthcare information using industry-specific tools.
Perform data cleaning, validation and mapping.
Perform machine learning.

Listed Topics

Java and Python
Data mining
Data validation
Data visualization and presentation
Machine learning
Fraud, waste and abuse

Reference Materials
Current appropriate software and textbooks

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: 04/13/2025
Last Reviewed: 04/13/2025

Course and Section Search