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Corra, McMaster University Continuing Education Health Information Management graduate Corra, McMaster University Continuing Education Health Information Management graduate

Health Information Management

Managing information throughout the health care system.

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HTH 119 - Data Analytics for Healthcare- Spring 2020

Academic Credit Value:
3 units
Course Delivery Mode:
Hours of Study:
36 hours
Course Prerequisite(s):
HTH 101 Health Information Management I, HTH 102 Health Information Management II, HTH 108 Information Analysis & Data Analytics
Course Anti-requisite(s):
Instructor Name:
Dennis Cheung
Course Dates:
05/11/2020 - 07/12/2020

Required Course Materials:
1. A Practical Approach to Analyzing Healthcare Data, 3rd Ed. 2. Fundamentals of Health Information Management, 2nd Ed. 3. EHR Go Subscription
Optional Course Materials:
Course Description:
The application of data analysis methods and tools can provide an organization with meaningful insights for improvement and strategic planning. This course will examine different types of health information data - how the data is collected, mined, analyzed and interpreted – for the purposes of quality, performance and utilization management. The use of data analysis tools and practices provides a practical approach for understanding the impact data analytics has within the health care system.
Learning Outcomes:

Upon completion of this course, students will:

1. Define data analytics

2. Identify types of health care data and collection processes

3. Describe the role of data analysis for planning and decision making processes

4. Apply the tools and techniques used for data analytics in health care organizations

5. Analyze patterns and trends in data sets/systems

6. Create data reporting and visualization objects (effectively communicate data analysis insights)

7. Develop an analytic strategy to frame a health care issue and solution

8. Apply analytics to various contexts of quality and performance improvement

Course Evaluation
The final grade is calculated based on the following components:
Labs: 25% Assignments: 40% EHR Go Activities: 35%
Course Format:
This course is designed to present the fundamental concepts and theories of data analytics in healthcare. Course learning will include instructor podcasts required readings from textbooks and other source materials and content-related videos. Course activities will focus on practical application of learning via assignments with real-world applications, labs, and data analysis and visualization activities in a simulated EHR environment.
Assignment Submission:
Course assignments are submitted to the appropriate A2L Assignment folder by the specified due date
Late Coursework:
Late assignments will be subject to a 2% per day late penalty (includes weekends and holidays) for up to seven (7) days. After this date, no assignments will be accepted and a grade of zero (0) will be applied. Extensions for course work must be approved by the instructor before the due date (see Academic Regulations below), and will be granted for illness or emergencies only. Students may be asked to submit supporting documentation for an extension request.

Policy & Procedures:

Academic Regulations (Attendance, Coursework, Tests/Exams):
(Attendance, Coursework, Tests/Exams):
In accordance to McMaster University’s General Academic Regulations, “it is imperative that students make every effort to meet the originally scheduled course requirements and it is a student’s responsibility to write examinations as scheduled.” Therefore, all students are expected to attend and complete the specific course requirements (i.e. attendance, assignments, and tests/exams) listed in the course outline on or by the date specified. Students who need to arrange for coursework accommodation, as a result of medical, personal or family reasons, must contact the course instructor within 48 hours of the originally
scheduled due date. It is the student’s responsibility to contact the Program Manager to discuss accommodations and procedures related to deferred tests and/or examinations within 48 hours of the originally scheduled test/exam, as per policy. Failure to contact the course instructor, in the case of missed coursework, or the Program Manager, in the case of a missed test/examination, within the specified 48-hour window will result in a grade of zero (0) on the coursework/exam and no further consideration will be granted.
*Note: Supporting documentation will be required but will not ensure approval of accommodation(s).
Academic Integrity
You are expected to exhibit honesty and use ethical behaviour in all aspects of the learning process. Academic credentials you earn are rooted in principles of honesty and academic integrity. Academic dishonesty is to knowingly act or fail to act in a way that results or could result in unearned academic credit or advantage. This behaviour can result in serious consequences, e.g. the grade of zero on an assignment, loss of credit with a notation on the transcript (notation reads: “Grade of F assigned for academic dishonesty”), and/or suspension or expulsion from the university.
It is your responsibility to understand what constitutes academic dishonesty. For information on the various types of academic dishonesty please refer to the Academic Integrity Policy, located at
The following illustrates only three forms of academic dishonesty:
1. Plagiarism, e.g. the submission of work that is not one’s own or for which other credit has been obtained.
2. Improper collaboration in-group work.
3. Copying or using unauthorized aids in tests and examinations.
Academic Accommodations:
Students with disabilities who require academic accommodations must contact the Student Accessibility Centre (SAS) to meet with an appropriate Disability Services Coordinator. To contact SAS, phone 905-525-9140 ext. 28652, or email For further information, consult McMaster University’s Policy for Academic Accommodation for Students with Disabilities.
On-line Elements:

In this course, we will be using on-line elements, which may include email, Avenue to Learn, WebEX, and external web sites. Students should be aware that, when they access the electronic components of this course, private information such as first and last names, user
names for the McMaster e-mail accounts, and program affiliation may become apparent to all other students in the same course. The available information is dependent on the technology used. Continuation in this course will be deemed consent to this disclosure. If you have any questions or concerns about such disclosure please discuss this with the course instructor.
In this course, we will be using a web-based service ( to reveal plagiarism. Students will be expected to submit their work electronically to and in hard copy so that it can be checked for academic dishonesty. Students who do not wish to submit their work to must still submit a copy to the instructor. No penalty will be assigned to a student who does not submit work to All submitted work is subject to normal verification that standards of academic integrity have been upheld (e.g., on-line search, etc.). To see the Policy, please go to McMaster Academic Integrity Policy.
Course Changes:
The instructor reserves the right to modify elements of the course and will notify students accordingly.
Course Withdrawal Policy:
Policies related to dropping a course and course withdrawals are posted to the Centre for Continuing Education’s program webpage, FAQs & Policies (
Grading Scale:
Grade                        Equivalent
Grade Point

A+                                     12                                 90-100
A                                      11                                  85-89
A-                                     10                                  80-84
B+                                      9                                   77-79
B                                        8                                   73-76
B-                                       7                                   70-72
C+                                      6                                   67-69
C                                        5                                   63-66
C-                                       4                                   60-62
D+                                      3                                   57-59
D                                       2                                   53-56
D-                                       1                                   50-52
F                                        0                                    0-49
Course Schedule:

Module 1: Introduction to Data Analysis
Assignment 1 – Wait Times

Module 2: Health Information Data
Lab 1 – Healthcare Data
EHR Orientation to Data Analytics I

Module 3: Decision Support & Data Warehousing
EHR Applied Data Analytics II
EHR Assessing Employee Productivity

Module 4: Data Organization, Analysis and Visualization
Lab 2 – Data Dictionary and Excel
EHR Applied Data Analytics III

Module 5: Analytical Variables
Lab 3 – Statistical Analysis

Module 6: Data Analytics in Research
Lab 4 – Study Form
EHR Orientation to Data Visualization IV

Module 7: Data Analytics and Quality Improvement
Assignment 2 – Case Costing

Module 8: Data Analytics and Performance Management
Assignment 3 – Balanced Scorecard
EHR Quality Improvement with the EHR

Module 9: Trends, Predictive Analytics, and Big Data
EHR Clinical Reminder Data Visualization V