Syllabus
Master of Science in Health Informatics
HIN 715 – Health Data Analysis, Visualization, and Storytelling – Spring B 2021
Credits - 3
Description
Large data sets are not useful in their native state. Informaticists have to begin by defining the question that will be answered by the data and then organizing, analyzing, and visualizing the dataset. Analytics provide meaningful patterns in the data, and data visualization communicates the information clearly through graphical means. This course is designed to familiarize students with core concepts in communicating information through effective data visualization. This course introduces students to data visualization elements and best practices in data visualization using Tableau. Students will gain hands-on experience building explanatory and exploratory visualizations using healthcare data.
Materials
Learning Objectives and Outcomes
Program Outcome addressed by this course:
- Apply core concepts of database design to facilitate managing data produced and captured in the healthcare setting
Course Outcomes:
Upon completion of the course, students will be able to:
- Create a variety of types of graphics in order to visualize data appropriately
- Normalize data in order to make use of it in visualizations
- Evaluate a research question in order to select appropriate method(s) of visualization
Assignments
Please note that all times in the syllabus and in Blackboard refer to Eastern Time. The discussion board for each week will open at the start of the week for submissions.
Discussion Board Posts:
These assignments will assess your ability to clearly and accurately apply concepts from your readings and from your own experiences. Each week you are expected to submit an initial post and comment on at least 2 other students’ posts. You need to follow APA guidelines for citing any sources you may reference in either your initial post or your response to others. Refer to the Discussion Rubric and discussion question for submission guidelines.
Initial post: You should submit your initial post by 11:59 p.m. Sunday. Your initial post should be approximately 500 words.
Response to others: You should comment on at least 2 other students’ posts by 11:59 p.m. Wednesday. Your comments to others should be thorough, thoughtful, and they should offer some new content. Do not merely respond with “I agree” or “I disagree.” Engage directly with the ideas of your classmates and briefly mention which part of the post you are responding to.
Weekly Assignments:
In weeks 1-4 and 6 there are a number of short assignments. You will use either Tableau or Excel to create these assignments. Please see Blackboard for specifics and rubrics.
Key Assessments:
There are two key assessments for this course in which you will be asked to develop your own visualizations. The weekly assignments support and provide the knowledge and skills needed to complete these assessments. In these assessments, you will apply the core concepts in communicating information through effective data visualization.
Key Assessment 1, Explanatory Visualization Presentation – In week 5, you will use what you have learned in the first 4 weeks to create an explanatory visualization presentation to compare physician performance on a number of quality measures. Then, you will use a screencasting tool such as Screencast-o-Matic to present your visualizations. Please see Blackboard for specifics and rubrics.
Key Assessment 2, Exploratory Research, Visualizations, and Presentation – In this two-part assessment, you will integrate what you have learned into an interactive dashboard of your own creation.
Part 1: In week 7, you will research publicly available datasets for a health topic of your choice, then write a use case and description of your methods for visualizing your data, along with 3-5 references.
Part 2: In week 8, you will communicate your research visualizations in either a poster presentation or an interactive Tableau Dashboard. You will also record a 5-10 minute screencast presenting your visualization.
Please see Blackboard for specifics and rubrics.
Grading Policy
Your grade in this course will be determined by the following criteria:
Grade Breakdown
| Assessment Item | Possible Points | Percent of Total Grade |
|---|---|---|
| Discussion Forums (6) | 18 pts - (3 pts each) | 18% |
| Weekly Assignments (weeks 1-4, 6) | 42 points (point values vary by week) | 42% |
| Key Assessment 1: Explanatory Visualization Presentation (week 5) | 18 points | 18% |
| Key Assessment 2, Part 1: Exploratory Interactive Dashboard (week 7) | 10 points | 10% |
| Key Assessment 2, Part 2: Exploratory Visualizations and Presentation (week 8) | 12 points | 12% |
| Total | 100 pts | 100% |
Grade Scale
| Grade | Points Grade | Point Average (GPA) |
| A | 94 – 100% | 4.00 |
| A- | 90 – 93% | 3.75 |
| B+ | 87 – 89% | 3.50 |
| B | 84 – 86% | 3.00 |
| B- | 80 – 83% | 2.75 |
| C+ | 77 – 79% | 2.50 |
| C | 74 – 76% | 2.00 |
| C- | 70 – 73% | 1.75 |
| D | 64 – 69% | 1.00 |
| F | 00 – 63% | 0.00 |
Schedule
Course learning modules are divided into weeks. Each week starts on Wednesday at 12:00 am Eastern Time (ET) and closes on Wednesday at 11:59 pm ET, with the exception of Week 8, which ends on Sunday. All assignments must be submitted by 11:59 pm ET on the due date.
Course Schedule at a Glance
| Learning Modules | Topics | Assignments and Due Dates |
|
Week 1 Mar 3 – Mar 10 |
What is Data Visualization? |
Introductory Discussion Three Short Assignments due Wednesday |
|
Week 2 Mar 10 – Mar 17 |
Understanding Use Cases and Creating Simple Charts |
Discussion – Initial post by Sunday, responses by Wednesday Three Short Assignments due Wednesday |
|
Week 3 Mar 17 – Mar 24 |
Understanding Descriptive Statistics and Building Intermediate Charts (Part 1) |
Discussion -Initial post by Sunday, responses by Wednesday Four Short Assignments due Wednesday |
|
Week 4 Mar 24 – Mar 31 |
Understanding Descriptive Statistics and Building Intermediate Charts (Part 2) |
Discussion – Initial post by Sunday, responses by Wednesday Four Short Assignments due Wednesday |
|
Week 5 Mar 31 – Apr 7 |
Explanatory Visualizations |
Discussion – Initial post by Sunday, responses by Wednesday Key Assessment 1: Explanatory Visualization Presentation due Wednesday |
|
Week 6 Apr 7 – Apr 14 |
Principles of Good Visualizations |
Discussion – Initial post by Sunday, responses by Wednesday Create a Dashboard Assignment due Wednesday |
|
Week 7 Apr 14 – Apr 21 |
Exploratory Research and Visualizing Findings |
Discussion – Initial post by Sunday, responses by Wednesday Key Assessment 2, Part 1: Exploratory Research and Visualizations due Wednesday |
|
Week 8 Apr 21 – Apr 25 |
Communicating Results |
Discussion – Initial post by Friday, responses by Sunday Key Assessment 2, Part 2: Exploratory Visualizations and Presentation due Sunday |
Student Resources
Online Student Support
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Questions? Visit the Student Support Health Informatics page
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- MSIN Databases: https://library.une.edu/library-materials/find/research-by-subject/health-informatics/
- Library Tutorial: Find an article
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Attendance Policy
Online students are required to submit a graded assignment/discussion prior to Sunday evening at 11:59 pm ET of the first week of the term. If a student does not submit a posting to the graded assignment/discussion prior to Sunday evening at 11:59 pm ET, the student will be automatically dropped from the course for non-participation. Review the full attendance policy.
Late Policy
Assignments: Late assignments will be accepted up to 3 days late; however, there is a 10% grade reduction (from the total points) for the late submission. After three days the assignment will not be accepted.
Discussion posts: If the initial post is submitted late, but still within the discussion board week, there will be a 10% grade reduction from the total discussion grade (e.g., a 3 point discussion will be reduced by 0.3 points). Any posts submitted after the end of the Discussion Board week will not be graded.
Please make every effort ahead of time to contact your instructor and your student support specialist if you are not able to meet an assignment deadline. Arrangements for extenuating circumstances may be considered by faculty.
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