Healthcare Analytics

Name: Healthcare Analytics
Brand: Academic Documents Platform
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Author: Daniel Miller

Outlines university policies on class recordings, participation, and use of course materials. Emphasizes student responsibilities, access restrictions, and adherence to the Student Code of Conduct to ensure academic integrity and privacy.

Daniel Miller

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Course Syllabus
Course Information
Course Humber/Section
Course Title
Term
Meetings
HMGT 6334.MIS 6305
Healthcare Analytics
Fall 2023
Wednesdays 7 PM
Professor Contact Information
Professor
Office Phone
Email Address
Office Location
Office Hours
TA:
TA Office Hows
Mehmet U.S. Ayvaci
972-883-4747
[email protected]
JSOM3202
By email
Ozgur Aksoy, [email protected]
By email
Course Modality and Expectations
Course Platform This class is taught in the classroom.
Expectations
(1) Students can attend class in person.
(2) Students can use the class time to interact with the instructor real
time.
(3) There is no class attendance requirement for lectures, but attendance
can help in boosting grades through extra credit.
(4) Instructor will post discussions on a regular basis, using eLearning
tools. Student involvement in these discussions accounts towards
participation (which boosts your grade and ensures engagement).
Learning
Guidelines
All lecture material will be available for all students (lecture will not be
recorded You need to follow along at the pace of the class whether you
attend the class or not.
Course Pre-requisites* Co-requisites, and/or Other Restrictions
OPRE 6301 or SYSM6303 (Co-requisite).
This course is an approved elective for the M.S. degree in Healthcare Management and for
the Healthcare Analytics track in the NLS. degree in Business Analytics. It is also an
elective course for the M.S. degree in Information Technology Management (Healthcare
Systems Track) and the MBA degree (Healthcare Concentration). The course is ideally
suited to students who wish to focus on careers in the healthcare industry, as health IT
analysts, policy analysts, managers or administrative staff, or healthcare consultants, who
wish to develop a better understanding of healthcare analytics.
Healthcare Certificate Program Requirements
A qualifying grade in this class fulfills one of the requirements to receive an Academic Certificate
in Healthcare Information Technology from UTD. For more information or to apply for
admission to the certificate program, please go to https? osim.utdallas.edu program-
resources.'healthcare-certificateshealthcare-it'

Course Description
The purpose of this course is to introduce the use of business intelligence and decision
analytics for health-care problems. As the pressures of managed care and increasing health
care costs push providers, payers and purchasers of health care to become more efficient,
methods for understanding the appropriate basis for how to allocate shrinking health care
resources must be understood. Moreover, the health care industry is yet to- find ways to
maize best use of existing data to improve care, reduce costs, and provide more accessible
care. In addition to developing a conceptual understanding of business intelligence and
predictive analytics, the course will develop some technical skills in prescriptive analytics
using decision analysis and cost effectiveness. The course will include hands-on experience
with R using RStudio. Examples from the health care practice and managerial decision
making will be discussed.
Major topics in this course include:
• Foundations of healthcare analytics
• Healthcare delivery in the US and data creation process
• Medical decision making and Machine Learning Foundations
• R programming
• Measuring healthcare quality and value
• Data mining for improving health outcomes and reducing costs
• Predictive models in healthcare and clinical decision support
• Data-driven decision making in healthcare
• Cost-effectiveness analysis for medical decisions
• Future of healthcare analytics
Student Learning Objectives and Outcomes
1. Students will demonstrate applications of data analytics related to healthcare information
to develop decisions and healthcare management strategies.
2. Students will demonstrate know-how of how to extract and apply business intelligence
techniques to improve decision making using healthcare data.
CAHME Competency Model Mapping
Domain 2: Leadership
• Critically analyze organizational issues after a review of the evidence. (SLO1)
Domain 5: Business Knowledge and Skills
• Demonstrate an ability to analyze and evaluate information to support a decision or
recommendation (SLO 1)
• Show the ability to critically think and analyze data (SLO 2)
• Demonstrate an understanding of using analytics software to draw conclusions (SLO 2)
Mandatory Text:
Burke, J. Health analytics: gaining the insights to transform health care (Vol. 71). John
Wiley & Sons. ( Available Online Ll1 D Library]
Viswanathan, V. (2014). Data Analytics with r?: J Zfanfifc-OK Approach. Infivista Incorporated.
Recommended Text:
Data .Vining with Rattle and R by Graham Williams, 2011, Springer Publishing. ISBN 978-1-
4419-9890-3. (Available online at the library webpage)

Clinical Prediction Models: A Practical Approach io Development, Validation, and Updating by
Ewout W . Steyerberg, 2010, Springer Publishing. ISBN 978-1-4419-2648-7. (Available online at
the library)
Healthcare Analytics for Quality and Performance ImprovemertiS Trevor L. Strome, 2013.
Wiley Publishing, ISBN: 978-1-118-51969-1
of Health Care Programmes, Second Edition by Drummond MF, O'Brien
B: Stoddart GL, Torrance GW, Oxford Medical Publications, Oxford 1997.
Required Software:
j? software and Rattle add on. These are free software available for download and installation at
Open Source R Software: http: cran.r-project.org Please make sure you have downloaded R and
RStudio in your machine before attending. You can follow the step-by-step instructions from the
above link or this link: https: www.earthdatascience.org. courses earth-analytics document-your-
science setup-r-rstudio Depending on your operating system of your machine, please refer to the
sections in the webpage. At some point in the class, I will also introduce Rattle, an R add-on,
which can be found at http: rattle.togaware.com
Mandatory Readings: The instructor will supplement the text with other relevant course
materials as needed including but not limited to executive interviews, case studies, scholarly
journal articles, newspaper articles, magazine articles, and other relevant information. Visit
eLearning for all course-related information including syllabus, lecture notes, self-quizzes, and
assigned discussion problems.
Textbooks and some other bookstore materials can be ordered online through Off-Campus Books
or the L I’D Bookstore. They are also available in stock at both bookstores.
Suggested Course Materials
Suggested ReadingsTexts
The instructor will supplement course materials with other readings via email or web
links. No need for purchase.
Suggested Materials
None
Textbooks and some other bookstore materials can be ordered online or purchased at the UT
Dallas Bookstore.
Academic Calendar
MODULE/
DATES TOPIC ASSIGNEDl u r i v READINGS ASSESSMENT/
ACTIVITY
DUE
DATE
I
Aug 23
Foundations of Healthcare
Analytics
* Definitions
* Brief history7
* Types of Analytics
* Examples
■ Lecture Notes
■ Chapters 1-3
(Burke)

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