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Class Notes

Healthcare Analytics

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.

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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'

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    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)

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    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 ASSIGNED l u r i v READINGS ASSESSMENT/ ACTIVITY DUE DATE I Aug 23 Foundations of Healthcare Analytics * Definitions * Brief history 7 * Types of Analytics * Examples ■ Lecture Notes ■ Chapters 1-3 (Burke)

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