Course Syllabus

syllabus-gaynor-om-e-22.pdf

 

 

 

      

 

Department of Health Management & Policy

 

           

 

 

HMP-511

 

Health Operations Management

 

Summer 2022

 

Syllabus

 

May 23

 

In Optional in Class lab review/help Saturday June 4 via Zoom/Video

 

Office by Zoom (TBA)

 

 

 

 

 

Instructor:

Mark Gaynor

Professor

Salus Center

Cell Phone 314 – 308 - 9766

mgaynor@slu.edu

 

Office Hours: 

By appointment in person, phone, or Fuze meeting.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Introduction

This class will provide an introduction to the use of operations management in the healthcare industry.  This will give students the basics tools of decision science so that they understand how to use mathematical methods and thinking to optimize health care processes and operations.  The course will cover topics such as evidence-based medicine, optimization techniques including Linear programming, queuing theory, 6 Sigma, and Lean methods.

 

Purpose and Objectives   

This is a required class for MHA students that provides an introduction to operations management and quality control.

 

LEARNING OBJECTIVES

 

Course Learning Objectives	Cognitive / Affective	Level
1.     Appreciate the complex environment in which organizations utilize process improvement.	Affective	Receiving/ Attending
2.     Explain how organizations can use data to understand and improve the efficiency and quality of care.	Cognitive	Comprehension
3.     Align stakeholders with strategy by: (a)   Calculating the attributes of a process. (b)   Evaluating how to improve a process. (c)   Assessing if the improved process is meeting the intended goals.	Cognitive	Evaluation

 

 

MHA COMPETENCY

 

MHA Comp Domain	MHA Competency	Level (B, I, A)	Course Objectives	Assessment Methods
Critical Thinking	Able to understand and model systems	I	1	Final
	Able to make decisions in the presence of uncertainty	I	1, 2	Final
Science/Analysis	Understand the scientific method and how to apply it to decision-making and problem solving	I	1, 2, 3	Final
	Examine data quantitatively to determine patterns and trends	I	3	Final
	Learn how to effectively use complex analytical methods such as queuing theory and simulation	B	2, 3	Final
Communications	Develop, organize, synthesize and articulate ideas and information	I	1, 2, 3	Final

 

 

 

Course Description

 

Course Format:  This class will be comprised of a series of online lectures, one all day in class meeting, and special guest lectures.

 

Course Elements and Requirements:  Students will be expected to complete the required readings and other assignments as assigned.  Participation is a key element to this class, so be prepared with questions, concerns and topics of interest related to the readings and current events for the in class session. Students are expected to search for OM and IT healthcare related articles from sources such as the NY Times, Wall Street Journal, and other popular and research related venues. 

 

Grading Determination Policy 

 

Each student will be assessed on his/her performance and understanding of the material. The following distribution will comprise the final score:

• Final: 30% - The student must pass the final to pass the class
• Assignments 35%

1. Disruption Innovation (5%) –Due 5/30
2. Displaying Data with Tableau (15%) –Due 6/6
3. Process Analysis with QIMacros  (15%) –, Due 6/13

• 15% for 3 discussion posts.
• Each discussion is due on Monday night.  The discussion should be a summary and analysis of the reading or Case for the Week.  I will indicate which readings/case you should focus on in the schedule and for each module in Canvas .  This never includes the assigned reading from the text.  So, the second Monday the first discussion posting is due.  The third Monday, and the second discussion.
• You must post a introduction to yourself in the Intro Discussion. If possible I would like a video.
• You should respond to at least one student in the Student Introduction Discussion
• Tableau Labs 0%  - you will need to know how to use Tableau for the HW and final. All Labs on Video
• Tableau is complex and it is expected that this will be difficult and you may have problems.
• Lab 0  is an Introduction to Tableau Video.
• Lab 1 – 3 have exercises to do.
• I will have a optional zoom lab review/help session on Sat 6/4
• QI Macro Labs 0% - you will need the labs to do the homework and final. All Labs on Video
• QI macro lab 1 is an introduction of QI Macros.
• QI lab 2 will use real COVID data.
• Class Participation: 20%
• General class participation for in class session.
• Students start out at 80% and can gain or lose points

 

 

According to the University, the final grades that are allowed are: A, A- B+, B, B-, C+, C, C-, F and AF.

 

 

 

Week	Topics	Readings (See References)	Other Items
Pre 5/16 – 5-23	Read:   Posted Reading   Watch:   Intro to OM Intro to Web Site   Do:   ·       Student Introduction Discussion ·       Get Tableau ·       Get QIMacros	The Digital Doctor (Preface, Ch 1 (Intro), Ch 12 (The Error)) [1] Reading by Deming (the god of quality) [2]	Download Tableau Software! Request a student license from Tableau   Buy QI macros at the Student price
1 5/23/ - 5/30	Intro to OM for Healthcare Visualization of data Balanced Scorecard   Read:   Text and Posted Reading for week 1   Watch:   Videos for Week 1   Do:   ·       Student Introduction Discussion ·       Week 1 Reading Discussion ·       Tableau Labs 0 ·       Tabeau Lab 1 ·       HW 1	Text [3] Chapters 1 – 5;   Tufte reading on Cholera in London 1854 [5];   Data Visualization for 2018 [6]   Health Affairs Blog on MACRA [7]   Balanced Scorecard [8]   Skim Balanced Scorecard for Healthcare [9]   Tableau reading for Lab [16]	HW 1 Assigned, Due 5/30; Week 1 discussion Assigned, Due 5/30
2 5/30 – 6/6	Project Management Tools Intro to Stats   Read:   Text and Posted Reading for Week 2   Watch:   Videos for Week 2   Do: ·       Week 2 Reading Discussion ·       Tableau Lab 2 ·       Tableau Lab 3 ·       HW2	Text Chapters 6 – 8;   Cedar Sinai article [10];   Patient Preference (decision trees) [11];   Mistaking Proofing [12] (Chaps 1, 7, 8 and 9) Skim rest   Radiation of Patients #1 [13] Radiation of Patients #2 [14]   Patient-Experience Data and Bias – What Ratings Don’t Tell Us [15]   National Cancer Institute writeup on Mammograms   Breast Cancer Reading   Simulation in Healthcare [17]	HW1 Due; Week 1 discussion Due; HW2 Assigned, Due 6/6;
Zoom/VideoClass 6/4			Help withTableau Labs
3 6/6 – 6/13	Finish Stats Six Sigma and Lean   Read:   Text and Posted Reading for week 3   Watch:   Videos for Week 3   Do: ·       Week 3 Reading Discussion (Scanner Case) ·       QIMacro Lab 1 ·       QIMacro Lab 2 ·       HW3	Text Ch. 9 – 11   Case on Bed Turnaround [18];   Case on Scanner   Medication Errors [19];   Intro to Six-Sigma in Hospitals [20]   High-performance medicine: the convergence of human and artificial intelligence [21]   MIT professor’s AI predicts breast cancer .. mammograms   What Ever Happened to IBM’s Watson	HW2 Due; Week 2 discussion due HW3 Assigned, Due 6/13
4 6/13 – 6/20	Simulation, Supply Chain Management, and putting it all together   Read:   Text and Posted Reading for week 4   Watch:   Videos for Week 4   Do:   Final Due 6/20 at 11:59pm	Read Ch. 12 – 16 in Text;   Preface, Summary, and Introduction in Health IT errors [22]   Death By 1,000 Clicks: where Electronic Health Records Went Wrong [23]   Read nyt editorial about Paperwork Crisis [24]   Read Summary and Intro to Clinician Burnout [25] and/or watch: https://www.youtube.com/watch?v=iwswuifCWnw       Process Analysis Note [26]   Hint – Review Breast cancer readings from week 2 for final	Week reading 3 discussion due HW3 Due; Final Posted, Due

 

 

 

 

 

About the Course Instructor:

Mark Gaynor, PhD, MS, ME, MA is a Professor of Health Management at the College for Public Health and Social Justice at Saint Louis University. Mark’s PhD in Computer Science is from Harvard University. His research interests include distributed sensor networks for medical applications, innovation with distributed architecture, IT/HealthCare standardization, designing network based health care services, IT for healthcare, interoperability with HIT systems, and emergency medical services. He was CTO and member of the board of directors at 10Blade a small company building EMRs for NASA.  His first book, Network Services Investment Guide: Maximizing ROI in Uncertain Markets, is published by Wiley (2003). He has been a PI and Co-PI on several grants from Google, NSF, NIH, NSBI, and the US army. His current teaching includes Health Operations Management, Health Information systems, Security and Privacy of Health Care Information, and Green Belt Six Sigma for Health Care.

 

 

Academic Integrity Expectations and Policy

 

Refer to the Google site for academic resources at https://sites.google.com/a/slu.edu/pdf-host-site/policies-and-procedures for the module and policy.  Note, you are responsible for completing the academic integrity module during your first semester.  If you do not complete it, you will not be allowed to register for courses. Violation of Academic Integrity expectations and/or the Honor Code Pledge may result in severe consequences/penalties, up to and including expulsion.

 

All students enrolled in College for Public Health and Social Justice courses are also expected to abide by and uphold Saint Louis University’s Policy on Academic Integrity and Ethics.  This policy can be found at: the Google site for academic resources at https://sites.google.com/a/slu.edu/pdf-host-site/policies-and-procedures.

 

Just don’t do it because the expected gain is less than the expected loss.  If you like I can prove this for you J.

 

Policy on Style for Citation and Plagiarism

Please refer to the Google site for academic resources at https://sites.google.com/a/slu.edu/pdf-host-site/policies-and-procedures for the policy on style and plagiarism.

 

Student Support Services

In recognition that people learn in a variety of ways and that learning is influenced by multiple factors (e.g., prior experience, study skills, learning disability), resources to support student success are available on campus. The Student Success Center, a one-stop shop, which assists students with academic and career related services, is located in the Busch Student Center (Suite, 331) and the School of Nursing (Suite, 114). Students who think they might benefit from these resources can find out more about:

• Course-level support (e.g., faculty member, departmental resources, etc.) by asking your course instructor.
• University-level support (e.g., tutoring services, university writing services, disability services, academic coaching, career services, and/or facets of curriculum planning) by visiting the Student Success Center or by going to slu.edu/success.
  
  

Disability Services Academic Accommodations
Students with a documented disability who wish to request academic accommodations are encouraged to contact Disability Services to discuss accommodation requests and eligibility requirements. Please contact Disability Services, located within the Student Success Center, at Disability_services@slu.edu or 314.977.3484 to schedule an appointment. Confidentiality will be observed in all inquiries. Once approved, information about academic accommodations will be shared with course instructors via email from Disability Services and viewed within Banner via the instructor’s course roster. 

University Writing Services
We encourage you to take advantage of university writing services in the Student Success Center; getting feedback benefits writers at all skill levels. Trained writing consultants can help with writing projects, multimedia projects, and oral presentations. University Writing Services offers one-on-one consultations that address everything from brainstorming and developing ideas to crafting strong sentences and documenting sources. For more information for undergraduates, call 314-977-3484 or visit https://www.slu.edu/retention-and-academic-success/university-writing-services.

 

 

Reading

 

Text The textbook for this course is Healthcare Operations Management by Daniel Mclaughlin, John Olson and Luv Sharma.  Publication Date: Jan 30, 222 | SBN-13: 978-1640553071

ISBN-10: 164055307X

 | Edition: Fourth. It is available through the bookstore on at the following link on amazon.com:

https://www.amazon.com/Healthcare-Operations-Management-Fourth-Olson/dp/164055307X/ref=sr_1_1?crid=1LKNU0H0O74KW&keywords=healthcare+operations+management+mclaughlin&qid=1650038911&sprefix=health+care+operations+management+mclaughlin%2Caps%2C63&sr=8-1

 

Posted Reading

 

Pre-Week

Introduction and The Error– Drug prescribing error for a child from a talk by Dr. Watchter [1]

Quality, Productivity and Competitive Position - Reading by Deming (the god of quality) [2]

 

Week 1

Balanced Scorecard  – Overview of Balanced Scorecard

A Review of the Use of the Balanced Scorecard in Healthcare – Overview of how BS is used in HC with several good examples.

Visual display of Information – Tufte reading on Cholera in London 1854 [5], this is important and will be on the final.

Best DataVisualization in 2018 [6] – Good examples from 2018

MACRA Blog Post – Post from Health Affairs about Changes needed to improve MACRA [7]

Tableau for Healthcare [16] – Will help with Labs

 

 

 

Week 2

Cedar Sinai article [10] – A failed early EHR project

Patient Preference (decision trees) [11] – Probability trees, useful for HW2

Report on Error Proofing for Health Care [12] – Book by ASQ about mistake proofing

Two articles on Radiation Errors [13, 14] - NYT article about Radiation Errors on Cancer Patients (Skim)

Patient Experience and Ratings Bias [15]– Paper about looking past ratings.

National Cancer Institute on Mammograms – Good writeup about the technology

Breast Cancer Reading – About the statistics discussed in class.

Simulation in Healthcare [17] – Using simulation to teach management in healthcare.

 

 

 

 

healthcare

 

In Class Session

Simulation in Healthcare [17] – Using simulation to teach management in healthcare.

Intro to Tableau for data visualization [16]

 

Week 3

Case on Bed Turnaround [18] – Improving bed turnaround time

Medication Errors [19] – Preventing errors with prescribing medications

Six-Sigma in Hospitals [20] – Chapter 4 of Jay Arthur book on Six-Sigma in Hospitals

Using AI in Medicine [21] – Good overview of machine learning and AI in the future of medicine.

MIT professor’s AI – Discusses how to predicts breast cancer with AI

What Ever Happened to IBM’s Watson – What happened to Dr. Watson

 

 

Week 4

IT errors [22] – Book by IOM on how medical errors have changed with IT

Process Analysis Note [26] – Good write up on how to compute some process metrics, might be useful on the final

Death By A Thousand Clicks [23] – Good overview of some of the emerging problems with EHRs

Editorial in nyt about Paperwork Crisis [24] – discusses how Drs and Nurses can unite to help solve the paperwork crisis.

Report about Clinician Burnout [25] – New report about Burnout, very current.

 

 

 

 

 

 

References

 

1. Wachter, R., The Digital Doctor - Hope, Hype, and Harm at the Dawn of Medicine's Computer Age. 2015: McGraw Hill.
2. Deming, E., Quality, Productivity, and Competitive Position. 1982: MIT.
3. Mclaughlin, D., and Olson, John, Healthcare Operations Management (3rd edition). Second ed. 2017.
4. Medicine, I.o., Crossing the Quality Chasm. 2001.
5. Tufte, E., Visual Explanations: Images and Quantities, Evidence and Narrative - Cholera Case. 1997.
6. Kopf, D. The berst data visualization in 2018, according to data visualization experts. 2019 [cited 2019; Available from: https://qz.com/1513260/the-best-data-visualization-in-2018-according-to-data-visualization-experts/.
7. O'Shea, J., As MACRA Implementation Proceeds, Changes Are Needed, in HealthAffair Blog, H. Blog, Editor. 2017, Health Affairs: Health Affairs.
8. Institute, B.S., Balanced Scorecard Basics. 2011.
9. McDonald, b., A Review of the Use of the Balanced Scorecard in Healthcare. 2012.
10. Connolly, C., Cedars-Sinai Doctors Cling to Pen and Paper, in Washingtonpost. 2005: Washington. p. 4.
11. Ruland, C., Patient Preferences in Health Care Decision Making. 2002.
12. Grout, J., Mistake-Proofing the Design of Health Care Processes. 2007: Agency for Healthcare Research and Quality (ARQ).
13. Bogdanich, W., Radiation Offers New Cures, and Ways to Do Harm, in New York Times. 2010: nyc.
14. Bogdanich, W., As Technology Surges, Radiation Safeguards Lag, in New York Times. 2010: Nyc.
15. Poole, K., Patient-Experience Data and Bias – What Ratings Don’t Tell Us. The New England Journal of Medicine, 2019.
16. Benevento, D., Rowell, K., Steeger J., Cutrell, A. and Morales, M, The Best Boring Book Ever of Tableau for Healthcare (3rd edition). 2017.
17. Hamrock, E., et al., Discrete event simulation for healthcare organizations: a tool for decision making. Journal of healthcare management / American College of Healthcare Executives, 2013. 58(2): p. 110-24; discussion 124-5.
18. Pellicone, A., and Martcci, Maude, Faster Turnaround Time, in Solutions to the Health care Quality Crisis, S. Bisgaard, Editor. 2009.
19. Esimai, G., Lean Six Sigma Reduces Medication Errors, in Solutions to the Health care Quality Crisis, S. Bisgaard, Editor. 2009.
20. Arthur, J., Lean Six Sigma for Hospitals. 2011: McGraw Hill.
21. Topol, E., High-performance medicine: the convergence of human and artificial intelligence. Nature Medicine, 2019. 25.
22. Medicine, I.I.o., Health IT and Patient Safety: Building Safer Systems for Better Care. 2010.
23. Schulte, F.a.F., Erika, Death by 1,000 clicks: Where Electronic Health Records Went Wrong, in Fortune - Kaiser Health News. 2019.
24. Bergman, T.B.a.S., Doctors, Nurses and the Paperwork Crisis

That Could Unite Them, in New York Times. 2019.

25. National Acadedmies of Sciences, E., and Medicine, Taking Action Against Clinician Burnout: A Systems Approach to Professional Well-Being. 2019: National Academies Press.
26. University, B., Note on Process Analysis in Health Care. 1996, Boston University: Boston.
27. Gigerenzer, G., How to Know When Numbers Deceive You - Calculated Risks 2002: Simon & Schuster.
28. NIH. National Cancer Institute Discussion on Mammograms. 2016; Available from: https://www.cancer.gov/types/breast/mammograms-fact-sheet.
29. Group, M.S., Blanced Scorecards for Small Rural Hospitals: Concept Overview & Implementation Guidance, in Blanced Scorecards for Small Rural Hospitals: Concept Overview & Implementation Guidance.
30. Hermann, R., Regner, J., Erickson, P., Yang, D., Developing a Quality Management System for Behavioral Health Care: The Cambridge Health Alliance Experience. Harvard Review Psychiatry, 2000.
31. Cruz, P., Simulated Dendrochronology of U.S. Immigration 1790-2016. 2019.
32. WysockI, B., To Fix Health Care, Hospitals Take Tips From Factory Floor, in The Wall Street Journal. 2004.
33. Groop, J., Reijonsaari, Karita, and Lillrank, Paul, Applying the Theory of Constraints to Health Technology Assessment. International Journal on Advances in LIfe Sciences, 2010. Vol 2.
34. Youngman, K., A Guide to Implementing the Theory of Constraints (TOC). 2008, Theory of Constraints Healthcare.
35. Does, R., Vermatt, Thijs, Koning, Henk, Bisgaad, Soren, and Heuvel, Van, Standardizing Healthcare Projects, Generic Teplates are Useful for Early DMAIC Phases, in Solutions to the Health cre Quality Crisis, S. Bigaard, Editor. 2009.
36. Improvement, I.f.H., Going Lean in Health Care, in Innovation Series 2005. 2005.
37. ASQ. National Healthcare Quality Report. 2017 2014; Available from: https://www.ahrq.gov/sites/default/files/wysiwyg/research/findings/nhqrdr/2017nhqdr.pdf.
38. Louis, B.S., St. Louis Health Care Industry Overview - Hospital and Financial Overview. 2018.
39. Louis, B.S., St. Louis Health Care Industry Overview - Outpatient and Physician Care. 2018.