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Health Information Analytics Courseware
1. 1
Health Information Analytics
Course Syllabus: HCAD 6635
Fall 2016
West Haven Campus MAXY 200A
University of New Haven
Instructor
Frank F. Wang, MBA, MS 203-558-0095 (Cell)
(FWang@newhaven.edu)
Prerequisites:HCAD 6620
Learning Objectives and Competencies:
Learning Objectives and Competencies
1.Learn how health analytics can help support a more efficient, more
effective, and lessexpensivehealthcare system.
2.Understand what analyticsisand is not, what healthcareanalyticsisand is
not, and learn what the key elementsofa good business
intelligence/analyticssystem are.
3.Learn conceptsof data,data management,data acquisition and data
enrichment.Recognizethe importanceofdata quality and data governance
in healthcareanalytics.
4.Study a framework of healthcareanalyticsstrategydevelopment and
implementation by aligning businessobjectives,analytical needs,and
information technologyapproaches.
5.Study basic healthcare qualitymeasures,key performanceindicators(KPI)
required by regulatorybodiesand how they are reported. Engage
physicians, patients, and payersto develop appropriatequality system.
6.Learn how to select the optimaldata display to present healthanalytic
data; appreciatethe art and science ofdata visualization.
2. 2
7.Study examplesof a traditional healthcaredata warehouseand
understand conceptsofdata transformation (ETL),metadata,masterdata
management(MDM),controlledvocabulary,ontologyand data standards.
8.Review basic statistics and apply appropriately in healthcare data discovery.
Performrealworld evidence-based data analysis (healthdata.gov)to develop
competencies of descriptiveanalytics and diagnostic analytics skills.
9.Explore data-driven healthcarequalityand performanceimprovement
initiativesassociated with value-based purchasing and bundled payments.
Review continuousprocessimprovement frameworksused in healthcare.
10. Develop skills in manipulating and analyzing largedatasets using
Microsoft Excel, and gain familiarity with SPSS. Develop skillsto choose
different businessintelligence and analyticsplatforms.
11. Learn advanced analytics(predictiveanalytics)in health care in relation
to analytic needsofpopulation healthmanagement and accountablecare
organizations.
12.Study concepts ofbig data analyticsand how it differentiatesfrom
traditional warehousetechniques. Explorethe use of big data analysisin
translational medicineand personalizedmedicineresearch.
Course Dates
Class 1 Sept 1 2016 Thursday 6:00 – 8:40 PM
Class 2 Online
Class 3 Sept 8 2016 Thursday 6:00 – 8:40 PM
Class 4 Online
Class 5 Sept 15 2016 Thursday 6:00 – 8:40 PM
Class 6 Online
Class 7 Sept 22 2016 Thursday 6:00 – 8:40 PM
Class 8 Online
Class 9 Sept 29 2016 Thursday 6:00 – 8:40 PM
Class 10 Online
Class 11 Oct 6 2016 Thursday 6:00 – 8:40 PM
Class 12 Online
Class 13 Oct 13 2016 Thursday 6:00 – 8:40 PM
3. 3
Class Format
This is a "blended" course meaning that some of the classes are taught in the conventional classroom
format, face to face, and others are taught "on line" per University of New Haven Policy.
ď‚· Live Classes: These classes are more interactive in nature requiring active student
participation.
ď‚· On-line Classes: Some materials as well as learnings on how to use analytics software
are prerecorded and delivered online within the blackboard.com system. Students are
expected to learn these materials and complete assignments on time.
Required Textbook
o Trevor Strome, Healthcare Analytics for Quality and Performance Improvement,Hoboken: John
Wiley & Sons, Inc., 2013
For Reference
o HealthCatalyst. It All Starts with a Data Warehouse, HealthCatalyst.com, 2014.
o David Burton, MD. Accountable Care Transformation Framework, HealthCatalyst.com, 2016.
Supplemental Materials
Other materials for the class will be posted in the “MODULES” and “CONTENTS” section of
Blackboard.com. These are materials I have acquired over past few years and they will be used in
conjunction with the textbooks. Additionally, here is what you will find posted on blackboard:
ď‚· This syllabus
ď‚· Detailed class agenda
ď‚· Copies of all the PowerPoints used in class
ď‚· Supplemental reading materials
ď‚· Templates for all business cases and presentations
ď‚· Healthcare business intelligence and analytics artifacts
Evaluation Criteria
The final grade will be based on in-class participation and performance on individual and group
assignments, as described below. There will be no final examination. Instead, I will try to “ease”
student evaluation over the course of eight weeks, in an effort to reduce test anxiety about an impeding
final. I hope this approach will allow students to focus more on the course material and apply them
to case studies/projects/presentations without culminating towards a singular examination.
In Class ParticipationandQuizzes (30% of grade)
All students are expected to attend “ALL” classes and be on time. Missing one class means missing a
significant part of the overall course material due to the accelerated nature of the course. In class
participation will be evaluated based on active participation and occasionally quizzes. I came
from industry and recognize that some students work full time jobs that may require business
travel and that illness does occur. All absences and tardiness must be discussed with the
instructor in advance.
4. 4
Take Home Assignments (40%of grade)
After each online session, there will be assignments including data analysis, business case studies,
development of analytics strategies and governance models. Sample templates and real world examples
will be provided to help students complete the assignments. Students are expected to complete
assignments on time. The instructor will need to concur with any delay in home assignment completion.
TeamAssignment(30% of grade)
Because health analytics is generally performed in groups, I will assign students to groups of four to
complete a teamwork assignment. The teamwork assignment will be based on real world
analytics problems bought to the class by students. Groups will be created by on Sept 1 in
the class. On the final day of our onsite class (Oct 13, 2016), imagine that I am the CEO of your
healthcare facility, and the rest of the students are members of the operating committee including the
COO, CFO, CMO, CNO, CIO and CMIO, you are giving this presentation to persuade us to make a
decision (to launch a new performance and quality improvement project, to develop a data warehouse to
facilitate clinical transformation, to show case your population health management tools for us to buy)
based on your analysis. This exercise will allow each group to learn from the others and recognize
the different roles healthcare analysts can play. Grades will be based on the written reports/slide decks
submitted prior to the meeting and on the presentations. All students are expected to present
and to exchange ideas during the discussions. We will spend the group presentation session
reviewing strategies different groups employed to manipulate, analyze, and visualize the data.
The best way to succeed in this class will be to attend all the lectures, interact with the content
actively, play a proactive role in the group assignments, and do the readings.
Course Grading Scale:
99-100 A+
94-98 A
90-93 A-
88-89 B+
87-84 B
83-80 B-
78-79 C+
77-74 C
73-70 C-
69-68 D+
67-64 D
63-60 D-
59 and less F
5. 5
Expectations and Policies: Information about university grades
can be found at:
http://www.newhaven.edu/academics/17041/
Adding/Droppinga Class: The final day to drop a course
without it appearing on your transcript is Wednesday, August
31st. After this day, the University policy will be followed:
http://www.newhaven.edu/academics/17435/
Attendance: All students are expected to attend regularly and
promptly all their classes, appointments, and exercises. While
the university recognizes that some absences may occasionally
be necessary, these should be held to a minimum. A maximum
of two weeks of absences will be permitted for illness and
emergencies. The instructor has the right to dismiss from class
any student who has been absent more than the maximum
allowed. After the last date to drop as published in the
academic calendar, a student will receive a failure (F), if failing at
that point, or a W, if passing at the time of dismissal.
http://www.newhaven.edu/academics/16648/
Make Ups: If you are going to be absent for an examination or
quiz you must notify the instructor prior to the examination to
seek permission unless there is an emergency that prevents you
from doing this.
Academic Integrity Policy: Academic integrity is a core
university value that ensures respect for the academic
reputation of the University, its students, faculty and staff, and
the degrees it confers. The University expects that students will
conduct themselves in an honest and ethical manner and
respect the intellectual work of others. Please be familiar with
6. 6
the UNH policy on Academic Integrity. Please ask about my
expectations regarding permissible or encouraged forms of
student collaboration if they are unclear.
Students are required to adhere to the Academic Integrity
Policies found at: http://www.newhaven.edu/academics/16246/
University Support Services:
a) Campus Access Services: The University of New Haven
seeks to maintain a supportive academic environment for all
students inclusive of those with any disabilities, chronic medical
conditions or military related disorders. If you feel that you
may need reasonable accommodations in this course, please
provide me with your Verification of Disability/Request for
Reasonable Accommodations letter or contact the Campus
Access Services office to begin the process to ensure that
accommodations can be made available to you. Campus
Access Services is located in Sheffield Hall on the ground floor
in the rear of the building, and can be reached by email at
CampusAccess@newhaven.edu or by phone at (203) 932-
7332. For additional information, please visit:
http://www.newhaven.edu/student-
life/CampusLife_StudentAffairs/Campus_Access_Services/
b) Writing Resources: The Center for Learning Resources
(CLR), located on the lower level of the Library, offers FREE
tutoring support for most freshman and sophomore, and select
upper-level, courses, as well as general writing and computer
assistance. Students who sought CLR support in 2011-2012
saw a 91.7% success rate in their final course grade. Students
may make appointments online
7. 7
(http://www.newhaven.edu/academics/13736/) or see a tutor
on a walk-in basis, although appointments are recommended
to ensure immediate assistance. Students may choose their
tutor from a range of professional, graduate student, and
undergraduate staff. Visit the CLR website, or call (203) 932-
7215, for more information.
Commitment to Positive Learning Environment: The
University adheres to the philosophy that all community
members should enjoy an environment free of any form of
harassment, sexual misconduct, discrimination, or intimate
partner violence. If you have been the victim of sexual
misconduct we encourage you to report this. If you report this
to a faculty/staff member, they must notify our college's Title IX
coordinator about the basic facts of the incident (you may
choose to request confidentiality from the University).
If you encounter sexual harassment, sexual misconduct, sexual
assault, or discrimination based on race, color, religion, age,
national origin, ancestry, sex, sexual orientation, gender
identity, or disability please contact the Title IX Coordinator,
Caroline Koziatek at (203) 932.7479
or ckoziatek@newhaven.edu.
8. 8
About the Faculty
Frank F. Wang, MBA, MS
A seasoned executive with years of healthcare and life sciences
industry/consulting experience transforming business landscapes, driving technology innovation and
igniting business growth, Mr. Wang is known to formulate strategies to help enterprises to expedite
development of new products and services, accelerate new market penetration, streamline business
processes and reduce operational costs.
Mr. Wang was employed by or consulted for blue chip organizations such as Amgen, Bayer AG,
BlueCross BlueShield Association, Boehringer-Ingelheim GmBH, Daiichi Sankyo Inc., Children’s
Hospital of Boston, Cigna, Harvard Partner’s Health System, Hawaii State Department of Health,
Ministry of Health of China, Merck, National Institute of Health (NIH), Pfizer, Procter & Gamble,
University of Texas MD Anderson Cancer Center, University of Pittsburg Medical Center (UPMC), US
Food and Drug Administration (FDA) and many others. He is a trusted advisor to CEOs, Chief Medical
Officers (CMOs), Chief Scientific Officers (CSOs) and CIOs.
Mr. Wang has had various leadership roles directing informatics and analytics organizations to shorten
product development cycle time, advance quality of patient care, increase customer acquisition and
enhance sales and marketing effectiveness.
Mr. Wang has been a speaker at many conferences related to big data analytics and industry trends
organized by Cambridge Healthtech Institute, International Business Communication, and many global
organizers. He contributes to healthcare and life sciences key issues on LinkedIn
(www.linkedin.com/in/frankfangwang) and Slideshare and has many followers.
Mr. Wang is a member of American Competitive Intelligence Society, member of Drug Information
Association (DIA), member of Healthcare Information and Management Systems Society (HIMSS),
member of Managed Care Executive Group (MCEG), member of American Health Insurance Plan
(AHIP).
Mr. Wang is a principal at FFW Consulting, a firm that is specialized in advising healthcare and life
sciences clients on analytics issues. He is also an adjunct professor at the University of New Haven.
Prior to that, he was WW Lead, Healthcare and Life Sciences, Hewlett Packard Company (HP),
responsible for healthcare and life sciences consulting and managed services business.
Mr. Wang earned his M.S. in biochemistry from University of Texas Medical Branch and his MBA
from Xavier University of Cincinnati, OH. He also had executive continuing educations at Harvard
Business School and MIT Sloan School of Management. He lives in Connecticut with his wife and
two children.