Fall 2021

NURS 7320-ONL1 Statistical Methods and Data Analysis to Evaluate Healthcare Delivery Systems

All students are responsible for checking their UTHSCSA Livemail account regularly (i.e., daily or several times every week) to obtain Official University Communication regarding their courses, program and student status.

Students are expected to follow all policies related to COVID-19 found on the university webpage: https://wp.uthscsa.edu/coronavirus/.

NOTE: Our campus has enabled the CANVAS MOBILE LEARN application. CANVAS tools such as discussions, quizzes or videos May or May NOT function on all mobile devices. This is because mobile devices are available with rapidly changing and different configurations. Hence, students must not depend on only a mobile device to access course materials. Students must have access to a laptop or desktop device to access course materials and complete assignments.

This course is Web Enhanced with WebCT icon
Please be sure to check the Current Computer Requirements

Welcome to NURS 7320: Statistical Methods and Data Analysis to Evaluate Healthcare Delivery Systems [Sections ONL1 and 1]. During this semester, students will learn how to use QI Macros, an Excel add-on designed to create Six Sigma tools and Statistical Process Control charts. All students will download a 180-day free trial version of QI Macros from: https://www.qimacros.com/trial/student/At the end of the trial, students will have an opportunity to purchase the software at an educational discount from: https://www.qimacros.com/store/orderstudent/

    Please check CANVAS for course updates and first week readings.

Our First Class will be on Saturday August 28th from 12 - 3 pm, SON Room 1.204 (Face to Face class). There will be no class on Sunday the 29th. 

We will also meet every Tuesday via Canvas videoconferencing from 1:00 - 3:50pm starting August 31, 2021 – December 7th, 2021.
Please mark your calendar for all these meeting days.
Attendance is expected.
All Tuesday meetings are online via Canvas videoconferencing. 

Recordings will be available for CANVAS Conference Sessions. 

Students are expected to follow all policies related to COVID-19 found on the university webpage:  https://wp.uthscsa.edu/coronavirus/.


Azizeh (ZZ) Sowan, PhD, RN. MSN, MSDA, MBA, FAAN
Associate Professor
Email: sowan@uthscsa.edu
Office Phone: 210.567.5799
Fax: 210.567.1719
Office: 2.628

Office Hours: Virtual office hours will be scheduled during the 1st CANVAS Conference Session.


Students will be introduced to analytical methods for knowledge translation and implementation to evaluate processes that impact system, practice, and patient level outcomes. Students will build skills to analyze patient, practice, and outcome data using descriptive statistics, quality improvement tools, and statistical process control.Students will examine appropriate models, methods, measures, data sources, and analyses to evaluate healthcare quality and patient outcomes. Student swill also build capacity to interpret, visualize, and present data to advance practice and improve patient outcomes. 


Credit Hour Allocation:  3 semester credit hours
Clock Hour Allocation: 45 clock hours class


Graduate Standing


Upon completion of the Doctor of Nursing Practice (DNP) Program students will:

  1. Integrate nursing science, ethics, biophysical, psychosocial, analytical, and organizational sources to provide the highest level of specialty nursing practices.
  2. Develop, implement, and evaluate healthcare practices in healthcare systems that ensure quality improvement and patient safety.
  3. Use analytic methods and evidence based practices to improve practice outcomes and the practice environment.
  4. Implement and evaluate ethical healthcare information systems and patient care technology to improve the quality of patient health outcomes and care systems.
  5. Advocate for healthcare practices that advance social justice, equity, and ethical policies within all healthcare arenas.
  6. Employ interprofessional collaborative teams to improve patient and population health outcomes and healthcare delivery systems.
  7. Lead the integration and institutionalization of (evidence based) clinical prevention and population based health guidelines.
  8. Use clinical judgment, systems thinking, accountability, and specialized knowledge to design, deliver, and evaluate evidence based, culturally proficient care to improve patient, population, and health systems outcomes.


1.    Distinguish models, methods, and tools to evaluate data from healthcare delivery systems and processes. (DNP Essentials I, II; NONPF Competencies: Scientific Foundation 1, 3, Technology and Information Literacy 5, Health Delivery System 6)


2.    Evaluate appropriate and consistent measures and data sources for patient, practice, and systems outcomes. (DNP Essentials I, II; NONPF Competencies: Scientific Foundation 1, 3, Technology and Information Literacy 5, Health Delivery System 5)


3.    Design a data analysis plan to describe current system processes, evaluate the impact of an evidence-based intervention, and identify sustainable change. (DNP Essentials I, II; NONPF Competencies:Scientific Foundation 4, Quality 3)


4.    Apply appropriate quality improvement tools and statistical methods to analyze patient, practice and systems outcomes. (DNP Essentials I, II; NONPF Competencies: Scientific Foundation 3, 4, Quality 3)


5.    Analyze variations in process and outcome measures over time using statistical process control. (DNP Essentials I,II; NONPF Competencies: Scientific Foundation 1, 3)


6.   Construct clear and meaningful data displays. (DNP Essentials I, II; NONPF Competency: Scientific Foundation 3)

7.  Design reports with pertinent findings for appropriate stakeholders. (DNP Essentials I, II; NONPF Competencies: Quality 5, Practice Inquiry 5)




A = 4 points (90-100)
B = 3 points (80-89)
C = 2 points (75-79)
D = 1 point (66-74)
F = 0 points (65 or below)


Further details on assignments and grading criteria will be made available on CANVAS the first week of class.



Attendance in class is an expectation of each student.


  1. If written assignments are made in a course they are required.
  2. Students are expected to submit written work on the scheduled date and time.
  3. The student must notify the course coordinator prior to the scheduled due date and time if they are unable to submit the written work as scheduled. Failure to make this notification in advance will result in a "zero" for that written work.
  4. If the excuse is accepted as reasonable and necessary, arrangements will be made for an alternative due date and time.
  5. Each student is responsible for making sure that he or she has completed the written work prior to submission.
  6. Late work will be accepted with consequences as outlined per course syllabi.


The APA Publication Manual 7th edition is required for use in all nursing school programs. 


Students are expected to be above reproach in all scholastic activities. Students who engage in scholastic dishonesty are subject to disciplinary penalties, including the possibility of failure in the course and dismissal from the university. "Scholastic dishonesty includes but is not limited to cheating, plagiarism, collusion, and submission for credit of any work or materials that are attributable in whole or in part to another person, taking an examination for another person, any act designed to give unfair advantage to a student or the attempt to commit such acts." Regents Rules and Regulations, Part One, Chapter VI, Section 3, Subsection 3.2, Subdivision 3.22.


Students who are nurses or are preparing to enter the profession of nursing are expected to treat others with respect and compassion. “The principle of respect for persons extends to all individuals with whom the nurse interacts. The nurse maintains compassionate and caring relationships with colleagues and others with a commitment to the fair treatment of individuals, to integrity-preserving compromise and to resolving conflict. This standard of conduct precludes any and all prejudicial actions, any form of harassment or threatening behavior, or disregard for the effects of one’s actions on others” (American Nurses Association Code for Nurses, Interpretive Statement 1.5).

The students, faculty, Department Chairs, Associate Deans, and the Dean of the School of Nursing of the University Texas Health Science Center San Antonio subscribe to the highest standards of conduct. Our aim is professional behavior beyond reproach. Failure to abide by the signed code of professional conduct may lead to suspension and/or permanent dismissal from the UTHSCSA SON. In particular, we subscribe to the provisions of the Code of Ethics for Nurses (http://bit.ly/1mtD5p2) and the following points of conduct.


School of Nursing Netiquette Guidelines for Online Interaction

Netiquette guidelines provide information for behaving properly online, when using email, tweets or texts so that you may successfully communicate your thoughts in a manner that is respectful and avoids misunderstandings with others.


Any student seeking reasonable accommodations through the Americans with Disabilities Act (ADA) should contact either the Associate Dean for Admissions and Student Services within the first week of the semester or schedule a meeting with the UTHSCSA ADA Compliance Office so that appropriate accommodations may be arranged. A request for accommodations (Form ADA-100: http://uthscsa.edu/eeo/form100-Faculty-student-resident.pdf) must be completed and submitted to the Executive Director of the ADA Compliance Office before accommodations can be provided. Additional information can be provided in the Student Success Center, Room 1.118 or through the ADA Compliance Office website: http://uthscsa.edu/eeo/request.asp.


American Psychological Association. (2019). Publication manual of American Psychological Association. (7th Ed.). Washington D.C.:  American Psychological Association. ISBN: 978-1433832154

Carleton, S., & Six Sigma Academy (2018). The Lean Six Sigma Tools Memory Jogger. Methuen, MA: Goal/QPC. ISBN: 978-1576811856

Provost, L.P., & Murray, S. (2011). The Health Care Data Guide: Learning from Data for Improvement. (1st Ed.). San Francisco, CA.:  Jossey-Bass. ISBN: 978-0470902585

Readings will be assigned through Canvas modules with links to downloadable files. Please check Canvas regularly for course readings.


Module 1. Healthcare Improvement and Data Collection

Module 2. Quality Improvement Tools and Methods

Module 3. Descriptive Statistics and Data Displays

Module 4. Statistical Process Control: Understanding and Charting Variation

Module 5. Interpreting and Disseminating Results 

CALENDAR - 1st Day Only

Please check the schedule for recent updates on Class Dates & Room.

First Day of Class: August 28, 2021 (Saturday) on campus, Room 1.204, from 12:00 - 3:00 PM. 
All other classes are online via Canvas videoconferencing on Tuesdays (starting August 31) from 1:00 - 3:50 PM.   

All meetings are online via CANVAS Conference Sessions, and recordings will be available.

Please review Week 1 materials on CANVAS prior to the first day of class for required readings and discussion.

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