Statistical Process Improvement

Course Number & Title

HAP 725: Statistical Process Improvement

Faculty

This course is taught by Farrokh Alemi, PhD. and includes input from a number of different instructors.  If you wish to meet with Alemi person, check his availability in the attached calendar. Text before you show.  Calendar►  Contact►

Course Description

Students focus on using data from electronic health records to improve health care. Students acquire a variety of knowledge and skills that prepare them to contribute to health care providers’ quality management efforts including: How to assess patient’s multi-morbidity risks, conduct risk-adjusted statistical process control analyses, and analysis of systemic failures contributing to adverse outcomes. Student learn about trends influencing the quality management system and the drivers for change, including measures used by CMS (including satisfaction, never-pay events, etc.) to strengthen value based payment.

Course Objectives

At the conclusion of the course participants should be able to:

  • Understand the drivers for improvement in health care quality, safety and value
  • Integrate health data analytics and quality management methods in health care settings
  • Articulate how use of data supports the management and delivery of health care services
  • Merge data from multiple tables within electronic health records
  • Utilize CMS and AHRQs quality metrics using data from electronic health records to analyze health care provider performance and safety; including (including Patient Safety Events and Indicators)
  • Analyze process outcomes using risk-adjusted statistical process control charts
  • Evaluate competing causes of outcomes and prepare causal control charts
  • Communicate analytical findings using narrated storyboards and data visualization. Plan efforts to assess patients' satisfaction or health status.

Required Textbooks

  • This course uses an open textbook.  Required reading are posted to the course web pages, no purchase is necessary.

Recommended Textbooks

  • Recommended readings are posted under the section titled "More" within each lecture. An excellent introduction to statistics is provided through "Open Introduction to Statistics."  Free Download►

Course Requirements

To benefit from this course you need to have the following:

  • Both clinicians and managers are encouraged to enroll. 
  • A bachelor or higher degree from an accredited University. The course is limited to graduate students.
  • Familiarity with the US health care system. All examples are from the US health care system.
  • A concurrent or previous introduction to concepts in quality improvement is helpful
  • Following software are needed:
    • Computer, modem, microphone, speaker, phone line and Internet connection.  A fast computer and modem will save considerable time in this course.  A stand alone microphone (that rests on the head) is needed.
    • A frame-based browser is needed.
    • Working knowledge of Microsoft Excel is needed.  If you do not have experience with use of Excel, please take free introductory courses available on the web.
    • Microsoft Power Point is needed for viewing some portions of reading and lectures. 
    • Flash reader is needed.

Course Assignments

There are five assignments in the course that are used to evaluate student's learning:

  1. Weekly Assignment:  Each week, you are asked to analyze data.  Correct answers are typically posted to the web. Each week of delay in submitting a correct assignment is associated with 10% reduction in grade. 
  2. Class Participation: We subscribe to the principle of "Learn one, do one, teach one."  The best way to learn is to teach the topic.  At start of the course, you select a topic in the course to teach.  A week prior to the due date, you submit all assignments in the topic to the instructor.  On due date, you email to all students in the class a You Tube video showing how to solve assigned homework.  Missing any of the deadlines on this assignment will lead to 10% reduction in your grade for each week of delay.
  3. Midterm and Final Exam:  The final exam is a comprehensive, open book, timed, take home exam that focuses on statistical process control tools.   

Course Evaluation

The assignments in the course are graded as follows:

Distribution of the grade

Letter grades correspond to
following numerical grades

Take home exams

50%

Weekly assignments

30%

Teach one assignment

20%
96+ A
90-95 A -
86-89 B +
74-85 B
70-74 C
70- F

Teaching Methods/Strategies

  • Learn one, do one, teach one.  Students learn better when they do projects and teach the concepts covered in the lectures. 
  • Use technology. This course actively uses technology to help improve interaction among the students and the faculty. Class attendance is optional. 

Course Topical Outline

The following table shows dates of various lectures.  Teach One assignment is due prior to lecture date.  Assignments are due a week after the lecture date. 

Topic Lecture Date
Introduction 29-Aug
Preparing Data 5-Sep
Probability & Distributions 12-Sep
  Risk Assessment  19 Sep & 26 Sep
   Midterm Exam 3-Oct
Comparison of Means 10 Oct & 17-Oct
Comparison of Rates 24 Oct & 31-Oct
Time to Adverse Events 7-Nov
Non-Parametric Distributions 14-Nov
Causal Control Chart 21-Nov
Bivariate Analysis 28-Nov
Benchmarking Clinicians 56-Dec

Final exam is timed online open-book exam.  It must be completed in maximum of 4 hours and available during class time in the final exam week.

Open Environment

This is an open environment course.  Faculty and students from other universities are welcomed to use this course.  Do not assume that comments and questions you see are from your classmates.  Do not enter names in the comments you leave.  For more information send email to Farrokh Alemi, Ph.D.  Email► 

Disability Accommodations

If you are a student with a disability and you need academic accommodations, please contact the instructor.  We are committed to comply with the Rehabilitation Act of 1973 and the Americans with Disabilities Act of 1990 by providing reasonable accommodations for disabled students.


This page is part of the course on Statistical Process Improvement, the section on "About the course."  It was first created in 1996.  It was last edited on 08/29/2007 by Farrokh Alemi, Ph.D.  Copyright protected.