Patient no shows create a problem for healthcare facilities and other patients. How are Lean and Six Sigma being applied to reduce patient no shows?
We’ll look at three case studies to answer the question: one from Italy, one from Michigan, and one from China.
Agile, Lean, Six Sigma, and Simulation
Giovanni Improta and others explore the use of Agile, Lean, Six Sigma, and simulation to reduce patient now shows in an Italian hospital in their article titled, “Agile Six Sigma in Healthcare: Case Study at Santobono Pediatric Hospital.”
First the authors give an overview of Agile, Lean, and Six Sigma, and previous work on patient no shows.
They then focused on booking services at the hospital in question.
“An agile Six Sigma approach was implemented following the DMAIC cycle to identify process gaps and to measure performance improvements. A model was developed to simulate, examine, and evaluate different strategic choices adopted to manage and reduce patient no-shows.”
Their study focused on the absentee rates and waiting times in the following eight areas:
- General neurology
- Emergency surgery
- General orthopedics
- Infant neuropsychiatry
- Medical day hospital
Based on the data, they zeroed in on the Infant neuropsychiatry department.
They developed a representative simulation model and validated it. “The proposed simulation model for overbooking appointments proved to be an effective method of dealing with no-shows.”
You can read their article here.
Using Six Sigma to Prioritize No Show Categories
In a poster session titled “Using Six Sigma to Reduce Patient No-Show Rates to Clinic Appointments,” John Charles Knight discusses how Six Sigma was used at the Longway Clinic in Flint, Michigan.
“Based on the outcomes in the results section, clinic leadership will use the no-show prediction model to divide patients into low, medium, and high risk of no-show categories.”
You can access John’s poster session here.
Lean Six Sigma used to Reduce Unplanned Surgery Cancellations
In an article titled “Applying Lean Six Sigma to Reduce the Incidence of Unplanned Surgery Cancellation at a Large Comprehensive Tertiary Hospital in China,” Ling-Feng Zhu and others give the details of their case study.
The project resulted in a decrease in unplanned cancellations from 10.21% in Jan. 2016 to 3.8% in Dec. 2016.
You can read the details of their case study here.
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