statistical process control tim wiemken, phd mph cic assistant professor, university of louisville...
TRANSCRIPT
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Statistical Process Control
Tim Wiemken, PhD MPH CICAssistant Professor, University of Louisville School of Medicine, Division of Infectious DiseasesDirector, University of Louisville Hospital Epidemiology ProgramAssistant Director of Epidemiology and Biostatistics, Clinical and Translational Research Support CenterLouisville, [email protected]
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Overview
• Appropriate use of charts• Run Charts• Statistical Process Control Charts• Examples…
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Appropriate Use of Charts
1. Pie is to eat, not to display your data.
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Appropriate Use of Charts
1. Pie is to eat, not to display your data.
“Use a pie chart when you don’t have anything to say”
- Dr. Julio Ramirez
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Appropriate Use of Charts
2. Bars are for buying booze, not for displaying consecutive data points.
Don’t do this
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Appropriate Use of Charts
2. Bars are for drinking, not for displaying consecutive data points.
Or this
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Appropriate Use of Charts
3. Line charts are good. They display consecutive data points. That’s all.
Do this
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Overview
• Appropriate use of charts• Run Charts• Statistical Process Control Charts• Examples…
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Run Charts
• Line chart when you have few time periods (e.g. <25 months).
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Run Charts
Anatomy• Center Line / Median –represents the median of
all of the data points. • X-axis –represents the time period of interest
(days, weeks, months, quarters, years).• Y-axis –represents the scale of the plotted data
points (e.g. rate or count of infection).• Data points – the actual data values.
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Y-axis (Rate)
X-axis (Month)
Center Line (Median)
Data Points (<25)
Run Charts
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Use to identify when the data are different than you expect (for better or worse) through
detecting abnormal variation
Run Charts
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Rules for abnormal variation
1. Seven or more consecutive points on either side of the Center Line (median).
2. Five or more consecutive points increasing or decreasing.
3. Fourteen or more consecutive points alternating up and down.
Run Charts
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Rule 17 points below median
Rule 25 consecutive points increasing
Run Charts
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Overview
• Appropriate use of charts• Run Charts• Statistical Process Control Charts• Examples…
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• Use when you have many time periods (e.g. ≥25 months).– These are much better than run charts.
Statistical Process Control Charts
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• Use when you have many time periods (e.g. ≥25 months).– These are much better than run charts.
• But not more than 50 points
Statistical Process Control Charts
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They help identify the difference between
Statistical Process Control Charts
1. Common cause variation (in-control)
2. Special cause variation (out of control)
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• Anatomy• Center Line / Mean–represents the average of all
of the data points. • X-axis –represents the time period of interest
(days, weeks, months, quarters, years).• Y-axis –represents the scale of the plotted data
points (e.g. rate or count of infection).• Data points – the actual data values.• Standard deviation lines (control limits) –
represent 1, 2 or 3 standard deviations on each side of the center line
Statistical Process Control Charts
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• What’s up with the standard deviation?
Statistical Process Control Charts
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• What’s up with the standard deviation?• All data have a distribution.
Statistical Process Control Charts
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• What’s up with the standard deviation?• All data have a distribution. • This distribution can be broken up into
standard deviations – measures of variation from the average
Statistical Process Control Charts
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Statistical Process Control Charts
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1. 68% of data fall in 1 standard deviation of the average
2. 95% of the data will fall within 2 standard deviations
3. 99% will fall within 3 standard deviations
Statistical Process Control Charts
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1. 68% of data fall in 1 standard deviation of the average
2. 95% of the data will fall within 2 standard deviations
3. 99% will fall within 3 standard deviations
One point outside of 3 standard deviations would be abnormal
Statistical Process Control Charts
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Statistical Process Control Charts
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Statistical Process Control Charts99
% o
f Dat
a S
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ere!
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• one point above or below 3SD
• two of three points above/below 2SD
• four of five points above/below 1SD
• eight points in a row on either side of the mean
• trends of 6 points in a row increasing or decreasing
• fourteen points in a row alternating up and down
• eight points in a row outside of 1SD
Statistical Process Control Charts
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• There are many different types of charts
• Using the wrong chart will give you the wrong results
• You may miss an outbreak
• You may institute interventions that are not necessary (e.g. waste your time!)
Statistical Process Control Charts
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P Chart
Use for:
1. Microbiological surveillance rates
2. Compliance rates
U Chart
Use for:
1. Device-associated infections
Statistical Process Control Charts
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• Put all of your data into a nice clean report!
• Not all reports are appropriate for all audiences.
• Remember it is about the audience’s interests, not yours!
Statistical Process Control Charts
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Example introductory slide for MRSA rates
Hospital-associated Methicillin-resistant Staphylococcus aureus
(MRSA)
Case of MRSA (Numerator): A case of MRSA was defined as a new and unique, hospital-associated (isolated >48 hours after admission), microbiological isolate from a patient admitted to hospital x during the month of interest without a prior history of MRSA.
Patient days (Denominator): The denominator for the calculation of the rate of MRSA was defined as the number of patient-days for hospital x during the month of interest, regardless of risk status.
Rate: (Numerator / Denominator) * 1,000
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UCL 0.003
CL 0.001
0.0000
0.0005
0.0010
0.0015
0.0020
0.0025
0.0030
0.0035
0.0040
0.0045
0.0050
Ra
te P
er
Be
d-d
ay
of
Ca
re
Date
June 2006:Rate peaked to 4.30. Suspect increase was due to a change in MRSA precautions implemented affected staff compliance with when to wear PPE.
Hospital-Associated Methicillin-resistant Staphylococcus aureus Isolates: Hospital X, MICU, January 2006 – January 2010
# HA MRSA Isolates divided by # Bed-days of Care
Date
Number of Isolates
Number of Bed-Days of Care
Rate Per 1000 Bed-days of Care
Jan 10
Feb 10
Mar 10
Apr 10
May 10
Jun 10
Jul 10Aug 10
Sep 10
Oct 10
Nov 10
Dec 10
0 2
1319 1117
0.0 1.8
Average Rate per 1000 Bed-days of Care 2008
Average Rate per 1000 Bed-days of Care 2009
Average Rate per 1000 Bed-days of Care 2010 YTD
0.4 0.6 0.9
Assessment: Process is in statistical control.
Plan: Continue surveillance activities.
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Statistical Process Control Charts
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Examples
Statistical Tools Workbook
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you must use clinical judgement in addition to statistics
Conclusion