1 / 33

Colorado 5M WebEx Variation, Run Charts, and Control Charts Beth A. Katzenberg, EdM, MBA, CPHQ Director, Corporate Qual

2. Types of variation. Common causeAlways presentInherent in processCan predict performance with a range of variationCannot tell what specifically causes variation. Special causeAbnormal, unexpectedDue to causes not inherent in processCan be identified (e.g., change in shift, weather, process).

ophelia
Download Presentation

Colorado 5M WebEx Variation, Run Charts, and Control Charts Beth A. Katzenberg, EdM, MBA, CPHQ Director, Corporate Qual

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

    1. 1 Colorado 5M WebEx Variation, Run Charts, and Control Charts Beth A. Katzenberg, EdM, MBA, CPHQ Director, Corporate Quality & Compliance Colorado Foundation for Medical Care

    2. 2 Types of variation Common cause Always present Inherent in process Can predict performance with a range of variation Cannot tell what specifically causes variation Special cause Abnormal, unexpected Due to causes not inherent in process Can be identified (e.g., change in shift, weather, process)

    3. 3 You must understand the type of variation that is occurring as this will determine how you address the problem.

    4. 4 Variation

    5. 5 Pitfalls If only common cause variation and treat as special cause (tampering), leads to greater variation, mistakes, defects If common cause and special cause, and change the process, leads to wasted resources because the change won’t work

    6. 6 Tools to identify variation

    7. 7 Run charts

    8. 8 Run chart

    9. 9 Run chart analysis: Common cause variation only

    10. 10 Run chart analysis: Runs Run = one or more consecutive data points on the same side of the median Excludes data points on the median

    11. 11 Expected number of runs

    12. 12 High probability of special cause variation: Too few runs Too many runs

    13. 13 Run chart analysis: Run length

    14. 14 Run chart analysis: Trends

    15. 15 Run chart analysis: Freaks

    16. 16 Run chart analysis: Cycling

    17. 17 Run charts tips How many data points? 15-20 minimum is preferable Median = 50%/50% split point Precisely half of the data set will be above the median and half below it

    18. 18 Control charts

    19. 19 Control chart

    20. 20 Dividing control chart into zones

    21. 21 Identifying special causes Apply independently to each side of the center line: 1 point outside the 3 sigma limit 2 out of 3 consecutive points in zone A or beyond 4 out of 5 consecutive points in zone B or beyond <20 total data points: 7 consecutive points in zone C or beyond on one side of center line 20+ total data points: 8 consecutive points in zone C or beyond on one side of center line (continued)

    22. 22 Identifying special causes, cont. Apply this test to entire chart: <21 total data points: 6 or more points in a row steadily increasing or decreasing 21+ total data points: 7 or more points in a row steadily increasing or decreasing 14 consecutive points alternating up and down in saw-tooth pattern 15 consecutive points in zone C (above and below center line)

    23. 23 Deciding which control chart to use

    24. 24

    25. 25 Control chart example 1

    26. 26 Control chart example 2

    27. 27 Control chart example 3

    28. 28 Control chart example 4

    29. 29 Just because a process is under control (common cause variation only), it does not mean that the process is meeting expectations. It just means that the process is predictable and you are getting consistent performance.

    30. 30 Control charts tips Control limits are not specifications limits (specification limits related to customer requirements) After removing special causes and recalculating chart, continue to plot new data on this chart, without recalculating control limits. Recalculate control limits only when a permanent, desired change has occurred in the process and only using data after the change occurred

    31. 31 Share the data Team meetings Post in break-rooms Newsletters Intranet

    32. 32 Examples of Software QI Macros www.qimacros.com StatSoft www.statsoft.com Minitab www.minitab.com

    33. 33 References Carey, R.G. & Lloyd, R.C. Measuring Quality Improvement in Healthcare: A Guide to Statistical Process Control Applications, Quality Resources, 1995. Pyzdek, R. The Six Sigma Handbook: A Complete Guide for Green Belts, Black Belts, and Managers at All Levels, 2003. The Six Sigma Memory Jogger II, GOAL/QPC, 2002.

    34. 34 Beth Katzenberg, EdM, MBA, CPHQ Director, Corporate quality & compliance Colorado Foundation for Medical Care bkatzenberg@cfmc.org

More Related