To help us make good management decisions in the way we react to that variation. To understand the variation that lives within our data

Transcription

1 Wednesday 15 July 2015 Why do we analyse and present data? To understand the variation that lives within our data To help us make good management decisions in the way we react to that variation Source: Robert Lloyd IHI

2 But often we have presented data in a different way... We have 2 quarterly data points - is this an improvement? Executive Time Series Something Important J F M A M J J A S O N D Months Higher is better 2

3 Are we assuming something like this? Executive Time Series - linear trend Something Important J F M A M J J A S O N D Months But it could be like this... Executive Time Series - no trend Something Important J F M A M J J A S O N D Months 3

4 Or this... Executive Time Series - seasonal dip Something Important J F M A M J J A S O N D Months Or this! Executive Time Series - one month blip 100 Something Important J F M A M J J A S O N D Months 4

5 Walter A. Shewhart (early 1920 s, Bell Laboratories) While every process displays variation: some processes display only controlled variation (common cause) stable, consistent pattern of variation constant causes/ chance while others display uncontrolled variation as well pattern changes over time special cause variation/ assignable cause 9 Shewhart s purpose Data contains both signals and noise. To be able to extract information, one must separate the signal from the noise within the data. To fulfill that purpose he created the control chart 5

6 A statistical process control chart Plot data in time order Calculate and plot process limits as lines Upper process limit Calculate and plot mean as a line Lower process limit F M A M J J A S O N D J F M A M J J A S O N D Analyse chart by studying how values fall around mean and limits How often to measure? Barnsley stroke pathway time in hospital before getting onto stroke ward 6

7 Monthly data shows improvement 3.5 Average length of pre-ward stay on Barnsley Stroke Ward from 01/2007 to 07/ Months Weekly data tells a different story 9.0 Average length of pre-ward stay on Barnsley Stroke Ward from 01/2007 to 07/ Weeks 7

8 Patient level data adds another level of understanding 15 Source: Lloyd Nelson, Technical Aids: The Shewhart Control Chart Tests for Special Causes SPC CHART RULES 16 8

9 Rule # 1: Any single point outside the control limits Upper control limit Lower control limit Rule # 2: A shift At least 7 points consecutively either above or below the centre line Upper control limit Lower control limit 9

10 Rule #3: A drift At least 7 points consecutively ascending or descending Upper control limit Lower control limit Note: the points can cross the centre line Rule #4: At least 14 points alternating up and down Upper control limit Lower control limit Note: the points do not have to alternate above and below the centre line 10

11 Other tests require you to plot the intermediate variation values +3V +2V +1V -1V -2V -3V Upper control limit Lower control limit Rule #5: 2 out of 3 points outside 2V on the same side of the centre line +3V +2V +1V -1V -2V -3V Upper control limit Lower control limit 11

12 Rule #6: 4 out of 5 points outside 1V on the same side of the centre line +3V +2V +1V -1V -2V -3V Upper control limit Lower control limit Rule #7: Reduced variation 15 points within 1V either side of the centre line +3V +2V +1V -1V -2V -3V Upper control limit Lower control limit 12

13 Rule #8: 2 processes 8 points in a row on both sides of the centre line with none within 1V +3V +2V +1V -1V -2V -3V Upper control limit Lower control limit Process 1 RULE PREDICTABLE? YES / NO / NOT SURE 13

14 Process 2 RULE PREDICTABLE? YES / NO / NOT SURE Process 3 RULE PREDICTABLE? YES / NO / NOT SURE 14

15 Process 4 RULE PREDICTABLE? YES / NO / NOT SURE Process 5 RULE PREDICTABLE? YES / NO / NOT SURE 15

16 Process 6 RULE PREDICTABLE? YES / NO / NOT SURE What decision do you make? Decision Do nothing Contingency plans Process redesign Because Performance ok Special cause variation Common cause variation Is your information presented in a way that allows you to confidently make one of these decisions? 16

17 So why run or control charts? One picture, one message Shows change over time Allows you to see variation and differentiate between signal and noise Helps you to make the right decision Gap between successive events /01/05 17/01/05 21/01/05 21/01/05 01/02/05 04/02/05 MRSA performance City Hospital Hospital 10/02/05 20/02/05 24/02/05 03/03/05 07/03/05 07/03/05 07/03/05 08/03/05 16/03/05 03/04/05 04/04/05 Date of event 09/04/05 12/04/05 13/04/05 17/04/05 22/04/05 28/04/05 03/05/05 06/05/05 Gap betw een specimens Average LCL UCL SPC tools Baseline Winchart from Prism Europe Chartrunner from PQ Systems nner/chartrunner.php 17

18 Useful references Donald Wheeler. Understanding Variation. Knoxville: SPC Press Inc, 1995 Donald Wheeler. Making sense of data. SPC for the service sector. Knoxville: SPC Press Inc, 2003 WE Deming. Out of the crisis. Massachusetts: MIT 1986 American Society for Quality Donald M Berwick. Controlling variation in health care: a consultation from Walter Shewhart. Med Care 1991; 29: Walter A Shewhart. Economic control of quality of manufactured product. New York: D Van Nostrand