Scottish Improvement Skills

1. Scottish Improvement Skills Analysing data: Interpretation of run charts

2. System of Profound Knowledge Deming 2000

3. Analysing data: interpretation of run charts • By the end of this session you will be able to: • Explain the importance of using annotation to help interpret run charts • Discuss how the type of median used affects interpretation of signals from run charts and impacts on decision making • Explain use of phasing, stratification, and what to do with extreme values on run charts.

4. Analysing data: Interpretation of run charts • Annotation • Median • Phasing • Extreme values • Stratification

5. Aim: promote staff wellbeing Aim 1 Driver 2 Driver Change ideas Offer Bereavement support programme for managers Promote the physical, mental and emotional wellbeing of staff. Within 12 months (1) reduce staff absences from 5.2% to 4.2% (2) reduce staff related incidents from 140 to 100 per month. A workplace that is safe for staff Flyer on staff health and wellbeing programmes Staff education Hold staff health fairs Smoking cessation campaign Staff engaged in health and wellbeing practices Set up walking groups Healthy lifestyle programmes for staff Improve staff diet at work Offer lunchtime yoga Enable cycling to/from work

6. AnnotationHours lost through sickness absence Median 5.2 Fit Note introduced Goal

7. Median (1)Women walking 10,000 steps Baseline medianExtended median Challenge announced Pedometers issued

8. Median (2)Women walking 10,000 steps Signal detected here Challenge announced Pedometers issued

9. Median (1)Women walking 10,000 steps Baseline medianExtended median Signal detected here Challenge announced Pedometers issued

10. Creating a baseline median • Use historical data if available • Collect new baseline data before introducing a change, if this makes sense in your context • If no baseline data is available, create a baseline median using the first 10 data points.

11. PhasingWomen walking 10,000 steps Pedometers issued Challenge announced

12. Interpretation of run charts • Each run chart can be improved to make the data easier to interpret. Possible improvements may relate to: Type of median line used Measure used • For each chart, decide what improvements would be most useful, and why. Annotation Design

13. Extreme values • Frequent events • Rare events • More than half the data falls on the median line • More than half the data is at ‘extreme’ values eg 0 or 100 on percentage scale

14. Extreme values (1)Compliance with hand hygiene

15. Extreme values (2a): Number of needlestick incidents per month

16. Extreme values (2b): Number of patients seen between needlestick incidents

17. Stratification (1):Inpatient requests for MRI

18. Stratification (1): Inpatient requests for MRI

19. Stratification (1): Inpatient requests for MRI

20. Stratification (2) Staff walking 10,000 steps (men and women) Median 35.25 Challenge announced Pedometers issued

21. Stratification (2) Staff walking 10,000 steps (women) Median 29 Pedometers issued Challenge announced

22. Stratification (2) Staff walking 10,000 steps (men) Median 41 Pedometers issued Challenge announced

23. Interpretation of run charts • Each run chart can be improved to make the data easier to interpret. Possible improvements may relate to: Type of median line used Measure used • For each chart, decide what improvements would be most useful, and why. Annotation Design

24. Analysing data: Interpretation of run charts: summary • Annotation • Median • Phasing • Extreme values • Stratification

25. References and further resources Provost Lloyd P & Murray S (2011) The Health Care Data Guide: Learning from Data for Improvement Jossey-Bass