Understanding Tukey Control Chart in Health Informatics Program at GMU

Explore the Tukey Control Chart methodology as part of the Health Informatics Program at George Mason University (GMU). Learn about the seven essential steps including assumptions, outliers, median, fourths, and control limits to enhance data analysis and decision-making in healthcare settings.

• Health Informatics
• Tukey Control Chart
• Data Analysis
• GMU
• Healthcare

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1. Tukey Control Chart Farrokh Alemi, Ph.D. HEALTH INFORMATICS PROGRAM HI.GMU.EDU

2. Seven Steps 1. Assumptions HEALTH INFORMATICS PROGRAM GEORGE MASON UNIVERSITY

3. Assumption 1 per Period HEALTH INFORMATICS PROGRAM GEORGE MASON UNIVERSITY

4. Assumption Outliers HEALTH INFORMATICS PROGRAM GEORGE MASON UNIVERSITY

5. Seven Steps 2. Median & Fourths HEALTH INFORMATICS PROGRAM GEORGE MASON UNIVERSITY

6. 2. Median & Fourths Median, Below HEALTH INFORMATICS PROGRAM GEORGE MASON UNIVERSITY

7. 2. Median & Fourths Median, Below 1. Order 2. Equal halves 3. Odd or Even? HEALTH INFORMATICS PROGRAM GEORGE MASON UNIVERSITY

8. 2. Median & Fourths Lower Fourth, Below HEALTH INFORMATICS PROGRAM GEORGE MASON UNIVERSITY

9. 2. Median & Fourths Upper Fourth, Below HEALTH INFORMATICS PROGRAM GEORGE MASON UNIVERSITY

10. Seven Steps 3. Fourth Spread HEALTH INFORMATICS PROGRAM GEORGE MASON UNIVERSITY

11. 3. Fourth Spread Upper Fourth-lower Fourth HEALTH INFORMATICS PROGRAM GEORGE MASON UNIVERSITY

12. Seven Steps 4. Control Limits HEALTH INFORMATICS PROGRAM GEORGE MASON UNIVERSITY

13. UCL = Upper Fourth + 1.5 * Fourth Spreads LCL = Lower Fourth 1.5 * Fourth Spreads HEALTH INFORMATICS PROGRAM GEORGE MASON UNIVERSITY

14. Seven Steps 5. Plot Chart HEALTH INFORMATICS PROGRAM GEORGE MASON UNIVERSITY

15. Seven Steps 6. Interpret Findings HEALTH INFORMATICS PROGRAM GEORGE MASON UNIVERSITY

16. Seven Steps 7. Distribute HEALTH INFORMATICS PROGRAM GEORGE MASON UNIVERSITY

17. EXAMPLE: EXERCISE DATA Pre- intervention HEALTH INFORMATICS PROGRAM GEORGE MASON UNIVERSITY

18. ANALYSISOF EXERCISE DATA: STEP 1 Lower half of data Upper half of data Two halves both include Median because it is an observed data point Median HEALTH INFORMATICS PROGRAM GEORGE MASON UNIVERSITY

19. ANALYSISOF EXERCISE DATA: STEP 2 Lower Fourth is Median of lower data set, it is a value between 25 & 30, so it is 27.5 HEALTH INFORMATICS PROGRAM GEORGE MASON UNIVERSITY

20. ANALYSISOF EXERCISE DATA: STEP 3 Upper Fourth is Median of upper data set, it is a value between 35 & 40, so it is 37.5 HEALTH INFORMATICS PROGRAM GEORGE MASON UNIVERSITY

21. Fourth Spread = 37.5-27.5 = 10 Upper Fourth Lower Fourth HEALTH INFORMATICS PROGRAM GEORGE MASON UNIVERSITY

22. UCL = 37.5+1.5*10 = 52.5 Upper Fourth Fourth Spread HEALTH INFORMATICS PROGRAM GEORGE MASON UNIVERSITY

23. UCL = 37.5-1.5*10 = 52.5 Fourth Spread Lower Fourth HEALTH INFORMATICS PROGRAM GEORGE MASON UNIVERSITY

24. CONTROL CHARTFOR EXERCISE DATA Figure 3: Seven-day limits for data in Table 1 Minutes of exercise 80 60 40 20 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 Days of observation HEALTH INFORMATICS PROGRAM GEORGE MASON UNIVERSITY

25. Budget deviation in 1000s 23 -5 -70 -7 -8 9 12 30 24 25 -4 -2 Month 1 2 3 4 5 6 7 8 8 10 11 12 HEALTH INFORMATICS PROGRAM GEORGE MASON UNIVERSITY

26. ANALYSISOF BUDGET DATA: STEP 1 Budget deviation in 1000s 23 -5 -70 -7 -8 9 12 30 24 25 -4 -2 Budget deviation in 1000s -70 -8 -7 -5 -4 -2 9 12 23 24 25 30 Month Rank 1 2 3 4 5 6 7 8 8 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 Sort the data from lowest to highest value HEALTH INFORMATICS PROGRAM GEORGE MASON UNIVERSITY

27. ANALYSISOF BUDGET DATA CONTINUED Budget deviation in 1000s -70 -8 -7 -5 -4 -2 9 12 23 24 25 30 Rank 1 2 3 4 5 6 7 8 9 10 11 12 Lower Fourth is Median of lower half and is -4.5 Lower half Fourth spread is 23.5 minus - 4.5 = 29 Median Upper Fourth is Median of upper half and is 23.5 Upper Half UCL is 23.5 + 1.5 * 29 LCL is -4.5 - 1.5* 29 HEALTH INFORMATICS PROGRAM GEORGE MASON UNIVERSITY

28. CONTROL CHARTFOR BUDGETDATA HEALTH INFORMATICS PROGRAM GEORGE MASON UNIVERSITY

29. Tukey control chart works with medians and is less sensitive to outliers than mean-based charts