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Scottish Stroke Audit

Scottish Stroke Audit. 3rd National Meeting 7th Dec 04. Welcome. NHS QIS funded audit - Oct 02 - 05 Original plan - 6 to 10 hospitals Impact of CHD & Stroke strategy NHS QIS standards and visits. Program. Comparisons between hospitals Control charts

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Scottish Stroke Audit

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  1. Scottish Stroke Audit 3rd National Meeting 7th Dec 04

  2. Welcome • NHS QIS funded audit - Oct 02 - 05 • Original plan - 6 to 10 hospitals • Impact of CHD & Stroke strategy • NHS QIS standards and visits

  3. Program • Comparisons between hospitals • Control charts • Demonstration of real time data capture system • Audit of swallow screening • Update on “MCNs on the Web”

  4. How can these data help improve patient care? • Identify variation in “performance” and to raise questions about cause of variation • Identify methods which increase performance? • Highlight services requiring more investment or re design

  5. Reasons for variation in “Performance” • Method of collection data • Definitions, case ascertainment and audit period • Method of analysing data • Which numerator and denominator? • Chance • Actual performance of service

  6. Some statistical terms • Proportions (%) • 95% confidence intervals • Means and medians • Inter quartile range

  7. Proportions • Numerator / Denominator = Proportion • 100 patients admitted • 60 enter stroke unit • Proportion is 60/100 = 0.6 or 60% • We have had problems with denominators • NHS QIS ask % admitted SU within 1 day • Is denominator 60 or 100?

  8. Denominators • If admit 100 stroke patients • 60 enter the stroke unit • therefore 60% managed in a stroke unit • if half get into stroke unit within a day • % admitted to SU <1day = 50% or 30% • NHS QIS want 30% figure

  9. 95% confidence intervals • Measure the proportion entering your stroke unit once • Calculate the 95% Confidence intervals • Measure the proportion a further 100 times and one would expect 95 estimates to lie within the 95% confidence intervals.

  10. Effect of sample size

  11. A normal distribution No. of patients Mean = 10 Median = 10 Length of stay in Days

  12. Length of stay Mean = 10 Median = 10 No of people. Length of stay (days) Mean = total no. of days / total no. of people Median = LOS where half the people have longer ones and half shorter ones

  13. A skewed distributione.g. length of stay in acute stroke unit No. Mean = 7.3 Median = 6 Days

  14. A very skewed distributione.g. delay to CT scan No. Mean = 4.9 Median = 3 Days

  15. Quartiles (quarters) No. Mean = 10 Median = 10 Days Interquartile range (IQR) (half the patients are included)

  16. Comparisons between hospitals A few hospitals which are currently collecting data are not included because too few data are available.

  17. Inpatients

  18. Data collection periods vary • Longer period will provide more patients and more precise estimates • Longer period will include older data • Recent short period will not include patients still in hospital - therefore may give biased estimates

  19. Variable data collection times

  20. No. of admissions available for analysis – Group 1 Ninewells estimates will have wide Confidence intervals so differences are more likely to be due to chance

  21. No. of admissions per year Group 1 At Ninewells may be missing cases - not identified or simply not yet discharged

  22. No. of admissions available for analysis – Group 2

  23. No. of admissions per year – Group 2

  24. No. of admissions per year – Group 3

  25. No. of admissions per year -Group 4 The estimate in your hand out for St Johns is incorrect

  26. No. of admissions per year – Group 5

  27. Length of Stay in HospitalMean MedianGroup 1 Patients with longer LOS in Ninewells not yet discharged Why is LOS shorter in ARI than Edinburgh??

  28. Length of Stay in HospitalMean MedianGroup 2 Length of Stay in HospitalMean MedianGroup 2

  29. Length of Stay in HospitalMean MedianGroup 3 Length of Stay in HospitalMean MedianGroup 3 Two fold difference Monklands & Falkirk - why?

  30. Length of Stay in HospitalMean MedianGroup 4 Length of Stay in HospitalMean MedianGroup 4

  31. Length of Stay in HospitalMean MedianGroup 5 Length of Stay in HospitalMean MedianGroup 5 Imprecise estimates because small numbers Shetland a different model of service?

  32. Proportions admitted to Stroke Unit – Group 1 77 beds 42 beds 18 beds Note the 95% CI vary with amount of data collected

  33. 43 beds 35 beds 30 beds 16 beds 10 beds Proportions admitted to Stroke Unit – Group 2 Ayr & Crosshouse are doing well! - ? chance because only 3 month 7.6-8.3 pts/SU bed/yr cf 14 pts/SU bed/yr in Inverclyde

  34. Proportions admitted to Stroke Unit – Group 3 24 bed 24 beds 25 beds 30 beds 15 male

  35. Proportions admitted to Stroke Unit – Group 4 15 beds 14 beds 21 beds 17 beds 8 beds 0 beds

  36. Proportions admitted to Stroke Unit – Group 5 6 beds Variable

  37. Mean Delay in accessing SU – Group 1

  38. Mean Delay in accessing SU – Group 2

  39. Mean Delay in accessing SU – Group 3

  40. Mean Delay in accessing SU – Group 4 X

  41. Mean Delay in accessing SU – Group 5 X

  42. Proportion of admission in Stroke Unit – Group 1 Reflects delay in admission % entering SU and exit from SU before discharge X

  43. Proportion of admission in Stroke Unit – Group 2

  44. Proportion of admission in Stroke Unit – Group 3

  45. Proportion of admission in Stroke Unit – Group 4 X

  46. Proportions of admission in Stroke Unit – Group 5 X X

  47. Proportions scanned – Group 1 ARI seem to be having problems getting scans

  48. Proportions scanned – Group 2 Delays in Ayr and Crosshouse

  49. Proportions scanned – Group 3

  50. Proportions scanned – Group 4 Raigmore and Victoria Hospital Kirkaldy having problems

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