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Australian Masterclass

Australian Masterclass. Sally Batley Deputy Director of Analysis , NHS Modernisation Agency (UK) Working in partnership with the Patient Flow Collaborative (Victoria AU). So what are we going to cover. Measurement for Improvement What is Statistical Process Control (SPC)

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Australian Masterclass

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  1. Australian Masterclass Sally Batley Deputy Director of Analysis, NHS Modernisation Agency (UK) Working in partnership with the Patient Flow Collaborative (Victoria AU)

  2. So what are we going to cover • Measurement for Improvement • What is Statistical Process Control (SPC) • Understanding Variation • Benchmarking • Build you own SPC charts

  3. So what are we going to cover • Measurement for Improvement • What is Statistical Process Control (SPC) • Understanding Variation • Benchmarking • Build you own SPC charts

  4. Measurement for Improvement

  5. Sir Josiah Stamp Public agencies are very keen on amassing statistics - they collect them, add them, raise them to the Nth power, take the cube root and prepare wonderful diagrams. But ... what you must never forget is that every one of those figures comes in the first instance from the village watchman (or admissions clerk?) - who puts down what he damn pleases.

  6. There are three kinds of lies:lies, damned lies and statistics After Mark Twain

  7. Collecting your data

  8. How good is your data? • Is the routine data you collect and distribute 100% accurate? • Is it complete rubbish? • So it must be somewhere in between

  9. Issues • Definitions • Accuracy • Consistency • Timing

  10. The information vicious circle Information is not used Information is: Inaccurate Incomplete Late Inconsistent

  11. Task In groups you have to describe the people in the room so answer these questions … • How many people are there in the room? • How many are wearing something red? • How many are tall? • How many types of footwear are there? • Find one word to describe the group?

  12. Issues • Timing • Definitions • Accuracy • Consistency

  13. Data types

  14. Types of data • Routine v special collection • Qualitative v Quantitative • Soft v hard • Descriptive v numeric • Example of current performance: “Patients are satisfied” v waiting time is 4 hours • Example of change: “Communication with patients has improved” v Average X-ray waits reduced by 20 minutes

  15. Which types are you collecting?

  16. Types of measurement

  17. Different types of measurements • measurements for judgement • league tables

  18. Performance Indicators • Measure probability not certainty • Are better in groups • Are better at identifying poorer performance • Should not be used for league tables

  19. Different types of measurements • measurements for diagnosis • to show where the problems are • lots of measures • comparative data useful • measurements for improvement • to show if improvement are being made • linked to the project objectives and aims • a few specific measures

  20. Measurement for Improvement or how do we know that a change is an improvement?

  21. Model for improvement What are we trying to accomplish? How will we know that a change is an improvement? What changes can we make that will result in the improvements that we seek ? Act Plan Study Do

  22. Model for improvement What are we trying to accomplish? How will we know that a change is an improvement? What changes can we make that will result in the improvements that we seek ? Act Plan Study Do project aims

  23. Model for improvement What are we trying to accomplish? How will we know that a change is an improvement? What changes can we make that will result in the improvements that we seek ? Act Plan Study Do project aims global measurements

  24. Model for improvement What are we trying to accomplish? How will we know that a change is an improvement? What changes can we make that will result in the improvements that we seek ? Act Plan Study Do project aims global measurements change principles

  25. P A D Data S D S P A S D A P A P S D Building Improvement Knowledge Changes that result in improvement Improvement Time

  26. Measurement for improvement: • Answers the question How do we know change is an improvement ? • Is linked to the project objectives or aims • usually requires no more than five to seven measures • crosses the whole process of care • measures change over time

  27. Change areas, aims and measures should be related • Area - Effective Delivery of Health Care • Aim - To improve access to the appropriate treatment • Measure - Reduce the number of days between referral and first definitive treatment Example from Action On programme

  28. Measuring quantitativeoutcomes

  29. Measuring quantitativeoutcomes • A descriptive goal eg reduce DNAs • But by how much? • Quantify the starting point (baseline) • Set an objective (improve by x%) • How will you measure that? (methods) • Monitor progress

  30. An example - hospital cancellations Baseline = 15% Target = 5%

  31. How are we doing?Setting the baseline • Baseline period must be representative • Small numbers issue • Baseline period can be greater than monitoring frequency

  32. Over what period to measure baseline? Average = 8.7%

  33. Over what period to measure baseline? Average = 8.7%

  34. How will we know?Tips on measurement • Measurement periods • Census point (particular time of day - eg 12pm) • Period of time (eg 24 hour period) • Don’t mix the two! • Use routine data where possible to allow cross-checking • Specify method precisely eg process time in hours for patients from triage to admission onto appropriate ward

  35. How much will we improve? - Expressing the measurement of change • Be realistic in your expectations Don’t think you can reduce error rate from 50% to 0% • Mostly express values to one decimal place DNA rate = 5.6% (not 6%) • Express target as a value not as an improvement If baseline is 5 patients/hour and you want to improve by 10% then state target as 5.5 patients/hour • Avoid confusion over percentages Baseline is 10% and you want to improve (reduce) by 25% then state target as 7.5%

  36. Process Mapping Understand the process before settling on your measures

  37. Arrival in A&E Seen by o/c team Seen by A&E Triage DTA Leave A&E Route A - Self-referral W3 W4 W1 Indicative waits W1 - 5 minutes W2 - by category W3 - 1 hour W4 - 1 hour W5 - 4 hours W2 W5

  38. We want to improve the overall patient journey Global measure: % patients seen within recommended waiting times at three key identified stages in care

  39. But Changes are made at specific points Global measure: % patients seen within recommended waiting times at three key identified stages in care

  40. The Measurement Paradox We want to improve the whole patient experience/ journey but we make changes at specific points. How do we cope with measuring the change? Specific measures • can be temporary • to monitor change ideas Global measures • are permanent • to monitor overall improvement

  41. Measurement at specific points In addition to reported global measures plotted, additional measures may be required during changes: • specific measures related to the change • results for sub-groups of patients • results by consultant groups • results for patients experiencing a particular clinical process

  42. Impact of changes on global measures (hopefully!) Average waiting times across the care pathway in days 60 Change 1 50 40 Change 3 30 20 Change 2 10 0 Jul Jan Jun Jan Nov Oct Apr Mar Aug Dec Feb May Sept

  43. Setting the baselineOr how are we doing right now? • Baseline period must be representative • Watch out for small numbers! • Baseline period can be greater than monitoring frequency

  44. Measurement guidelines • key measures plotted and reported each month should clarify your project team’s aim and make it tangible. • be careful about over-doing process measures. • consider sampling to obtain data. • integrate measurement into the daily routine. • plot data on the key measures each month during the programme

  45. Task: Creating measures for your project aims Your Project is Improving Patient Flow • what is your measurement strategy? • what are you aims • what quantified measures could be used? • Data collection method • what baseline are you going to use? • what is the potential performance? • frequency of measurement? • How are you going to feed it back and to whom?

  46. Patient experience monitoring

  47. Why? To use patient feedback to improve services

  48. Agenda • evaluating patient experience • quantitative versus qualitative • rating versus reporting • practical hints and tips

  49. Task On your table, brainstorm ideas for measuring and monitoring patients’ experience with a service: How can we measure what patients think of the service?

  50. Approaches to monitoring • quantitative • structured • questionnaires • “tick box” • surveys qualitative • semi-structured • interviews • questionnaires that • combine “tick box” • with comment spaces • unstructured • interviews • patient focus groups • critical incident • technique

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