1 / 60

Scottish Improvement Skills Workshop 1 Day 3

Learn the stages of the Plan-Do-Study-Act framework and how to create measurement plans, use run charts to track improvement, influence stakeholders, and share your knowledge. Includes examples of testing change in an ICU.

hughgardner
Download Presentation

Scottish Improvement Skills Workshop 1 Day 3

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Scottish Improvement Skills Workshop 1 Day 3

  2. System of Profound Knowledge Deming 2000

  3. Day 3 • Planning a test of change using the Plan-Do-Study-Act framework • Creating measurement plans • Using run charts to tell an improvement story • Influencing colleagues and other stakeholders • Bringing it all together – sharing your knowledge

  4. Planning a test of change using the PDSA framework • By the end of this session you will be able to: • explain all stages of the PDSA framework to others (planning, including theory and prediction; analysing results; applying learning to next cycles) • use all stages of the PDSA cycle in your improvement work.

  5. System of Profound Knowledge Deming 2000

  6. ICU Length of Stay Aim Primary Driver Secondary Driver Change idea Assess sedation and agitation using the RASS tool (Richmond Agitation Sedation Scale) Validated sedation tool Reduce average length of stay in Central General ICU by 20% by March 2015 Assessment and management of sedation and agitation Develop and follow guidelines for daily sedation breaks Structured daily sedation breaks Improve multidisciplimary team communication Use Dexmedetomidine as alternative to benzodiazipines Appropriate sedation Improved identification of delirium Use ear plugs to improve sleep Medical staff and family jointly keep an ICU diary Incidence of acute cognitive dysfunction Assess for delirium using CAM-ICU (Confusion Assessment Method for ICU patients) Validated delirium tool Staff education Improved management of delirium Staff training sessions Include delirium as part of safety brief Staff information leaflets Investigate and correct underlying causes Care bundle initiated within 2 hours of diagnosis Engage with patient/family/carer Mobilise patients earlier and more frequently

  7. Testing change: ICU examples Sequence the 5 PDSA reports • What links do you identify from one cycle to the next? • What do you notice about the scale of the tests? • How many different measures were used? • How did theory change through the cycles? • How did qualitative data inform subsequent tests?

  8. Qualitative and quantitative data “Why did you use the hand gel?” “Because it’s the start of my shift – I’ve just come from home.” Which of the following are occasions when you use hand gel? • At the start of a shift • Between patients • After lunch etc On what percentage of occasions do you use hand gel at the start of your shift? 0 – 20 21 – 40 41 – 60 61 – 80 81 - 100

  9. Project work: plan a test of change • Create an aim for your first test of change: how good, by when? • Start small • Match your questions to your predictions and measures • Plan tasks • Complete who/when/where

  10. Model for Improvement The Improvement Guide Langley J et al 2009

  11. System of Profound Knowledge Deming 2000

  12. Planning measurement • By the end of this session you will be able to: • Create operational definitions for your measures that others can follow reliably to collect data • Create a measurement plan for your improvement work.

  13. How big is your banana?

  14. Operational definitions • Define the specific components of the measure • If it is an average, specify the calculation for deriving the average • If it is a score (eg patient satisfaction score), describe how the score is derived. • If it is a percentage or a rate, specify the numerator and denominator • Describe any special equipment needed • Describe the criteria to determine concepts such as ‘accurate’ or ‘complete’.

  15. Project work: measurement planning • Pick one of your measures • Create an operational definition • Consider exclusions and stratifiers • Provide outline data collection method

  16. Planning measurement: summary

  17. Data analysis • By the end of this session you will be able to: • Explain why it is important to measure data over time • Interpret run charts using rules to differentiate between random and non-random variation • Use run charts to explain outcomes of improvement work to others • Use and explain the importance of using a family of measures.

  18. Understanding Variation • Random variation – affects everyone and all outcomes over time • Non-random variation – does not affect everyone or not part of the system all the time; arises because of specific circumstances.

  19. Analysing data: before and after ‘When you have two data points, it is very likely that one will be different from the other.’ W Edwards Deming

  20. Data analysis: Introduction to run charts Weight (lbs)

  21. Data tells a story: New healthier me!

  22. Introduction to run charts • A ‘time series’ chart tells a story. • Baseline data helps us to see whether a change is an improvement. • Any changes made are shown on the chart.

  23. What is a run?Vanessa’s Weight

  24. Run charts: signals that identify non-random variation • Six or more data points in a run (all above or all below median) • Five or more consecutive data points all increasing or decreasing • Too many or too few runs • An ‘astronomical’ data point A shift A trend See table Consider

  25. Run charts: Rule 1 – a shift

  26. Run charts: Rule 2 – a trend

  27. Run charts: Rule 3 (a) Too few or too many runs

  28. Run charts: Rule 3 (b) Total useful data points Total data points

  29. Run charts: Rule 4

  30. Applying the rules (4)

  31. Baseline data • How urgent is a change? • Is it necessary to identify whether the system has any non-random variation before introducing a change? • What is the source of historical data? • If there is existing data, make use of it. • If there is no existing data, decide whether to start collecting data before introducing the change.

  32. Project work: baseline data • Does baseline data exist somewhere? If so, how can you access it? • If you are going to collect it, how long will you collect baseline data for before introducing a change? Why?

  33. Data analysis: Introduction to run charts: summary • Data tells a story • Look for signals of non-random variation • Rules: • Shift • Trend • Too few or too many runs • Astronomical point • Baseline data

  34. System of Profound Knowledge Deming 2000

  35. Influencing colleagues and other stakeholders • By the end of this session you will be able to: • Apply frameworks to identify key stakeholders and gain understanding of their needs • Plan for positive influencing using reflection, advocacy and inquiry.

  36. Stakeholder analysis: RACI matrix Responsible Accountable Consulted Informed

  37. RACI matrix: template

  38. RACI matrix: example

  39. Planning communications • Stakeholders • Purpose of communication • Key messages to be communicated • Timing of communication • How to communicate • Who is responsible for communication.

  40. Influencing: Ladder of Inference

  41. Your Story Something similar has happened to all of us. What’s your story?

  42. Example Hand hygiene

  43. Example: Hand Hygiene • In a corridor near the door to a clinic. A handwash gel dispenser is on the wall by the door. Liz approaches the door. Chris is just beyond the door, along the corridor, holding a clipboard. Liz uses the gel dispenser and rubs a dose of gel into her hands. She steps towards the door. Chris says ‘Excuse me, can I …’. Liz says ‘Sorry, I’ve been bleeped,’ and goes t through the door.

  44. Actions Beliefs Conclusions Assumptions Meanings Data I select Observable Data

  45. Example: Hand Hygiene • In a corridor near the door to a clinic. A handwash gel dispenser is on the wall by the door. Liz approaches the door. Chris is just beyond the door, along the corridor, holding a clipboard. Liz uses the gel dispenser and rubs a dose of gel into her hands. She steps towards the door. Chris says ‘Excuse me, can I …’. Liz says ‘Sorry, I’ve been bleeped,’ and goes t through the door.

  46. Actions Beliefs Conclusions Assumptions Meanings Data I select Observable Data

  47. Actions Beliefs Conclusions Reflexive Loop Assumptions Meanings Data I select Observable Data

  48. Your Own Example • What action did you take, or what did you say? • What beliefs was that action based on? • What conclusions led you to those beliefs? • What assumptions did you make? • What meanings did you add? • What data might have been available that you selected out?

  49. Actions Beliefs Reflection Advocacy Inquiry Conclusions Reflexive Loop Assumptions Meanings Data I select Observable Data

More Related