Setting Goals & Aims: The Model for Improvement. Cheryl Ruble, RN, MS, CNS Improvement Advisor

Transcription

1 Setting Goals & Aims: The Model for Improvement Cheryl Ruble, RN, MS, CNS Improvement Advisor

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3 Objectives By the end of the session you will: Be able to create an aim statement Explore the Model for Improvement and plan a test of change using PDSA Discuss the difference between outcome, process, and balance measures and understand the why of measurement

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6 What does healthcare have in common with Mountain Climbing?

7 How Hazardous Is Health Care? (Leape)

8 Complexity of Healthcare 90,000 people in an ICU every day Five million Americans will receive care in an ICU in a year Average LOS in ICU is 4 days Survival rate is 68% Average patient requires 178 individual actions per day (suctioning, medication, wound care, etc.) An error is made 1% of the time Average of 2 errors/day/patient Gawande, A. (2007, December 10). The checklist: If something so simple can transform intensive care, what else can it do? The New Yorker.

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10 ADE EED HAPU Falls VAP SSI CLABSI CAUTI VTE Readmits

11 10 Years Ago Central Line Blood Stream Infections were a part of doing business Ventilator Associated Pneumonia was an unfortunate consequence of being sick Sepsis was defined as shock from infection and carried a 50% mortality rate

12 2012: Zero Tolerance

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14 While all changes do not lead to improvement, all improvement requires change.» Thomas Nolan, The Improvement Guide

15 From Alice in Wonderland One day Alice came to a fork in the road and saw a Cheshire Cat. Which road do I take? she asked. His response was a question: Where do you want to go? I don t know, Alice answered. Then, said the cat, it doesn t matter. Lewis Carroll

16 Model For Improvement What are we trying to accomplish? How will we know that a change is an improvement? What change can we make that will result in improvement? AIM MEASURE Selecting Change Act Study Plan Do Small Tests of Change

17 BIG BOLD

18 WHAT? WHERE? HOW MUCH? BY WHEN?

19 Kentucky AIM Statements Reduce the overall readmission rate by 20% by December 31, 2013 Reduce the prevalence of hospital acquired Stage III and IV pressure ulcers by 40% by December 31, 2013.

20 Reduce the rate of Falls with injury by 40% by December 31, Another Example

21 Let s Give this a Try At your tables, for the next 3 minutes create an AIM Statement for a project you are working on or planning to start

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23 WHAT? WHERE? HOW MUCH? BY WHEN?

24 Model For Improvement What are we trying to accomplish? How will we know that a change is an improvement? What change can we make that will result in improvement? AIM MEASURE Selecting Change Act Study Plan Do Small Tests of Change

25 MEASURE

26 Successful measurement is the cornerstone of successful improvement Measurement

27 Why Measure? How else will you know that the change(s) you made resulted in improvement?

28 Differences Research Improvement Purpose Discover new knowledge Bring learnings into daily practice Tests One large blind test Many test cycles, sequential, observable Biases Control for as many biases as possible Data Just in case Just enough Stabilize the biases from test to test Duration Can take a long time Small tests of significant changes accelerates the rate of improvement

29 Making Improvement Measurement Rewarding Senior management support Separate improvement from external reporting Provide constant visual feedback

30 Our Question? ADAPT ADOPT ABANDON

31 Keys to Measurement for Improvement Effective measures: Clarify the aim statement Allow results to be seen quickly Are actionable

32 Measurement Caveats Measurement is a representation of a selected aspect of reality Measurement is not a sustained improvement technique e.g. You can t fatten a cow by weighing it. It is not an act ; it is not the do

33 Use Multiple Measure Types Process Measures Outcome Measure Balance Measures

34 Balanced Measure Set Outcome Measure VAP Rate Process Measures Balancing Measure HOB, PUD, VTE, SAT/SBT, Oral Care Self Extubations with Re-intubations

35 Let s Give this a Try At your tables, for the next 3 minutes create an Outcome, Process, and Balance Measures for a project you are working on or planning to start

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37 Reduce the Data Burden So many choices Know when enough is enough Small is okay ask 5 people, if different answers, you have enough Not enough time Need just enough data to make a sensible judgment for next steps Large amounts of data may not give clarity but will slow to stop improvement

38 Measurement and data can become a barrier to improvement Roadblock

39 Early Mobility Team Data requested: Who ambulated How far Number of times walked If not walked, what kind of mobility chair, dangle, standing Who ambulated patient

40 Early Mobility Team s Measurements Outcome measure: Percent of patients mobilized Process measure: Percent no documentation Balance measure: falls & PT referrals 100.0% 90.0% Ambulation/Progressive Activity Documented House-wide (ICU, Step Down, MS) 4W pilot launch 8/08/11 Step Down pilot launch 8/29/11 3W pilot 10/10/11 4E pilot 80.0% 70.0% 60.0% 50.0% 40.0% 30.0% 20.0% 10.0% 0.0% Jan '11 Feb '11 Mar '11 Apr '11 May '11 Jun '11 July '11 Aug '11 Sept '11 Oct '11 Nov '11 Dec '11 Ambulate/Progressive None

41 Make Routine Conserve resources by incorporating data collection into daily work Example: VAP bundle data collection during charge nurse rounds Admission checklist completed & turned in to capture Falls & Pressure Ulcer risks

42 Optimize Forms Include only info need Keep form easy to complete

43 Plot Data Over Time Urinary Catheter Compliance Rate Goal 100% 100% 90% 80% 70% 60% Unit pilot daily review launched House-wide daily review launched - CL = 82% Pilot RN Directed P&P expanded to Hospitalists Apr '11 50% 40% 30% 20% 10% 0% April '10 May '10 June '10 July '10 Aug '10 Sep '10 Oct '10 Nov '10 Dec '10 Jan '11 Feb '11 Mar '11 Apr '11 May '11 Jun '11 Jul '11 Aug '11 Sep '11 Oct '11 Nov '11 Dec '11

44 Display Data Effectively Motivating Visuals serve as motivators & reality checks Validating Don t need to be perfect, just useful

45 Motivating

46 Immediate Feedback

47 Validating Chest Pain RRT Calls AMI Protocol Implemented House-wide Chest pain RRT calls per 1000 D/Cs Month Chest pain Calls/1000 discharges

48 Got that?

49 The KISS Principle Plan your data collection who, what, when, where, how? Seek usefulness, not perfection! Test data collection method Train all data collectors

50 Model For Improvement What are we trying to accomplish? How will we know that a change is an improvement? What change can we make that will result in improvement? AIM MEASURE Selecting Change Act Study Plan Do Small Tests of Change

51 Find out what s working Brainstorm Rank Construct Plan to Test Test SMALL

52 The PDSA Cycle What s next? Act Ready to implement? Try something else? Next cycle Plan Objective Questions & predictions Plan to carry out: Who?When? How? Where? What will happen if we try something different? Did it work? Study Complete data analysis Compare to predictions Summarize Do Carry out plan Document problems Begin data analysis Let s try it!

53 Example of a Test of Change Discharge: Planned visits for blood sugar management Plan: Ask one patient if he or she would like more information on how to manage his or her blood sugar. Do: Dr. J. asked his first patient with diabetes on Tuesday. Study: Patient was interested; Dr. J. was pleased at the positive response. Act: Dr. J. will continue with the next five patients and set up a planned visit for those who say yes. Act Ready to implement? Try something else? Next cycle Study Complete data analysis Compare to predictions Summarize Plan Objective Questions & predictions Plan to carry out: Who?When? How? Where? Do Carry out plan Document problems Begin data analysis

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55 The PDSA Cycle What s next? Act Ready to implement? Try something else? Next cycle Plan Objective Questions & predictions Plan to carry out: Who?When? How? Where? What will happen if we try something different? Did it work? Study Complete data analysis Compare to predictions Summarize Do Carry out plan Document problems Begin data analysis Let s try it!

56 Why Test?

57 The Value of Failed Tests I did not fail one thousand times; I found one thousand ways how not to make a light bulb. Thomas Edison

58 Guidelines For Testing Change Fail early, fail often What can we do by next Tuesday? Pick willing volunteers AIM big, but test small Steal shamelessly

59 Guidelines For Testing Change Do not try to get buy-in, consensus Be innovative to make test feasible Collect useful data during each test Test over a wide range of conditions

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61 Just Do It! Wait! Also, Study It Reasons for failed tests 1. Change not executed well 2. Support processes inadequate 3. Hypothesis/hunch wrong: Change executed but did not result in local improvement Local improvement did not impact aim Collect data during the Do phase of the cycle to help differentiate these situations.

62 Common Traps Plan Do, Plan Do Do Act, Do Act No testing, only data collection No ramps of tests, random PDSAs Undisciplined PDSAs, no documentation Prediction what are we going to learn Beware of Cycles longer than 30 days

63 Wrapping It Up: Mistakes Made In Improvement Teams Try to take on the entire project at once Failure to state a measurable, specific aim Failure to tie measures to aims Over-reliance on education and awareness Failure to state a population focus Failure to abandon a change that does not lead to an improvement Failure to engage process owners on a team and solicit their ideas Failure to make data visible to all engaged in the process

64 Test small Aim BIG

65 Work with the willing

66 Don t try to get consensus

67 Fail Early, Fail Often

68 What can I do by next Thursday?

69 Be innovative

70 Collect useful data during each test

71 Applying Lessons Learned

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73 References The Improvement Guide: A Practical Approach to Enhancing Organizational Performance. G. Langley, K. Nolan, T. Nolan, C. Norman, L. Provost. Jossey- Bass Publishers., San Francisco, Quality Improvement Through Planned Experimentation. 2nd edition. R. Moen, T. Nolan, L. Provost, McGraw-Hill, NY, Understanding Variation, Quality Progress, Vol. 13, No. 5, T. W. Nolan and L. P. Provost, May, A Primer on Leading the Improvement of Systems, Don M. Berwick, BMJ, 312: pp , Accelerating the Pace of Improvement - An Interview with Thomas Nolan, Journal of Quality Improvement, Volume 23, No. 4, The Joint Commission, April, Patient Safety and Quality: An Evidence-Based Handbook for Nurses

74 Questions? Cheryl Ruble, RN, MS, CNS Improvement Advisor