An Introduction to Quality Improvement Day 2

Transcription

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2 An Introduction to Quality Improvement Day 2

3 QUALITY IMPROVEMENT SCIENCE

4 Deming s Lens of Improvement Appreciation of a system Theory of Knowledge Psychology Understanding Variation

5 One need not be eminent in any part of profound knowledge in order to understand it and to apply it. The various segments of the system of profound knowledge cannot be separated. They interact with each other.

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7 Development of Profound Knowledge Variation Shewhart Control Chart 1924 Design of Experiments Sir Ronald Fisher, 1925 Shewhart s 1931 and 1939 Books on Quality Control* Sampling methods Developed, H. F. Dodge Use of statistical methods to support the war effort Enumerative vs Analytic Studies in Statistics, Deming Systems Psychology Hawthorne Experiments Plant 1927 General Systems Theory Lugwig von Bertalanffy, 1949 Tavistock Institute 1951 Socio-technical System Principles of Systems Jay Forrester, 1968 Maslow Hierarchy of Needs1962 Theory of Constraints The Goal E. Goldratt, th Discipline Peter Senge 1990 Switch Dan Heath 2011 Knowledge Mind & The World Order, C.I. Lewis 1929* Lectures at The USDA, 1938, organized By Deming* How We Think Dewey, 1933 Human Side of Enterprise D. McGregor, 1960 Motivation Theory Herzberg, 1968 Double Loop Learning in Organizations Chris Argyris, 1977 Drive Daniel Pink 2009

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9 Two Types of Knowledge Subject Matter Knowledge: Knowledge basic to the things we do in life. Professional knowledge. Subject Matter Knowledge Improvement Science Profound Knowledge: The interaction of the theories of systems, variation, knowledge, and psychology.

10 Knowledge for Improvement Subject Matter Knowledge Improvement: Learn to combine subject matter knowledge and profound knowledge in creative ways to develop effective changes for improvement. Improvement Science

11 System of Profound Knowledge Subject matter Knowledge Appreciation of a system Theory of Knowledge Psychology Understanding Variation Knowledge for Improvement

12 PSYCHOLOGY OF IMPROVEMENT

13 MOTIVATION

14 CAN T The COM-B model, Michie et al (2011)

15 WON T The COM-B model, Michie et al (2011)

16 One More Time: How Do You Motivate Employees? Harvard Business Review (reprint Jan, 2003)

17 Allow autonomy Enable Mastery How to motivate Create sense of purpose

18 CHANGE

19 The COM-B model, Michie et al (2011)

20 Opportunity

21 The Everett Rogers curve

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23 Direct the Rider (rational) Motivate the Elephant (emotional) Chip and Dan Heath, Switch

24 Improvement in health care is 20% technical and 80% human Marjorie Godfrey, MS, RN, PhD The Dartmouth Institute for Health Policy and Clinical Practice

25 CHANGE IDEAS - INNOVATION

26 Take a Specific Aim We know what we want to improve Change ideas are the possible how s. BE CREATIVE!

27 Fishbone (Cause and Effect Diagram) Communication Fax machine doesn t work properly Dictation delays clinic, always get out of sync Late & early arrivals Culture it s accepted See early patients early (sometimes) See patients even if late Patients don t have own transport Scheduling Mismatch of arrivals and resources Hospital transport is late Reliant on others for lifts Don t know how long things take cycle times Non standardised variation in content Waiting for other professionals to finish CF Clinic Why are Patients waiting in the CF clinic? Trials PEG changes, not planned into timings Notes Scales Going to find nebuliser from the ward X ray Going to the Pharmacy if patient too unwell Pharmacy Taking patient off for a ward tour Answering the doorbell Telephone Calls Calls from the ward Service Improvement Treatments Finding Things 17 Interruptions

28 5 Whys Getting to the root cause WHY did this patient stay in hospital 111 days WHY?...because they developed hospital acquired pneumonia WHY?...because they were immobile WHY?...because they fell on the ward WHY?...because they suffered from dementia and would have been better cared for in the familiar environment of their own home

29 Review Your Process Map Input Output

30 Change Ideas Langley s Change Concepts Some Examples Eliminate waste are all processes essential? Eliminate multiple entry can this be combined? Move steps closer together Find and remove bottlenecks Do tasks in parallel Use pull systems Give people access to information Use proper measurement Smooth workflow, reduce variation Minimise handoffs passing work between depts or individuals Reduce waiting times Standardise use exactly same system Listen to customers

31 Meetings: Traditional Adversarial Thinking Take sides. Argue. Prove the other side wrong.

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33 Brainstorming - Creative thinking! No idea is too big, too small or out of the question Do not judge or criticise others ideas Listen to others ideas and build on them 1. Silent period think about improvements to the process and write on a post it 2. Interactive period shout out other ideas that come to mind!

34 Multivoting Review all the ideas & merge similar ideas Vote for 1/3 ideas, use selection criteria, e.g. Ideas that can be started fast The change is reasonably low cost The effort is small compared to the impact The idea can be tested without getting permission from others Count the votes Test the top change ideas using PDSA

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36 Time Series Data: All improvement is change, not all change is improvement.

37 Looking at Data Here are two numbers what s going on? Value 5 0 A B

38 Hold on A B Series

39 But A B Series

40 But then again A B Series

41 Erm 30 A 25 B Series

42 Here are two pie charts we wanted to decrease DNAs (no shows)

43 No Shows Hold on A B Series Weeks

44 No Shows But A B Series Weeks

45 No Shows But then again A B Series Weeks

46 What s going on with this data? Test 1 Test 2 Test 3 Test

47 What s going on with this data? Test 1 Test Series2 Series Test 3 Test Series2 15 Series Service Improvement

48 Beware of averages too Here are our two numbers (Monthly data) Value 5 0 A B

49 Here s what s happening by week 40? Weekly Data Series A B

50 Or Even Series

51 Summary One number will always be different to another plot data over time Tables take time to understand Chart your data to see what s happening Beware of averages they can be misleading

52 VARIATION

53 Profound Knowledge Understanding Variation Appreciation of a System Theory of Knowledge Psychology Understanding Variation

54 Reacting to Variation

55 William Sealy Gosset ( ) Sir Ronald Fisher ( )

56 Austin Bradford Hill

57 Sampling Water Content

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59 Sampling Water Content TIME

60 Walter Shewhart ( ) W. Edwards Deming ( )

61 Sampling Water Content TIME

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63 If I had to reduce my message for management to just a few words, I d say it all had to do with reducing variation. W. Edwards Deming

64 What Time is it? Write down the current time in minutes past the hour

65 Unintended variation patients vary

66 What do people call me? Dr. Downes Tom Dad Intended Variation

67 Intended and Unintended Variation

68 Shewhart s Theory of Variation Common Causes: those causes inherent in the system over time and affect all outcomes of the system Chance cause Stable over time

69 Common Cause Variation

70 Shewhart s Theory of Variation Special Causes: those causes not part of the system all the time. Arise because of specific circumstances Assignable cause Unstable process

71 Special Cause - My trip to work Upper process limit Mean Lower process limit

72 Theatre Incidents January March 2012 SSC implemented

73 Responding to Special Cause Variation Identify the cause: If positive then can it be replicated or standardised. If negative then cause needs to be eliminated

74 Theatre Incidents January March 2012 SSC implemented

75 Responding to Common Cause Variation 1. Reduce variation: make the process even more predictable or reliable (and/or) 2. Not satisfied with result: redesign process to get a better result

76 Process with special cause variation Identify the cause: if positive then can it be replicated or standardized. If negative then cause needs to be eliminated Process with common cause variation Reduce variation: make the process even more reliable Not satisfied with result: redesign process to get a better result

77 Theatre Incidents January March 2012 SSC implemented

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79 SPC CHARTS

80 SPC, Statistical Process Control or The Control Chart Elements 1. Run chart/graph showing data, running record, time order sequence 2. A line showing the mean 3. 2 lines showing the upper and lower process control limits You only need 25 data points to set up a control chart, but 50 are better if available

81 Common cause variation - a stable process F M A M J J A S O N D J F M A M J J A S O N D Upper process limit Mean Lower process limit

82 Standard Deviation or σ In statistics, standard deviation shows how much variation exists from the mean. A low standard deviation indicates that the data points tend to be very close to the mean; high standard deviation indicates that the data points are spread out over a large range of values.

83 Standard Deviation and a normal distribution

84 PRACTICAL INTERPRETATION OF THE STANDARD DEVIATION 99.6% will be within 3 s Mean - 3s 1 in 256 Mean Mean + 3s

85 3s AND THE CONTROL CHART 3s 3s UCL Mean LCL 6s

86 Special cause variation F M A M J J A S O N D J F M A M J J A S O N D

87 SPECIAL CAUSES - RULE 1 UCL Point above Upper Control Limit (UCL) MEAN LCL

88 SPECIAL CAUSES - RULE 1 UCL MEAN LCL Or point below Lower Control Limit (LCL)

89 SPECIAL CAUSES - RULE 2 UCL MEAN LCL Eight points above centre line

90 SPECIAL CAUSES - RULE 2 UCL Or eight points below centre line MEAN LCL

91 SPECIAL CAUSES - RULE 3 UCL Six points in a downward direction MEAN LCL

92 SPECIAL CAUSES - RULE 3 UCL Or six points in an upward direction MEAN LCL

93 What use is this? Evaluate and improve underlying process Is the process stable? Use data to make predictions and help planning Recognise variation Prove/disprove assumptions and (mis)conceptions Help drive improvement identify statistically significant change

94 Example

95 Annotated SPC Charts One of the most powerful tools for improvement Describe a process captured over time (as opposed to being a single sample) Reveal any trends a process might be experiencing When combined with careful annotation they track the impact of change

96 Why We Want to Annotate Our Charts 'And this is the period when the cat was away. '

97 Annotated SPC Charts

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99 CAPACITY AND DEMAND

100 If I had to reduce my message for management to just a few words, I d say it all had to do with reducing variation. W. Edwards Deming

101 Procedure Time (Minutes) Variation & Queues 100% 80% 50% Consecutive Patients 80% rule is the most efficient balancing waiting and waste

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104 Calculating the 80% rule 80% Rule = Variation x Lowest Value (Variation = High Value Low Value) Variation = 23 7 = x 0.8 = = (approx. 20min)

105 Plan Cycle Time = 20m

106 More Variable More Reliable Cycle time at 80% - PDSA 1 Role Cycle Time at 80% Lung Function 15m Weight & Nurse 10m Dietician 20m Dr 20m Others 15m

107 Patient 10 PDSA - Plan Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient 9 L L L W N D D D D Dr Dr Dr Dr O O O L L L W N D D D D Dr Dr Dr Dr O O O L L L W N D D D D Dr Dr Dr Dr O O O L L L W N D D D D Dr Dr Dr Dr O O O L L L W N D D D D Dr Dr Dr Dr O O L L L W N D D D D Dr Dr Dr Dr L L L W N D D D D Dr Dr L L L W N D D D D L L L W N D D

108 PDSA - Plan Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient 9 Patient 10 Patient 11 Patient 12 Patient 13 Patient 14 Patient 15 Patient 16 Patient 17 Patient 18 L L L W N D D D D Dr Dr Dr Dr O O O L L L W N D D D D Dr Dr Dr Dr O O O L L L W N D D D D Dr Dr Dr Dr O O O L L L W N D D D D Dr Dr Dr Dr O O O L L L W N D D D D Dr Dr Dr Dr O O O L L L W N D D D D Dr Dr Dr Dr O O O L L L W N D D D D Dr Dr Dr Dr O O O L L L W N D D D D Dr Dr Dr Dr O O O L L L W N D D D D Dr Dr Dr Dr O O O L L L W N D D D D Dr Dr Dr Dr O O O L L L W N D D D D Dr Dr Dr Dr O O O L L L W N D D D D Dr Dr Dr Dr O O O L L L W N D D D D Dr Dr Dr Dr O O O L L L W N D D D D Dr Dr Dr Dr O O O L L L W N D D D D Dr Dr Dr Dr O O O L L L W N D D D D Dr Dr Dr Dr O O O L L L W N D D D D Dr Dr Dr Dr O O O L L L W N D D D D Dr Dr Dr Dr O O O

109 PDSA Do & Study

110 Demand is increasing... More slots needed...

111 80% = 21mins 3hrs = 8 Patients

112 80% = 21mins 80% = 18mins 3hrs = 8 Patients 3hrs = 10 Patients

113 80% = 21mins 80% = 18mins 80% = 14mins 3hrs = 8 Patients 3hrs = 10 Patients 3hrs = 12 Patients

114 HOW DO YOU REDUCE COMMON CAUSE VARIATION?

115 Volume drives value.

116 Capacity required = (27-7) x 80% + 7 = 23

117 Capacity required = (27-7) x 80% + 7 = 23

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119 Capacity required = 42 (previously = 46) (4 beds less than separate units ~ 320,000)

120 Lung Cancer Clinic =

121 Lung Cancer - pooled

122 More Queuing...

123 Which is best? C S S C S C C C S C S S

124 And Finally - Which is best? S C Long S C Long C Short C Long S C Short S S

125 Quiz Example Clickers at the ready

126 THE MARSHMALLOW CHALLENGE

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129 SPREAD

130 Testing Multiple cycles investigating the change idea under many different conditions What can you learn from continued testing?

131 Implementation Once a team has achieved a high degree of belief What would it really take to achieve this step

132 Confidence PDSA Cycle: Deciding on Scale of Test Engagement, Readiness to Change Current Situation Resistant (No commitment) Indifferent (some commitment) Ready (strong commitment) Low Degree of Belief that change idea will lead to Improvement Cost of failure large Cost of failure small Very Small Scale Test Very Small Scale Test Very Small Scale Test Very Small Scale Test Very Small Scale Test Small Scale Test High Degree of Belief that change idea will lead to Improvement Cost of failure large Cost of failure small Very Small Scale Test Small Scale Test Large Scale Test Small Scale Test Large Scale Test Implement Source - The Improvement Guide

133 SUSTAIN

134 When you have achieved your specific aim Building reliability into the process Restrict variation from your process Sustain improvement long term Quality Improvement - The structure PDSA SDSA Standardise Some techniques.. Assessment - 5Ps Change Ideas Define Themes

135 SOP (Standard Operating Procedures) or Playbooks Define exactly how a process works Great for new staff Reduce variation

136 Use Visual Management to build-in knowledge

137 Strategy: Use Visual Controls Which dial turns on the burner?

138 Schipol Airport, Amsterdam

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140 Amsterdam Science Museum Amsterdam Shopping Centre Amsterdam Art Deco Cinema

141 International Spread Lausanne Olympic Museum, Switzerland

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145 Surprise!

146 Design in reliability Make it easiest to do the process the redesigned way Don t rely on one person being able to deliver part of your process they will take leave at some point! 5S (Sort, Straighten, Shine, Standardise, Sustain) remove all old materials not required for your new process

147 The Sheffield MCA

148 We aim to help teams improve the quality and efficiency of services for patients and staff Pathway Improvement Microsystem Coaching Intensive Improvement Support Support for Large Scale Change Project Management Programme Management

149 Coaches per Cohort C1 C2 C3 C4 C5 C6 C7 869 Improvement Collaboratives Ward Outpatients Weston Park

150 Based on Dartmouth s evidence based ecoach the Coach programme translated to NHS and UK context Sheffield Faculty 6 month taught portion Experiential learning you need to coach a microsystem, learn from and report on this

151 WARD Collaborative What are we testing?

152 What are we learning? This is really hard work but results can be achieved

153 What are we learning? Leadership is essential - time and space is needed for improvement work to happen.

154 What are we learning? It s hard to coach your own team

155 What are we learning? The structured approach helps you make measurable sustainable improvements 5 P Assessment 5P The Microsystem Improvement Ramp Dartmouth Microsystem Improvement Curriculum Cause & Effect Global Specific Aim Aim Global Aim Theme Theme PDSA Change Ideas Measures Specific Aim Change Ideas Effective Meeting Skills 1 2 PDSA 2 A P Measures 1 S D A S P D Flowchart A P S D A P S D Global Aim 2 2 A P SDSA S D 3 3 A S P D Global Aim SDS A

156 What are we learning? Assess the system before deciding on solutions

157 What are we learning? Improvement work is 80% human and 20% technical - use the team & the patients knowledge and skills

158 What are we learning? Giving the team ownership of ideas and decisions - what to improve and how to improve it.

159 What are we learning? Involving patients in the work from the start is essential

160 What are we learning? Start small and build confidence.

161 What are we learning? Use measurement to show that changes are measurable improvements 50% reduction in length of stay

162 Over 160 teams have worked on microsystem improvement across STH, SCH and the care trust Geriatric and Stroke Medicine Microsystem designed a new discharge checklist and introduced reminders which reduced the average length of time to complete E-discharge from 37 to 11 hours Urology outpatients saved 37 hours of nursing time per week by redesigning how clinics run Community Stroke Microsystem reduced waiting times to see a physiotherapist by 44% Medical Photographer Microsystem increased the number of reports completed within 21 days from 56% to 97% Dermatology Microsystem & Skin Cancer Pre-operative assessment removed the FLOW Pathway reduced average time to need for 300 patient return visits and 300 surgery from 27 days to 10 days hours of nurse time each month using an electronic assessment tool Sheffield Health and Social Care Paediatric Psychology Service Microsystem Wainwright Crescent Respite care unit reduced the number of letter templates reduced average length of stay from 46 to from 80 to 9, saving up to 2 and half hours 24 days by discussing housing issues each week earlier in a patients stay

163 Want more information? Stories & case Studies Events (Open Invite) Apply to be a Coach Apply to have your team coached

164 FLOW FLOW COACHING ACADEMY

165 Flow Coaching Academy: Cohort 1

166 Length of stay for >75y medical patients

167 FLOW FLOW FLOW COACHING ACADEMY FLOW COACHING ACADEMY Shared System Understanding Participation Build a Consensus Build a Big Room Collective Creativity FLOW FLOW COACHING ACADEMY FLOW FLOW COACHING ACADEMY FLOW FLOW FLOW COACHING ACADEMY FLOW COACHING ACADEMY Rhythm & Pace Move beyond silos A forum A physical space

168 WHO SHOULD ATTEND THIS COURSE?

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