Improving Care: More Method, Less Uncertainty, Impact summit 30 October 2013
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Transcript of Improving Care: More Method, Less Uncertainty, Impact summit 30 October 2013
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Improving Care: More Method, Less Uncertainty,
Impact summit
30th October 2013
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Professor Moira LivingstonClinical Director of Improvement Capability NHS Improving Quality
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Housekeeping
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Starting the journey
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The journey so far…EVENT Improving Care: More Method, Less Uncertainty
Friday 6th September
The first in a series of measurement master-classes for senior clinicians
Dr Bob Lloyd, Institute for Healthcare Improvement US, Professor Moira Livingston, NHS Improving Quality, Professor Sir Bruce Keogh, NHS England, Julian Hartley, NHS Improving Quality, Dr Maxine Power, Salford Royal NHS Foundation Trust
WEBINAR Thursday 10th Oct
Different national approaches - how to use national data to drive improvement at all levels
Dr Veena Raleigh, Kings Fund, Göran Henriks, Jönköping County Council, Sweden, Prof Jonathon Gray, Dr Mataroria Lyndon, Counties Manukau Health, New Zealand
WEBINAR Thursday 17th Oct
19 Delegates
Different national approaches – mortality, exploring how to use complex indicators to drive improvement
Dr Bob Lloyd, Institute for Healthcare Improvement US, Dr Anna Trinks, Jönköping County Council, Sweden
WEBINAR
Wednesday 23rd Oct
Different national approaches - improvement and transparency
Dr Carol Peden, Royal United Hospital Bath, Alide Chase, Diane Waite, Kaiser Permanente, US
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Time Topic Lead
0930-0945 Welcome, introductions and overview of the day
Professor Moira LivingstonClinical Director of Improvement Capability NHS Improving Quality
0945-1000 View from the top Professor Sir Bruce Keogh
National Medical Director, NHS England
1000-1100
The strategic measurement for improvement journey• Choosing the right measures
Mike Davidge with Dr Bob Lloyd (15 min video) Dr Maxine Power Dr Veena Raleigh
1115-1130 Break
1130-1230
The strategic measurement for improvement journey• Collecting good data• Making sense of data
Mike Davidge with Dr Maxine Power Dr Veena Raleigh
1230-1310 Lunch
1310-1430 Knowledge Exchange: Making it happen• Details on your desks Mark Outhwaite
1430-1550 Steering the measurement journey: what next? Mark Outhwaite
1550-1600 Summary and Closing Professor Sir Bruce Keogh
Shape of the day
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Purpose of the impact summitThe key aims:
• Reflect and review learning and implications from the master-class so far
• Build depth of knowledge
• Discuss and identify how to make improvements in our measurement systems– based on better / more informed decision making
• Promote understanding of the difference between measurement for improvement and for other purposes
• Share and embed practical techniques for choosing measures, applying measures and interpreting measures
We will do this by:
• Case studies of real world examples, with opportunity to discuss and question
• Providing interactive sessions to work through some personal measurement challenges, to identify some actions and next steps
• Create the opportunity to identify further support needed to take for forward a measurement for improvement system, culture and practices
Note: this course will be eligible for CPD points, information to be circulated after the event
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Speakers for this morning
Professor Sir Bruce KeoghNational Medical Director, NHS England
Mike DavidgeDirector (Measurement), NHS Elect
Veena S Raleigh PhDSenior Fellow, The King’s Fund
Maxine Power PhD, MPHDirector of Innovation and Improvement Science, Salford Royal NHS Foundation Trust and Managing Director of Haelo
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Knowledge Exchange Speakers• Mel Varvel, Improvement Manager, NHS Improving Quality
• Preventing People from Dying Prematurely: GRASPing the Measurement Nettle
• Dr Frances Healey, RGN, RMN, PhD, Senior Head of Patient Safety Intelligence, NHS England & Matthew Foggarty, Patient Safety, NHS England
• The genie is out of the bottle: when Measurement for Improvement is used for other purposes
• Clare Howard, MRPharmS, Deputy Chief Pharmaceutical Officer NHS England• Developing metrics for safer medication practice
• Dr Carol Peden, Quality Improvement Fellow-Health Foundation and Consultant in Anaesthesia and Critical Care Medicine, Royal United Hospital Bath
• Mortality Reviews
• Martin McShane, Director (Domain 2) Improving the quality of life for people with Long Term Conditions, NHS England & Professor Alistair Burns, National Clinical Director for Dementia, NHS England and The University of Manchester
• Dementia
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Professor Sir Bruce KeoghNational Medical DirectorNHS England
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Mike DavidgeDirector (Measurement)
NHS Elect
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Using Poll EverywhereLive feedback and polling
Either
Text: mfimp to 07624806527 to link your phone to the session
Then all you do is send poll responses to that number as a normal SMS/textWill not work if you withhold your number
OrPoint your smartphone/tablet browser at
www.pollev.com/mfimpTo participate in the polls
Wifi: MMCNHSIQ – no passwordNo premium costs – just contained within your normal contract rates
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Question 1
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Question 2
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A word from our teacher
• Bob Lloyd reminds us briefly what he covered on 6th September
• We will be revisiting some of these points this morning with practical exercises
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CHOOSING THE RIGHT MEASURESBe clear why you are measuring and the messiness of life
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Choosing indicators
Veena Raleigh
Senior Fellow
30 October 2013
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Precursors of measurement: clarity about...
Who (audience): providers, commissioners, patients etc
Why (aim):- quality improvement, judgement, research
What (content):- dimension of quality, efficiency- population, service/sector, pathway- unit of measurement
How (process):- definition, data sources- statistical methods- interpretation
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Audience for measurement (1)
parliament / government
the NHS:- commissioners- managers - professional staff
patients, families, carers
the public
regulators, auditors
researchers
the media
The appropriate content and presentation formats of indicators for these audiences differ
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Audience for measurement (2)
For example:
clinicians need disaggregated, risk-adjusted information at small unit level, benchmarked against peers, and showing trends over time
commissioners want information on outcomes, and quality linked to cost-effectiveness
patients, public want information that is simply constructed, clearly presented, and easy to interpret ie good vs bad
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• Judgement:- performance assessment/management - incentivising quality improvement (P4P eg QOF, CQUIN, quality premiums)- supporting patient choice- public accountability
assumes unambiguous evidence of performance, designed for EXTERNAL accountability
Aim of measurement
• Quality improvement:- internal use- benchmarking against peers for feedback and learning
assumes indicators are 'tin openers' for INTERNAL use, designed to prompt further investigation and appropriate action
or
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Indicators for judgement Indicators for improvement
unambiguous interpretation variable interpretation possible
unambiguous attribution ambiguity tolerable
definitive marker of quality screening tool
good data quality ‘good enough’ data quality
good risk-adjustment partial risk-adjustment tolerable
statistical reliability preferred but not essential
cross-sectional time trends (SPCs, run charts etc)
punishment/reward learning, change in practice
external control internal control
data for public use data for internal use
stand-alone allowance for context
risk of unintended consequences low risk
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Content of measurement (1)
dimension of quality:effectiveness, patient experience, safety ………..timely, access, equity, VfM, care coordination and integration
population group, condition, service
structure, process and outcome indicators: S + P = O
unit of measurement eg commissioner and/or provider
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Content of measurement (2)
Indicators for commissioners (CCGs, LAs):- population based
Indicators for providers:- Primary care- Community care- Out-of-hours care- Hospital care (emergency and planned)- Tertiary and specialist care- Mental health care- Palliative care- Social care (residential & home care)
Indicators by population group,
condition
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Example: cancer
NHSOF / COIS domain 1 indicators:cancer mortality < 75cancer survival
reducing cancer mortality depends on:reducing cancer incidence ANDimproving cancer survival
these outcomes require improvement in the underlying drivers eg:cancer incidence: preventive measures eg smoking cessation services (process measure)cancer survival: screening, timely referral, treatment rates (process measures), staff capacity/skills and surgical volumes (structure measures)
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Cancer (example indicators)
Risk factors and prevention Diagnosis, treatment, end-of-life care
Rates of: - incidence O- smoking prevalence, diet etc IO- population awareness P
- no of smoking cessation clinics S- smoking quitters O
Rates of:- screening P - referrals, diagnostic tests, time to results P- detection rates O- stage at diagnosis O- access, waiting times P- cancers detected at emergency presentation P- surgical volumes S- treatment (surgery, radiotherapy) rates P- information for patients P - length of stay, readmission, mortality rates O- one-year survival: proxy for late diagnosis O- management by a multidisciplinary team P
- staff skills, training S- adherence to guidelines P- access to end-of-life care P- patient experience and wellbeing O- cancer deaths by place of death O- participation in national clinical audits S
PRIMARY OUTCOME MEASURESCancer mortality O
Cancer incidence O Cancer survival O
KeyS=structure measureP=process measuresIO=intermediate outcome measureO=outcome measures
Inequalities
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30
If you were in a lift with the rest of your table group could you clearly and briefly describe your aim in a sentence – i.e. the time it takes to travel from one floor to the next?
Write your aim statement down
Share with your table
Aims exercise
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Driver Diagrams
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Aim
Measurement
Drivers (changes)
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What is a Driver Diagram?
• Reinforces the aim statement as the goal • Clarifies the big picture • Identifies primary system components• Identifies projects which will influence • Aids in development of measurement
Most importantly: Helps to articulate the overall aim and avoid missing important system components
33
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What are driver diagrams used for?
• Personal improvement projects• Clarification in complex tasks• Project / Programme Management• Strategy, design and execution
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Primary Drivers
• Push conceptual thinking • Avoid focus on one area alone • Usually categorical• Abstract• Removal reduces likelihood of success• Projects wrap into them
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Secondary Drivers
• Projects• Tasks• Actions • Focus Areas
• Aid allocation of workload• Ensure clarity and focus for testing
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Lose
2 stone
by March
2014
Healthy Eating
Measurement & feedback
Exercise
Prevent avoidable complications
(Lifestyle)
• Regular shopping• More fresh fruit• 3 meals per day• No food after 6pm• 2 litres of water per day
• Weekly weight• Measure Inches• Pictures on the fridge• Regular support• Weight record chart updated showing trend
• Daily exercise for a minimum of 20 mins• Measure progress• Identify barriers• Build distractions to help• Add something nice – sauna / jacuzzi• Search for an exercise that suits
• Plan for eating out / weekends• Beer & wine – develop a plan• Know your weaknesses• Habits and patterns• Avoid bad influencers• Encourage contact with supportive
people
My driver diagram for weight loss
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Develop & test a
measurement instrument for harm free care from pressure ulcers, falls,
catheters and VTE by
September 2011
Agree Operational Definitions
Develop Technical Capability
Determine how the instrument is used
Determine the level of user satisfaction
• Evidence review• Expert debate / input• Grey areas agreed• Practical use
• Design characteristics• Local, regional, national• Universal platform• Guidelines for use
• Who collects & when?• From where?• What happens after?• How are data used?
• Local users - feedback• Data leads - feedback• Leadership• Senior stakeholders
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Outcome : Rate of patient’s harmed by falls
1
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Process : training in falls2
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Cancer (example indicators)
Risk factors and prevention Diagnosis, treatment, end-of-life care
Rates of: - incidence O- smoking prevalence, diet etc IO- population awareness P
- no of smoking cessation clinics S- smoking quitters O
Rates of:- screening P - referrals, diagnostic tests, time to results P- detection rates O- stage at diagnosis O- access, waiting times P- cancers detected at emergency presentation P- surgical volumes S- treatment (surgery, radiotherapy) rates P- information for patients P - length of stay, readmission, mortality rates O- one-year survival: proxy for late diagnosis O- management by a multidisciplinary team P
- staff skills, training S- adherence to guidelines P- access to end-of-life care P- patient experience and wellbeing O- cancer deaths by place of death O- participation in national clinical audits S
PRIMARY OUTCOME MEASURESCancer mortality O
Cancer incidence O Cancer survival O
KeyS=structure measureP=process measuresIO=intermediate outcome measureO=outcome measures
Inequalities
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REDUCE MORTALITY
FROM CANCER IN ENGLAND
BY XX% BY MARCH 2016
PRIMARY PREVENTION
SECONDARY PREVENTION
SERVICE OPTIMISATION
END OF LIFE AND SOCIAL CARE
• Lifestyle • Genetics • Campaigns• Social determinants
• Screening • Primary care • Access to L2/3 service • Lifestyle change• Medicines optimisation
• Value driven• Quality greater than cost• Equity in access• Excellent experience
• Cross sector working• Hospice & faith • Seven day HSC service• Equipment• Pain management
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Cascading drivers
1
2
3
1
2
3
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Limitations of driver diagrams
• Not a perfect science
• Two dimensional & simplistic
• Working schematic – requires amendment
• Interplay between drivers
• Contribution of each driver is not equal
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Question 3
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Question 4
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COFFEEPlease take only 15 minutes
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COLLECTING GOOD DATAThe measurement journey
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Introducing the Measures checklist
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Define measures
An operational definition is a description, in quantifiable terms, of what to measure and the steps to follow to measure it consistently
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Example definitionMeasure name:
DNA rate for clinic AWhy is it important? (Provides justification and any links to organisation strategy)
We need to ensure that the clinic is not disrupted by having unexpected gaps in the clinic schedule. The policy for this clinic is to offer another appointment which means that other patients may be disadvantaged if we have too many patients being rescheduled.Who owns this measure? (Person responsible for making it happen)
The outpatient clinic manager
Measure definitio
n
What is the definition? (Spell it out very clearly in words)
The percentage of patients booked to attend clinic A who did not attend for their appointment and no warning was received at the clinic before it started.What data items do you need?
The number of patients booked to attend clinic (B) and the number of patients who failed to attend without warning (F)What is the calculation?
100 x DNA patients (F) / Booked patients (B)Which patient groups are to be covered? Do you need to stratify? (For example, are there differences by shift, time of day, day of week, severity etc)
All patients booked into clinic
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Collecting data
• What – All patients, a portion or a sample?
• Who – collects the data? • When – is it collected
– real time or retrospective?
• Where – is it collected?• How – is it obtained
– Computer system or audit?
You need a plan which you test using PDSA cycles
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Checklist exercise
• Complete page one and collect on page two of the measures checklist provided - for a measure that you are using or are planning to use
• Share with your colleagues
You have 15 minutes
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Question 5
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Question 6
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MAKING SENSE OF DATAVariation
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Variation exercise
• Using the materials provided make the best paper aeroplane you can
• Put your initials on it
You have 15 minutes
When instructed - throw your planes!
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Aeroplanes fly different
distances
Problem
Equipment People Procedures
Materials
Causes
Types of paper e.g.
card, tracing paper,
No clear instructions provided
Some tables had scissors, rulers to help
Skills / ideas
Throwing styles
Fishbone diagram
Environment
Air /Wind
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CommonCause
Special Cause
Classifying variation
Stable in time and therefore relatively
predictable
Irregular in time and therefore unpredictable
The paper used
Persons technique
Design of the plane
Water spill
Mike’s plane
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“There are different improvement strategies depending of which type of variation is present (common cause or special cause), so it is important for a team to know the difference.”
Michael GeorgeChairman and CEO of George Group
Consulting
Why classify variation?
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Question 7
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Question 8
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Instructions for the afternoon session
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The Knowledge Exchange Carousel
• After lunch you will be directed to move direct to a Knowledge Exchange Carousel ‘Pod’ with the same number as your table number
• You will rotate through 3 ‘Pods’ at 25 minute intervals• In each Pod you will discuss a case study presented by a speaker• After the third Knowledge Exchange session you will remain in
the Pod for the next task
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Knowledge Exchange Speakers• Mel Varvel, Improvement Manager, NHS Improving Quality
• Preventing People from Dying Prematurely: GRASPing the Measurement Nettle
• Dr Frances Healey, RGN, RMN, PhD, Senior Head of Patient Safety Intelligence, NHS England & Matthew Foggarty, Patient Safety, NHS England
• The genie is out of the bottle: when Measurement for Improvement is used for other purposes
• Clare Howard, MRPharmS, Deputy Chief Pharmaceutical Officer NHS England• Developing metrics for safer medication practice
• Dr Carol Peden, Quality Improvement Fellow-Health Foundation and Consultant in Anaesthesia and Critical Care Medicine, Royal United Hospital Bath
• Mortality Reviews
• Martin McShane, Director (Domain 2) Improving the quality of life for people with Long Term Conditions, NHS England & Professor Alistair Burns, National Clinical Director for Dementia, NHS England and The University of Manchester
• Dementia
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Sharing your learning
• At the end of the Knowledge Exchange you will remain in your last Pod
• Using the A0 poster template rapidly brainstorm the Barriers and Drivers in the current environment for each step in the measurement process
• Identify your top 2 Barriers and top 2 Drivers (dot vote if necessary)
• Transfer them to your Action Planner Driver Diagram
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Action Planning
• Identify the actions you could take collectively as a senior leadership cadre to address the barrier or driver
Or• The support you need as a
senior leadership cadre to address the barrier or driver
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Feedback
• One barrier or driver and the associated actions• One headline – if a journalist had been in the Pod with you what
would be the headline they would have written
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Personal Action Planner
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Afternoon thoughts and reflections
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Lunch1230 - 1310
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Knowledge Exchange
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Feedback
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Professor Sir Bruce KeoghNational Medical DirectorNHS England
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The Improving Care: More Method, Less Uncertainty,
Impact summitFurther details about the webinar series :
www.nhsiq.nhs.uk