Midlands PHM Academy · stage 2 attainment • 1.18% decrease in the achievement of 5 GCSEs or more • 0.7% decrease in the attainment 8 scores (the achievement of a pupil across

Population Health Management

NHS England and NHS Improvement

Midlands PHM Academy19th and 20th November



Welcome and Introductions

Fraser Battye

PHM programme

overall

Core Teams

specifically

Complete Coming

‘Perspectives on PHM’ (with our

Professors)

Introduction to logic models

Health and social care programme

budgeting pack (all STPs)

Ongoing support

Qualitative research methods

Systems leadership

Evidence into design

Analysis

Webinars

Actuarial support

End of life

midlandsphmacademy.nhs.uk

The Analyst Academy has been well received

Introduction to PHM and the science of improvement

Needs assessment and opportunity analysis

Impact assessment and evaluation

Population segmentation and risk prediction

Introduction to actuarial modelling

Problem structuring and communicating results

It is being extended geographically

It is also extending in scope…

5x technical masterclasses for analysts

3x sessions for leaders:

‘Everything you always wanted to

know about analysis but were afraid to

ask’

…and into an agenda for future action

Major next step: Decision Support Units

Update on PHM

programme Core Teams

You (Core Teams) are halfway through

April - June July September January

STP

engagement

November March

Day 1 for

Core TeamsDays 2&3 Days 4&5 Day 6

End of

programme

event

There is real diversity between teams (and team members!)

Needs

• How to engage stakeholders

with PHM – especially leaders

• Translating project lessons

into strategy / PHM

approaches

• Technical elements – especially

analytical

• Culture needed for PHM

• Peer learning

Stage of project cycle and likely end point

‘Technical’ ‘Relational’

Population

segmentation

Resource

mapping

Actuarial

analysis

Impactability

analysis

Risk

stratification

IG

Digital

infrastructure

Logic

modelling

Outcome

definition /

measurement

Librarian

skills

Evaluation

Multi-

disciplinary

workingLeading in

systems

Culture of

stewardship

Project

working

Influence,

persuasion,

story telling

Analyst-decision

maker

relationships

Where the

real value

lies:

move

from

analysis

to action

Learning from

the people we

serve

Valuing and

prioritising

1. Be able to describe leadership behaviours and culture needed for successful

implementation of PHM

2. Know how to engage stakeholders by articulating the value of PHM for them

3. Have started a plan for transferring lessons from your project within your STP/ICS

4. Have progressed the design of your project and have learnt from other STP/ICSs

5. Have a better understanding of specific PHM techniques

By the end of these two days, you should:

We will also ask what more you need from the Faculty experts

09:45-11:00 A leader’s perspective on PHM

11:00-11:15 Break

11:15-12:45Influencing across systems and leading from the middle: Core Team

members as PHM Champions

12:45-13:45 Lunch

13:45-14:45 Three perspectives on PHM in practice

14:45 – 15:00 Break

15:00-16:00 Rolling out PHM across your STP/ICS

16:00 – 16:10 Wrap up and look ahead to tomorrow

Evening Danny Dorling at University of Birmingham



Celebrity InterviewPeter Spilsbury and Paul Maubach

Paul MaubachChief Executive, Black Country and West Birmingham CCGs

Population Health ManagementA leadership perspective

• Using PHM techniques at a place / PCN level• Dudley outcomes framework

• Using PHM at a system level• Creating a common compelling narrative

• Reasons why we don’t want PHM

• Making it happen

Themes to consider

The Dudley GP Outcomes Frameworkhas been developed locally to replace QOF.An extensive range of screening, case finding, disease monitoring and management outcomes have been set and the first year of this initiative underway with data capture and reporting via the GP EMIS Web system.

The Dudley GP Outcomes Framework is interpolated within the wider MCP Outcomes Framework which is incentivised through the Improvement Payment Scheme of the new NHS ACO Contract for Dudley.

MC

P O

utc

om

es

Fram

ewo

rk

Outcomes focus in Dudley

• Focuses service delivery priorities on measurable key outcomes that make a practical actionable difference to our population

• Long-term condition specific targets

• Patient experience actions that we can evidence have an impact

• Relates the analysis and actions to aligned agendas for different organisations

• Shared outcomes cover the whole pathway of care/treatment

• Commissioning objectives aligned to clinical imperatives

• But what learning are we getting from this?• Clear outcomes is only part of the process

• Significant variation in method of delivery still exists

What this enables us to do

60.9

59.6

57.457.7

58.7

58.2

59

57.1

63.8

63.4

52

54

56

58

60

62

64

66

Female HLE Male HLE

Health Life Expectancy

Dudley

Walsall

Wolverhampton

Sandwell & WB

England

Healthy Life Expectancy CombinedDarker colours = Lower HLE

HLE for both females and males is lower for all place based areas within the STP compared to the national average. Walsall has the lowest Female HLE in the STP while Sandwell & WB have the lowest male HLE.

However, Dudley has the highest inequality (gap between the best and worst areas) in HLE.

Healthy Life Expectancy

Low Healthy Life Expectancy

Deprivation

Low School Readiness

Low academic attainment

Low Educational Attainment

Poor diet

Low levels of physical activity

Crime Deprivation

Income Deprivation

Low levels of affordable

housing

High levels of unemployment

High proportion of teenage pregnancy

Low Key Stage 2 Attainment

High levels of obesity

Economic Inactivity

Higher levels of physical and mental impairment for

longer periods of life

Cyclical reinforcement of poor health behaviours

Lack of educational, economic facility to

improve outlook Obesity

Depressive reasoning –‘things will always be

the same’ Increased risk of diabetes

Increased risk of chronic

diseases later in life

Reduced self esteem

Reduced academic

performance

Lower emotional, behavioural, social,

and school wellbeing Increased

disability

Increased risk of anxiety and depression

HLE Problem Tree

Decrease in family role models for physical literacy

Lower numbers of micro, small

and medium size businesses in the

area

Low phonics

Readiness

High proportion of Lone parents

Low GCSE attainment

Impaired development of motor skills and cognitive function

High density of fast food

outlets

Increase in Fast food consumption, sugary

beverages, snack foods and portion sizes.

Income Deprivation

Crime Deprivation

Decrease in family role models for physical literacy

Low levels of activation

Drivers

Consequences

Wolverhampton

Dudley

Walsall

Sandwell & West Birmingham

HLE

IMD

No Qualifications

School Readiness

Economic Inactivity

5 Fruit & Veg Day

Physical Inactivity

Yr 6 Obesity

Adult Obesity

HLE

IMD

No Qualifications

School Readiness

Economic Inactivity

5 Fruit & Veg Day

Physical Inactivity

Yr 6 Obesity

Adult Obesity

HLE

IMD

No Qualifications

School Readiness

Economic Inactivity

5 Fruit & Veg Day

Physical Inactivity

Yr 6 Obesity

Adult Obesity

HLE

IMD

No Qualifications

School Readiness

Economic Inactivity

5 Fruit & Veg Day

Physical Inactivity

Yr 6 Obesity

Adult Obesity

All predictors have been arranged to the same polarity so red is worst and green best. The bars depict centiles 1 to 100. Predictors are arranged in order of influence in the model. Arrows show trend.

Predictor Variable Benchmarking

• For every percentage point increase in children who are not school ready there is a:

• 0.7% decrease in key stage 2 attainment

• 1.18% decrease in the achievement of 5 GCSEs or more

• 0.7% decrease in the attainment 8 scores (the achievement of a pupil across 8 qualifications)

• 1.1% increase in the proportion of the adult population who have no formal qualifications

Low levels of school readiness are associated with the following:

• High levels of low income families

• High proportions of lone parents

• High rates of teenage pregnancies

• High levels of deprivation• High proportions of long

term conditions, especially obesity, diabetes, CHD and depression

Low levels of School Readiness

Early educational attainment

• For every percentage point increase in the proportion of the adult population who have no formal qualifications there is a:

• 0.5% increase in income deprivation

• 2.2% increase in unemployment

• 1.1% increase in reception age obesity

And a reduction in the average HLE of 8 months

Situation/Prospects

Poor educational achievement is one of the strongest predictors of low Healthy Life ExpectancyA bad educational start in life fuels a trajectory of reduced educational attainment and reduced prospects later on

Higher proportions of the population who have no formal qualifications are also strongly correlated with high percentages of the following:

• Smoking Prevalence• Poor diet (low levels of

consuming 5 portions of fruit/veg per day)

• Physically inactive

Other Associations

Population data strongly suggests that in certain areas there is a cycle of poor educational attainment and the associated consequences being repeated generation after generation. On average, recovering a bad educational start appears almost insurmountable.

For every percentage point increase in the proportion of physically inactive adults there is a:

• 1.1% increase in adult obesity

• 1.2% increase in musculo-skeletal conditions

• 0.4% increase in Strokes

For every percentage point decrease in the proportion of the population who eat 5 portions of fruit/veg per day there is a

• 0.89% increase in obesity year 6

• 0.94% increase adult obesity

• 0.61% decrease in the proportion of physically inactive adults

5 a day Fruit and Veg Physical Activity

For every percentage point increase in the proportion of the adult population who are obese there is:

• 0.4% increase in the proportion of people with no formal qualifications

• 0.5% increase in the proportion of economically inactive

And a reduction in the average HLE of 9 months

Situation/Prospects

Poor health behaviours is one of the strongest predictors of low Healthy Life ExpectancyAgain there is evidence that a poor start in health behaviours

is difficult to correct

Higher proportions of the population who are obese are associated with high proportions of the following factors:

• Smoking Prevalence• Income deprivation• Teenage pregnancy• Lone Parents

Other Associations

Population data strongly suggests that in certain areas there is a cycle of poor health and wellbeing behaviours and the associated consequences being repeated generation after generation.

Strong Correlation between HLE and Emergency Admissions

The scatterplot and regression line (left) shows the relationship between healthy life expectancy and the standardised emergency admissions ratio (SAR). The plotted data are local authorities in England.

There is a very strong correlation between HLE and the standardised emergency admissions ratio, Spearman Rank Correlation Coefficient =-0.71 with a P value of 0.000.

Therefore a very strong, statistically significant correlation with less than a 1 in 10,000 chance of being a random or fluke finding.

This relationship shows that higher HLE figures are associated with lower emergency admissions.

The slope of the correlation indicates that with each extra year of HLE there is a reduction of 3.9% in emergency admissions.

Healthy Life Expectancy Correlation with Emergency Admissions

5,540,121

9,873,255

7,023,045

15,464,712

Million

2Million

4Million

6Million

8Million

10Million

12Million

14Million

16Million

18Million

Dudley Walsall Wolverhampton Sandwell & WB

HLE Burden of Emergency Admissions HLE Burden of Emergency Admissions Costs

These graphs show the extra burden of emergency admissions due to the lower HLE figures across the STP compared to the national average.

Across the STP this equates to a HLE deficit burden of

15,792Emergency Admissions

£37.9mEmergency Admissions Costs

Healthy Life Expectancy Deficit in comparison to the National Average calculated in Emergency Admissions

-1.41

-1.01

-0.29 -0.31

-1.60

-1.40

-1.20

-1.00

-0.80

-0.60

-0.40

-0.20

0.00


Red

uct

ion

in H

LE Y

ear

s

5 Year Forecasts for HLE Across the STP

2,329,800

1,646,235

395,263

858,756

-

500,000

1,000,000

1,500,000

2,000,000

2,500,000


Using the trends and coefficients for the predictor variables a forecast over the next 5 years shows further reduction in Healthy Life Expectancy across the STP.

Dudley and Walsall are predicted to have the greatest decrease in HLE.

Across the STP, these decreases are likely to result in a total increase of

2,179 Emergency Admissions

£5.23m Emergency Admissions Costs

Increase in Emergency Admissions Costs

• Creates an understandable compelling narrative that describes the need for change

• Identifies the opportunities for improvement

• Relates the PHM analysis to meaningful agendas for different organisations

• Improving Health and Wellbeing – Health & Wellbeing Boards

• Emergency pressures - Impact on acute providers

• But what are the actionable insights?• Great analysis is only part of the process

• What retraining is needed for staff to be able to take this forward?• Workforce and technology should go hand-in-hand

What this enables us to do

Why we might not want PHM?

“Never let the truth get in the way of a good story.” – Mark Twain,

“If we have data, let’s look at data. If all we have are opinions, let’s go with mine.”

– Jim Barksdale, former Netscape CEO

“It may be hard for an egg to turn into a bird: it would be a jolly sight harder for it to learn to fly while remaining an egg. We are like eggs at present. And you cannot go on indefinitely being just an ordinary, decent egg. We must be hatched or go bad.”

– C.S. Lewis,

http://en.wikipedia.org/wiki/Jim_Barksdale



A more optimistic perspective

“Things get done only if the data we gather can inform and inspire those in a position to make [a] difference.”

– Mike Schmoker, school administrator, english teacher, football coach, author.

“No individual can win a game by himself.”

– Pele,

http://mikeschmoker.com/

http://mikeschmoker.com/



Break



Leading from the middlethe art of influence and connection

Belinda Weir

An exercise in influencing.

Ugli Orange

Leading from the Middle

• Leading when you’re not ‘in charge’

• Using influence and relationships to enable change

• Connecting laterally and hierarchically

• Networking

• Stepping up to leadership

A suggestion about Influence

• Influence ∫ Expertise x Relationships

• Expertise:

o PHM

o How PHM benefits those you’re seeking to influence to change

• Relationships:

o Based on trust, openness, honesty

o Built on your understanding of ‘their’ needs

• You have to be connected

A definition: ‘strategic’ influencing?

• Developing a pro-active strategy to inform your influencing behaviours in order

to make them

o more targeted

o more collaborative

o more effective

The organisation chart

The real organisation chart

What do we mean by ‘influencing’?

◼Getting others to do something willingly without the use of formal power

◼Actions which seek to have someone else modify their behaviour, feelings, thoughts, ideas, attitudes, beliefs…

◼Things we do or don’t do, the way we are or are not, that somehow have an effect on the way another person behaves, feels, thinks, has ideas, attitudes, beliefs…

A continuum of influencing styles?

Passive Assertive Aggressive

You matter more than me (and what you want

matters more than what I want)

I matter and you matter (what we both want matters to me) I matter more than you

(and what I want matters more than

what you want)

Passive Aggressive

Assertive

Responsive

I have less control over my reaction to the situation

Reactive

I choose how I want to act in response to the situation

Responsive

Reactive

Assertive

Passive Aggressive

Expressing opinions

Drawing out

Active listening

Stating needs

Applying pressure

Building relationships

PushPull

Push Styles: raising my status, lowering yours

• Statements of fact

• Statements of opinion

• Demands for agreement

• Demands for commitment

• Statements about objectives

Pull Styles: raising your status, lowering mine

• Asking about values and principles

• Questions about objectives

• Probing for feelings and perceptions

• Asking for examples

• Listening and following up

In STP groups consider, in developing and implementing your PHM approach:

• When are push styles most effective? And least?

• What about pull styles?

• Are there any you rarely/never use?

• Actions for you in developing your influencing strategy?



Lunch



Three perspectives on PHM in practice

Dr Karen Chumbley, Wes Baker and Valerie de Souza

Population Health Management in End of Life Care

Dr Karen Chumbley Clinical Director and Deputy CEO of St Helena

@kchums

[email protected]

50

Who is my patient ?

As hospices are we providers or are we leaders?

51

© 2019 St Helena Hospice and Oxford Centre for Triple Vaslue

What is population health management?• 1. Define population

• 2. Clarify what is important for that population

• 3. Measure current achievement

• 4. Create a case for change – examining spend against outcome

• 5. Create a network

• 6. Engage patients

• 7. Define a budget

• 8. Delegate authority to the network

• 9. Create change

52

Building Blocks

53

My Care Choices

Alliance End of Life Board

Data with early outcomes

Primary Care

Enhanced service

Locality wide patient

identification

Shared End of Life Strategy

Identified population

54

What is population health management?

1. Define population

2. Clarify what is important for that population


Value FrameworkOutcomes that matter at the end of life

1. To identify and recognise people in the last 12 months of life

2. To inform people thought to be within the last 12 months of life and their families of the likelihood of death within the next 12 months sensitively and honestly

3. To elicit and record people’s preferences for care during the last 12 months of life

4. To respect people’s preferences for care during the last 12 months of their life

5. To ensure people’s preferences for care are accessible to all parts of the health and social care system/end-of-life-care system

6. To treat people at end of life as individuals, with dignity, compassion and empathy

7. To control pain and manage symptoms for people during the last 12 months of life

8. To minimise inappropriate, unnecessary and futile medical intervention during the last 12 months of people’s life

9. To ensure that people at end of life have equitable access to flexible 24/7 end-of-life care services irrespective of the place of care or the organisation/s providing care

10. To provide support to the families and other carers during and after their loved one’s end of life55

56




3. Measure current achievement


To identify and recognise people

in the last 12 months of life

To elicit and record people’s preferences for care during the

last 12 months of life

dignity, compassion and

empathy and carer support

To respect people’s

preferences for care during the

last 12 months of their life

My Care Choices Data

My Care Choices Preferred Place Data

Achievement of Preferred place

To control pain and manage symptomsTo minimise

inappropriate medical

intervention

Hospital Admission data

Anticipatory Prescribing levels

Bereavement survey57

58





4. Create a case for change – examining spend against outcome

Atlas of Value

59


There is a correlation between MCCR use and spend in hospital (p=0.07)

60

PracticesAve

rage

sp

end

per

pat

ien

t in

last

yea

r o

f lif

e


We can improve outcomes

People registered with high MCCR user practices have a 70% chance of dying at home. Others have a 50% chance (p=0.03)

By supporting practices/ PCNs to increase meaningful MCCR use, we can improve outcomes

Note: User % = % of people who died on MCCR

61

High user >5% Medium user (3-5%) Low user (<3%)

In hospital Out of Hospital In hospital Out of Hospital In hospital Out of Hospital

Place of death

62






5. Create a network

63






5. Create a network

6. Engage patients

64






5. Create a network

6. Engage patients

7. Define a budget

65






5. Create a network

6. Engage patients

7. Define a budget

8. Delegate authority to the network

9. Create change

The So What

66https://youtu.be/oy0HobXbM2I

https://youtu.be/oy0HobXbM2I

67

Population Health

Wes Baker

Pathway Improvement Methodology

4

21

Reference cost

5

RightCare Metrics

Produce a list of specialities

Short list

Model Hosptial Data

Acute Utilisation

3

Making the case for Integration

Life Expectancies in Liverpool and Sefton Place

Population Health

Management:

approach and reflectionsValerie de Souza

two local authorities

three ccgs

four provider trusts

historically close working relationships across the patch

Strong strategic support from across organisations

Existing culture of partnership working

Significant interest in PHM

Major system changes

Reducing resources with continuing emphasis on performance

No ‘space’ to work differently

The issue: high admission rate for young people with suicidal

ideation in Coventry and Warwickshire

What have we done already as a system to address this?

-Strategic ‘Children in Crisis’ group established, alongside

operational group to manage admissions

-Initial analysis identified broad demographic and risk factors for

admission

Further work needed:

-Geographical mapping of patient cohort

-Patient journey and contact with services

-How to build and support evidence-based service

Wider PHM outputs and reflections

development of analyst network

strategic leadership from STP population health and prevention workstream

licence to drive public health agenda around targeting and use of evidence

messy to embed into a system in flux

high expectation to result in savings



Break



Rolling out PHM across your STP/ICS

Margaret Mulley

Is your STP/ICS ready to embrace PHM?

C = D x x F > RV

Change Equation Elements

D = Dissatisfaction with how things are now

V = Vision of what is possible

F = First concrete steps that can be taken towards the vision

Assess your STP/ICS Change Equation

•Assess your change equation – as an STP/ICS and for each of the providers you represent.

•What resistance to change could you expect in rolling our PHM?

•How would you assess your change equation using a 0 – 10 scale?




•Brainstorm actions you could take within your STP/ICS that could improve your change equation.

Summary of Your Equations

0

1

2

3

4

5

6

7

8

BC & WB

Derby

Bsol

C&W

Notts

HBW

Change Equation by STP/ICS

Dissatisfaction Vision First Step

Dissatisfaction: Generally

Highest

Vision: Generally Lowest

Report Back - Your Change Equation

•What resistance to change could you expect in rolling our PHM?

•How did you assess your change equation using a 0 – 10 scale?




•Share at least 2 actions you could take within your STP/ICS that could improve your change equation.

8 Thoughts for Your Implementation Plan

1. Understand the process – learn by doing & encouraging others to participate

2. Lead through co-creation

3. Lead by example

4. Practice empathy

5. Talk about the quantitative statistics and metrics and the human experience – stories usually trump data

6. Reduce fear of failure – that will lower resistance

7. Use user-centric KPIs and use them across silos

8. Make PHM tangible – stop talking about it and do it and make what you do visible

We need to create networks alongside hierarchies…

Social Care

Primary Care Network

Hospital

Hierarchies and

population-centred

networks

Community of Value

BetterValueHealthcare

A SYSTEM is a set of activities with a common set of objectives and outcomes; and an annual report. Systems can focus on symptoms, conditions or subgroups of the population(delivered as a service the configuration of which may vary from one population to another )

A NETWORK is a set of individuals and organisations that deliver the system’s objectives(a team is a set of individuals or departments within one organisation)

A PATHWAY is the route patients usually follow through the network

Introduce new language

It is easier to seek forgiveness than permission

never ask a question unless you know the answer

keep your boss happy in three days a week

just imagine you are dealing with troubled families and institutionalized people

BetterValueHealthcare

Work like an ant colony; Neither markets

nor bureaucracies can solve the

challenges of complexity



Looking ahead to tomorrow

Peter Spilsbury

Evening session



Day 2: Welcome and Introductions

Fraser Battye

‘Technical’ ‘Relational’

Where the

real value

lies:

move

from

analysis

to action

YesterdayToday

09:30-11:15 Population definition and insight: Tell the story of your population

11:15-11:30 Break

11:30-13:00 Technical masterclasses and expert advice:

1.Outcomes that matter for populations and individuals

2.Practical tools to understand the needs and preferences of the

population you are serving

3.Demystifying PHM’s analytical techniques: analysis for non-analysts

Teams split themselves to ensure topic coverage

13:00-13:45 Lunch

13:45-14:45 Team time

14:45 – 15:00 Break

15:00 – 16:00 Applying what you’ve learnt: next steps and commitment

16:00-16:15 Next steps and close

We will also ask what more you need from the Faculty experts



Population definition and insight: Tell the story of

your populationTim Wilson, Muir Gray and Erica Ison

•Break-out to 4 rooms – 2 STPs per room

•Each STP takes it in turns to be the ‘school of fish’

Groupings

A. BC&WB and Derby (Alysia)

B. CW and Shrop/TW (Simon)

C. Nottingham and Bsol (Erica)

D. HW and Staffs (Karen)

User-Experience Fishbowl

PHM FacultyObserversChair

•‘School of fish’ to have a conversation about their population subgroup using the prompts

•Observers and Faculty to listen, observe non-verbal exchanges and formulate questions

•Observers and Faculty to ask questions; ‘school of fish’ to respond

•Observers and Faculty to make suggestions for the STP to:

• Ask for coaching in a defined area

• Offer coaching to others

User-experience Fishbowl

PHM FacultyObserversChair

In the context of your project please discuss these prompts – either known as you’ve completed this action or your planned approach

•How you identified them

•How many people there are in this group

•The resources being used with this group

•Any inequities (e.g. do people from more deprived areas have different access to services than those from less deprived areas?)

•Any variation – is it warranted or unwarranted – explain why

•Any inequalities in outcomes and possible causes (including inequity)

•Any other insights gained – perhaps from engaging directly with people from your sub-group.

Prompts

Coaching

Requests for coaching

Who to approach for

coaching

User-Experience Fishbowl Rooms

Coventry and

Warwickshire

&

Shropshire, Telford

and Wrekin

Simon, Abe, Al

and Steven

Platform – Level 1

Black Country and

West Birmingham

&

Derbyshire

Alysia, Muir and

Fraser


Nottingham and

Nottinghamshire

&

Birmingham and

Solihull

Erica, David and

Mohammed

Room 495 – Level

4

Herefordshire and

Worcestershire

&

Staffordshire and

Stoke on Trent

Karen, Tim,

Margaret and

Peter

Room 496 – Level

4



Break



Technical masterclasses

Technical Masterclass Rooms

Defining and measuring

outcomes that matter for

populations and

individuals

Tim Wilson and Erica Ison


Practical tools and tips to

help understand the

needs and preferences of

the population you are

serving

Margaret Mulley and Al

Mulley

Room 496– Level 4

Demystifying PHM’s

analytical techniques:

analysis for non-analysts

Mohammed Mohammed,

Steven Wyatt and Muir

Gray

Room 495– Level 4



Demystifying PHM’s analytical techniques:

analysis for non-analysts

We will provide an outline of three analytical methods that are commonly referenced in the PHM literature;

• population segmentation

• risk prediction / risk stratification

• impactability

But before we start we’d like to know if you have any questions / queries about analytical techniques for PHM that you would like us to address?

Session outline

Population segmentation

Treat everyone as a

unique individual

design

communications,

interventions and

services on a case by

case basis

Treat everyone the

same

one size fits all

more tailored / personalised

simpler / less complexity

Segment the

population and assign

each individual to a

group / stereotype

design

communications,

interventions and

services for each

segment

Population segmentation is the process of dividing the population base into distinct and internally homogeneous groups in order to

develop differentiated strategies according to their characteristics.

Whilst there are some principles to guide the design of a segmentation approach;

e.g.

• all members of a segment are similar

• each segment is different to all other segments

• everyone should belong to one and only one segment

• limit the number of segments

• segments are static; people can move between segments over time

• segments need unequivocal definitions

The true value of a segmentation approach can only be assessed in its utility for a given application.

People / patients / service users are the most common subjects of segmentation methods, but the can also be applied to;

staff members

geographical entities

organisational units or sub-units

medical images

plants, cars, films, etc etc…..

Common types of population segmentation

Who are the population: by sex, age, life-stage,

income, location?Demographics

What do they do: how much, when, where, what are

the triggers?Behaviour

What do they think: needs, feelings, beliefs, values?Attitudes

Burden of disease: clinical conditions, wellness,

illness, multi-morbidity, risk of adverse event, current /

future healthcare costsHealth status

• Judgemental splits

• Prescribed binning

• Decision tress

• Unsupervised learning (e.g. cluster analysis)

In each case, a key step is to name and describe each segment.

Approaches to population segmentation;

• Geodemographic classifications systems• Mosaic (Experian)

• P2 - People and places (Beacon Dodsworth)

• Acorn (CACI)

• Area classification (ONS)

• Health groups• Bridges to health

• Joynt (Segmenting high-cost Medicare patients into potentially actionable cohorts)

• Adjusted clinical groups (ACGs)

•Risk stratification• PARR / PARR+

• QRisk

• Electronic frailty index (eFI)

• National Early Warning Score (NEWS)

• Glasgow admission prediction score (GAPS)

Some well-known segmentation tools

If you’re considering commissioning / buying a segmentation method, make sure its;

• Fit for you specific purpose(s)

• Transparent – no black boxes

• Appropriately priced / licensed

• Compares favourably with current / potential in-house developments

Questions & discussion

Risk prediction

• People experience adverse and costly health events;• a stroke / acute myocardial infarction

• a fall >> hip or forearm fracture

• an unplanned hospital admission

• death

•If we could predict these events the we could;• set health insurance premiums at appropriate levels

• allocated healthcare funding / set capitated budgets / at an appropriate level

•If we could predict these events and intervene to reduce the risk of the event then we could;• reduce the frequency of adverse events

• improve the quality of people’s lives

• reduce (net) healthcare costs

Why predict risk?

1 Gather (or access existing) patient-level data which contains information about;

• the presence / absence of the adverse event of interest

• other information which might predict the likelihood of the event occurring

2 Partition the data into a training dataset(s), and a test and validation dataset(s)

3 Use the training dataset(s) to build a statistical model to postdict* adverse events using an established statistical technique (usually logistic regression, but other machine learning methods are increasingly being used)

4 Use the test and validate dataset(s) to assess the accuracy of the model on data that was not used to construct it

5 Deploy the model to predict new adverse events ahead of time

* Postdict = the estimate the likelihood of a historical event

Approaches to risk prediction

•Accuracy • What proportion of cases were correctly classified?

•Positive predictive accuracy (precision)•Of those cases that the model predict will experience the adverse event, what proportion go on to experience the adverse event?

•Recall (sensitivity)•Of those that experienced the adverse event, what proportion did the model predict?

•Specificity •Of those cases that the model predicts will not experience the event, how many do not go on to experience the adverse event?

•Area under the receiver operating characteristic curve (AUC)•The probability that the model will assign a higher risk to a random positive case than to a random negative case?

Common measures of predictive accuracy (for binary outcomes)

Y N

Y 205 191

N 346 1923

reality

mo

de

l

Y N

Y T F

N F T

Y N

Y TP FP

N FN TN

Predictive risk stratification model: a randomised stepped-wedge trial in primary care (PRISMATIC)

•Background: With a higher proportion of older people in the UK population, new approaches are needed to reduce emergency hospital admissions, thereby shifting care delivery out of hospital when possible and safe.

•Study aim: To evaluate the introduction of predictive risk stratification in primary care.

•Objectives: To (1) measure the effects on service usage, particularly emergency admissions to hospital; (2) assess the effects of the Predictive Risk Stratification Model (PRISM) on quality of life and satisfaction; (3) assess the technical performance of PRISM; (4) estimate the costs of PRISM implementation and its effects; and (5) describe the processes of change associated with PRISM.

125

•Design: Randomised stepped-wedge trial with economic and qualitative components.

•Setting: Abertawe Bro Morgannwg University Health Board, south Wales.

•Participants: Patients registered with 32 participating general practices.

•Intervention: PRISM software, which stratifies patients into four (emergency admission) risk groups; practice-based training; and clinical support.

•Main outcome measures: Primary outcome – emergency hospital admissions. Secondary outcomes – emergency department (ED) and outpatient attendances, general practitioner (GP) activity, time in hospital, quality of life, satisfaction and costs.

•Data sources: Routine anonymised linked health service use data, self-completed questionnaires and staff focus groups and interviews.

126

•Results: Across 230,099 participants, PRISM implementation led to increased emergency admissions to hospital [ΔL = 0.011, 95% confidence interval (CI) 0.010 to 0.013], ED attendances (ΔL = 0.030, 95% CI 0.028 to 0.032), GP event-days (ΔL = 0.011, 95% CI 0.007 to 0.014), outpatient visits (ΔL = 0.055, 95% CI 0.051 to 0.058) and time spent in hospital (ΔL = 0.029, 95% CI 0.026 to 0.031). Quality-of-life scores related to mental health were similar between phases (Δ = –0.720, 95% CI –1.469 to 0.030); physical health scores improved in the intervention phase (Δ = 1.465, 95% CI 0.774 to 2.157); and satisfaction levels were lower (Δ = –0.074, 95% CI – 0.133 to –0.015).

•PRISM implementation cost £0.12 per patient per year and costs of health-care use per patient were higher in the intervention phase (Δ = £76, 95% CI £46 to £106). There was no evidence of any significant difference in deaths between phases (9.58 per 1000 patients per year in the control phase and 9.25 per 1000 patients per year in the intervention phase).

•PRISM showed good general technical performance, comparable with existing risk prediction tools (c-statistic of 0.749). Qualitative data showed low use by GPs and practice staff, although they all reported using PRISM to generate lists of patients to target for prioritised care to meet Quality and Outcomes Framework (QOF) targets.

127

•Limitations: In Wales during the study period, QOF targets were introduced into general practice to encourage targeting care to those at highest risk of emergency admission to hospital. Within this dynamic context, we therefore evaluated the combined effects of PRISM and this contemporaneous policy initiative.

•Conclusions: Introduction of PRISM increased emergency episodes, hospitalisation and costs across, and within, risk levels without clear evidence of benefits to patients.

128

•Given the uncertainties, consider design stage evaluation before taking the final decision to implement.

•If it doesn’t stack up in theory, it’s unlikely to in practice.

129

A worked example

130

From a practice of 5,000, a

risk tool identifies 100

individuals (top 2%) having

the highest risk of unplanned

admission in the next 12

months

36 would have

experienced an

emergency admission

in the next 12 months

PPV = 0.36

For every eighteen

people treated, one

emergency admission

is avoided

NNT = 18

2 admissions

avoided

Let’s assume

£2000 per

admission

How much must

your intervention

cost per person

to save money?

In general

•A is the average cost of an adverse event;

•PPV is the positive predictive value of a tool which aims to identify patients who will have an adverse event in a given period;

•NNT is the number of people that need to receive the intervention in order to avoid one adverse event; and

•I is the unit cost of an intervention to prevent an adverse event which is delivered to those identified by the predictive risk tool then,

• I < A.PPV/NNT for the intervention to save money.

131


Impactibility

• Many risk prediction / risk stratification projects, which attempted to identify and avoid unplanned hospital admissions were shown to have no effect (or worse).

• Initial efforts focused on improved the predictive power of the models.

• More recently, the focus moved to selection of high risk cases for intervention.

• These approaches have become known as impactability modelling.

•Early days – little evidence to indicate whether these approaches are successful or not.

Note: Still very little attention payed to improving the efficacy of the intervention

The origins of impactability

A worked example

135






months

36 would have

experienced an

emergency admission


PPV = 0.36

For every eighteen

people treated, one

emergency admission

is avoided

NNT = 18

Incorporating impactability






months

27 would have

experienced an

emergency admission


PPV = 0.36

For every 13.5 people

treated in our subset,

one emergency

admission is avoided

NNT = 13.5

Select an impactible subset

of say 75, that you think will

respond well to the

intervention

Approaches to impactibility

• Giving Priority to Patients with Conditions That Make Them Amenable to Preventive Care

• Excluding Patients Who Are Unlikely to Respond to Preventive Care

• Tailoring Preventive Care to the Individual Patient

Taken from: “Impactibility Models”: Identifying the Subgroup of High‐Risk Patients Most Amenable to Hospital‐Avoidance Programs, G Lewis, 16 June 2010 https://doi.org/10.1111/j.1468-0009.2010.00597.x

https://doi.org/10.1111/j.1468-0009.2010.00597.x




Learning from Your PopulationsMaking Choices Matter for Health & Wellbeing

Al Mulley, Margaret Mulley and Abeda Mulla

Learning from Your Populations: Setting the Stage

• What methods have you used?

• Who did you speak to?

• What worked well?

• What did not work well? Why?

• Were there any surprising findings?

• Are there common themes, challenges?

• What ‘technical’ questions should we address?

Overview of Research Approaches for Populations

•Approaches to new populations•Ethnography (e.g., ‘follow-me-home’ research)•Narrative •In-dept individual interviews and focus groups•Case studies

•Synthesis of Research•Creation of persona(s)•Patient Journey mapping –( expanded pathway adding more touchpoints and emotions)

Engagement methods for ongoing user/patient engagement

•Expanding time with patients who are connected to a clinician or care team can make them feel known in a trusting relationship, improving bidirectional learning, diagnostic accuracy, compliance and care co-management

•Relational team-based care can learn from patients by understanding life circumstances and preferences – to improve the quality of prevention, diagnostic and treatment decisions– increasing personal and population value

•Tools to assess patient engagement – CollaboRATE

•Changing consultations•Change the way you begin a consultation by asking, ‘What are you going through? What can I do for you today?’ Then listen actively, until the person stops speaking, for up to two minutes.

•When persons present with nonspecific symptoms, begin by asking, ‘What do you think may be causing this?’

•Identify five persons for whom you want to improve the value of services. Invite them to help you better understand what matters most to them.

•Shared decision making -> Choice Talk

•Motivational interviewing -> Change Talk

•Social Prescribing -> Community-oriented asset-mapping and care

Learning from Variation for PHM: Conceptual and Operational Barriers

Learn from

Variation

Deliver

What is

Valued

System

Leadership

at all Levels

Measure

What

Matters

Deliver with

Teams

Organise

for

Innovation

Learning from Variation for PHM: Conceptual and Operational Barriers

Learn from

Variation

Deliver

What is

Valued

System

Leadership

at all Levels

Measure

What

Matters

Deliver with

Teams

Organise

for

Innovation

Context

Sensitivity

Complexity

Competencies

1

23

http://www.goinvo.com

Learning the Most from Vulnerable Populations How can we avoid substituting high risk and cost health care for services in

the community that would better meet the needs of those we serve?

Co-Designing with the

Vulnerable for the Vulnerable

Preferences Matter: Measuring Decision Quality for PHM

Uncertainty about Outcomes

Dis

ag

ree

me

nt

ab

ou

t V

alu

e

High

High

Low

Low

Control &

Planning

Chaos

Complexity

Evidence-Based

Respecting Complexity at the Level of the System and the Individual

The Need for Simple Rules:

1. Meeting needs and wants; no less but no more

2. No decisions made with avoidable ignorance

3. Showing manifest respect for the individual

Modified from Stacey, Plsek, IOM, 2001

Context-Sensitivity

High

High

Low

Low

Mea

sure

men

t-Su

bje

ctiv

ity

Measuring What Matters for PHM Making People’s Choices Matter

Control &

Planning

Personal Value

Level of competence

Dif

ficu

lty

of

the

task

High

HighLow

Low

Inefficient

Ineffective

Complementary Competencies for PHM: Technical and Relational

Relational Competence

Re

lati

on

alD

iffi

cult

y

High

HighLow

Low

Inefficient

Ineffective


Level of competence

Dif

ficu

lty

of

the

task

High

HighLow

Low

Inefficient

Ineffective

Measuring Teamwork as Relational Coordination (Gittel)• Shared Goals• Shared Knowledge• Mutual Respect• Communication that is…

• Frequent• Timely• Problem- solving• Accurate

Measuring Teamwork as Patient Experience



Understanding Patients’ Life Circumstances

as Context for Decision Making

How can we avoid substituting high risk and cost health care for services in


‘I didn’t need this new hip.

All I needed was a

bannister so I could get

down to see the postman!’

‘You forgot to ask about

the dog. It died. That’s

why she doesn’t get out

or take care of herself as

much.’



Learning the Most from Vulnerable Populations How can we avoid substituting high risk and cost health care for services in


Co-Designing with the

Vulnerable for the Vulnerable




Outcomes that matter

Tim Wilson and Erica Ison

Warning!

•In this session, we will be taking you through the interactive exercises quickly

•This is deliberate: the goal is for you to be able to work with your team members and others in your STP to repeat and validate the outputs from these exercises

•The PHM Faculty are available to help review and provide support as you do this; speak to your account manager about it

155

Outline of session

1. Thinking about outcomes2. Defining outcomes3. Verifying outcomes

156

1. Thinking about outcomes

157

What might be the underpinning principles of your ICS?

“The NHS belongs to the people.”1. Providing a comprehensive service, available

to all

2. Access to services is based on clinical need, not an individual’s ability to pay

3. Aspires to the highest standards of excellence and professionalism

4. Put patients at the heart of everything it does

5. Working across organisational boundaries and in partnership with other organisations in the interest of patients, local communities and the wider population

6. Committed to providing best value for taxpayers’ money and the most effective, fair and sustainable use of finite resources

7. Accountable to the public, communities and patients that it serves

NHS Constitution

“In an integrated care system, NHS organisations, in partnership with local councils and others, take collective responsibility for managing resources, delivering NHS standards, and improving the health of the population they serve.”

NHS England

Apologies to local government and non-NHS

colleagues



to all







NHS Constitution


NHS England


colleagues

Health

•Turn to your neighbour and define what health means: 2 minutes

160

Health

“Health is a state of complete physical, mental and social well-being and not merely the absence of disease or infirmity.”

WHO

161

Value

•Turn to your neighbour and define what value means: 2 minutes

162

Value is subjective

•Its definition depends upon what you value

•Its meaning becomes real when you measure it

Therefore, a definition of value should be rooted in the core

principles of your health and care system.

It should not be copied from others, although frameworks and

guides can be helpful.

164

OutcomeResource

165

OutcomeResource

Identify resources that are

important to you

166

OutcomeResource

Identify the resources that are

important to you

✓ Workforce✓ Leadership time✓ Clinical time✓ Capacity to change✓ Carbon✓ Money

167

OutcomeResource

bit.ly/2qwslVr

Rank the measures

•Drag them up and down the screen

•Put the most important measure at the top

•Although you will respond as individuals, feel free to discuss your response with others at your table

168

Rank the measures

•Feedback

169

See, for instance: Demain, 2015; Cribb, Entwistle & Christmas 2015, 16; Fitzpatrick et al 2016,17



to all







NHS Constitution


NHS England


colleagues

173

OutcomeResource

Whose outcome?

Identify the stakeholders who

will want and need the

outcomes that matter to them

to be addressed

174

OutcomeResource

Whose outcome?




to be addressed✓ Patients | People receiving care and/or services✓ Population with a need✓ Communities✓ Providers of healthcare (NHS and private sector)✓ Partners providing care and related services (local government, third sector)✓ Commissioners✓ Taxpayers ✓ Civil society

2. Defining outcomes

175

© 2019 Oxford Centre for Triple Value Healthcare

What is the overall aim for your population group? • Identify your overall aim: 2

minutes

• Hear about the aim of another STP and discuss the similarities and differences: 2 minutes

176

Do you need to subdivide your population group into subgroups?

177

All people aged >18 years with diabetes

Suggestions?

Do you need to subdivide your population group into subgroups?

178

All people aged >18 years with

diabetes

People at high risk of type 2

diabetes

People with type 1 diabetes


Subdivide your population group: 3 minutes

What outcomes matter for your population group and subgroups?

179

All people aged >18 years with

diabetes

People at high risk of type 2

diabetes



Suggestions?

What outcomes matter for each subgroup?

180


People at high risk of type 2 diabetes

Feel healthy and prevent diabetes


Feel healthy, confident and

minimise complications




Develop outcomes for your population subgroups: 3 minutes

How will you measure these?

181










Suggestions?

How will you measure these?

182




QoL score, rate of increase in diabetes




QoL score, diabetes distress score,

complication rates





complication rates

Develop measures for your population subgroups: 3 minutes

Anything missing?

183




QoL score, rate of increase in diabetes





complication rates





complication rates

Suggestions?

This is when you can start to think about the interventions you want to put in place

184

Objective: Achieve 3 treatment targets – HbA1C, cholesterol and blood pressure.

Criterion: % people achieving 3 treatment targets

Objective: Minimise adverse events.

Criterion: % people with diabetic keto-acidosis (DKA), hyperglycaemic hyperosmolar non-ketotic

coma (HONKC), diabetic hypoglycaemia (hypo’), emergency admissions

Objective: support self-care.

Criterion: % people confident to manage own condition

Objective: Address mental health and wellbeing

Criterion: % score on mental health questionnaire

Objective: Successfully complete a diabetes prevention programme (DPP)

Criterion: % people with maintenance of significant weight loss

To these objectives, we need to add four others

185

Objective: HbA1C, cholesterol and blood pressure. Criterion: % people achieving 3 treatment

targets

Objective: Minimise adverse events. Criterion: % people with DKA, HONKC, Hypo’, emergency

admissions

Objective: Support self-care. Criterion: % people confident to manage own condition

Objective: Address mental health and wellbeing. Criterion: % score on mental health questionnaire

Objective: Successfully complete DPP. Criterion: % people with maintenance of significant weight

loss

Objective: Make optimal use of resources. Criterion: Spend against outcomes benchmarks

Objective: Reduce inequity. Criterion: % Difference in outcomes between wards

Objective: Develop and support staff. Criterion: Staff satisfaction scores

Objective: Be accountable. Criterion: Production of an annual value report

3. Verifying outcomes

186

187

OutcomeResource

Whose outcome?




to be addressed✓ Patients | People receiving care and/or services✓ Population with a need✓ Communities✓ Providers of healthcare (NHS and private sector)✓ Partners providing care and related services (local government, third sector)✓ Commissioners✓ Taxpayers ✓ Civil society

Case-study: Stakeholder engagement End-of-life-care outcomes that matter

Method of engagement:

Focus groups

Stakeholders consulted:

1. Group of relatives of people who died plus representatives from third-sector providers/support services

2. Group of staff from frontline care providers: residential care homes, nursing homes, GPs, social services, community care, district nursing

3. End-of-life Care Board: representatives from all agencies providing care and support at end of life

188

Focus group questions/topics for exploration

•Which people should we be including in the population when we consider care at the end of life?

•What outcomes matter most in care at the end of life?

•Identify examples of overuse in the care of people at end of life

•Identify examples of underuse in the care of people at end of life

•Identify examples of inequity in the care of people at end of life

•Identify high/er-value and low/er-value interventions in the care of people at end of life

•Identify potential measures/criteria to monitor the achievement of outcomes

189

Stakeholder engagement

•Who would you engage with to identify the outcomes that matter most to your population and population subgroups? [3 minutes]

•What methods would you use to engage them? [2 minutes]

190

What matters to adults at the end of lifeand their families | other carers?

•To be treated:•With dignity, compassion and empathy•As individuals

•To be heard•For health and social care staff to identify, recognise and acknowledge when people are at the end of life/Not to be given “false hope”

•For the person at end of life, to have personal care needs met (e.g. hygiene, toileting) irrespective of place of care

•For people at the end of life to have equitable access to a flexible, 24/7 end-of-life care service irrespective of the place of care and the organisation/s providing care

•For people at the end of life to be cared for by staff skilled in palliative and end-of-life care to ensure effective and appropriate pain control/symptom management irrespective of the place of care and the organisation providing care

•For people at the end of life and their families/other carers to be cared for by staff skilled in communication, who are aware of and informed about the current health status of the person at end of life

•To reduce/avoid unnecessary and futile medical intervention•For families and other carers, to receive support both during and after their loved one’s end of life, e.g. for people being cared for at home, support for family/other carers overnight and at weekends, knowledge and skills development in how to care for a dying person, spontaneous home visits to check how the dying person is, facilities to stay in hospital when needed, and bereavement counselling

What matters to people receiving/in need of care?

•How would you use the information about the outcomes that matter to your population and population subgroups? [3 minutes]

192

Developing measures/criteria from the outcomes that matter most to people at end of life and their families•Identified existing measures/criteria for care of adults at end of life

•Matched existing measures/criteria to outcomes identified by relatives of adults at end of life and other acknowledged representatives

•Identified gaps in existing measures/criteria

•Identified measures/criteria that could be developed to rectify the gaps

•Identified ways of collecting the information needed to rectify the gaps and develop a dashboard of indicators for end-of-life care

•Producing an ‘Atlas of Value’ with existing indicators enhanced by statistical analyses using existing data to gain deeper insights (Phase 1)

•Planning the parameters of future data linkage and survey development to increase the ‘value’ of the dataset thereby facilitating population health management, in particular increasing value in the care of adults at the end of life

193

Going forward: outcomes that matter

•What would be the key points of insight or learning about outcomes that matter which you would want to introduce across the STP/ICS [3 minutes]?

•How would you transform these insights into action for roll-out across the ICS? [3 minutes]

194



Lunch



Team timeMargaret Mulley



Applying what you’ve learnt

Karen Bradley, Alysia Dyke and Shammas Rahim

15% Solutions

In relation to your PHM project what is your 15% Solution?

A 15% Solution is something you can do right away without needing any more freedom, resources, permission, authority, or control.

Where you have discretion to act right now.

On your own

What is your 15%?

Where do you have discretion and freedom to act?

What can you do without more resources or authority?

In a small group

Share and ask for help refining your 15% Solution.

• Each person to share their 15%

• Ask the sharer clarifying questions and offer advice

As a team collect your 15% solutions and agree when to revisit them.

Resources

Need

Need + Demand

If we do nothing, need and demand will increase by about 20% in the next decade and resources will not

…Resources: •workforce • leadership

bandwidth •carbon•capacity to

change•money

All of these are finite2019 2024 2029

Waste

In the wastepaper basket

can we use less resources and increase productivity?

Can we use less resources and get better outcome through higher quality and safer care thus increasing efficiency

BUT “there is nothing so useless as doing something efficiently, [safely and at high quality] that which should not be done at all”.

Would we get more value if we used the resources on another sub group of the population ?

POINT

OF

OPTIMALITY

BENEFIT

HARM

Resources

BENEFIT -

HARM

Effect

Size

UNDERUSE OVERUSE

transforming healthcare for a sustainable future

CARBON FOOTPRINT

NHS ENGLAND

18 million tonnes CO2 in 2004


1. Malnutrition

2. Deaths and injuries caused by storms and floods. (Flooding can also be followed by outbreaks of diseases, such as

cholera)

3. Water scarcity / contamination (droughts and sudden

floods) – increased burden of diarrhoeal disease.

4. Heatwaves – direct increases in morbidity and mortality; indirect

effects via increases in ground-level ozone, contributing to asthma

attacks.

5. Vector-borne disease – malaria and dengue.

CLIMATE CHANGE THREATENS HEALTH

DIRECTLY…



HIGH CARBON CARE

• Tests repeated because doctors unaware of earlier

results?

• Drugs continued when no longer needed?

• Patients travelling on separate days to separate

teams – for related problems?

• Hi-tech interventions preferred?

• Focus on immediate problems not underlying cause?

• Patient as passive recipient of care



FeedbackFraser Battye



Thank you and safejourney home!

Documents

Midlands PHM Academy · stage 2 attainment • 1.18% decrease in the achievement of 5 GCSEs or more • 0.7% decrease in the attainment 8 scores (the achievement of a pupil across