© Nuffield Trust

Can the voluntary sector help to prevent

hospital admissions?

Theo Georghiou

& the Nuffield Research team

22 June 2015

© Nuffield Trust

Social action to prevent admissions

Cabinet Office Reducing winter pressures fund (£3m).

(also match-funding by local commissioners)

Seven funded organisations

• Age UKs, British Red Cross, Westbank (Exeter), Royal Voluntary

Service.

• Explicit aim to reduce emergency admissions (+other) over

2014/15 winter, using volunteers

• Required to work with Nuffield Trust as independent evaluators

(collect and transfer data as necessary)

© Nuffield Trust

Main types of service

Home from hospital

• Inpatient wards, and A&E

Upstream prevention

• Referrals from GPs, wards, local integrated H&SC teams,

community

Signposting

• Referring to other voluntary or statutory orgs

‘Active’ support

• Transporting, befriending, shopping, meals, …

© Nuffield Trust

Story so far and to come

Since October 2014

• 7,900 people supported (500 to 2,270)

• 470 volunteers recruited (4 to 140)

• 62 staff in place (5 to 12)

Extension to September 2015 (…9,500 people supported?)

Analysis (this autumn):

Matched control evaluation (Cono Ariti, this morning)

Link local voluntary sector admin data to hospital data

© Nuffield Trust

Data from voluntary sector organisations

Personal

identifiers

Info about person

and/or service provided

Mrs

Louise

Smith

F

DOB

13/12/40

…

Day 54 - Referred;

Consent , Assessed

Day 56 - Driven

home, shopping

(3 hr volunteer time)

Day 60 - Visited

(1 hr volunteer time)

…

Might include

Referrals [dates, route..]

Assessments [Recorded needs, plans, wellbeing surveys…]

Services provided [what, dates, volunteer or staff, time spent…]

© Nuffield Trust

Data from voluntary sector organisations

Personal

identifiers

Info about person

and/or service provided Hospital data

Mrs

Louise

Smith

F

DOB

13/12/40

…

Day 54 - Referred;

Consent , Assessed

Day 56 - Driven

home, shopping

(3 hr volunteer time)

Day 60 - Visited

(1 hr volunteer time)

…

…

Day 52 - Emergency admission

(Diagnosis of COPD, … , … )

Day 56 - Discharged home

Day 83 - AE visit, not admitted

….

Might include

Referrals [dates, route..]

Assessments [Recorded needs, plans, wellbeing surveys…]

Services provided [what, dates, volunteer or staff, time spent…]

© Nuffield Trust

Data from voluntary sector organisations

linked to hospital data for evaluation

Info about person and/or

service provided Hospital data

…

Day 52 - Emergency hospital admission; Diagnosis of COPD, … , … ;

Day 54 - Referred to scheme; Consent , Assessed

Day 56 - Discharged home

Day 56 - Driven home, shopping (3 hr volunteer time)

Day 60 - Visited (1 hr volunteer time)

…

Day 83 - AE visit, not admitted

…

Linkage to

to hospital data

via HSCIC

(consent issues)

Analysis data are

pseudonymous

© Nuffield Trust

Varied status of the different schemes

Seven different schemes - mix of situations:

• Well established intervention, advanced data collection (and data

sharing) locally

• New intervention and databases put together from scratch

• Others somewhere in the middle – adapted existing interventions,

and modified data collection with our advice

Some are collecting a lot of data…

© Nuffield Trust

Age UK South Lakelands – assessment data

Health Wellbeing - over last two weeks About your home Hospital stays last 18 months? Little interest or pleasure in doing things Live with someone?

A&E Not Admitted last 18 months? Feeling down, depressed, or hopeless Your accomodation - class

Emergency Treatment at Home last 18 months Trouble falling or staying asleep, or sleeping Type of home

Doc/Nurse last 3 months? Feeling tired or having little energy Type of heating

How many Medicines? Poor appetite or overeating Insulation

Diabetes? Feeling bad about yourself Need repairs?

Controlled by diet/insulin/etc? Trouble concentrating on things Moving around home safely?

Angina? Moving or speaking so slowly that other people Aids and adaptations in home ok?

Spray/Tabs times per week? Thoughts that you would be better off dead or Working smoke detector?

Respiratory? Feeling nervous, anxious or on edge Personal alarm?

Inhaler times per week? Not being able to stop or control worrying Feel safe now?

Stroke? Worrying too much about different things Safe in future?

How many months ago? Trouble relaxing Your money Infect/UTI's Being so restless that it is hard to sit still State pension(s), total £

Number last 18 months? Becoming easily annoyed or irritable Occupational Pensions, total £

Arthritis/Osteoporosis? Feeling afraid as if something awful might happen Pension Credit, £

Falls? Social life Other earnings, £

Fractures? Social visitors - how often? Attendance Allowance

Health impact on daily living? Family contact - how often? DLA mobility

Hot meals number per week? Get out for engagements - how often? DLA care

Weight changing? What transport do you use? PIP mobility

Appetite changing? Have Telephone/Mobile? PIP care

Smoke? Per Day Have internet? ESA amount, £

Drinks? Per Week Use internet? Housing benefit, £

Physical Activities number per week? Confident internet? CT Reduct., £

Current health (Very good to poor) Social changed over last 3 years? Fuel costs, £ per month

Knowledge of Conditions (very confident to not) If care for someone - how impact? Manage now?

Future health management (very confident to not) Lifestyle or culture affects social life? Manage in the future?

Difficulty with Activities? (no diff to impossible) Unplanned costs?

Shortness of breath? (rest to no problems)

Walking aids?

Get up in the night number of times

Statutory care or support?

Lifestyle or culture affect access to health?

© Nuffield Trust

Follow all 7,900 people’s hospital history before, and after:

Data needed – minimum

Two most important things from each area:

Good quality personal identifiers > Data linkage to HES

A start date for service > Reference date

?

?

© Nuffield Trust

Good quality personal identifiers

Illustration of ‘minimum’ necessary (2013 study)

N % of initial N

Initial Cohort 3,946

Dropped from

analysis

No linkage to HES 1,240 31%

Link to HES, but not found in hospital 727 18%

Other - analytical reasons 406 10%

Final analysis cohort 1,573 40%

© Nuffield Trust

Good quality personal identifiers

A start date for service – almost the only data we had…

Illustration of ‘minimum’ necessary (2013 study)

N % of initial N

Initial Cohort 3,946

Dropped from

analysis

No linkage to HES 1,240 31%

Link to HES, but not found in hospital 727 18%

Other - analytical reasons 406 10%

Final analysis cohort 1,573 40%

0.0 1.0 2.0

All Sites (N=1,573)

Site 2 (N=269)

Site 3 (N=156)

Site 4 (N=79)

Site 5 (N=111)

Site 6 (N=364)

Site 7 (N=152)

Site 9 (N=442)

Risk of future emergency admission

High

risk Low

risk

© Nuffield Trust

We’d (all) like to know more

From HES data - client characteristics

• multiple long terms conditions, previous admissions, age,

deprivation, …

But what about the interventions themselves?

• Home from hospital vs community

• Signposting vs ‘active’

• Light vs intensive support

• Volunteer vs staff delivered

• Short vs long term follow up

> Who best to target? And how?

© Nuffield Trust

Final thoughts

• Cabinet office social action study – part of a suite of work on voluntary sector’s impact on health

• Past and current work – it’s possible to use voluntary sector person level data and link to hospital data

• Data quality and completeness - limits what you can do

• Homogeneous interventions (and data), more likely to make nuanced (and useful?) evaluation findings

© Nuffield Trust

www.nuffieldtrust.org.uk

Sign-up for our newsletter www.nuffieldtrust.org.uk/newsletter

Follow us on Twitter http://twitter.com/NuffieldTrust

© Nuffield Trust

Thank You