Reducing emergency admissions:

are we on the right track?

Martin Roland

Professor of Health Services Research

University of Cambridge

What not to do …….. and what to do

• What not to do: five common misconceptions

about emergency admissions

• What to do

Five common misconceptions

• Overestimating the importance of frequent

fliers

• Forgetting about regression to the mean

• Assuming interventions are beneficial

• Ignoring supply induced demand

• Forgetting about random variation

What not to do …….. and what to do

1. Overestimating the importance of

‘frequent fliers’

Overestimating the importance of ‘frequent fliers’

Percentage reduction in admissions in each risk group required to meet

targets for reducing emergency admissions

Target overall

reduction (%):

% reduction required in risk group

Very high risk

(0.5% of

population)

High risk (0.5-

5% of

population)

Moderate risk

(6-20% of

population)

Low risk (80%

of population)

1 10.8 4.0 3.9 2.5

2 21.5 8.1 7.8 5.0

3 32.3 12.1 11.8 7.5

4 43.0 16.2 15.7 10.0

5 53.8 20.2 19.6 12.5

10 107.5 40.4 39.2 25.0

What not to do …….. and what to do

2. Forgetting about regression to the mean

Forgetting about regression to the mean

Years 1 2 3 4 5 6

Roland et al. BMJ 2005; 330: 289

What not to do …….. and what to do

3. Assuming all interventions are beneficial

English Integrated Care Pilots (2009-2011):

Evaluation of case management interventions

English Integrated Care Pilots (2009-2011):

Evaluation of case management interventions

Aims included

• Reduced emergency admissions

• Better co-ordinated care

• Greater patient involvement of patients in decisions about their

care

English Integrated Care Pilots (2009-2011):

Evaluation of case management interventions

• Staff thought care had improved

• Patients said they were less likely to be able to see a doctor of

nurse of their choice and felt less involved in decisions about their

care

• Emergency admissions increased by 9%

• Small net reduction in costs (reduced elective admissions and

outpatient referrals)

Roland et al. International Journal of Integrated Care 2012, 12: 24 July

What not to do …….. and what to do

3. Ignoring supply induced demand

• NHS Direct

• NHS walk-in centres

• ‘New workers’ of many sorts…

It’s much easier to improve quality than reduce cost

% of studies with

a positive

outcome for

health

% of studies with

positive outcome

for patient

experience

% of studies

which showed

reduction in cost

55.4% 45.2% 17.9%

Powell Davies et al Med J Aust 2008; 188 (8): S65-S68

Systematic review of interventions to improve coordination in healthcare

“A bad day”

Forgetting about random variation due to chance

Variation due to chance (more correctly a Poisson

distribution)

Variation in number of referrals or admissions that would

occur if variation was due solely to chance

Expected no of

events

Expected range.

Percentage of time that results would fall outside range

by chance alone:

50% 10% 5%

5 3-6 2-9 1-9

10 8-12 5-15 4-16

25 22-28 17-33 16-35

50 45-54 38-61 37-64

100 93-106 84-116 81-120

200 190-209 177-223 173-228

500 485-515 463-536 457-544

1000 979-1021 948-1052 939-1062

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All practices A&E rates per 1,000 weighted population compared to Greater Cambridge rate, Apr-May 11/12-12/13

All Practices 2011/2012 All Practices 2012/2013 Greater Camb 2012/2013 Series4

Off the Scale

What not to do …….. and what to do

• What not to do: five common misconceptions

about emergency admissions

• What to do

• Don’t assume that reductions in admissions in a high

risk group are due to your intervention - evaluate your

intervention against changes in overall patterns of

admission or using a control group

• Don’t assume there is a correct level of admission or

referral to hospital - clinical audit makes numbers

meaningful and should be used to identify where there

are problems in care

• Don’t assume that fewer admissions or referrals are

necessarily better - doctors with low rates of specialist

use may be a danger to their patients, just as high

referrers may be wasting resources. Use clinical audit

to bring meaning to crude rates of referral or admission

• Be cautious about using data for short time periods or

referrals to single specialties - random fluctuations may

account for much of the apparent variation in provider

performance when numbers are small. Use the table in

the BMJ paper to assess how much variation might be

due to chance

• Remind everyone who will listen that change is usually

slower than people expect (or at least hope for)

• Choose interventions that are evidence based – e.g.

from systematic reviews (Purdy et al 2012)

• However, bear in mind that context is important.

Carefully shaping the way an intervention is introduced

may increase its effectiveness, and don’t forget that

most changes can have unexpected consequences too.

Purdy et al 2012. www.bristol.ac.uk/primaryhealthcare/docs/projects/unplannedadmissions.pdf

What do systematic reviews tell us?

Intervention Effect

Case management Overall no effect except for heart failure

Specialist clinics Overall no effect except for heart failure

Care pathways and guidelines No effect, but limited evidence

Medication review No effect, but limited evidence

Education and self management Weak evidence for heart failure

Exercise and rehabilitation Effective in COPD

Telemedicine Possible effect on heart disease, diabetes,

hypertension and older people

Hospital at home Increased readmissions

Purdy et al 2012.

www.bristol.ac.uk/primaryhealthcare/docs/projects/unplannedadmissions.pdf

Patient recognises a problem

Patient arrives in A&E

GP surgery

Out of hours centre

Patient needs admission

Patient admitted

Patient doesn’t need admission

Availability of appointments

Opening hours

Continuity of care

Triage expertise

Triage expertise

Community support

Transport

‘Too late’

Patient behaviour

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