1. Approaches to case finding:
models and application
Managing referral rates and
reducing admissions

2. Introduction
Outer north east London have implemented two risk based
approaches to case finding in order to reduce hospital admissions
and referrals
• Clinical risk
Population targeting
• Disease risk
Disease analytics

3. Population • Clinical risk targeting
Laura Osborn
Planning and Delivery Project Manager
NHS North East London and the City

4. Outline and aims
Risk stratification
• Identifies those most at risk of emergency admission - top 1% risk
Partnership working
• Between the GP practice, Social services and provider services.
Avoid duplication
• Services, resources and patient contacts
Proactive management
• Long term conditions and social needs
Prevents avoidable hospital admissions
• Robust planned care and patient education in the community

5. Integrated care model of care
Identify
Service User
Case Conference Care Plan
Health Analytics used
to identify top 1% of Fortnightly cluster meetings held.
patients at risk. Attended by core team Team agrees action plan for
Clinical judgement Meetings approximately 45 each patient
used to supplement minutes.
the risk stratification 2-3 new patients plus other
tool. existing patients discussed.
Self Management
Patient is provided
with information on Care Plan Review Care Delivery
what to do in case of
emergency Care plan shared with MDT and Community Matrons undertake an
discussed at next meeting. assessment of the patient .
Onward Referral The MDT team reviews the care Members of the MDT provides
Patient referred to plan and agrees if other measures patient with the necessary care to
supporting services need to be put in place to prevent prevent admission.
in the community the admission.
Liaison officer follows through with
Ongoing Care The team risk rates the patient patient and MDT to ensure service
and agrees a follow-up period. is provided.
Patient kept on the
register for a period
of 6 months for on-
going care.
5

6. The integrated care team
GP
End of Life Mental
Care health
Community
liaison
Matron
officer
Service
Therapies Practice
User Third
Sector
Nurse Social
Worker
(Optional)
District Drug &
Alcohol
Nurse services
Acute care
specialists

7. Risk profiling for integrated care
Use Health Analytics
• Combined Predictive Model
Commissioning tool
• Integrated electronic solution for patient care
information
Multi functional tool
• Integrates care data from any source
• Financial and clinical data

8. Functionality
Segment by :
• Risk score
• Age
• Emergency admissions and attendance
• Cost (primary and secondary)
• Specific long term conditions
Role-based access
Electronic care plan functionality

9. Risk profiling for Integrated Care:
Modelling the clusters
The data from Health analytics enabled us to group the practices into the ‘clusters’
depending on location & number of high risk patients in the cohort.
This also allowed us to work with community providers and social care to begin work
aligning the teams
Number of
Practice List Size patients in HA
top 1%
Practice 1 7798 167
Practice 2 7425 122
Cluster 1
Practice 3 3246 54
Practice 4 3686 61
Practice 5 5103 97
Practice 5 5200 82
Practice 6 4348 47
Practice 7 12498 204
Practice 8 10378 152
Cluster 2
Practice 9 4724 46
Practice 10 6394 39
Practice 11 4222 38
Practice 12 3082 56
Practice 13 2748 26

10. Risk profiling for integrated care:
Selecting the cohort
Identify top 1%
risk segment – Modelling
4239 in Redbridge indicates that
90% of these will
have one or
more LTC
Reviewed by
Integrated Care
team – accepted
if suitable
These people accepted into Integrated Care will then be discussed
by the team and a care plan will be developed across both health
and social care

11. Identifying the highest risk patients
Within the top 1% there is a significant variance in
risk scores – we are able to sort the patients in
order of risk score to ensure
the highest risk patients are
considered first for
case management
Bottom 10 risk
Top 10 highest scores in
risk scores in the top 1%
the top 1% (Average
(Average Emergency
Emergency Admissions
Admissions 6.4) 0.1)

12. Outcomes
 Over 1300 patients with MDT care plans in place
 132 GP practices, 3 local authorities, 2 acute trusts and
1 community provider delivering the model of care
 Improved co-ordinated care by multi-disciplinary teams
and reduced duplication
 Every patient has a nominated and dedicated liaison
officer to coordinate personalised care
 Rapid access to social care as needed through direct
referral to social care
 Co-location of health and social care teams in B&D and
Redbridge building “high trust” partnership teams

13. Disease •Disease risk analytics
Robert Meaker
Associate Director for Commissioning
Support and Innovation
NHS North East London and the City

14. Why Chronic Obstructive Pulmonary
Disease ?
Chronic Obstructive Pulmonary Disease (COPD)
Direct healthcare cost of over affects around 4% of the adult 10 % of emergency admissions 1
£950,000,000 1 population. 1
14 % admitted patients die 1
Indirect costs of £1,300,000,000 1 Highest costing individual with
COPD over 2 years £50,299 2 35 % are readmitted within 90 days
1
2 year cost of COPD in Barking & Severe mean, 10 care visits £8,000
Dagenham £5.5 million 2 p.p. 1
1 2
Source European respiratory Society Source ONEL business intelligence

15. High Cost –Secondary Care Use
Practice 1 Practice 2 Practice 3 Practice 4 Practice 5 Practice 6 Practice 7 Practice 8 Practice 9 Practice 10 Practice 11

16. Intention
• Defining quality “Risk factors” – NICE Quality Standards
for COPD
• Measuring Quality= Health Analytics data extraction
system installed in each surgery
• Education programme at multiple levels – offering
support where needed and wanted
• Empowering patients

17. Identification of Interventions
Establish and monitor a set of 7 core
areas for patient care, within primary care.
1) Post bronchodilator spirometry
2) Severity Measurement
3) Annual review
4) Smoking cessation
5) Pulmonary rehabilitation
6) Self management plan
7) Palliative care
The Health Analytics tool, identified a 10 fold baseline
variation between practices on many quality measures

18. Interventions to reduce risk (Quality)

19. Impact of Interventions
100
90
80
70
60
50
40 Pre
30 Post
20
10
0
Spirometry Self Management Ref. PR
Confirmed Plan Issued
Diagnosis
Key Indicators Pre and Post Intervention
45 Practices with 2788 Registered COPD Patients

20. Impact on COPD Admissions
1200
Number of
patients not
diagnosed with
COPD by GP,
having a COPD
related IP
admission (any
type) in the last
681 690 684 12 months
658 656 657 647
641 651 646
610 Number of
599
600 584 patients not
561
540 545 diagnosed with
519 COPD by GP,
499
479 479 having a COPD
461 470 related IP
admission (any
type) in the last
12 months
Total number of
COPD related IP
479 453 632 608 562 534 483 464 664 623 618 617 604 583 562 543 528 514 503 412 398 393 admissions (any
300 type) in the last
12 months
1/1/2010
1/3/2010
1/4/2010
1/6/2010
1/9/2010
1/3/2011
1/4/2011
2/7/2011
4/8/2011
1/9/2011
1/2/2012
3/3/2012
8/4/2012
9/6/2012
1/11/2010
31/1/2011
16/6/2011
8/10/2011
21/1/2012
19/5/2012
19/11/2011
11/12/2011
COPD admissions showing sub analysis by patients
known and not known to GP with a diagnosis of COPD
within : Barking and Dagenham

21. Intervention stage 2
Patient empowerment
Promote improvement through patients
Send each COPD patient a score card containing a report on
the core primary care interventions
VIDEO

22. Learning
• Define Patient Risk factors “Quality Care”
• Measure Quality Care
• Multi Level Educational Intervention
• Data reliability critical
• Massive Practice Variation
• Huge Learning need
• Work from within
• You can make a difference (and quickly)