1. The Role of Virtual Wards in Reducing Unplanned Admissions
Maggie Ioannou MSc BA RGN RSCN RHV
Director of Community Health Services
Croydon PCT

2. Identifying Patients
Key to success is in accurate identification of patients
Clinician referrals do not work
Threshold modelling (e.g. all patients aged >65 with 2+ admissions) do not work

3. Regression to the mean Average number of emergency bed days - 5 - 450 45 40 35 30
Average number of emergency bed days 25 20 15 10 5
Intense year
- 5
- 4
- 3
- 2
- 1
+ 1
+ 2
+ 3
+ 4

4. Emerging Risk Average number of emergency bed days - 1 + 1 + 2 + 3 + 450 45 40 35 30 25
Average number of emergency bed days 20 15 10 5
- 1
+ 1
+ 2
+ 3
+ 4
- 5
- 4
- 3
- 2
Intense year

5. Predictive Risk Modelling
Kaiser Permanente and other US providers have been using this method successfully for 20 years
Their algorithms are proprietorial
NHS commissioned its own algorithms which can be downloaded free of charge by PCTs

6. Intervention A&E data GP Practice data In-patient data
A&E data
GP Practice data
In-patient data
Social Services data
Intervention
Combined Model
Out-patient data

7. Intervention

8. 10 Croydon Virtual Wards Croydon population = 340,000 10 virtual wards
Catchment population of 34,000 residents per ward
One ward per 15 GPs
100 “beds” per ward

9. Virtual Wards Mimic hospital ward
Patients cared for in their own homes
No physical ward building, hence the term virtual wards
Patients case managed by multidisciplinary team
Ward Team headed by Community Matron

10. Specialist Staff Specialist nurses Asthma Continence Heart Failure
Virtual Ward B
Virtual Ward A
GP Practice 1
GP Practice 2
GP Practice 3
Virtual Ward A
Community Matron
Nursing complement
Health Visitor
Ward Clerk
Pharmacist
Social Worker
Physiotherapist
Occupational Therapist
Mental Health Link
Voluntary Sector Helper
Specialist Staff 
Specialist nurses
Asthma
Continence
Heart Failure
etc.
Palliative care team
Alcohol service
Dietician
GP Practice 5
GP Practice 4
GP Practice 6
GP Practice 7
GP Practice 8
Virtual Ward B
Community Matron
Nursing complement
Health Visitor
Ward Clerk
Pharmacist
Social Worker
Physiotherapist
Occupational Therapist
Mental Health Link
Voluntary Sector Helper

11. Medical Input
Community matron given the bypass telephone number to the duty doctor at each of the constituent GP practices
Community matron able to book appointments to see the patient’s usual doctor

12. CICS “Weekly” 35 Patients “Daily” 5 Patients “Monthly” 60 Patients
Croydon
Intermediate
Care
Service
Expert
Patients’
Programme
“Weekly”
35 Patients
“Daily”
5 Patients
“Monthly”
60 Patients
Discharge

13. 100 patients per ward
“Weekly”
35 Patients
“Monthly”
60 Patients
“Daily”
5 Patients 5
(35  5)
(60  20) =
= 15 patients for discussion each day

14. PREDICTED 0 PARR Score 98 100 OBSERVED 0 PARR Score 98 100 Admissions

15. Key Strengths
Patients identified according to predicted need thereby reduces health inequalities and counters the inverse-care law
Multidisciplinary, multi-sector partnership
Eliminates duplication
Patient-focused
Simple intervention that is being adopted across the UK

16. Lessons learnt so far 1 Wards must make sense to primary care teams
Takes time to integrate social care
Issues of confidentiality must be faced early
Impact across whole system is dynamic – in particular community nursing
Takes time to keep acute trust on board and not antagonistic

17. More lessons Do not underestimate change management demands
Trying to map savings across HRG groups is very complicated
Important to remember that savings are whole system not attributable to one intervention
Public relations crucial
The price of winning awards!

18. What makes the partnership work
Genuine trust and respect
Shared vision that unplanned admissions are frequently avoidable
Communication at all levels
Sharing success; creating solutions together
Facing the difficult issues in an open manner – brush nothing under the carpet
Leadership
“Can do” environment