Using informatics to target use of Specialist Nurses to improve hospital
care for people with learning
disabilities
Daniel Marsden – Practice Development NursePene Stevens – Head of Learning Disability NursingSteven Taylor – Senior PractitionerPenny Moroney – Senior Practitioner
Background
• Current Monitor Compliance Indicator– Does the trust have a
mechanism in place to identify and flag patients with learning disabilities and protocols that ensure that pathways of care are reasonably adjusted to meet the health needs of these patients?
Hospital Context
• One F/T Practice Development Nurse
• 1400 beds over 3 Acute Hospitals – 3rd biggest Trust in UK
• How do I develop practice of over 7000 staff?
Data Analysis
Figure 5 showing the number of admissions for people with
learning disabilities between July 2008 and July 2010
0
2
4
6
8
10
12
0 100 200 300 400 500 600 700
Number of people with learning disabilities using Trust services
Nu
mb
er o
f A
dm
issi
on
s
Patient Centre Flagging
• GP Registers?
• Hospital Information Team provided us 1500 names F819 ICD- 10 code
• Manually inputting on Patient Centre
Inquiry into use of data
• Realised Patient Centre Flag was not having the desired effect
• Leadership for Informed Practice had me question again how we could track
• EKHUFT Information team solution QlikView
QlikView Dashboard
• EKHUFT bought QlikView for Business and financial management
• Information Dept adapted it for clinical applications
QlikView – Excel Spreadsheet
• Behind the dashboard is an Spreadsheet that draws information out of Patient Centre every 2 minutes.
• The blue dots represent people with learning disabilities Flagged on Patient Centre.
Learning Disability Link role
• Formalised links between EKHUFT & KCHT
• Exploration of what Learning Disability Link Nurse role meant
Referrals to Learning Disability Link Nurses
• One Nurse for each Hospital
• Who would be referred and why?
• How would we create an audit trail and evaluate?
Refining the questions
• Referrals for people– visiting A&E > 4 times or – being admitted > 3 times in the
last year.
• Excel spreadsheet to gather details and outcomes.
• 30 referrals in the last 14 weeks
Outcomes- Case studies
• One man experienced significant bowel pain and diarrhoea.
• 12 visits to A&E and 8 admissions.
• Discharge planning with CLDN, reduced pain and discomfort.
• One man visited A&E 50 times in the last year ~ £10,000
• Collaborative intervention = 9 weeks without visits.
Outcomes – Case studies
• Individual with urology issues – repeated admissions for washouts via A&E.
• CLDN input has most washouts in the community.
Themes
F819 Learning Disability prevalence EKHUFT vs Local Population
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
Apr-11 May-11 Jun-11 Jul-11 Aug-11 Sep-11 Oct-11 Nov-11 Dec-11 Jan-12 Feb-12 Mar-12 Apr-12 May-12 Jun-12
Month
% LD
Prev
alenc
e Rate
Number of admissions per 1000 (All) Number of admissions per 1000 (with Learning Disabilty)
• Responsive service – Specialist Nurse intervention
• Increasing productivity
• Data quality
• Gap analysis – May – 79 Admissions, 10
referrals.
• Other uses for QlikView
What’s next?
• Evaluation– Individual outcomes– Cost savings
• Publication?
• Further adaptations to QlikView
For further information
• Daniel Marsden – Practice Development Nurse for people with learning disabilities
• Email [email protected] • Mobile 07786 171008 • www.ekhuft.nhs.uk/
learningdisabilities • Twitter: @dmarsden49
