1. Measuring Health and Homelessness - in Fife
Summary of Results:     Jan 14 update
NHS Fife hospital activity for those on the Fife Council homeless register. Data is sourced from OASIS and PIMS to provide activity in Acute, Psychiatric, Obstetrics and A&E from 2006 to Below comments referring to Fife are for 15 to 64 years of age. Population based on average number of people on HL1 on 1st day of each quarter (January, April, July and September).      
A&E    
HL1 Attendance Rate; Male > Female
Attendance Rate; HL1 > Fife  
Attendance Age; HL1 < Fife        
Inpatient Daycase Admissions (IPDC)
Emergency Admission Rate; HL1 > Fife
Multiple Emergency Rate; HL1 > Fife
% Admissions relating to Alcohol/Drug Misuse; HL1 > Fife
Rate of admission relating to Alcohol/Drug Misuse; HL1 > Fife      
Obstetrics (OBS)    
Obstetric Admission Rate; HL1 > Fife
Admission Age; HL1 < Fife        
Psychiatic (PSY)    
Psychiatric Admission Rate; HL1 > Fife      
Outpatient Appointments (OP) Return:New Ratio; HL1 < Fife  
% DNA New/Total; HL1 > Fife  
% Women's Health Appointments; HL1 > Fife
Dr Neil Hamlet Consultant Public Health Medicine Fife Health & Homelessness Lead

2. Homelessness - a cross cutting agenda
Voluntary Agencies
Council Housing Departments
Substance Misuse
Dental Care
Foot and skin care
Alcohol Abuse
Mental Health Issues
Nutrition and diet
Health & Social Care Integration Bodies
Homelessness
Community Health Partnerships
Social Work
Cross-cutting agencies
Cross- cutting NHS specialties and services
What is the response? Who can help? What skills are needed? Who is missing here?
Need to superimpose CPP, HSCPs etc
Need a 2nd map with:
Inter-personal coping skills – conflict resolution
Education & Skills
Employment – work ready
Welfare Mitigation
Foodbanks
Income Maximisation
Fuel Poverty
Home Health Checks
Embed Housing Options/Adaptations teams in 24/7 services
Registered Social Landlords
NHS Acute Services

3. NHS Housing HSCP Vol Sector
Multi-agency – falling through the gaps is a regular experience for clients
Walking up river (upstream wherever possible)
Communication, communication, communication
NHS
Vol Sector
Housing
HSCP

4. Linkage of Hospital data and Homelessness data in the Kingdom of Fife
Bryan Archibald, Senior Information Officer
Bryan Archibald

5. The Data Sources Fife Council NHS Fife Acute Hospitals HL1
National data set for each homeless application
Based on the application (not the number of homeless individuals)
NHS Fife Acute Hospitals
eOASIS (patient administration system)
SMR data submitted to ISD (information Services Division of NHS Scotland)
Based on Patient Episodes
Permission by SASPI – good relationships with Head of Housing/Homeless Service
HL1 Excel spreadsheet data entry form:
HL1 data collecting form:

6. NHS Data (OASIS) A&E (and Minor Injuries Unit [MIU])
Inpatients & Day cases
Obstetrics
Mental Health Inpatients
Outpatients
Mental Health Outpatients
Linked HL1 data to NHS data obtained from OASIS (NHS Fife patient administration system)
MIU – Minor Injuries Unit
We interrogated the linked data set for the 6 ‘settings/departments’
Date from

7. Results: A&E Inpatients & Day cases HL1 data
Year on year A&E attendances by age and trend from 2006 – 2011 by sex. Not split by flow. Only numbers
IPDC SMR01

8. Obstetrics Outpatients
Year on year hospital obstetric admission by age and trend from Not necessarily the episode of birth. Further analysis required.
(get clarity on the meaning of the rate per 100 of what?)
SMR02

9. So far so good but what does this mean?
We need a comparator for the homeless population
Fife’s ‘securely - housed’ population
Try to compare by similar age profile
Started with Fife population as our crude method of ‘standardisation’
Further refinements planned in ‘standardisation process’
Aiming to compare ‘apples’ with ‘apples’ by security of housing as defined by HL1 registration
Compare like with like by housing situation – insecurely housed vs securely-housed / and by age band
(How would it look if we included older people and addressed the needs of housing for frail and elderly)
Need a couple of slides explaining ‘standardisation’ of comparator NHS hospital population using European Standard Population 2013.

10. HL1 – age determined by the age of the ‘household applicant’ (hence no children seem to appear homeless)

11. ‘Insecurely Housed’ ‘Securely Housed’
The value of shared data analysis
Explain methodology:
Fife HL1 annual extract linked to NHS PAS (patient administration system)
Annonymised and graphed
Can now compare the 2 populations over time, gender and by usage of various in-patient services
Looking at rates not numbers
(get original graph and format legend etc)
(check denominator for rate / 1k popln)
‘Insecurely Housed’
‘Securely Housed’

12. Abuse ? Pragmatic ? £££ How did folk get to A/E?
Note the excess use of blue light / emergency services / ambulances (expensive ++)
Abuse of the service or pragmatic solution for the homeless person?
Get costings for a standard blue light ambulance call and calculate cost to SAS
£££
Pragmatic ? 12

13. Over 80% are under 40 yrs Over 50% are under 30 yrs
Shift to the left of the life stages – more under 30s
Over 50% are under 30
Over 80% are under 40
(what if the comparator pop was – even more skewed)
Over 80% are under 40 yrs

14. Patients who come back time and again – 3 fold difference in the rates

15. £ Moving further into the hospital.....
Actual admission to a hospital bed:
Much higher rates of use
(how would this look with an age band graph? Ie homeless is comparable to the rate experienced by the >80s?
Why gone up in past 2 yrs? (when HL1 actual numbers are going down) – why sicker/more prone to admission? 15

16. Revolving Hospital Door effect
Revolving Hospital Door effect (cf Prison situation – try and examine the multiple overlapping revolving doors of prison and temp accommodation)
Rate (not absolute numbers) of folk who use hospital admission to a bed the most frequently
The care is not working as it should – the system is failing 16

17. Drill down to specific topics/departments/causes of admission Alcohol
Red bars R axis % of total admissions for that HL1 / comparator group
Blue line L axis Rate (number/1000 population)
Red Bars: In % vs 27% for alcohol related admissions
Blue Lines: In /1000 vs 80/ a 10 fold difference 17

18. Blue line L axis - Rate (number/1000 population)
Drug Misuse
Red bars R axis % of total admissions for that HL1 / comparator group
Blue line L axis Rate (number/1000 population)
Under 1.7% vs 17% 10 fold difference 18

19. Clear role for Community Safety Partnerships ?
Injury and Poisoning – measure of violence experienced in homeless community
link to Community Safety agenda – how to protect / prevent
Self harm rates 4 times higher in HL1 19

20. Pregnancy / Fertility – why are they having so many babies?
Why? Cause or consequence
Cf graph of fertility in war torn society in Africa
Measure of crisis or contentment
Can’t tell if due to more pregnancies or difficulties in fewer pregnancies 20

21. Massive shift to the young – should need less medical intervention for the natural childbirth process in this age group
28% under vs 8%
62% under vs 31%
12% over vs 40% 21

22. Mental distress / psychiatric illness requiring admission – very tip of the iceberg
Men >> Women
Is the early drop due to bed shortages keeping them out?
Men rate rising past 2 yrs (unemployment)

23. Access / Expectation Changed address Fearful to open official mail
Appointment too early
No money for the bus
‘it won’t do any good’
Access / Expectation
Finally – you are given an appt for OPD – but do you get there?
Outpatient Services – how many folk fail to turn up for their appt as a percentage
Is the service ‘accessible’ ?
Is it misused or not-person focussed for the specific challenges of the homeless (eg changing address, lost internet, too early in the morning etc) 23

24. Inverse Care Law
“The availability of good medical care tends to vary inversely with the need for it in the population served.”
“Those who need healthcare least use the services more, and more effectively, than those with the greatest need and those people in the worst health receive the least services.”
Julian Tudor Hart 1971 24 24

25. Making a Difference
On call nurse manager gets a text alert on her work phone when a homeless person is seen in Accident and Emergency Dept.
A daily report is now generated listing all the patients in the hospital at 8am who have a temporary homeless accommodation address .
Impact of populating the NHS hospital PAS system with the addresses of council and third sector temporary accommodation:
Concept of embedding HO worker in hospital acute care team – SHELTER Pilot 25 25

26. Admissions to Fife Hospitals with Homeless Accommodation Address
Based on Current Homeless Accommodation List & Patient Address in Oasis at time of report refresh
Nov-14
Dec-14
Jan-15
Feb-15
Mar-15
Apr-15
May-15
Jun-15
Jul-15
Aug-15
Sep-15
Elective
Medical 2 3
Orthopaedic
Surgical 1
Theatres
Women & Children
Total 4
Emergency 8 5 10 14 20 21 22
We now get a monthly automated listing of numbers of admissions of those with a temp accommodation at time of report analysis.
This will slowly build a picture.
Need a Next Steps slide:
DATA
Add costs
Repeat for Prevent 1
Improve comparator age profile 15-55? Or 15-45?
ACTIONS
Embed HO expertise in acute hospitals
Smoother cross-referral to both prevent and mitigate
What of all the opportunities in Foodbanks / Primary Care / SW / Education / ADPs / Youth Diversion etc Employability Partnerships

27. Resilience Factors Supportive friends / family Strong social networks
Appropriate support services
Savings or access to financial help
Available advice & advocacy
In stable employment
Personal empowerment/capacity
If u have no GP then you are not recorded on SCI store
CHI allocated as soon as your born

28. Meet needs of safety, nurture, belonging and purpose
'Houseless and Hungry' by Luke Fildes depicting homeless paupers queuing outside the casual ward of a London workhouse
Back to Maslow – met needs of safety, nurture, belonging and purpose
A study entitled 'Houseless and Hungry' by Luke Fildes depicting homeless paupers queuing outside the casual ward of a London workhouse. A policeman stands at the left of the scene.
Luke Fildes, Houseless and Hungry, Graphic, 4 December 1869 – For Houseless Poor Act
This wood engraving depicts homeless people of all ages queuing outside a police station in order to gain a ticket for admission to a casual ward. Casual wards were attached to workhouses and provided a night’s accommodation in return for a few hours work the next morning. The same scene was the subject of a later painting by Fildes, entitled Applicants for Admission to a Casual Ward (1874).
'Applicants to a Casual Ward' (1874)
In the first edition of the Graphic magazine that appeared in December 1869, Luke Fildes was asked to provide an illustration to accompany an article on the Houseless Poor Act, a new measure that allowed some of those people out of work shelter for a night in the casual ward of a workhouse. The picture produced by Fildes showed a line of homeless people applying for tickets to stay overnight in the workhouse. The engraving, entitled Houseless and Hungry, was seen by John Everett Millais who brought it to the attention of Charles Dickens, who was so impressed he immediately commissioned Fildes to illustrate 'The Mystery of Edwin Drood'.
Meet needs of safety, nurture, belonging and purpose