2. A quick resume
BSc (Hon) in microbiology/biochemistry
PhD in Chemical Engineering
Chartered Management Accountant
Research Gate score ranks in the top 5% of scientists
Over 200 publications
25 years experience analysing trends in health care
Spent the last 8 years publishing studies unravelling
why health care costs and activity behaves in the way it
does
3. Key Points
Highly complex very-small-area simultaneous spread of
increased medical admissions and deaths
Males and females behave as separate compartments
Both in-hospital and out-of-hospital deaths increase
Admissions/deaths show a unique step-increase which
endures for 12-months before returning back to baseline
Same patterns in sickness absence and gender ratio at birth
Sickness absence in health care workers affected worse than
other professions
Time-dependant sickness/condition cascades are initiated
by each outbreak
Conditions sensitive to immune function most affected
4. Why the unusual trends?
4,700,000
4,800,000
4,900,000
5,000,000
5,100,000
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5,500,000
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5,700,000
Running12monthtotalemergencyadmissions
12 month period ending at:
EM admissions
Demographic Growth
2014 event commences
A 2015 event?
2008 event
2010 event commences
2012 event commences
Footnote: Monthly emergency admission data was obtained from the Health and Social Care Information Centre (HSCIC) website and is an extract from Hospital
Episode Statistics (HES), http://www.hscic.gov.uk/searchcatalogue?productid=20537&returnid=1684. The trend for demographic growth was determined using 5
year age-banded HES data for 2014/15 which was matched with mid-year 5 year age-banded population estimates from the Office for National Statistics. Age
standardised admission rates were then applied to population growth between 2008 and 2015.
5. A running total explained
Add up deaths Jan-Dec, now move forward one month and
repeat the sum
Effectively minimises the underlying seasonal profile
Dampens down the small number monthly scatter
A running total is excellent at detecting step-like change,
i.e. a sudden jump from and average of 100 per month to
120, etc
If the jump lasts for 12 months you get a ramp up (the
inverted ‘V’), whose slope equals the magnitude of the step
change and the foot of the ramp indicates initiation
Other background events can modify the shape of the ‘V’
6. Everything changes together
At the points of step-like increase in emergency admissions, everything
simultaneously increases
All-cause mortality (especially in persons with neurological conditions)
Staff sickness absence
A&E attendances (and case-mix)
Medical admissions (and case-mix)
Including adult-only appendicitis
Acute bed occupancy
Outpatient first and follow-up (and case mix)
Ambulance journeys (and case-mix)
Gender ratio at birth
Inflammatory markers in blood
Appears to accentuate winter pressures
The resulting increased deaths, etc have been (on occasions)
incorrectly attributed to influenza, cold and other winter infections
7. Which conditions?
Everything that changes has an immune basis in infection,
inflammation or auto-immunity
In the elderly, appears to lead to unusually high long-term
growth in conditions associated with multi-morbidity
A wide range of common conditions increase such as
pneumonias, pharyngitis, tonsillitis, ‘viral’ infections,
certain cancers
Especially affects female versus male deaths from
cardiovascular conditions
The group most susceptible to death are those with existing
neurological conditions (Alzheimer’s, dementia,
Parkinson’s, etc)
An interaction with influenza appears highly likely
8. All the above show spatial spread
Evidence for spatial spread at every size of geography
Country, state, region, local authority, MSOA, LSOA
Both initiation date and magnitude vary
Clear differences between males and females, which behave as
separate compartments (different routes to infection??)
Relatively slow spread, and an approximate 12 month duration
leads to overlapping small area spread which masks the full
extent of the increase in larger geographies
At very large geographies, i.e. USA, spatial spread generates
the appearance of cycles as the inverted ‘V’ features are
blurred (see next on the effect of size)
9. Apparent effect diminishes with size
Step-like increase in deaths for English LSOA
2001-2013, around 1,500 persons per LSOA, >98% confidence interval, n = 44,000
100%
1000%
1 10 100
Maximumstep-likeincrease
Average deaths per annum
Female Male
10. Effect appears far smaller at
country and regional level
1%
10%
100%
1000%
1 10 100 1,000 10,000 100,000 1,000,000 10,000,000
Maximumstep-change
Relative size (deaths per annum)
England & Wales (LA)
Scotland (LA)
Northern Ireland (District Councils)
27 EU Countries
Arizona (Counties)
Australia (LGA)
New Zealand (Cities & Districts)
Data from the previous chart overlaps with this chart
11. Why is end-of-life so important?
Demand for acute health care escalates in the last 18 weeks of life
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DailycountofPCAscores
AveragePCAscore
Weeks to death
Average PCA score
Average daily count of PCA
The PCA score is derived from 12 common biochemical tests and typically shows a dramatic increase in the weeks and months prior
to death. The daily count of PCA scores is equivalent to bed occupancy, i.e. persons in a hospital bed with associated blood tests
12. Unlike emergency admissions
deaths revert back to the baseline
Running 12 month total deaths
No one has any ‘official’ explanation for the inverted ‘V’ features
Every two years since 2000, but evidence for spread across the UK
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12monthtotaldeaths
Eden (Cumbria)
Maldon (Essex)
14. Staff sickness absence – month of initiation of step-
increase in sickness absence in English hospitals Source: HSCIC website
0
5
10
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Countorganisationswithmaxincrease
Month of Initiation
15. Deaths, etc all show very small
area spread
In an infectious outbreak the agent spreads via transmission
along social networks with random effects determining speed
and strength
At LSOA level (a LSOA has about 1,500 people) an average of a
50% increase in medical admissions and deaths occurs as the
agent moves into an area
The 50% figure is real, not a mistake!
Spread within local authority areas combines to give the picture
illustrated for Malvern and Eden above
Most probably (mainly) carried by young children who infect
their grandparents with catastrophic consequences!
This scenario appears to apply more to elderly women than men
For a list of publications:
http://www.hcaf.biz/2010/Publications_Full.pdf
16. Deaths lag behind medical
admissions and A&E attendances
Approximate 6 week lag
Local authority areas in Northern Ireland step-like changes in medical
admissions and deaths (2000-2014)
y = -0.6797x2 + 0.343x + 0.031
R² = 0.805
-8%
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Changeinadmissions
Change in deaths
17. Latest research
Spread of the infectious agent behaves differently between
males and females
Maximum amplitude outbreaks of the agent occur in 1% of
small areas at any point in time
These localised outbreaks appear to aggregate to give the
larger national events
Up to 1,000% increase in deaths possible in a small social
network (around 8 households)
A time-cascade of biological effects
First affected is the gender ratio at birth (in first trimester)
Next are emergency medical admissions
Then deaths
18. In Conclusion
To many things happening at once has clouded the debate
on fundamental cause of unexplained increases in
unscheduled care
No one though to look for evidence of infectious spread
Everyone assumed it was something to do with the ageing
population and failures in the provision of health and
social care
Growth by age band reveals evidence for ‘original antigenic
sin’, i.e. the process whereby the immune system is primed
by repeated exposure to strains of the same infectious
agent
