Director, Dept of Cardiothoracic Surgery Princess ... · PDF fileFRAILTY IN CARDIAC SURGERY...
Transcript of Director, Dept of Cardiothoracic Surgery Princess ... · PDF fileFRAILTY IN CARDIAC SURGERY...
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FRAILTY IN CARDIAC SURGERY
Assoc Prof Julie Mundy
Director, Dept of Cardiothoracic Surgery
Princess Alexandra Hospital. Brisbane
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Which old people should we operate on?
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Which old people should we operate on?
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Which old people should we operate on?
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An issue that is not going to go away
From Pyramid to Coffin Changing Age Structure of the Australian Population, 1925-2045
Source: Productivity Commission 2005
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Reasons for the ageing population
• past falls in fertility • increasing life expectancy
• the effect of the ‘baby boomer’ generation
moving through older age groups in coming decades
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Australian population projections
• number of people aged over 65 years will increase from the current 2.5 million to around 7.2 million by 2050
• proportion of people aged over 65 years will grow from the current 13%, to one quarter of the population by 2050
• proportion of people over 85 years will grow from the current
1.4% to approximately 6% by 2050
• proportion of the population aged between 15-64 years (labour force age) will fall from the current 67%, to around 59% by 2050.
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The increased costs of an ageing population
Aged care services
Infrastructure
Housing
Transport
Health promotion programs
Community facilities
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PAH Cardiac Surgery
Data obtained from prospectively collected data
Using ANZSCTS registry fields and definitions
All patients undergoing cardiac surgery at PAH
1999 to mid-2014
Over 10,000 patients
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How big is the “elderly”problem and is it increasing?
0
5
10
15
20
25
30
35
40
45
>80
70-79
perc
ent
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Operation status
0
10
20
30
40
50
60
70
80
Elective Urgent Emergent/Salvage
<70 yrs
70-79 yrs
>80 yrs
perc
ent
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Operation type
0
10
20
30
40
50
60
70
CABG AVR AVR/CABG MVR/Repair MVRRep/CABG
<70
70-79
>80
perc
ent
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Postoperative stay
<50 50-59 60-69 70-79 >80
Total cases 1183 2187 3394 3105 577
Deaths
(%)
17
(1.4%)
30
(1.4%)
63
(1.9%)
67
(2.2%)
14
(2.4%)
<50 50-59 60-69 70-79 >80
By day 5 71.7% 73.5% 69.0% 55.8% 41.1%
By day 7 85.0% 87.3% 86.9% 79.8% 72.6%
Discharge day
Mortality
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Morbidity <50 yrs 50-59
yrs 60-69 yrs
70 – 79 yrs
>80 yrs
New AF 10.7% 18.7% 27.2% 33.1% 36.9%
Insertion PPM
2.0% 1.1% 1.6% 2.0% 4.0%
Stroke 0.9% 0.8% 1.1% 1.8% 0.7%
Deep sternal infection
0.3% 0.7% 0.9% 1.0% 0.5%
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Logistic Euroscore
Does it adequately predict morbidity
length of hospital stay
Or do we need to look at other factors?
Patient FactorsChange sheet below to
change language
Age 85yr
Sex
Chronic pulmonary disease
Extracardiac arteriopathy
Neurological dysfunction
Previous cardiac surgery
Serum creatinine >200 µmol/ L
Active endocarditis
Critical preoperative state
Cardiac Factors
Unstable angina
LV dysfunction moderate or LVEF 30-50%
Lv dysfunction poor or LVEF<30
Recent myocardial infarct
Pulmonary hypertension
Operation Factors
Emergency
Other than isolated CABG
Surgery on thoracic aorta
Postinfarct septal rupture
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Moderate OR
Poor
Female
Additive EuroSCORE 11
Logistic EuroSCORE (mortality %) = 19.07%
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Frailty: the missing element in predicting operative risk?
Risk stratification scores e.g. Logistic Euroscore address the disparity between chronological and biological age by considering
Patient demographics
Co-morbidities
Operative variables
Age
BUT
Do not take physiological reserve into account and therefore tend to
Overestimate operative risk in robust elderly patients
Underestimate operative risk in frail patients
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Frailty
Defined as a state of increased vulnerability to stressors caused by deterioration across multiple physiological systems
Can be quantified to a certain extent by the use of scoring systems
Is a well recognised predictor of decreased event-free survival in the community.*
* Rockwood K et al. Lancet 353:205. 1999
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What about the cardiac surgical cohort?
Frailty has only recently been investigated as a risk for adverse outcomes after cardiac surgery, partly because
effective assessment requires prospective evaluation
Until recently the only alternatives to conventional valve surgery carried unacceptably high morbidity and mortality, obviating the need for more sophisticated patient selection
Spiralling health care costs
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Studies to date
There have been 5 studies to date
Lee DH et al. Circulation 121:973. 2010 Analysed prospectively collected data on 3826 adult patients (2004+)
Age 15 to 91 yrs
Divided into frail n=157 and non-frail n=3669 on the presence of any impairment of
The KATZ index of daily living
Independence of ambulation
Previous diagnosis of dementia by a specialised physician
Frail patients were Older
More likely to be women
Have other risk factors for adverse postoperative outcomes
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Lee DH et al. Circulation 121:973. 2010
Frailty was an independent risk factor for in hospital mortality (OR 1.8)
Reduced mid-term survival (OR1 1.5)
Prolonged institutional care (OR 6.3)
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Sunderman et al Eur J Cardiothorac Surg, 39:33. 2011 Focussed on 400 patients with a mean age of 80.2 years including 59 having a trans-catheter valve
Assessed Logistic Euroscore Self-reported
Unintentional weight loss Exhaustion Low activity
Assessment of Grip strength Balance Gait speed Co-ordination
Spirometry Biochemical panel
Adds an additional 20+ mins to the assessment per patient
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Sunderman et al Eur J Cardiothorac Surg, 39:33. 2011 Median logistic Euroscore was 8.5%
Correlation between the risk score and the frailty measure was low to moderate
Frailty predicted 30 day mortality almost as closely as the predictive risk score however their predictive accuracy was only “fair” (area under ROC 0.79)
Authors concluded that combining frailty scores with cardiac surgery risk scores may offer the potential to optimize accuracy of predictive scoring systems.
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Sunderman et al Interact CardiovascThorac Surg 13:119. 2011
Modified their “CAF” score, which takes 10-20 mins to perform and requires special equipment to
Frailty predicts death One yeaR after Elective CArdiac Surgery Test “FORECAST” - using those factors which showed the best discrimination concerning 1 year mortality with good accuracy
The modified test includes Chair rise: patient is asked to get up and down from a chair 3 times and time is measured Weak: patient is asked if they felt weak in the last 2 weeks Stair: patient is asked to climb as many stairs as they are able CFS: Clinical frailty scale independently assed by a cardiac surgeon and physician Creatinine: serum creatinine level
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de Arenaza DP et al. Heart 96:113. 2010
This was performed as a sub-analysis of a randomised trial of stentless versus stented aortic valve replacement.
The ability of patients to walk further than 300 metres in a standardised 6 minute walk test was the only independent predictor of the composite endpoint of death, myocardial infarction or stroke at 12 months
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Afilalo J et al. J Am Coll Cardiol 56:1668. 2010.
Gait speed as an incremental predictor of major morbidity and mortality in elderly patients undergoing cardiac surgery
Multi-centre
Age >70 yrs
CABG and/or valve surgery (non-emergent)
“Slow walkers” defined as taking more than 6 seconds to walk 5 metres.
Able to use an aid.
Primary endpoint was in hospital mortality major morbidity
Stroke
renal failure
prolonged ventilation >24 hours
deep sternal wound infection
re-operation
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Afilalo J et al. J Am Coll Cardiol 56:1668. 2010.
Secondary endpoints Discharge to a health care facility
(rehab, convalescence, other hospital, nursing home)
Prolonged postoperative length of stay >14 days after the index surgery
Principal finding 5 metre gait speed is an incremental predictor of mortality and major morbidity in elderly patients undergoing cardiac surgery
Associated with a 2 to 3-fold increase in mortality risk
Associated Higher rates of complications
Higher rates of discharge to a health care facility
Longer lengths of hospital stay
Simple, easy to administer test
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Other issues
Mental toughness
When the going gets tough……
……… the frail watch the dominoes fall
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Other issues
Mental toughness
Unmasked early dementia Acute confusion in first couple of days
“Sundowning”
Collateral history (usually from daughters) that patient has been undergoing mental decline
Often evident preop but subtle and difficult for doctors without english as a first language
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Other issues
Mental toughness
Unmasked early dementia
Social supports Increasingly patients have no family or friends Men commonly die before their wives When family are around they are increasingly reluctant to provide after care because of their own “busy” lives
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Other issues
Mental toughness
Unmasked early dementia
Social supports
Long term QOL It musn’t just be about 30 day survival
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HEALTH ECONOMICS
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Health Expenditure - % of GDP
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0.0
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1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Australia
Austria
Belgium
Canada
Denmark
France
Germany
Greece
Ireland
Italy
Japan
Netherlands
New Zealand
Poland
Portugal
Spain
Sweden
Switzerland
United Kingdom
United States
Health expenditure trends - % of GDP
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Government Debt - % of GDP
0
50
100
150
200
250
Jap
an
Gre
ece
Ital
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Port
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Irel
and
Uni
ted S
tate
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Icel
and
Bel
gium
Fra
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Can
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Uni
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ingd
om
Ger
man
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Isra
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Aus
tria
Spa
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Net
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land
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Pola
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Nor
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Sw
itze
rlan
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Slo
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Den
mar
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Fin
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Slo
vaki
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Mex
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Cze
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epub
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Tur
key
Sw
eden
New
Zea
land
Sou
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orea
Aus
tral
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Lux
embou
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Chile
Est
onia
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Australian Govt Debt - % of GDP
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So when you are broke
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So when you are broke
you need to be mindful about how you spend your
money!
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What criteria do we currently use?
Age
Comorbidities
Who can afford to pay for it But Medicare pays 75% of the private patient fee!
Risk stratification scores
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The ideal older patient
Survive the operation with minimal morbidity
Return to independent living
Good quality of life
Life expectancy to match age-adjusted norms
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What to look at
Multiple ‘frailty indicators’ have already been identified in the literature
Assessment tools must be simple, quick and easily performed
Additive “frailty” scores utilised in combination with other validated risk scores
Composite endpoint including morbidity and quality of life indices not just mortality
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Frailty in Cardiac Surgery Study Methodology
• Prospectively collected data
• Informed consent
• All patients >70yo undergoing elective or urgent cardiac surgical cases eligible
• Assessment done preoperatively
• Demographic information retrieved from database
• Postoperative follow-up
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Demographics
• Mean age 77.1 yrs (70-92yo)
• 85 males, 38 females
• 88 Elective, 35 Urgent
• All ‘on pump’
• Operation
– 56 – CABG
– 35 – AVR
– 13 – AVR & CABG
– 5 – MVR or MVRepair
– 4 – CABG & MVRepair
– 4 – MVR & TVRepair
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Who is ‘Frail’?
Biochemical Markers
Creatinine Frail if > 120mmol/L
Albumin Frail if < 33g/L
Haematocrit Frail if < 0.35
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Who is ‘Frail’?
Self Reported Markers
Low Activity Q: How often do you engage in activities that require a low to moderate level of activity (gardening, cleaning the car, going for a walk)?
Frail if responds “1-3 times a month” or “Hardly ever”
Exhaustion Q: How often in the last week did you feel you could not get going? Q: How often in the last week did you feel everything you did was an effort?
Frail if responds “Most of the time” or “All of the time”
Falls Frail if any falls in the past 6 months
Dependence Frail if dependent in Katz Index of ADLs
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Who is ‘Frail’?
Physical Assessment Markers
Weight Loss Frail if >4.5kg unintentional weight loss in 12 months or BMI <18.5
5m Walk Test Frail if average walk time ≥ 6 seconds
Chair Rise Frail if total chair rise (3 times) ≥ 11 seconds
Weakness Frail if best grip strength is
Men Women
BMI Grip (kg) BMI Grip (kg)
≤ 24 ≤ 29 ≤ 23 ≤ 17
24-28 ≤ 30 23-26 ≤ 17.3
> 28 ≤ 32 26-29 ≤ 18
> 29 ≤ 21
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Number of Frail Indices
47
37 37
24
15 15 13
11 11
6 6
0
10
20
30
40
50
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Normal 60
49% Borderline
46 37%
Frail 17
14%
Frailty Grouping
0 10 20 30 40
Zero
1
2
3
4
5
6
7
8
Total Summative Frailty Score
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Demographic Variable Normal Population
Borderline Population
Frail Population
Mean Age (yrs) 76.0 77.0 80.6 *
Male (%) 78 65 47 *
Mean BMI (kg/m2) 28.0 29.6 28.7
LVEF <40% (%) 7 17 12
Median Log Euroscore 5.85 7.25 15.67
Median Euroscore II 1.90 2.48 3.65 *
Smoking History 65% 48% 47% *
Family History 27% 28% 24%
Hyperlipidaemia 82% 76% 76% *
Hypertension 90% 80% 88%
Diabetes 20% 43% 24%
Cross Clamp (mins) 73.6 63.5 75.5
Bypass Time (mins) 102.5 91.7 107.6
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Composite Outcome
Composite “Poor Outcome”
1. Death
2. Deep Sternal Wound Infection
3. Length Of Stay ≥ 11 days
4. Inter-facility Transfer at discharge
Increase the ability to detect clinically significant differences in outcome
A LOS of 11 days is greater than twice the median stay in this cohort
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P=0.003
0
10
20
30
40
50
60
Normal Borderline Frail
Risk of unfavourable outcome by frailty pe
rcent
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Individual Measures
Four measures showed independent relationship (p< 0.05) to the composite outcome
Walking speed
Chair Rise
Grip Strength
Serum Albumin
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Blood Usage
Frailty also predicts need for blood product transfusion
Independent of HCT in scoring system
p=0.01
14.3
30.6
58.3
14.3
25.0
75.0
0
10
20
30
40
50
60
70
80
Normal Borderline Frail
Perc
ent
age
of
Patient
s re
ceiving
Tra
nsfu
sion
Likelihood of Transfusion
Excluding HCT Standard
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Predicted Mortality
Mean Logistic Euroscore
Mean Euroscore II
Actual In Hospital Mortality
Overall 9.0 3.6 4/123 (3.3%)
Non-Frail Subset 7.8 3.2 3 / 106 (2.8%)
Frail Subset 16.2 6.1 1 / 17 (5.8%)
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Quality of Life at Three Months
Assessed preoperatively and at three months post operatively
SF-36 Questionnaire
Eight Domains of Function
Follow-up at 3 months was 94% complete
(110 of 117 survivors)
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0
20
40
60
80
100
SF
-36
Sco
re
Normal
Borderline
Frail
Preoperative QoL
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Postoperative QoL
0
20
40
60
80
100
SF-3
6 S
core
Normal
Borderline
Frail
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Change in QoL
-15
-10
-5
0
5
10
15
20
25
30
35
Chan
ge in
SF
-36
Sco
re
Normal
Borderline
Frail
* p < 0.05
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2 year follow-up -living status
0
10
20
30
40
50
60
70
80
90
1 2 3 4 5
Normal
Borderline
Frail
perc
ent
1. In own home without services 2. In own home with in-home services 3. With family who provide daily care 4. In low care nursing facility or hostel 5. In high care nursing facility
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2 year follow-up ADL’s requiring assistance
0
10
20
30
40
50
60
70
80
90
Bathing Dressing Mobility Home maintenance
Normal
Borderline
Frailty
perc
ent
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Kaplan-Meier Survival Curves
0.5
0.6
0.7
0.8
0.9
1
0 3 6 9 12 15 18 21 24 27 30
Group
Normal
Borderline
Frail
months
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So where does this leave us?
We will need to become increasingly selective about who we spend this precious resource on
We will need to improve our risk stratification of patients to encompass factors such as frailty
We will need to consider QOL outcomes not just mortality/ morbidity
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So where does this leave us?
• We will need to become increasingly selective about who we spend this precious resource on
• We will need to improve our risk stratification of patients to encompass factors such as frailty
• We will need to consider QOL outcomes not just mortality/ morbidity
WE WILL NEED TO BECOME HEALTH ECONOMISTS
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The IMF said health costs will be the biggest burden for governments, and that the main driver is not ageing populations but generous health care systems, costly procedures based on new technologies, and the rising incomes that have so far afforded rising medical costs.
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The IMF said health costs will be the biggest burden for governments, and that the main driver is not ageing populations but generous health care systems, costly procedures based on new technologies, and the rising incomes that have so far afforded rising medical costs.
HOWEVER
The end goal must be a substantial reduction in the unsustainable costs in health, quality of life and resources incurred by flawed decision making in this large (and increasing) patient population