Projected Demographic Effect
on Health Service Costs
in 2015
Information Unit
Department of Health
May 2014
1
Table of Contents
Page
List of Figures
3
Executive Summary
6
Section 1: Introduction
9
Section 2 : Demographic Overview
14
Section 3: Top Down Estimate of Total Demographic Effect on Health Care
Costs
Section 4: Utilisation Rates
24
Section 5: Demographic Effect on Acute Hospital Casemix Costs
38
Section 6: Demographic Effect on Schemes under the Primary Care
Reimbursement Service (PCRS)
48
Section 7: Demographic Effect on Mental Health Services
55
Section 8: Demographic Effect on Disability Services
56
Section 9: Demographic Effect on Nursing Home Care
59
Section 10: Bottom Up Estimate of Total Demographic Effect on Health
Care Costs
Section 11: Discussion and Conclusions
61
Appendix A: Projected Population (2011 to 2021)
73
Appendix B: Data for Top Down Estimates of Projected Overall Cost
Pressures (2013 to 2021)
Appendix C: Data on Projected Inpatient and Daycase Activity and Costs
(2013 to 2021)
Appendix D: Projecting Preterm Infant Care Cost Pressures (2014 to 2021)
75
Appendix E: Methodology for Projecting Number of Persons in Nursing
Homes
Appendix F: Projecting Primary Care Reimbursement Services (PCRS)
Demographic Cost Pressures (2013 to 2017)
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30
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82
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List of Figures
Page
Figure 1: Growth in population of Ireland, 1992 to 2013
14
Figure 2: Percentage population growth, 2001 to 2013, Ireland compared
with EU average and selected EU countries
Figure 3: Actual population 2011-2013 and projected population 2014-2021
and percentage cumulative change for Ireland, 2011-2021
Figure 4: Population by age group Censuses 2006 and 2011 and projections
for 2017
Figure 5: Population pyramids, 2011 and 2040
15
Figure 6: Annual Growth in numbers and percentage increases for older age
groups, 2011-2021
Figure 7: Projected percentage population growth in the 65 years and older
age group, Ireland compared with EU-28 average and selected EU countries,
2013-2021
Figure 8: Total Fertility Rate (TFR), Ireland and EU-28 average, 2003 to
2012
Figure 9: Total Fertility Rate (TFR) in Ireland compared with other EU
countries, 2012
Figure 10: Total number of births, 2003 to 2012 and projected number of
births 2013-2021
Figure 11: Relative per capita public health expenditure by age group for
females, EU 15 and Norway.
Figure 12: Relative per capita public health expenditure by age group for
males, EU 15 and Norway
Figure 13: Relative per capita public health expenditure by age group and
gender for Ireland
Figure 14: Projected percentage increases in overall health service cost
pressures based on pure demographic effect, 2013 to 2021.
Figure 15: Annual percentage change in cost pressures based on pure
demographic effects ages 65+, 2013 to 2021
Figure 16: Total inpatient and daycase discharge rates per 1,000 population,
2008 and 2013
Figure 17: Percentage of adults with 1 or more outpatient attendance in the
12 months prior to interview, by age group (over 17 years)
Figure 18: Percentage of persons with a medical card by age category, 2012
and 2013
Figure 19: Number of medical cards and percentage of population holding a
medical card, 2004 to 2013
Figure 20: Admission rate per 100,000 population to psychiatric hospitals by
age category, 2007 and 2012
Figure 21: Numbers of persons registered on the National Physical and
Sensory Disability Database (NPSDD), 2008 and 2013
19
3
16
17
18
20
21
22
23
25
26
27
28
29
31
32
33
33
34
35
Figure 22: Numbers of Persons registered on the National Intellectual
Disability Database (NIDD), 2008 and 2013
Figure 23: Percentage of each age cohort in nursing homes, Censuses of
Population, 2006 and 2011
Figure 24: Relative cost of inpatient treatment (casemix index) by age
category, 2013
Figure 25: Inpatient discharge rate per 1,000 population by age category,
2013
Figure 26: Projected percentage increases in inpatient cost pressures based
on demographic effect, 2013 to 2021
Figure 27: Projected percentage increases in inpatient cost pressures based
on demographic effect, 65+ age group, 2013 to 2021
Figure 28: Casemix index by age group for daycases, 2013
36
Figure 29: Day case discharge rate per 1,000 population by age group, 2013
42
Figure 30: Projected percentage increase in daycase cost pressures based on
demographic effect, 2013 to 2021
Figure 31: Projected percentage increase in daycase cost pressures based on
demographic effect, aged 65+, 2013 to 2021
Figure 32: Total inpatient and daycase cost pressures, 2013 to 2021
43
Figure 33: Total inpatient and daycase cost pressures, for ages 65 years old
and over, 2013 to 2021
Figure 34: Projected inpatient and daycase discharges based on demographic
effect, 2013 to 2021
Figure 35: Actual casemix spend, 2008 to 2013, and projected demographic
cost pressures, 2014 to 2021, by age group
Figure 36: Percentage of persons covered by a medical card by age category,
April 2013
Figure 37: Average annual cost per medical card holder, in euro, of GMS
pharmaceutical schemes, 2013
Figure 38: Projected increase in cost of various GMS medical card
payments, 2013 to 2017
45
Figure 39: Projected increase in cost of various other GMS payments (nonmedical card schemes), 2013 to 2017
Figure 40: Projected number of admissions to psychiatric hospitals, 2014 to
2020
Figure 41: Percentage of each age cohort with a self-reported disability,
2011
Figure 42: Projected number of persons on the National Physical and
Sensory Disability Database (NPSDD), 2013 to 2021
Figure 43: Projected number of persons on the National Intellectual
Disability Database (NIDD), 2013 to 2021
Figure 44: Projected numbers of persons in nursing homes by age category,
2014 to 2021
53
4
37
39
40
40
41
42
43
44
46
47
49
50
52
55
56
57
58
59
Figure 45: Projected number of publicly funded persons in nursing homes,
2014 to 2021
Figure 46: Age distribution of discharges from casemix and non-casemix
hospitals, 2013
Figure 47: Cumulative effective reduction in resources, budget reductions
and demographic deficit combined, 2010 to 2016
5
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64
71
Executive Summary
This paper estimates the additional cost pressures on the provision of public health
services generated by demographic change in 2015. In this context, demographic
change refers to alterations in the size and age structure of the population. The
approach adopted is generally referred to as the estimation of the “pure demographic
effect.” This approach applies current per capita costs by age group to the projected
population in 2015 to derive the cost pressures associated with demographic change.
In doing so, the assumption is made that age-specific rates of service utilisation and
unit costs of service provision remain constant between 2014 and 2015. Over the
longer term many factors such as population health (e.g. the effects of obesity, chronic
conditions etc.), medical inflation and structural changes to service delivery influence
service utilisation and cost. Over the course of a single year (2014 to 2015), the
contention of this paper is that the presumption of stability in cost and utilisation
provides the best basis for determining the size and direction of cost pressures due
specifically to changing demographics. The background, methodology and results are
summarised below:

Between 2014 and 2015, the overall population of Ireland is projected to
increase by 0.6% while the population aged 65 years and over will increase by
3.2%. Ireland is now in a period of rapid population ageing which will
continue for a number of decades. In 2015, the numbers of people age 65
years and over will increase by around 20,000. (see Section 2).

Overall, utilisation and cost of health services are higher for the older age
groups. Data from The 2012 Ageing Report, produced by the European
Commission, shows that per capita public health care expenditure is around
twice the national average expenditure at age 65 and rises linearly to nearly
four times average expenditure at ages 85 years of age and over. As in last
year’s exercise, The 2012 Ageing Report has been used to generate a “top
down” estimate of the demographic cost pressures in 2015 (see Section 3).
However, estimates based on The 2012 Ageing Report use EU averages rather
than Irish data and should be treated with caution.
6

In the present report, a more robust and detailed “bottom up” approach has
been applied in arriving at estimated demographic cost pressures arising in
2015. This has been made possible by two recent developments. First, a new
set of official national population projections was produced by the Central
Statistics Office (CSO) last year. Second, a wider range of detailed cost and
utilisation data by age has been accessed which enables a more accurate
estimation to be undertaken across a range of service areas.

Prior to projecting demographic cost pressures in 2015 by service area, an
analysis of trends in service utilisation across a number of sectors was
undertaken in order to verify that the assumption of stability in rates of
utilisation by age group between 2014 and 2015 appeared reasonable. This
analysis demonstrates reasonable stability and, if anything, a gradual increase
in utilisation in recent years across some major service areas such as acute
hospital and primary care reimbursement services (PCRS). (see Section 4).

Sections 5 to 9 of the paper look at acute casemix-funded hospitals, primary
care reimbursement services (PCRS), mental health services, disability
services, and nursing home care respectively. For casemix and PCRS data a
wide range of detailed age and cost specific utilisation data was available
which facilitated robust calculation of the demographic cost pressure in these
areas in 2015. For the other areas, only age-specific utilisation data was
available. In these cases, the calculation of cost pressures was based solely on
projected increases in activity in each age group. No assumptions were made
concerning likely increases in per capita cost with advancing age.

For areas of public health expenditure which were not amenable to agespecific analysis, estimates of demographic cost pressure were based on a
qualitative consideration of the likely target group (e.g. older people services
have an older age profile) in conjunction with the projected population.

The overall results are summarised in Table 1. For each service area the
demographic cost pressure in 2015 is set out based on baseline expenditure
figures for 2014 as set out in the Health Service Executive’s (HSE) Service
Plan. For each service area a high and low estimate of the demographic cost
pressure is presented. To some extent, this represents the level of uncertainty
in the calculation. For certain areas (e.g. acute hospital casemix and PCRS
7
data) where age and cost specific data were available, there is little uncertainty
and the high and low estimates are the same. For other areas, particularly
where age specific data is either not available or not directly relevant, a higher
degree of uncertainty exists. The rationale behind the high and low estimates
for each area of expenditure is set out in Section 10.

For the public health services as a whole, the demographic cost pressure in
2015 has an estimated range of €201 million to €180 million. For specific
service areas, the highest estimate occurs in the acute hospital sector where an
additional €56-60 million is required to accommodate demographic change in
2015. The PCRS sector accounts for a further €40-48 million of the additional
cost pressure, and together these two areas make up more than half the total
estimated additional cost requirement. Other significant areas of additional
cost pressure include NHSS –A Fair Deal (€30 million) and the broad area of
Services for Older People (€20 million).
In summary, the bottom up estimates of demographic cost pressure derived in this
paper should be seen as essential evidence to be incorporated into planning and
resourcing the health services. Ireland is experiencing rapid population ageing
resulting in accumulating pressures on health service provision. The cost of providing
for demographic change must be included as an upfront measure of the additional cost
of maintaining services in 2015 and in subsequent years. Realistic evaluation of the
effects of reductions in the health service budget must take account of the significant
pressures generated by demographic change. Realised savings and achieved
efficiencies can reduce the demographic cost pressure, but the principal cost driver is
the additional number of older people who will require care. For the future, better data
will permit more accurate estimation. Longer term models should be developed
which take full account of the potential effects of projected increases in chronic
conditions such as diabetes and heart disease as well as in cancer prevalence. Other
important economic variables should also be included in longer term modelling and
appropriate health economics expertise will be required to enhance the analysis and
planning capacity of the Department.
8
Section 1: Introduction
The purpose of this paper is to estimate the additional cost pressures generated by
demographic change in providing publicly-funded health services in 2015. The
approach adopted is generally referred to as the measurement of the “pure”
demographic effect. In practice, this means projecting the demographic impact on
health service costs of providing the same level of services in 2015 as in 2014. The
underlying assumption is that all other factors affecting costs remain constant over the
projection period. Some of the more important variables influencing expenditure on
public health services include medical inflation, the health of the population, the state
of the national economy, changes in policies on eligibility and utilisation, and the
expectations of the public. Clearly, over the medium to longer term, pure
demography in the sense of population size and age distribution will not on its own
provide an accurate basis for estimating health service cost pressures. For example,
the national framework for health and wellbeing, Healthy Ireland, identifies major
risks to health from increases in adverse population trends related to obesity, diabetes,
and physical activity. These have the potential to reverse the significant gains in life
expectancy in recent decades and to place significant additional burdens on health
services. The immediate objective of this paper is, however, to focus on
demographically driven funding requirements arising in 2015. Over the space of a
single year, the contention is that the pure demographic approach can provide a
reliable measure of the actual additional cost requirements to deliver the same level of
service to a larger and older population. There are a number of reasons for confidence
in this assertion both in theoretical terms but also due to improved data and
methodology.
First, in theory, many of the factors affecting unit cost and service utilisation can be
expected to remain largely stable between one year and the next. This includes
changes in population health as well as age-specific utilisation of services. In the case
of the latter, Section 4 of the paper examines trends in utilisation rates and
demonstrates, in practice, year-on-year stability across a range of service areas. The
very significant growth in the proportion of the population covered by medical cards
since 2007 (see Figure 19) illustrates the conservative nature of the “no change”
assumption with respect to eligibility.
9
A second reason for confidence in the estimation of demographic cost pressures in
2015 is that a new set of population projections was produced last year by the Central
Statistics Office (CSO) based on the 2011 Census together with updated migration,
fertility and mortality estimates. This gives the best possible estimate of population
change between 2014 and 2015 and takes full account of the effects of the recession in
reducing population growth.
The third reason is based on the fact that the effects of population growth and ageing
on health service cost pressures are cumulative. It could be argued that in a scenario
where budget increases outpace population growth that the net effect remains an
improvement in service provision. In Ireland, however, in recent years the reverse has
been the case. Since 2009, there has been a reduction, in nominal terms, of 12% in
the health service budget at a time when the population continues to grow, albeit at a
reduced rate, and when population ageing is accelerating. Further, the impact of
demographic change has not been fully factored into these reducing budgets. This
means that, as the scope for achieving further efficiencies reduces, the annual
demographic effect must be addressed either by a reduction in services or by taking
full account of the cost implications of demographic change if services are to be
maintained. Not to recognise this would mean that the cumulative effects of an ever
decreasing budget are effectively hidden from view.
The final reason for expressing confidence in the present approach arises from access
to a wider range of age-specific utilisation and cost data facilitates more accurate and
targeted cost projections by service area. In particular, age and cost data in respect of
a range of PCRS payment schemes representing approximately 75% of total PCRS
expenditure facilitates robust modelling of the pure demographic effect in this sector.
In other areas such as nursing home care, mental health services and disability
services, while costs by age remain unavailable, age-specific utilisation data has been
analysed to estimate the demographic effect based on the conservative assumption
that age-specific costs do not increase with age.
In terms of overall methodological improvements, the present exercise continues last
year’s analysis of sector-specific projections across all areas of health service
10
spending in order to estimate the differential effects by service area. For example,
where the client base for a particular service is principally the older age groups, such
as nursing home care, then this will be reflected in cost pressures significantly higher
than the overall growth in the population. These sector-specific effects are then
combined in order to arrive at an overall bottom up estimate of the total additional
demographic cost required to maintain service levels. As with last year, a top down
analysis has also been carried out based on The 2012 Ageing Report produced by the
European Commission. Comparison of the two approaches assists in providing a
level of confirmation of the scale of the pure demographic effect in Ireland for 2015.
The paper begins with a Demographic Overview (Section 2) of the Irish population.
The ageing of the population is the most striking feature, and this section provides
evidence that the population in Ireland is now ageing at a rate which is nearly double
the EU average. The combination of an ageing population and generally higher health
service requirements for the older age groups is, of course, the primary driver of the
demographic cost pressures.
Section 3 of the paper presents the top down derivation of projected additional
demographically driven costs. As indicated above, it is based on The 2012 Ageing
Report from which overall age-specific cost relativities can be derived and applied to
the Irish population projections. For reasons which are considered in the concluding
section of the paper there is a likelihood that this top down methodology may result
in an underestimate of the total demographic effect for Ireland in 2015.
One of the principal assumptions underlying the pure demographic effect is that the
utilisation of services remains reasonably constant over the projection period. Section
4 tests this assumption across a number of service areas where trend data on
utilisation by age is available. To a great degree, the evidence indicates that, if
anything, the assumption errs on the conservative side.
Having demonstrated that it is reasonable to roll 2014 utilisation rates forward to
2015, Sections 5 to 9 then proceed to use age-specific utilisation data as well as age
and cost specific data, where available, to derive estimates of the demographic effect
and consequent cost implications across a number of service areas. These are
11
respectively: acute hospital casemix costs, PCRS costs for a range of services,
disability and mental health costs and, finally, the costs associated with the Nursing
Homes Support Scheme.
In Section 10, the various estimates derived in Section 5 to 9 are brought together and
combined with all the other areas of health service expenditure for which age and cost
specific or age-specific data is not currently available. For these areas, where data
does not support direct calculation of the demographic effect, an estimate has been
made based on an assessment of the target client group in terms of age for each area.
Both a low and a high estimate of the potential demographic effect is recorded and
presented in tabular format (see Table 1). The rationale behind the high and low
estimates is discussed in detail in Section 10. The end result is a bottom up
calculation of the overall demographically driven additional expenditure required in
2015 in order to maintain service levels. The high and low figures give an indicative
range for each area of expenditure and for the total estimate of the pure demographic
effect.
Finally, in Section 11, the results are discussed and conclusions drawn as appropriate.
The discussion includes consideration of how to explain and/or reconcile differences
in the results generated by the top down and bottom up approaches. It also emphasises
that, irrespective of and to some extent because of data shortcomings, both approaches
are more likely to underestimate than overestimate the impact of demographic change
on costs in 2015. The present exercise should, therefore, be taken as an estimate of the
minimum size of the demographic effect. To the extent that successive budget
reductions over the past 5 years have not taken full account of the additional annual
and cumulative effects of demographic change on service demand and provision,
considerable additional weight is added to the argument that the evidence-based
estimates for 2015 set out in this paper represent the minimum additional cost
requirement to address the needs of a rapidly ageing population.
In interpreting the graphics in this report a caveat needs to be borne in mind. In many
cases, the graphics project and illustrate demographic cost pressures up until 2021
whereas the specific objective of the report is to estimate single year pure
demographic cost pressure for 2015. The longer trend, over the next 7 years, has been
12
included in many graphs primarily in order to draw attention to the fact that the
population of Ireland will continue to experience rapid population ageing in the
coming years and that demographic pressures on health service funding will
accumulate. For the future, it is recommended that, with better data, longer term
models should be developed, bringing in appropriate health economics expertise, in
order to include the most important variables affecting health costs and to extend the
planning capacity of the Department.
13
Section 2 - Demographic Overview
The population of Ireland has grown very rapidly in recent decades, and the 2011
Census confirms a continuation of this trend since the last Census in 2006, though at a
more moderate pace (see Figure 1).
Figure 1: Growth in population of Ireland, 1992 to 2013
4,800
Population in Thousands
4,600
4,400
4,200
4,000
3,800
3,600
3,400
3,200
Year
Source: Central Statistics Office (CSO).
The pace of growth in Ireland was particularly striking in the period from 2001 to
2007 and was much more rapid than in most other EU countries and when compared
with average growth across the EU. Since 2007 annual growth rates have declined
significantly and are now closer to average EU growth (see Figure 2).
14
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
3,000
Figure 2: Percentage population growth, 2001 to 2013, Ireland compared with
EU average and selected EU countries
Percentage Population Growth since 2001
25%
EU-28
20%
Belgium
Ireland
15%
Greece
10%
France
5%
Netherlands
0%
United
Kingdom
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Year
Source: Eurostat
The most recently published population and migration estimates for 2013 from the
CSO indicate a very small increase in overall population compared with 2012. Net
outward migration is estimated to have remained broadly the same as the previous
year, standing at 33,100 in the year to April 2013 compared with 34,400 in the year to
April 2012.
15
Population projections
A set of population projections was produced by the CSO in 2013 which now
provides estimates based on a range of assumptions regarding migration and fertility.
The medium migration (M2) and low fertility assumption (F2) have been used in this
report. A summary of the projected population by age group for this scenario is
contained in the appendix. Actual and projected total population together with
cumulative percentage increases over the period are displayed in Figure 3.
Figure 3: Actual population 2011-2013 and projected population 2014-2021 and
percentage cumulative change for Ireland, 2011 to 2021
6.6%
4,900
5.7%
Population in Thousands
4,850
4.9%
4,800
4.0%
3.2%
4,750
2.4%
4,700
4,650
4,600
1.1%
0.2%
1.7%
0.4%
4,550
4,500
4,450
4,400
2011 2012 2013
2014 2015 2016 2017
2018 2019 2020 2021
Year
Source: CSO – Population Estimates and “Population and Labour Force
Projections, 2016 -2046”.
Note: the increases quoted are cumulative percentage increases from 2011.
16
Population Ageing
In Ireland, numbers in the older age groups are now growing rapidly in absolute terms
and represent an increasing proportion of the total population. Figure 4 shows changes
in the population by age group between Census 2006 and Census 2011 and projected
changes in 2017. Figure 5 demonstrates that this trend is set to continue for the next
few decades resulting in a very different population structure by 2040.
Figure 4: Population by age group Censuses 2006 and 2011 and projections for
2017
450,000
400,000
Census 2006
350,000
Census 2011
Number
300,000
Projected 2017
250,000
200,000
150,000
100,000
50,000
0
Age Category
Source: CSO– “Population and Labour Force Projections, 2016 -2046” and
Censuses of Population – 2006 & 2011.
Note: M2F2 scenario used for the 2017 projection.
17
Figure 5: Population pyramids, 2011 and 2040
Source: CSO – “Population and Labour Force Projections, 2016 -2046
Old age dependency ratio
Population ageing will also have an effect on the proportion of the elderly to the
working population. The old age dependency ratio, which is a ratio of the number of
people aged 65 and over to the working population aged 15-64, is set to continue
increasing in the coming years. In 2013, this ratio was 18.8%. This will increase to
21.3% in 2017 and to 23.7% by 2021.
Projected growth in population aged 65 and over
Over the next few years, the population aged 65 and over will increase by
approximately 20,000 per year. While there was a 14% rise in the 65 and over
population between Census 2006 and Census 2011, growth in the older age groups
will be approximately 21% in the period 2011 to 2017. By 2021, the population over
the age of 65 will have increased by close to 40% since 2011, representing an
additional 200,000 people (see Figure 6).
In previous years, prior to 2007, the overall increase in population represented the
greatest challenge but this has now slowed markedly (see Figure 2). Between 2014
and 2017, the national population is expected to increase by approximately 2%. In
fact, the population under the age of 65 is expected to remain almost unchanged
between 2014 and 2017 (0.9% growth) while the population aged 65 and over will
increase by 9.9% (see appendix).
18
Figure 6: Annual growth in numbers and percentage increases for older age
groups, 2011 to 2021
800,000
37.7%
29.2%
700,000
21.1%
6.9%
600,000
13.8%
Number
500,000
Total over 65
65 - 74
400,000
75 - 84
300,000
85 and over
200,000
100,000
0
2011
2013
2015
2017
2019
2021
Source: CSO –– Population Estimates and “Population and Labour Force
Projections, 2016 -2046”.
Note: the increases quoted are cumulative percentage increases in the numbers aged 65 and over from
2011.
19
Projected Population Ageing in EU
Very significant population ageing has taken place across Europe in recent decades.
Ireland is at an earlier stage of a similar process and is now experiencing population
ageing at a greater rate than most other EU countries. The percentage increase in
population over the age of 65 will continue to grow in the coming years at a higher
rate than the average for the EU. The number of people over the age of 65 in Ireland
is expected to increase by about a quarter by 2021 compared with a 15% rise for the
EU as a whole (see Figure 7). It should be noted that these EU-wide projections were
produced by Eurostat in 2013 and differ slightly from the CSO national projections
used for the analysis in this report due to different assumptions being used by
Eurostat.
Figure 7: Projected percentage population growth in the 65 years and older age
group, Ireland compared with EU-28 average and selected EU countries, 2013 to
2021
25%
24.1%
EU-28
Belgium
21.0%
Ireland
20%
Greece
17.8%
France
Netherlands
15%
14.8%
United Kingdom
11.6%
10%
8.6%
5.7%
5%
2.6%
0
0%
2013
2014
2015
2016
2017
2018
2019
Source: Eurostat Population Projections (EUROPOP 2013)
Note: the increases quoted are cumulative percentage increases from 2013.
20
2020
2021
Fertility and births
At the other end of the age spectrum, Ireland has experienced high rates of fertility by
EU standards for many years (see Figure 8) and this continues to be the case (see
Figure 9).
Figure 8: Total Fertility Rate (TFR), Ireland and EU-28 average, 2003 to 2012
2.5
Total Fertility Rate
2.0
1.5
EU-28
Ireland
1.0
0.5
0.0
2003 2004 2005 2006 2007 2008 2009 2010 2011 2012
Source: Eurostat
21
Figure 9: Total Fertility Rate (TFR) in Ireland compared with other EU
countries, 2012
France
Ireland
United Kingdom
Sweden
Finland
Belgium
Denmark
Netherlands
Lithuania
Slovenia
EU-28
Luxembourg
Estonia
Romania
Croatia
Bulgaria
Czech Republic
Austria
Latvia
Malta
Italy
Cyprus
Germany
Slovakia
Hungary
Greece
Spain
Poland
Portugal
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
2.0
Total Fertility Rate
Source: Eurostat
In contrast with the older age groups, the numbers of births is expected to fall over the
next decade even if fertility remains at its current relatively high rate (see Figure 10).
This is because, despite the high fertility, numbers of women in the child-bearing age
cohorts are declining year on year. The population projections published by the CSO
earlier last year has two fertility scenarios. The high fertility scenario (F1) assumes
the total fertility rate (TFR) will remain at the level observed in 2010 of 2.1 for the
lifetime of the projections up to 2046. The low fertility scenario (F2) assumes the
TFR will decrease linearly from 2.1 to 1.8 by 2026, and then stabilise at this level
until the end of the projection period in 2046.
The low fertility assumption (F2) has been used in this report on the basis that it may
be reasonable to expect some convergence with EU norms over the full projection
22
period. In any event, for the period of principal concern, total births are expected to
decline in the coming years based on the scenario chosen for this report (M2F2).
Figure 10: Total number of births, 2003 to 2012 and projected number of births
2013-2021
80,000
70,000
Number of births
60,000
50,000
40,000
30,000
Actual
Projected
20,000
10,000
-
Sources: CSO –– “Population and Labour Force Projections, 2016 - 2046” and
CSO––Vital Statistics Reports
Note: Projected number of births in above graph is based on the M2F2 scenario. Depending on scenario
chosen, the number of births in 2021 is projected to be in the range of 57-66 thousand.
23
Section 3 Top Down Estimate of Total Demographic Effect
on Health Care Costs
In order to estimate the effect of demographic change on total public health care costs
over the next year, a measure is required of the relative cost of treatment by age
group. A breakdown of cost by age group can then be estimated and rolled forward
taking account of increases in population and changes in population structure (e.g.
population ageing). In this top down estimate of pure demographic effect, it is
assumed that all other factors influencing costs remain unchanged.
There is currently no consensus on the extent to which population ageing necessarily
results in proportionally higher health expenditure. As life expectancy continues to
increase there is ongoing debate as to whether this will result in increasing morbidity
and disability (termed: “expansion of morbidity”), whether it will mean that poor
health is deferred until later in life with a significant proportion of lifetime health care
costs occurring in the last year of life (termed: “compression of morbidity”), or
whether a combination of effects is at play (termed: “dynamic equilibrium”). The
first scenario could result in rising costs with an ageing population; the second could
potentially result in reduced costs; the third might balance out the first two scenarios.
The 2012 Ageing Report, produced by the European Commission, models these
scenarios up to 2060, and it is clear that over several decades, assumptions concerning
“lifetime health status” can have a significant influence on health care costs.
However, as indicated, these issues remain matters of some contention, and, in any
event, over the short time frame of this paper (2014 to 2015) any effects are not likely
to be significant. The main health status-related cost driver of pure demographic
change between 2014 and 2015 is the rapidly increasing numbers of people in the
older age groups rather than any gradual long term projected changes in age-specific
morbidity or mortality.
Of course, a range of other important factors influence health care costs and
expenditure, not least the amount of money available at national and personal levels to
devote to health services. Other significant factors include medical inflation, public
expectation, utilisation of and access to health services, and health policy and
structural change. The present exercise assumes that all these variables remain
constant over the projection period. Its purpose is to provide a measure of the annual
24
incremental cost pressure due purely to the size and, more particularly, to the
increasing age of the population over the next year. Whether budgets are reduced,
increased, or remain unchanged, this cost pressure remains, and if it is not taken into
account accumulates over time (see Section 11 for a representation of cumulative
effect). Over the short time frame (2014 to 2015) of this report, unit costs and
utilisation rates are unlikely to change significantly, and both cost pressures, in
percentage terms, and the actual additional cost required to maintain service levels are
likely to provide useful estimates.
Modelling relative health care costs by age and gender
The 2012 Ageing Report published by the EU Commission collected data on agespecific health care costs from across the EU. Data on the original EU15 countries
which had detailed costing data by age available demonstrated significant agreement
on relative per capita health care costs by age and sex (Figures 11 and 12). Ireland
was not in a position to provide age and sex specific costing data and its cost profile
was estimated by averaging across EU15 countries. These estimates are included in
Figures 11 and 12.
Figure 11: Relative per capita public health expenditure by age group for
females, EU 15 and Norway.
Source: The 2012 Ageing Report, EU Commission (2012) (Data received directly
from ECFIN).
25
Figure 12: Relative per capita public health expenditure by age group for males,
EU 15 and Norway.
Source: The 2012 Ageing Report, EU Commission (2012) (Data received directly
from ECFIN).
Access to the raw estimated data for Ireland on which the authors of The 2012 Ageing
Report based their calculations allowed the derivation of cost relativities by age and
gender for Ireland. This data was then normalised so that average expenditure per
capita equated to a value of 1. Figure 13 displays these results, and, for example,
indicates that average per capita annual public expenditure on health for a female aged
85 or over is approximately 3 times higher than the per capita expenditure across all
age groups for females. As expected, the data also show somewhat higher relativities
for females compared with males for the principal childbearing years between the
ages of 20 and 39.
26
Figure 13: Relative per capita public health expenditure by age group and
gender for Ireland.
4.00
3.50
Realtive Expenditure per Capita
3.00
2.50
2.00
1.50
1.00
0.50
Males
Females
Irish Total
Average for Entire Population
Source: The 2012 Ageing Report, EU Commission (2012) (Data received directly
from ECFIN).
Once these relativities have been derived, the projected population for Ireland by age
group and gender can be applied to produce an estimate of annual changes in cost
pressures due solely to population growth and ageing (see Appendix B for data tables
and further methodological information). As indicated previously, this assumes no
change in utilisation rates, eligibility, and medical inflation etc. over the period.
Under these conditions, the results show cumulative increases in cost pressures
directly attributable to demographic change rising to 11.3% by 2021. This largely
reflects a continuation of population ageing over the period (see Figure 14). From
2014 to 2015, a demographically driven cost pressure of 1.3% is calculated (see
Appendix B). It should be noted that this is 2.2 times greater than the projected
overall increase in population of 0.6% and reflects both the higher relative costs and
the larger relative population increases in the older age groups.
27
85 years and over
80 - 84 years
75 - 79 years
70 - 74 years
65 - 69 years
60 - 64 years
55 - 59 years
50 - 54 years
45 - 49 years
40 - 44 years
35 - 39 years
30 - 34 years
25 - 29 years
20 - 24 years
15 - 19 years
10 - 14 years
5 - 9 years
1-4 years
Under 1 year
-
Figure 14: Projected percentage increases in overall health service cost
pressures based on pure demographic effect, 2013 to 2021
Source: CSO and 2012 Ageing Report: European Commission (2012) (Data
received directly from ECFIN).
Older age groups
Focussing on the over 65 years of age category shows markedly higher annual
increases. This reflects population ageing and explains why the cumulative cost
pressure over the period to 2021 is approximately 30% for the older age groups (see
Figure 15). This has particular relevance for services, such as long term care, which
are utilised principally by older people (see Section 9). It is also significant for acute
hospital services where admission rates and case complexity tend to increase with age
(see Section 5).
28
Figure 15: Annual percentage change in cost pressures based on pure
demographic effects ages 65+, 2013 to 2021
Source: CSO and 2012 Ageing Report: European Commission (2012) (Data
received directly from ECFIN).
Projected cost pressure: 2014 to 2015
The application of these estimated age and gender-specific cost relativities to the Irish
population data indicates, as derived above, that a 1.3% upward adjustment in public
health spending would be required for 2015 in order to take account of the pure
demographic effect. In other words, the older and marginally larger population in
2015 compared with 2014 would require an additional 1.3% in public health service
resources in order to deliver the same level of service (i.e. same utilisation, eligibility
etc.) at the same unit cost as in 2014. In monetary terms, this level of increase on
2014 allocated expenditure for the Health Service Executive (€12.8 billion) equates to
an additional funding requirement of €166 million.
29
Section 4: Utilisation Rates
The estimates of demographic cost pressures set out in this paper are largely based on
the presupposition of stable unit costs and rates of utilisation by age group across the
range of publicly provided health services. The absence of such stability, for example
related to cost containment measures, does not negate the existence of demographic
pressures but it does mean that calculations of cost requirements needed to address
those pressures could be either overstated or understated. Subsequent sections of this
paper will look at specific areas of the health services with a view to estimating
demographic pressures where age-specific rates and costs are available. In advance of
this it is useful to examine some trends in the area of age-specific utilisation in order
to assess whether the assumption of stability in utilisation seems reasonable. Even
where changes in patterns of utilisation are apparent, it needs to be emphasised that
the focus of this paper is on what is likely to happen next year, and single year shifts
in utilisation are unlikely to be large. In addition, most trends in utilisation rates by
age, as will be seen, have been upward in recent years which means that the
assumption of stability may be more likely to underestimate the underlying
demographic pressures on service provision. The exception to this trend is in the area
of psychiatric hospital utilisation where it has been the policy over many years to
reduce reliance on inpatient care for psychiatric conditions and to move toward
community based services. However, even in this area of care reductions in utilisation
have moderated in recent years and the assumption of limited change between 2014
and 2015 appears reasonable. Again, the focus on a single year is perhaps the best
guarantee of arriving at a reasonably accurate projection of demand.
Utilisation of hospital care
The most comprehensive source for acute public hospital inpatient data is the Hospital
InPatient Enquiry (HIPE) system which is administered by the Healthcare Pricing
Office (formerly the Economic and Social Research Institute) and which captures
detailed information on every discharge (inpatient and daycase) from publicly-funded
acute hospitals. Figure 16 shows the total annual discharge rates per 1,000 population
by age group for 2008 and 2013 respectively and indicates increasing utilisation. It
includes both inpatients and daycases and the increase in the discharge rate largely
reflects the higher volumes of treatment now being carried out on a day case basis.
30
Expressed as total bed days per 1,000 population, where each day case is counted as 1
bed day, discharge rates have not fluctuated significantly in recent years. For present
purposes it is sufficient to draw attention to the consistent age-related utilisation rates
over the period and to the likelihood of very similar rates applying to activity in both
2014 and 2015. Any model aimed at making medium term projections over several
years would need to take account of the changing balance in hospital admissions
towards treatment on a day case basis.
Figure 16: Total inpatient and daycase discharge rates per 1,000 population,
2008 and 2013
600
Rate per thousand population
500
400
300
2008
2013
200
100
Under 1 1-14
15-24
25-34
35-44
45-54
55-64
65-74
75-84
85+
Age Category
Source: Hospital In-Patient Enquiry, 2008 and 2013.
With respect to outpatient care, detailed data on age-specific usage is not available.
However, self-reported survey based data was collected in a Health Module carried
out by the Central Statistics Office in both 2007 and 2010. Figure 17 shows the
percentage of respondents by age reporting at least one outpatient attendance during
the previous 12 months. There has been an increase in utilisation over the period for
all age groups with the exception of 18 to 24 year olds, but overall there is a very
close correspondence in relativities by age between 2008 and 2013.
31
Figure 17: Percentage of adults with 1 or more outpatient attendance in the 12
months prior to interview, by age group (over 17 years)
33%
30%
28%
30%
25%
23%
20%
19%
20%
18%
17%
12%
11%
18-24
15%
13%
25-34
35-44
45-54
55-64
65-69
70+
Total
Age Group
Q3 2007
Q3 2010
Source: CSO, Quarterly National Household Survey (QNHS), Health Modules,
2007 and 2010.
Utilisation of primary care
The CSO surveys in 2007 and 2010 also asked questions regarding GP consultations
for medical card holders who are entitled to fully-subsidised GP care. However, since
GPs are paid on a capitation basis rather than on fee-per-visit, it is more relevant to
measure utilisation in terms of population-based trends in medical card cover by age
group. The percentage of the population covered by a medical card by age group in
2012 and 2013 is set out in Figure 18. This shows increasing levels of coverage for
all age groups with the exception of the 70+ age groups where coverage remains close
to 100%. Access to a medical card is means-tested, and overall medical card coverage
has increased from 28% of the population 10 years ago to almost 41% in 2013 (see
Figure 19). It should be emphasised that the pure demographic effect on Primary
Care Reimbursement Services (PCRS) costs calculated in this paper (see Section 6)
does not take account of any potential change in medical card coverage in 2015.
32
Percentage of population with a Medical Card
Figure 18: Percentage of persons with a medical card by age category, 2012 and
2013
100%
90%
80%
70%
60%
50%
40%
2012
30%
2013
20%
10%
0%
Age Category
Source: Primary Care Reimbursement Service (PCRS).
Figure 19: Number of medical cards and percentage of the population holding a
medical card, 2004-2013
45%
1,800
40%
1,700
1,600
35%
1,500
1,400
30%
1,300
1,200
25%
1,100
1,000
20%
2004
2005
2006
2007
2008
2009
Number of Medical Cards
2010
2011
2012
2013
Percentage of Population
Source: Health Service Executive (HSE) Performance Reports (various) for
medical card numbers and CSO for general population.
33
Percentage of population with a Medical Card
Number of persons with a Medical Card ('000s)
1,900
Utilisation of mental health services
As noted earlier, the trend in psychiatric hospital utilisation has been downward as the
policy over many years is to reduce reliance on inpatient care for psychiatric
conditions and to move toward community based services. Figure 20 below illustrates
the trend between 2007 and 2012 for admission rates to psychiatric hospitals. This
shows continued gradual declines for most age groups over this 5 year period.
Calculation of the demographic cost pressure for this area (see Section 7) presumes
stability in utilisation rates between 2014 and 2015.
Figure 20: Admission rate per 100,000 population to psychiatric hospitals by age
category, 2007 and 2012.
Admission Rate per 100,000 population
800
700
600
500
400
2007
300
2012
200
100
0
under
18
18-19
20-24
25-34
35-44
45-54
55-64
65-74 75 and
over
Age Category
Source: The National Psychiatric In-Patient Reporting System (NPIRS), HRB and
CSO for population data.
Utilisation of disability services
Data on service usage in the areas of physical and sensory disability as well as
intellectual disability by age group are available from two databases respectively: the
National Physical and Sensory Disability Database (NPSDD) and the National
Intellectual Disability Database (NIDD). It should be noted that inclusion of clients
on these information systems is voluntary. While the information needs to be
34
interpreted with caution to the extent that it may not be an accurate reflection of
population-based prevalence or unmet need, it nevertheless demonstrates reasonable
stability in age-specific service utilisation in both sectors since 2008, however there
has been a reduction in the number of people registered with the NPSDD.
Figure 21: Numbers of persons registered on the National Physical and Sensory
Disability Database (NPSDD), 2008 and 2013.
Number of persons registered with the NPSDD
30,000
25,000
20,000
15,000
2008
2013
10,000
5,000
0
0-4
5-12
13-17
Note: 2013 data are provisional.
18-24
25-39
Age Category
Source: Health Research Board.
35
40-59
60-65
Total
Figure 22: Numbers of persons registered on the National Intellectual Disability
Database (NIDD), 2008 and 2013.
Number of persons registered on the NIDD
30,000
25,000
20,000
15,000
2008
2013
10,000
5,000
0
0-4
5-9
10-14
Note: 2013 data is provisional.
15-19
20-34
35-54
55+
Total
Age Category
Source: Health Research Board.
Utilisation of nursing home care
Reasonably stable patterns of utilisation over the past few years are observable for
nursing home care based on comparison of data from the Censuses of Population in
2006 and 2011 (see Figure 23). In fact, all of the older age groups show some
percentage increase in population based age-specific utilisation of nursing home care.
Later in this paper demographic projections are derived for utilisation and associated
cost in the provision of services under the Nursing Homes Support Scheme. The
Census based results in Figure 23 provide a level of confidence in rolling forward
population-based utilisation rates based on age-specific Nursing Homes Support
Scheme data for 2014 through to 2015.
36
Figure 23: Percentage of each age cohort in nursing homes, censuses of
population, 2006 and 2011
Percentage of Persons in Nursing Homes
20%
17.6%
18%
16.0%
16%
14%
12%
10%
8%
6.3% 6.8%
6%
4%
2%
2.7% 2.9%
0.1% 0.1%
0.6% 0.7%
1.2% 1.3%
0.5% 0.6%
0%
Under 65
years old
65 - 69 years 70 - 74 years 75 - 79 years 80 - 84 years 85 years and
above
Year
2006
Source: Census of Population, 2006 and 2011.
37
2011
Total
Section 5 Demographic Effect on Acute Hospital Casemix
Costs
Activity and costs by age group for publicly-funded acute hospitals is available from
the Hospital Inpatient Enquiry (HIPE) and from the casemix system. Under the
assumption that hospital discharge rates, unit costs and the ratios between inpatients
and daycases remain stable between 2014 and 2015, this data can be used to estimate
levels of activity and associated costs. The graphics displayed in this as in other
sections extends the analysis out to 2021 for the purposes of illustrating the potential
trend in the absence of changes in either cost structure or utilisation patterns. Of
course, this should not be taken to be a realistic scenario in the longer term. The
principal focus is on the level of demographic pressure which will arise between this
year and next year, and over that short term time scale the assumptions of stability in
utilisation and costs provide a reasonable benchmark. In the case of service utilisation,
the previous section demonstrates that there has been no reduction in acute hospital
use by age group in recent years. The grouping of cases into Diagnosis Related
Groups (DRGs) allows a casemix relative value to be assigned to each case. The DRG
cost weights are based on Irish costing data derived from the national patient-level
costing (PLC) project. This involves obtaining detailed costs by patient from a
representative sub-sample of Irish hospitals. 2011 was the first year for which Irish
PLC-derived cost weights were the primary source for setting weights and it has
continued since. Use of cost weights based principally on Irish data serves to
strengthen the validity of the estimates in this paper.
The casemix relative values represent the relative cost of each DRG. These values
can then be used to derive a set of cost relativities by age group for acute hospital
care. This exercise has been undertaken separately for inpatient and day case care and
the results are presented below (see Appendix C for data tables and further
methodological information).
Projected Inpatient Costs
Considering inpatients first, the graph below shows the relative cost of providing
inpatient care by age group where a value of 1 represents the overall average cost (see
Figure 24). The relative cost of care is around 1.4 for infants under 1 year of age, then
38
falls steeply to values of around 0.6 for ages up to 39 years, followed by a steady rise
to a value of just under 1.6 for those 85 years of age and over.
Figure 24: Relative cost of inpatient treatment (casemix index) by age category,
2013
1.8
Casemix Index
1.6
1.4
1.2
1
0.8
0.6
0.4
0.2
0
Under 1 5 - 9 years
year
15 - 19
years
25 - 29
years
35 - 39
years
45 - 49
years
55 - 59
years
65 - 69
years
75 - 79
years
85 years
and over
Age Category
Source: Healthcare Pricing Office.
The casemix data above can then be matched with data on age-specific discharge rates
in order to obtain estimates of total inpatient costs for each age group. The
relationship between discharge rates and age is shown in Figure 25. It is evident that
discharge rates rise much more steeply with age than do the associated costs. It
should be noted that Figure 25 does not present the same data as Figure 16 above
since the latter includes both inpatients and daycases.
39
Figure 25: Inpatient discharge rate per 1,000 population by age category, 2013
600
Rate of Discharge
500
400
300
200
100
-
Age Category
Source: Healthcare Pricing Office (HPO)
Keeping the casemix indices and the age-specific discharge rates constant, the values
for each age group can be applied to the projected populations up to the year 2021 in
order to obtain a forecast trend in total inpatient costs based on a pure demographic
effect. This is shown in Figure 26.
Figure 26: Projected percentage increases in inpatient cost pressures based on
demographic effect, 2013 to 2021
14.0%
13.2%
12.0%
Percentage Increase Since 2013
11.2%
10.0%
9.3%
8.0%
7.5%
6.0%
5.8%
4.2%
4.0%
2.7%
2.0%
1.4%
0.0%
0.0%
2013
2014
2015
2016
Source: HPO and CSO.
40
2017
2018
2019
2020
2021
As expected, the steepest rises in cost pressures occur in the older groups reflecting
the combination of higher utilisation rates with age, higher casemix-based costs with
age, and rapid population ageing. The trend in projected inpatient costs for those over
the age of 65 is shown in Figure 27.
Figure 27: Projected percentage increases in inpatient cost pressures based on
demographic effect 65+ age group, 2013 to 2021
35.0%
31.3%
Percentage Increase Since 2013
30.0%
26.8%
25.0%
22.4%
20.0%
18.3%
15.0%
14.2%
10.5%
10.0%
6.8%
5.0%
3.5%
0.0%
0.0%
2013
2014
2015
2016
2017
2018
2019
2020
2021
Source: HPO and CSO.
Projected Day Case Costs
The pattern of relative costs and of hospital discharge rates by age group is very
different for day cases as compared with inpatients. In fact, relative costs decline with
age (with the exception of the very young), and discharge rates, while increasing up to
the age of 79, decrease thereafter. Figures 28 and 29 display relative costs and
discharge rates by age respectively.
41
Figure 28: Casemix index by age group, daycases, 2013
1.6
Casemix Index
1.4
1.2
1
0.8
0.6
0.4
0.2
0
Under 1 5 - 9 years
year
15 - 19
years
25 - 29
years
35 - 39
years
45 - 49
years
55 - 59
years
65 - 69
years
75 - 79
years
85 years
and over
Age Category
Source: HPO.
Figure 29: Daycase discharge rate per 1,000 population by age group, 2013
Source: HPO.
Using this data to project daycase costs up to 2021 results in a trend very similar to
that of inpatient costs for both all ages and for the 65+ age group. The reason for this,
42
despite the very different cost structure and pattern of discharges, appears to be that
the very marginal decline in relative cost by age is offset by the steep rise in discharge
rates in the large age cohorts up to the age of 79. Projecting this forward results in a
significant population ageing effect (see Figures 30 and 31).
Figure 30: Projected percentage increase in daycase cost pressures based on
demographic effect, 2013 to 2021
14.0%
12.9%
12.0%
Percentage Increase Since 2013
11.1%
10.0%
9.3%
8.0%
7.6%
6.0%
5.9%
4.3%
4.0%
2.8%
2.0%
1.4%
0.0%
0.0%
2013
2014
2015
2016
2017
2018
2019
2020
2021
Source: HPO and CSO.
Figure 31: Projected percentage increase in daycase cost pressures based on
demographic effect, aged 65+, 2013 to 2021
35.0%
Percentage Increase Since 2013
30.0%
29.5%
25.4%
25.0%
21.3%
20.0%
17.4%
15.0%
13.4%
10.0%
9.9%
6.4%
5.0%
3.0%
0.0%
0.0%
2013
2014
2015
2016
Source: HPO and CSO.
43
2017
2018
2019
2020
2021
Projected total hospital inpatient and daycase activity and costs
Combining inpatient and daycase discharges provides a view of total cost pressures
facing publicly funded acute hospitals in managing their inpatient workloads over the
period to 2021. This shows average annual demographically driven pressures of
around 1.7% for the years from 2013 to 2021 with a rising rate reflecting the
acceleration in population ageing over the period (see Figure 32). From 2014 to 2015,
which is the focus of this paper, cost pressures of 1.4% are predicted. Figure 33
presents the same information for the population aged 65 years and over.
Figure 32: Total inpatient and daycase cost pressures, 2013 to 2021.
16%
14%
13.4%
Percentage Increase Since 2013
12%
11.4%
10%
9.5%
8%
7.7%
6%
6.0%
4.4%
4%
2.8%
2%
1.5%
0%
0%
2013
2014
2015
2016
Source: HPO and CSO.
44
2017
2018
2019
2020
2021
Figure 33: Total inpatient and daycase cost pressures, for aged 65 years old and
over, 2013 to 2021
35%
31.1%
30%
Percentage Increase Since 2013
26.6%
25%
22.3%
20%
18.1%
15%
14.1%
10.4%
10%
6.8%
5%
3.4%
0%
0%
2013
2014
2015
2016
2017
2018
2019
2020
Source: HPO and CSO.
It is instructive to compare the calculated incremental cost pressures over the period
with projections of additional numbers of daycases and inpatients. The fact that the
annual increment in numbers is somewhat less than the cost increments is a reflection
of the shift in population to the older and somewhat more resource intensive age
groups for inpatient care in particular. Figure 34 displays this trend. Although not
included in the present model, it is clear that continuing progress in treating higher
proportions of appropriate patients on a day case basis will have the effect of
lessening these pressures.
45
2021
Figure 34: Projected inpatient and daycase discharges based on demographic
effect from 2013 to 2021.
Source: HPO and CSO.
Finally, it is useful to display the accumulating demographic cost pressures against the
actual reductions in hospital funding (based on casemix costs) since 2008 (see Figure
35). Further reductions in overall health service funding are projected up to 2014 and
while these have not been incorporated into Figure 35 their cumulative effects taken
together with the projected population effects are considered in Section 11 below.
46
Figure 35: Actual casemix spend, 2008 to 2013, and projected demographic cost
pressures, 2014 to 2021, by age group.
Actual
Spend
4,000,000
Estimated
Spend
3,500,000
Expenditure thousands of Euro
3,000,000
2,500,000
2,000,000
1,500,000
1,000,000
500,000
2008
2009
2010
Under 1 year
1-4 years
2011
5 - 14 years
2012
15 - 44 years
2013
45 - 64 years
2014
2015
65 - 69 years
2016
70 - 74 years
2017
75 - 79 years
2018
80 - 84 years
2019
85 years and over
Source: HPO and CSO.
Projected cost pressure: 2014 to 2015
The above analysis indicates that a demographic cost pressure of 1.4% is applicable
for the period of 2014 to 2015 (see Appendix C, Table C5). Again, this assumes no
change in either utilisation or in the cost structure of the public acute hospital system.
It should also be noted that the projected decline in numbers of births from 2014 to
2015 is incorporated into the analysis in terms of a reduction in maternity hospital
costs. Application of this result to the 2014 total allocation of €3,256 billion
estimated to be included in the casemix system indicates that additional funding of
€46 million will be required to maintain the same levels of utilisation at the same unit
costs. It is important to make the general point here, which applies across all areas of
service provision, that if reductions in expenditure can be achieved in 2015 without
affecting the levels of public service provision that this does not imply that the
underlying demographic pressure does not need to be taken into account. For
example, reduction in spending of 5% would simply have the effect of applying a
similar reduction to the additional cost associated with population growth and ageing.
47
2020
2021
Section 6: Demographic Effect on Schemes under the
Primary Care Reimbursement Service (PCRS)
The Primary Care Reimbursement Service (PCRS) pays GPs, dentists, pharmacists
and other professionals for services provided, either free of charge or at reduced rates,
to eligible members of the public. In 2013, the total spend of the PCRS was
approximately €2.4 billion euro1. Of this sum, by far the largest portion (69%) related
to payments made under the General Medical Services (GMS) heading2. The GMS
refers to services provided to people who hold medical cards as a result of a meanstested evaluation. In addition to the GMS, the PCRS also funds a range of demandled schemes such as the Long Term Illness (LTI) scheme, Drug Payment Scheme
(DPS), Dental Treatment Services Scheme (DTSS), and the Ophthalmic Services
Scheme.
Finally, there are a number of other services paid for by the PCRS for
eligible clients.
Demographic cost pressures on PCRS payments can be expected to be significantly
higher than the general projected population increase. The reason for this is that both
eligibility/utilisation as well as per capita cost of provision increase with age for many
of the payment schemes. In relation to medical card (GMS) services, Figure 36 below
shows the relationship between medical card coverage rates and age. The percentage
of older persons with medical cards is significantly higher than the average population
as the medical card is means tested and those over 65 have higher limits and generally
have lower incomes. Whereas 17% of the general population are over the age of 60,
28% of medical card holders are over 60 years of age. At present, approximately 40%
of the population is covered under the medical card scheme. This has risen from just
under 30% in 2007. As discussed below, however, the estimated cost pressures
presented in this paper assume that the percentage remains fixed at 40% over the
projection period.
1
2
HSE December 2013 Management Data Report
All payments to doctors plus payments to pharmacists under the GMS Scheme
48
Percentage of population with a Medical Card
Figure 36: Percentage of persons covered by a medical card by age category,
April 2013
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
Age Category
Source: CSO for population figures and PCRS for medical card numbers.
In addition to coverage, there is also a positive correlation between age and cost of
service provision. This is most pronounced in the area of pharmaceutical costs (see
Figure 37) but is also evident to varying degrees across other service areas, e.g.
capitation rates for GP services.
49
Figure 37: Average annual cost per medical card holder, in euro, of GMS
pharmaceutical schemes, 2013
Average Cost per Medical Card Holder
€1,400
€1,200
GMS
Pharmaceutical
Ingredient Costs
€1,000
€800
GMS
Pharmaceutical
Pharmacy Fees
€600
€400
€200
80 - 84
75 - 79
70 - 74
85 and over
Age Group
65 - 69
60 - 64
55 - 59
50 - 54
45 - 49
40 - 44
35 - 39
30 - 34
25 - 29
20 - 24
15 - 19
10-14
5-9
0-4
€0
Source: Monthly data submissions from PCRS to Department of Health
For the purposes of the present exercise, data from regular monthly data submissions
to the Department of Health for 2013 has been used. From these data, age-specific
utilisation and costs have been calculated for a number of services. These services are
listed below categorised as either falling under the GMS medical card or as nonmedical card GMS services. The total annual cost associated with each service has
been calculated from the monthly data submissions and is indicated in brackets. The
Department began receiving monthly data for non-medical card schemes by age group
from July 2013. These 6 months of data have been grossed up to estimate the total for
2013 in this analysis.
GMS Medical Card
(i)
GMS Pharmaceutical Ingredient Costs - payments made to Pharmacists
(excluding VAT) in relation to eligible individuals (€840 million);
(ii)
GMS Pharmaceutical Pharmacy Fees - payments made to Pharmacists in
relation to eligible individuals (€320 million);
50
(iii)
GP Visit Card Capitation Fee - payments made to GPs in relation to
eligible individuals (€11 million);
(iv)
Medical Card Capitation Fee - payments made to GPs in relation to
eligible individuals (€222 million);
(v)
Other GMS Fees paid to GPs in relation to eligible individuals (€34
million);
(vi)
Out of Hours Service Fee - payments made to GPs in relation to eligible
individuals (€34 million).
Non-Medical Card GMS3
(i)
Long Term Illness Scheme (€100 million)
(ii)
Dental Treatment Services (€65 million)
(iii)
Community Ophthalmic Scheme (€32 million)
(iv)
Drug Payment Scheme (€168 million).
Other payments, for example payment to GPs in relation to sick/study/annual leave,
are unrelated to age-specific utilisation and in the case of certain services, for example
subsidy of High Tech medicines, use and cost data by age are not currently available.
Nevertheless, services for which age-specific cost and utilisation are available account
for approximately €1.8 billion or 75% of the estimated €2.4 billion PCRS expenditure
in 2013.
Methodology
The availability of age-specific cost and utilisation data for each of the 10 specific
services listed above allows for the calculation of population-based per capita costs by
5-year age group. Per capita costs across the national population by age are held
constant over the projection period which assumes that both the cost structure and
rates of utilisation (e.g. percentage of population in receipt of a medical card) remain
unchanged. The application of population projections by age to these per capita costs
results in year on year estimates of total costs by service type and by age group.
Summing these cost estimates across all age groups and services gives the projected
pure demographic effect on the total cost of service provision.
3
The Department began receiving data for non-medical card schemes from July 2013. These 6 months
of data have been grossed up to estimate the total for 2013 in this analysis.
51
Results
The projected cost increases due solely to demographic change are displayed in
Figures 38 and 39 below respectively for the GMS Medical Card based schemes and
the other non-medical card GMS schemes.
Figure 38: Projected increase in cost of various GMS medical card payments,
2013 to 2017
10%
9.5%
Percentage increase since 2013
9%
9.0%
8%
8.0%
7%
6%
GMS
Pharmaceutical
Ingredient Costs
GMS
Pharmaceutical
Pharmacy Fees
GP Visit Card
Capitation Fee
5.9%
5%
4.6%
4%
3.2%
2.8%
3%
Medical Card
Capitation Fee
Other GMS Fees
paid to GPs
Out of Hours
Service Fee
2%
1%
Population Increase
0%
2013
2014
2015
2016
2017
Source: PCRS. Analysis by Information Unit, Department of Health.
52
Figure 39: Projected increase in cost of various other GMS payments (NonMedical Card Schemes), 2013 to 2017
10%
9.4%
9%
Percentage increase since 2013
8%
7.7%
7%
6%
5.6%
5%
5.0%
4%
DPS payment to
pharmacists
DTSS - Total
payments to
Dentists
LTI payment to
pharmacists
Optical
3%
2.8%
2%
Population
Increase
1%
0%
2013
2014
2015
2016
2017
Source: PCRS. Analysis by Information Unit, Department of Health.
For illustrative purposes, the projected percentage increase in the general population
has been included in both Figures 38 and 39. It is evident that in all cases the cost
pressures on the various schemes are expected to rise at a more rapid rate than the
population as a whole. The reasons for this relate to both higher eligibility and uptake
of services with increasing age as well as higher per capita costs of service provision
with age. This is illustrated in the discussion section below.
Projected cost pressure: 2014 to 2015
For the purposes of the present exercise, the objective is to estimate the additional cost
required to provide the same level of service taking account of demographic pressures
from 2014 to 2015 at the same unit cost as in 2013. Taking all the GMS medical card
schemes (Figure 38) together, additional funding of 2.1% will be needed to provide
for population growth and ageing. For the non-medical card GMS schemes taken
together (Figure 39), a 1.7% increase in costs is estimated. In total, estimated
additional funding of PCRS of 2.0% would be required to take account of
demographic change between 2014 and 2015 on schemes where age-specific costs are
53
available. This equates to €36.9 million in additional demographically-driven costs. It
should be noted that this figure is based on approximately 75% of the PCRS budget.
Projecting forward to 2017, it is estimated that additional funding of PCRS of 6.4%
above 2014 levels would be required to take account of the demographic pressures
from 2014 to 2017. Cumulatively over the 3 year period, this equates to
approximately €118 million in additional funding to address demographic pressures.
54
Section 7: Demographic Effect on Mental Health Services
Age-specific costs are not available for mental health services, but as noted earlier
utilisation rates by age are available from the National Psychiatric In-Patient
Reporting System (NPIRS). Assuming that the rates experienced in 2012 remain the
same, the projected numbers of admissions are shown in figure 40.
Figure 40: Projected number of admissions to Psychiatric hospitals, 2014 -2020.
19,200
4.7%
Number of Admissions
19,000
3.7%
2.7%
18,800
1.8%
18,600
1.0%
18,400
0.4%
18,200
18,000
17,800
17,600
2014
2015
2016
2017
2018
2019
2020
Source: The National Psychiatric In-Patient Reporting System and CSO Population
Projections 2016 to 2046.
Projected cost pressure: 2014 to 2015
On the assumption that an increase in admissions due to demographic pressure is
representative of the overall demographic cost pressure in mental health services a
projected increase of 0.4%, based on a total allocation in 2014 of €766 million for the
mental health programme, results in an additional demographically-driven cost
pressure of €3.1 million in 2015 based on continuing levels of utilisation.
55
Section 8: Demographic Effect on Disability Services
Age-specific costs are not available for disability services; however utilisation rates
by age are to some degree available from various sources. For example, the Census in
2011 showed that 13% of the population reported some form of disability with higher
proportions in the older age cohorts (see Figure 41). Projecting forward this age
distribution in order to estimate demographic cost pressure, would be likely to
overestimate the cost pressure as the rates are not based on utilisation but rather are
self-reported assessments. However, it may provide an indication of unmet need
which may result in higher future demands on services. Another issue worth noting is
the higher survival rates of complex preterm and neo natal babies which may again
indicate higher future demand for disability services.
Figure 41: Percentage of each age cohort with a self-reported disability, 2011.
Source: Census of Population, 2011.
As noted above, age-specific data on utilisation of disability services are available
from the National Physical and Sensory Disability Database (NPSDD) and from the
56
National Intellectual Disability Database (NIDD). Application of age-specific rates
to projected population change for both these databases is illustrated in Figures 42 and
43 respectively.
Figure 42: Projected number of persons on the National Physical and Sensory
Disability Database (NPSDD), 2013 to 2021
26,500
Number of persons registered with NPSDD
1.2%
26,000
1.2%
1.3%
25,500
1.2%
25,000
1.1%
0.9%
24,500
1.0%
0.9%
24,000
23,500
23,000
22,500
2013
2014
2015
2016
2017
2018
2019
2020
2021
Sources: Health Research Board for 2013 actual numbers and Information Unit,
Department of Health, for 2014-2021 projections.
57
Figure 43: Projected number of persons on the National Intellectual Disability
Database (NIDD), 2013 to 2021
30,000
Number of persons registered with NIDD
0.9%
0.9%
29,500
1.0%
29,000
1.0%
0.8%
28,500
0.7%
0.6%
0.7%
28,000
27,500
27,000
26,500
2013
2014
2015
2016
2017
2018
2019
2020
2021
Sources: Health Research Board for 2013 actual numbers and Information Unit,
Department of Health, for 2014-2021 projections.
Projected cost pressure: 2014 to 2015
On the assumption that the age distribution of clients registered on the NIDD and/or
NPSDD are indicative of service demand by age group in the area of disability, it is
possible to estimate a corresponding demographic cost pressure. The estimated
demographic effects were 0.9% and 0.6% respectively for physical/sensory and
intellectual disability services in 2015. Since the estimated costs in these areas are
divided in a ratio of approximately 70 to 30 between intellectual and physical/sensory
disability services, a blended rate gives an overall demographic effect of 0.7% for
2015. Based on an approved allocation of €1,406 million for the full programme of
disability services for 2014, the projected increase of 0.7% results in an additional
demographically-driven cost pressure of €9.8 million in 2015 based on continuing
levels of utilisation.
58
Section 9: Demographic Effect on Nursing Home Care
The number of persons recorded as resident in nursing homes in the most recent
Census of Population (2011) was 26,265. On the assumption that the populationbased age-specific rates remain stable over the period from 2011 to 2021 it is
estimated that there will be an increase of nearly 9,000 persons or 33% by 2021. More
than half of this increase (4,700) is expected to be in the 85+ age group. Indeed,
longer term trends in nursing home care show the age distribution shifting toward the
more elderly and more highly dependent categories of client. Section 4 on utilisation
of services, shows utilisation rates based on Census data to be somewhat higher in
2011 than in 2006 across all age groups.
Focussing more specifically on estimated demographic pressures on nursing home
care in 2015 based on Census data, it is estimated that there will be an increase of
2.7% in the number of persons requiring nursing home care between 2014 and 2015
(see Figure 44).
Figure 44: Projected numbers of persons in nursing homes by age category: 2014
to 2021
Numbers in Nursing Home
40,000
35,000
30,000
2.7%
5.8%
8.9%
12.1%
2015
2016
2017
2018
15.8%
19.7%
23.7%
2019
2020
2021
25,000
20,000
15,000
10,000
5,000
0
2014
Year
Under 65
65 - 69 years
70 - 74 years
75 - 79 years
80 - 84 years
85 years and over
Source: CSO Population Projections 2016 to 2046 and Census of Population 2011.
59
For the purposes of projecting the demographic cost effect between 2014 and 2015
based on actual public service usage, age-specific utilisation data from the Nursing
Homes Support Scheme (NHSS) for 2014 has been employed. The results are
displayed in Figure 45 below.
Over the short term to 2015, it is estimated that there
will be an additional 3.2% of people on this scheme.
Figure 45: Projected number of publicly funded persons in nursing homes, 2014
to 2021
29,000
27.2%
28,000
22.5%
Projected number of persons
27,000
18.1%
26,000
13.9%
10.2%
25,000
6.7%
24,000
3.2%
23,000
22,000
21,000
20,000
19,000
2014
2015
2016
2017
2018
2019
2020
2021
Source: Fair Deal Section, Health Service Executive, and Information Unit,
Department of Health.
Projected cost pressure: 2014 to 2015
Based on a total cost of €939 million for the Nursing Homes Support Scheme in 2014,
a projected increase of 3.2% results in an additional demographically-driven cost
pressure of €30 million in 2015. This is based on continuing levels of utilisation and
per capita costs.
60
Section 10: Bottom up Estimate of Total Demographic
Effect on Health Care Costs
In Sections 5 to 9 of this paper, the cost implications arising from population growth
and ageing between 2014 and 2015 have been estimated for a number of specific
areas of the health services. The present section extends consideration of demographic
cost pressures to the remaining areas of the health services in order to derive a bottom
up estimate of the total demographic effect on health care costs in 2015. The results
are set out in Table 1.
Methodology
For each area, a low and a high estimate of the projected effect on costs is included. In
general, in areas such as hospital casemix costs and medical card expenditure where
detailed data on age and cost specific utilisation permits an accurate calculation the
low and high figures will not differ. In other areas, where age-specific utilisation data
may be available but not matched by age-related cost, the high estimate will reflect
the age distribution of clients in receipt of the service while the low figure applies a
weighting reflecting general population growth. Similarly, where only total service
costs are available with no age breakdown, consideration is given to the likely age
distribution of clients. For example, where a service (e.g ambulance services)
considered to be disproportionately used by older people the estimates will generally
be based on the overall increase in the older age groups. The rationale behind these
estimates for each area is summarised below.
In interpreting the projected figures in Table 1, it must be reiterated that the pure
demographic approach assumes that all other factors influencing unit costs and
utilisation, such as population health, medical inflation, medical card numbers etc.,
remain unchanged. In many areas, where age-specific data on costs is not currently
obtainable, there is a further inbuilt assumption that per capita costs remain the same
across age groups. Further, the paper focuses on a single year and, therefore, takes no
account of the cumulative effects of demographic change over the preceding years.
The total figures for estimated additional cost, therefore, provide a measure of the
additional cost for the maintenance of publicly provided health services in 2015 based
solely on the existing level and cost of services.
61
Table 1 Estimated demographic cost pressure: percentages and cost by programme, 2015
2014 Budget
€ Millions
Care Group by Programme
Acute
Of which:
Demographic
cost pressure
percentage
High
Low
2015 Budget €
Millions
Demographic cost
pressure € Millions
High
Low
High
Low
Casemix Cost available
Other
4,315
3,256
1,059
1.4
1.4
1.4
1
4,375
3,302
1,074
4,371
3,302
1,070
60
45.6
14.8
56
45.6
10.6
Age Specific Costs available
Other
2,433
1,860
573
2
2
2
0.6
2,482
1,897
584
2,474
1,897
576
48.4
36.9
11.5
40.3
36.9
3.4
Older People
Disability
Corporate Social Care
NHSS
Vote Adjustment
3,055
639
1,406
79
939
-8
3.2
0.7
0.6
3.2
0
3.2
0.2
0
3.2
0
3,116
659
1,416
79
969
-8
3,108
659
1,409
79
969
-8
61
20.4
9.8
0.5
30.0
0.0
53
20.4
2.8
0.0
30.0
0.0
Primary Care
Health and Wellbeing
Mental Health
Ambulance Service
Multi Care Group
Other
726
234
766
139
122
3
0.6
0.6
0.4
3.2
0.6
0.6
0.6
0.6
0.4
3.2
0.6
0.6
730
235
769
143
123
3
730
235
769
143
123
3
4.4
1.4
3.1
4.4
0.7
0.0
4.4
1.4
3.1
4.4
0.7
0.0
Corporate
Statutory Pensions
National Services
Repayment Scheme
204
573
200
8
0.6
2.9
0.6
0
0
2.9
0.6
0
205
590
201
8
204
590
201
8
1.2
16.6
1.2
0.0
0.0
16.6
1.2
0.0
12,778
1.6
1.4
12,981
12,960
203
182
-140
1.3
1.1
-142
-142
-1.8
-1.5
12,638
1.6
1.4
12,839
12,818
201
180
PCRS
Of which:
Social Care
Of which:
Subtotal
Haddington Road
Total
62
Rationale for high and low estimates
The rationale for the assignment of specific percentage increases for each care group and non-care
group category is set out below in the order in which each service area appears in Table 1. The
source for the baseline 2014 budgetary figures by care and non-care group category is the Health
Service Executive (HSE) National Service Plan for 2014.
Care groups
Acute care
The total hospital allocation of € 4,315 million has been divided into two groups:
-
Casemix cost available
-
Other (including outpatient and ED activity)
The allocated budget in each group has been estimated using the percentage of total hospital spend
captured in the most recent casemix model which relates to 2013 activity and cost data. This
indicates that approximately 71% of the total allocation to hospitals relates to inpatient and
daycase activity carried out in the hospitals which participate in the casemix programme. For these
hospitals a projected demographic cost pressure of 1.4% has been calculated in respect of 2015
(see Section 5 and Appendix C for details). Since HIPE data and casemix costs are detailed and
robust, this figure of 1.4% has been used for both the high and low estimates.
While non-casemix hospitals, included in the “Other” category, are not participants in casemix
budget modelling, it is still possible to estimate the demographic effect since each hospital
discharge is assigned to a Diagnostic Related Group (DRG) and each DRG has an associated
relative cost. In fact, when this analysis is carried out it shows that the non-casemix hospitals
have a higher projected demographic cost index than the casemix hospitals (i.e. 1.5% for the noncasemix hospitals compared with 1.4% for the casemix hospitals). This reflects the older age
distribution of patients in these hospitals (see Figure 46). The “Other” category also includes costs
of outpatient and emergency department (ED) attendances both of which can be reasonably
expected to have client age distributions significantly older than the general population. For this
reason, a high estimate of 1.4% has been assigned and a low estimate of 1% has been assigned to
the “Other” category.
63
Figure 46: Age Distribution of discharges from casemix and non-casemix hospitals, 2013
Source: Healthcare Pricing Office.
PCRS
PCRS refers to the Primary Care Reimbursement Service which has responsibility for
reimbursements in relation to medical cards as well as a range of other schemes. The total budget
for the PCRS exceeds €2.4 billion. For the present exercise, these services have been divided into
two categories in Table 1 as follows:
- Age-specific costs available
- Other
The first category refers to repayment services for which age-specific cost and volume data has
been made available. Detailed description and analysis of this data is set out in Section 6 and in
Appendix F. Across all PCRS services with detailed age and cost data, a pure demographic cost
pressure factor of 2% was derived. Again, this represents the additional percentage budget
increment required to provide services at the same level and unit costs in 2015 as in 2014. It
64
encompasses approximately 75% of total PCRS costs. It should be noted that it makes no
provision for the increasing proportions of the population in each age group (under the age of 70)
entitled to a medical card and assumes these proportions remain constant in 2015. Given the
accuracy of the age-specific costs, the figure of 2% has been used as both the high and low
estimate for this category. See Section 6 and Appendix F for details.
For the remaining 25% of PCRS expenditure for which age and cost breakdowns are not currently
available, a high estimate of 2% has been assigned on the basis of similar higher levels of
eligibility and usage by the older age groups across a number of schemes (e.g mobility
allowances, blind welfare allowances and hardship medicines). However, it is also the case that a
proportion of PCRS expenditure in the “Other” group may be less directly related to older age
groups. Again, however, it should be noted that no assumptions have been made about nondemographic cost pressures (e.g. expected increases in High Tech drug expenditure).
In the
absence of detailed data, a low estimate of 0.6%, equivalent to the general projected increase in
population in 2015, has been attached to the “Other” PCRS costs.
Older People
On the basis that in this area, the services are predominantly required by the older age groups both
a high and a low percentage demographic effect of 3.2% has been applied to determine the
expected demographically-driven costs in 2015.
Disability
Age-specific data on utilisation of disability services is available from the National Intellectual
Disability Database (NIDD) and from the National Physical and Sensory Disability Database
(NPSDD). Application of age-specific rates to projected population change in 2015 results in an
estimated demographic effect of 0.9% and 0.6% respectively for 2015. It is estimated that cost in
this area are split approximately 70:30 in favour of persons with intellectual disabilities. Applying
this blend rate gives a demographic effect of 0.7% for 2015. See Section 8 for details.
As both the NIDD and NPSDD are largely restricted to persons under the age of 65, a
conservative figure of 0.2%, corresponding to projected population growth in the under 65 age
groups, has been assigned as the low estimate. The underlying assumptions are that utilisation
rates and per capita costs remain constant and that the latter do not increase with the age of clients
in receipt of services.
65
Corporate Social Care
A high estimate of 0.6% and a low estimate of 0% have been applied in the area of corporate
expenditure. The high figure reflects the overall growth in population; the low figure is based on
the assumption that corporate services is an area not directly related to either population growth or
ageing and where additional efficiencies may be achievable.
Nursing Homes Support Scheme (NHSS) - A Fair Deal
Using age-specific utilisation rates available from the Fair Deal scheme and applying the projected
population for 2015 yields a demographic cost pressure of 3.2% in this area. On the basis that
nursing home care is predominately utilised by the older age groups, this figure of 3.2% has been
used as both the high and low estimate Again, in this as in other areas, the conservative
assumption that per capita costs do not change with client age is inbuilt. See Section 9 for details.
Primary care
Budget allocations in the area of primary care services relate principally to the development of
primary care teams (PCTs) and community intervention services. To the extent that these services
are intended to provide improved primary care across the entire population, the overall projected
population increase of 0.6% has been applied as both the high and the low estimate for the
demographic cost pressure.
Health and Wellbeing
On the basis that expenditure on population health is for the benefit of the entire population, the
general population increase of 0.6% projected for 2015 is used as both the high and low estimate
of demographic cost pressure.
Mental health
Age-specific data on utilisation of mental health services is available from the Health Research
Board’s National Psychiatric In-Patient Reporting System (NPIRS). Application of age-specific
rates to projected population change in 2015 results in an estimated demographic effect of 0.4%
for 2015 and has been applied as both the high and the low estimate of demographic cost pressure
in 2015. See Section 7 for details.
66
Ambulance Service
In the absence of age-specific utilisation data and given the expectation that these services will be
principally required by older age cohorts, the population increase of 3.2% in numbers of people
over the age of 65 in 2015 has been used for both the high and the low estimate of demographic
cost pressure.
Multi Care Group and Other
Since none of these service areas are specifically concentrated on particular age groups, the overall
population increase of 0.6% has been applied as the demographic cost pressure in 2015.
Non-Care Areas
Corporate
A high estimate of 0.6% and a low estimate of 0% have been applied in the area of corporate
expenditure. The high figure reflects the overall growth in population; the low figure is based on
the assumption that corporate services are an area not directly related to either population growth
or ageing and where additional efficiencies may be achievable.
Statutory Pensions
A figure of 2.9% has been applied as both the high and low estimate of additional demographic
cost pressure in 2015. The basis for this is the overall growth in the population over the age of 60
and a corresponding estimated increase in persons with pension entitlements from the HSE.
National Services
In the absence of age-specific utilisation data, the general population increase of 0.6% in 2015 has
been used for both the high and the low estimate of demographic cost pressure.
Haddington Road
A figure of EUR140 million was highlighted in the 2014 Service Plan. The high and low
percentage estimate for the other categories has been averaged and applied to the estimated
Haddington Road savings for 2015.
67
Section 11: Discussion and Conclusions
Although Ireland is no longer experiencing population growth at anything like the high levels seen
during the earlier years of this century, the population is still increasing but at rates which are
similar to average growth across the EU. Where Ireland diverges from the EU average is in the
rate of growth in the older age groups (i.e. 65 years and over) for which the rates of increase are
nearly double those for the EU as a whole. Ireland is now in the midst of relatively rapid
population ageing, and this is a trend which will continue over a number of decades. In many
respects, Ireland is now catching up with trends which have occurred somewhat earlier in other
countries of Europe.
While it includes projections up to 2021, the immediate concern of this paper has been to estimate
the additional cost pressures generated solely by demographic change in 2015. Between 2014 and
2015, the overall population is projected to increase by 0.6% while the population 65 years and
over will increase by 3.2%. These figures are based on the most up-to-date official population
projections for Ireland which were produced by the Central Statistics Office (CSO). A medium
migration assumption (M2) and the low fertility assumption (F2) have been used in this paper. It
should be noted that in focussing on a single year, the choice of assumptions has only a marginal
influence on the projected population, and, in any case, migration and fertility have very little
effect on the older age groups.
The methodological approach adopted in the paper entails the calculation of the pure demographic
effect on health service cost pressures in 2015. It is important to emphasise that this method
assumes that the health services have the same age-specific population-based utilisation rates and
the same unit costs in 2015 as in 2014. In doing so, it effectively presupposes no change in the
range of variables which might be expected to influence utilisation and cost. These factors include,
inter alia, medical inflation, alteration in service structures/eligibility (including medical cards),
stability in population health and wider economic factors (e.g. employment levels). Over the
medium to longer term, this assumption is clearly untenable. Over the course of a single year
(2014 to 2015), the contention is that the presumption of stability provides the best basis for
determining the size and direction of the cost pressures due specifically to changing
demographics. Utilisation rates in recent years have been examined and support the assumption of
year to year stability. The actual cost of providing services to this larger and older population will
then depend on achieving cost reductions, operational efficiencies and also factoring in upward
cost pressures such as medical inflation. The important point is that the demographic cost
68
pressures across the various service areas are quantified and taken into full account in determining
resources required to maintain service levels.
The analysis in this paper continues the significant improvement and extension of work which was
highlighted in last year’s paper. In addition to the availability of official population projections,
the paper benefits from the use of a much wider range of health service data where it has been
possible to obtain a breakdown by age and cost. For example, application of the projected
population by age in 2015 to the PCRS data allows a robust calculation of the pure demographic
pressure on costs for each scheme. Similarly robust analysis has been undertaken on acute
hospital casemix data (accounting for €3.3 billion of expenditure) for which the HIPE system can
be merged with DRG-specific costs to estimate the pure demographic effect. Furthermore, a set of
cost weights is available based on Irish costing data derived from the patient-level costing (PLC)
project. In areas where detailed costs are unavailable, age-specific utilisation data on its own has
been used to estimate the pure demographic effect in other significant service areas such as the
Nursing Homes Support Scheme and mental health services. It should be noted that these
estimates incorporate the conservative assumption that costs do not increase with age.
The method has been extended to produce estimates of the pure effect of demography on cost
pressures for all service areas. Where age-specific data is not currently available, the demographic
effect has been estimated by reference to the expected target client group in specific service areas.
A high and low estimate of demographic effect has been included for each area to specifically take
account of uncertainty in areas where data is scarce. Where information is robust (i.e. casemix
and PCRS), there is no difference between the high and low estimates. Summation of the resulting
cost pressures across all areas provides a bottom up estimate, based exclusively on data from the
Irish health services, of the actual additional expenditure required in 2015 to address demographic
change while maintaining services with similar access and at similar cost.
The results are set out in Table 1 and show a variety of estimates both in terms of percentage cost
pressure and net effect on additional cost. For areas utilised principally by older people the
percentage cost pressure will be higher than the overall population increase of 0.6%; for services
directed at younger people, the cost pressure will be lower than this figure; for services utilised
broadly in proportion across the age groups, the estimate will match population growth of 0.6%.
For the health services as a whole, the estimated total demographic cost pressure in expenditure
terms ranges from a high of €201 million to a low estimate of €180 million.
69
As at least a partial check on the scale of the pure demographic effect, a top down measure has
also been derived based on the same methodology employed last year. This approach uses agespecific cost relativities for the provision of public health services in Ireland which have been
estimated by averaging the relativities across a number of other EU countries which were in a
position to provide age-specific costs for the whole of their services (see The 2012 Ageing Report,
European Commission). Using this data and applying Irish population projections, the total
estimated additional cost in 2015 due to population change works out at €166 million.
While it is to some extent reassuring that top down and bottom up come up with a similar scale of
demographic effect, there are very good reasons for preferring estimates based on our own data
and also for a level of scepticism regarding trusting to European averages. In the first place, for
the present analysis it has been possible to use either age and cost specific data (i.e. casemix and
PCRS) or age-specific data ( i.e. non-casemix hospitals, mental health, disability, Nursing Homes
Support Scheme) for services accounting for approximately two-thirds of total health expenditure.
Secondly, demographic estimates vary by service area and this more detailed analysis is far more
valuable in determining budgets. Thirdly, in terms of top down scepticism, basing policy on
cross-country averages implies a level of similarity between health systems and health system
funding which may be exaggerated. And Ireland’s health system is unique in many ways.
A number of particular characteristics of the health system in Ireland in fact make it likely that the
top down analysis may significantly underestimate the extent of the demographic cost pressure in
Ireland. In comparison with many other European countries, Ireland’s health services encompass
a wider range of social services. For many of these services (e.g. home help) the client base is
largely elderly. In addition, it could be argued that health services in Ireland may be more
focussed, in terms of expenditure, on hospital services (which have a steep utilisation age
gradient) and service for the elderly as well as having a primary care sector where full eligibility is
much higher for those over the age of 70. If this is the case, it would lead to higher overall
relativities for the older age groups and consequently cost pressure resulting in additional cost
greater than the top down estimate of €166 million.
Turning attention back to the demographic estimates based on data from the Irish health system,
there is a strong case to be made for considering the range of estimates derived in the bottom up
approach as set out in Table 1 as constituting minimum values for additional demographic cost
pressures. There are three reasons for this assertion. First, the cost pressures are projected forward
70
to 2015 based on the HSE budget allocation for 2014. They do not take account of actual costs in
2014 which, in some areas, may be higher than the allocated budgets. Second, costs generally rise
with age (e.g. top down relativities for all countries provide evidence of this) and without detailed
age and cost specific data for all services it has not been possible to build this expected rise into
the model. Finally, with a growing and ageing population, demographic pressures are cumulative,
and to the extent that this effect is likely to have been underestimated and/or not provided for
during the last 5 years of successive budget reductions this will have a carryover effect in 2015.
Figure 47 should be seen as illustrative only in that it shows the potential cumulative effective
budget reduction in 2016 assuming no account is taken of demographically driven cost pressures.
Figure 47: Cumulative effective reduction in resources, budget reductions and
demographic deficit combined, 2010 to 2016.
Source: Finance Unit, DoH, for budget data; Top down method for demographic effect (see
Section 3).
In summary, the bottom up estimates of demographic cost pressure derived in this paper should be
seen as essential evidence which needs to be incorporated into planning and resourcing the health
services. Ireland is experiencing rapid population ageing. The population continues to grow and an
additional 20,000 people over the age of 65 are being added to the population of Ireland each year.
The cost of providing for demographic change cannot be treated as an afterthought but needs to be
included as an upfront measure of the additional cost of maintaining services in 2015 and in
subsequent years. Furthermore, the high and low total values in Table 1 should be treated as
71
minimum estimates of that additional cost. In order to realistically evaluate the effects of
reductions in the health service budget, these are costs which need to be added to the total
expenditure required to maintain services. Realised savings and achieved efficiencies will serve to
reduce the demographic cost pressure. Upward pressures such as medical inflation will have the
effect of increasing that pressure. In addition, as identified in the national framework for health
and wellbeing, Healthy Ireland, major risks to health from increases in adverse population trends
related to obesity, diabetes have the potential to reverse the significant gains in life expectancy in
recent decades and to place significant additional burdens on health services. For the future, better
data will permit more accurate estimation. In addition, longer-term models should be developed,
bringing in appropriate health economics expertise, in order to include the most important
variables affecting health costs and to extend the planning capacity of the Department.
72
Appendix A
Projected Population (2011 to 2021)
Projected population (2011 to 2021)
Official population projections were published in 2013 by the Central Statistics Office
(CSO) and were based on the results of the 2011 Census of Population.
The CSO produced eight population projections on the basis of four migration
assumptions and two fertility assumptions.
The most positive assumption (M1) envisages net migration returning to positive by
2016 and rising steadily thereafter to plus 30,000 by 2021. The least positive
assumption (M3) envisages net migration remaining negative for the whole period.
The middle assumption (M2) envisages net migration returning to positive by 2018
and rising thereafter to +10,000 by 2021. An alternative more theoretical assumption
(M0) was also produced which has zero net migration for the entire period. Given the
uncertainty, at this stage, as to which assumption is most likely to be most accurate, it
was felt appropriate to utilise the middle scenario of M2.
The recent population projection has two fertility scenarios. The high fertility
assumption (F1) assumes the total fertility rate will remain at the level observed in
2010 of 2.1 for the lifetime of the projections up to 2046. The low fertility
assumption (F2) assumes the total fertility rate will decrease from 2.1 to 1.8 by 2026,
and then stabilise at this level until the end of the projection period in 2046. Again it
is uncertain which is more likely to be correct, however, it was considered on the
balance of probabilities that some convergence with EU norms over the period is
likely to take place and the F2 scenario has therefore been used in this paper.
Table A.1 below outlines M2F2 population by age category from 2011 up until 2021.
73
Table A.1: Population Projection M2 F2 by Age Category , 2011 - 2021
Age Category
Under 1 year
1-4 years
5 - 9 years
10 - 14 years
15 - 19 years
20 - 24 years
25 - 29 years
30 - 34 years
35 - 39 years
40 - 44 years
45 - 49 years
50 - 54 years
55 - 59 years
60 - 64 years
65 - 69 years
70 - 74 years
75 - 79 years
80 - 84 years
85 years and over
Total Population
% Increase from 2011
65 years old and over
% Increase from 2011
% 65 years old and over
2011
2012
2013
2014
2015
Year
2016
2017
2018
2019
2020
2021
72,452
283,587
319,638
301,039
281,040
298,571
362,877
393,367
363,089
329,334
304,110
273,737
243,380
217,104
172,071
130,127
101,366
69,757
58,242
74,235
289,580
324,882
304,919
275,567
280,713
342,445
392,064
363,594
335,121
308,345
278,532
248,109
220,020
181,155
132,564
103,605
71,081
60,605
75,160
292,904
333,417
309,027
275,939
264,846
321,594
387,667
363,387
341,595
311,849
283,955
251,618
223,798
188,972
137,603
105,432
72,694
62,454
73,004
296,039
342,640
312,742
282,537
251,563
303,905
376,847
366,060
347,515
314,387
290,559
256,102
226,698
195,949
142,884
107,619
74,738
64,635
70,775
296,829
351,590
317,597
289,018
242,747
290,269
360,864
370,640
351,162
318,844
297,018
260,863
231,113
201,954
148,867
110,248
76,694
67,062
68,561
295,448
360,577
322,016
295,152
237,582
281,074
343,210
375,915
353,302
325,436
300,886
267,854
235,288
205,683
157,749
112,245
78,633
69,873
66,512
290,038
368,930
327,762
300,392
240,260
271,507
327,725
377,648
355,451
331,998
305,605
273,054
240,365
209,003
166,689
114,914
80,922
72,457
64,602
281,633
373,823
336,849
305,893
248,678
264,431
312,216
376,466
357,007
339,310
309,652
278,922
244,315
213,220
174,555
119,968
82,943
75,114
62,732
273,406
375,314
346,513
310,577
261,784
258,538
298,984
368,414
361,176
345,946
312,649
285,872
249,138
216,520
181,588
125,232
85,291
78,293
60,855
265,492
374,285
355,809
316,161
273,452
255,724
288,963
354,725
366,977
350,200
317,471
292,619
254,184
221,213
187,671
131,095
87,969
81,552
59,107
257,891
371,011
365,066
321,220
283,717
255,252
282,611
338,896
373,213
352,833
324,333
296,764
261,345
225,619
191,611
139,500
90,093
85,040
4,574,888
4,587,136
0.3%
4,603,911
0.6%
4,626,423
1.1%
4,654,154
1.7%
4,686,484
2.4%
4,721,232
3.2%
4,759,597
4.0%
4,797,967
4.9%
4,836,417
5.7%
4,875,122
6.6%
531,563
549,010
3.3%
12%
567,155
6.7%
12%
585,825
10.2%
13%
604,825
13.8%
13%
624,183
17.4%
13%
643,985
21.1%
14%
665,800
25.3%
14%
686,924
29.2%
14%
709,500
33.5%
15%
731,863
37.7%
15%
12%
Source: Central Statistics Office (2013), Population and Labour Force Projections, 2016 to 2046
74
Appendix B
Data for Top Down Estimates of Projected Overall Cost Pressures (2013 to 2021)
The calculation and projection of overall pure demographic cost pressures on public health
financing depends both on age-specific population projections but also on the relative cost of
health service provision by age group. With this data, the relativities can be applied to the agespecific populations to derive a “cost pressure” index on the assumption that these relativities
remain constant over the projection period.
Costing data in Ireland is not sufficiently detailed at present to produce national figures for relative
health care costs by age and gender. In a previous exercise, Canadian relativities were utilised as a
proxy estimate for Irish relative costs. For the present exercise, it has been possible to derive
relative costs by age and gender for Ireland based on work carried out for The 2012 Ageing Report
published by the European Commission. This report collected national cost relativities by age and
gender for a number of EU15 countries. For countries, such as Ireland, the authors applied a
population-weighted average of these relativities. While this report may be seen as an
improvement on the previous year’s reliance on Canadian relativities to the extent that it is based
on data from a range of European countries, it nevertheless remains a proxy and may not
accurately reflect real Irish relativities.
Table B.1 below sets out the estimated age-specific relativities for Ireland and shows the derived
“cost pressures” when these relativities are applied to the projected population up to 2021. From
2014 to 2015, a demographically driven cost pressure of 1.2% is calculated by dividing the total
health cost units for 2015 ( 4,714,130 ) by the total health cost units for 2014 ( 4,656,426 ).
75
Table B.1: Projection of Health Cost unitrs by Age Category, 2013-2021
Age Category
Under 1 year
1-4 years
5 - 9 years
10 - 14 years
15 - 19 years
20 - 24 years
25 - 29 years
30 - 34 years
35 - 39 years
40 - 44 years
45 - 49 years
50 - 54 years
55 - 59 years
60 - 64 years
65 - 69 years
70 - 74 years
75 - 79 years
80 - 84 years
85 years and over
Relative
Expenditure
1.72
0.77
0.47
0.45
0.53
0.56
0.65
0.72
0.72
0.78
0.91
1.08
1.28
1.55
1.90
2.28
2.72
3.03
3.29
2013
129,189
226,056
157,615
139,525
147,016
147,066
208,150
277,482
260,807
266,162
283,611
305,875
323,053
347,319
358,808
313,979
286,572
220,197
205,429
2014
125,483
228,476
161,975
141,202
150,532
139,690
196,701
269,738
262,725
270,775
285,919
312,989
328,810
351,819
372,056
326,029
292,517
226,388
212,603
2015
121,652
229,086
166,205
143,394
153,985
134,794
187,875
258,298
266,012
273,616
289,973
319,946
334,922
358,671
383,458
339,681
299,663
232,313
220,586
2016
117,846
228,020
170,454
145,389
157,253
131,926
181,924
245,661
269,798
275,284
295,968
324,113
343,898
365,150
390,538
359,948
305,091
238,186
229,832
2017
114,324
223,844
174,403
147,983
160,045
133,413
175,732
234,577
271,042
276,958
301,936
329,196
350,574
373,030
396,842
380,347
312,345
245,120
238,332
2018
111,041
217,358
176,716
152,086
162,976
138,088
171,152
223,477
270,194
278,170
308,586
333,556
358,108
379,160
404,849
398,295
326,082
251,242
247,071
2019
107,827
211,008
177,420
156,449
165,471
145,365
167,338
214,005
264,415
281,419
314,621
336,784
367,031
386,645
411,115
414,343
340,390
258,354
257,528
2020
104,601
204,900
176,934
160,647
168,446
151,845
165,516
206,833
254,590
285,939
318,490
341,978
375,694
394,476
420,026
428,223
356,326
266,466
268,248
2021
101,596
199,034
175,386
164,826
171,142
157,545
165,211
202,286
243,229
290,798
320,884
349,370
381,016
405,589
428,391
437,213
379,172
272,900
279,721
Total Health Unit Costs
% Increase from 2013
4,603,911
0.0%
4,656,426
1.1%
4,714,130
2.4%
4,776,280
3.7%
4,840,043
5.1%
4,908,205
6.6%
4,977,529
8.1%
5,050,176
9.7%
5,125,308
11.3%
65 years and over
% Increase from 2013
1,384,985
0.0%
1,429,593
3.2%
1,475,700
6.5%
1,523,595
10.0%
1,572,986
13.6%
1,627,540
17.5%
1,681,730
21.4%
1,739,289
25.6%
1,797,397
29.8%
% 65 years and over
30.1%
30.7%
31.3%
31.9%
32.5%
33.2%
33.8%
34.4%
35.1%
Source: The 2012 Ageing Report, EU Commission(2012) - country-specific relative costs for Ireland obtained directly from the authors
76
Appendix C
Data on Projected Inpatient and Daycase Activity and Costs (2013 to 2021)
Data on each inpatient and daycase discharge from publicly-funded acute hospitals is
collected via the Hospital Inpatient Enquiry (HIPE) system. This includes
information on the age and gender of patients as well as detailed diagnostic and
procedure data which is coded using the ICD-10-AM classification system. Each
discharge on HIPE is subsequently classified into a specific Diagnosis Related Group
(DRG) which characterises a case based on clinical details and on homogeneity with
respect to costs. DRGs can then be used in combination with specialty-costing data
from each hospital to derive relative cost weights for each DRG. A hospital’s
casemix index, reflecting the relative costliness of its caseload, is computed as its
average relative cost weight across all DRGs weighted by the number of patients
treated in each DRG. This exercise is carried out separately for inpatients and
daycases. Casemix is used in the calculation of annual financial allocations for
hospitals.
For the purposes of the present exercise, average cost weights can be computed for
each age group and separately for inpatients and daycases for the most recent
available year (2013 activity data, 2013 costing data). These weights can then be
applied to the projected numbers of inpatients and daycases to obtain estimates of
total “cost units”, often referred to as casemix units (CMUs), for each age group and
each year. For 2011, for the first time, the cost weights for Ireland are primarily based
on Irish data derived from the patient-level costing (PLC) project which collected
detailed data from a representative range of hospitals and this has continued for 2013
model.
The underlying assumptions in these calculations are that age-specific discharge rates
and relative costs by age group remain unchanged over the projection period. No
attempt is made to model potential changes in average length of stay or in the ratio of
daycases to inpatients over the period. The results reflect the pure demographic effect
and indicate activity and cost “pressures” given existing treatment models, population
health, etc.
77
Projected inpatient and daycase activity: 2013 to 2021
Assuming inpatient and daycase age-specific discharge rates remain the same over the
projection period, these rates can be applied to the projected population to obtain
estimates of inpatient and daycase discharges for each year up to 2021. Table C.1 sets
out projections for inpatients; Table C.2 sets out projections for daycases. It should
be noted that these projections make no assumptions about potential changes in modes
or models of service delivery over the period.
Table C.1: Projected Inpatient Discharges based on 2013 rates
Rate of
Discharge per
'000
Population
% Increase from 2013
2013
2014
2015
2016
2017
2018
2019
2020
2021
28,554
28,390
27,523
26,662
25,865
25,122
24,395
23,665
22,986
25,767
25,916
25,985
25,866
25,392
24,656
23,936
23,243
22,578
15,429
15,835
16,247
16,660
17,046
17,273
17,342
17,294
17,144
13,751
13,902
14,118
14,314
14,570
14,974
15,404
15,817
16,228
19,521
20,074
20,531
20,968
21,351
21,748
22,091
22,476
22,841
31,289
30,480
29,388
28,756
29,017
30,053
31,645
33,054
34,306
48,181
45,475
43,295
41,676
40,155
38,929
37,964
37,524
37,452
65,675
63,839
61,441
58,655
55,998
53,205
50,697
48,780
47,372
50,137
50,519
51,269
52,176
52,675
52,752
51,810
50,073
47,970
28,756
29,216
29,539
29,735
29,927
30,082
30,471
30,982
31,545
23,614
23,789
24,127
24,625
25,122
25,675
26,177
26,499
26,698
26,009
26,614
27,204
27,558
27,993
28,368
28,650
29,096
29,725
28,059
28,552
29,080
29,858
30,433
31,087
31,857
32,606
33,069
32,696
33,080
33,719
34,314
35,048
35,616
36,316
37,048
38,092
35,201
36,478
37,577
38,267
38,868
39,636
40,241
41,108
41,908
35,003
36,331
37,855
40,121
42,407
44,421
46,205
47,733
48,735
35,916
36,643
37,562
38,267
39,196
40,930
42,744
44,757
47,641
32,050
33,110
34,013
34,897
35,945
36,866
37,942
39,169
40,150
31,163
32,587
33,867
35,374
36,770
38,203
39,910
41,654
43,522
606,770 610,828 614,337 618,750 623,779 629,596 635,795 642,579 649,962
0%
0.67%
1.25%
1.97%
2.80%
3.76%
4.78%
5.90%
7.12%
65 years old and over
% Increase from 2013
169,333 175,149 180,875 186,925 193,185 200,056 207,041 214,421 221,956
0%
3.43%
6.82%
10.39%
14.09%
18.14%
22.27%
26.63%
31.08%
Under 1 year
1-4 years
5 - 9 years
10 - 14 years
15 - 19 years
20 - 24 years
25 - 29 years
30 - 34 years
35 - 39 years
40 - 44 years
45 - 49 years
50 - 54 years
55 - 59 years
60 - 64 years
65 - 69 years
70 - 74 years
75 - 79 years
80 - 84 years
85 years and over
Total Number Discharges
% 65 years old and over
378
85
45
45
70
110
129
158
134
85
79
96
116
149
195
266
352
458
546
28%
29%
29%
Source: HPO.
78
30%
31%
32%
33%
33%
34%
Table C.2: Projected Daycase Discharges based on 2013 rates
Rate of
Discharge
per '000
Population
Under 1 year
1-4 years
5 - 9 years
10 - 14 years
15 - 19 years
20 - 24 years
25 - 29 years
30 - 34 years
35 - 39 years
40 - 44 years
45 - 49 years
50 - 54 years
55 - 59 years
60 - 64 years
65 - 69 years
70 - 74 years
75 - 79 years
80 - 84 years
85 years and over
Total Number Discharges
% Increase from 2013
65 years old and over
% Increase from 2013
% 65 years old and over
2013
2014
2015
2016
2017
2018
2019
2020
2021
60
4,239
4,347
4,214
4,082
3,960
3,847
3,735
3,623
3,519
56
16,431
16,531
16,575
16,502
16,199
15,730
15,270
14,828
14,403
44
14,613
15,043
15,433
15,826
16,192
16,409
16,473
16,428
16,286
34
10,606
10,743
10,912
11,063
11,262
11,573
11,907
12,225
12,541
55
14,963
15,402
15,755
16,089
16,375
16,676
16,932
17,235
17,511
75
19,509
18,982
18,314
17,923
18,117
18,754
19,744
20,623
21,399
101
32,229
30,566
29,169
28,199
27,221
26,478
25,870
25,584
25,536
115
44,555
43,337
41,565
39,579
37,791
35,972
34,393
33,194
32,392
140
50,837
51,186
51,869
52,672
53,009
52,931
51,867
50,009
47,825
165
56,470
57,293
57,913
58,284
58,651
58,935
59,666
60,649
61,722
201
62,873
63,298
64,181
65,509
66,849
68,344
69,718
70,594
71,143
255
72,252
74,152
75,808
76,797
77,987
79,006
79,738
80,951
82,700
318
79,838
81,430
82,942
85,165
86,815
88,681
90,888
93,032
94,350
401
89,656
90,906
92,666
94,311
96,334
97,900
99,826
101,841
104,711
536 101,516 104,918 108,083 110,067 111,799 114,011
115,752
118,249
120,554
613
84,696
87,552
91,226
96,684 102,190 107,040
111,341
115,028
117,443
704
74,501
75,814
77,729
79,201
81,134
84,730
88,496
92,668
98,648
631
45,824
47,206
48,508
49,779
51,288
52,613
54,162
55,929
57,345
452
28,003
29,134
30,341
31,786
33,135
34,520
36,159
37,829
39,618
196.7323 903,611 917,840 933,203 949,518 966,310 984,150 1,001,937 1,020,518 1,039,648
0%
1.57%
3.27%
5.08%
6.94%
8.91%
10.88%
12.94%
15.05%
334,540 344,624 355,887 367,516 379,546 392,914
0%
3.01%
6.38%
9.86% 13.45%
17.45%
37%
38%
Source: HPO.
79
38%
39%
39%
40%
405,910
21.33%
419,703
25.46%
433,608
29.61%
41%
41%
42%
Projected inpatient and daycase cost pressures: 2013 to 2021
The pure demographic cost pressures for inpatients and daycases separately are derived by
multiplying the relative cost per case by the projected numbers of discharges for each age group
and year. This provides an estimate of total casemix units( CMUs). Again, these estimates are
based on the assumption that the only variable changing over the projection period is the size and
age distribution of the population. Table C.3 sets out cost pressure projections for inpatients;
Table C.4 sets out cost pressure projections for daycases. Table C.5 gives the overall projected
cost pressure for total projected inpatient and daycase activity combined.
Table C.3: Projected Inpatient Casemix Units based on 2013 rates
Casemix
Index
2013
2014
2015
2016
2017
2018
2019
2020
2021
Under 1 year
1.37
39,135
38,933
37,745
36,564
35,471
34,453
33,455
32,454
31,522
1-4 years
0.62
15,869
15,959
16,001
15,928
15,636
15,183
14,739
14,312
13,903
5 - 9 years
0.67
10,296
10,567
10,841
11,118
11,375
11,527
11,572
11,540
11,440
10 - 14 years
0.75
10,281
10,394
10,555
10,702
10,893
11,195
11,516
11,825
12,133
15 - 19 years
0.64
12,495
12,843
13,136
13,416
13,657
13,909
14,125
14,375
14,607
20 - 24 years
0.57
17,945
17,434
16,814
16,454
16,616
17,205
18,115
18,922
19,636
25 - 29 years
0.56
27,004
25,504
24,303
23,431
22,591
21,928
21,399
21,155
21,115
30 - 34 years
0.58
38,082
36,995
35,569
33,931
32,395
30,796
29,373
28,288
27,511
35 - 39 years
0.65
32,526
32,755
33,224
33,785
34,070
34,083
33,447
32,298
30,922
40 - 44 years
0.82
23,505
23,873
24,130
24,283
24,435
24,551
24,852
25,259
25,702
45 - 49 years
0.99
23,341
23,520
23,857
24,350
24,837
25,380
25,870
26,184
26,378
50 - 54 years
1.08
28,048
28,697
29,331
29,713
30,185
30,591
30,901
31,385
32,064
55 - 59 years
1.26
35,396
36,013
36,675
37,656
38,373
39,199
40,162
41,105
41,688
60 - 64 years
1.27
41,552
42,037
42,846
43,595
44,525
45,241
46,128
47,057
48,384
65 - 69 years
1.37
48,108
49,849
51,341
52,280
53,092
54,132
54,953
56,135
57,217
70 - 74 years
1.45
50,666
52,594
54,803
58,086
61,402
64,324
66,905
69,109
70,560
75 - 79 years
1.46
52,479
53,549
54,898
55,934
57,295
59,834
62,490
65,435
69,655
80 - 84 years
1.51
48,540
50,148
51,519
52,861
54,452
55,850
57,484
59,347
60,837
85 years and over
1.59
49,551
51,815
53,850
56,246
58,464
60,744
63,456
66,229
69,198
Total Number of Casemix Units
604,816 613,479 621,438 630,330 639,766 650,123 660,944 672,417 684,473
% Increase from 2013
0%
1.43%
2.75%
4.22%
5.78%
7.49%
9.28%
11.18%
13.17%
65 years old and over
% Increase from 2013
% 65 years old and over
249,343 257,955 266,411 275,406 284,707 294,883 305,288 316,256 327,468
0%
3.45%
6.85% 10.45%
14.18%
18.26%
22.44%
26.84%
31.33%
41%
42%
43%
80
44%
45%
45%
46%
47%
48%
Table C.4: Projected Daycase Casemix Units based on 2013 rates
Casemix
Index
2013
2014
2015
2016
2017
2018
2019
2020
2021
Under 1 year
1.01
4,288
4,397
4,262
4,129
4,006
3,891
3,778
3,665
3,560
1-4 years
1.33
21,819
21,955
22,012
21,916
21,514
20,891
20,280
19,693
19,129
5 - 9 years
1.43
20,836
21,452
22,008
22,567
23,088
23,398
23,491
23,425
23,224
10 - 14 years
1.26
13,368
13,541
13,754
13,944
14,195
14,588
15,009
15,409
15,808
15 - 19 years
1.10
16,396
16,876
17,263
17,629
17,942
18,270
18,549
18,883
19,185
20 - 24 years
1.03
20,039
19,492
18,807
18,406
18,608
19,261
20,277
21,181
21,977
25 - 29 years
1.02
32,974
31,265
29,832
28,832
27,828
27,063
26,439
26,145
26,096
30 - 34 years
1.02
45,230
43,994
42,200
40,186
38,370
36,522
34,916
33,695
32,877
35 - 39 years
1.01
51,369
51,725
52,419
53,237
53,586
53,516
52,446
50,573
48,369
40 - 44 years
1.03
58,272
59,134
59,781
60,172
60,556
60,860
61,633
62,658
63,783
45 - 49 years
1.03
65,050
65,477
66,385
67,759
69,152
70,707
72,142
73,054
73,630
50 - 54 years
1.02
73,688
75,624
77,316
78,325
79,535
80,570
81,306
82,537
84,320
55 - 59 years
1.01
80,255
81,852
83,376
85,610
87,276
89,151
91,377
93,535
94,859
60 - 64 years
1.00
89,419
90,660
92,423
94,083
96,109
97,683
99,609
101,624
104,488
65 - 69 years
0.97
98,967 102,303 105,408 107,347 109,053 111,227
112,935
115,375
117,643
70 - 74 years
0.98
83,167
85,976
89,581
94,935 100,334 105,087
109,313
112,947
115,318
75 - 79 years
0.96
71,551
72,805
74,630
76,029
77,874
81,319
84,923
88,920
94,650
80 - 84 years
0.97
44,244
45,574
46,822
48,044
49,493
50,765
52,252
53,949
55,307
85 years and over
0.95
26,491
27,571
28,694
30,031
31,276
32,554
34,070
35,616
37,271
Total Number of Casemix Units
917,424 931,673 946,973 963,183 979,796 997,324 1,014,743 1,032,885 1,051,495
% Increase from 2013
0%
1.55%
3.22%
4.99%
6.80%
8.71%
10.61%
12.59%
14.61%
65 years old and over
% Increase from 2013
% 65 years old and over
324,419 334,229 345,136 356,387 368,029 380,953
0%
3.02%
6.39%
9.85%
13.44%
17.43%
35%
36%
36%
Source: HPO.
Source: HPO.
81
37%
38%
38%
393,493
21.29%
406,807
25.40%
420,189
29.52%
39%
39%
40%
Appendix D
Projecting Preterm Infant Care Cost Pressures
2014 to 2021
Data on maternal and infant inpatient care in publicly-funded acute hospitals is collected via the
Hospital Inpatient Enquiry (HIPE) system. As described in Appendix C, classification of cases
into Diagnosis Related Groups (DRGs) and subsequent costing of DRGs allows the relative
costliness of various categories of patients to be computed. These relative values for each DRG
can be summed over all patients in a particular category giving an estimate of total cost in
Casemix Units (CMUs) for that category. These costs can then be projected forward based on the
expected numbers of patients in each category.
In the present exercise, the objective was to estimate the potential impact of the likely increasing
numbers as well as increasing complexity of pre-term births on maternity hospital costs. Rolling
forward trends from recent years, annual estimates of percentage growth in numbers and
percentage increase in relative costliness were projected. The relative cost was then multiplied by
the expected numbers to derive a total cost index, expressed in terms of CMUs. The first 3 rows
of Table D.1 below show the likely effect on costs of the combined potential increase in both the
rates and complexity of pre-term births. The second 3 rows show costs (i.e. CMUs) if no increase
in pre-term activity or complexity is projected.
82
Source: Healthcare Pricing Office (HPO)
83
Appendix E
Methodology for projecting number of persons in nursing homes.
Age-specific projections for the numbers of persons in nursing homes in the coming years are set
out in Tables E1 and E2. The figures are derived by applying the age-specific population based
rates from Census 2011 and from the Nursing Homes Support Scheme (NHSS) to the CSO’s
recently published population projections (see Appendix A). In arriving at both these estimates, it
is assumed that the utilisation of nursing home care by age group remains constant over the
projection period. Both methods result in an estimated 2.7%-3.2% increase in nursing home
requirements in 2015.
84
Table E1 Actual (2011) and projected numbers of persons in nursing homes, 2011 to 2021
Age Category
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
Under 65
65 - 69 years
70 - 74 years
75 - 79 years
80 - 84 years
85 years and over
5,463
1,137
1,742
2,955
4,714
10,254
5,456
1,197
1,775
3,020
4,803
10,670
5,454
1,249
1,842
3,074
4,912
10,996
5,463
1,295
1,913
3,137
5,051
11,380
5,481
1,334
1,993
3,214
5,183
11,807
5,512
1,359
2,112
3,272
5,314
12,302
5,551
1,381
2,231
3,350
5,469
12,757
5,592
1,409
2,337
3,497
5,605
13,224
5,639
1,431
2,431
3,651
5,764
13,784
5,690
1,462
2,512
3,822
5,945
14,358
5,749
1,491
2,565
4,067
6,088
14,972
Total
26,265
26,921
27,526
28,238
29,012
29,871
30,739
31,664
32,699
33,788
34,932
2.5%
4.8%
7.5%
10.5%
13.7%
17.0%
20.6%
24.5%
28.6%
33.0%
Percentage increase since 2011
Source: Central Statistics Office.
Table E2 Projected increase in numbers of people funded by the NHSS, 2014-2021
Scheme Category
2014
2015
2016
2017
2018
2019
2020
2021
15,799
16,301
16,854
17,407
17,996
18,660
19,355
20,086
NHSS Public + Saver Public
4,835
4,989
5,159
5,329
5,512
5,716
5,930
6,155
SAVER Private
1,545
1,594
1,648
1,702
1,760
1,825
1,893
1,965
22,179
22,885
23,661
24,438
25,269
26,201
27,179
28,206
3.2%
6.7%
10.2%
13.9%
18.1%
22.5%
27.2%
NHSS Private
Total
Percentage increase since 2014
Source: HSE
85
Appendix F
Projecting Primary Care Reimbursement Services (PCRS) Demographic Cost Pressures
2013 to 2017
The methodology used in projecting forward the demographic cost pressure in the PCRS is similar
to that used throughout this report, in that population per capita costs for 5 year age categories
were calculated on the basis of the latest available data. The latest complete data referred to 2013,
and these per capita costs were combined with age-specific population projections and then
aggregated to give a total cost for each scheme.
The data source used to determine the per capita cost was the regular monthly reports provided by
the PCRS unit to the Department, in relation to the following schemes:
(i)
GMS Pharmaceutical Ingredient Costs
(ii)
GMS Pharmaceutical Pharmacy
(iii)
GP Visit Card Capitation Fee
(iv)
Medical Card Capitation Fee
(v)
Other GMS Fees paid to GPs
(vi)
Out of Hours Service Fees
(vii)
Long Term Illness Scheme
(viii) Dental Treatment Services
(ix)
Community Ophthalmic Scheme
(x)
Drug Payment Scheme
These were aggregated to give yearly totals. Six months data for Long Term Illness Scheme,
Dental Treatment Services, Community Ophthalmic Scheme and Drug Payment Scheme was
received for 2013. These data were grossed up to estimate an annual total for these schemes based
on the monthly distribution of payments made for the remaining schemes.
The age specific cost per capita is available in Table F1 below and the results for each individual
scheme are shown in Table F2 below.
86
Table F1: Comparison of population per capita cost by age group for various PCRS schemes 2013
(Euros)
Age Category
0-4 years
5-9 years
10-14 years
15-19 years
20-24 years
25-29 years
30-34 years
35-39 years
40-44 years
45-49 years
50-54 years
55-59 years
60-64 years
65-69 years
70-74 years
75-79 years
80-84 years
85 years and
over
GMS
Pharmaceutical
Ingredient Costs
GMS
Pharmaceutical
Pharmacy Fees
GP Visit
Card
Capitation
Fee
Medical
Card
Capitation
Fee
Other GMS Fees
paid to GPs
26.82
26.10
28.51
40.62
54.76
60.15
65.66
81.89
105.75
136.66
175.25
229.70
315.53
448.78
770.33
1,006.82
1,145.63
10.92
9.23
8.74
14.36
19.57
20.26
22.03
26.92
34.44
44.40
58.03
78.50
111.94
166.21
302.80
419.64
514.55
2.73
1.73
1.67
1.98
1.46
1.76
2.32
2.42
2.42
3.55
3.20
3.08
3.39
4.11
1.94
0.68
0.54
26.60
19.35
19.19
27.94
28.75
24.19
22.74
23.62
24.49
37.29
35.58
37.69
44.71
63.08
228.54
269.92
279.49
4.01
3.32
3.25
5.08
7.49
5.47
4.79
4.84
4.89
4.80
7.60
6.17
8.34
13.20
21.63
28.14
32.33
13.15
7.43
4.96
5.63
6.85
5.47
5.01
4.83
4.62
4.42
4.39
4.84
5.69
7.51
12.25
18.11
26.84
5.81
3.67
5.05
10.16
8.32
5.98
13.60
22.07
27.67
34.50
58.04
92.17
130.21
168.49
84.84
44.84
43.19
1,206.71
554.69
0.38
284.61
35.03
45.93
42.69
Source: Primary Care Reimbursement Service.
*Estimated based on 6 months data.
87
Out of
Hours
Service
Fee
DPS
Dental
payment to
Claims*
pharmacists*
Long Term
Illness
Claims*
Optical
Claims*
0.00
0.00
0.00
10.34
14.37
12.99
12.25
12.83
14.01
15.18
16.55
19.22
21.92
28.03
41.77
44.47
39.35
4.38
9.58
14.88
16.21
13.42
11.66
13.28
15.39
17.78
24.36
34.24
48.68
60.29
64.24
35.68
10.32
6.43
0.05
0.15
0.94
2.96
2.51
1.87
1.78
2.14
3.70
6.48
7.80
9.38
12.33
17.84
32.19
40.34
41.92
29.46
3.88
36.96
Table F2: Projected demographic cost pressures in millions of Euro for various PCRS schemes, 20132017
PCRS Scheme
2013
2014
2015
2016
2017
GMS Pharmaceutical Ingredient Costs
839.9
857.0
875.3
895.1
915.8
GMS Pharmaceutical Pharmacy Fees
320.0
326.8
334.2
342.1
350.4
GP Visit Card Capitation Fee
10.9
11.0
11.1
11.2
11.3
Medical Card Capitation Fee
222.0
225.9
230.0
234.7
239.7
Other GMS Fees paid to GPs
34.0
34.5
34.9
35.4
36.0
Out of Hours Service Fee
34.1
34.5
34.9
35.3
35.7
168.2
171.4
174.7
177.9
181.1
Dental Claims*
64.6
65.2
66.0
66.8
67.8
Long Term Illness Claims*
99.8
101.1
102.5
103.9
105.4
Optical Claims*
31.9
32.6
33.3
34.1
34.9
1,825.3
1,860.0
1,896.8
1,936.7
1,978.1
1.9%
1.9%
2.0%
3.9%
2.1%
6.1%
2.1%
8.4%
DPS payment to pharmacists*
Total
Percentage Change from previous year
Percentage Change from 2013
Source: Primary Care Reimbursement Service and CSO Population Projections 2016-2046.
*2013 estimated based on 6 months data.
88