This presentation was made by Joaquim Oliveira Martins at the 5th Meeting of the joint OECD DELSA/GOV Network on Fiscal Sustainability of Health Systems, held on 4-5 February 2016 at the OECD Conference Centre in Paris.

1. THE DRIVERS OF PUBLIC HEALTH
SPENDING: INTEGRATING POLICIES
AND INSTITUTIONS
5th DELSA/GOV meeting on Sustainability of Health Systems
OECD, 4-5 February 2016
Joaquim Oliveira Martins
(OECD, Public Governance Directorate)

2. 2
Growth in health spending has decreased
since the crisis…
Source: OECD Health Statistics 2015
0
1
2
3
4
5
6
7
8
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
Health expenditure growth rates in real terms
(Unweighted OECD average)
Total
Public

3. 3
Source: OECD Health database (2015).
…but has continued to increase in % of GDP
4.5
5
5.5
6
6.5
7
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
Public Health expenditure as a % of GDP
(Unweighted OECD average)

4. Future Health expenditure pressures are sizeable
(much larger than pension systems)
4
0
2
4
6
8
10
12
14
16
18
% 2006-2010
Cost pressure,2060
Cost containment, 2060
Projections by country of Public Health + Long-term care expenditures (in % of GDP)
Source: de la Maisonneuve and Oliveira Martins (2013)

5. The age structure of Health expenditures will
significantly change…
0
10
20
30
40
50
60
70
2010 2030 2060
People aged below 65
People aged over 65
5
NB: Non-demographic effects are assumed to be homothetic across
ages, so they do not change the age structure of spending
Expenditure shares in % of total spending

6. … because the share of population aged over 65 and 80 will
double between 2010-50
Source: OECD Historical Population Data and Projections Database, 2015
2.5 X
2X
6

7. Main health expenditure drivers
Health care
expenditure
Demography
(I)
Income
(II)
Residual
(III)
7
It is not ageing per se
that will create
expenditure pressures
Only an income
elasticity of 1.8 could
explain most of the
expenditure growth in
the OECD

8. What is the size of the unexplained
expenditure residual?
Average annual growth rate 1995-2009 of health expenditures per capita (in %)
8
With an income elasticity of 0.8
Health spending Age effect Income effect Residual
Memo item :
Residual with
unitary income
elasticity
Selected countries:
Austria 3.3 0.4 1.3 1.5 1.2
Denmark 3.7 0.2 0.8 2.7 2.5
Finland 4.1 0.6 2.0 1.5 1.1
France 1.6 0.5 0.9 0.3 0.0
Germany 1.7 0.6 0.8 0.2 0.0
Italy 3.1 0.6 0.4 2.1 2.0
Japan 2.7 1.2 0.8 0.7 0.5
Korea 11.0 1.1 3.1 6.5 5.7
Netherlands 5.2 0.5 1.4 3.3 2.9
Portugal 4.6 0.6 1.5 2.4 2.0
Spain 3.4 0.5 1.5 1.4 1.0
Switzerland 2.9 0.4 0.9 1.6 1.4
United Kingdom 4.6 0.2 1.5 2.8 2.5
United States 3.6 0.3 1.1 2.3 2.0
OECD total average 4.3 0.5 1.8 2.0 1.5
BRIICS average 6.2 0.5 3.2 2.5 1.7
Total average 4.6 0.5 2.0 2.0 1.5

9. Unbundling the expenditure residual
Residual
(III)
a) Relative
prices
b)
Technology
c) Institutions
and policies
If price elasticity < 1
then price increases
increase expenditures
9
Preferences for better
health products could
explain a rebound
effect even when unit
costs are reduced

10. Unbundling the expenditure residual
Residual
(III)
a) Relative
prices
b)
Technology
c) Institutions
and policies
10
This work investigates (1) the relationship between policy and
institutional factors and healthcare expenditures and (2) how
much policy/institutions can explain of cross-country
dispersion in expenditures.

11. 11
How to introduce policies and institutions
among the determinants of health
spending?

12. Characterizing health care systems: country groups
Source: Joumard, André and Nicq (2010), "Health Care Systems: Efficiency and Institutions " , OECD
Economics Department Working Papers. No. 769.
12

13. Policy and
Institutional
determinants
of Health
spending
The information concerning
the set of different policies
and institutions used in this
paper was derived from
official questionnaires sent to
governments by the OECD.
This qualitative information
(269 variables) was
transformed into quantitative
indicators, ranging from 0-6.
This set of indicators for
policies and institutions was
subsequently limited to 20
(see Paris et al., 2010).
13

14. Large variation in Policy and institutional settings
14
0
2
4
6
Scope and depth of
basic coverage
"Over the basic"
coverage
Patient choice among
providers
Incentive for HC
quality
Hospital payment (1)
Delegation to health
insurers
Public objectives (2)
Regulation prices (3)
Denmark
0
2
4
6
Scope and depth of
basic coverage
"Over the basic"
coverage
Patient choice among
providers
Incentive for HC
quality
Hospital payment (1)
Delegation to health
insurers
Public objectives (2)
Regulation prices (3)
France
0
2
4
6
Scope and depth of
basic coverage
"Over the basic"
coverage
Patient choice among
providers
Incentive for HC
quality
Hospital payment (1)
Delegation to health
insurers
Public objectives (2)
Regulation prices (3)
Sweden
0
2
4
6
Scope and depth of
basic coverage
"Over the basic"
coverage
Patient choice among
providers
Incentive for HC
quality
Hospital payment (1)
Delegation to health
insurers
Public objectives (2)
Regulation prices (3)
UnitedKingdom
Source: Paris et al. (2010)

15. Policy and institutions indicators
Supply-side Hospitalsupply
legislation
Regulationofcapital
investment
Regulationofhospitals(opening,bed supply, services,
high-costequipment):quotas, authorisationatlocal
and/orcentrallevel(higherscore=strongerregulation)
Negative Negative Negative
Supply-side Providerprice
regulation
Regulationofpricefor
physicianservices
Regulationofprices/fees forphysicianservices:degree
offlexibility forcharges(higherscore=lessflexibility,
strongerregulation)
Negative Negative No effect
Supply-side Providerprice
regulation
Regulationofpricefor
hospitalservices
Regulationofpricesforhospitalservices:degreeof
flexibilityforsettingcharges(higherscore=less
flexibility,strongerregulation)
Negative Negative Negative
Category
Institutional
aspect
Variable name Short definition and interpretation
Effect on health spending
Expected Estimated
Linear model
Estimated non-
Linear model
Some indicators have a clear expected sign confirmed by the estimates:
Supply-side Provider
payment
Incentives for quality Incentives for health care quality (patient outcomes and
satisfaction): guidelines/protocol adherence incentives
(including financial) and sanctions for physicians and/or
specialists and/or hospitals (higher score = stronger
incentives)
Ambiguous Positive Positive
Supply-side Insurer
competition
User choice of insurer Single or multiple insurers; degree of patient choice of
insurer for basic coverage and their market shares
(higher score = more choice)
Ambiguous Positive Positive
Others have an ambiguous expected sign:
Demand-side Definition of
health benefit
package and
priority setting
Definition of benefit
basket
Whether and how the benefit basket is defined for
medical procedures and pharmaceuticals:
negative/positive lists by providers and/or SHI funds
and/or central level (higher score = more centralised and
positive definition)
Ambiguous Negative Negative

16. Policy and institutions indicators
Category
Institutional
aspect
Variable name Short definition and interpretation
Effect on health spending
Expected Estimated
Linear model
Estimated non-
Linear model
Some are estimated to have an opposite sign from the expected one:
Supply-side Budget caps Control of volume Monitoring, regulations and controls on volumes of
care: activity volume, monitoring of guideline
adherence, drugs advertising to consumers, physician
payment reduced according to exceeded volume targets
(higher score = stronger controls)
Negative Positive Positive
Public
management,
coordination
and financing
Health
technology
assessment
Use of health technology
assessment
Existence and use of healthtechnologyassessment in
determiningbenefit coverage, reimbursement
levels/prices and clinical guidelines (higher score =
higher reliance)
Negative No effect Positive
Supply-side Provider
payment
Physician payment Incentives for higher volume in physician payment
mechanisms (primary care, outpatient and inpatient
specialists): predominant mechanism(s) from salary,
capitation, FFS (higher score = stronger incentive to
generate volume)
Positive Negative Negative
Although it cannot be excluded that these results may be due to reverse causality

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Model 1: traditional determinants of spending (income, age, prices and
technology/quality), time and country-specific effects – FE estimation
Econometric specifications
Model 2: country-specific effects replaced by time-invariant policy and
institutional variables (k = 20) – pooled OLS estimation
Model 3: non-linearities through interactions between the vector of policy and
institutions and all other explanatory variables – non-linear LS estimation

18. Baseline
results:
Public
health
spending
per capita
Robust
results for:
Total health
spending
Or indicators
tested one-by-
one
(1) (2) (3)
Dependent variable: log of real Public Health
Expenditures per capita Linear FE
Pooled OLS with
Institutions
Non-Linear with
Institutions
Log of GDP per capita 0.922*** 1.277*** 1.343***
(0.223) (0.070) (0.057)
Dependency ratio 0.026 0.023*** 0.027***
(0.020) (0.005) (0.004)
Log relative Health prices -0.865*** -1.016*** -1.067***
(0.192) (0.090) (0.087)
Quality effect -0.003 0.015*** 0.015***
(0.006) (0.002) (0.002)
Physician payment -0.094*** -0.039***
(0.019) (0.006)
Hospital payment -0.013 0.004
(0.021) (0.007)
Incentives for quality 0.146*** 0.056***
(0.031) (0.009)
Choice among providers 0.008 0.006
(0.026) (0.011)
User choice of insurer 0.119* 0.064***
(0.062) (0.016)
Lever -0.096 -0.053***
(0.059) (0.014)
Regulation of physician supply 0.049*** -0.012*
(0.015) (0.007)
Regulation of capital investment -0.050*** -0.019***
(0.015) (0.007)
Regulation of price for physician services -0.068*** -0.012
(0.021) (0.008)
Regulation of price for hospital services -0.064*** -0.027***
(0.020) (0.008)
Regulation of pharmaceutical price -0.002 0.005
(0.018) (0.004)
Regulation of prices charged to third-party 0.043 0.006
(0.037) (0.009)
Stringency of budget constraint -0.063 -0.019
(0.039) (0.015)
Control of volume 0.049*** 0.023***
(0.012) (0.004)
Gatekeeping 0.004 0.015**
(0.022) (0.007)
Depth of basic insurance 0.153*** 0.064***
(0.019) (0.006)
Definition of benefit basket -0.065*** -0.024***
(0.018) (0.007)
Public health objectives 0.076** 0.020**
(0.030) (0.008)
Use of health technology assessment 0.020 0.026**
(0.044) (0.012)
Degree of decentralisation -0.037 -0.025***
(0.027) (0.007)
Constant -7.204*** -10.961*** -11.703***
(2.446) (0.644) (0.511)
Country Fixed Effects Yes No No
Year Fixed Effects Yes Yes Yes
Number obs 240 240 240
R2 0.594 0.981 0.999

19. Demographic and non-demographic factors
explain a large share, but not all expenditures
(1) Log differences between country averages and OECD sample average.
Residual: Part of health expenditures that is not explained by demographic and economic factors.

20. With institutions most of the cross-country
variation is explained
Note: Residuals after age, income, relative prices and technology have been taken into account.
-0.6
-0.5
-0.4
-0.3
-0.2
-0.1
0
0.1
0.2
0.3
0.4
Institutions Non-explained residual Residual

21. – Reasonably good fit between expected signs of
coefficients for the institutional indicators and
actual estimates:
• The models including policies can explain most of the
cross-country dispersion in health expenditures
– Policies and institutions matter for differences in
health care spending:
• Supply (e.g., competition, tighter regulation of service
prices) and demand (e.g., more explicit definition of the
publicly funded benefit package) matter for cost-
containment
Main conclusions

22. OECD References:
• Joumard, André and Nicq (2010), "Health Care Systems:
Efficiency and Institutions", OECD Economics Department Working
Papers, No. 769.
• de la Maisonneuve, Christine and Joaquim Oliveira Martins (2014),
“The future of health and long-term care spending”, OECD Journal:
Economic Studies.
• de la Maisonneuve, Moreno-Serra, Murtin, Oliveira Martins (2016),
”The drivers of Public Health Spending: integrating Policy and
institutions”, OECD Economics Department Working Papers
(forthcoming)
• OECD (2015), Health at a Glance, Paris
www.oecd.org/health/healthataglance
22

23. Thank you!
23