HMI Seminar WHO / OECD Working Paper 85 review 30 …...HMI Seminar WHO / OECD Working Paper 85...
Transcript of HMI Seminar WHO / OECD Working Paper 85 review 30 …...HMI Seminar WHO / OECD Working Paper 85...
<Nice cover picture
HMI Seminar
WHO / OECD Working Paper 85 review
30 August 2016
Healthcare focused actuarial consulting firm
Insight Actuaries & Consultants
2
Manage Risk | Develop Opportunity
Do more than ‘keep score’
Data centric
ActuarialConsulting
ProviderBenchmarking
Managed CareAdvisory
PRMAValuations
BusinessIntelligence
DiagnosisRelated Groups
Technical Policy Advisory
StrategicAnalytics
ProductDevelopment
Insight Actuaries & Consultants
Wide range of clients across the spectrum
Independence and trust built up over many years of conduct across
market segments
Sample of current and recent Insight clients
March 2016
Engaged the authors, WHO,
DOH and HMI to establish the
process of formal engagement
Timeline and Insight involvement in OECD Health Working paper 85
4
May 2014
Engaged by WHO to
assist in studying SA
private hospital prices
Sept 2014
Assisted with data from GEMS,
clinical cross walks,
regular query support and refinement
June 2015
Shown initial findings of the
report and verbal feedback
given
Oct 2015
Report released but
subsequently withdrawn
Dec 2015
OECD health Working
Paper 85 referenced in
the NHI white paper
Feb 2016
WHO & OECD presents results
of the Working Paper at the
HMI and the paper is released
Submitted written
response to authors
and the WHO 10
March 2016
Written feedback
received from the WHO
31 March 2016 and
republished working
paper
July 2016
Critiques and responses
released on the CompCom
website
9 May 2016 wrote
back to the WHO
to clarify and
respond and ask
to meet
Clarifying our role in the Working Paper
5
We offered ongoing assistance to the WHO on request, independently and at our own cost.
We facilitated the handover of GEMS data to the WHO at the request of GEMS as part of our actuarial function
for the scheme.
We offered a critique of the Working Paper directly to the authors independently and at our own cost.
Clarifying our role in the Health Market Inquiry
6
Informal briefing session with HMI panel and advisors before public hearings and data collection commenced
Prepared an expert report for Netcare; and presented with Netcare, Bestmed and the IPA Foundation at the
public hearings.
Points of disagreement with the Working Paper
Context
7
Framing
Affordability
Comparability
Test of reasonability
Case mix
Risk Profile
Inferences and suggestions
Two amendments were made to the Working Paper arising from our feedback and correspondence.
1. The data on pathology was corrected.
2. The graph with South African income deciles was included as an appendix (figure 20).
The following areas raised in our letter remain points of disagreement with the Working Paper:
The main points
The paper is mainly concerned with 2 points:
8
1. How do “private hospital prices” in South Africa compare to those in OECD countries?
2. Are these prices affordable for South Africans?
Context
Insufficient context is given as to the reasons why South Africa’s health system looks the way it does.
9
Context does not legitimise the current system but aids in understanding how we got here and why
things look the way they do.
The role of the private sector is not discussed in any detail.
The public sector receives no attention in the paper.
South Africa’s (very) low out-of-pocket expenditure gets a mention, as well as a footnote that it is not
unusual for developing countries to have well developed private health insurance; but private health
insurance as a share of total current health expenditure for South Africa against OECD countries is
the graphic plotted (figure 1) making South Africa look like the outlier.
Framing
10
“Private hospital prices” are the theme of the paper whereas all services
performed in hospital are considered.
While the issue is mentioned in the paper, it is not emphasised, and the
reader is left with the label of “Private hospital prices” throughout the
paper.
Hospital entities are confused with hospitals as a place of service, which
brings significant interpretation risks for readers unfamiliar with the
South African private provider structures.
62.6%
17.7%
7.0%5.2%5.1%2.4%
Pathology
Doctors
Allieds
Radiology
Hospital
Other
Split of spend for
hospital admissions
The Working Paper makes the argument that “prices set in the private
sector set labour benchmarks that doctors face in choosing between
working in a public or private facility” – but this has nothing to do with
private hospitals. If that were the question, doctor tariffs and earnings
should be compared to doctor salaries in the public sector.
Affordability
11
Inequality in South Africa is not discussed in the paper.
Including the income decile figure goes some way, but not far enough in highlighting the issue and its
bearing on the analysis.
Cross subsidies between private and public sectors are ignored (medicines being the main example).
Income cross subsidies are ignored.
Prices are deemed to relate to income when comparing between countries, but not within countries.
Affordability and Correspondence
12Source: Stats SA, Income and Expenditure survey 2010/2011
0.0%
2.0%
4.0%
6.0%
8.0%
10.0%
12.0%
14.0%
16.0%
18.0%
R 0
R 8
33
R 1
,667
R 2
,500
R 3
,333
R 4
,167
R 5
,000
R 5
,833
R 6
,667
R 7
,500
R 8
,333
R 1
0,0
00
R 1
1,6
67
R 1
3,3
33
R 1
5,0
00
R 1
6,6
67
R 1
8,3
33
R 2
0,0
00
R 2
1,6
67
R 2
3,3
33
R 2
5,0
00
R 2
9,1
67
R 3
3,3
33
R 3
7,5
00
R 4
1,6
67
R 4
5,8
33
R 5
0,0
00
R 5
4,1
67
R 5
8,3
33
R 6
2,5
00
R 6
6,6
67
Proportion of population Proportion of population (grant income removed)
27 million people live below
the upper bound poverty line
(R780 per capita in 2015)
Household income per month
Affordability and Correspondence
OECD countries have more equitable societies and health systems.
Hospital price data from the OECD countries represents hospital usage from each country’s overall population.
Hospital price data for South Africa represents hospital usage from the wealthiest portion of South Africa’s population.
13
1.4% 0.9% 1.3% 1.0% 1.6%2.9%
5.9%
12.8%
26.1%
46.2%
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
30.0%
35.0%
40.0%
45.0%
50.0%
1 2 3 4 5 6 7 8 9 10
% of medical scheme membership from each household income decile
Source: Stats SA, Income and Expenditure survey 2010/2011
85% of medical scheme members are in
the top 3 income deciles
On average, medical schemes members
income decile is 8.8 (9.4 if weighted by
income)
Inequality in South Africa cannot be
ignored in such analyses, especially when
data from only a wealthy subset of the
population is considered.
Comparability
14
Its not immediately obvious why South Africa should be compared to 20 of the most developed countries
in the world, particularly with respect to the maturity of their health systems.
The data being available for only these countries does not validate the comparison.
There are undeniable structural and economic differences between South Africa and the 20 Eurostat countries.
Even low-income OECD countries are very different from South Africa.
If one was asking the question of whether South Africa’s “private hospital prices” were appropriate one
should start by looking for suitable comparators.
Either the subsection of the South African economy that approximates the OECD should be compared to
the OECD, or South Africa as a whole should be compared to more comparable countries.
Comparability
15
0
20000
40000
60000
80000
100000
120000
GDP per capita, US$, PPP
South Africa’s GDP per capita is 70% below the
comparator countries. And 55% below the
“low-income” OECD countries compared to.
Source: OECD, Eurostat countries & South Africa
Comparability
16
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
Gini Coefficient, South Africa versus comparator set
South Africa’s Gini coefficient stands in stark
contrast to the comparator countries,
including “low-income” countries.
Source: OECD, Eurostat countries & South Africa
South Africa has a small subsection of its
economy and population that might proxy
European living standards, but this is not
representative of the population as a whole.
Affordability and Comparability
The working paper insists that “private hospital prices” are unaffordable for
South Africans, including upper income South Africans.
17
SA
SA(Decile7) SA(Decile8) SA(Decile9) SA(Decile10)
PolandHungary
Portugal
Slovenia
Czech Republic Estonia
Spain United Kingdom
Italy
France
IcelandNetherlands
Germany
Austria
SwedenFinland
Ireland
SwitzerlandNorway
Luxembourg
0
50
100
150
200
250
0 5000 10000 15000 20000 25000 30000 35000
(13%)(6%)
Given private hospitals are accessed
predominantly through medical
schemes, and the previously shown
income distribution of medical
scheme membership, the statement
is incorrect.
Furthermore, the analysis ignores
income cross subsidy in the system
in terms of differential hospital
prices on some so called ‘low
income options’ and income banded
scheme contributions.
(46%)(26%)Ho
spit
al co
mp
ara
tive p
rice
level
Household final consumption expenditure per capita (US$ PPP)
Figure 20 - Working Paper 85, recreated
Tests of reasonability
We remain of the view that the results of the paper as seen in figure 5
fail the test of reasonability.
18
Consider what South African
“private hospital prices”
would have to be to not be
deemed an outlier. The
consequences of such an
assertion are unreasonable.
South Africa
Poland
Hungary
Portugal
Slovenia
Czech Republic Estonia
Spain United Kingdom
Italy France
Iceland Netherlands
Germany
AustriaSweden
FinlandIreland
SwitzerlandNorway
Luxembourg
-10%
-25%
-50%
-75%
0
50
100
150
200
250
0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 90,000 100,000
Ho
spit
al co
mp
ara
tive p
rice
level
GDP per capita (US$ PPP)
Figure 5 - Working Paper 85, recreated
Case mix
Some prices are higher and some are lower which makes case mix
important, as well as the weights used.
19
-80
-60
-40
-20
0
20
40
60
Acutemyocardialinfarction
Anginapectoris
Normaldelivery
Malignantneoplasm of
bronchusand lungs
Heart failure Cholelitiasis Pneumonia
% difference in cost per case for Medical cases SA vs OECD
-60
-40
-20
0
20
40
60
% difference in cost per case for Surgial cases SA vs OECD
-40
-30
-20
-10
0
10
20
30
40
50
Cataract surgery Arthroscopic excisionof meniscus of knee
Ligation and strippingof varicose veins -
lower limb
Tonsillectomy and/oradenoidectomy
% difference in cost per case for Outpatient cases SA vs OECD
The study uses “typical” cases making up around 30% of total
admissions types.
The study data has 60% of cases as surgical rather than 50% in
medical scheme data which would affect the weighting and result.
Many “typical” case types missing, including mental health
admissions.
Change in profile
GEMS data over the period included a large
take-on of pensioners which had a noticeable
effect on the age profile and burden of disease.
However the working paper cites no significant
change in age profile when considering
increases in certain procedures like hip
replacements.
20
Jan
-11
Ap
r-11
Jul-
11
Oct
-11
Jan
-12
Ap
r-12
Jul-
12
Oct
-12
Jan
-13
Ap
r-13
Jul-
13
Oct
-13
Jan
-14
Ap
r-14
Jul-
14
Oct
-14
Jan
-15
Ap
r-15
Jul-
15
Oct
-15
Jan
-16
Ap
r-16
Dis
ease
bu
rden
in
dex
“pre-92” pensioner group joined
GEMS
Source: Dr Guni Goolab, BHF 2016
Inferences and conclusions
21
South Africa is not alone in having
“hospital prices” above “general
price” levels.
Norway, Switzerland, Luxembourg
and Ireland show similar (or higher)
differentials.
Source: OECD Health Working Paper 85
Inferences and conclusions
22
Working Paper 85 and its precursor working paper 75 mention notable shortcomings in the data used
for the analysis. For observation and study this is tolerable, but caution should be exercised when
extending the conclusions of such studies to high impact policy recommendations.
South Africa’s short length of stay compared to other countries is highlighted as a potential quality
concern without considering quality data.
Considering only price differences without considering output or quality differences presents an
incomplete picture.
Clarifications on the Ramjee paper
23
The purpose of the research was to highlight the considerations for setting equivalent prices across the
public and private sectors in a pluralistic purchasing arrangement.
The research illustrated that structural differences between the two sectors accounts for a large
component of the cost differential.
Very clear from the report that the analysis was constrained by data availability. Part of the intention of the
research was to raise awareness about the data requirements to enable price setting across the two
sectors – an essential part of the preparatory work for NHI.
Unfortunately three years later we face similar data constraints – the absence of reliable case-mix data in
the public sector, as well as meaningful cost data for various types of admissions in the public sector.
In our view it is not appropriate to use the Ramjee paper to defend prices in the private sector – and we
did not make reference to it in our communications with the WHO.
Overall conclusions
We note the WHO responses to the criticisms. In our view these responses do not adequately
address the concerns and we remain of the view that the paper has interpretive flaws.
24
Data collected from only upper income South Africans is weighted against the countries overall GDP,
overall comparative price index, and compared to data from OECD countries where data is
representative of the whole population.
The paper’s findings reflect on how poor South Africans are relative to OECD country residents,
rather than whether private hospitals are expensive.
Extension of the findings to upper income South Africa’s seems a particularly big stretch.