EXPENDITURE BY DISEASE, AGE & GENDER

15th meeting of the health accounts experts

• In 2007-08, project “Estimating Expenditure by Disease, Age and Gender under the System of Health Accounts (SHA) Framework”

– Guidelines developed

– Case studies of 6 countries

• Between 2011-2013, the follow-up project is launched to accelerate consistent and comparable health expenditure data by disease categories

– Increase # of countries for hospital (i.e. inpatient care) sector

– Expand the data collection beyond hospital expenditures to include outpatient (ambulatory) and pharmaceutical spending

– Investigate the use of other sources when resources do not allow for a full expenditure study (e.g. activity data)

– Assess the link between direct, indirect and intangible costs

Background and Objectives

SHA 2011 Framework

SHA Framework in Disease Accounts

Cost of Illness = Direct costs + Indirect Costs + Intangible costs

Direct (the National Health Service) + Indirect (ratio of indirect to direct costs) + intangible costs using WHO Global Burden of Disease data

Example of Direct, Indirect and

Intangible Costs

Economic burden of disease in England by disease

direct, indirect and intangible costs(indirect costs estimated using Canadian ratios : direct costs)

£0

£20,000

£40,000

£60,000

£80,000

£100,000

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Direct costs

2011

Economic Burden of Disease in England, 2011

Source: Department of Health, 2013

Top-down allocation of expenditures

SHA Current Health Exp.

Partition into homogeneous cost units (HP, HC, HF)

Hospital in-patient

Hospital out-

patient

Dentist offices

Specialists ….. GP

offices

Use a cost unit specific utilisation key to allocate costs over dimensions (disease, age, gender)

• Increased from 6 in 2008 to 16 countries in 2011-13 – Mostly in hospital or inpatient spending

– Australia, Canada, Czech Republic, England, Finland, France, Germany, Hungary, Israel, Japan, Korea, the Netherlands, Slovenia, Sweden, Switzerland, and the United States

– Not all countries follow SHA framework (e.g. Germany, Korea and Netherlands v.s. England, Japan)

Overall data availability

Type Frequency Countries Disease Groups Direct cost components

Regularly producing

Regular (1-3 years)

Australia Canada Germany Netherlands Japan

Country-specific categories (all), but can be re-grouped to ICD-10/ISHMT

Direct costs by all HPs

Capable of producing

on an ad-hoc basis or on demand

Czech Republic Hungary Korea Sweden Finland Slovenia Israel Switzerland

ICD chapters, ISHMT

Direct costs by some HPs (mainly hospitals) or HCs (inpatient)

Producing but not official

Frequent (i.e. annual)

England Country-specific categories or GBD only

Varies

Countries at different stages of

production in disease accounts

Top spending in inpatient/hospital care

(HC.1.1/HP.1)

0%

5%

10%

15%

20%

25%

30%

IX - Circulatory system II - Cancer XIX - Injuries XIII - Musculoskeletal XI- Digestive system

• high share of spending on circulatory diseases in the inpatient sector in most countries (around 18% on average) with a range between below 15% in Australia and Korea and 25% or more in Japan and the Czech Republic

Mental Health by ISHMT (1)

0%

5%

10%

15%

20%

Canada(2008)

Czech Republic(2009)

Finland(2010)

Germany(2008)

Korea(2009)

Netherlands(2007)

Dementia Alcohol Psychoactive substances Schizophrenia mood disorders other mental

• Chapter V, Mental and Behavioural Disorders, consists of dementia and other mild to severe mental health conditions, thus, further breakdown is preferable.

• Higher share of spending on treatment of schizophrenia in Finland and Korea while mood disorders make up a higher share in Germany and the Netherlands.

Breakdown of different mental health conditions as a share of acute in-patient expenditures

Mental Health by ISHMT (2)

• Hospitals are by far the common platform to provide care of those with mental health conditions, followed by long-term care insititutions.

• Ambulatory sector plays a large role in caring of mental health patients in Czech Republic comparing to other countries.

• Per capita spending differs greatly from country to country. For example, hospital spending ranges from US$295 (NLD), $147 (DEU), $71.7 (KOR) and $36 (CZE).

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Germany Korea Netherlands Czech Republic

Breakdown of mental health conditions by ISHMT

Hospital Long-term care Ambulatory Pharmaceuticals Other providers

0%

5%

10%

15%

20%

25%

30%

35%

DEU FRA KOR JPN NLD SVN Average

Digestive system Symptoms/Other factors Musculoskeletal system Circulatory system Respiratory system Genitourinary system

Top spending in outpatient/ambulatory

sector

• On average 25% of outpatient spending relates to Chapter XI (Digestive system) which includes expenditure on oral health.

• Between 6 and 10% on average, relate to Chapter XIII (Musculoskeletal), Chapter X (Respiratory) and Chapter XIV (Genitourinary).

• Challenges are that the sector combines separate data sources and the greater role of private financing

• Availability of medical goods and particularly pharmaceuticals which typically account for around 90% of the category.

• Chapter IX: Circulatory disease accounts for 20% on average of pharmaceutical spending and more than twice the level of the next category, Chapter X: Respiratory system.

Top spending on medical goods/retailers

0%

5%

10%

15%

20%

25%

30%

DEU FRA HUN KOR NLD SVN Average

Circulatory system Respiratory system Disease of the eye Endocrine, nutritional Digestive system

• Difficulties in allocating across the SHA classification categories (e.g. different data sources, private spending)

• Unallocated amounts (0% in Korea and Germany up to 35% in Czech Republic for CHE)

• Allocation by provider versus function

• The lack of or reduction in resources in statistical offices and ministries

• Reason for identifying other ‘short-cuts’ through existing data (e.g. activity data such as hospital discharge, etc)

Challenges need to be addressed

• Question: Is it possible to derive expenditures using the data from countries with good expenditure by disease data and health utilisation data (e.g. bed-days)? – Using per-diem (which assumes all bed-days for

all diseases use are the same) not enough

– Resource intensity is not homogeneous across treatment of different diseases • E.g. Diagnosis Related Groups (DRGs) classifying

patient based on primary diagnosis used for reimbursement of hospital stays

Deriving expenditure by disease for in-

patient curative care (1)

• Steps: – Using country specific health utilisation data (e.g.

bed-days by ICD), health spending and health data (e.g. morbidity and mortality)

– Coming up with average weight by ICD by country [the ratio of the share of expenditures (as a percentage of all hospital spending) to the share of bed-days (as a percentage of all bed-days), by diagnostic category]

– Fitting a regression model to see if we can actually ‘predict’ the level of spending (i.e.%)

– Filling information gaps of countries that do not produce expenditure by disease category

Modeling inpatient expenditures using

activity data (2)

Average weights (initial)

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• Model 1: employed ICD chapter level data

• Model 2: employed ISHMT level data

• E.g. Canada - Results: predicted expenditure values, as expected, perform better than using straight bed-days as an allocation key

Modelling and filling information gaps

0

0.02

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0.12

0.14

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bed-days exp model 1 model 2

• Expenditure on medical goods accounts for 23% of CHE across EU on average

• Private spending data is limited (e.g. OTC medicines)

• An inventory of pharmaceutical consumption and sales figures has also been compiled

• Australia, Canada, Germany, Korea, and the Netherlands, are examples

• Australia and the Netherlands reply upon national physician surveys. Korea from social insurance data. Canada and Germany from IMS

• Mapping ATC to ICD needed

Linking Pharmaceutical Data to Disease

• Derive a general, or average, mapping based on the data that is currently available for Australia, and the Netherlands based on the national samples of physicians.

• Derive a general, or average, mapping based on the data that is currently collected by IMS.

• Use the country-specific data that IMS collects in the 24 OECD countries. Under this option there further exists the option of using IMS’ data on expenditures or the available national data.

Options on mapping from ATC to ICD

• Data: physician surveys or bottom up methods based on encounter data.

• Less variation in the intensity of services according to disease, particularly for basic GP consultations.

• A clear relationship between number of consultations per disease category and the resource costs of the associated health care services.

• In the absence of detailed costing data, the use of basic encounter information (i.e. ambulatory sector to total numbers of outpatient/ physician and dentist consultations) can be used.

Linking Physician/Outpatient Spending

to Disease

• The Bettering the Evaluation and Care of Health (BEACH) programme continuously collects information about the clinical activities in general practice in Australia including: – characteristics of the GPs

– patients seen

– reasons people seek medical care

– problems managed, and for each problem managed (direct link)

• Data from BEACH were used to allocate private medical services provided by both GPs and specialists.

Example of Australian BEACH survey

• Data is allocated according to ICD-10 chapters at minimum;

• Using International Hospital Morbidity Short List (ISHMT) to properly analyse the expenditures associated with specific diseases;

• All attempts should be made to allocate as possible; where data is lacking expenditures should remain unallocated; and

• The frequency of reporting needs to be standardised (3 years, for example).

Overall recommendations

• The OECD.Stat data warehouse as summary tables

– The accessibility of the data and the transparency of the methodologies will act as a spur to improve the country coverage and comparability in the future.

• Dedicated page for health spending by disease will be created as part of the OECD SHA website.

• Health Working Paper comparing the methodologies and results of the available country data is planned to be released by Q1 2014.

Dissemination Plan (1)

• The following tables and charts are expected to be made available:

– Current health expenditure by ICD chapter (age, gender) - NCU, % current health spending, per capita spending;

– Hospital/inpatient expenditure by ICD chapter (age, gender) - NCU, % total hospital/inpatient spending, expenditure by discharge / bed day;

– Outpatient/ambulatory expenditure by ICD chapter (age, gender) - NCU, % total outpatient/ambulatory spending;

– Medical goods expenditure by ICD chapter (age, gender) - NCU, % total medical goods spending.

Dissemination Plan (2)

• More innovative and dynamic charts for countries and changes over time will be produced

In bubble charts

I. Infectious diseases 3.0%

II. Neoplasms 10.9%

III. Diseases of the blood 0.8%

IV. Endocrine,etc diseases 2.3%

V. Mental disorders 7.4%VI. Nervous system

3.0%

VII. Eye and adnexa 0.4%

VIII. Ear 0.4%

IX. Circulatory system 17.7%

X. Respiratory system6.3%

XI. Digestive system 7.6%

XII. Skin 0.9%

XIII. Musculoskeletal system 7.0%

XIV. Genitourinary system 4.0%

XV. Pregnancy etc 5.3%

XVI. Perinatal period 2.3%

XVII. Congenital malformations 1.3%

XVIII. Symptoms, etc, n.e.c. 4.7%

XIX. Injury 11.6%

Other 3.0%

Total hospital inpatient

expenditure72 242 mln SEK

2011

• COMMENT on the plans to disseminate available data;

• REVIEW the country data sources in Chapters 5, 7 and 8;

• INFORM the Secretariat of the intention to undertake expenditure by disease studies in the near future.

The Secretariat invites participating

experts to: