Health care expenditure (SHA 2011) (hlth_sha11)

National Reference Metadata in ESS Standard for Quality Reports Structure (ESQRS)

Compiling agency: Swiss Federal Statistical Office (FSO)


Eurostat metadata
Reference metadata
1. Contact
2. Statistical presentation
3. Statistical processing
4. Quality management
5. Relevance
6. Accuracy and reliability
7. Timeliness and punctuality
8. Coherence and comparability
9. Accessibility and clarity
10. Cost and Burden
11. Confidentiality
12. Comment
Related Metadata
Annexes (including footnotes)
 



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1. Contact Top
1.1. Contact organisation

Swiss Federal Statistical Office (FSO)

1.2. Contact organisation unit

Section Health Services

 

1.5. Contact mail address

Espace de l'Europe 10

2010 Neuchâtel


2. Statistical presentation Top
2.1. Data description

Health care expenditure quantifies the economic resources dedicated to health functions, excluding capital investment. Healthcare expenditure concerns itself primarily with healthcare goods and services that are consumed by resident units, irrespective of where that consumption takes place (it may be in the rest of the world) or who is paying for it. As such, exports of healthcare goods and services (to non-resident units) are excluded, whereas imports of healthcare goods and services for final use are included.
Health care expenditure data provide information on expenditure in the functionally defined area of health distinct by provider category (e.g. hospitals, general practitioners), function category (e.g. services of curative care, rehabilitative care, clinical laboratory, patient transport, prescribed medicines) and financing scheme (e.g. social security, private insurance company, household). For the collection of the data on health care expenditure the System of Health Accounts (SHA) and its related set of International Classification for the Health Accounts (ICHA) is used. SHA sets out an integrated system of comprehensive and internationally comparable accounts and provides a uniform framework of basic accounting rules and a set of standard tables for reporting health expenditure data. The System of Health Accounts - SHA 2011 is a statistical reference manual giving a comprehensive description of the financial flows in health care.

It provides a set of revised classifications of health care functions, providers of health care goods and services and financing schemes. The SHA is currently used as a basis for a joint data collection by OECD, Eurostat and WHO on health care expenditure. The manual sets out in more detail the boundaries, the definitions and the concepts of health accounting – responding to health care systems around the globe with very different organisational and financing arrangements.

Accounting period: Health expenditure and financing data pertain to the calendar year (1 January to 31 December).
The time coverage of this Quality report is 2010 to 2017 reference years.

2.2. Classification system

Healthcare expenditure is recorded in relation to the international classification for health accounts (ICHA) defining:

  • healthcare expenditure by financing schemes (ICHA-HF) — which classifies the types of financing arrangements through which people obtain health services; health care financing schemes include direct payments by households for services and goods and third-party financing arrangements;
  • healthcare expenditure by function (ICHA-HC) — which details the split in healthcare expenditure following the purpose of healthcare activities — such as, curative care, rehabilitative care, long-term care, or preventive care;
  • healthcare expenditure by provider (ICHA-HP) — which classifies units contributing to the provision of healthcare goods and services — such as hospitals, residential facilities, ambulatory health care services, ancillary services or retailers of medical goods.
2.3. Coverage - sector

1. Household individual consumption on health, including the collective consumption with two exceptions:
i. Occupational health care (intermediate consumption within establishments) minus an estimated share of occupational health in health providers’ and other medical industries net administration;
ii.“Remunerated” unpaid household production in the form of transfer payments (social benefits in cash) for home care of sick, disabled and elderly persons provided by family members.
SHA 2011 Manual recommends following the standard System of National Account (SNA) rules for drawing the production boundary of health care services, albeit with two notable exceptions:
- Occupational health care is included in the national totals of health care spending. In SNA, this item is recorded as ancillary services and part of intermediate production of enterprises and
- Part of the cash transfers to private households for care givers of home care for the sick and disabled are treated as the paid household production of health care.
2. Health care financing schemes: HF1 Government schemes and compulsory contributory health care financing schemes; HF2 -voluntary health care payment schemes;
HF3 - Household out-of-pocket payment; HF4 - rest of the world financing schemes.
3. NACE rev. 2, section Q, human health and social work activities.

2.4. Statistical concepts and definitions

SHA concept is the consumption of health care goods and services.
Health care statistics describe the process of providing and financing health care in countries by referring to health care goods and services, its providers and financing. For the collection of the data on health care expenditure the System of Health Accounts (SHA) and its related set of International Classification for the Health Accounts (ICHA) is used. SHA is a tri-axial system in which the financing, provision and consumption dimensions are covered by the ICHA (International Classification for Health Accounts): Health Care Functions (HC), Health Care Providers (HP), Health Care Financing Schemes (HF).
Data are presented in 3 summary (one-dimensional) tables and 3 cross-classification tables (2-dimensional tables).

Summary tables provide data on:

  • Current expenditure by provider (ICHA-HP)
  • Current expenditure by function (ICHA-HC)
  • Current expenditure by financing scheme (ICHA-HF)

Cross-classification tables refer to:

  • HC x HP: Health care expenditure by function and provider: data on which type of health care goods and services are supplied by which health care provider;
  • HC x HF: Health care expenditure by function and by financing scheme: data on how are the different types of services and goods financed;
  • HP x HF: Health care expenditure by provider and by financing scheme: data on from which health care provider and under which particular financing scheme are the services and goods purchased.
2.5. Statistical unit

Commission Regulation 2015/359 concerns the collection of data on "current expenditure on healthcare" which is defined as the "final consumption expenditure of resident units on health care goods and services".
There is a very close relationship between the concept of "final consumption expenditure" as defined in the System of Health Accounts (SHA) and in National Account and, as a consequence, also between the underlying economic transactions as recorded in the two accounting frameworks.
In National Accounts there are two types of statistical units: institutional units and local kind-of-activity units (KAU). A local KAU groups all the parts of an institutional unit in its capacity as producer which are located in a single site. A local KAU belongs to one and only one institutional unit.
SHA uses the same two types of units for data compilation.
Local KAUs operating as providers of healthcare goods and services to resident units are statistical units in SHA.
Also transactions by institutional units are recorded in SHA, in which framework institutional units are also referred to as "financing agents". More precisely, SHA financing agents are institutional units that manage one or more financing schemes. The transactions are executed by the financing agents, according to the rules of the financing schemes.
Financing agents serve as key statistical units in producing national health accounts. While financing schemes are the key units for analysing how the consumption of health care goods and services is financed, the data concerning the relevant transactions are collected either from the financing agents that operate the different financing schemes or from the providers.
The concept of "healthcare financing schemes" in SHA is an application and extension of the concept of "social protection schemes" defined by the European System of Social PROtection Statistics (ESSPROS):  "a distinct body of rules, supported by one or more institutional units, governing the provision of social protection benefits and their financing ...". The social protection scheme is the statistical unit in ESSPROS. It is an analytical unit that allows describing the complete structure of the social protection financing system:  expenditure and receipts.
According to SHA Manual 2011, "the key concepts for describing the structure of the health care financing system are based on measuring: (a) the expenditure of health care financing schemes, under which goods and services are purchased directly from health care providers, on the one hand, and (b) the types of revenues of health care financing schemes, on the other hand.  
Commission Regulation 2015/359 limits its scope to the collection of data on the expenditure of health care financing schemes.

2.6. Statistical population

SHA focuses on the consumption of health care goods and services by the resident population irrespective of where this takes place. This implies the inclusion of imports (from non-resident providers) and the exclusion of exports (health care goods and services provided to non-residents).

2.7. Reference area

The data aims at providing a complete overview of expenditure on health care goods and services consumption of services and goods by the resident population on the national territory of a country.

2.8. Coverage - Time

SHA 2011 Data is calculated for the three dimensions of providers, functions and financing with fine granularity from 2010 until today.

SHA 2011 Data is retropolated with fine granularity for financing and wider granularity for providers and functions from 1995 to 2009.

SHA 2011 Data is retropolated for providers with raw granularity from 1985 to 1994.

SHA 2011 Data is retropolated for providers with very raw granularity from 1960 to 1984.

2.9. Base period

Not applicable.


3. Statistical processing Top
3.1. Source data

Several data sources are used (as of data notification in March 2018):

-          Surveys/census: 7

-          Public administrative records: 7

-          Financial reports: 2

-          Other: 0

 

Surveys/censuses

Source name

Brief description of source

Primary SHA variable(s) using this data source

Time period covered by this data source

Timeliness

(Number of months after the end of the accounting period)

Frequency

Processing

Hospitals Statistics, FSO

Annual full survey HP.1, HC.1.1, HC.1.3.1 HC.2.1, HC.0 since 1998 11 months annual Treatment of missing data on hospital revenues

Statistics of Medico-Social Institutions, FSO

Annual full survey

HP.2, HC3.1

since 2002

11 months

annual

 

Community Nursing and Home Care Statistics, FSO

Annual full survey

HP.3.5, HC.3.4

since 2011

11 months

annual

 

Data of Swiss pharmaceutical association

annual HP.5.1, HC.5.1 since 2012 10 months annual  

Data of Swiss Drug store association

annual

HP.5.2, HC5.1

since 2012

20 months

annual

 

Data of zewo (a certification agency for NPO)

annual

HP.6, HC6.1

since 2013

6 months

annual

 

Household budget surveys FSO

Annual sample survey

HP.9, HC.1.3, HC.5.1

since 2010

16 months

annual

 

 

Public administrative records

Source name

Brief description of source

Primary SHA variable(s) using this data source

Time period covered by this data source

Timeliness

(Number of months after the end of the accounting period)

Frequency

Processing

Old age Insurance statistics, Invalidity Insurance statistics, Supplementary benefits, Federal Social Insurance Office

Annual statistical data on finances, incl. paiments for health goods and services

HP.8.1, HC 3.4., HF1.1, HF1.2.2

since 1985

10 months

annual

 

TVA statistics

annual

HP.4.2, HC4.1, HP.5.9, HC.5.1

since 2008

25 months

annual

 

Public finance Statistics, Federal Finance Administration

Annual full survey, except for municipalities (sample)

HP.6, HP7.1, HC.6.1, HC.6.2, HC.7.1, HF.1

since 1985

20 months

annual

 

Compulsory Sickness Insurance Statistics, Federal Office of Public Health

Annual full survey on Sickness Funds in charge of this social insurance

HP.7.2, HP.7.3 HC.7.2. HC.7.3

since 1996

10 months

annual

 

Compulsory Accident Insurance Statistics, Statistical pool 

Annual survey of Insurance companies in charge of this social insurance, mandate from surveillance authority (Central Government)

HF1.2.1

since 1985

12 months

annual

 

Compulsory Sickness Insurance Statistics, Statistical pool 

Annual survey of Insurance companies in charge of this social insurance, mandate from surveillance authority (Central Government)

HF.1.2.1, HF.3.2

since 2000

12 months

annual

 

Private insurance statistics, Swiss Financial Market Supervisory Authority FINMA

Annual full survey

HF.2.1, HF.3.2

since 1996

11 months

annual

 

 

Financial reports

Source name

Brief description of source

Primary SHA variable(s) using this data source

Time period covered by this data source

Timeliness

(Number of months after the end of the accounting period)

Frequency

Processing

Accounting reports Swiss dental association

annual survey HP.3.3,  HC.1.3.2 since 1998 16 months annual Use of figures on revenues for the purpose of estimating turn overs of health professionals for health goods and services

Annual reports

For specific providers/provisions: Swiss Air Rescue, Suva (accident insurance, Tobacco Fund, Health Promotion Fund, non professional accidents prevention (bfu) HP.6, HP.7.1., HC.7.1. since 2010 6 -12 months annual  
3.2. Frequency of data collection

Annual.

3.3. Data collection

Data are collected through the joint health accounts questionnaire (JHAQ) that countries submit to Eurostat during the annual data collection exercise. There is a voluntary deadline to send the JHAQ questionnaire for the calendar year T by the 31st of March T+2. The joint health accounts questionnaire (JHAQ) is coordinated in agreement with the World Health Organisation (WHO) and the Organization of Economic Co-operation and Development (OECD). These three international organisations are known collectively as the International Health Accounts Team (IHAT). Countries submit data to Eurostat on the basis of Commission Regulation (EU) 2015/359 of 4 March 2015 implementing Regulation (EC) No 1338/2008 of the European Parliament and of the Council as regards statistics on healthcare expenditure and financing.

3.4. Data validation

The 2018 JHAQ includes a number of features which allow national data correspondents to perform various quality checks before submitting the data. The embedded programmes allow the verification of:


1- Consistency of the data between tables,
This step checks if the marginal totals reported in each table of the JHAQ are consistent across all tables. For example, for each function (HC), the total across all financing schemes (HF) in the HCxHF table has to be equal to the total across all providers (HP) in the HCxHP table, i.e. the values in the column “All HF” in the HCxHF table have to be equal to the values in the column “All HP” in the HCxHP table. Any detected differences are flagged up in the corresponding row or column in the relevant tables and all inconsistencies are listed in the “Report” worksheet by variable code together with the amount by which the respective variable differs between the two compared tables. A positive value indicates that the first listed table has a higher value for the same variable, and vice versa.

 

2- Consistency of the data within tables,
Any detected inconsistencies are listed by variable code together with an indication of which total is not equal to the sum of its subcomponents as well as the numerical difference. A positive figure indicates that the total is greater than the reported sub-components, and vice versa.

  • The presence of negative values,

Entries in the tables cannot be negative as they refer to the consumption of goods and services.
If an individual data table is checked for internal consistency, the negative values check is performed for the relevant table and then any negative values are highlighted red and crossed out.

  • The presence of atypical entries,

The atypical entries check provides information whether the data tables contain values in cells which are – if at all – only reported by very few countries and are thus atypical for health accounting.
If an individual data table is checked for internal consistency, the atypical entries check is performed for the relevant table. In the data tables, any cell containing an atypical entry will be highlighted for national data providers.
Should any atypical entries be identified, compilers should scrutinize in detail the transactions that led to entries in those cells and assess whether the accounting rules of SHA have been correctly applied. If they come to the conclusion that the transactions are recorded in the correct categories of the ICHA classifications, then the corresponding atypical entries represent unique – and correctly accounted for – features of the country’s health system. In this case a short description of the nature of the transactions should be included in the accompanying Metadata file under “II.3. Atypical entries”.
If, on the other hand, compilers come to the conclusion that the transactions are not recorded correctly, then they need to make adjustments in the concerned tables. In case the transactions recorded in a cell do not belong to the boundaries of SHA (e.g. they refer to intermediate consumption) the value of the respective cell should be deleted (and all cells that are affected by this change adjusted accordingly). In case the transactions are misreported and another category of the ICHA classification is more appropriate, the value of the cell should be transferred to the correct cell of the table.

 

3- The growth rates against the previous year and the magnitude of revisions as compared to previously submitted data. Results are grouped into three different categories:

  • Breaks in series (the current questionnaire shows no data for an item that is not null in the other file)
  • Newly reported (the current questionnaire contains data for an item that is empty in the other file)
  • Differences (all other types of differences)
3.5. Data compilation

SHA data is compiled both by a bottom-up approach as well as by a top-down approach, depending on the data source. Compilation is done by financing schemes and by different health care functions/task areas. The results of the several calculations are then aggregated.

To gain the differentiation between the different SHA-dimensions (especially HC and HP) quotas and pro-rating and utilisation keys are applied on some spending items. For some spending items it is necessary to extra-/intrapolate data as there is no up-to-date data available or data is missing for certain years. For some other spending items, estimation methods have to be applied.

 

Several methods are normally used for estimations:

  • Balancing item/Residual method: For example, if data are available from the financing side, which permit accurate estimation of the flows to a provider or function, then an acceptable estimation method is to subtract these expenditure flows from the total revenues, and derive the expenditure flows from the unmeasured financing scheme as a residual.
  • Pro-rating/Utilisation key: Typically in the absence of direct spending data, a utilisation key linked to the proportion of resources used can be constructed in order to distribute e.g. aggregate provider spending across functions. For every key a fraction of total utilisation within the cost-unit is assigned: fractions in the key must add up to 100% of all care delivered by the cost-unit. Examples of utilisation keys are admissions, bed-days, contacts, staffing, etc.
  • Interpolation/Extrapolation: In the absence of data for the period in question, missing values can be estimated using known data points.
  • Or other.

SHA variable(s)

Main method

Brief description of methodology

HP.4.1 Providers of patient transportation and emergency rescue

Pro-rating/Utilisation key Estimation of health professionals turnover based on employement and accounting data, plus public expenditure for emergency services

HP.3.1 Medical practice

Interpolation/Extrapolation Estimation on pension fund data from 2008, since then extrapolated by using the respective values in sickness-fund-data

HP.3.3 Other health care practitioners

Pro-rating/Utilisation key Estimation by fixed factor on respective value in sickness-fund-data
3.6. Adjustment
Restricted from publication


4. Quality management Top
4.1. Quality assurance

Authorities responsible for SHA data collection are working to ensure that the statistical practices used to compile national health accounts are in compliance with SHA methodological requirements and that good practices in the field are being followed, according to the methodology underlined in the SHA 2011 Manual and European Statistics Code of Practice respecting professional independence of the statistical authorities. Procedures are in place to plan and monitor the quality of the health care expenditure statistical production process.

4.2. Quality management - assessment

Quality issues mainly arise from the use of extrapolations, because source data is not available. This pertains mainly to:

- doctors (this issue will be resolved in the delivery starting in spring 2020)

- homes for handicapped people and substance abuse (new issue since 2015, source statistics has been cancelled)

- other ambulatory providerd

- providers of ambulatory care.


5. Relevance Top
5.1. Relevance - User Needs

The statistics is used by:

- health care stakeholders (insurances, hospitals, providers of ambulatory care),

- the federal government, especially for several policy indicators and for the reply to questions from the parlament

- the cantonal (regional governments)

- the general public in order to assess the the cost burden of health

- by researchers.

5.2. Relevance - User Satisfaction

The FSO is in dialogue with stakeholders and receives feedback and questions from them. No systematic surveys are done, however.

5.3. Completeness

Source data is partly incomplete and has to be estimated (see 5.3.1).

5.3.1. Data completeness - rate

Source data is incomplete and has to be estimated for:

- medical practices (new survey available for 2018), homes for disabled and substance-abusing (since 2016), psychologists, physiotherapists, ergotherapists, logopaedists, chiropracticians, midwifes, pendulary migration for home health care

- ventilation of financing by private insurers according to providers/functions

- homes for handicapped people and substance abuse (statistics was cancelled).


6. Accuracy and reliability Top
6.1. Accuracy - overall

Overall accuracy is sufficient.

6.2. Sampling error

- ventilation of accident insurance data to providers and functions is only covering the public accident insurers (60%), not the private insurers.

- sample data for dentist practices covers only the German speaking area (about 65% of the country).

6.2.1. Sampling error - indicators

No information available.

6.3. Non-sampling error

No information available.

6.3.1. Coverage error

No information available.

6.3.1.1. Over-coverage - rate

 Not applicable.

6.3.1.2. Common units - proportion

No information available.

6.3.2. Measurement error

No information available.

6.3.3. Non response error

No information available.

6.3.3.1. Unit non-response - rate

No information available.

6.3.3.2. Item non-response - rate

No information available.

6.3.4. Processing error

No information available.

6.3.4.1. Imputation - rate

No information available.

6.3.5. Model assumption error

No information available.

6.4. Seasonal adjustment

Not applicable.

6.5. Data revision - policy

No general revision policy, but an established routine of two practices. Firstly, publication of provisional data in spring and revised definitive data in autumn, and secondly, punctual revision of sources and methods if data quality makes it neccessary.

6.6. Data revision - practice

Data 2010-2015 has been completely revised. Older values have been retropolated based on growth rates in the old model.

6.6.1. Data revision - average size

No information available.


7. Timeliness and punctuality Top
7.1. Timeliness

Member States are required to transmit their data to Eurostat in compliance with the Commission Regulation 359/2015 transmission deadlines.
Data and reference metadata for the reference year T should be transmitted to Eurostat by 30 April T+2.

7.1.1. Time lag - first result

First data is published nationally in April/May of the year T+2.

7.1.2. Time lag - final result

Final data is published nationally in October of the year T+2.

7.2. Punctuality

Provisional data for April was postponed to June due to illness. Definitive data was punctual.

7.2.1. Punctuality - delivery and publication

Provisional data for April was postponed to June due to illness. Definitive data was punctual.


8. Coherence and comparability Top
8.1. Comparability - geographical

Not applicable at national level.

8.1.1. Asymmetry for mirror flow statistics - coefficient

Not applicable.

8.2. Comparability - over time

Breaks in time series resulting from methodological changes

Year

Items affected by the break

Explanations

1995

All items

Starting its time series in 1995, the FSO published in 2009 revised data of HA according to OECD methodology. Backward estimations of the most important aggregates of health expenditure have been calculated back to 1960. Some less aggregated time series have been partially adjusted.

2010

All items With the 2017 revision all values since 2010 have been recalculated. Older values have been retropolated on a weighted mix of annual growh rates.
8.2.1. Length of comparable time series

SHA 2011 Data is calculated for the three dimensions of providers, functions and financing with fine granularity from 2010 until today.

SHA 2011 Data is retropolated with fine granularity for financing and wider granularity for providers and functions from 1995 to 2009.

SHA 2011 Data is retropolated for providers with raw granularity from 1985 to 1994.

SHA 2011 Data is retropolated for proversider with very raw granularity from 1960 to 1984.

8.3. Coherence - cross domain

Coherence with ESSPROS is not guaranteed, though some data from Health Accounts is used for ESSPROS.

8.4. Coherence - sub annual and annual statistics

Not applicable.

8.5. Coherence - National Accounts

Coherence with National Accounts is not guaranteed, though some data from Health Accounts is used for National Accounts.

8.6. Coherence - internal

Atypical entries:

Years(s)

Atypical entry

Explanations

 since 2010

HC.7.1 x HP.7.1 x HF.3.1

This is a residual value in the public finance statistics : expenses minus revenues. It represents for the most important part fees for  administrative and preventive services paid by private households

 since 2010

HC.7.1 x HP.7.1 x HF.1.1

Public services (gemeinwirtschaftliche Leistungen) in hospitals are a new national category. Expenditure for Research & Teaching/Training as well as structural policy is financed solely by the Cantons since the last revision of the LMAL


9. Accessibility and clarity Top
9.1. Dissemination format - News release

Regular press release in April/May of the year T+2.

9.2. Dissemination format - Publications

Currently no regular publications/commentaries.

9.3. Dissemination format - online database

Data is provided with an extensive set of standard tables, additional information is given upon request.

9.3.1. Data tables - consultations

No information available.

9.4. Dissemination format - microdata access

Not applicable.

9.5. Dissemination format - other

No information available.

9.6. Documentation on methodology

A methodological report was compiled concering the last revision in 2017

German: https://www.bfs.admin.ch/bfs/de/home/statistiken/gesundheit/kosten-finanzierung/finanzierung.assetdetail.3644715.html

French: https://www.bfs.admin.ch/bfs/fr/home/statistiques/sante/cout-financement/financement.assetdetail.3644714.html

9.7. Quality management - documentation

A methodological report for the statistic has been published in 2017 following the last revision of the statistics. A handbook for producing the statistics, which shall be as well open to the public, shall be developed soon.

9.7.1. Metadata completeness - rate

No information available.

9.7.2. Metadata - consultations

No information available.


10. Cost and Burden Top

No specific burden on individual respondents, since only existing surveys are used.


11. Confidentiality Top
11.1. Confidentiality - policy

The Regulation (EC) No 223/2009 on European statistics (recitals 23-27, 31-32 and Articles 20-26) applies.

11.2. Confidentiality - data treatment

Data is treated only within the FSO, section Health Care services. Source data is only given away if the original owner of the dataset has agreed on it.


12. Comment Top

In 2017 national data have been revised and fully recalculated, starting with data from 2010. Values from 1995 to 2009 have been retropolated, albeit with a less detailed data granularity. The continuity with the international classification is guaranteed. The new national model includes negative values since outpatient hospital treatment incurs losses. For the international classification those negative values were eliminated by modifying the values in the HC classification.

Provisional revised figures for the years 2010 to 2015 were reported in March 2017. Definitive figures for the years 2010 to 2015 with some minor adaptions have been published nationally in October 2017. Most notably, inpatient medication in hospitals is reported as well as pendulary migration. Minor coding errors  of the provisional figures have as well been corrected.


Related metadata Top


Annexes Top