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6. RELATIONSHIP TO OTHER STATISTICAL SYSTEMS
Principles and analytical use
SHA relates to all activities carried out in economic and human life. To provide information for the assessment of health system performance requires the linkage of health accounts to other statistical systems that refer both to economic aspects of health statistics such as ESPROSS and COFOG and other systems like Diagnosis Related Group (DRG) classification.
The possibility of linking SHA to other statistical systems first of all shall enhance the credibility of health accounts. Linkage should be perceived here both as a direct link and as a description of SHA departures from other system.
Compatibility with ESA/SNA will lead to greater transparency of SHA in relation to other classifications like COFOG, COPNI, or COICOP that use the SNA/ESA framework8. Beside the possibility of double checking of some health expenditure aggregates, the value added of such a link is the fact that one of the main indicators used for health care policy is health expenditure presented as a share of GDP, the main aggregate that is derived from SNA. Matching SHA categories of expenditure on functions with certain categories of expenditure on benefits in kind and in cash recorded under ESPROSS, may help data compilers to double check and improve information related to social protection policy.
The statistical unit in the functional distribution within the SHA can be treated as a specific functionally defined health care output for final use. Here the linkage between SHA and DRG or any other output item like 'mixed cases' should follow the rule of 'treatment episode' to be taken into account when attributing them according to categories of function dimension. The examples of such mapping exercises might be of great interest and help for many SHA data compilers.
Available national sources of information determine the staring point in the SHA data compilation. Data sources differ between countries, therefore clear description of the links between SHA and other main statistical systems are of great importance for data compilers and for policy analysts. The policy relevance of the use of the new SHA 2.0 is highly dependent on the clarity to be created in its relations to other systems both in national and international terms. It has to be linked to the national systems in use and compatible with international systems.
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