1 A framework for international comparisons of volume and prices in health care Interim Report Manfred Huber 7 th Meeting of HA Experts and Correspondents for Health Expenditure Data

2 Overview of presentation Objectives of the project of health specific PPPs (H-PPPs) Expenditure classifications for price comparisons Potential data sources: Where are we? What’s missing? Aggregation strategies for multilateral comparisons Which role for quality adjustment? Conclusions & Next steps

3 The project of price and volume comparisons: objectives Set of comparative indicators at different levels of aggregation (ICHA-HC [three]/two/one digit level) Indicators for bilateral comparisons Simple comparisons of volume measures with unweighted OECD averages But also aggregation to Indicators for multilateral comparisons....for Improved purchasing power parities for health (H-PPPs) (“health-specific” PPPs)

4 Basic definitions (SNA terminology) Expenditure = price x volume Value: synonym to “expenditure” Quantity: units for homogenous, individual goods or services Volume: weighted average of quantities of individual products or groups of products Output: volume of well-defined bundle of goods

5 Expenditure classifications for price comparisons: ICHA

6 Expenditure classifications for price comparisons: ICHA (cont)

7 Four estimation methods and their data requirements

8 Method of choice ? Unit prices for market services (in particular for medical goods) Indirect comparison for non-market services via output measures from (secondary) administrative data sources  suggested for the H-PPP project Input price method for non-market services (Eurostat- OECD, 2002 PPPs) But: non-market/market distinction in SHA-based health accounts not available....and what about expenditure corresponding to transaction prices for mixed public-private payment (cost-sharing)?

9 Expenditure classification: ICHA modified

10 Which are the “shortcuts” used for health in current PPPs?

11 Current specification of health in PPPs Detailed list of market prices for medical goods and selected ambulatory/outpatient services (~540 of which 85% are pharmaceuticals Advantages: questionnaire with very detailed specifications, tested in the field Potential to complement list of ambulatory services (e.g. put in more services which correspond to current/latest technology; more expensive treatment) E.g. complement unit-prices for long-term care

12 Example of detailed specification: pharmaceutical

13 Example of detailed specification: home care

14 Example of detailed specification: dental care

15 How to improve PPPs and move to H-PPPs? Focus on “comparative resistant” item of hospital care Big spending item, not covered well in current PPPs Select inpatient care items: high spending items; dynamic spending development (ageing/chronic conditions); e.g. surgery like: hip/knee replacement Complement ambulatory care list with high volume surgical procedures (cataract etc.) Further develop indicators for long-term care

16 Potential data sources Use of secondary data sources: survey too costly? Design hospital data set with a view to provide relevant data for H-PPP purposes Same for long-term care Health care quality indicators project: many indicators refer to volumes (often measuring times, “right thing is done”) Co-operate with main PPPs project to improve available items in questionnaire and for quality checking?

17 Calculation and aggregation: standard methods of linking countries Comparison of four countries with a multilateral average Complete system of bilateral comparisons Source: Hill (2002) Linking Countries and Regions using Chaining Methods and Spanning Trees

18 Linking countries with (minimum) spanning trees Examples of spanning trees Source: Hill (2002) Linking Countries and Regions using Chaining Methods and Spanning Trees

19 Example of spanning tree Source: Hill (2002) Linking Countries and Regions using Chaining Methods and Spanning Trees

20 Which role for quality adjustment? Quality differences important issue that needs to be addressed Direct adjustment versus post-adjustment/analysis? Suggestion to keep volume/output/quality separate for the first phases of the project Later on, test regression models before “adjustments” can be justified Hedonic regression technique for PPPs available, but seldom used so far; should be tested once more data available

21 Conclusions and next steps Project of H-PPPs major undertaking, potentially resource intensive Better linking of SHA to SNA becomes a concern Synergy with overall PPP project? Break project down in manageable parts Get countries involved in bilateral comparisons to improve quality, commitment and save cost? Need to write down the math on index formulas to be tested and do first tests with hospital data

22 Points for discussion Comments on conceptual framework Data availability and feasiblity from national sources Interest to participate in further methodological work and work with test data