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Socio-economic status and medical expenditures

Socio-economic status and medical expenditures. Health Systems Research, Public Health School, UCL. Vincent Lorant. June 2002. Health System Research, Public Health School, Université Catholique de Louvain. Objective.

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Socio-economic status and medical expenditures

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  1. Socio-economic status and medical expenditures Health Systems Research, Public Health School, UCL Vincent Lorant June 2002 Health System Research, Public Health School, Université Catholique de Louvain

  2. Objective Why and how socio-economic status (SES) should be considered in risk adjustement model ?

  3. Contents • Rationale for SES adjustement :fairness and quality • International review of SES adjustement • Methodological consideration • Indicators to be used

  4. Why adjust for socio-economic status ? • Horizontal equity : SES catches unobserved differences in health • Vertical equity : differences in ability to pay. • SES influence the bundle of care • For given use of care, lower SES individuals have a poorer health outcome

  5. What other countries do ? • In a recent international review 10 countries out of 20 included some SES adjustement • Employment and welfare had the edge • 8 countries adjusted for geographical features • SES weights are similar to the morbidity weights in the British formula

  6. How to adjust for SES ? • Separate the income effect from the deprivation effect • Poor relevance of observed pattern of care to model capitation formulae • SES at the ecological level should be considered • Availability of data is a weak argument

  7. Summarize your points. • State your conclusion. Make it relevant to your audience.

  8. Spatial autocorrelation of socio-economic status, health and health care : 589 Belgian municipalities Source : Lorant, Social Science and Medicine, 2001

  9. Which SES indicator to use ? • Continuous prefered to binary • Time-invariant • Applying to active and inactive • Assessing status and deprivation • Educational status and deprivation are good choices

  10. Recommendations • The formula should be designed on expected care or on the least unequitable type of care • Use more valid and continous SES indicators • Models should consider spatial clustering • Models aiming not only to avoid cream- skimming but also to promote quality of care

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