1. Use of health surveys in resource allocation Matt Sutton Senior Research Fellow University of Glasgow m.sutton@clinmed.gla.ac.uk Health Survey's User Group Friday 23 January 2004 DoH, Skipton House, London

2. Colleagues on previous work Scotland: Derivation of an adjustment to the Arbuthnott formula for socioeconomic inequities in health care with Alex McConnachie England: Allocation of Resources to English Areas Report with Hugh Gravelle, Stephen Morris, Alastair Leyland, Frank Windmeijer, Chris Dibben and Mike Muirhead [http://www.isdscotland.org/isd/info3.jsp?pContentID=842&p_applic=CCC&p_service=Content.show&]

3. Outline Overview of resource allocation formulae Direct use of survey information Indirect use of survey information experience in Scotland experience in England

4. Overview of resource allocation formulae Purpose - Allocate national resources to health care organisations to: Scotland: promote equitable access to health care Wales: ensure more equitable access to health services in accordance with health needs England: contribute to the reduction of avoidable inequalities in health

5. Structure of resource allocation formulae Population size Adjusted for demography Adjusted for additional need factors Adjusted for additional cost factors Market Forces Factor Additional costs of remoteness and rurality

6. Three basic approaches to allocation 1. Based on relationships between population characteristics and use of health care 2. Based on actual prevalence of ill-health 3. Based on relationships between population characteristics and prevalence of ill-health (predicted prevalence)

7. 1. Adjustments based on average costs Rich £200 Poor £400

8. 2. Adjustments based on actual prevalence Region A 5% Region B 7% Cost per prevalent case = £3000

9. 3. Adjustments based on predicted prevalence Rich 4% Poor 8% Cost per prevalent case = £3000

10. Use of health surveys Wales: Direct use of survey to make adjustments for demography and additional need Scotland, England & NI: Indirect use of surveys to improve adjustments for additional need

11. Direct method Obtain region-specific prevalence rate estimates for each age-group using a health survey Apply region-specific prevalence rate estimates to age profile of resident population to obtain estimated numbers of cases Calculate each regions share of national cases Obtain national budget for the condition Derive regional budgets by multiplying national budget by the regional shares of cases

12. Practical issues for direct method Reliability of survey results at regional level Representativeness of survey results Updateability of survey results Differences in reporting behaviour between regions

13. Conceptual issues for direct method Choice of prevalence measure, e.g. circulatory disease Symptom-based measures – Rose Questionnaire Self-reported measures – longstanding illness Doctor-diagnosed measures Breadth of definition – IHD, CVD or CVC Converting prevalence into need for health care resources Share of prevalent cases implies: All non-cases have zero need for health care resources All cases have same need for health care resources

14. Alternative measures of circulatory disease

15. Indirect methods Model risk of being a prevalent case as a function of individual-level (age/gender) and area-level characteristics Apply risk equation to small-area data to obtain prevalence rate estimates for each small area Model relationship between use of services and prevalence rate estimate(s) to obtain relative needs index for each area

16. Approach in Scotland Adjustment for additional need based on single composite needs variable: Arbuthnott Index Standardised Mortality Ratio, 0-64 years Proportion claiming income support, 65+ years Standardised rate of unemployment benefit claims Proportion of households with multiple deprivation

17. Indirect methods - Scotland Original work assumed linear relationship between Arbuthnott Index and use of health care services Work on adjustment involved: Non-linear modelling of relationship between Arbuthnott Index and prevalence estimates from Scottish Health Survey Modelling of effect of fitted prevalence on use of care Simultaneously testing for unmet need (whether high deprivation or low deprivation areas had levels of use that departed significantly from prevalence-use relationship)

18. Data - Scotland 1995 & 1998 Scottish Health Surveys 1995 = 7,932 individuals aged 16-64 years 1998 = 12,939 individuals aged 2-74 years Respondents sampled from 451 of 717 areas Standardised prevalence rates calculated for six longstanding illnesses

19. Circulatory disease prevalence and deprivation

20. Modelling effect of prevalence on use of health care

21. Relative need profiles under different models

22. Relative needs by deprivation decile

23. Approach in England Additional needs modelled using a large number of potential indicators Particular concerns raised about previous reviews ability to avoid unmet need

24. Use of surveys - England Individual-level tests of unmet need Unmet need tests in small area levels of health care use model risk of morbidity as function of area characteristics augment set of potential need indicators with predicted morbidity indices examine effects on other coefficients

25. Data - England Health Survey for England, 1994-2000 Total respondents = 122,500 Binary measures of health care use since 1998 Individuals sampled from 5,893 of 8,414 electoral wards Records linked to a range of population, utilisation and supply variables

26. Individual-level tests of unmet need

27. Morbidity models

28. Augmentation of model with morbidity indices

29. Impact on relative need indices

30. Summary - I Health surveys are increasingly being used in resource allocation availability of data concerns about unmet need in activity-based formulae Direct methods practical issues conceptual issues

31. Summary - II Indirect methods allow for non-linear relationships between deprivation and need inform selection of need variables provide non-linear combinations of need variables to augment data-set permit tests of unmet need