Accounting for social risk in medical and social service payments: the English experience

1. Accounting for social risk in medical and social service payments: the English experience  Peter C. Smith Imperial College Business School University of York European Observatory on Health Systems and Policies

2. Structure • Introductory comments • The English National Health Service (NHS) • General practices • Clinical commissioning groups • Allocating funds to geographical areas • Weighted capitation • The ‘York’ formula • Indices of deprivation • Allocating funds to ‘reduce avoidable health inequalities’ • Concluding comments

3. 5th July 1948 • “...there are no charges, except for a few special items. There are no insurance qualifications. But it is not a ‘charity’. You are all paying for [the NHS], mainly as taxpayers, and it will relieve your money worries in times of illness.”

4. General practices in England 2019 • All citizens must register with a primary care practice • Access to non-emergency secondary care only with the referral of a general practitioner • Total registered population in England 59,759,638 • 6,980 practices • Average practice population 8,562 Source: NHS Digital https://digital.nhs.uk/data-and-information/publications/statistical/patients-registered-at-a-gp-practice/april-2019

5. Local administration: clinical commissioning groups • 207 clinical commissioning groups • Statutory bodies, appointed by the minister, strong influence of local primary care physicians • Geographically defined, average population 280,000 • Responsible for • Routine acute care • Maternity services • Mental health services • Community services • Prescribing costs (outside hospital) • Not responsible for • Specialized services • Public health

6. Resource Allocation Working Party 1976 • Intention was to allow geographical regions to offer NHS patients ‘equal opportunity of access [to health care] for those at equal risk’. • The geographical targets of the RAWP approach were the 14 regional health authorities, covering populations of about 3 million • RAWP recommended distributing finance on the basis of population, weighted according to demography and disease-specific standardized mortality rates.

7. Typical elements of empirical formulae seeking to model hospital expenditure • Intention has been to develop capitation payments that reflect the expected expenditure on patients with different personal circumstances, subject to data availability: • Age and sex • Local area social and economic characteristics (eg pensioners living alone, unemployment, receipt of welfare payments, housing type) • But not explicitly income as this is not generally made available • Local epidemiology (mortality rates; prevalence of chronic disease, eg asthma, diabetes) • Individual diagnosis data (from 2013) • Local costs of delivering services (wages; capital) • … plus adjustments for indicators of local supply of services

8. The ‘York’ formula 1995: small area indicators associated with acute hospital expenditure • Standardized mortality rate (age 0-74) • Standardized long-standing illness rate (age 0-74) • Proportion of pensionable age living alone • Proportion of economically active unemployed • Proportion of dependants in single carer households Source: Smith, P., Sheldon, T. A., Carr-Hill, R. A., Martin, S., Peacock, S. and G. Hardman (1994) “Allocating resources to health authorities: results and policy implications of small area analysis of use of inpatient services”, British Medical Journal, 309, 1050-1054.

9. Percentage gain/loss for local administrations caused by age and needs adjustments, 2006/07 Age adjustment Needs adjustment

10. English index of multiple deprivation • Based on seven different domains of deprivation: • Income Deprivation (22.5%) • Employment Deprivation (22.5%) • Education, Skills and Training Deprivation (13.5%) • Health Deprivation and Disability (13.5%) • Crime (9.3%) • Barriers to Housing and Services (9.3%) • Living Environment Deprivation (9.3%) • Each of these domains is in turn based on a basket of indicators. Source: Ministry of Housing, Communities & Local Government (2015), English indices of deprivation 2015 https://www.gov.uk/government/statistics/english-indices-of-deprivation-2015

11. Life expectancy in England by deprivation quintile:Gap Q1 to Q5: males 7.7 years; females 6.2 years Source: Office for National Statistics (2019), Health state life expectancies by national deprivation deciles, England and Wales: 2015 to 2017

12. Hospital care highly redistributive, even though more deprived quintiles have lower life expectancy Source: Asaria M, Doran T, Cookson R. 2016, “The costs of inequality: whole-population modelling study of lifetime inpatient hospital costs in the English National Health Service by level of neighbourhood deprivation”, J Epidemiol Community Health doi:10.1136/jech-2016-207447

13. Size of funding flows 2016/17 Source: https://www.england.nhs.uk/allocations/

14. Modelling annual contact time in primary care: a basis for primary care allocations • Models annual ‘weighted contact time’ (open computer file) with patients: medical practitioner weight = 1.0 • Sample = 4.4 million, average annual weighted time 54.6 minutes • Explanatory variables: age group, gender, rural/urban, IMD decile • On average, a patient from IMD decile 10 (most deprived) has 13.7 minutes more weighted contact time per annum than an equivalent patient from IMD decile 1. Source: NHS England (2016) Primary medical care –new workload formula for allocations to CCG areas https://www.england.nhs.uk/allocations/#formulae

15. Association between deprivation and annual general practice contact time

16. Introduction of a ‘person based’ model of hospital expenditure for routine acute care • Introduced modelling of hospital expenditure at an individual level and previous hospital diagnosis for the first time • Also retained local area variables as a supplement where needed Dixon, J., Smith, P., Gravelle, H. et al, (2011), “A person based formula for allocating commissioning funds to general practices in England: development of a statistical model”, British Medical Journal, 343:d6608 doi: 10.1136/bmj.d6608

17. England: small area needs and supply variables (attributed to the patient’s general practice) • Needs variables (135) • Self-reported health • Disease prevalence • Income and employment • Housing and environment • Demographic structure • Educational attainment • Standardized mortality rates • Supply variables (63) • Access to hospital beds • Access to other types of care • General practice characteristics • GP performance (quality) • Waiting times

18. Examples of small area needs variables that survived statistical selection process (2013) • The small area variables indicate expenditure on medical services not predicted by the age, sex and previous diagnosis variables. • They reflect the prevalence of some social or health characteristic of the population in the small area • They were selected using a statistical pre-defined selection algorithm that reduced the 167 candidate variables to a manageable number • Persons in social rented housing (+) • Disability allowance claimants (+) • People aged 16–74 years with no qualifications (age standardized) (+) • Mature city professionals (-) • Students in population (-) • Asthma prevalence (+) Dixon, J., Smith, P., Gravelle, H. et al, (2011), “A person based formula for allocating commissioning funds to general practices in England: development of a statistical model”, British Medical Journal, 343:d6608 doi: 10.1136/bmj.d6608

19. Impact of alternative model specifications

20. NHS equity criteria • The conventional criterion: to allocate the fixed National Health Service budget to geographical areas: • so as to secure “equal opportunity of access [to NHS services] for those at equal risk” • A revised criterion (2001): • “to contribute to the reduction in avoidable health inequalities”

21. “To contribute to the reduction in avoidable health inequalities” • An implication that the current outcomes of NHS care are unacceptable • Desire to shift NHS resources towards areas with the poorest health outcomes. • Limited scope for using empirical data – by definition, current NHS actions are not securing desired outcomes. • How much of poor health outcomes can be addressed by health services? Hauck, K., Shaw, R. and Smith, P. (2002), “Reducing avoidable inequalities in health: a new criterion for setting health care capitation payments”, Health Economics, 11(8), 667-677.

22. Age-standardised amenable mortality rates amongst CCGs • Bradford City 186.6 • Surrey Heath 52.2 • How much more funding should Bradford City receive to reduce this gap?

23. Current approach to allocating for ‘unmet need’ • Based on policy judgement, not evidence • Applied to a percentage of the relevant budget: • General acute and mental health services 10% • Primary care 15% • Specialized services 5% • Allocated according to standardized mortality rate (aged under 75) in small areas (average population 7,200) • 16 groups of small areas, ranked according to SMR • A weight per head 10 times higher for the group with the worst SMR compared with the group with the lowest SMR, on an exponential scale. • This skews resources towards the small areas with very high SMRs

24. Some criteria for funding formulae • Based on universally available, validated data; • Reflects the underlying social and medical needs in a locality; • Independent of previous spending in a locality; • Scientifically coherent and plausible; • Feasible, with low administrative cost; • Not vulnerable to manipulation or fraud; • Encourages efficient delivery of health services, and free from perverse incentives; • Transparent, verifiable, understandable and replicable; • Parsimonious; • Reflects policy intentions

25. Concluding comments • Clarity about the policy objective of the undertaking • Equalizing funding requirements (‘equal access for equal need’) • Reducing health inequalities • Clarity about what constitutes a ‘legitimate’ statistical adjuster • Agreement on analytic processes very important; otherwise vulnerable to claims of bias • Requires scrutiny of methods and outcomes that is ‘blind’ to the consequences for specific areas