title: Setting health care capitations through diagnosis-based risk adjustment: a suitable model for the English NHS?
abstract: The English system of health resource allocation has been described as the apotheosis of the area-level approach to setting health care capitations. However, recent policy developments have changed the scale at which commissioning decisions are made (and budgets allocated) with important implications for resource allocation. Doubts concerning the legitimacy of applying area-based formulae used to distribute resources between Primary Care Trusts (PCTs) to the much smaller scale required by Practice Based Commissioning (PBC) led the English Department of Health (DH) to introduce a new approach to setting health care budgets. To this end, practice-level allocations for acute services are now calculated using a diagnosis-based capitation model of the kind used in the United States and several other systems of competitive social health insurance. The new Coalition Government has proposed that these budgets are directly allocated to GP 'consortia', the new commissioning bodies in the NHS. This paper questions whether this is an appropriate development for a health system in which the major objective of resource allocation is to promote equal opportunity of access for equal needs. The chief reservation raised is that of circularity and the perpetuation of resource bias, the concern being that an existing social, demographic and geographical bias in the use of health care resources will be reinforced through the use of historic utilisation data. Demonstrating that there are legitimate reasons to suspect that this will be the case, the paper poses the question whether health systems internationally should more openly address the key limitations of empirical methods that select risk adjusters on the basis of existing patterns of health service utilisation.
authors.affiliation: Faculty of Health, University of Plymouth, Drake Circus, Plymouth, PL4 8AA, United Kingdom. sasthana@plymouth.ac.uk
authors.forename: Sheena
authors.initials: S
authors.lastname: Asthana
authors.forename: Alex
authors.initials: A
authors.lastname: Gibson
mesh_terms: D002204:Capitation Fee; D006296:Health Services / Q000706:statistics & numerical data; D006779:Hospitals, Public / Q000191:economics; D006801:Humans; D017146:Models, Organizational; D040841:Resource Allocation / Q000458:organization & administration*; D020379:Risk Adjustment / Q000379:methods*; D013222:State Medicine / Q000458:organization & administration*