Resource Allocation Formula Research Articles

Informing prescribing allocations at district level in England.

To derive a predictive model based on the morbidity, demographic and socio-economic characteristics of district populations to explain variations in prescribing costs in England. Inter-relations between morbidity, demographic, socio-economic, general practice supply characteristics and net ingredient cost per age, sex and temporary resident originated prescribing unit (ASTRO-PU) were explored statistically for 90 districts in England using 1994 cost data. The possibility of mutual inter-relationship between 'supply' and 'demand' was examined; then the associations between a range of factors and prescribing costs were estimated using ordinary least squares regression and the predictive power of the possible models was systematically examined. Whilst there was a relatively weak relationship between the supply factors that were measured, there did not appear to be any reciprocal relationship. Three parsimonious models estimated using ordinary least squares multiple regression techniques based on combinations of permanent sickness, low birth weight and the proportion of general practitioners registered for postgraduate certificate of education were identified. The models explained up to 61% of variation between districts in prescribing costs. 'Need' and 'supply' characteristics are independently associated with variations in prescribing costs at district level. The negative association between the proportion of general practitioners eligible for postgraduate education allowance and prescribing costs may reflect 'better' prescribing but could not be introduced into a resource allocation formula without introducing perverse incentives. The combination of permanent sickness and low birth weight complement each other by providing a proxy measure of morbidity mostly applicable to adult males (permanent sickness) and mothers (low birth weight being a measure of maternal health). These variables should be considered further for use in the process of allocating resources for prescribing to districts.

Outcomes-based resource allocation for indigenous health services: a model for Northern Australia?

Wide differentials continue to exist in mortality rates and other health outcomes between Aboriginal and non-Aboriginal Australians. In the Northern Territory (NT), where Aborigines make up 24% of the population, the all-causes age-adjusted Standardised Mortality Ratio for Aborigines compared to non-Aborigines has remained above 3 since the late 1970s, with significant regional variations. During 1995 an expenditure analysis was undertaken for primary health care (PHC) services in different regions of the NT and compared to mortality ratios. At the same time a method for needs-based funding was being developed which could replace the existing historical funding arrangements. In the first instance, the application of a simplified version of this Resource Allocation Formula (RAF) resulted in a significant shift of resources for new prevention program funding to regions of relatively high mortality and low per capita PHC expenditure. However, developing RAFs to redistribute at the margin within the NT is likely to generate further inequities between losing NT programs and counterparts in other states. If outcomes-based resource allocation is to be meaningful nationally, the reference point for the RAF should be national average PHC expenditure rather than existing state averages. There is a need for a combined approach to outcomes-based planning which takes into account both the equity arguments of resource allocation models and efficiency arguments to maximise health gains. Some of these arguments are explored in this paper.

Use of the Nottingham Health Profile to test the validity of census variables to proxy the need for health care.

Data on health or health service use are invariably used to test the validity of proxy measures of need, for use in resource allocation formulae. Perceived health state is a good measure to use in this respect, as it is closely linked to perceived need and the decision to consult health services. This being the case, a large community based study was undertaken which collected data on perceived health, using the Nottingham Health Profile (NHP), with the aim of testing the validity of a variety of Census based measures as proxy measures of the need for health care. A postal questionnaire survey of 9565 people living in the former South East Thames Regional Health Authority was conducted and the relationship between their perceived health state and the socio-economic characteristics of their electoral ward of residence analysed. A relatively low response rate (59 per cent) weakened any conclusions to be drawn from the results. However, significant correlations between perceived health and a variety of the Census based indicators were found. The highly skewed distribution of responses to the NHP statements made the results difficult to analyse and interpret. Although the study gave an indication of those variables that might be incorporated into resource allocation formulae, the NHP is not a particularly efficient instrument to use in a community setting. It is argued that the appropriateness of an approach to determining appropriate needs weights in allocation formulae, which attempts to find one indicator of all health care needs at the District Health Authority level, must be questioned.

A Proposal for a Local Resource Allocation Formula for Mental Health Services

A Proposal for a Local Resource Allocation Formula for Mental Health Services

Socioeconomic determinants of rates of consultation in general practice based on fourth national morbidity survey of general practices.

To identify the socioeconomic determinants of consultation rates in general practice. Analysis of data from the fourth national morbidity survey of general practices (MSGP4) including sociodemographic details of individual patients and small area statistics from the 1991 census. Multilevel modelling techniques were used to take account of both individual patient data and small area statistics to relate socioeconomic and health status factors directly to a measure of general practitioner workload. Higher rates of consultations were found in patients who were classified as permanently sick, unemployed (especially those who became unemployed during the study year), living in rented accommodation, from the Indian subcontinent, living with a spouse or partner (women only), children living with two parents (girls only), and living in urban areas, especially those living relatively near the practice. When characteristics of individual patients are known and controlled for the role of "indices of deprivation" is considerably reduced. The effect of individual sociodemographic characteristics were shown to vary between different areas. Demographic and socioeconomic factors can act as powerful predictors of consultation patterns. Though it will always be necessary to retain some local planning discretion, the sets of coefficients estimated for individual level factors, area level characteristics, and for practice groupings may be sufficient to provide an indicative level of demand for general medical services. Although the problems in using socioeconomic data from individual patients would be substantial, these results are relevant to the development of a resource allocation formula for general practice.

Deprivation indices: their interpretation and use in relation to health.

To examine the use of deprivation indices in relation to health. This paper reviews selected publications which illustrate the diversity of use of deprivation indices in the past decade. Most of this work is based in the major routine databases which exist in this country: the census, population, mortality, cancer register, and health service records all now incorporate a postcode identifier which permits the derivation of data at small area level, and thus the examination of health events in relation to the characteristics of that area - usually ward or postcode sector. The small area approach provides a valuable tool both in deprivation and in other epidemiological studies which examine the influence of the environment on health. The setting is various journals and official publications. The link between deprivation and health has been clearly demonstrated in a number of studies, with populations living in deprived areas exhibiting levels of mortality, particularly below the age of 65, which vastly exceed those in affluent areas. In the decade 1981-91, these differentials increased in Scotland and the Northern Health Region and inequalities in health are shown to have widened. Analysis shows that particular causes of death and sites of cancer are more likely to reflect the influence of socio-economic factors. The work so far mostly shows the associations between these factors and health measures and more investigation is required into the determinants of health, which are likely to reside as much in past as in current circumstances. A measure of deprivation has proved of value in excluding the likely variation in the incidence of disease in studies directed towards determining the influence of the physical environment on populations living in the vicinity of possible harmful industrial processes. A deprivation measure has been adopted by the Department of Health as a basis for making enhanced payments to general practitioners for patients living in these areas, but the resource allocation formula for allocating funds to regional authorities has failed to incorporate such a measure in the formula. An area measure of deprivation has proved a valuable tool in examining differentials in health and death and is likely to prove of continuing value to health authorities in planning the delivery of health care. Future work should strive to examine the determinants of health as well as the associations, although this is unlikely to be possible through the routine databases which have provided the main basis for analysis so far.

IMPROVING EQUITY AND EFFICIENCY IN THE BUSH: A NEEDS‐BASED METHOD FOR HEALTHCARE RESOURCE ALLOCATION IN REMOTE COMMUNITIES

ABSTRACT: Outback Australia still exists as a frontier economy, relying on public sector provision of the vast majority of services, including health care. In the Northern Territory (NT), high mortality ratios and hospitalisation rates reflect the poor health status of Aborigines who, in 1990‐91, accounted for 25% of the population but 40% of hospital patients and 53% of hospital bed days. Funding for primary health care continues to be based on historical utilisation rates, which perpetuates the existing bias towards the urban hospital sector. Health care expenditure analysis suggests that current expenditure patterns fail to fulfil national goals of equity of access and allocation efficiency (maximisation of health outcomes) for the NT Aboriginal population.This paper outlines a population needs‐based resource allocation formula for remote communities, which takes account of three factors: mortality, cost of remoteness and demographic structure. National per capita health care utilisation data are used as a baseline and an allocation weighting is proposed based on the above three factors. This formula is then applied to a typical remote central Australian community. The cost‐benefit implications of this alternative funding strategy are explored.

Geographical Resource Allocation in the English National Health Service, 1971-1994: The Tension between Normative and Empirical Approaches

The policy response to the problem of developing a geographical resource allocation formula sensitive to relative population needs for hospital and community health services resources in the National Health Service demonstrates a continuing tension between normative and empirical solutions. Since 1988, the balance has shifted in favour of a more empirical approach to identifying and weighting population needs indicators in response to concerns about the theoretically justified, but essentially approximate, nature of the Resource Allocation Working Party formula introduced in 1977-1978. However, judgements and assumptions about the nature of 'need' have still to be made in order to construct a usable resource allocation formula since empirical data on what is cannot provide a complete guide to what ought to be a fair distribution of resources in relation to need.

New resource allocation formula

New resource allocation formula

Variations in general practice prescribing costs and implications for budget setting.

Indicative prescribing amounts, and the equivalent prescribing element of funds in the case of fund-holding practices, are now an established part of UK general practice. This paper examines the implications of variations in GP prescribing behaviour for the determination of prescribing budgets. Using regression analysis, the extent to which variations in total practice prescribing costs can be explained by factors suggested for inclusion in a weighted capitation formula is established. The results indicate that 97% of the variation in practice prescribing costs can be explained by differences in practice list size, the proportion of patients aged 65 years and over, the proportion of patients living in 'deprived areas' and whether or not the practice qualifies for 'inducement payments'. The implications of the results for budget setting are discussed. A resource allocation formula based on regression analysis of expenditures can be used to promote horizontal equity in terms of equal budgets for equal need. However, its implications for vertical equity and efficiency are more ambiguous.

Rurality and resource allocation in the UK

Unlike many other countries, the health and health care of rural populations are not often seen as specific concerns by the United Kingdom's health service. This paper considers the present ways in which resource allocation within the National Health Service takes account of rural areas and highlights a number of inconsistencies. It goes on to discuss ways in which rurality could influence future resource allocation formulas, and identifies priorities for future research.

Weighting in the dark: resource allocation in the new NHS.

National allocation of resources to regional health authorities and by them to districts is now determined by a weighted capitation formula. The national formula was derived from regression analysis, with hospital utilisation as an index of need for health care--a method which has fundamental limitations. This paper argues that the search for an empirically based resource allocation formula of high precision in the name of promotion of equity is largely fruitless given the impossibility of measuring the true need for, and costs of, providing health care, especially with the limited data available. The inclusion of measures of social deprivation is also poorly thought out. The availability of data from the 1991 census, which included a question regarding long-standing illness, together with the intention of the Department of Health to review the weighted capitation formula using this information may stimulate much work but little light. It is essential that the impact of resource allocation formulas is justifiable on grounds other than the composition of any particular formula.

Move to Fairer Resource Allocation

The NSW Health Department has begun using a Resource Allocation Formula (RAF) as a guide to achieving a fairer distribution of health resources.

Resource Allocation and Planning in Health Care Systems

Resource allocation formulae and planning models have both been suggested as methods for calculating how to distribute funds for health care between a number of geographical regions. Recently, consideration has been given to how to link these two methods. An attempt is made in this paper to demonstrate the connection that exists between certain resource allocation formulae and planning models. Although this dependency may be a useful theoretical property, problems exist in that the best allocation formulae correspond to the worse planning models, and vice versa, so that this connection may be difficult to use in practice. Despite this problem, this property can be used to define some alternative allocation formulae, and a number of recommendations for doing this are given.

Measuring housing need and the provision of social housing

Abstract The Bramley Report (ADC, 1988), made a detailed attempt to construct a resource allocation formula for social housing provision. In this paper we stand back from the debate over the detail of the models being proposed by Bramley to consider instead the principles which underlie the modelling of housing needs and resource allocation in this context. The measurement of housing need depends on a few key concepts; the definition of acceptable standards of accommodation, the total numbers of households, and the supply of housing of at least the required standard. Questions then arise as to which indicator should be included in a needs model and how they should be measured. Overcrowding and homelessness are likely to be included whether these indicators are chosen by consumers or by social decision‐makers. Having chosen the indicators they have to be ‘normalised’ to take account of cyclical factors in the housing market, and of the efficiency and policy stances of local authorities. After this the indi...

From equalisation to rationalisation: public health care provision in New South Wales

This article examines the changing nature of the resource allocation formula for health care provision in New South Wales. It looks at the technical changes to the formula reviewing its problems and limitations and subsequent modifications. The impact of the formula on actual resource provision is established and this provision is placed in the context of health policy and public expenditure debates in Australia. Finally, the formula and its use as a rationalisation device are examined in relation to economic crisis and state practice with the suggestion being made that certain features of the Australian state may lead to a review of aspects of the theory of the state.