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eMJA
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Casemix: moving forward
Casemix funding for acute hospital inpatient services in AustraliaStephen J Duckett
MJA 1998; 169: S17-S21 Synopsis -
Introduction -
Inpatient funding arrangements -
Funding models -
Cost variability -
Divergence in weights -
Price differences -
Outliers -
Intensive care -
Private patients -
Conclusion -
References -
Authors' details
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Synopsis | |
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Introduction | |
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In Australia, casemix funding was first introduced in Victoria in
1993-94,1 as part of a program of public
sector restructuring to reduce expenditure and improve the
efficiency.2,3 South
Australia4 followed in 1994-95, with a
casemix funding approach modelled substantially on the Victorian
scheme5 and also accompanied by
significant budget cuts. Since then, Western Australia6 and
Tasmania7 have also implemented
casemix funding (both in 1996-97), and Queensland8 has commenced a
phasing-in process for casemix funding. New South Wales is the only
State which has eschewed casemix funding arrangements, instead
structuring providers on the basis of an area responsibility for
hospitals and other service units (eg, community health centres).
Funding is distributed to areas based on their population. Even in New
South Wales, policy documents emphasise the importance of casemix in
informing budgets for hospitals and in paying for patients across
regional boundaries.9 The Northern Territory and
the Australian Capital Territory have also incorporated elements of
casemix funding, but because of their small populations and small
number of distinct providers, funding arrangements are essentially
determined individually, even when an elaborated formula is
used.10
Initial casemix implementation required an unravelling of hospital activity into the major streams of care: inpatient, outpatient, and teaching and research. Casemix implementation focused first on inpatient services where classification for describing services or "products" was the most sophisticated. | |
Inpatient funding arrangements | |
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The essence of casemix funding for inpatient services is quite
simple: the budget for a hospital is based on the number and type of
patients treated in the hospital. The development of
diagnosis-related groups (DRGs) as clinical and resource
homogeneous categories for inpatients11 provided a means of
grouping types of patients treated, which could be used for payment
purposes. The budgets of hospitals could thus be determined
primarily on performance or output, rather than negotiation,
history or politics.
The five States implementing casemix funding have all adopted some common funding elements. Firstly, a common nomenclature is used: all States currently use version 3.1 of Australian national diagnosis-related groups (AN-DRGs). Secondly, as these funding arrangements coincided with budget reductions, all the States have introduced capping, most commonly at the hospital level with hospital-specific targets. In some States, the throughput targets are flexible -- if hospitals exceed these targets, they receive additional funding, albeit at a marginal price. Thirdly, with DRG assignment based on recorded diagnosis and procedure codes, all States have introduced coding audits to ensure accuracy of recording. Other aspects of inpatient casemix funding reveal remarkable variability between the States. The Box compares key elements of inpatient funding arrangements across the States. | |
Funding models | |
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Two basic funding models have been developed. The initial Victorian
model was based on fixed and variable components, following the
recommendations of the 1990 Scotton and Owens review of the prospects
of casemix funding in Australia.12 Queensland has also
adopted this model.
A fixed and variable model involves two elements: a fixed grant to cover hospital overhead costs, and a payment for each patient treated covering only the variable costs of that patient. The theory behind this approach is that efficiency is maximised if the incentives are such that hospitals can treat additional patients up to the point at which marginal treatment cost equals marginal revenue. Marginal revenue is the variable payment made by State health authorities. This fixed and variable model mitigates the incentive for hospitals to maximise admissions. After current capacity limits are reached, additional fixed costs are required (eg, for commissioning new wards), but these are not fully reimbursed by the funding system. Thus, States retain control over growth in system capacity. The alternative model is used in Western Australia and Tasmania, which both provide an integrated payment to hospitals for each patient treated covering both the fixed and variable costs. South Australia also uses an integrated payment system, but if a hospital does not achieve the negotiated volume target, payments are discounted, effectively recognising that the savings to hospitals are at marginal or variable costs. | |
Cost variability | |
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It would be expected that the utility of treating a patient in a
particular DRG would be constant across all hospitals. Likewise,
logically, the payment for that DRG should be the same, regardless of
the hospital. However, the different State funding systems
recognise that there are differences in costs and four of the State
systems (Victoria, Queensland, Western Australia and South
Australia) have established several funding subgroups that receive
different payments.
Interestingly, assumptions about economies of scale vary. The Victorian and Western Australian systems assume economies of scale exist, as the payment for a patient in a particular DRG is less in a larger hospital than in a smaller hospital. On the other hand, in Queensland and South Australian diseconomies of scale are assumed and payments are higher in larger hospitals than in smaller hospitals. | |
Divergence in weights | |
| The weight setting process also differs across the country. Three States (Queensland, South Australia and Tasmania) use variants of the weights developed as part of the national cost weight study, which are derived from cost modelling undertaken as part of national costing studies.13 Victoria and Western Australia, on the other hand, use data from clinical costing systems in their own State to set weights. In Victoria, for example, weights are set using a dataset of patient costs from over 0.5 million recorded patient admissions to 15 Victorian public acute hospitals in the financial year two years prior to the payment year.14 | |
Price differences | |
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As a result of these different weight setting processes, different
relative weights are used across the country for each DRG, as well as
different base prices. The different prices and weights mean that
there are differences between States in the price paid for the same
case treated in a similar hospital. This effect can be seen with AN-DRG
674, Vaginal delivery without complicating diagnoses.
In the two States with fixed and variable funding (Victoria and Queensland) the variable price paid for an inlier patient in AN-DRG 674 in a major hospital in 1997-98 varies by more than 20% ($925 in Victoria versus $1121 in Queensland). Similarly, in the integrated funding States there is a difference of more than 40% ($1455 in South Australia versus $2097 in Tasmania, with the Western Australian price lying in between these at $1685). Payment differences of this size need some explanation. Firstly, in some DRGs, these differences might reflect differences in inpatient payment system design (eg, in intensive care payments), but this should not be relevant in this DRG. Secondly, they might be attributable to differences in other aspects of the payment system (eg, in training and development), but this would not be sufficient to account for the magnitude of the payment differences. Finally, the differences might reflect different input costs, a factor taken into account in payment system design in the United States.15 However, most employees in public hospitals are now covered by Federal awards and so input price variation is not a feasible explanation. It is thus difficult to see how cost differences of this order of magnitude can be justified for this reasonably homogeneous DRG. | |
Outliers | |
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The DRG classification system has been developed to describe the
normal, or typical, case in a DRG, known as an inlier. Outlier cases are
those which do not fit the normal pattern and, in terms of
distribution, lie outside so called "trim points". The basis for
setting trim points, and thus determining outliers in all States,
follows work done by McGuire et al on the effect of different trim point
methods.16
The common trimming method used in Australia is the L3H3 method: the low trim point is a third of the average length of stay, and the high trim point is three times the average length of stay. Some States use modifications of this approach: Queensland has an extra high trim point based on five times average length of stay; and in South Australia the low trim point is determined parametrically at 3 SD below the mean length of stay (where average length of stay is greater than four days). Two States, Western Australia and South Australia, also have trim points based on cost, which provide for additional funding for cases identified as costing more than $75 000 and $60 000, respectively. The cost-based trim points rely on hospitals having robust clinical costing systems with agreed bases for allocation of costs, as different assumptions about allocation of overhead costs, for example, can significantly affect the recorded cost of a case.14 | |
Intensive care | |
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Intensive care funding is a particularly sensitive issue, given that
variation in system-wide use of intensive care cannot be fully
explained by variation in epidemiological and demographic
factors.17 There is considerable
variation across States in the funding arrangements for intensive
care units, and the payment systems have quite different incentive
effects. Within an individual hospital there can also be
differential incentives on intensive care unit staff to admit to
hospital or retain patients within the unit, depending on the funding
structure.
Victoria and Tasmania provide no specific additional funding for intensive care units. Western Australia provides block funding for intensive care units on top of the existing funding arrangements. In South Australia intensive care units are effectively funded on a per diem basis, with the DRG cost weight calculation being adjusted to exclude intensive care costs. | |
Private patients | |
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Costs of private patients obviously differ from those of public
patients. Private patients' medical costs (including pathology and
radiology costs) and prostheses costs are met by the patients
themselves, and are normally reimbursed by health insurance funds.
Hospitals also accrue revenue from these patients.
The Victorian and Queensland funding models provide differential payments for public and private patients to take account of these different cost structures. Western Australia provides a block payment to compensate for the differing proportion of public patients. On the other hand, the South Australian and Tasmanian arrangements do not provide differential payments, and although revenue differences are compensated for, there would still be an effective incentive to admit private rather than public patients because of the lower hospital costs for private patients. | |
Conclusion | |
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Five States have either implemented or are in the process of
implementing casemix funding, but the funding models used have
significant design differences. Some of the systems are clearly
fairer to hospitals than others, and it is therefore not surprising
that recent reviews of both Victorian and South Australian formulas
have indicated that providers believe that there are still problems
in funding design.18,19 Although the design of
a funding system is in part a technical process to ensure that
hospitals have appropriate incentives for efficiency, it is also a
political process insofar as providers need to be assured that the
funding formula is fair. The large variation in prices for the
indicator DRG used in this article (DRG 674) also suggests an element
of inequality between States in pricing strategies.
Design of a casemix funding system involves a number of complex technical choices to maintain appropriate balances between competing policy objectives (eg, minimising waiting lists versus reducing stays in hospital emergency departments). Similarly, maintenance of casemix payment systems needs to take account of changes in health technology and to monitor perverse effects of funding system design. There is thus a strong argument that there should be some form of joint development to facilitate better funding system design. State casemix funding arrangements have evolved in a number of areas, such as in the weight setting processes and in the elaboration of the role of the purchaser (including how volume controls are implemented). Although casemix funding arrangements are characterised by relatively low transaction costs, annual funding policy reviews in each State probably incorporate unnecessary overheads. Differences between the States should not preclude the possibility of learning across State boundaries. As casemix funding enters a more mature phase, knowledge of what is effective and what is ineffective in casemix funding arrangements should be used to develop Australian best practice in this area. National cooperation (and national leadership) produced an agreed national casemix classification. Further national action is warranted to facilitate transfer of the best practice elements of each State's funding systems. This should occur early in casemix funding development to reduce the costs incurred by States "reinventing the casemix funding wheel" each year. Furthermore, there remain several areas in which casemix funding is deficient; for example, in identifying and funding teaching and research activities of hospitals, and in the development of funding policy in ambulatory care. Cooperative national action in these areas is needed. | |
References | |
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Authors' details | |
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La Trobe University, Melbourne, VIC
Stephen J Duckett, BEc, MHA, PhD, Professor of Health Policy; and Dean, Faculty of Health Sciences.
Reprints: Professor S J Duckett, Faculty of Health Sciences,
La Trobe University, Bundoora, VIC 3083. |
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© 1998 Medical Journal of Australia.
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