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D Hindle

Publications and source records attributed to D Hindle.

At least 37 records · Page 2Linked to original sources
PubMed1999

Out with the old, in with the young: lifetime community rating.

Lifetime community rating has some potential benefits to private insurers, but they can only be realised if there is much greater control over private care providers than is currently the case. There is reason to fear that insurers' initial gains will disappear through increased provision of marginal care. Some members will gain through reduced premiums, and the main benefits will be derived by people who continue to maintain insurance. Most members will benefit hardly at all, and some (and particularly those who were unwilling or unable to take out insurance when they were young) will be significant losers. The public health care sector will remain under pressure at best, and it is more likely that the pressures will increase. The majority of Australians who do not have insurance will tend to lose. The obvious winners are the private care providers. The overall revenues of private health insurers will be relatively higher than if lifetime community rating were not introduced, and most of that revenue ultimately finds its way into the private care providers' pockets. Assuming they are able to increase the level of marginally useful care, there could be an increase in profitability to the extent that marginally useful care is actually less expensive to deliver. Finally, the government will derive another Pyrrhic victory. It will reduce its own outlays, but cause a decline in overall cost-effectiveness of the health system. We have been here before, most recently in the period leading up to passage of the 30% rebate. There is good reason, therefore, to expect that lifetime community rating will be implemented. At least, the government will be able to claim it is defending Medicare from the more extreme privatisation ideas of Premier Kennett. This kind of argument will probably be sufficient. If so, the government will no doubt be stimulated to move to the next stage of dismantling of Medicare (which will presumably be something like means-testing of public hospital services). Many people believe that this is not an achievable goal in the near future. However, there was a popular view that the GST was not implementable after it lost the Coalition one election and led to Prime Minister Howard stating that he would 'never ever' raise the possibility again. The electorate is a sleeping giant, as is the public health care sector. It would be useful to know what could possibly serve as a wake-up call. Lifetime community rating is a small matter in the general trend towards killing off Medicare. But it is never too soon to send a message.

Actuarial Analysis↗
PubMed1998

Casemix funding in Australia.

Casemix funding for hospitals with the use of diagnosis-related groups (DRGs), which organise patients' conditions into similar clinical categories with similar costs, was introduced in Australia five years ago. It has been applied in different ways and to a greater or lesser extent in different Australian States. Only Victoria and South Australia have implemented casemix funding across all healthcare services. Attempts have been made to formally evaluate its impact, but they have not met the required scientific standards in controlling for confounding factors. Casemix funding remains a much-discussed issue. In this Debate, Braithwaite and Hindle take a contrary position, largely to stimulate policy debate; Phelan defends the casemix concept and advocates retaining its best features; and Hanson adds a plea for consumer input.

Diagnosis-Related Groups↗
PubMed1998

Casemix-based funding of Northern Territory public hospitals: adjusting for severity and socio-economic variations.

The Northern Territory intends to make use of Australian National Diagnosis Related Groups (DRGs) and their cost relativities as the basis for the allocation of budgets among public hospitals. The study reported here attempted to assess the extent to which there are variations in severity of illness and socio-economic status which are not adequately explained by DRG alone and, if so, to develop a DRG payment adjustment index by use of routinely available data items. The investigation was undertaken by use of a database containing all discharges between July 1992 and June 1995. Hospital length of stay was used as a proxy for cost. Multivariate analysis was undertaken and it was found that several variables were associated with cost variations within DRGs. Stepwise multiple linear regression was used to develop a model in which 14 variables were able to explain 45% of the variations. Index values were subsequently computed from the regression model for each of eight categories of admitted patient episodes which are the intersections of three binary variables: Aborigine or non-Aborigine, rural or urban usual place of residence of the patient and hospital type (teaching or other). It is intended that these index values will be used to compute differential funding rates for each hospital in the Territory.

Aged↗
PubMed1998

Linking measures of health gain to explicit priority setting by an area health service in Australia.

A demonstration project was undertaken to develop an integer programming model that could help a regional health authority to take into account data on service effectiveness when allocating resources to acute inpatient services. The model was designed to find the mix of services that would maximise health gain from the available resources, and so provide information that could be used to encourage hospitals to change their patient mix. It was developed in collaboration with an Area Health Service in New South Wales, Australia, with the aim of assessing its potential as a decision support tool. Acute inpatient services were categorised in the model using classes derived from the Australian National Diagnosis Related Groups (AN-DRG) classification and the classes developed by the Oregon Health Services Commission. Estimates for the effectiveness of each service was derived from the Oregon benefit data. Estimates of resource use were derived from AN-DRG data. The expected demand for each service was derived from local activity data. Various scenarios were developed to assess the potential of the model to support decision makers. These mimicked plausible policy options and tested the sensitivity of the results to changes in the data. The scenarios demonstrated the model could reveal the consequences of different policy options, but also suggested that the difference in the cost-effectiveness of services close to the margin would be small and so a rigid approach to priority setting is undesirable. Difficulties in developing the model also demonstrate that incorporating health gain data into resource allocation decisions will not be straight-forward for health planners.

Cost-Benefit Analysis↗
PubMed1998

Using simulation to educate hospital staff about casemix.

When the Australian government funded a casemix development program, few hospital clinicians or staff knew much about casemix classifications like Diagnosis Related Groups (DRGs). Although the concepts behind casemix are essentially simple, it is not a trivial task to explain the logic used to assign patients to classes, or the use of casemix data for management or funding. Therefore, as part of a project to create educational material, a computer-based management game, built around a simulation model of a hospital, was developed. The game was designed for use in a workshop setting, to allow participants to test their understanding of the casemix information presented to them. The simulation mimicked the operation of a hospital, with a player taking the role of a hospital manager. It aimed to demonstrate how AN-DRGs might be used for funding; how patient costs are influenced by hospital activity; and how casemix data can assist in monitoring the use of resources. The game, called Dragon, proved to be very successful, and is now distributed as part of the National Casemix Education series.

Australia↗
PubMed1998

Severity variations within DRGs: measurement of hospital effects by use of data on significant secondary diagnoses and procedures.

The Diagnosis Related Group classification has provided an excellent basis for enhancing the equity of resource allocation between public acute hospitals. However, it underestimates the higher levels of severity and consequent costliness of referral hospitals. This paper describes a practical way of measuring within-DRG variations in severity, which can be used to increase the precision of casemix-based funding. It involves the regression of length of stay against the numbers of significant diagnoses and procedures, and bence the prediction of additional justified costs. An example is given of its application to data from South Australian public hospitals.

Diagnosis-Related Groups↗
PubMed1998

Casemix funding in rural NSW: exploring the effects of isolation and size.

The New South Wales Department of Health (NSW Health) wishes to make appropriate use of casemix data as inputs to the determination of funding levels for small rural hospitals. However, other factors such as hospital size and degree of isolation might need to be taken into account. The study reported here involved correlation of actual expenditures with those predicted by use of a casemix model alone, across 105 small public hospitals in the State. We then explored the extent to which the correlation could be increased by the addition of distance and isolation variables. It was found that actual costs were highly correlated with those predicted from the casemix data alone, and that the correlation increased when both the distance and the size variables were introduced. However, contrary to expectations, reduced size was associated with reduced costs, and reduced isolation was associated with increased costs. It was concluded that, while the predicted relationships may be present, they are likely to be relatively weak and are probably being masked by other factors not present in the model. In particular, it seems likely that there are variations in severity within the acute admitted patient category which are not fully explained by the casemix instrument used in this study (the DRG classification). We suggest that other terms be introduced to control for this possibility before any further attempt is made to test whether size and distance factors can be identified which work in the expected direction.

Catchment Area, Health↗
PubMed1998

The second national hospital costing study: background, results and implications.

The costing of hospital outputs, and especially of acute admitted patients categorised by DRG, has been the focus of considerable attention in the last decade. Many individual hospitals now routinely estimate the costs of their main products, several State and Territory health authorities undertake periodic multi-site studies, and there have been a few one-off national studies. This paper summarises the methods and results of the most recent national study, which measured costs at a sample of public and private hospitals around Australia for the 1996-97 financial year. We briefly describe the main results and note some implications.

Australia↗
PubMed1996

Hospital input price indexes in Australia: are they worth the effort?

This paper summarises aspects of the design and use of hospital input price indexes, and describes four indexes produced in Australia in the last decade. It argues that there would be some benefit in establishing a routine national index, if it were designed to be low-cost. However, care should be taken to avoid excessive reliance on the results in the resource allocation and funding context. Input prices contribute relatively little in hospitals' expenditure changes. It is also necessary to monitor and manage changes in the volumes of inputs, and this is likely to be a more rewarding task.

Australia↗
PubMed1994

Adapting DRGs: the British, Canadian and Australian experiences.

The DRG classification was developed in the United States, and has been widely used there for analytical and resource allocation purposes. Its utility has been recognised in other countries. Some have adopted US versions without change, and others have chosen to develop their own adaptations. This paper discusses the processes and outcomes of adaptation in Canada, Britain and Australia. An attempt is made to generalise the trends. It is concluded that there is a high degree of similarity of intent, although different solutions have been adopted in some cases. Where major differences remain, they are mostly a consequence of the lack of resources to pursue all opportunities for refinement at the same time. All three countries have correctly focused on involvement of their own clinician groups. However, they have tended to restrict their view to US experiences when looking overseas. It is argued that greater attention should be paid to sharing their ideas with countries with which they have a greater degree of similarity.

Australia↗