Janette P Green

An Australian casemix classification for palliative care: technical development and results

Objectives: To develop a palliative care casemix classification for use in all settings including hospital, hospice and home-based care. Sample: 3866 palliative care patients who, in a three-month period, had 4596 episodes of care provided by 58 palliative care services in Australia and New Zealand. Method: A detailed clinical and service utilization profile was collected on each patient with staff time and other resources measured on a daily basis. Each day of care was costed using actual cost data from each study site. Regression tree analysis was used to group episodes of care with similar costs and clinical characteristics. Results: In the resulting classification, the Australian National Sub-acute and Non-acute Patient (AN-SNAP) Classification Version 1, the branch for classifying inpatient palliative care episodes (including hospice care) has 11 classes and explains 20.98% of the variance in inpatient palliative care phase costs using trimmed data. There are 22 classes in the ambulatory palliative care branch that explains 17.14% variation in ambulatory phase cost using trimmed data. Discussion: The term ‘subacute’ is used in Australia to describe health care in which the goal — a change in functional status or improvement in quality of life — is a better predictor of the need for, and the cost of, care than the patients underlying diagnosis. The results suggest that phase of care (stage of illness) is the best predictor of the cost of Australian palliative care. Other predictors of cost are functional status and age. In the ambulatory setting, symptom severity and the model of palliative care are also predictive of cost. These variables are used in the AN-SNAP Version 1 classification to create 33 palliative care classes. The classification has clinical meaning but the overall statistical performance is only moderate. The structure of the classification allows for it to be improved over time as models of palliative care service delivery develop.

An Australian casemix classification for palliative care: lessons and policy implications of a national study.

Objectives: To provide a nontechnical discussion of the development of a palliative care casemix classification and some policy implications of its implementation. Sample: 3866 palliative care patients who, in a three month period, had 4596 episodes of care provided by 58 palliative care services in Australia and New Zealand. Method: A detailed clinical and service utilization profile was collected on each patient with staff time and other resources measured on a daily basis. A statistical summary of the clinical variables was compiled as the first stage of the analysis. Results: Palliative care phase was found to be a good predictor of resource use, with patients fairly evenly distributed across the five categories. Clients treated in an inpatient setting had poorer function and higher symptom severity scores than those treated in an ambulatory setting, a result that is not surprising in this Australian setting. Discussion: Implementation of the resultant AN-SNAP classification has been proceeding since 1998 in some Australian jurisdictions. The development and implementation of a classification such as AN-SNAP provides the possibility of having a consistent approach to collecting palliative care data in Australia as well as a growing body of experience on how to progressively improve the classification over time.

Towards a measure of function for home and community care services in Australia: Part 2 - Evaluation of the screening tool and assessment instruments

The National Home and Community Care (HACC) Dependency Data Items Project was established to recommend, for national use, validated and reliable instruments for measuring the dependency of people eligible for HACC services. In Stage 2 of the project - reported here - a screening tool and assessment instruments selected in Stage 1 of the project were field-tested in a range of HACC agencies. The performance of the screen and the associated assessments was evaluated, as was their acceptability to HACC staff and clients. The results suggest that all of the five instruments are suitable for the target population of HACC services and they can be used effectively across a broad range of service types and by providers of diverse professional backgrounds.

Health services research and development in practice: an Australian experience

While there is a growing literature on how health services research can inform health policy decisions, the practical challenge is for health services researchers to develop an effective interface with health policy-making processes and to produce outputs that lead to outcomes. The experience of the Centre for Health Service Development at the University of Wollongong, Australia, is used to illustrate the issues so commonly described in the literature and to reflect on our experience of trying to remain viable while producing relevant and valid research. A case study in a specific policy area - namely, the development of case-mix classifications and information systems to inform policy and funding in the subacute and non-acute hospital and community care sectors - is used as a practical example of the research-policy interface.

Functional Assessment to Predict Capacity for Work in a Population of School‐leavers with Disabilities

This study reports on an assessment system for school‐leavers with disabilities to identify their capacity for work and the type of transition‐to‐work programme best suited to each person. Participants were 1,556 high school students in four cohorts who left school between 1999 and 2002. Each school‐leaver was assessed by rehabilitation counsellors for functional ability and capacity for work. In a supplementary study, the 2002 cohort was assessed by special transition teachers using a short screening tool. The results demonstrate that there is a predictable hierarchy of functional acquisition among school‐leavers with disabilities and that the single best predictor of future capacity for work and need for transition‐to‐work programmes among this group of young people is the capacity to manage activities of daily living. The results also demonstrate that a short screen used by teachers, together with a behavioural assessment, is sufficient to stream school‐leavers with a disability into a range of transition‐to‐work programmes.

The Australian National Sub-acute and Non-acute Patient Casemix Classification (AN-SNAP): its application and value in a stroke rehabilitation programme

Objective: To investigate whether the Australian National Sub-acute and Non-acute Patient Casemix Classification (SNAP) and Functional Independence Measure and Functional Related Group (Version 2) (FIM-FRG2) casemix systems can be used to predict functional outcome, and reduce the variance of length of stay (LOS) of patients undergoing rehabilitation after strokes. Design and setting: The study comprised a retrospective analysis of the records of patients admitted to the Cedar Court Healthsouth Rehabilitation Hospital for rehabilitation after stroke. Subjects: The sample included 547 patients (83.3% of those admitted with stroke during this period). Patient data were stratified for analysis into the five SNAP or nine FIM-FRG2 groups, on the basis of the admission FIM scores and age. Main outcomes: The AN-SNAP classification accounted for a 30.7% reduction of the variance of LOS, and 44.2% of motor FIM, and the FIM-FRG2 accounts for 33.5% and 56.4% reduction respectively. Comparison of the Cedar Court with the national AN-SNAP data showed differences in the LOS and functional outcomes of older, severely disabled patients. Intensive rehabilitation in selected patients of this type appears to have positive effects, albeit with a slightly longer period of inpatient rehabilitation. Conclusions: Casemix classifications can be powerful management tools. Although FIM-FRG2 accounts for more reduction in variance than SNAP, division into nine groups meant that some contained few subjects. This paper supports the introduction of AN-SNAP as the standard casemix tool for rehabilitation in Australia, which will hopefully lead to rational, adequate funding of the rehabilitation phase of care.

Current Funding and Financing Issues in the Australian Hospice and Palliative Care Sector

This article overviews current funding and financing issues in the Australian hospice and palliative care sector. Within Australia, the major responsibilities for managing the health care system are shared between two levels of government. Funding arrangements vary according to the type of care. The delivery of palliative care services is a State/Territory responsibility. Recently, almost all States/Territories have developed overarching frameworks to guide the development of palliative care policies, including funding and service delivery structures. Palliative care services in Australia comprise a mix of specialist providers, generalist providers, and support services in the public, nongovernment, and private sectors. The National Palliative Care Strategy is a joint strategy of the Commonwealth and States that commenced in 2002 and includes a number of major issues. Following a national study in 1996, the Australian National Subacute and Nonacute Patient (AN-SNAP) system was endorsed as the national casemix classification for subacute and nonacute care. Funding for palliative care services varies depending on the type of service and the setting in which it is provided. There is no national model for funding inpatient or community services, which is a State/Territory responsibility. A summary of funding arrangements is provided in this article. Palliative care continues to evolve at a rapid rate in Australia. Increasingly flexible evidence-based models of care delivery are emerging. This article argues that it will be critical for equally flexible funding and financing models to be developed. Furthermore, it is critical that palliative care patients can be identified, classified, and costed. Casemix classifications such as AN-SNAP represent an important starting point but further work is required.

Emergency department waiting times: do the raw data tell the whole story?

OBJECTIVE To determine whether there are real differences in emergency department (ED) performance between Australian states and territories. METHODS Cross-sectional analysis of 2009-10 attendances at an ED contributing to the Australian non-admitted patient ED care database. The main outcome measure was difference in waiting time across triage categories. RESULTS There were more than 5.8 million ED attendances. Raw ED waiting times varied by a range of factors including jurisdiction, triage category, geographic location and hospital peer group. All variables were significant in a model designed to test the effect of jurisdiction on ED waiting times, including triage category, hospital peer group, patient socioeconomic status and patient remoteness. When the interaction between triage category and jurisdiction entered the model, it was found to have a significant effect on ED waiting times (P<0.001) and triage was also significant (P<0.001). Jurisdiction was no longer statistically significant (P=0.248 using all triage categories and 0.063 using only Australian Triage Scale 2 and 3). CONCLUSIONS Although the Council of Australian Governments has adopted raw measures for its key ED performance indicators, raw waiting time statistics are misleading. There are no consistent differences in ED waiting times between states and territories after other factors are accounted for. WHAT IS KNOWN ABOUT THE TOPIC? The length of time patients wait to be treated after presenting at an ED is routinely used to measure ED performance. In national health agreements with the federal government, each state and territory in Australia is expected to meet waiting time performance targets for the five ED triage categories. The raw data indicate differences in performance between states and territories. WHAT DOES THIS PAPER ADD? Measuring ED performance using raw data gives misleading results. There are no consistent differences in ED waiting times between the states and territories after other factors are taken into account. WHAT ARE THE IMPLICATIONS FOR PRACTITIONERS? Judgements regarding differences in performance across states and territories for triage waiting times need to take into account the mix of patients and the mix of hospitals.