Tasmanian sub-acute care pathways
Duration: October 2013 – June 2015
Health service planning is core business for jurisdictions and local areas. Traditionally age-sex standardised utilisation rates for individual DRGs have been applied to ABS population projections to predict the future need for subacute services. However, improved methods are required to address the acknowledged underservicing of subacute care. In this project, funded as a component of the suite of projects lead by the Commission on the Delivery of Health Services in Tasmania, AHSRI incorporated the concept of “rehabilitation-sensitive” AR-DRGs to develop a predictive tool to assess demand for rehabilitation and Geriatric Evaluation and Management (GEM) care following acute inpatient episodes provided in public sector facilities.
What we did
A set of acute care AR-DRGs from which patients were more likely to require subsequent rehabilitation had been identified previously and designated “rehabilitation-sensitive”. This work was extended in the current project by:
- Updating the version of AR-DRG from 5.2 to 7.0 and revising “rehabilitation-sensitive” list;
- Extending the concept by quantifying the degree of sensitivity and by incorporating the age distribution of patients; and
- Expanding the scope from just rehabilitation to rehabilitation and GEM, primarily because of inconsistencies between jurisdictions in the allocation of patients to these two care types.
Data available for the project included the 2010/11 and 2011/12 admitted patient dataset provided by the Australian Institute of Health and Welfare and additional data sourced from AROC. Logistic regression and other statistical techniques enabled a predictive model to be built. Consultations with clinicians and jurisdictional representatives guaranteed that the results were clinically valid and that the method was an improvement on others currently available.
The predictive model takes the form of tables of probabilities that patients will require rehabilitation or GEM care after an acute episode and can be applied to acute inpatient administrative datasets in any Australian jurisdiction or local area. Its use of patient-level characteristics will enable service planners to improve their forecasting of demand for these services.
The model was tested using Tasmanian data. The use of a national dataset in the model development and the series of national clinical consultations undertaken during the project, however, ensured that the model is suitable for application in all jurisdictions.