Public Sector
Demand for acute hospital services has been increasing at a rate exceeding population growth. Hardes & Associates were pioneers in Australia in the development of acute hospital planning models that take account of both demographic (population growth and ageing) and non-demographic (clinical trends) drivers of demand.
For more than a decade our database modelling has been used in all Australian states and Territories for acute hospital planning. The model is used to facilitate public sector service planning, workforce planning and capital works. The model is also extensively used throughout the private sector. A similar approach has been used for services planning in human services sectors including mental health services, dental services, community health services, accident and emergency services, child protection services and homelessness.
Our model is conceptually straightforward. It recognises that growth in use of acute hospital services is determined by population growth, population ageing and changes in clinical practice. Each of these components, not just population growth and ageing, must be projected to forecast future demand. The base case projection is undertaken by applying admission rates and average length of stay (derived by extrapolation of historic trends at the subspecialty/age/sex level) - to projected populations.
The review and extrapolation of clinical trends is critical to the success of the modelling. Hardes & Associates have experience with clinical trend reviews in every Australian State/Territory and reviews are undertaken by staff with tertiary qualifications in Medicine, Epidemiology and Clinical Coding.
In the base case or status quo model projected activity (after modification for geographic variation in admission rates) is distributed across hospitals in accordance with current referral patterns. The base case describes and quantifies where the system is heading. It provides a point for services planning.
The scenario modelling software allows planners to model alternate scenarios by adjusting the demand projections (admission rates, length of stay, geographic variation, population projections) and/or supply (changing the distribution of services including opening or closure of hospitals or parts thereof). This allows quantification of scenarios including changes in models of care.
The model is based upon routinely collected data. No additional collection is required. No additional software is required. The model works entirely within a Microsoft environment and runs easily on PC. Training in the use and interpretation of the model is standardised.
