August 2014 Commonwealth of Australia 2014

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The simulation modelling techniques used to produce the projections rely on two key inputs:

  • The set of assumptions about future conditions; and

  • The data from which the model’s parameters inputs and starting position are derived.

The assumptions are important as they affect the interpretation of workforce projection results. The projections provide likely outcomes given the assumptions on which they are based, so if any of the assumptions are not applicable or cease to reflect real world situations, the projections will not provide an accurate indication of future outcomes. For the input data, any inaccuracies that may exist will directly impact on the accuracy of the modelled results.

Major assumptions and data treatments underlying the scenarios are outlined in the following sections. These are critical to understand as the interpretation of the modelled outputs needs to be done in the context of the underpinning assumptions.

Supply assumptions

  • The base oral health workforce is set at 2012 levels.

  • Workforce entrants enter the model as graduates or as internationally-trained oral health professionals through either temporary or permanent migration streams.

  • Dental graduates entering the workforce are grown through to 2017 based on ACODS data and held constant thereafter. For the other workforces, graduates are grown through to 2015, and held constant thereafter.

  • The inflow of oral health professionals via migration is obtained from the Department of Immigration and Border Protection. The model holds constant 2012 levels of international migration.

  • The proportion of graduating international students entering the workforce is calculated at 70 per cent for dentists.

  • Hours worked are calculated and applied separately for each age/sex cohort within each oral health workforce (dentists, dental prosthetists, oral health therapists, dental hygienists, dental therapists). The data from which hours worked is calculated is taken from the National Health Workforce Dataset for 2012.

  • Exit rates are calculated separately for dentists, dental prosthetists and for oral health practitioners (comprised of oral health therapists, dental hygienists, dental therapists). They are calculated for each five year age/sex cohort.

  • Exit rates are a composite measure including all forms of removal from the workforce, permanent or temporary.

  • All graduating oral health professionals are assumed to remain in the workforce, even in situations of workforce supply exceeding demand. That is, exit rates are not adjusted to take account of possible movements away from a profession in an oversupply situation

Demand assumptions

  • For the total population, the expressed demand rate for the comparison scenario was calculated based on the growth in the number of visits provided between 1994 and 2010, using data from the ARCPOH NDTIS. This was calculated to be 2.55 per cent. A constant, linear growth rate is then applied to the various age/sex cohorts. This provides for variation in demand as a result of different sizes of age/sex cohorts over time, but not due to different demand patterns within an age/sex cohort.

  • Demand and supply start from an ‘in balance’ position. This is for the purposes of modelling only and should not be taken to imply that the workforces are (or are not) currently in balance.

Accuracy of workforce projections

It should be noted that projections become less accurate as the period of time over which they are applied increases. This is due to the inherent error in any projection methodology, and/or changes in technology (or other factors) which over an extended period are likely to change the relationship between type and number of services provided per practitioner. Another factor that influences the projection period is the changes and reliability in data sets used. For example, over a long period of time the population projections applied to the modelling may change. However, it is the graduate numbers over the projection period that could change most dramatically. Both will alter the workforce projections. In summary, the relevance of long term projections generated will in part depend on the quality of the data inputs for those projections, while less robust data will limit the projection period.

Appendix F – Data sources

Data sources available to HWA vary significantly in terms of their frequency, source and length of time series available. Many sources are only newly available, are only partially complete (due to the need to collect data over an extended period) or are collected infrequently. The extent to which HWA can accurately model the future oral health workforce is entirely dependent on the quality and availability of relevant data.

In preparing this report, potential data sources were assessed to determine the availability, coverage and quality of those data items which are essential for estimating the current workforce and projecting the future workforce. Appropriate data sources which have been used in the modelling in this report are listed in the tables below.

Where the process of selecting input data identified data gaps, options for addressing the gaps were considered and assessed on the basis of the:

  • type of data required

  • collection methods used

  • tool and infrastructure required

  • resource cost and time requirements

  • potential analysis in the future, such as developing a survey to conduct annually or longer intervals to provide ongoing information.

HWA will continue to augment and refine the capabilities of the model over time to reflect the accumulation of additional datasets, changes in underlying demand and supply factors, and finer levels of detail (for example, modelling regional versus metropolitan service levels).

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