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What will make a difference? Assessing the impact of policy and non-policy scenarios on estimations of the future GP workforce

Overview of attention for article published in Human Resources for Health, June 2017
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (52nd percentile)

Mentioned by

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3 tweeters

Citations

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2 Dimensions

Readers on

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23 Mendeley
Title
What will make a difference? Assessing the impact of policy and non-policy scenarios on estimations of the future GP workforce
Published in
Human Resources for Health, June 2017
DOI 10.1186/s12960-017-0216-1
Pubmed ID
Authors

Caroline O. M. Laurence, Jonathan Karnon

Abstract

Health workforce planning is based on estimates of future needs for and supply of health care services. Given the pipeline time lag for the training of health professionals, inappropriate workforce planning or policies can lead to extended periods of over- or under-supply of health care providers. Often these policy interventions focus on one determinant of supply and do not incorporate other determinants such as changes in population health which impact the need for services. The aim of this study is to examine the effect of the implementation of various workforce policies on the estimated future requirements of the GP workforce, using South Australia as a case study. This is examined in terms of the impact on the workforce gap (excess or shortage), the cost of these workforce policies, and their role in addressing potential non-policy-related future scenarios. An integrated simulation model for the general practice workforce in South Australia was developed, which determines the supply and level of services required based on the health of the population over a projection period 2013-2033. The published model is used to assess the effects of various policy and workforce scenarios. For each policy scenario, associated costs were estimated and compared to baseline costs with a 5% discount rate applied. The baseline scenario estimated an excess supply of GPs of 236 full-time equivalent (FTE) in 2013 but this surplus decreased to 28 FTE by 2033. The estimates based on single policy scenarios of role substitution and increased training positions continue the surplus, while a scenario that reduces the number of international medical graduates (IMGs) recruited estimated a move from surplus to shortage by 2033. The best-case outcome where the workforce achieves balance by 2023 and remains balanced to 2033, arose when GP participation rates (a non-policy scenario) were combined with the policy levers of increased GP training positions and reduced IMG recruitment. The cost of each policy varied, with increased role substitution and reduced IMG recruitment resulting in savings (AUD$752,946,586 and AUD$3,783,291 respectively) when compared to baseline costs. Increasing GP training costs over the projection period would cost the government an additional AUD$12,719,798. Over the next 20 years, South Australia's GP workforce is predicted to remain fairly balanced. However, exogenous changes, such as increased demand for GP services may require policy intervention to address associated workforce shortfalls. The workforce model presented in this paper should be updated at regular intervals to inform the need for policy intervention.

Twitter Demographics

The data shown below were collected from the profiles of 3 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 23 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 26%
Unspecified 4 17%
Student > Master 3 13%
Researcher 2 9%
Student > Doctoral Student 2 9%
Other 6 26%
Readers by discipline Count As %
Medicine and Dentistry 8 35%
Unspecified 5 22%
Business, Management and Accounting 2 9%
Social Sciences 2 9%
Computer Science 1 4%
Other 5 22%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 06 July 2017.
All research outputs
#6,409,349
of 11,435,137 outputs
Outputs from Human Resources for Health
#516
of 611 outputs
Outputs of similar age
#119,763
of 261,320 outputs
Outputs of similar age from Human Resources for Health
#16
of 18 outputs
Altmetric has tracked 11,435,137 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 611 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.2. This one is in the 10th percentile – i.e., 10% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 261,320 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 52% of its contemporaries.
We're also able to compare this research output to 18 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.