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Making people work longer – What is the impact on the medical workforce?

Making people work longer – What is the impact on the medical workforce?
Making people work longer – What is the impact on the medical workforce?
The current work examined the sociological impact of increasing the State Pension Age on the medical workforce in the United Kingdom. This project mainly focussed on Trained Hospital Doctors in England due to the extremely large data and time constraint. The government of the United Kingdom had carried forward the increment of the State Pension Age to 67 between year 2026 and 2028, which was earlier planned to be implemented between year 2034 and 2036. System dynamics modelling was chosen to be the most appropriate approach for this project. The project applied the qualitative and quantitative modelling. Qualitative modelling was done by constructing a causal loop diagram. Quantitative modelling consisted of two stages. The first stage was the development of retirement profile tool to calculate the retirement rate at each age group. Secondly, a system dynamics simulation model was developed using Vensim DSS to forecast the supply and demand of the English medical workforce up to year 2040 by generating plausible scenarios. Plausible scenarios were developed based on the retirement behavior of the medical workforce in response to the reformation of the State Pension age. The results showed the size of Trained Hospital Doctor workforce annually and evaluated the proposed reformation of the State Pension age.
Chow, May Kee
1e49b246-a40b-47fe-9994-2eac88067ddf
Chow, May Kee
1e49b246-a40b-47fe-9994-2eac88067ddf
Penn, Marion. L.
f5635327-14a8-4572-a592-1f46324504ba

(2013) Making people work longer – What is the impact on the medical workforce? University of Southampton, Mathematical Sciences, Masters Thesis, 108pp.

Record type: Thesis (Masters)

Abstract

The current work examined the sociological impact of increasing the State Pension Age on the medical workforce in the United Kingdom. This project mainly focussed on Trained Hospital Doctors in England due to the extremely large data and time constraint. The government of the United Kingdom had carried forward the increment of the State Pension Age to 67 between year 2026 and 2028, which was earlier planned to be implemented between year 2034 and 2036. System dynamics modelling was chosen to be the most appropriate approach for this project. The project applied the qualitative and quantitative modelling. Qualitative modelling was done by constructing a causal loop diagram. Quantitative modelling consisted of two stages. The first stage was the development of retirement profile tool to calculate the retirement rate at each age group. Secondly, a system dynamics simulation model was developed using Vensim DSS to forecast the supply and demand of the English medical workforce up to year 2040 by generating plausible scenarios. Plausible scenarios were developed based on the retirement behavior of the medical workforce in response to the reformation of the State Pension age. The results showed the size of Trained Hospital Doctor workforce annually and evaluated the proposed reformation of the State Pension age.

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More information

Published date: September 2013
Organisations: University of Southampton, Operational Research

Identifiers

Local EPrints ID: 368540
URI: http://eprints.soton.ac.uk/id/eprint/368540
PURE UUID: 02fda20c-3e86-4080-b142-e9c17512531a

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Date deposited: 03 Sep 2014 09:24
Last modified: 18 Jul 2017 01:46

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Contributors

Author: May Kee Chow
Thesis advisor: Marion. L. Penn

University divisions

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