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Modelling human resources policies with Markov models: an illustration with the South African nursing labour market

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  • Mylene Lagarde
  • John Cairns

Abstract

This article proposes a modelling framework to simulate and assess the immediate and long-term effects of policy interventions to attract and retain nurses in rural areas. Specifically, we use a Markov model to model the dynamics of movements of health care workers in a professional labour market. A model is developed to simulate the movements of South African nurses between different segments of the labour market over time. The model builds upon a series of assumptions that are stated in details, and uses predictions generated by discrete choice experiments. The results demonstrate the ability of Markov models to model the effects of human resources policy interventions in the short and long run. They highlight the effects of time on the effectiveness of some potential policy interventions, whose immediate positive effects can be eroded as different adverse effects appear. Despite its complexity, this innovative method provides a transparent and useful tool to inform the design of policies to address rural staff shortages. Copyright Springer Science+Business Media, LLC 2012

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  • Mylene Lagarde & John Cairns, 2012. "Modelling human resources policies with Markov models: an illustration with the South African nursing labour market," Health Care Management Science, Springer, vol. 15(3), pages 270-282, September.
  • Handle: RePEc:kap:hcarem:v:15:y:2012:i:3:p:270-282
    DOI: 10.1007/s10729-011-9184-5
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    References listed on IDEAS

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    1. Gloria Likupe, 2006. "Experiences of African nurses in the UK National Health Service: a literature review," Journal of Clinical Nursing, John Wiley & Sons, vol. 15(10), pages 1213-1220, October.
    2. Walker, Liz & Gilson, Lucy, 2004. "'We are bitter but we are satisfied': nurses as street-level bureaucrats in South Africa," Social Science & Medicine, Elsevier, vol. 59(6), pages 1251-1261, September.
    3. Mariel Lavieri & Martin Puterman, 2009. "Optimizing nursing human resource planning in British Columbia," Health Care Management Science, Springer, vol. 12(2), pages 119-128, June.
    4. Briggs, Andrew & Sculpher, Mark & Claxton, Karl, 2006. "Decision Modelling for Health Economic Evaluation," OUP Catalogue, Oxford University Press, number 9780198526629.
    5. Andrew H. Briggs & A. E. Ades & Martin J. Price, 2003. "Probabilistic Sensitivity Analysis for Decision Trees with Multiple Branches: Use of the Dirichlet Distribution in a Bayesian Framework," Medical Decision Making, , vol. 23(4), pages 341-350, July.
    6. Frank A. Sonnenberg & J. Robert Beck, 1993. "Markov Models in Medical Decision Making," Medical Decision Making, , vol. 13(4), pages 322-338, December.
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    Cited by:

    1. Mandeville, Kate L. & Hanson, Kara & Muula, Adamson S. & Dzowela, Titha & Ulaya, Godwin & Lagarde, Mylène, 2017. "Specialty training for the retention of Malawian doctors: A cost-effectiveness analysis," Social Science & Medicine, Elsevier, vol. 194(C), pages 87-95.
    2. Cardoso-Grilo, Teresa & Monteiro, Marta & Oliveira, Mónica Duarte & Amorim-Lopes, Mário & Barbosa-Póvoa, Ana, 2019. "From problem structuring to optimization: A multi-methodological framework to assist the planning of medical training," European Journal of Operational Research, Elsevier, vol. 273(2), pages 662-683.
    3. Lagarde, Mylene & Blaauw, Duane & Cairns, John, 2012. "Cost-effectiveness analysis of human resources policy interventions to address the shortage of nurses in rural South Africa," Social Science & Medicine, Elsevier, vol. 75(5), pages 801-806.
    4. Arora, Nikita & Crastes dit Sourd, Romain & Hanson, Kara & Woldesenbet, Dorka & Seifu, Abiy & Quaife, Matthew, 2022. "Linking health worker motivation with their stated job preferences: A hybrid choice analysis in Ethiopia," Social Science & Medicine, Elsevier, vol. 307(C).
    5. Georgiou, Andreas C. & Thanassoulis, Emmanuel & Papadopoulou, Alexandra, 2022. "Using data envelopment analysis in markovian decision making," European Journal of Operational Research, Elsevier, vol. 298(1), pages 276-292.

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