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

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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.

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Notes

  1. Here, and in subsequent similar cases, time should be understood as “time from when the model started”.

  2. It is therefore implicitly assumed that at least 5% of nurses graduate before the age of 25. According to data from the South African Nursing Council fewer than 5% of registered nurses currently working are less than 30 years old (http://www.sanc.co.za/stats). However, these data are notoriously unreliable as the register of nurses is rarely updated and over-estimate the number of nurses still working. Moreover, in a study carried out in six nursing colleges in South Africa (http://www.crehs.lshtm.ac.uk/safrica_corhort_12Jul.pdf), 25% of final year students interviewed were aged 24 or below.

  3. Squaring the parameter λ in the exponent provides a smoother effect (i.e. a less rapid decline in turnover probability) compared to what would be obtained without squaring it. Also, using the same parameter lambda, instead of two different parameters, ensures that the general shape of the function is preserved while lambda varies.

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Authors and Affiliations

  1. Department of Global Health and Development, London School of Hygiene and Tropical Medicine, 15-17 Tavistock Place, London, WC1H 9SH, UK

    Mylene Lagarde

  2. Department of Health Services Research and Policy, London School of Hygiene and Tropical Medicine, 15-17 Tavistock Place, London, WC1H 9SH, UK

    John Cairns

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  1. Mylene Lagarde
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Correspondence to Mylene Lagarde.

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Lagarde, M., Cairns, J. Modelling human resources policies with Markov models: an illustration with the South African nursing labour market. Health Care Manag Sci 15, 270–282 (2012). https://doi.org/10.1007/s10729-011-9184-5

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