Department of Global Health and Development, London School of Hygiene and Tropical Medicine, 15-17 Tavistock Place, London, WC1H 9SH, UK.
Health Care Manag Sci. 2012 Sep;15(3):270-82. doi: 10.1007/s10729-011-9184-5. Epub 2011 Nov 15.
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.
本文提出了一个建模框架，以模拟和评估吸引和留住农村地区护士的政策干预的短期和长期影响。具体来说，我们使用马尔可夫模型来模拟专业劳动力市场中卫生保健工作者流动的动态。建立了一个模型来模拟南非护士在劳动力市场不同部分之间随时间的流动。该模型建立在一系列详细说明的假设基础上，并使用离散选择实验生成的预测。结果表明，马尔可夫模型能够在短期和长期内模拟人力资源政策干预的效果。它们突出了时间对某些潜在政策干预措施有效性的影响，这些政策干预措施的即时积极影响可能会随着不同的不利影响的出现而逐渐消失。尽管它很复杂，但这种创新方法提供了一个透明且有用的工具，可用于制定解决农村人员短缺的政策。
