How to Recruit and Retain Health Workers in Rural and Remote Areas in Developing Countries

Worldwide the geographical distribution of health workers is skewed towards urban and wealthier areas. This pattern is found in nearly every country in the world, regardless of the level of economic development and health system organization, but the problem is especially acute in developing countries. The geographical imbalances in the health workforce further exacerbate inequities in the health sector, as the services are not available where needs are higher and impact greater.

A variety of interventions have been applied in different contexts and for different types of health workers to address this problem. There is an emerging consensus that policies for recruitment and retention in rural and remote areas need to address two critical issues: i) to be effective, interventions need to be implemented in bundles, combining different packages of interventions according to the variety of factors influencing the health worker’s decision to work in rural or remote areas; ii) to match the interventions with health worker’s preferences and expectations, since the health worker’s employment decisions are a function of these preferences.

In order to respond to these requirements, this paper proposes the application of Discrete Choice Experiments (DCEs) to allow for measurement of health workers’ preferences and quantitatively predicts the job uptake given a set of job characteristics. This paper has a two-fold objective: i) to give the reader an overview of the magnitude of unequal health workforce distribution in the developing countries, provide a summary of the evidence to date on the factors that contribute to these imbalances, and present a systematic set of policy interventions that are being implemented around the world to address the problem of recruitment and retention of health workers in rural and remote regions of the developing countries; and ii) to introduce the reader to the potential application of the DCE to elicit health workers’ preferences and determine the factors likely to increase their probability of taking up a rural or remote job.