Conceptualizing and Validating a Health Worker Mobility Score to Strengthen Retention in Nigerias Health System.

Abstract

Nigeria faces an escalating crisis of health worker attrition and international migration, driven by persistent push factors such as low remuneration, poor working conditions, insecurity and limited career progression. Existing human resources for health (HRH) information systems are largely retrospective and descriptive, providing insufficient visibility into the behavioral signals that precede internal mobility or international migration. This paper conceptualizes and proposes the validation of a Health Worker Mobility Score (HWMS)--a behaviour-based, real-time predictive analytics tool designed to identify early warning signs of attrition among Nigerias health workforce. We developed a composite, weighted mobility score informed by labour-market theory, migration theory, and human capital theory. Eight behavioural indicators--captured routinely through ManagedMedics, a novel digital HR management platform--form the scores core domains, including job stability, locum intensity, absenteeism, training participation and digital engagement. We propose a prospective 18-month longitudinal cohort study across six Nigerian states (Lagos, Federal Capital Territory, Kaduna, Rivers, Imo, Ekiti), recruiting 800-900 health workers from approximately 200 private hospitals. Predictor data will derive exclusively from ManagedMedics platform logs, while administrative HR records and periodic surveys will serve as validation data. Predictive accuracy will be assessed using logistic regression, Cox proportional hazards models, and machine-learning classifiers (random forests, XGBoost, SVMs), following TRIPOD guidelines. The HWMS provides a structured mechanism for transforming micro-level behavioural signals into attrition-risk tiers (low, moderate, high). Conceptual illustration shows how diverse behavioural indicators aggregate into meaningful predictors of internal mobility and potential migration. Proposed use cases span early-warning analytics, targeted retention strategies, state-level and facility-targeted workforce planning, integration with national HRH systems, and operationalization of Nigerias managed migration policy. The HWMS represents an innovative, context-appropriate approach to strengthening HRH stability in Nigeria. By shifting from retrospective enumeration to predictive intelligence, the score offers policymakers, hospital managers and development partners a tool for proactive retention, ethical recruitment, and data-informed workforce planning. Future empirical validation will determine the scores predictive accuracy, refine indicator weights and assess its feasibility for national scale-up and integration into Nigerias digital health ecosystem.

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