Publication Details

AFRICAN RESEARCH NEXUS

SHINING A SPOTLIGHT ON AFRICAN RESEARCH

medicine

Density of Health Workforce Correlates to Disease Outcomes: Evidence From Global Data in Otolaryngology

OTO Open, Volume 6, No. 1, Year 2022

Objective: To better understand the impact of the otolaryngology-specific workforce on the burden of related diseases. Study Design: Retrospective analysis of existing workforce density data as compared with the incidence, mortality, and morbidity data for 4 otolaryngologic diseases. Setting: An overall 138 countries with known otolaryngology–head and neck surgery workforce and epidemiologic data. Methods: We obtained raw data on workforce estimates of ear, nose, and throat surgical specialists from the World Health Organization. Disease burdens for 4 conditions were estimated via 2 ratios, the mortality:incidence ratio (MIR) and YLD:incidence ratio (years lost to disability), as specified in the Global Burden of Disease database. These were correlated to country-specific otolaryngologist density data in univariate and multivariate analyses. Results: Increased density of the ear, nose, and throat workforce correlated with better outcomes for otolaryngologic-treated surgical diseases. A 10% increase in otolaryngology workforce density was associated with a 0.27% reduction in YLD:incidence ratio for chronic otitis media, a 0.94% reduction in MIR for lip and oral cavity cancer, a 1.46% reduction in MIR for laryngeal cancer, and a 1.34% reduction in MIR for pharyngeal cancer (all P <.001)—an effect that remained after adjustment for health systems factors for all conditions but chronic otitis media. Conclusion: The density of the surgical workforce is assumed to affect disease outcomes, but ours is the first analysis to show that increased workforce density for a specific surgical specialty correlates with improved disease outcomes. While there is a consensus to increase access to health care providers, quantifying the effect on disease outcomes is an important metric for those performing health economics modeling, particularly where resources are limited.
Statistics
Citations: 6
Authors: 6
Affiliations: 7
Identifiers
Research Areas
Cancer
Disability
Health System And Policy
Study Design
Cohort Study