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Reconstructive surgery outreach to low- and middle-income countries: An interdisciplinary analysis of 131 non-governmental organizations

BACKGROUND: A significant portion of surgical aid to low- and middle-income countries (LMICs) is provided by non-governmental organizations (NGOs) in concert with surgeons, but little is known about the overall scope of this work or how it corresponds to indicators typically used to guide developmen...

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Detalles Bibliográficos
Autores principales: Chao, Albert H, McAllister, Jacqueline R
Formato: Online Artículo Texto
Lenguaje:English
Publicado: International Society of Global Health 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8822145/
https://www.ncbi.nlm.nih.gov/pubmed/35186281
http://dx.doi.org/10.7189/jogh.12.04002
Descripción
Sumario:BACKGROUND: A significant portion of surgical aid to low- and middle-income countries (LMICs) is provided by non-governmental organizations (NGOs) in concert with surgeons, but little is known about the overall scope of this work or how it corresponds to indicators typically used to guide developmental aid distribution. The objective of this study was to characterize and investigate the collective efforts of NGOs providing reconstructive surgical aid to LMICs. METHODS: An interdisciplinary approach was taken drawing from political science to examine this issue in reconstructive surgery. NGOs providing reconstructive surgical aid were identified, and then catalogued with respect to the LMICs they serve. LMICs were characterized using 28 variables in 6 domains based on contemporary developmental theory. Univariate and multivariate regression analyses were performed. RESULTS: A total of 131 reconstructive surgery NGOs were identified serving 718 sites in 136 LMICs. Univariate analysis found that LMICs that were more frequent recipients of aid were more populous (P < 0.001), had lower ‘Hospital Beds Density’ (P = 0.001), and had higher rates of ‘Mortality by Injury’ (P = 0.001). Multivariate regression analysis identified population as the sole predictor among all indicators analyzed (95% confidence interval (CI) = 1.154 to 1.469; P = 0.001). CONCLUSIONS: The distribution of reconstructive surgical aid by NGOs is guided most by population, but not other characteristics traditionally used to guide aid distribution. Greater coordination and data-sharing among NGOs is recommended to optimize outreach efforts.