Global Neurosurgery: A Retrospective Cohort Study to Compare the Effectiveness of Two Training Methods in Resource-Poor Settings

Document Type

Article

Abstract

BACKGROUND AND OBJECTIVES: Many low- and middle-income countries are experiencing profound health care workforce shortages. Surgical subspecialists generally practice in large urban centers but are in high demand in rural areas. These subspecialists must be trained through sustainable programs to address this disparity. We quantitatively compared the relative effectiveness of 2 unique training models to advance neurosurgical skills in resource-poor settings where formally trained neurosurgeons are unavailable. METHODS: Neurosurgical procedure data were collected from 2 hospitals in Tanzania (Haydom Lutheran Hospital [HLH] and Bugando Medical Centre [BMC]), where 2 distinct training models ("Train Forward" and "Back-to-Back," respectively) were incorporated between 2005 and 2012. RESULTS: The most common procedures performed were ventriculoperitoneal shunt (BMC: 559, HLH: 72), spina bifida repair (BMC: 187, HLH: 54), craniotomy (BMC: 61, HLH: 19), bone elevation (BMC: 42, HLH: 32), and craniotomy and evacuation (BMC: 18, HLH: 34). The number of annual procedures at BMC increased from 148 in 2008 to 357 in 2012; at HLH, they increased from 18 in 2005 to 80 in 2010. Postoperative complications over time decreased or did not significantly change at both sites as the diversity of procedures increased. CONCLUSION: The Train Forward and Back-to-Back training models were associated with increased surgical volume and complexity without increased complications. However, only the Train Forward model resulted in local, autonomous training of surgical subspecialists after completion of the initial training period. Incorporating the Train Forward method into existing training programs in low- and middle-income countries may provide unique benefits over historic training practices.

Publication Date

9-4-2023

Publication Title

Neurosurgery

E-ISSN

1524-4040

PubMed ID

37665218

Digital Object Identifier (DOI)

10.1227/neu.0000000000002652

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