Trina Stephens1, Alexander Mezei2, Nathan N O'Hara3, Jeffrey Potter4, Rodney Mugarura5, Piotr A Blachut6, Peter J O'Brien6, Tito Beyeza5, Gerard P Slobogean7. 1. School of Medicine, Queen's University, 99 University Ave, Kingston, ON, K7L 3N6, Canada. 2. Faculty of Medicine, University of British Columbia, 317 - 2194 Health Sciences Mall, Vancouver, BC, V6T 1Z3, Canada. 3. Department of Orthopaedics, University of Maryland School of Medicine, 110 South Paca St., Baltimore, MD, 21201, USA. 4. Division of Orthopaedic Surgery, Queen's University, 76 Stuart St., Kingston, ON, L7L 2V7, Canada. 5. Department of Orthopaedics, Makerere University, PO Box 7051, Kampala, Uganda. 6. Department of Orthopaedics, University of British Columbia, 3114 - 910 West 10th Ave, Vancouver, BC, V5Z 1M9, Canada. 7. Department of Orthopaedics, University of Maryland School of Medicine, 110 South Paca St., Baltimore, MD, 21201, USA. gslobogean@umoa.umm.edu.
Abstract
BACKGROUND: In low- and middle-income countries, the volume of traumatic injuries requiring orthopaedic intervention routinely exceeds the capacity of available surgical resources. The objective of this study was to identify predictors of surgical care for lower extremity fracture patients at a high-demand, resource-limited public hospital in Uganda. METHODS: Skeletally mature patients admitted with the intention of definitive surgical treatment of an isolated tibia or femur fractures to the national referral hospital in Uganda were recruited to participate in this study. Demographic, socioeconomic, and clinical data were collected through participant interviews at the time of injury and 6 months post-injury. Social capital (use of social networks to gain access to surgery), financial leveraging, and ethnicity were also included as variables in this analysis. A probit estimation model was used to identify independent and interactive predictors of surgical treatment. RESULTS: Of the 64 patients included in the final analysis, the majority of participants were male (83%), with a mean age of 40.6, and were injured in a motor vehicle accident (77%). Due to resource constraints, only 58% of participants received surgical care. The use of social capital and femur fractures were identified as significant predictors of receiving surgical treatment, with social capital emerging as the strongest predictor of access to surgery (p < 0.05). CONCLUSION: Limited infrastructure, trained personnel, and surgical supplies rations access to surgical care. In this environment, participants with advantageous social connections were able to self-advocate for surgery where demand for these services greatly exceeded available resources.
BACKGROUND: In low- and middle-income countries, the volume of traumatic injuries requiring orthopaedic intervention routinely exceeds the capacity of available surgical resources. The objective of this study was to identify predictors of surgical care for lower extremity fracturepatients at a high-demand, resource-limited public hospital in Uganda. METHODS: Skeletally mature patients admitted with the intention of definitive surgical treatment of an isolated tibia or femur fractures to the national referral hospital in Uganda were recruited to participate in this study. Demographic, socioeconomic, and clinical data were collected through participant interviews at the time of injury and 6 months post-injury. Social capital (use of social networks to gain access to surgery), financial leveraging, and ethnicity were also included as variables in this analysis. A probit estimation model was used to identify independent and interactive predictors of surgical treatment. RESULTS: Of the 64 patients included in the final analysis, the majority of participants were male (83%), with a mean age of 40.6, and were injured in a motor vehicle accident (77%). Due to resource constraints, only 58% of participants received surgical care. The use of social capital and femur fractures were identified as significant predictors of receiving surgical treatment, with social capital emerging as the strongest predictor of access to surgery (p < 0.05). CONCLUSION: Limited infrastructure, trained personnel, and surgical supplies rations access to surgical care. In this environment, participants with advantageous social connections were able to self-advocate for surgery where demand for these services greatly exceeded available resources.
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