School of Medicine

Surgical conditions have been a largely neglected public health issue in low- and middle- income countries (LMICs). It is estimated that 11% of the global burden of disease can be treated surgically. While access maintains a barrier, more should be done to ensure quality surgical care. Developing a risk-adjustment tool to fairly measure surgical outcomes is one way in which we can begin to evaluate surgical quality. This requires that outcomes be adjusted based on the risk of the patient population. For example, a hospital with a high mortality rate but high-risk patients may provide better surgical care than a hospital with a similarly high mortality rate but low-risk patients. Our research seeks to develop a risk-adjustment tool by collecting 17 preoperative variables from surgical patients at a district hospital in Mozambique. We will then perform a statistical analysis to find <10 variables that are most predictive of mortality. This model can help establish a system to benchmark surgical outcomes in LMICs.