Pediatric surgical quality improvement in low- and middle-income countries: What data to collect?

Abstract

Background: As surgical access expands in low- and middle-income countries, risk-adjusted outcomes data are needed to measure and improve surgical quality. Existing data collection tools in high-income countries are complex and may be burdensome to implement in low and middle income countries. This study determined the minimum dataset needed for adequate risk adjustment to predict perioperative mortality using data collected in a low- and middle-income countries.

Methods: All patients admitted to the pediatric surgery ward at Mulago National Referral Hospital in Kampala, Uganda, from January 1, 2014 through December 31, 2018 were included. Studies were performed modelling the effects of reducing data granularity and reducing number of variables on the area under the receiver operating curve.

Results: Of the 3,194 patients included, 1,941(61%) were male, 957(30%) were neonates, 1,714 (54%) had an operation, and the overall mortality rate was 14%. Granularity reduction analyses found that measuring age in ranges was equivalent to recording age in days (area under the receiver operating curve = 0.776; 95% confidence interval, 0.754%-0.798%, vs 0.815, 95% confidence interval, 0.794%-0.837%). Variable reduction analyses found that models with 3 predictor variables (diagnosis, procedure, and district) reached a maximum area under the receiver operating curve of 0.915 (95% confidence interval, 0.903%-0.928%), which was equivalent to the model using all available predictor variables (area under the receiver operating curve = 0.932; 95% confidence interval, 0.922%-0.943%). For all 3-variable models, the primary diagnosis contributed most to predictive ability (P < .001).

Conclusion: Effective risk adjustment for perioperative mortality can be performed in low and middle income countries using minimal, objective variables often already part of the patient's medical record. This approach can be used by clinicians, hospital administrators, and policymakers low- and middle-income countries looking to begin data collection to track and improve patient outcomes.