Linking world bank development indicators and outcomes of congenital heart surgery in low-income and middle-income countries: retrospective analysis of quality improvement data.

OBJECTIVE

Many low-income and middle-income countries (LMICs) struggle to provide the health services investment required for life-saving congenital heart disease (CHD) surgery. We explored associations between risk-adjusted CHD surgical mortality from 17 LMICs and global development indices to identify patterns that might inform investment strategies.

DESIGN

Retrospective analysis: country-specific standardised mortality ratios were graphed against global development indices reflective of wealth and healthcare investment. Spearman correlation coefficients were calculated.

SETTING AND

PARTICIPANTS

The International Quality Improvement Collaborative (IQIC) keeps a volunteer registry of outcomes of CHD surgery programmes in low-resource settings. Inclusion in the IQIC is voluntary enrolment by hospital sites. Patients in the registry underwent congenital heart surgery. Sites that actively participated in IQIC in 2013, 2014 or 2015 and passed a 10% data audit were asked for permission to share data for this study. 31 sites in 17 countries are included.

OUTCOME MEASURES: In-hospital mortality: standardised mortality ratios were calculated. Risk adjustment for in-hospital mortality uses the Risk Adjustment for Congenital Heart Surgery method, a model including surgical risk category, age group, prematurity, presence of a major non-cardiac structural anomaly and multiple congenital heart procedures during admission.

RESULTS

The IQIC registry includes 24 917 congenital heart surgeries performed in children<18 years of age. The overall in-hospital mortality rate was 5.0%. Country-level congenital heart surgery standardised mortality ratios were negatively correlated with gross domestic product (GDP) per capita (r=-0.34, p=0.18), and health expenditure per capita (r=-0.23, p=0.37) and positively correlated with under-five mortality (r=0.60, p=0.01) and undernourishment (r=0.39, p=0.17). Countries with lower development had wider variation in mortality. GDP per capita is a driver of the association between some other measures and mortality.

CONCLUSIONS

Results display a moderate relationship among wealth, healthcare investment and malnutrition, with significant variation, including superior results in many countries with low GDP per capita. These findings provide context and optimism for investment in CHD procedures in low-resource settings.