The impact of socioeconomic status on emergency department outcome in a low-income country setting: A registry-based analysis.

Background: The impact of socioeconomic status on health has been established via a broad body of literature, largely from high-income countries. Investigative efforts in low- and middle-income countries have suffered from a lack of reporting standardization required to draw comparisons across countries of varying economic strata. In this study we aimed to evaluate the impact of socioeconomic status on emergency department outcomes in a low-income African country using international data classification systems.

Methods: This was a retrospective cohort study was conducted at a tertiary care center in northern Madagascar. Data were abstracted from paper charts into an electronic registry using Integrated Public Use Microdata Series codes for occupation, Nam-Powers-Boyd (NPB) scores for socioeconomic status, and Clinical Classifications Software ICD-9 equivalents for diagnosis. Outcome was dichotomized to the combined disposition of death or transfer directly to operating theater (OT) versus discharge. We used t-tests to compare baseline characteristics between these groups. We used chi-square analysis to test the association between occupational class and diagnosis. Finally, multivariate logistic regression analysis was performed examining the impact of NPB score on death/OT outcome, adjusting for age, gender, diagnosis and occupation.

Results: 5271 patients were seen during the 21-month study period with a death/OT rate of 9.7%. Older age and male gender were more common in death/OT patients (both p<0.001), and were shown to have positive odds ratios for this outcome in multivariate modeling (p<0.006 and <0.001). Occupational class was found to influence diagnosis for all classes (p<0.001) except Sales and Office. Adjusting for these 3 factors, we found a strong independent association between NPB quartile and death/OT outcome. Relative to the 1st quartile, the odds ratio in the 4th quartile was 2.9 (p = 0.004), the 3rd quartile 1.8 (p = 0.094), and the 2nd quartile 3.1 (p<0.001).

Conclusion: To our knowledge, this is the first Malagasy study describing the relationship between socioeconomic status on emergency care outcomes. We found a stronger effect on health in this setting than in high-income countries, highlighting an important healthcare disparity. By using standardized classification systems we hope this study will serve as a model to facilitate future comparative efforts.