Scoring tools to identify TB patients facing catastrophic costs in the Philippines.

Abstract

Background: This study was to meet a practical need to design a simple tool to identify TB patients who may potentially be facing catastrophic costs while seeking TB care in the public sector. Such a tool may help prevent and address catastrophic costs among individual patients.

Methods: We used data from the national TB patient cost survey in the Philippines. We randomly allocated TB patients to either the derivation or validation sample. Using adjusted odds ratios (ORs) and β coefficients of logistic regression, we developed four scoring systems to identify TB patients who may be facing catastrophic costs from the derivation sample. We validated each scoring system in the validation sample.

Results: We identified a total of 12 factors as predictive indicators associated with catastrophic costs. Using all 12 factors, the β coefficients-based scoring system (area under the curve [AUC] 0.783, 95% CI 0.754-0.812) had a high validity. Even with seven selected factors with OR > 2.0, the validity remained in the acceptable range (β coefficients-based: AUC 0.767, 95% CI 0.737-0.798).

Conclusion: The β coefficients-based scoring systems in this analysis can be used to identify those at high risk of facing catastrophic costs due to TB in the Philippines. Operational feasibility needs to be investigated further to implement this in routine TB surveillance.