Assessing intersectional gender analysis in Nepal’s health management information system: a case study on tuberculosis for inclusive health systems

Abstract

Background: Tuberculosis (TB) remains a major public health problem in Nepal, high in settings marked by prevalent gender and social inequities. Various social stratifiers intersect, either privileging or oppressing individuals based on their characteristics and contexts, thereby increasing risks, vulnerabilities and marganilisation associated with TB. This study aimed to assess the inclusiveness of gender and other social stratifiers in key health related national policies and the Health Management Information System (HMIS) of National Tuberculosis Programme (NTP) by conducting an intersectional analysis of TB cases recorded via HMIS. Methods: A desk review of key policies and the NTP’s HMIS was conducted. Retrospective intersectional analysis utilized two secondary data sources: annual NTP report (2017–2021) and records of 628 TB cases via HMIS 6.5 from two TB centres (2017/18–2018/19). Chi-square test and multi-variate analysis was used to assess the association between social stratifers and types of TB, registration category and treatment outcome. Results: Gender, social inclusion and concept of intersectionality are incorporated into various health policies and strategies but lack effective implementation. NTP has initiated the collection of age, sex, ethnicity and location data since 2014/15 through the HMIS. However, only age and sex disaggregated data are routinely reported, leaving recorded social stratifiers of TB patients static without analysis and dissemination. Furthermore, findings from the intersectional analysis using TB secondary data, showed that male more than 25 years exhibited higher odds [adjusted odds ratio (aOR) = 4.95, 95% confidence interval (CI): 1.60–19.06, P = 0.01)] of successful outcome compared to male TB patients less than 25 years. Similarly, sex was significantly associated with types of TB (P < 0.05) whereas both age (P < 0.05) and sex (P < 0.05) were significantly associated with patient registration category (old/new cases). Conclusions: The results highlight inadequacy in the availability of social stratifiers in the routine HMIS. This limitation hampers the NTP’s ability to conduct intersectional analyses, crucial for unveiling the roles of other social determinants of TB. Such limitation underscores the need for more disaggregated data in routine NTP to better inform policies and plans contributing to the development of a more responsive and equitable TB programme and effectively addressing disparities.