Evidence map›Paper›PMID 38659012›Full record

ArticleInfectious diseases of poverty2024

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

Ayuska Parajuli, Sampurna Kakchapati, Abriti Arjyal, Deepak Joshi, Chandani Kharel, Mariam Otmani Del Barrio, Sushil C Baral

Open access · goldAbstract read
In one paragraph

Article in Infectious diseases of poverty, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
2.2field-weighted citation impact, top 13% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 2 institutions in 2 countries.

Ayuska ParajuliHERD International, Saibu Awas Cr-10 Marga, Bhaisepati, Lalitpur, Nepal.
Sampurna KakchapatiHERD International, Saibu Awas Cr-10 Marga, Bhaisepati, Lalitpur, Nepal.
Abriti ArjyalHERD International, Saibu Awas Cr-10 Marga, Bhaisepati, Lalitpur, Nepal.
Deepak JoshiHERD International, Saibu Awas Cr-10 Marga, Bhaisepati, Lalitpur, Nepal.
Chandani KharelHERD International, Saibu Awas Cr-10 Marga, Bhaisepati, Lalitpur, Nepal.
Mariam Otmani Del BarrioUNICEF/UNDP/World Bank/WHO Special Programme for Research and Training in Tropical Diseases (TDR), World Health Organization, Geneva, Switzerland.
Sushil C BaralHERD International, Saibu Awas Cr-10 Marga, Bhaisepati, Lalitpur, Nepal. sushil@herdint.com.ORCID http://orcid.org/0000-0002-3425-6915
Nepal Development Research Institute · NPWorld Health Organization · CH

Funding

UNICEF/UNDP/World Bank/WHO Special Programme for Research and Training in Tropical Diseases (TDR), World Health Organization Reference 2019/980668-1World Health Organization 001
6 · The paper itself

Abstract

backgroundTuberculosis (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.

methodsA 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.

resultsGender, 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).

conclusionsThe 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.

Indexed as

TuberculosisAdolescentAdultAgedChildChild, PreschoolFemaleHealth Information SystemsHealth PolicyHumansInfantMaleManagement Information SystemsMiddle AgedNepalRetrospective StudiesGenderGender and social inequitiesHealth Management Information SystemIntersectional gender analysisNational Tuberculosis ProgrammeSocial determinantSocial inclusionTuberculosis

Identifiers

PMID38659012
PMCPMC11044533
OpenAlexW4395462743

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.