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

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(a OR)=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.

Construction of HMI Network System for Individualized Maternity Intervention Service against Birth Defects in Community

The paper expounds the community maternity service system against birth defects, from the viewpoint of individualized service in family planning. We have utilized modern information technology to develop health management information （HMI） network with individualized maternity, and to establish the community service system for intervention of birth dejects. The service system applied the concept of modern health management information to implementing informational management for screening, treatment, following up, outcome monitoring, so as to provide a base for promotion of health, diagnosis, treatment as well as scientific research, with the prenatal screening of Down＇s syndrome as a model. The introduction to informational network during the processes of service has been carried out with regards to its composition, function and application, while introducing the effects of computerized case record individualized in prevention, management and research of Down＇s syndrome.

Evaluation of malaria surveillance system in Kano State,Nigeria,2013–2016

Background:Malaria surveillance system strengthening is essential in the progress towards malaria elimination.In Nigeria,more attention is being given to this recently as the country is striving towards achieving elimination.However,the surveillance system performance is fraught with challenges including poor data quality with varying magnitude by state.This study evaluated the operation of the Kano State malaria surveillance system and assessed its key attributes.Methods:An observational study design comprising a survey,record review and secondary data analysis,and mixed methods data collection approach were used.Four key stakeholders’and 35 Roll Back Malaria Focal Persons(RBMs)semi-structured interviews on operation of the system and attributes of the surveillance system,were conducted.We analyzed the abstracted 2013–2016 National Health Management Information System web-based malaria datasets.The surveillance system was evaluated using the“2001 United States Centers for Disease Control’s updated guidelines for Evaluating Public Health Surveillance Systems”.Data were described using means,standard deviation,frequencies and proportions.Chi-squared for linear trends was used.Results:Overall,24 RBMs(68.6%)had≤15-year experience on malaria surveillance,29(82.9%)had formal training on malaria surveillance;32 RBMs(91.4%)reported case definitions were easy-to-use,reporting forms were easy-to-fill and data flow channels were clearly defined.Twenty-seven respondents(69.2%)reported data tools could accommodate changes and all RBMs understood malaria case definitions.All respondents(4 stakeholders and 34 RBMs[97.1%])expressed willingness to continue using the system and 33(84.6%)reported analyzed data were used for decision-making.Public health facilities constituted the main data source.Overall,65.0%of funding were from partner agencies.Trend of malaria cases showed significant decline(χ2 trend=7.49;P=0.0006).Timeliness of reporting was below the target(≥80%),except being 82%in 2012.Conclusions:Malaria surveillance system in Kano State was simple,flexible,acceptable,useful and donor-driven but the data were not representative of all health facilities.Timeliness of reporting was suboptimal.We recommended reporting from private health facilities,strengthening human resource capacity for supportive supervision and ensuring adequate government funding to enhance the system’s representativeness and improve data quality.