Webinar: Gender equity and health outcomes – beyond just “male” and “female”
July 1st, 2021 | event
On April 14, the USAID Country Health Information Systems and Data Use (CHISU) Project hosted the second webinar in their technical leadership series, Gender equity and health outcomes: experiences with and opportunities for gender integration in health information systems.
The panel examined gender inequities in health information systems (HIS) development and strengthening, sharing how data collection, analysis, and use all play an important role in gender integration in HIS.
Derek Kunaka, HIS Director, CHISU Project, JSI, moderated the webinar with panelists: Rajeev Colaço, Director of Monitoring, Evaluation, Research, Learning, and Adapting (MERLA) in RTI International Development Group, Roopa Dhatt, Executive Director, Women in Global Health, Mzikazi Nduna, Associate Professor, Department of Psychology for the School of Human and Community Development, University of the Witwatersrand, South Africa, and Preeti Negandhi, Lecturer from the Public Health Institute of India.
Gender considerations and sensitivities are an important lens to view our work, at all stages including design, implementation, evaluation, and learning. However, in practice, how often are we checking the box, quite literally, of male or female, reporting sex-disaggregated data, and allowing that to be the benchmark? Or how often are we inviting all relevant stakeholders to the table without carefully considering who is missing on the go-to roster?
In health information systems, if gender integration is associated with merely collecting and reporting male vs. female health care recipients, who and what other factors are we overlooking? The answer might be much more than we expect, and the consequences are drastic. While most HIV data are disaggregated by sex, some health data are not consistently disaggregated, and this is a first and foundational step for HIS gender integration. At the minimum, being able to examine health data and outcomes by sex differences will illuminate gaps and disparities that health programs can investigate and address.
The next step of moving from collecting sex disaggregated data to gender disaggregated data (data based on gender identity) has implications for health service delivery, policy, and research that can include and highlight disparities among groups of people who identify as transgender, nonconforming, nonbinary, or other marginalized identities. We must remember that decisions made about an HIS may symbolize larger and broader issues than limited health information data collection forms. Roopa states “health information systems are a product of their gendered political context and we know that there’s counting and collecting data, but there’s so much missing.”
Even once a country or data source moves from sex disaggregated data to gender disaggregated data, this doesn’t mean equity as been achieved. Mzikazi states “We take it for granted that gender inclusive health information systems is as easy as including the variable “gender” in all our data collection forms…and then once we’ve presented this information according to gender, then we’ve achieved gender inclusiveness.” But can we claim inclusiveness if we don’t expand our understanding and programming to consider who else could be excluded or overlooked and who is making the decisions?
Considering how we collect data is another factor in gender equity. We must choose and train our data collectors with a gender sensitive lens. It is important to understand how cultural and personal factors can help or hinder collection of gender and health data. Rajeev adds “Just including gender in a questionnaire is not going to give us the richness. Data collectors need to be sensitized and respondents need to be primed for asking and answering questions about gender identity.”
And as important as making sure we’re collecting the right data, is ensuring we are using the data in our work, and considering other intersectional equity factors including age, race/ethnicity, economic status, and others. Preeti encourages that we need a “culture of using the data, even if we get to the point where we’ve trained our HMIS [Health Management Information System] officials, but we’re not thinking beyond the basic analysis, we need to think a little bit outside of box, we need to cross-stratify with other factors.”
Finally, it is critical to think about who is making decisions about the HIS. HIS leadership and governance also plays a significant role in setting the tone of a gender-responsive HIS. Ensuring that gender considerations are regularly discussed in meetings, striving for parity in decision-making bodies, and including ministries, departments, or community-based organizations focused on gender equality will institutionalize gender as a key component in HIS strengthening, ultimately leading to improved health outcomes for all.
