Use human resources information systems (HRIS), and special studies to analyze sex-disaggregated data about health professional students, faculty, and health workers. Analyze the data to assess whether pregnancy and family responsibilities discrimination may be a problem in your context.

Suggested data analyses

• Gender distribution of medical specialists vs. generalists

Consider the case of generalist vs. specialist doctors in Kenya: four in ten generalists are female, but only two in ten specialists are female. This sex-disaggregated analysis indicates that there are differences in the proportion of women vs. men who succeed in specializing, which requires additional training.

 

What could be the reasons for these differences?

 Becoming a specialist usually requires additional years of training. Could it be that health professionals who take time for pregnancy or family responsibilities may be excluded from these training opportunities due to inflexible schedules or perceptions about their priorities?

This sex-disaggregated data analysis could be interpreted to indicate that there may be unequal opportunities for female medical practitioners to specialize, hindrances including the burden of caregiving or challenges to travel for long periods of time.

• Gender distribution of in-service training participants

Health workers who have family responsibilities may not be able to travel long distances and/or for extended periods of time, limiting the in-service trainings they can attend. Family responsibilities typically affect female workers. Female health workers therefore may be underrepresented in in-service training and may have fewer opportunities to upgrade their knowledge and skills.

• Average years to promotion, by sex

Typical health professional and faculty career paths do not allow for time out for pregnancy, or time off for family responsibilities, without career penalties. This can negatively affect women, who are more frequently expected to assume childcare responsibility and take time off than men. In the sex-disaggregated data analysis from Kenya in the figure below, female nurses/midwives worked for an average of 14.6 years before getting a promotion, while their male counterparts worked for an average of 12.7 years before promotion; this difference of almost two years indicates unequal opportunities.

• Special studies and qualitative approaches

Pregnancy and family responsibilities discrimination may be present in education, hiring, training, and promotion processes. However, standard workforce statistics and reports may not reveal this form of discrimination. Use multiple methods to understand the gender trends and underlying dynamics in the workforce. Collect qualitative and quantitative sex-disaggregated data through targeted interviews, focus group discussions, and surveys on the following to reveal how pregnancy and family responsibilities discrimination may be affecting health workers:

• Accommodation: Do regulations allow married women to access housing or housing loans?
• What is the proximity of the health worker posts in relation to their families?
• Are female and male health workers equally distributed at rural/hardship posts?
• Does a health worker’s marital status or number of children affect his/her uptake or retention at a job posting?