My area of interest is the experience of obstetric care, specifically the mistreatment of women in health facilities. It is not terribly useful to get national prevalence estimates of mistreatment, as the rates and types of mistreatment tend to vary by health facility. Obstetric practice patters also tend to vary greatly from hospital to hospital. So, in order to determine facility prevalence of different types of mistreatment I would use a cluster sampling method by dividing the geographic area into sensible units (for instance, by hospital catchment area), and then sample 100 women from each hospital prior to discharge. I would vary the day of data collection randomly, as practice patterns can vary significantly depending on day/night shift and weekend.
Logistically, this approach would be much easier than trying to determine the national sampling frame of women who have recently given birth; these women are more easily accessed at the hospital level. A disadvantage is that women may not want to answer sensitive questions about their care prior to hospital discharge, or it may take time to reflect on the experience in order to develop opinions about the quality of care. For this reason, women could be contacted in 6 months time to see how their opinions have changed. Also, ideally research staff would observe care on labor unit to compare rates of observed mistreatment to reported mistreatment.
Incorporating a sampling strategy that varies by time of day would greatly reduce (though not eliminate) bias of univariate quantities (such as, prevalence of mistreatment).
However, in terms of causal effects several issues arise. For instance, if we wanted to ask this question: Do higher levels of mistreatment predict postpartum mental health problems? I think there would need to be some combination of rates of mistreatment gathered by observers and reported by women. For instance, there may be unmeasured selection bias in that women who accept a certain level of care (however low that standard may be) may select to go to the same hospital. Or more likely, women who seek a higher standard of care select to go to hospitals with higher quality care (ideally also lower rates of mistreatment). Also, women may interpret even bad experiences in a positive light after the baby is born. Thus, the better sampling strategy would occur prenatally (rather than at hospital discharge), so women’s preferences and expectations can be measured prior to delivery and rates of mistreatment could be followed over time.