Back

The relationship between payer type and quality of care for women undergoing emergency cesarean section at three hospitals in rural Uganda.

Mwiindi, J.; Delgado, R.; Revere, L.; Wangigi, B.; Muguthu, E.; Busingye, P.

2024-03-18 obstetrics and gynecology
10.1101/2024.03.17.24304434 medRxiv
Show abstract

BackgroundThe study examined the relationship between payer type, and quality of care among mothers who deliver through emergency cesarean section in rural Ugandan hospitals. MethodsWe analyzed retrospective, de-identified patient data from three rural private-not-for-profit hospitals in Uganda. Two groups were included in the study, a self-payer patient group and a group fully sponsored by an international funding organization. The data was analyzed using hierarchical linear regression models comparing length of stay against payer type, and controlling for patient age, education level, parity, and indication for C-section. Length of stay (LOS) was assumed to represent a realistic proxy variable for patient quality of care. ResultsThe self-pay group had statistically significant longer postoperative LOS (surgery to clinical discharge), and longer aggregate LOS, or admission to clinical discharge, compared to the sponsored group. Payer type was not significant in the admission-to-decision LOS, but payer type was highly significant for aggregate LOS (p < .001). ConclusionCase management in rural Ugandan hospitals influences quality of post-operative care for patients undergoing emergency C-sections. Expanding surgical funding, combined with effective case management approaches, is likely to increase quality of surgical care as measured by length of stay. Synopsis: Post-operative quality of care for emergency C-section cases, measured by length of stay in Ugandan rural hospitals, is impacted by case management.

Matching journals

The top 1 journal accounts for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.