Back

Application of chaos and systems theories to explore health workforce re-organization following district splitting in Uganda

Mutebi, A.; Mukuru, M.; Kiwanuka, S.; Makumbi, F.; RUTEBEMBERWA, E.

2024-08-30 health policy
10.1101/2024.08.29.24312785 medRxiv
Show abstract

BackgroundDistrict splitting (DS) began in 1962 and intensified in 1997 during implementation of decentralization. This legislative process focuses on geographical demarcation. The health system, organized along local government structures, was re-organized as a result of DS. However, this study explored how the health workforce, as a component of the local government health system, re-organized following district splitting. MethodsConducted between June and December 2018, the qualitative study involved 22 key informant interviews in eight districts, representing four broader regions (North, Western, Eastern and Central) of Uganda. Participants included district political leaders, local government staff, district service commission members, district health team officials, and district senior management. Data was collected using an interview guide and four themes were identified for deductive thematic analysis. ResultsFindings reveal that district splitting led to an involuntary division of the health system between old and new districts, triggering multidirectional reorganization of the health workforce. Health workers were systematically allocated to districts based on the geographical location of their health facilities during the splitting process. Subsequently, inter-district migration occurred through health workforce secondment or appointment, while intra-health system migration involved vertical movement of health workers within districts during recruitment. This reorganization resulted in workforce shortages in health facilities vacated by migrating health workers. ConclusionsThe study concludes that district splitting caused unintended consequences as a result of chaotic occurrences that led to reorganization of the health workforce in both new and old districts, and caused gaps in service delivery capabilities. Adopting a systems and chaos perspective, the study emphasizes the importance of considering frontline service delivery systems as subsystems of the overall district system when evaluating the impact of district splitting. Such an approach provides a comprehensive framework for understanding the disruptive effects of district splitting on health system organization and service delivery.

Matching journals

The top 2 journals account 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.