Advancing the application of systems thinking in health: exploring dual practice and its management in Kampala, Uganda
Bibliographic record
Abstract
BACKGROUND: Many full-time Ugandan government health providers take on additional jobs - a phenomenon called dual practice. We describe the complex patterns that characterize the evolution of dual practice in Uganda, and the local management practices that emerged in response, in five government facilities. An in-depth understanding of dual practice can contribute to policy discussions on improving public sector performance. METHODS: A multiple case study design with embedded units of analysis was supplemented by interviews with policy stakeholders and a review of historical and policy documents. Five facility case studies captured the perspective of doctors, nurses, and health managers through semi-structured in-depth interviews. A causal loop diagram illustrated interactions and feedback between old and new actors, as well as emerging roles and relationships. RESULTS: The causal loop diagram illustrated how feedback related to dual practice policy developed in Uganda. As opportunities for dual practice grew and the public health system declined over time, government providers increasingly coped through dual practice. Over time, government restrictions to dual practice triggered policy resistance and protest from government providers. Resulting feedback contributed to compromising the supply of government providers and, potentially, of service delivery outcomes. Informal government policies and restrictions replaced the formal restrictions identified in the early phases. In some instances, government health managers, particularly those in hospitals, developed their own practices to cope with dual practice and to maintain public sector performance. Management practices varied according to the health manager's attitude towards dual practice and personal experience with dual practice. These practices were distinct in hospitals. Hospitals faced challenges managing internal dual practice opportunities, such as those created by externally-funded research projects based within the hospital. Private wings' inefficiencies and strict fee schedule made them undesirable work locations for providers. CONCLUSIONS: Dual practice prevails because public and private sector incentives, non-financial and financial, are complementary. Local management practices for dual practice have not been previously documented and provide learning opportunities to inform policy discussions. Understanding how dual practice evolves and how it is managed locally is essential for health workforce policy, planning, and performance discussions in Uganda and similar settings.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.010 | 0.022 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".