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Int. J. Environ. Res. Public Health 2017, 14(9), 1007; doi:10.3390/ijerph14091007

Combining Theory-Driven Evaluation and Causal Loop Diagramming for Opening the ‘Black Box’ of an Intervention in the Health Sector: A Case of Performance-Based Financing in Western Uganda

1
Institute of Development Policy and Management (IOB), University of Antwerp, Antwerp, 2000, Belgium
2
Department of Public Health, Institute of Tropical Medicine, Antwerp, 2000, Belgium
*
Author to whom correspondence should be addressed.
Academic Editor: Paul B. Tchounwou
Received: 15 July 2017 / Revised: 25 August 2017 / Accepted: 1 September 2017 / Published: 3 September 2017
(This article belongs to the Special Issue Health Systems and Services)
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Abstract

Increased attention on “complexity” in health systems evaluation has resulted in many different methodological responses. Theory-driven evaluations and systems thinking are two such responses that aim for better understanding of the mechanisms underlying given outcomes. Here, we studied the implementation of a performance-based financing intervention by the Belgian Technical Cooperation in Western Uganda to illustrate a methodological strategy of combining these two approaches. We utilized a systems dynamics tool called causal loop diagramming (CLD) to generate hypotheses feeding into a theory-driven evaluation. Semi-structured interviews were conducted with 30 health workers from two districts (Kasese and Kyenjojo) and with 16 key informants. After CLD, we identified three relevant hypotheses: “success to the successful”, “growth and underinvestment”, and “supervision conundrum”. The first hypothesis leads to increasing improvements in performance, as better performance leads to more incentives, which in turn leads to better performance. The latter two hypotheses point to potential bottlenecks. Thus, the proposed methodological strategy was a useful tool for identifying hypotheses that can inform a theory-driven evaluation. The hypotheses are represented in a comprehensible way while highlighting the underlying assumptions, and are more easily falsifiable than hypotheses identified without using CLD. View Full-Text
Keywords: complexity; performance-based financing; LMIC; Uganda; systems thinking; theory-driven evaluation; health systems; methodology; causal loop diagramming complexity; performance-based financing; LMIC; Uganda; systems thinking; theory-driven evaluation; health systems; methodology; causal loop diagramming
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Renmans, D.; Holvoet, N.; Criel, B. Combining Theory-Driven Evaluation and Causal Loop Diagramming for Opening the ‘Black Box’ of an Intervention in the Health Sector: A Case of Performance-Based Financing in Western Uganda. Int. J. Environ. Res. Public Health 2017, 14, 1007.

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