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Chapters 4 and 5 described the problems with the treatment received by febrile patients attending health facilities and medicine retail outlets in Nigeria and Cameroon. This research paper sets out to explore why, and reports on providers’ knowledge of the national malaria treatment guidelines and the determinants of providers’ stated

preference for treating uncomplicated malaria. The findings from this paper were used to select and design interventions to improve the diagnosis and treatment of uncomplicated malaria.

A primary motivation for this analysis was to assess whether an intervention targeting providers’ knowledge would be effective, or whether additional effort would be needed to ensure providers’ preference over alternative antimalarials was aligned to the national guidelines. The paper focuses on providers’ stated preference, since their revealed preference (i.e. their practice) may be constrained by the resources and information available. The analysis is underpinned by agency theory, and recognises that providers are not only agents for their patients, but may also act on behalf of other health sector actors, such as their employer, the Ministry of Health and pharmaceutical suppliers.

Providers’ stated preference was elicited by asking each provider “which antimalarial do you think is the best for treating patients with uncomplicated malaria?”. The brand and generic names stated were subsequently coded and the analysis was undertaken using a binary outcome: whether or not the provider had stated an ACT. As discussed in the paper, there is some uncertainty in how providers understood the question used and we

161 was administered and no problems were reported. However, this particular question was not given specific attention in the piloting since this analysis was not planned a priori and the provider questionnaire contained more than a hundred questions.

The econometric analysis uses a discrete choice model based on random utility theory [1-2]. Although utility cannot be directly observed, individuals are assumed to be economically rational and make choices that maximize their utility. In this application I examine whether providers prefer an ACT and use an multilevel logit regression to assess the extent to which providers’ stated preference depends on financial and non-financial incentives, subject to information they have available on different antimalarials and the underlying institutional environment.

The analysis uses pooled data from provider surveys conducted at different types of facility in Cameroon and Nigeria. This resulted in a heterogeneous study population and the opportunity to explore the extent to which providers’ preference reflected their institutional and social context. It was straightforward to merge the data from the two countries since a standardized questionnaire had been used. Using pooled data also increased the sample size, which was restricted because the provider survey was part of a larger study that had been designed to examine the treatment supplied to febrile patients. As pooled data were used, country-specific effects were examined in the multilevel

analysis. This included an explanatory variable for the country, and interactions to

investigate whether any of the provider, facility and area attributes had a country-specific effect. Interactions were added to the random-intercept model one at a time and their statistical significance was assessed using the Wald test and the likelihood ratio test at a 10% level of significance. As noted in the paper, model specification was assessed using various methods, and none of the interactions were found to significantly improve the fit of the model.

162 patients, drug company representatives, and other providers who work at the same

facility or in the same locality. The findings also contributed to a theory-based approach to intervention design. Based on these findings, the enhanced training incorporated

interactive small-group work and sessions on communicating with patients. In addition, the enhanced training was intended to build consensus within a facility and all providers attending the training workshops were encouraged to hold training and share what they had learnt with their colleagues.

References:

1. McFadden D (1981). Econometric models for probabilistic choice. In Manski C, McFadden D eds. Structural analysis of discrete data with econometric

applications. Cambridge: MIT Press.

2. McFadden D, (2001) Economic choices. The American Economic Review 91(3): 351-378.

Authors: Lindsay Mangham-Jefferies(1)_{, Kara Hanson}(1)_{, Wilfred Mbacham}(2)_{, Obinna} Onwujekwe(3)

(1) Department of Global Health and Development, Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, 15-17 Tavistock Place, London, WC1H 9SH, UK

(2) Laboratory for Public Health Research Biotechnologies, University of Yaoundé 1, Nkolbisson, Yaoundé, Cameroon

(3) Department of Health Administration and Management, College of Medicine, University of Nigeria (Enugu Campus), Old UNTH Road, 40001, Enugu, Nigeria

163 paper was peer-reviewed.

Copyright: The authors retained copyright. The article is open access and distributed under the terms of the Creative Commons Attribution-NonCommericial- ShareAlike License.

Contribution: I was the lead author and responsible for the conception, analysis and preparation of the manuscript. Co-authors commented on a full draft of the research paper, and read and approved the final draft.

164

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1.2 When was the work published? January 2014

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NAME IN FULL (Block Capitals) LINDSAY JEAN MANGHAM JEFFERIES

STUDENT ID NO 244504

CANDIDATE’S SIGNATURE DATE 5 May, 2014

SUPERVISOR / SENIOR AUTHOR’S SIGNATURE