Examining intersectoral integration for malaria control programmes in an urban and a rural district in Ghana: a multinomial multilevel analysis
Examining intersectoral integration for malaria control programmes in an urban and a rural district in Ghana: a multinomial multilevel analysis
Background: Intersectoral integration is acknowledged to be essential for improving provision of health care and outcomes, yet it remains one of the main primary health care strategic challenges. Although this is well articulated in the literature, the factors that explain differentials in levels of intersectoral integration have not been systematically studied, particularly in low and middle-income countries. In this study, we examine the levels and determinants of intersectoral integration amongst institutions engaged in malaria control programmes in an urban (Kumasi Metropolitan) district and a rural (Ahafo Ano South) district in Ghana.
Methods: Interviews were conducted with representatives of 32 institutions engaged in promoting malaria prevention and control. The averaging technique proposed by Brown et al. and a two-level multinomial multilevel ordinal logistic regression were used to examine the levels of integration and the factors that explain the differentials.
Results: The results show high disparity in levels of integration amongst institutions in the two districts. Integration was higher in the rural district compared to the urban district. The multivariate analysis revealed that the district effect explained 25% of the variations in integration. The type of institution, level of focus on malaria and source of funding are important predictors of intersectoral integration.
Conclusion: Although not causal, integrated malaria control programmes could be important for improving malaria-related health outcomes in less developed regions as evident from the rapid decline in malaria fatality rates observed in the Ahafo Ano South district. Harmonisation of programmes should be encouraged amongst institutions and the public and private sectors should be motivated to work in partnership.
intersectoral integration, intersectoral collaboration, malaria control programmes, multilevel multinomial ordinal regression
1-10
Owusu, N.O.
7f81c1bf-1fdd-422d-846d-87b8e67b7f73
Baffour-Awuah, B.
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Amoako Johnson, F.
e348fd15-9fe2-472f-a701-2980b8cec4d5
Mohan, J.
01d0f96b-aee7-4f4d-ad3f-e177231005f6
Madise, N.J.
2ea2fbcc-50da-4696-a0a5-2fe01db63d8c
7 August 2013
Owusu, N.O.
7f81c1bf-1fdd-422d-846d-87b8e67b7f73
Baffour-Awuah, B.
ea26c08c-46a3-43e1-826f-f9d1d92aab22
Amoako Johnson, F.
e348fd15-9fe2-472f-a701-2980b8cec4d5
Mohan, J.
01d0f96b-aee7-4f4d-ad3f-e177231005f6
Madise, N.J.
2ea2fbcc-50da-4696-a0a5-2fe01db63d8c
Owusu, N.O., Baffour-Awuah, B., Amoako Johnson, F., Mohan, J. and Madise, N.J.
(2013)
Examining intersectoral integration for malaria control programmes in an urban and a rural district in Ghana: a multinomial multilevel analysis.
International Journal of Integrated Care, 13, .
Abstract
Background: Intersectoral integration is acknowledged to be essential for improving provision of health care and outcomes, yet it remains one of the main primary health care strategic challenges. Although this is well articulated in the literature, the factors that explain differentials in levels of intersectoral integration have not been systematically studied, particularly in low and middle-income countries. In this study, we examine the levels and determinants of intersectoral integration amongst institutions engaged in malaria control programmes in an urban (Kumasi Metropolitan) district and a rural (Ahafo Ano South) district in Ghana.
Methods: Interviews were conducted with representatives of 32 institutions engaged in promoting malaria prevention and control. The averaging technique proposed by Brown et al. and a two-level multinomial multilevel ordinal logistic regression were used to examine the levels of integration and the factors that explain the differentials.
Results: The results show high disparity in levels of integration amongst institutions in the two districts. Integration was higher in the rural district compared to the urban district. The multivariate analysis revealed that the district effect explained 25% of the variations in integration. The type of institution, level of focus on malaria and source of funding are important predictors of intersectoral integration.
Conclusion: Although not causal, integrated malaria control programmes could be important for improving malaria-related health outcomes in less developed regions as evident from the rapid decline in malaria fatality rates observed in the Ahafo Ano South district. Harmonisation of programmes should be encouraged amongst institutions and the public and private sectors should be motivated to work in partnership.
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Published date: 7 August 2013
Keywords:
intersectoral integration, intersectoral collaboration, malaria control programmes, multilevel multinomial ordinal regression
Organisations:
Social Statistics & Demography
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Local EPrints ID: 357455
URI: http://eprints.soton.ac.uk/id/eprint/357455
PURE UUID: d02e8424-5eb3-40ce-8ad3-c29d545ef4eb
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Date deposited: 08 Oct 2013 08:50
Last modified: 22 Jul 2022 18:45
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Contributors
Author:
N.O. Owusu
Author:
B. Baffour-Awuah
Author:
F. Amoako Johnson
Author:
J. Mohan
Author:
N.J. Madise
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