Methods to estimate access to care and the effect of interventions on the outcomes of congenital disorders

Congenital Disorders Expert Group; Hannah Blencowe; Sowmiya Moorthie; Matthew W. Darlison; Stephen Gibbons; Bernadette Modell

doi:10.1007/s12687-018-0359-3

Methods to estimate access to care and the effect of interventions on the outcomes of congenital disorders

Congenital Disorders Expert Group, Hannah Blencowe, Sowmiya Moorthie, Matthew W. Darlison (Lead / Corresponding author), Stephen Gibbons, Bernadette Modell

Dentistry

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Abstract

In the absence of intervention, early-onset congenital disorders lead to pregnancy loss, early death, or disability. Currently, lack of epidemiological data from many settings limits the understanding of the burden of these conditions, thus impeding health planning, policy-making, and commensurate resource allocation. The Modell Global Database of Congenital Disorders (MGDb) seeks to meet this need by combining general biological principles with observational and demographic data, to generate estimates of the burden of congenital disorders. A range of interventions along the life course can modify adverse outcomes associated with congenital disorders. Hence, access to and quality of services available for the prevention and care of congenital disorders affects both their birth prevalence and the outcomes for affected individuals. Information on this is therefore important to enable burden estimates for settings with limited observational data, but is lacking from many settings. This paper, the third in this special issue on methods used in the MGDb for estimating the global burden of congenital disorders, describes key interventions that impact on outcomes of congenital disorders and methods used to estimate their coverage where empirical data are not available.

Original language	English
Pages (from-to)	363-376
Number of pages	14
Journal	Journal of Community Genetics
Volume	9
Issue number	4
Early online date	17 Mar 2018
DOIs	https://doi.org/10.1007/s12687-018-0359-3
Publication status	Published - Oct 2018

Keywords

Access to care
Congenital malformations
Estimation
Interventions
Pregnancy outcomes

ASJC Scopus subject areas

Epidemiology
Public Health, Environmental and Occupational Health
Genetics(clinical)

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1007/s12687-018-0359-3Licence: CC BY

Final published version
© The Author(s) 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http:// creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Final published version, 1.89 MBLicence: CC BY

Cite this

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title = "Methods to estimate access to care and the effect of interventions on the outcomes of congenital disorders",

abstract = "In the absence of intervention, early-onset congenital disorders lead to pregnancy loss, early death, or disability. Currently, lack of epidemiological data from many settings limits the understanding of the burden of these conditions, thus impeding health planning, policy-making, and commensurate resource allocation. The Modell Global Database of Congenital Disorders (MGDb) seeks to meet this need by combining general biological principles with observational and demographic data, to generate estimates of the burden of congenital disorders. A range of interventions along the life course can modify adverse outcomes associated with congenital disorders. Hence, access to and quality of services available for the prevention and care of congenital disorders affects both their birth prevalence and the outcomes for affected individuals. Information on this is therefore important to enable burden estimates for settings with limited observational data, but is lacking from many settings. This paper, the third in this special issue on methods used in the MGDb for estimating the global burden of congenital disorders, describes key interventions that impact on outcomes of congenital disorders and methods used to estimate their coverage where empirical data are not available.",

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AU - Blencowe, H.

AU - Christianson, A.

AU - Cousens, S.

AU - Darlison, M.

AU - Gibbons, S.

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AU - Howson, C. P.

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AU - Povey, S.

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AB - In the absence of intervention, early-onset congenital disorders lead to pregnancy loss, early death, or disability. Currently, lack of epidemiological data from many settings limits the understanding of the burden of these conditions, thus impeding health planning, policy-making, and commensurate resource allocation. The Modell Global Database of Congenital Disorders (MGDb) seeks to meet this need by combining general biological principles with observational and demographic data, to generate estimates of the burden of congenital disorders. A range of interventions along the life course can modify adverse outcomes associated with congenital disorders. Hence, access to and quality of services available for the prevention and care of congenital disorders affects both their birth prevalence and the outcomes for affected individuals. Information on this is therefore important to enable burden estimates for settings with limited observational data, but is lacking from many settings. This paper, the third in this special issue on methods used in the MGDb for estimating the global burden of congenital disorders, describes key interventions that impact on outcomes of congenital disorders and methods used to estimate their coverage where empirical data are not available.

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Methods to estimate access to care and the effect of interventions on the outcomes of congenital disorders

Abstract

Keywords

ASJC Scopus subject areas

UN SDGs

Access to Document

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Mossey, Peter

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Methods to estimate access to care and the effect of interventions on the outcomes of congenital disorders

Abstract

Keywords

ASJC Scopus subject areas

UN SDGs

Access to Document

Other files and links

Fingerprint

Profiles

Mossey, Peter

Cite this