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Finagle’s laws of information: lessons learnt evaluating a complex health intervention in Nigeria
Evaluations cannot support evidence-informed decision making if they do not provide the information needed by decision-makers. In this article, we reflect on our own difficulties evaluating the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) approach, an intervention that...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10040038/ https://www.ncbi.nlm.nih.gov/pubmed/36963784 http://dx.doi.org/10.1136/bmjgh-2022-010938 |
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author | Alba, Sandra Taylor, Callum van Gurp, Margo Balogun, Paul |
author_facet | Alba, Sandra Taylor, Callum van Gurp, Margo Balogun, Paul |
author_sort | Alba, Sandra |
collection | PubMed |
description | Evaluations cannot support evidence-informed decision making if they do not provide the information needed by decision-makers. In this article, we reflect on our own difficulties evaluating the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) approach, an intervention that provides high-resolution demographic and geographical information to support health service delivery. GRID3 was implemented in Nigeria’s northern states to support polio (2012–2019) and measles immunisation campaigns (2017–2018). Generalising from our experience we argue that Finagle’s four laws of information capture a particular set of challenges when evaluating complex interventions: the weak causal claims derived from quasi-experimental studies and secondary analyses of existing data (the information we have is not what we want); the limited external validity of counterfactual impact evaluations (the information we want is not what we need); the absence of reliable monitoring data on implementation processes (the information we need is not what we can obtain) and the overly broad scope of evaluations attempting to generate both proof of concept and evidence for upscaling (the information we can obtain costs more than we want to pay). Evaluating complex interventions requires a careful selection of methods, thorough analyses and balanced judgements. Funders, evaluators and implementers share a joint responsibility for their success. |
format | Online Article Text |
id | pubmed-10040038 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-100400382023-03-27 Finagle’s laws of information: lessons learnt evaluating a complex health intervention in Nigeria Alba, Sandra Taylor, Callum van Gurp, Margo Balogun, Paul BMJ Glob Health Practice Evaluations cannot support evidence-informed decision making if they do not provide the information needed by decision-makers. In this article, we reflect on our own difficulties evaluating the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) approach, an intervention that provides high-resolution demographic and geographical information to support health service delivery. GRID3 was implemented in Nigeria’s northern states to support polio (2012–2019) and measles immunisation campaigns (2017–2018). Generalising from our experience we argue that Finagle’s four laws of information capture a particular set of challenges when evaluating complex interventions: the weak causal claims derived from quasi-experimental studies and secondary analyses of existing data (the information we have is not what we want); the limited external validity of counterfactual impact evaluations (the information we want is not what we need); the absence of reliable monitoring data on implementation processes (the information we need is not what we can obtain) and the overly broad scope of evaluations attempting to generate both proof of concept and evidence for upscaling (the information we can obtain costs more than we want to pay). Evaluating complex interventions requires a careful selection of methods, thorough analyses and balanced judgements. Funders, evaluators and implementers share a joint responsibility for their success. BMJ Publishing Group 2023-03-24 /pmc/articles/PMC10040038/ /pubmed/36963784 http://dx.doi.org/10.1136/bmjgh-2022-010938 Text en © Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY. Published by BMJ. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Practice Alba, Sandra Taylor, Callum van Gurp, Margo Balogun, Paul Finagle’s laws of information: lessons learnt evaluating a complex health intervention in Nigeria |
title | Finagle’s laws of information: lessons learnt evaluating a complex health intervention in Nigeria |
title_full | Finagle’s laws of information: lessons learnt evaluating a complex health intervention in Nigeria |
title_fullStr | Finagle’s laws of information: lessons learnt evaluating a complex health intervention in Nigeria |
title_full_unstemmed | Finagle’s laws of information: lessons learnt evaluating a complex health intervention in Nigeria |
title_short | Finagle’s laws of information: lessons learnt evaluating a complex health intervention in Nigeria |
title_sort | finagle’s laws of information: lessons learnt evaluating a complex health intervention in nigeria |
topic | Practice |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10040038/ https://www.ncbi.nlm.nih.gov/pubmed/36963784 http://dx.doi.org/10.1136/bmjgh-2022-010938 |
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