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A comparison of four quasi-experimental methods: an analysis of the introduction of activity-based funding in Ireland
BACKGROUND: Health services research often relies on quasi-experimental study designs in the estimation of treatment effects of a policy change or an intervention. The aim of this study is to compare some of the commonly used non-experimental methods in estimating intervention effects, and to highli...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9635092/ https://www.ncbi.nlm.nih.gov/pubmed/36329423 http://dx.doi.org/10.1186/s12913-022-08657-0 |
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author | Valentelyte, Gintare Keegan, Conor Sorensen, Jan |
author_facet | Valentelyte, Gintare Keegan, Conor Sorensen, Jan |
author_sort | Valentelyte, Gintare |
collection | PubMed |
description | BACKGROUND: Health services research often relies on quasi-experimental study designs in the estimation of treatment effects of a policy change or an intervention. The aim of this study is to compare some of the commonly used non-experimental methods in estimating intervention effects, and to highlight their relative strengths and weaknesses. We estimate the effects of Activity-Based Funding, a hospital financing reform of Irish public hospitals, introduced in 2016. METHODS: We estimate and compare four analytical methods: Interrupted time series analysis, Difference-in-Differences, Propensity Score Matching Difference-in-Differences and the Synthetic Control method. Specifically, we focus on the comparison between the control-treatment methods and the non-control-treatment approach, interrupted time series analysis. Our empirical example evaluated the length of stay impact post hip replacement surgery, following the introduction of Activity-Based Funding in Ireland. We also contribute to the very limited research reporting the impacts of Activity-Based-Funding within the Irish context. RESULTS: Interrupted time-series analysis produced statistically significant results different in interpretation, while the Difference-in-Differences, Propensity Score Matching Difference-in-Differences and Synthetic Control methods incorporating control groups, suggested no statistically significant intervention effect, on patient length of stay. CONCLUSION: Our analysis confirms that different analytical methods for estimating intervention effects provide different assessments of the intervention effects. It is crucial that researchers employ appropriate designs which incorporate a counterfactual framework. Such methods tend to be more robust and provide a stronger basis for evidence-based policy-making. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-022-08657-0. |
format | Online Article Text |
id | pubmed-9635092 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-96350922022-11-05 A comparison of four quasi-experimental methods: an analysis of the introduction of activity-based funding in Ireland Valentelyte, Gintare Keegan, Conor Sorensen, Jan BMC Health Serv Res Research BACKGROUND: Health services research often relies on quasi-experimental study designs in the estimation of treatment effects of a policy change or an intervention. The aim of this study is to compare some of the commonly used non-experimental methods in estimating intervention effects, and to highlight their relative strengths and weaknesses. We estimate the effects of Activity-Based Funding, a hospital financing reform of Irish public hospitals, introduced in 2016. METHODS: We estimate and compare four analytical methods: Interrupted time series analysis, Difference-in-Differences, Propensity Score Matching Difference-in-Differences and the Synthetic Control method. Specifically, we focus on the comparison between the control-treatment methods and the non-control-treatment approach, interrupted time series analysis. Our empirical example evaluated the length of stay impact post hip replacement surgery, following the introduction of Activity-Based Funding in Ireland. We also contribute to the very limited research reporting the impacts of Activity-Based-Funding within the Irish context. RESULTS: Interrupted time-series analysis produced statistically significant results different in interpretation, while the Difference-in-Differences, Propensity Score Matching Difference-in-Differences and Synthetic Control methods incorporating control groups, suggested no statistically significant intervention effect, on patient length of stay. CONCLUSION: Our analysis confirms that different analytical methods for estimating intervention effects provide different assessments of the intervention effects. It is crucial that researchers employ appropriate designs which incorporate a counterfactual framework. Such methods tend to be more robust and provide a stronger basis for evidence-based policy-making. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-022-08657-0. BioMed Central 2022-11-03 /pmc/articles/PMC9635092/ /pubmed/36329423 http://dx.doi.org/10.1186/s12913-022-08657-0 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Valentelyte, Gintare Keegan, Conor Sorensen, Jan A comparison of four quasi-experimental methods: an analysis of the introduction of activity-based funding in Ireland |
title | A comparison of four quasi-experimental methods: an analysis of the introduction of activity-based funding in Ireland |
title_full | A comparison of four quasi-experimental methods: an analysis of the introduction of activity-based funding in Ireland |
title_fullStr | A comparison of four quasi-experimental methods: an analysis of the introduction of activity-based funding in Ireland |
title_full_unstemmed | A comparison of four quasi-experimental methods: an analysis of the introduction of activity-based funding in Ireland |
title_short | A comparison of four quasi-experimental methods: an analysis of the introduction of activity-based funding in Ireland |
title_sort | comparison of four quasi-experimental methods: an analysis of the introduction of activity-based funding in ireland |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9635092/ https://www.ncbi.nlm.nih.gov/pubmed/36329423 http://dx.doi.org/10.1186/s12913-022-08657-0 |
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