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Economic Evaluations Alongside Efficient Study Designs Using Large Observational Datasets: the PLEASANT Trial Case Study
BACKGROUND: Large observational datasets such as Clinical Practice Research Datalink (CPRD) provide opportunities to conduct clinical studies and economic evaluations with efficient designs. OBJECTIVES: Our objectives were to report the economic evaluation methodology for a cluster randomised contro...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Springer International Publishing
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5385191/ https://www.ncbi.nlm.nih.gov/pubmed/28110382 http://dx.doi.org/10.1007/s40273-016-0484-y |
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author | Franklin, Matthew Davis, Sarah Horspool, Michelle Kua, Wei Sun Julious, Steven |
author_facet | Franklin, Matthew Davis, Sarah Horspool, Michelle Kua, Wei Sun Julious, Steven |
author_sort | Franklin, Matthew |
collection | PubMed |
description | BACKGROUND: Large observational datasets such as Clinical Practice Research Datalink (CPRD) provide opportunities to conduct clinical studies and economic evaluations with efficient designs. OBJECTIVES: Our objectives were to report the economic evaluation methodology for a cluster randomised controlled trial (RCT) of a UK NHS-delivered public health intervention for children with asthma that was evaluated using CPRD and describe the impact of this methodology on results. METHODS: CPRD identified eligible patients using predefined asthma diagnostic codes and captured 1-year pre- and post-intervention healthcare contacts (August 2012 to July 2014). Quality-adjusted life-years (QALYs) 4 months post-intervention were estimated by assigning utility values to exacerbation-related contacts; a systematic review identified these utility values because preference-based outcome measures were not collected. Bootstrapped costs were evaluated 12 months post-intervention, both with 1-year regression-based baseline adjustment (BA) and without BA (observed). RESULTS: Of 12,179 patients recruited, 8190 (intervention 3641; control 4549) were evaluated in the primary analysis, which included patients who received the protocol-defined intervention and for whom CPRD data were available. The intervention’s per-patient incremental QALY loss was 0.00017 (bias-corrected and accelerated 95% confidence intervals [BCa 95% CI] –0.00051 to 0.00018) and cost savings were £14.74 (observed; BCa 95% CI –75.86 to 45.19) or £36.07 (BA; BCa 95% CI –77.11 to 9.67), respectively. The probability of cost savings was much higher when accounting for BA versus observed costs due to baseline cost differences between trial arms (96.3 vs. 67.3%, respectively). CONCLUSION: Economic evaluations using data from a large observational database without any primary data collection is feasible, informative and potentially efficient. Clinical Trials Registration Number: ISRCTN03000938. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s40273-016-0484-y) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5385191 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-53851912017-04-24 Economic Evaluations Alongside Efficient Study Designs Using Large Observational Datasets: the PLEASANT Trial Case Study Franklin, Matthew Davis, Sarah Horspool, Michelle Kua, Wei Sun Julious, Steven Pharmacoeconomics Original Research Article BACKGROUND: Large observational datasets such as Clinical Practice Research Datalink (CPRD) provide opportunities to conduct clinical studies and economic evaluations with efficient designs. OBJECTIVES: Our objectives were to report the economic evaluation methodology for a cluster randomised controlled trial (RCT) of a UK NHS-delivered public health intervention for children with asthma that was evaluated using CPRD and describe the impact of this methodology on results. METHODS: CPRD identified eligible patients using predefined asthma diagnostic codes and captured 1-year pre- and post-intervention healthcare contacts (August 2012 to July 2014). Quality-adjusted life-years (QALYs) 4 months post-intervention were estimated by assigning utility values to exacerbation-related contacts; a systematic review identified these utility values because preference-based outcome measures were not collected. Bootstrapped costs were evaluated 12 months post-intervention, both with 1-year regression-based baseline adjustment (BA) and without BA (observed). RESULTS: Of 12,179 patients recruited, 8190 (intervention 3641; control 4549) were evaluated in the primary analysis, which included patients who received the protocol-defined intervention and for whom CPRD data were available. The intervention’s per-patient incremental QALY loss was 0.00017 (bias-corrected and accelerated 95% confidence intervals [BCa 95% CI] –0.00051 to 0.00018) and cost savings were £14.74 (observed; BCa 95% CI –75.86 to 45.19) or £36.07 (BA; BCa 95% CI –77.11 to 9.67), respectively. The probability of cost savings was much higher when accounting for BA versus observed costs due to baseline cost differences between trial arms (96.3 vs. 67.3%, respectively). CONCLUSION: Economic evaluations using data from a large observational database without any primary data collection is feasible, informative and potentially efficient. Clinical Trials Registration Number: ISRCTN03000938. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s40273-016-0484-y) contains supplementary material, which is available to authorized users. Springer International Publishing 2017-01-21 2017 /pmc/articles/PMC5385191/ /pubmed/28110382 http://dx.doi.org/10.1007/s40273-016-0484-y Text en © The Author(s) 2017, corrected publication 2018 Open AccessThis 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 Creative Commons license, and indicate if changes were made. |
spellingShingle | Original Research Article Franklin, Matthew Davis, Sarah Horspool, Michelle Kua, Wei Sun Julious, Steven Economic Evaluations Alongside Efficient Study Designs Using Large Observational Datasets: the PLEASANT Trial Case Study |
title | Economic Evaluations Alongside Efficient Study Designs Using Large Observational Datasets: the PLEASANT Trial Case Study |
title_full | Economic Evaluations Alongside Efficient Study Designs Using Large Observational Datasets: the PLEASANT Trial Case Study |
title_fullStr | Economic Evaluations Alongside Efficient Study Designs Using Large Observational Datasets: the PLEASANT Trial Case Study |
title_full_unstemmed | Economic Evaluations Alongside Efficient Study Designs Using Large Observational Datasets: the PLEASANT Trial Case Study |
title_short | Economic Evaluations Alongside Efficient Study Designs Using Large Observational Datasets: the PLEASANT Trial Case Study |
title_sort | economic evaluations alongside efficient study designs using large observational datasets: the pleasant trial case study |
topic | Original Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5385191/ https://www.ncbi.nlm.nih.gov/pubmed/28110382 http://dx.doi.org/10.1007/s40273-016-0484-y |
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