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Supporting the implementation of new healthcare technologies by investigating generalisability of pilot studies using area-level statistics

BACKGROUND: Implementation of new technologies into national health care systems requires careful capacity planning. This is sometimes informed by data from pilot studies that implement the technology on a small scale in selected areas. A critical consideration when using implementation pilot studie...

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Autores principales: Doorbar, James Alexander, Mathews, Christopher S., Denton, Karin, Rebolj, Matejka, Brentnall, Adam R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9694587/
https://www.ncbi.nlm.nih.gov/pubmed/36434583
http://dx.doi.org/10.1186/s12913-022-08735-3
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author Doorbar, James Alexander
Mathews, Christopher S.
Denton, Karin
Rebolj, Matejka
Brentnall, Adam R.
author_facet Doorbar, James Alexander
Mathews, Christopher S.
Denton, Karin
Rebolj, Matejka
Brentnall, Adam R.
author_sort Doorbar, James Alexander
collection PubMed
description BACKGROUND: Implementation of new technologies into national health care systems requires careful capacity planning. This is sometimes informed by data from pilot studies that implement the technology on a small scale in selected areas. A critical consideration when using implementation pilot studies for capacity planning in the wider system is generalisability. We studied the feasibility of using publicly available national statistics to determine the degree to which results from a pilot might generalise for non-pilot areas, using the English human papillomavirus (HPV) cervical screening pilot as an exemplar. METHODS: From a publicly available source on population indicators in England (“Public Health Profiles”), we selected seven area-level indicators associated with cervical cancer incidence, to produce a framework for post-hoc pilot generalisability analysis. We supplemented these data by those from publicly available English Office for National Statistics modules. We compared pilot to non-pilot areas, and pilot regimens (pilot areas using the previous standard of care (cytology) vs. the new screening test (HPV)). For typical process indicators that inform real-world capacity planning in cancer screening, we used standardisation to re-weight the values directly observed in the pilot, to better reflect the wider population. A non-parametric quantile bootstrap was used to calculate 95% confidence intervals (CI) for differences in area-weighted means for indicators. RESULTS: The range of area-level statistics in pilot areas covered most of the spectrum observed in the wider population. Pilot areas were on average more deprived than non-pilot areas (average index of multiple deprivation 24.8 vs. 21.3; difference: 3.4, 95% CI: 0.2–6.6). Participants in HPV pilot areas were less deprived than those in cytology pilot areas, matching area-level statistics. Differences in average values of the other six indicators were less pronounced. The observed screening process indicators showed minimal change after standardisation for deprivation. CONCLUSIONS: National statistical sources can be helpful in establishing the degree to which the types of areas outside pilot studies are represented, and the extent to which they match selected characteristics of the rest of the health care system ex-post. Our analysis lends support to extrapolation of process indicators from the HPV screening pilot across England. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-022-08735-3.
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spelling pubmed-96945872022-11-26 Supporting the implementation of new healthcare technologies by investigating generalisability of pilot studies using area-level statistics Doorbar, James Alexander Mathews, Christopher S. Denton, Karin Rebolj, Matejka Brentnall, Adam R. BMC Health Serv Res Research Article BACKGROUND: Implementation of new technologies into national health care systems requires careful capacity planning. This is sometimes informed by data from pilot studies that implement the technology on a small scale in selected areas. A critical consideration when using implementation pilot studies for capacity planning in the wider system is generalisability. We studied the feasibility of using publicly available national statistics to determine the degree to which results from a pilot might generalise for non-pilot areas, using the English human papillomavirus (HPV) cervical screening pilot as an exemplar. METHODS: From a publicly available source on population indicators in England (“Public Health Profiles”), we selected seven area-level indicators associated with cervical cancer incidence, to produce a framework for post-hoc pilot generalisability analysis. We supplemented these data by those from publicly available English Office for National Statistics modules. We compared pilot to non-pilot areas, and pilot regimens (pilot areas using the previous standard of care (cytology) vs. the new screening test (HPV)). For typical process indicators that inform real-world capacity planning in cancer screening, we used standardisation to re-weight the values directly observed in the pilot, to better reflect the wider population. A non-parametric quantile bootstrap was used to calculate 95% confidence intervals (CI) for differences in area-weighted means for indicators. RESULTS: The range of area-level statistics in pilot areas covered most of the spectrum observed in the wider population. Pilot areas were on average more deprived than non-pilot areas (average index of multiple deprivation 24.8 vs. 21.3; difference: 3.4, 95% CI: 0.2–6.6). Participants in HPV pilot areas were less deprived than those in cytology pilot areas, matching area-level statistics. Differences in average values of the other six indicators were less pronounced. The observed screening process indicators showed minimal change after standardisation for deprivation. CONCLUSIONS: National statistical sources can be helpful in establishing the degree to which the types of areas outside pilot studies are represented, and the extent to which they match selected characteristics of the rest of the health care system ex-post. Our analysis lends support to extrapolation of process indicators from the HPV screening pilot across England. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-022-08735-3. BioMed Central 2022-11-24 /pmc/articles/PMC9694587/ /pubmed/36434583 http://dx.doi.org/10.1186/s12913-022-08735-3 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 Article
Doorbar, James Alexander
Mathews, Christopher S.
Denton, Karin
Rebolj, Matejka
Brentnall, Adam R.
Supporting the implementation of new healthcare technologies by investigating generalisability of pilot studies using area-level statistics
title Supporting the implementation of new healthcare technologies by investigating generalisability of pilot studies using area-level statistics
title_full Supporting the implementation of new healthcare technologies by investigating generalisability of pilot studies using area-level statistics
title_fullStr Supporting the implementation of new healthcare technologies by investigating generalisability of pilot studies using area-level statistics
title_full_unstemmed Supporting the implementation of new healthcare technologies by investigating generalisability of pilot studies using area-level statistics
title_short Supporting the implementation of new healthcare technologies by investigating generalisability of pilot studies using area-level statistics
title_sort supporting the implementation of new healthcare technologies by investigating generalisability of pilot studies using area-level statistics
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9694587/
https://www.ncbi.nlm.nih.gov/pubmed/36434583
http://dx.doi.org/10.1186/s12913-022-08735-3
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