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Asking informed consent may lead to significant participation bias and suboptimal cardiovascular risk management in learning healthcare systems
BACKGROUND: The Utrecht Cardiovascular Cohort – CardioVascular Risk Management (UCC-CVRM) was set up as a learning healthcare system (LHS), aiming at guideline based cardiovascular risk factor measurement in all patients in routine clinical care. However, not all patients provided informed consent,...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10122202/ https://www.ncbi.nlm.nih.gov/pubmed/37087415 http://dx.doi.org/10.1186/s12874-023-01924-6 |
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author | Zondag, Anna G. M. Groenhof, T. Katrien J. van der Graaf, Rieke van Solinge, Wouter W. Bots, Michiel L. Haitjema, Saskia |
author_facet | Zondag, Anna G. M. Groenhof, T. Katrien J. van der Graaf, Rieke van Solinge, Wouter W. Bots, Michiel L. Haitjema, Saskia |
author_sort | Zondag, Anna G. M. |
collection | PubMed |
description | BACKGROUND: The Utrecht Cardiovascular Cohort – CardioVascular Risk Management (UCC-CVRM) was set up as a learning healthcare system (LHS), aiming at guideline based cardiovascular risk factor measurement in all patients in routine clinical care. However, not all patients provided informed consent, which may lead to participation bias. We aimed to study participation bias in a LHS by assessing differences in and completeness of cardiovascular risk management (CVRM) indicators in electronic health records (EHRs) of consenting, non-consenting, and non-responding patients, using the UCC-CVRM as an example. METHODS: All patients visiting the University Medical Center Utrecht for first time evaluation of a(n) (a)symptomatic vascular disease or condition were invited to participate. Routine care data was collected in the EHR and an informed consent was asked. Differences in patient characteristics were compared between consent groups. We performed multivariable logistic regression to identify determinants of non-consent. We used multinomial regression for an exploratory analysis for the determinants of non-response. Presence of CVRM indicators were compared between consent groups. A waiver (19/641) was obtained from our ethics committee. RESULTS: Out of 5730 patients invited, 2378 were consenting, 1907 non-consenting, and 1445 non-responding. Non-consent was related to young and old age, lower education level, lower BMI, physical activity and haemoglobin levels, higher heartrate, cardiovascular disease history and absence of proteinuria. Non-response increased with young and old age, higher education level, physical activity, HbA1c and decreased with lower levels of haemoglobin, BMI, and systolic blood pressure. Presence of CVRM indicators was 5–30% lower in non-consenting patients and even lower in non-responding patients, compared to consenting patients. Non-consent and non-response varied across specialisms. CONCLUSIONS: A traditional informed consent procedure in a LHS may lead to participation bias and potentially to suboptimal CVRM, which is detrimental for feedback on findings in a LHS. This underlines the importance of reassessing the informed consent procedure in a LHS. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12874-023-01924-6. |
format | Online Article Text |
id | pubmed-10122202 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-101222022023-04-23 Asking informed consent may lead to significant participation bias and suboptimal cardiovascular risk management in learning healthcare systems Zondag, Anna G. M. Groenhof, T. Katrien J. van der Graaf, Rieke van Solinge, Wouter W. Bots, Michiel L. Haitjema, Saskia BMC Med Res Methodol Research BACKGROUND: The Utrecht Cardiovascular Cohort – CardioVascular Risk Management (UCC-CVRM) was set up as a learning healthcare system (LHS), aiming at guideline based cardiovascular risk factor measurement in all patients in routine clinical care. However, not all patients provided informed consent, which may lead to participation bias. We aimed to study participation bias in a LHS by assessing differences in and completeness of cardiovascular risk management (CVRM) indicators in electronic health records (EHRs) of consenting, non-consenting, and non-responding patients, using the UCC-CVRM as an example. METHODS: All patients visiting the University Medical Center Utrecht for first time evaluation of a(n) (a)symptomatic vascular disease or condition were invited to participate. Routine care data was collected in the EHR and an informed consent was asked. Differences in patient characteristics were compared between consent groups. We performed multivariable logistic regression to identify determinants of non-consent. We used multinomial regression for an exploratory analysis for the determinants of non-response. Presence of CVRM indicators were compared between consent groups. A waiver (19/641) was obtained from our ethics committee. RESULTS: Out of 5730 patients invited, 2378 were consenting, 1907 non-consenting, and 1445 non-responding. Non-consent was related to young and old age, lower education level, lower BMI, physical activity and haemoglobin levels, higher heartrate, cardiovascular disease history and absence of proteinuria. Non-response increased with young and old age, higher education level, physical activity, HbA1c and decreased with lower levels of haemoglobin, BMI, and systolic blood pressure. Presence of CVRM indicators was 5–30% lower in non-consenting patients and even lower in non-responding patients, compared to consenting patients. Non-consent and non-response varied across specialisms. CONCLUSIONS: A traditional informed consent procedure in a LHS may lead to participation bias and potentially to suboptimal CVRM, which is detrimental for feedback on findings in a LHS. This underlines the importance of reassessing the informed consent procedure in a LHS. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12874-023-01924-6. BioMed Central 2023-04-22 /pmc/articles/PMC10122202/ /pubmed/37087415 http://dx.doi.org/10.1186/s12874-023-01924-6 Text en © The Author(s) 2023 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 Zondag, Anna G. M. Groenhof, T. Katrien J. van der Graaf, Rieke van Solinge, Wouter W. Bots, Michiel L. Haitjema, Saskia Asking informed consent may lead to significant participation bias and suboptimal cardiovascular risk management in learning healthcare systems |
title | Asking informed consent may lead to significant participation bias and suboptimal cardiovascular risk management in learning healthcare systems |
title_full | Asking informed consent may lead to significant participation bias and suboptimal cardiovascular risk management in learning healthcare systems |
title_fullStr | Asking informed consent may lead to significant participation bias and suboptimal cardiovascular risk management in learning healthcare systems |
title_full_unstemmed | Asking informed consent may lead to significant participation bias and suboptimal cardiovascular risk management in learning healthcare systems |
title_short | Asking informed consent may lead to significant participation bias and suboptimal cardiovascular risk management in learning healthcare systems |
title_sort | asking informed consent may lead to significant participation bias and suboptimal cardiovascular risk management in learning healthcare systems |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10122202/ https://www.ncbi.nlm.nih.gov/pubmed/37087415 http://dx.doi.org/10.1186/s12874-023-01924-6 |
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