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Developing an ethical framework-guided instrument for assessing bias in EHR-based Big Data studies: a research protocol

INTRODUCTION: The emergence of Big Data health research has exponentially advanced the fields of medicine and public health but has also faced many ethical challenges. One of most worrying but still under-researched aspects of the ethical issues is the risk of potential biases in data sets (eg, elec...

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Autores principales: Qiao, Shan, Khushf, George, Li, Xiaoming, Zhang, Jiajia, Olatosi, Bankole
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10441074/
https://www.ncbi.nlm.nih.gov/pubmed/37591640
http://dx.doi.org/10.1136/bmjopen-2022-070870
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author Qiao, Shan
Khushf, George
Li, Xiaoming
Zhang, Jiajia
Olatosi, Bankole
author_facet Qiao, Shan
Khushf, George
Li, Xiaoming
Zhang, Jiajia
Olatosi, Bankole
author_sort Qiao, Shan
collection PubMed
description INTRODUCTION: The emergence of Big Data health research has exponentially advanced the fields of medicine and public health but has also faced many ethical challenges. One of most worrying but still under-researched aspects of the ethical issues is the risk of potential biases in data sets (eg, electronic health records (EHR) data) as well as in the data curation and acquisition cycles. This study aims to develop, refine and pilot test an ethical framework-guided instrument for assessing bias in Big Data research using EHR data sets. METHODS AND ANALYSIS: Ethical analysis and instrument development (ie, the EHR bias assessment guideline) will be implemented through an iterative process composed of literature/policy review, content analysis and interdisciplinary dialogues and discussion. The ethical framework and EHR bias assessment guideline will be iteratively refined and integrated with preliminary summaries of results in a way that informs subsequent research. We will engage data curators, end-user researchers, healthcare workers and patient representatives throughout all iterative cycles using various formats including in-depth interviews of key stakeholders, panel discussions and charrette workshops. The developed EHR bias assessment guideline will be pilot tested in an existing National Institutes of Health (NIH) funded Big Data HIV project (R01AI164947). ETHICS AND DISSEMINATION: The study was approved by Institutional Review Boards at the University of South Carolina (Pro00122501). Informed consent will be provided by the participants in the in-depth interviews. Study findings will be disseminated with key stakeholders, presented at relevant workshops and academic conferences, and published in peer-reviewed journals.
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spelling pubmed-104410742023-08-22 Developing an ethical framework-guided instrument for assessing bias in EHR-based Big Data studies: a research protocol Qiao, Shan Khushf, George Li, Xiaoming Zhang, Jiajia Olatosi, Bankole BMJ Open Ethics INTRODUCTION: The emergence of Big Data health research has exponentially advanced the fields of medicine and public health but has also faced many ethical challenges. One of most worrying but still under-researched aspects of the ethical issues is the risk of potential biases in data sets (eg, electronic health records (EHR) data) as well as in the data curation and acquisition cycles. This study aims to develop, refine and pilot test an ethical framework-guided instrument for assessing bias in Big Data research using EHR data sets. METHODS AND ANALYSIS: Ethical analysis and instrument development (ie, the EHR bias assessment guideline) will be implemented through an iterative process composed of literature/policy review, content analysis and interdisciplinary dialogues and discussion. The ethical framework and EHR bias assessment guideline will be iteratively refined and integrated with preliminary summaries of results in a way that informs subsequent research. We will engage data curators, end-user researchers, healthcare workers and patient representatives throughout all iterative cycles using various formats including in-depth interviews of key stakeholders, panel discussions and charrette workshops. The developed EHR bias assessment guideline will be pilot tested in an existing National Institutes of Health (NIH) funded Big Data HIV project (R01AI164947). ETHICS AND DISSEMINATION: The study was approved by Institutional Review Boards at the University of South Carolina (Pro00122501). Informed consent will be provided by the participants in the in-depth interviews. Study findings will be disseminated with key stakeholders, presented at relevant workshops and academic conferences, and published in peer-reviewed journals. BMJ Publishing Group 2023-08-17 /pmc/articles/PMC10441074/ /pubmed/37591640 http://dx.doi.org/10.1136/bmjopen-2022-070870 Text en © Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) .
spellingShingle Ethics
Qiao, Shan
Khushf, George
Li, Xiaoming
Zhang, Jiajia
Olatosi, Bankole
Developing an ethical framework-guided instrument for assessing bias in EHR-based Big Data studies: a research protocol
title Developing an ethical framework-guided instrument for assessing bias in EHR-based Big Data studies: a research protocol
title_full Developing an ethical framework-guided instrument for assessing bias in EHR-based Big Data studies: a research protocol
title_fullStr Developing an ethical framework-guided instrument for assessing bias in EHR-based Big Data studies: a research protocol
title_full_unstemmed Developing an ethical framework-guided instrument for assessing bias in EHR-based Big Data studies: a research protocol
title_short Developing an ethical framework-guided instrument for assessing bias in EHR-based Big Data studies: a research protocol
title_sort developing an ethical framework-guided instrument for assessing bias in ehr-based big data studies: a research protocol
topic Ethics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10441074/
https://www.ncbi.nlm.nih.gov/pubmed/37591640
http://dx.doi.org/10.1136/bmjopen-2022-070870
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