Einzeltreffer — DigiBib

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.

Competing Interests: Competing interests: None declared.

Titel:	Developing an ethical framework-guided instrument for assessing bias in EHR-based Big Data studies: a research protocol.
Autor/in / Beteiligte Person:	Qiao, S ; Khushf, G ; Li, X ; Zhang, J ; Olatosi, B
Link:	Full Text Finder (Volltext)
Zeitschrift:	BMJ open, Jg. 13 (2023-08-17), Heft 8, S. e070870
Veröffentlichung:	[London] : BMJ Publishing Group Ltd, 2011-, 2023
Medientyp:	academicJournal
ISSN:	2044-6055 (electronic)
DOI:	10.1136/bmjopen-2022-070870
Schlagwort:	United States Humans Bias Public Health Big Data Ethics Committees, Research
Sonstiges:	Nachgewiesen in: MEDLINE Sprachen: English Publication Type: Journal Article; Research Support, N.I.H., Extramural Language: English [BMJ Open] 2023 Aug 17; Vol. 13 (8), pp. e070870. <i>Date of Electronic Publication: </i>2023 Aug 17. MeSH Terms: Big Data* ; Ethics Committees, Research* ; United States ; Humans ; Bias ; Public Health References: Med Hypotheses. 2018 Oct;119:32-36. (PMID: 30122488) ; Control Clin Trials. 1996 Feb;17(1):1-12. (PMID: 8721797) ; Int J Impot Res. 2017 Mar;29(2):65-69. (PMID: 27904149) ; BMJ. 2018 Apr 30;361:k1479. (PMID: 29712648) ; Ann Epidemiol. 2017 May;27(5):297-301. (PMID: 28595734) ; Trends Microbiol. 2012 Jan;20(1):1-4. (PMID: 22112388) ; NPJ Digit Med. 2018 Oct 2;1:53. (PMID: 31304332) ; Spine (Phila Pa 1976). 2003 Jun 15;28(12):1290-9. (PMID: 12811274) ; JAMA. 2019 Jun 18;321(23):2281-2282. (PMID: 31107500) ; Innov Clin Neurosci. 2020 Oct 01;17(10-12):24-30. (PMID: 33898098) ; J Adv Nurs. 1989 Apr;14(4):330-5. (PMID: 2661622) ; Nature. 2017 Jun 28;546(7660):686. (PMID: 28658222) ; Sci Data. 2016 Mar 15;3:160018. (PMID: 26978244) ; N Engl J Med. 2018 Mar 15;378(11):981-983. (PMID: 29539284) ; Nat Med. 2019 Jan;25(1):37-43. (PMID: 30617331) ; J Comp Eff Res. 2015 Jan;4(1):61-74. (PMID: 25565069) ; JAMA Intern Med. 2019 Mar 1;179(3):293-294. (PMID: 30556825) ; Database (Oxford). 2020 Jan 1;2020:. (PMID: 32185396) ; BMJ. 2000 Jan 8;320(7227):114-6. (PMID: 10625273) ; PLoS Comput Biol. 2015 Feb 09;11(2):e1004073. (PMID: 25664660) ; BMC Med Res Methodol. 2008 Jul 10;8:45. (PMID: 18616818) ; J Bioeth Inq. 2017 Dec;14(4):489-500. (PMID: 28321561) ; Ethics Hum Res. 2020 Sep;42(5):17-28. (PMID: 32937036) ; Bioethics. 2019 Mar;33(3):357-366. (PMID: 30667080) ; Sci Eng Ethics. 2018 Oct;24(5):1521-1536. (PMID: 28936795) ; Metabolism. 2017 Apr;69S:S36-S40. (PMID: 28126242) ; BMC Med Ethics. 2021 Feb 15;22(1):14. (PMID: 33588803) ; Health Serv Res. 2007 Aug;42(4):1758-72. (PMID: 17286625) ; Prog Community Health Partnersh. 2018;12(1):89-99. (PMID: 29606697) Grant Information: R01 AI164947 United States AI NIAID NIH HHS Contributed Indexing: Keywords: HIV & AIDS; MEDICAL ETHICS; PUBLIC HEALTH Entry Date(s): Date Created: 20230817 Date Completed: 20230821 Latest Revision: 20240112 Update Code: 20240112 PubMed Central ID: PMC10441074

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