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A novel metadata management model to capture consent for record linkage in longitudinal health research studies

McMahon, C; Denaxas, SC; (2019) A novel metadata management model to capture consent for record linkage in longitudinal health research studies. Informatics for Health and Social Care , 44 (2) pp. 176-188. 10.1080/17538157.2017.1364251. Green open access

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Abstract

Background: Informed consent is an important feature of longitudinal research studies as it enables the linking of administrative data of participants to data collected at baseline such as survey answers. The lack of standardised models to capture consent elements can lead to substantial challenges and a structured approach to capturing consent-related metadata can address these. Objectives: The aims were to: a) explore the state-of-art for recording consent; b) identify key elements of consent required for record linkage; and c) create and evaluate a novel metadata management model to capture consent-related metadata. Methods: The main methodological components of our work were: a) a systematic literature review and qualitative analysis of consent forms; b) the development and evaluation of a novel metadata model. Discussion: We qualitatively analyzed 61 manuscripts and 30 consent forms. We extracted data elements related to obtaining consent for linkage. We created a novel metadata management model for consent and evaluated it by comparison with existing standards and by iteratively applying it to case studies. Conclusion: The developed model can facilitate the standardised recording of consent for linkage in longitudinal research studies and enable the linkage of external participant data. Furthermore, it can provide a structured way of recording consent-related metadata and facilitate the harmonization and streamlining of processes.

Type: Article
Title: A novel metadata management model to capture consent for record linkage in longitudinal health research studies
Open access status: An open access version is available from UCL Discovery
DOI: 10.1080/17538157.2017.1364251
Publisher version: http://dx.doi.org/10.1080/17538157.2017.1364251
Language: English
Additional information: This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics > Clinical Epidemiology
UCL > Provost and Vice Provost Offices > VP: Research > Library Services
URI: https://discovery.ucl.ac.uk/id/eprint/1568942
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