» Articles » PMID: 39405526

Building and Sustaining Public Trust in Health Data Sharing for Musculoskeletal Research: Semistructured Interview and Focus Group Study

Overview
Publisher JMIR Publications
Date 2024 Oct 15
PMID 39405526
Authors
Affiliations
Soon will be listed here.
Abstract

Background: Although many people are supportive of their deidentified health care data being used for research, concerns about privacy, safety, and security of health care data remain. There is low awareness about how data are used for research and related governance. Transparency about how health data are used for research is crucial for building public trust. One proposed solution is to ensure that affected communities are notified, particularly marginalized communities where there has previously been a lack of engagement and mistrust.

Objective: This study aims to explore patient and public perspectives on the use of deidentified data from electronic health records for musculoskeletal research and to explore ways to build and sustain public trust in health data sharing for a research program (known as "the Data Jigsaw") piloting new ways of using and analyzing electronic health data. Views and perspectives about how best to engage with local communities informed the development of a public notification campaign about the research.

Methods: Qualitative methods data were generated from 20 semistructured interviews and 8 focus groups, comprising 48 participants in total with musculoskeletal conditions or symptoms, including 3 carers. A presentation about the use of health data for research and examples from the specific research projects within the program were used to trigger discussion. We worked in partnership with a patient and public involvement group throughout the research and cofacilitated wider community engagement.

Results: Respondents were supportive of their health care data being shared for research purposes, but there was low awareness about how electronic health records are used for research. Security and governance concerns about data sharing were noted, including collaborations with external companies and accessing social care records. Project examples from the Data Jigsaw program were viewed positively after respondents knew more about how their data were being used to improve patient care. A range of different methods to build and sustain trust were deemed necessary by participants. Information was requested about: data management; individuals with access to the data (including any collaboration with external companies); the National Health Service's national data opt-out; and research outcomes. It was considered important to enable in-person dialogue with affected communities in addition to other forms of information.

Conclusions: The findings have emphasized the need for transparency and awareness about health data sharing for research, and the value of tailoring this to reflect current and local research where residents might feel more invested in the focus of research and the use of local records. Thus, the provision for targeted information within affected communities with accessible messages and community-based dialogue could help to build and sustain public trust. These findings can also be extrapolated to other conditions beyond musculoskeletal conditions, making the findings relevant to a much wider community.

References
1.
Rai T, Morton K, Roman C, Doogue R, Rice C, Williams M . Optimizing a digital intervention for managing blood pressure in stroke patients using a diverse sample: Integrating the person-based approach and patient and public involvement. Health Expect. 2020; 24(2):327-340. PMC: 8077154. DOI: 10.1111/hex.13173. View

2.
Stockdale J, Cassell J, Ford E . "Giving something back": A systematic review and ethical enquiry into public views on the use of patient data for research in the United Kingdom and the Republic of Ireland. Wellcome Open Res. 2019; 3:6. PMC: 6402072. DOI: 10.12688/wellcomeopenres.13531.2. View

3.
Waterman L, Pillay M, Katona C . Sharing health data for immigration control affects marginalised communities. BMJ. 2021; 373:n1042. DOI: 10.1136/bmj.n1042. View

4.
Hays R, Daker-White G . The care.data consensus? A qualitative analysis of opinions expressed on Twitter. BMC Public Health. 2015; 15:838. PMC: 4556193. DOI: 10.1186/s12889-015-2180-9. View

5.
Atkin C, Crosby B, Dunn K, Price G, Marston E, Crawford C . Perceptions of anonymised data use and awareness of the NHS data opt-out amongst patients, carers and healthcare staff. Res Involv Engagem. 2021; 7(1):40. PMC: 8201435. DOI: 10.1186/s40900-021-00281-2. View