TY - JOUR
AU - Williamson, Kath
AU - Nimegeer, Amy
AU - Lean, Michael
PY - 2022
DA - November
TI - Navigating data governance approvals to use routine health and social care data to evidence the hidden population with severe obesity: a case study from a clinical academic's perspective
JO - Journal of Research in Nursing
EP - 636
VL - 27
IS - 7
DO - https://doi.org/10.1177/17449871221122040
AB - Background: Front-line professionals are uniquely placed to identify evidence gaps and the way routinely-collected data can help address them. This knowledge can enable incisive, clinically-relevant research. Aim: To document an example of the real-world approvals journey within the current NHS/Higher Education regulatory landscape, from the perspective of an experienced nurse undertaking doctoral study as a clinical academic. Methods: An instrumental case-study approach is used to explore the approvals process for a mixed-methods study. Relevant context is highlighted to aid understanding, including introduction of the General Data Protection Regulation and the integration of health and social care services. Results: Formal approvals by nine separate stakeholders from four different organisations took nearly 3 years, including 15 initial or revised applications, assessments or agreements. Obstacles included: conflicting views on what constitutes ‘research’ or ‘service evaluation’; isolated decision-making; fragmented data systems; multiple data controllers and a changing data governance environment. The dual perspectives of being both clinician and academic using routine data are explored. Conclusions: Practitioners face a complex approvals process to use data they routinely collect, for research or evaluation purposes. Use of data during the COVID-19 pandemic has demonstrated the need for streamlining of data governance processes. Practical recommendations are outlined.
PB - SAGE Publications
UR - https://eprints.gla.ac.uk/266653/
KW - Coronavirus (COVID-19)
KW - Social and community care
ER