Emily Mann

Background: Hospital electronic health record (EHR) systems contain extensive data of varying quality and suitability for research. Identifying research suitable data from hospital systems is rarely performed using a structured approach. Objective: To define a core set of research suitable data, from multiple hospital datasets and systems for the National Centre for Healthy Ageing Data Platform. Method: Candidate data were identified based on: published literature, researcher survey and quality audit. We recruited researchers and clinicians to participate in a modified Delphi method to achieve consensus on the core data. Live online surveys were conducted across 11 datasets. Participants rated the relevance of each data item using a Likert scale and provide additional feedback. Acceptance criteria were set at >70% agreement. Items meeting this threshold were included in the core dataset. Results: The end user group contained 16 university and 17 clinician researchers. An initial 144 data items were presented for consideration. Experts provided additional details for specialised items. Consensus to include an item was reached after one ( n = 127) or two ( n = 3) rounds with an additional three items identified by end-users. The final core dataset included 133 items across all 11 datasets. Conclusion: Our approach proved effective in reaching consensus among diverse researchers, ensuring that the selected data items are relevant for a range of purposes. Implications for health information management practice: Having a core dataset will support targeted activities that ensure these items are accurate, readily accessible and used appropriately to support patient care, administrative tasks and research.