Authors: Kumar, T.¹, McLaughlin, J.², Murray, E.², Gibson, D.², McCann, M.¹

Affiliations: 1. Department of Computing, Atlantic Technological University, Letterkenny, Ireland, 2. Personalised Medicine Centre, School of Medicine, Ulster University, Londonderry/Derry, United Kingdom.

Background/ Introduction: The iMPROVE project focuses on personalised prescribing and medicines optimisation in primary care by integrating clinical review, patient-reported information and pharmacogenomic data to support more tailored prescribing decisions. Accurate, standardised and clinically meaningful data collection is essential for research, pathway monitoring and service evaluation. As data are collected across multiple participant stages by clinicians and patients, a structured REDCap workflow was co-developed with target user groups to support consistent longitudinal data capture.

Material & Methods: The REDCap workflow was developed with research, clinical and data management teams. Data needs were determined from iMPROVE study materials and discussions with team members involved in delivery. Draft forms were iteratively reviewed for clarity, to reduce duplication and ensure consistency with longitudinal data collection needs. Data capture forms were structured to key stages such as: Entry route documentation, pre-consent eligibility screening, Consent and post-consent allocation, Baseline assessment, pre-medication review, Medication review, post-medication review, pre-follow-up, follow-up and post-follow-up

Forms were structured according to completion responsibility, data type and timing within the participant pathway. Clinician-completed forms captured eligibility, allocation, clinical and medical history, medication-related indicators, pharmacogenomic test data, medication review outcomes, prescription changes, service use and prescriber feedback. Patient-completed forms captured demographics, EQ-5D-5L, pain assessment, mental health assessments, medication review surveys and self-reported resource use.

Results: The resulting REDCap workflow established a structured electronic framework for iMPROVE research data capture. It improved consistency across participant stages, separated clinician-entered and patient-completed information, reduced ambiguity around timing and responsibility for data entry, supported repeated outcome collection and provided infrastructure for future analysis and service evaluation.

Conclusion: The development of a structured REDCap workflow provides core digital research infrastructure for the iMPROVE project. The co-development approach with target user feedback supports consistent longitudinal data collection and future evaluation of personalised prescribing, pharmacogenomic testing and medicines optimisation pathways in primary care.