Objectives: To realise the potential of big data to help bring innovative treatments to patients, a number of challenges need to be addressed. Not least of these is the ability to harmonise, select and collect the priority outcomes generated from diverse sources, settings and populations that are required by different key decision makers including HTA and regulatory agencies. The suite of projects in the IMI Big Data for Better Outcomes (BD4BO) programme (http://bd4bo.eu/) are addressing this specific challenge. To meet this need, strategic guidance aimed at providing practical methodological support for the identification, selection and measurement of outcomes within BD4BO projects was recognised as a key enabler. Results: A freely available toolkit based around the principles of core outcome sets (COS), a consensus agreed minimum sets of outcomes in a disease area has been developed. The approach features 6-stages, signposts to numerous methodological options, offering practical guidance and key considerations. A crucial feature relates to processes to incorporate multiple stakeholder perspectives and provides mechanisms to include regulator and HTA outcome preferences across the EU regulatory/reimbursement landscape. Additionally case examples for the application of COS in real world settings and/or datasets outside of clinical trials and the identification and agreement of a minimum dataset (such as on demographics, comorbidities) to contextualise outcome data are included. Practical implications: The Toolkit is a practical and clear guide that illustrates the importance of including multi-stakeholder preferences when considering outcome selection across the entire evidence ecosystem. Engagement of HTA agencies and incorporation of their outcome preferences within COS is a potentially important mechanism for signalling their evidence requirements and could improve the relevance and consistency of outcome selection and measures specifically for big data applications and real world evidence.