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Background Secondary data from different policy sectors can provide unique insights into the social, environmental, economic and political determinants of health. This is especially pertinent in the context of whole-systems approaches to healthy public policy, which typically combine cross-sectoral collaboration with the application of theoretical insights from systems science. However, the sharing and linkage of data between different sectors are still relatively rare. Previous research has documented the perspectives of researchers and members of the public on data sharing, especially healthcare data, but has not engaged with relevant policy and practice decision-makers. Aim We sought to work collaboratively with decision-makers relevant to healthy public policy and practice in Scotland to identify practical ways that cross-sectoral data sharing and linkage could be used to best effect to improve health and reduce health inequalities. Methods We facilitated three sequential stakeholder workshops with 20 participants from local and central government, public health teams, Health and Social Care Partnerships, the third sector, organisations which support data-intensive research and public representatives from across Scotland. Workshops were informed by two scoping reviews (carried out in June 2021) and three case studies of existing cross-sectoral linkage projects. Workshop activities included brainstorming of factors that would help participants make better decisions in their current role; reflective questions on lessons learnt from the case studies; and identifying and prioritising recommendations for change. Findings were synthesised using thematic analysis. Setting and scope Scotland; public and third sector data. Results Based on the workshops, and supported by the reviews and case studies, we created a visual representation of the use of evidence, and secondary data in particular, in decision-making for healthy public policy and practice. This covered three key overarching themes: differing understandings of evidence; diverse functions of evidence; and factors affecting use (such as technical, political and institutional, workforce and governance). Building on this, workshop participants identified six guiding principles for cross-sectoral data sharing and linkage: it should be pragmatic; participatory; ambitious; fair; iterative; with holistic and proportionate governance. Participants proposed 21 practical actions to this end, including: a strategic approach to identifying and sharing key data sets; streamlining governance processes (e.g. through standardised data sharing agreements; central data repositories; and a focus on reusable data resources) and building workforce capacity. To make these possible, participants identified a need for strong political and organisational leadership as well as a transparent and inclusive public conversation. Limitations Participation from some stakeholders was limited by workload pressures associated with the COVID-19 pandemic. No consensus was reached on the impact, effort, and/or timing of some recommendations. Findings were closely informed by the Scottish context but are nonetheless likely to be relevant to other jurisdictions. Conclusions There is broad consensus among key stakeholders that linked cross-sectoral data can be used far more extensively for public health decision-making than it is at present. No single change will lead to improved use of such data: a range of technical, organisational and political constraints must be addressed. Funding This article presents independent research funded by the National Institute for Health and Care Research (NIHR) Public Health Research programme as award number NIHR133585. Plain language summary A lot of information is generated every day by services such as health care, education, housing and social care, as part of their day-to-day work. This is often called ‘secondary data’ when it is used for research. Sharing and linking together secondary data from different sources can be used to help us better understand how to make people healthier by improving the circumstances in which they live. Although there has been a lot of research looking at issues with sharing National Health Service data, we know much less about how secondary data from other services are used by government officials, council officers, and people working in public health when making decisions which might affect health. This project aimed to identify practical ways that secondary data could be better used to help develop policies and design services that improve people’s health and reduce health inequalities. We reviewed published studies and three existing projects which linked secondary data between the National Health Service and other public services. We held workshops with decision-makers from local and central government, National Health Service public health teams, Health and Social Care Partnerships, the third sector, organisations which support research, and public representatives to discuss these findings and how they use evidence in their work. Workshop participants agreed that sharing and linkage of secondary data from different services could be used for public health decision-making more than it is at present, but that this requires change in multiple different areas, rather than one simple solution. Participants identified six guiding principles and 21 detailed recommendations. Principles included aiming for useful rather than perfect; ensuring all voices are heard; being ambitious; being fair; learning from feedback; and recognising both benefits and risks. Recommendations included a considered approach to which data sets should be shared; standardising oversight of data sharing; using existing data sets efficiently for different research purposes; investing in staff training; and promoting a public conversation about data sharing and linkage, and its benefits and risks.

Objectives We sought to describe barriers and facilitators faced by three research projects aiming to link routinely-collected data across various sectors, to produce evidence to inform healthy public policy. We conducted these case studies as a part of a wider research project on cross-sectoral sharing and linkage of secondary data. Approach We selected the case studies to cover a range of target populations and datasets. The chosen projects investigated (1) the health of care-experienced children; (2) the intersection of homelessness, justice involvement, drug use, and severe mental illness; (3) multi-morbidity among adults receiving social care. Information about timelines and governance processes was collected from lead investigators, including specific barriers and facilitators encountered, using a standardised pro forma and follow-up interviews. Thematic analysis was carried out by the research team, informed by themes identified in a parallel scoping review of existing literature on evidence use for healthy public policy and practice. Results Each project involved between 6 and 11 agencies, with co-ordination across multiple institutions and geographies proving challenging. Due to challenges encountered, all projects had to amend their original geographical or demographic scope. Forty-four barriers and facilitators to sharing and linkage of cross-sectoral routinely-collected data for public health research were identified. These included but were not limited to: integration of current data in an ever-changing linkage landscape; the need for timely feedback in undertaking the study; standardisation of information governance processes; highlighting the resourcing and funding issues for data linkage projects; the need for data controllers to recognise the value of such projects; and issues relating to staff turnover and workload pressures. Conclusion The interconnected nature of barriers and facilitators identified by the case studies suggests the importance of a whole-systems approach to cross-sectoral linkage. While literature offers relatively few case studies of cross-sectoral linkage for health research, the value of their insight into the linkage landscape derived from real-life experience is substantial.