Making Coordination Count: Mapping and Prioritising Measures of Care Coordination  for People with Multiple Long-Term Conditions

Abstract

Introduction: People living with multiple long-term conditions (MLTC) often experience fragmented and unequal access to health and social care. Effective coordination- ensuring that services are connected, communication is continuous, and responsibilities are clear - is central to integrated care and essential for reducing inequalities. Yet there is no agreed way to measure coordination across systems. Without robust, meaningful metrics, efforts to improve integration risk overlooking those with the most complex needs.   Aim: s and Objectives: This scoping review maps existing measures of care coordination for adults with MLTC, assessing their conceptual foundations, practical application, and suitability for use with routinely collected health and social care data in the UK. It also identifies “best-fit” measures that align with what matters to people with lived experience and to professionals working across system boundaries.   Methods: Systematic searches of academic and grey literature identified studies describing the development, adaptation, validation, or use of care coordination measures. The McDonald (2014) and ATLAS frameworks informed data extraction and analysis. The review took an inclusive approach, capturing both formally developed instruments and studies that operationalised coordination or continuity of care using routinely collected data. Measures were classified as direct (capturing coordination activities such as follow-up visits or shared care plans) or indirect (using proxies like continuity indices or network density). Each measure was appraised for relevance to stakeholder priorities, feasibility within UK electronic health records (EHRs), and burden of completion. Measures were further grouped into conceptual families (shared theoretical intent) and operational commonalities (shared data logic within EHRs). Appraisal and prioritisation were refined through workshops with stakeholders, patient and public involvement and engagement (PPIE) contributors, and data experts.   Findings: Over 60 distinct measures were identified, many reused across authors and contexts. These clustered within conceptual families such as continuity, network/teamwork, transitions, medication management, and care planning, and shared operational commonalities including encounter-linked, time-bounded, and documentation-flag indicators. Few addressed the full multidimensional coordination challenges faced by people with MLTC or incorporated social care and community support. Stakeholders valued measures capturing relational continuity, shared accountability, and information transfer-dimensions often missing from quantitative indices.   A shortlist of “best-fit” measures was identified that are (1) meaningful to people with lived experience, (2) feasible to implement using routine data, and (3) capable of highlighting coordination gaps contributing to inequalities.   Conclusion: sExisting measures offer useful starting points but remain fragmented and narrow in scope. This review highlights the need for integrated, data-driven measurement bundles that reflect real world coordination across health and social care. Working with patient and professional stakeholders, we have co-produced a shortlist of “best-fit” measures designed to capture what matters most to people with MLTC. These measures are feasible to implement using routine data and can help systems identify and address inequalities in coordinated care.   Findings from this collaborative process will be presented, illustrating how inclusive, people-centred measurement measure development can drive more equitable and person-centred integration.