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

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.