Background The NHS policy of constructing multispecialty community providers (MCPs) rests on a complex set of assumptions about how health systems can replace hospital use with enhanced primary care for people with complex, chronic or multiple health problems, while contributing savings to health-care budgets. Objectives To use policy-makers’ assumptions to elicit an initial programme theory (IPT) of how MCPs can achieve their outcomes and to compare this with published secondary evidence and revise the programme theory accordingly. Design Realist synthesis with a three-stage method: (1) for policy documents, elicit the IPT underlying the MCP policy, (2) review and synthesise secondary evidence relevant to those assumptions and (3) compare the programme theory with the secondary evidence and, when necessary, reformulate the programme theory in a more evidence-based way. Data sources Systematic searches and data extraction using (1) the Health Management Information Consortium (HMIC) database for policy statements and (2) topically appropriate databases, including MEDLINE, MEDLINE In-Process & Other Non-Indexed Citations, PsycINFO, the Cumulative Index to Nursing and Allied Health Literature (CINAHL) and Applied Social Sciences Index and Abstracts (ASSIA). A total of 1319 titles and abstracts were reviewed in two rounds and 116 were selected for full-text data extraction. We extracted data using a formal data extraction tool and synthesised them using a framework reflecting the main policy assumptions. Results The IPT of MCPs contained 28 interconnected context–mechanism–outcome relationships. Few policy statements specified what contexts the policy mechanisms required. We found strong evidence supporting the IPT assumptions concerning organisational culture, interorganisational network management, multidisciplinary teams (MDTs), the uses and effects of health information technology (HIT) in MCP-like settings, planned referral networks, care planning for individual patients and the diversion of patients from inpatient to primary care. The evidence was weaker, or mixed (supporting some of the constituent assumptions but not others), concerning voluntary sector involvement, the effects of preventative care on hospital admissions and patient experience, planned referral networks and demand management systems. The evidence about the effects of referral reductions on costs was equivocal. We found no studies confirming that the development of preventative care would reduce demands on inpatient services. The IPT had overlooked certain mechanisms relevant to MCPs, mostly concerning MDTs and the uses of HITs. Limitations The studies reviewed were limited to Organisation for Economic Co-operation and Development countries and, because of the large amount of published material, the period 2014–16, assuming that later studies, especially systematic reviews, already include important earlier findings. No empirical studies of MCPs yet existed. Conclusions Multidisciplinary teams are a central mechanism by which MCPs (and equivalent networks and organisations) work, provided that the teams include the relevant professions (hence, organisations) and, for care planning, individual patients. Further primary research would be required to test elements of the revised logic model, in particular about (1) how MDTs and enhanced general practice compare and interact, or can be combined, in managing referral networks and (2) under what circumstances diverting patients from in-patient to primary care reduces NHS costs and improves the quality of patient experience. Study registration This study is registered as PROSPERO CRD42016038900. Funding The National Institute for Health Research (NIHR) Health Services and Delivery Research programme and supported by the NIHR Collaboration for Leadership in Applied Health Research and Care South West Peninsula.

Publication Date


Publication Title

Health Services and Delivery Research



Organisational Unit

Peninsula Medical School


Multi-specialty community provider, England, Primary care, Realist synthesis, Multi-disciplinary team, Care coordination, Integrated care, Health information technology, Models of care