Search

A current priority within UK policy is to promote partnership working between healthcare and the community sector to support the delivery of integrated and person-centred care, and to tackle the wider determinants of health. This represents a shift in focus from a curative to a preventative system. Social prescribing has been put forward to address this. Definitions, models, and understanding of social prescribing vary which leads to differences in the implementation of the concept. However, at its core, it enables healthcare professionals to refer patients with non-medical needs to non-medical sources of support, to improve their health and wellbeing. In some models of social prescribing a link worker is employed to facilitate this process. Social prescribing is increasingly present in policy and the media. However, much research reports barriers to the implementation of services in practice, and, despite some evidence of the effectiveness of individual services, there is insufficient evidence to support the wide-scale implementation of the concept. As social prescribing is gradually implemented across the UK, it is paramount that the concept is understood, including the roles of stakeholders and the barriers that services face. A scoping review of the current literature was first conducted. Following this, the aim of the research was determined: to examine social prescribing in practice with a view to producing a framework of knowledge to progress understanding and implementation. A convergent parallel mixed-methods research design was adopted which was underpinned by a critical realist perspective and guided by the Rainbow Model of Integrated Care as the theoretical foundation. In study I secondary data from a social prescribing service were obtained for analysis to explore the underlying contributing factors to requiring a non-medical health intervention. Due to the poor quality of the data obtained, the planned quantitative analysis was not possible. However, the data highlighted the need for proper data collection and management. In study II three stakeholder groups took part in semi-structured interviews: GPs (n = 18), link workers (n = 15), and service users (n= 18). Inductive thematic analysis was adopted to analyse interview data, after which themes were deductively mapped against the domains of the Rainbow Model of Integrated Care. Non-thematic data present in interviews were analysed categorically. Study II identified a range of barriers to social prescribing. However, when the findings of study I and II were combined it was apparent that, instead of a fixed list of barriers, there are a set of factors that influence social prescribing in practice which turn into barriers when not present. These were identified from the research findings, but it was noted that there are complex interrelationships between all factors and, therefore, they could not be considered individually. Instead, they were summarised as the following five mechanisms: a clear definition and shared understanding, supportive context, sufficient and secure funding, IT infrastructure, and stakeholder 'buy-in'. When considered at a broad level, these mechanisms suggest that social prescribing needs to be established as a reputable intervention with formal links to healthcare. In the discussion, a new definition of social prescribing, developed through the research, was also introduced. This research contributes to the advancement of the evidence base and provides support to facilitate the implementation and delivery of social prescribing. Additionally, the limitations of this research, and the identified gaps in the evidence base, can inform future research into this area.

As a result of perceived insufficient non-acute care provision, the Government is making efforts to extend primary care hours to reduce the inappropriate utilisation of 999 and A&E services (NHS England, 2013c, 2014b; Kings Fund, 2017). The case management programme was implemented to reduce acute care use in the ageing and multimorbid demographic who are high-intensity service users (DOH, 2005a). However, case management typically has restricted hours of service delivery, which could place unnecessary burden on emergency and acute services during the out-ofhours period. The aim of this study was to understand the patterns of case-managed patients' use of 999 emergency services and presentations at A&E, and hospital admissions, as well as to explore what factors were perceived as influencing patterns of service interaction. Within a pragmatic paradigm, a sequential explanatory mixed methods study was deployed, delivered in five studies. Two cross-sectional observational studies analysed 999 callout (n=2,930, study one) and A&E attendance and hospital admission data (n=16,495, study two). Descriptive statistics were applied, and inferential statistics conducted according to data type. Key stakeholders were interviewed (patients n=19, study three, carers n=19, study four) and three focus groups conducted (case managers n=18, study five). Transcripts were analysed via an analysis spiral using both deductive and inductive approaches (Creswell, 2007). Using a pluralistic framework and previously unexploited flagged patient-level quantitative datasets produced a novel understanding of when, why and how casemanaged patients interact with services. Despite no out-of-hours emergency service burden within studies one and two, twenty-four-hour case management service provision may be required to align with acute services. Quantitative data highlighted that integration and digital interoperability across systems are required to aid admission avoidance and to improve patient experience. Qualitative investigation revealed service contact was seen in places where several parts of the system were seen to be under strain. Person-centred care and shared decision making may also need to be improved when conveyance and admission decisions are made. Case management as a model for admission prevention to manage the ageing and multimorbid population was valued in studies three to five. The inclusion of elderly and housebound participants brought the lived experience of older people to the forefront, highlighting the negative impact of the media in delaying service interactions. This research could be used to inform policy and service-level decisions at the macro- and meso-levels of healthcare. A conceptual model of the factors that contribute to service interaction presents a holistic infographic guide for case management admission prevention.