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Background: People with long term conditions (LTCs) make most of the daily decisions and carry out the activities which affect their health and quality of life. Only a fraction of each contact with a health care professional (HCP) is spent supporting this. This paper describes how care and support planning (CSP) and an implementation framework to redesign services, were developed to address this in UK general practice. Focussed on what is important to each individual, CSP brings together traditional clinical issues and the person's lived experience in a solution focussed, forward looking conversation with an emphasis on 'people not diseases'. Methods: The components of CSP were developed in three health communities using diabetes as an exemplar. This model was extended and refined for other single conditions and multimorbidity across 40 sites and two nations, over 15 years. Working with local teams and communities the authors used theoretical models of care, implementation and spread, developing and tailoring training, support and resources to embed CSP as usual care, sharing learning across a community of practice. Results: The purpose, content, process, developmental hurdles and impact of this CSP model are described, alongside an implementation strategy. There is now a robust, reproducible five step model; preparation, conversation, recording, actions and review. Uniquely, preparation, involving information sharing with time for reflection, enables an uncluttered conversation with a professional focussed on what is important to each person. The components of the Year of Care House act as a checklist for implementation, a metaphor for their interdependence and a flexible framework. Spreading CSP involved developing exemplar practices and building capacity across local health communities. These reported improved patient experience, practitioner job satisfaction, health behaviours and outcomes, teamwork, practice organisation, resource use, and links with wider community activities. Conclusions: Tested in multiple settings, CSP is a reproducible and practical model of planned care applicable to all LTCs, with the capacity to be transformative for people with LTCs and health care professionals. It recaptures relational dimensions of care with transactional elements in the background. Options for applying this model and implementation framework at scale now need to be explored. [ABSTRACT FROM AUTHOR]

Background: People are increasingly living for longer with multimorbidity. Medical education and healthcare delivery must be re-orientated to meet the societal and individual patient needs that multimorbidity confers. The impact of multimorbidity on the educational needs of doctors is little understood. There has been little critique of how learning alongside healthcare provision is negotiated by patients, general practitioners and trainee doctors. This study asked ‘what is known about how and why concurrent healthcare delivery and professional experiential learning interact to generate outcomes, valued by patients, general practitioners and trainees, for patients with multimorbidity in primary care?' Methods: This realist synthesis is reported using RAMESES standards. Relationship-centred negotiation of needs-based learning and care was the primary outcome of interest. Healthcare, social science and educational literature were sought as evidence. Data extraction focused on context, mechanism and outcome configurations within studies and on data which might assist understanding and explain; i) these configurations; ii) the relationships between them and; iii) their role and place in evolving programme theories arising from data synthesis. Mind-mapping software and team meetings were used to aid interpretative analysis. Results: The final synthesis included 141 papers of which 34 contained models for workplace-based experiential learning and/or patient care. Models of experiential learning for practitioners and for patient engagement were congruent, frequently referencing theories of transformation and socio-cultural processes as mechanisms for improving clinical care. Key issues included the perceived impossibility of reconciling personalised concepts of success with measurability of clinical markers or adherence to guidelines, and the need for greater recognition of social dynamics between patients, GPs and trainees including the complexities of shared responsibilities. A model for considering the implications of concurrency for learning and healthcare delivery in the context of multimorbidity in primary care is proposed and supporting evidence is presented. Conclusions: This study is novel in considering empirical evidence from patients, GPs and trainees engaged in concurrent learning and healthcare delivery. The findings should inform future interventions designed to produce a medical workforce equipped to provide multimorbidity care. Trial registration: PROSPERO International prospective register of systematic reviews CRD42013003862 [ABSTRACT FROM AUTHOR]

Background: A growing proportion of people are living with long term conditions. The majority have more than one. Dealing with multi-morbidity is a complex problem for health systems: for those designing and implementing healthcare as well as for those providing the evidence informing practice. Yet the concept of multi-morbidity (the presence of >2 diseases) is a product of the design of health care systems which define health care need on the basis of disease status. So does the solution lie in an alternative model of healthcare? Discussion: Strengthening generalist practice has been proposed as part of the solution to tackling multi-morbidity. Generalism is a professional philosophy of practice, deeply known to many practitioners, and described as expertise in whole person medicine. But generalism lacks the evidence base needed by policy makers and planners to support service redesign. The challenge is to fill this practice-research gap in order to critically explore if and when generalist care offers a robust alternative to management of this complex problem. We need practice-based evidence to fill this gap. By recognising generalist practice as a 'complex intervention' (intervening in a complex system), we outline an approach to evaluate impact using action-research principles. We highlight the implications for those who both commission and undertake research in order to tackle this problem. Summary: Answers to the complex problem of multi-morbidity won't come from doing more of the same. We need to change systems of care, and so the systems for generating evidence to support that care. This paper contributes to that work through outlining a process for generating practice-based evidence of generalist solutions to the complex problem of person-centred care for people with multi-morbidity. [ABSTRACT FROM AUTHOR]

Background: In the event of a release of a pathogen such as smallpox, which is human-to-human transmissible and has high associated mortality, a key question is how best to deploy containment and control strategies. Given the general uncertainty surrounding this issue, mathematical modelling has played an important role in informing the likely optimal response, in particular defining the conditions under which mass-vaccination would be appropriate. In this paper, we consider two key questions currently unanswered in the literature: firstly, what is the optimal spatial scale for intervention; and secondly, how sensitive are results to the modelling assumptions made about the pattern of human contacts? Methods: Here we develop a novel mathematical model for smallpox that incorporates both information on individual contact structure (which is important if the effects of contact tracing are to be captured accurately) and large-scale patterns of movement across a range of spatial scales in Great Britain. Results: Analysis of this model confirms previous work suggesting that a locally targeted 'ring' vaccination strategy is optimal, and that this conclusion is actually quite robust for different socio-demographic and epidemiological assumptions. Conclusions: Our method allows for intuitive understanding of the reasons why national mass vaccination is typically predicted to be suboptimal. As such, we present a general framework for fast calculation of expected outcomes during the attempted control of diverse emerging infections; this is particularly important given that parameters would need to be interactively estimated and modelled in any release scenario. [ABSTRACT FROM AUTHOR]