Advance care planning is being promoted as a central component of end-of-life policies in many developed countries, but there is concern that professionals find its implementation challenging. AimTo assess the feasibility of implementing advance care planning in UK primary care. Design of studyMixed methods evaluation of a pilot educational intervention. SettingFour general practices in south-east Scotland. MethodInterviews with 20 GPs and eight community nurses before and after a practice-based workshop; this was followed by telephone interviews with nine other GPs with a special interest in palliative care from across the UK. ResultsEnd-of-life care planning for patients typically starts as an urgent response to clear evidence of a short prognosis, and aims to achieve a 'good death'. Findings suggest that there were multiple barriers to earlier planning: prognostic uncertainty; limited collaboration with secondary care; a desire to maintain hope; and resistance to any kind of 'tick-box' approach. Following the workshop, participants' knowledge and skills were enhanced but there was little evidence of more proactive planning. GPs from other parts of the UK described confusion over terminology and were concerned about the difficulties of implementing inflexible, policy-driven care. ConclusionA clear divide was found between UK policy directives and delivery of end-of-life care in the community that educational interventions targeting primary care professionals are unlikely to address. Advance care planning has the potential to promote autonomy and shared decision making about end-of-life care, but this will require a significant shift in attitudes. Keywordsadvance care planning; cancer; palliative care; primary health care. INTRODUCTIONAdvance care planning is viewed as an intrinsic component of end-of-life care programmes in many developed countries. In the US, advance directives were originally intended to allow people to record an advance refusal of invasive, life-prolonging interventions.1 The limitations of this approach resulted in a progressive move internationally towards a broader process of advance care planning that also includes discussion of personal goals, wishes, and preferences about future care. [2][3][4] Programmes in the US and Australia that have adopted a regional strategy towards educating professionals, patients, and the general public about advance care planning have had some success. 5,6 Proactive care planning is central to recent UK policies, and the expectation is that it will now be offered to all patients approaching the end of life.

The Gold Standards Framework aims to optimize primary palliative care for patients nearing the end of their lives. This paper critically reviews the impact of the Gold Standards Framework since its introduction in 2001 and indicates direction for further research and development. Literature was accessed using specific databases and by contacting subject area specialists. The resultant literature was appraised using an established framework to evaluate healthcare interventions. Fifteen documents were reviewed. The quality of evidence is constrained by methodological limitations, but consistently demonstrates that the Gold Standards Framework improves general practice processes, co-working and the quality of palliative care. However, implementation of the Gold Standards Framework is variable and the direct impact on patients and carers is not known. We conclude that the Gold Standards Framework has considerable potential to improve end-of-life care, but further work is needed to support uptake and consistency of implementation. Additional evidence about patient and carer outcomes will add to existing insights.

Patients with cancer and their carers believe that there is an important and unique role for primary care in offering continuity of care and information that is patient-centred and holistic, throughout the cancer trajectory, from first presentation. This study successfully brought patient, carer and professional perspectives to the development of a care framework for primary care.

Alzheimer's disease (AD) patients exhibit alterations in the functional connectivity between spatially segregated brain regions which may be related to both local gray matter (GM) atrophy as well as a decline in the fiber integrity of the underlying white matter tracts. Machine learning algorithms are able to automatically detect the patterns of the disease in image data, and therefore, constitute a suitable basis for automated image diagnostic systems. The question of which magnetic resonance imaging (MRI) modalities are most useful in a clinical context is as yet unresolved. We examined multimodal MRI data acquired from 28 subjects with clinically probable AD and 25 healthy controls. Specifically, we used fiber tract integrity as measured by diffusion tensor imaging (DTI), GM volume derived from structural MRI, and the graph-theoretical measures 'local clustering coefficient' and 'shortest path length' derived from resting-state functional MRI (rs-fMRI) to evaluate the utility of the three imaging methods in automated multimodal image diagnostics, to assess their individual performance, and the level of concordance between them. We ran the support vector machine (SVM) algorithm and validated the results using leave-one-out cross-validation. For the single imaging modalities, we obtained an area under the curve (AUC) of 80% for rs-fMRI, 87% for DTI, and 86% for GM volume. When it came to the multimodal SVM, we obtained an AUC of 82% using all three modalities, and 89% using only DTI measures and GM volume. Combined multimodal imaging data did not significantly improve classification accuracy compared to the best single measures alone.

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