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Background: The provision of palliative care for severe COPD remains low, resulting in unmet needs in patients and carers.Research Questions: What are the palliative care needs of patients living with severe COPD and their caregivers? What views of accessing and providing palliative care and factors influence these experiences. To what extent have palliative care and COPD services been integrated?Study Design and Methods: A multicentre qualitative study was undertaken in COPD services and specialist palliative care in the United Kingdom involving patients with severe COPD, their carers, and health professionals. Data were collected using semistructured interviews and were analyzed using framework analysis. Themes were integrated using the constant comparison process, enabling systematic data synthesis.Results: Four themes were generated from interviews with 20 patients, six carers, and 25 health professionals: management of exacerbations, palliative care needs, access to palliative care and pathways, and integration of palliative care support. Uncertainty and fear were common in patients and carers, with identified needs for reassurance, rapid medical access, home care, and finance advice. Timely palliative care was perceived as important by health professionals. Palliative care was integrated into COPD services, although models of working varied across regions. Reliable screening tools and needs assessment, embedded psychological care, and enhanced training in palliative care and communication skills were perceived to be important by health professionals for timely palliative care referrals and optimized management.Interpretation: Palliative care increasingly is being implemented for nonmalignant diseases including COPD throughout the United Kingdom, although models of working vary. A theoretical model was developed to illustrate the concept and pathway of the integration of palliative care support. A standardized screening and needs assessment tool is required to improve timely palliative care and to address the significant needs of this population. [ABSTRACT FROM AUTHOR]

Introduction: A significant amount of research on palliative care (PC) has demonstrated the benefits of identification for a timely referral as well as enabling an integrated care approach. However, the prompt identification of PC in clinical practice has been a challenge. Despite PC needs may differ widely between patients, a short survival prediction is one of the most common proxies to start PC conversations, therefore predicting if the death will occur within the next year has a real value when screening for patients who may benefit from PC. Our objective was to create a clinical decision support system called Aleph to support healthcare providers in their screening for patients with PC needs. Aleph incorporates different quantitative and data-driven predictive services based on machine learning technology and electronic health records (EHR) data. Methods: Two machine learning services have been developed using retrospective hospital admission data from the EHR (39,310 episodes from 19,753 different patients; age >= 65). The first service incorporated three models: t models: a one-year mortality classifier, a mortality regressor, and a one-year frailty status classifier. The second service incorporated a compact and minimalist version of the one-year mortality models using only common variables. We validated Aleph's usability and user experience using a user-centred methodology involving 21 healthcare providers from six countries. Results: The models on the first service reported an area under the ROC curve (AUC-ROC) of 0.87 for the one-year mortality classifier, 94.67 days of mean absolute error for the regression model, and 0.89 of AUC-ROC for the one-year frailty classifier. The compact model on the second service reported an AUC-ROC of 0.83. Aleph made a great impression among the validation participants and scored 65 over 100 points on System Usability Scale and 1.5 over 3 in the User Experience Questionnaire-Short. Discussion: Aleph was developed as a multi-purpose clinical decision support system web application. Its design allows the incorporation of further integrated care services, even out of the realm of the PC. We have incorporated two PC services based on powerful predictive models. Documentation to create a new predicted service will be openly distributed to encourage researchers to contribute to the Aleph so their predictive models could be incorporated immediately into a usability-validated platform. Conclusion: Our contribution to the identification of patients who may benefit from PC are two predictive services with high predictive power models and a user-centred validated platform. These allow the integration of this outcome with other services available to address patients' needs as well as to 'plug and play' other predictive services. Implications for applicability and limitations: The use of Aleph can improve the detection of patients in need of PC, helping physicians and hospital administrators to address the growing demand for PC and improving the patient's care. The main limitation of the study is the lack of validation of the predictive model with other data sources. [ABSTRACT FROM AUTHOR]

Introduction: Early palliative care (PC) has proven to be effective on improving patients' quality of life and symptoms control. However, most of the research has been focused on oncological patients. In this sense, the InAdvance project (825750) addresses early PC among older patients with non-malignant diseases. A needs assessment (NAT:PD) intervention is being performed under a clinical trial in four European sites (ISRCTN24825698): Valencia-Spain, Thessaloniki-Greece, Lisbon-Portugal and Highland-Scotland. The aim of this study is to explore the acceptability, feasibility and attitudes of key health and care professionals (HCPs) around the implementation of the NAT:PD. Methods: HCPs involved in the implementation of the NAT:PD intervention participated in this qualitative study through individual interviews or focus groups. The interview guide was designed using the Consolidated Framework for Implementation Research (CFIR), which is a robust model for systematically assessing potential barriers and facilitators in preparation for the implementation of an intervention. Data was analysed using grounded theory. Results: 29 HCPs participated in this study, which were mostly women (62%) and the average age was 42.6 years. All respondents replied positively to the implementation of the NAT:PD intervention in their settings. All considered it as useful and necessary to improve their work with chronically ill patients to timely detect their needs in a systematic manner. Some sites already had resources or services that the intervention could be aligned with and for others the NAT:PD would be a notable resource to fill gaps in their current work. Lack of integration with other services and multidisciplinary professionals - such as primary care or psychologists - was detected as a relevant concern. Also, all HCPs highlighted potential time constraints and fatigue due to COVID19 pandemic as barriers as most of the participants felt exhausted after these complicated months. However, most of them expressed enthusiasm with this new intervention as it was considered of great relevance for their units and patients. Conclusions: In general, the four sites considered the early intervention as relevant to address the needs of their patients and also as an asset to reinforce their current resources. However, there were significant differences between sites in the level of information provided and the detail on implementation plans that HCPs disposed to run the trial. Additionally, addressing the needs detected under the NAT:PD require integrated, comprehensive and continuity care throughout the whole care system and with the involvement of multidisciplinary and multilevel services. Implications for transferability, sustainability and limitations: We recommend that clear and detailed materials and trainings are offered to those HCPs in charge of the implementation of NAT:PD that can increase their confidence and decrease anxiety. Also, it is crucial to have proper connections and alliances with different health and care services and stakeholders to make effective referrals of patients in accordance to their needs. [ABSTRACT FROM AUTHOR]

The implementation of a palliative and supportive care plan across community hospitals in the Grampian region of north east Scotland provided an opportunity to confirm the important role staff play in palliative and end of life care. Contact was made with the senior nurse in all 32 wards in the community hospitals and a series of monthly visits arranged. This ensured a staged introduction to the plan to facilitate understanding and implementation. Reviews were collated on 130 deaths (77% of all the deaths during the project). These revealed examples of good practice, as well as the challenges faced by staff working in community hospitals. The results show that staff are often involved in the delivery of palliative care and demonstrate the benefits of providing end of life care to people close to home. The earlier identification of the palliative phase of an illness may encourage further anticipatory care planning. [ABSTRACT FROM AUTHOR]

Background: Undergraduate education in palliative care is essential if doctors are to be competent to care for dying patients and their families in a range of specialties and healthcare settings. However, creating space for this within existing undergraduate and foundation year curricula poses significant challenges. We aimed to develop consensus learning outcomes for palliative care teaching in the university medical schools in Scotland. Methods: The General Medical Council (GMC) outlines a number of learning outcomes with clear relevance to palliative care. Leaders from the five Scottish medical schools identified and agreed a small number of outcomes, which we judged most relevant to teaching palliative care and collated teaching resources to support these. Results: Consensus learning outcomes for undergraduate palliative care were agreed by our mixed group of clinician educators over a number of months. There were many secondary gains from this process, including the pooling of educational resources and best practice, and the provision of peer support for those struggling to establish curriculum time for palliative care. Discussion: The process and outcomes were presented to the Scottish Teaching Deans, with a view to their inclusion in undergraduate and foundation year curricula. It is through a strong commitment to achieving these learning outcomes that we will prepare all doctors for providing palliative care to the increasing numbers of patients and families that require it. [ABSTRACT FROM AUTHOR]

Palliative care is an alternative to standard care for gravely ill patients that has demonstrated many clinical benefits in cost-effective interventions. It is expected to grow in demand soon, so it is necessary to detect those patients who may benefit from these programs using a personalised objective criterion at the correct time. Our goal was to develop a responsive and minimalist web application embedding a 1-year mortality explainable predictive model to assess palliative care at bedside consultation. A 1-year mortality predictive model has been trained. We ranked the input variables and evaluated models with an increasing number of variables. We selected the model with the seven most relevant variables. Finally, we created a responsive, minimalist and explainable app to support bedside decision making for older palliative care. The selected variables are age, medication, Charlson, Barthel, urea, RDW-SD and metastatic tumour. The predictive model achieved an AUC ROC of 0.83 [CI: 0.82, 0.84]. A Shapley value graph was used for explainability. The app allows identifying patients in need of palliative care using the bad prognosis criterion, which can be a useful, easy and quick tool to support healthcare professionals in obtaining a fast recommendation in order to allocate health resources efficiently. [ABSTRACT FROM AUTHOR]

Background: The last WHO definition of palliative care (PC) recognizes the integration of early PC in the course of illness and in conjunction with other therapies that are intended to treat disease as the way to provide optimal care. There is wide literature highlighting the benefits of early implementation of PC in oncological patients and there is a growing recognition of PC as an integral aspect of cancer treatment with the establishment of a range of specific guidelines concerning palliative cancer care. Nevertheless, these advances are not developed to the same extent in the approach of non-oncological chronic conditions. In this regard, patients of non-cancer diseases are rarely offered these services and even when they are admitted to a PC unit they are typically closer to death and have a lower functional level than those with cancer. It is important to highlight this situation as the great majority of adults in need of PC die from non-oncological diseases - such as cardiovascular diseases, chronic respiratory diseases or diabetes - accounting a higher percentage than those with cancer. Aims and objectives: INADVANCE project (funded under the H2020 Programme) seeks an earlier, integrated and more effective implementation of PC to adequately address the needs of nononcological chronic patients. Thus, this workshop is focused on early PC among patients with chronic conditions. This analysis will be encouraged by presenting the current state of early PC among this profile of patients, some experiences in their management at different healthcare systems. Finally, at the end of the workshop a common discussion between all presenters and attendants will be performed in order to analyze main barriers and facilitators to organize and implement PC services addressed to chronic complex patients. Format: A 90-minutes workshop session will be organized in order to achieve the aforementioned objectives. Two people from INADVANCE project will be in charge of organizing and running the workshop with the participation of the following speakers in these topics: "Introduction" (5min): outline of the main objectives and structure of the session (Ascensión Doñate). "Early PC for patients with complex chronic conditions" (10min): presentation of INADVANCE project, the current state of the art of PC services among non-oncological chronic conditions, how to identify patients in need of PC (Ascensión Doñate). "Experiences in the provision of PC among non-oncological conditions" (40min): five presentations of local experiences (Soledad Giménez, Vania Dimitrova, Panagiotis Bamidis, Adriano Fernandes & Gordon Linklater). Time for questions. "Barriers and facilitators to effectively implement PC" (30min): open discussion with speakers and attendants to the workshop (Soledad Giménez). For this session several materials will be arranged, such as a boards, markers or post-it. "Sum up" (5min): main conclusions (Ascensión Doñate). Target audience: People interested in PC, care and management of chronic conditions at clinical and organizational level. Learnings: Workshop participants will learn about differences in the provision of integrated PC between cancer vs. non-cancer diseases, real experiences improving the PC of chronic complex conditions and challenges for future improvement. [ABSTRACT FROM AUTHOR]

The article discusses the administration of the assessment tool Palliative Performance Scale at the regional health board NHS Grampian in Scotland effective 2008 originating from Victoria Hospice in Canadal. Topics covered include the benefits of the initiative identifying patient requirements, assisting nurses in evaluating the care provided, and a means in providing patient information. Also mentioned are the tiers in palliative care.

Palliative care (PC) has demonstrated benefits for life-limiting illnesses. Bad survival prognosis and patients' decline are working criteria to guide PC decision-making for older patients. Still, there is not a clear consensus on when to initiate early PC. This work aims to propose machine learning approaches to predict frailty and mortality in older patients in supporting PC decision-making. Predictive models based on Gradient Boosting Machines (GBM) and Deep Neural Networks (DNN) were implemented for binary 1-year mortality classification, survival estimation and 1-year frailty classification. Besides, we tested the similarity between mortality and frailty distributions. The 1-year mortality classifier achieved an Area Under the Curve Receiver Operating Characteristic (AUC ROC) of 0.87 [0.86, 0.87], whereas the mortality regression model achieved an mean absolute error (MAE) of 333.13 [323.10, 342.49] days. Moreover, the 1-year frailty classifier obtained an AUC ROC of 0.89 [0.88, 0.90]. Mortality and frailty criteria were weakly correlated and had different distributions, which can be interpreted as these assessment measurements are complementary for PC decision-making. This study provides new models that can be part of decision-making systems for PC services in older patients after their external validation.