Stephen Mason

Palliative care education in undergraduate medical curricula has historically lacked structured outcomes and measurable indicators, resulting in significan

Background: The use of artificial intelligence (AI) methods in palliative care research is increasing. Most AI palliative care research involves the use of routinely collected data from electronic health records; however, there are few data on the views of palliative care health care professionals on the role of AI in practice. Determining the opinions of palliative care health care professionals on the potential uses of AI in palliative care will be useful for policymakers and practitioners to determine and inform the meaningful use of AI in palliative care practice. Objective: This study aimed to explore the views of palliative care health care professionals on the use of AI for the analysis of patient data in palliative care. Methods: This was a phenomenological study using qualitative semistructured interviews with palliative care health care professionals with a minimum of 1 year of clinical experience in a hospice in the North West of England. Data were analyzed using inductive thematic analysis. Results: We interviewed 6 palliative care professionals, including physicians, nurses, and occupational therapists. AI was viewed positively, although most participants had not used it in practice. None of the participants had received training in AI and stated that education in AI would be beneficial. Participants described the potential benefits of AI in palliative care, including the identification of people requiring palliative care interventions and the evaluation of patient experiences. Participants highlighted security and ethical concerns regarding AI related to data governance, efficacy, patient confidentiality, and consent issues. Conclusions: This study highlights the importance of staff perceptions of AI in palliative care. Our findings support the role of AI in enhancing care, addressing educational needs, and tackling trust, ethics, and governance issues. This study lays the groundwork for guidelines on AI implementation, urging further research on the methodological, ethical, and practical aspects of AI in palliative care.

Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet #Preprint #PeerReviewMe: Warning: This is a unreviewed preprint. Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn. Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period. Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author). Background: The use of artificial intelligence (AI) methods in palliative care research is increasing. Most AI palliative care research involves the use of routinely collected data from electronic health records; however, there are few data on the views of palliative care health care professionals on the role of AI in practice. Determining the opinions of palliative care health care professionals on the potential uses of AI in palliative care will be useful for policymakers and practitioners to determine and inform the meaningful use of AI in palliative care practice. Objective: This study aimed to explore the views of palliative care health care professionals on the use of AI for the analysis of patient data in palliative care. Methods: This was a phenomenological study using qualitative semistructured interviews with palliative care health care professionals with a minimum of 1 year of clinical experience in a hospice in the North West of England. Data were analyzed using inductive thematic analysis. Results: We interviewed 6 palliative care professionals, including physicians, nurses, and occupational therapists. AI was viewed positively, although most participants had not used it in practice. None of the participants had received training in AI and stated that education in AI would be beneficial. Participants described the potential benefits of AI in palliative care, including the identification of people requiring palliative care interventions and the evaluation of patient experiences. Participants highlighted security and ethical concerns regarding AI related to data governance, efficacy, patient confidentiality, and consent issues. Conclusions: This study highlights the importance of staff perceptions of AI in palliative care. Our findings support the role of AI in enhancing care, addressing educational needs, and tackling trust, ethics, and governance issues. This study lays the groundwork for guidelines on AI implementation, urging further research on the methodological, ethical, and practical aspects of AI in palliative care.

Background The use of Artificial Intelligence (AI) methods in palliative care research is increasing. Most AI palliative care research involves the use of routinely collected data from electronic healthcare records patient data; however, there is little data about the of the views of palliative care healthcare professionals on the role of AI in practice. Determining the opinions of palliative care healthcare professionals on potential uses of AI in palliative care will be useful for policymakers and practitioners to determine, and inform, meaningful use of AI in palliative care practice. Aim To explore palliative care healthcare professionals’ views on the use of AI for analysis of patient data in palliative care. Methods Phenomenological study using qualitative semi-structured interviews of palliative care healthcare professionals with a minimum of one-year clinical experience in a hospice in the Northwest of England. Data were analysed using inductive thematic analysis. Results We interviewed six palliative care professionals comprising of doctors, nurses and occupational therapies. AI was viewed positively, although most participants had not used this in practice. No participants had received training in AI and said that education in AI would be beneficial. Participants described potential benefits of palliative care AI, which included identification of people requiring palliative care interventions, and to evaluate patient experience. Participants highlighted security and ethical concerns of AI, related to data governance, efficacy, patient confidentiality and consent issues. Conclusions This study highlights the importance of staff perceptions of AI in palliative care. Our findings support the role of AI in enhancing care, addressing education needs, and tackling trust, ethics, and governance issues. This study lays the groundwork for guidelines on AI implementation, urging further research on methodological, ethical, and practical aspects of AI in palliative care. What is already known about this topic? The use of Artificial Intelligence (AI) methods in palliative care research is increasing. Most AI palliative care research involves the use of routinely collected data from electronic healthcare records patient data There is little data about the of the views of palliative care healthcare professionals on the role of AI in practice. What this paper adds This study provides an overview of the views of specialist palliative healthcare professionals about AI in palliative care, which adds knowledge to a limited evidence base. Concerning the use of AI in palliative care, it is important to consider the opportunities of its use, the education needs of staff, the importance of human connection, and practical issues relating to trust and ethics. Implications for practice, theory or policy Future research on palliative care AI should establish standardised reporting for AI studies, seek external validation, and consider ethical issues, which are needed to ensure palliative care AI is safe, fair and reliable. Future research should explore the views (about palliative care AI) from different perspectives, including the multidisciplinary team, management, patients, caregivers and other relevant stakeholders.

Background: Volunteer services that provide direct support to patients receiving palliative and end-of-life care in hospitals are new and developing, but little is known about the use and experience of such services from key stakeholders. Aim: Explore the perceptions of volunteers, and healthcare professionals, towards newly established hospital end-of-life-care volunteer services, in five countries. Design: A phenomenological approach was adopted, using focus group interviews. Data were analysed using an adapted framework analysis. Setting/participants: Acute hospital in-patient units, in five European countries. Participants were recruited if they were: Volunteers from the end-of-life-care volunteer service, or Healthcare professionals working within the wards that the volunteer service is operational. Results: 20 Volunteers and 20 healthcare professionals were recruited. Most participants were female (70%, n = 14/65%, n = 13). The healthcare professionals included a majority nurses (60%). Three overall themes were generated: (1) Volunteers provided ‘unique, distinct, ‘community’ support’ bringing familiarity to an unfamiliar, medically focussed environment. (2) Volunteers were able to ‘establish a connection centred on ‘being there’ within the acute hospital environment’ despite the fast paced and highly changeable environment. (3) Through ‘relational interactions adapted to the individual person’ volunteers attended to patients’ existential and emotional needs. Conclusion: These services confer benefits that are transferrable across cultures and countries, ‘fusing’ formal care with the informal visiting of family or friends, attending to patients’ existential needs. Recommendations include exploring ways to embed the end-of-life care volunteer service into this unique environment, alongside continuing research to explore cultural differences across different countries.

Background: Accurately recognizing that a person may be dying is central to improving their experience of care at the end-of-life. However, predicting dying is frequently inaccurate and often occurs only hours or a few days before death. Methods: We performed urinary metabolomics analysis on patients with lung cancer to create a metabolite model to predict dying over the last 30 days of life. Results: Here we show a model, using only 7 metabolites, has excellent accuracy in the Training cohort n = 112 (AUC = 0·85, 0·85, 0·88 and 0·86 on days 5, 10, 20 and 30) and Validation cohort n = 49 (AUC = 0·86, 0·83, 0·90, 0·86 on days 5, 10, 20 and 30). These results are more accurate than existing validated prognostic tools, and uniquely give accurate predictions over a range of time points in the last 30 days of life. Additionally, we present changes in 125 metabolites during the final four weeks of life, with the majority exhibiting statistically significant changes within the last week before death. Conclusions: These metabolites identified offer insights into previously undocumented pathways involved in or affected by the dying process. They not only imply cancer’s influence on the body but also illustrate the dying process. Given the similar dying trajectory observed in individuals with cancer, our findings likely apply to other cancer types. Prognostic tests, based on the metabolites we identified, could aid clinicians in the early recognition of people who may be dying and thereby influence clinical practice and improve the care of dying patients.

Introduction: The remote delivery of dementia-related support services by information communication technology, defined as any hardware or software, including the telephone and videoconferencing software, increased during the coronavirus pandemic. To guide the future use of information communication technology, this study explored the experiences of delivering and accessing social care and support services during the pandemic in the UK. Method: Remote semi-structured interviews with social care and support providers, people with dementia and family carers were conducted between May-December 2022. Topic guides were co-developed with two public advisors (one former family carer, one person with dementia) and garnered information on delivering and accessing services during the pandemic. Audio recordings were transcribed verbatim. Employing a mixture of inductive and deductive analytic approaches, a thematic analysis was conducted. Results: Twenty-one interviews ( n = 14 social care and support providers; n = 6 family carers; n = 2 people with dementia) were conducted. Three themes were generated: adapting to changing circumstances; responding to unmet needs by information communication technology and information communication technology should be a tool, not the default. Social care and support providers’ creativity and motivation facilitated the adoption of information communication technology, however, available resources and guidance varied. While some people with dementia and family carers benefitted from accessing services by information communication technology to address some needs, the format was not suitable for everyone. Conclusions: Beyond the coronavirus pandemic, the use of information communication technology within service delivery needs to be carefully considered, to avoid disenfranchising some people with dementia and family carers, while empowering people with the option of how to access services. Digital training and guidelines advising the use of information communication technology within service delivery may facilitate its improved use during the current landscape, and amidst future pandemics.

Background: Understanding the principles and practice of research by health care professionals helps to improve the evidence base for palliative care practice and service delivery. Research is a core competency in palliative care that enables the identification and addressing of problems for patients and their families, establishes best practice and improves ways to manage pain, other symptoms, and concerns. This work was undertaken in the research for all palliative care clinicians (RESPACC) Erasmus+ project. Aim: To identify and develop a set of core research competencies within a structured framework for all members of the multidisciplinary palliative team. Design: A multi-method approach was used including rapid review of literature, Nominal Group Technique, and expert consultation. A quiz to self-assess research competencies outlined within the Framework was produced. Results: The Framework includes 17 competencies organized in 7 domains: The clinical context, Scientific thinking and research design, Ethics and regulatory framework for research, Study and site management, Data management and informatics, Communication and relationships, and Research leadership. In the consultation process 6 of the 17 competencies were considered as required by each individual team member, and 3 to be present within the palliative care team. Conclusion: Using a multi-method approach, the first Palliative Care Research Framework identifying core research competencies for palliative care clinicians has been developed. The aim of the framework was not to transform palliative care clinicians into researchers, but to ensure that clinicians understand the important role of research and its integration into clinical practice.