Objectives: Impending death is poorly recognised. Many undergraduate healthcare professionals will not have experience of meeting or caring for someone who is dying. As death can occur in any setting, at any time, it is vital that all healthcare students, regardless of the setting they go on to work in, have end-of-life care (EOLC) training. The aim was to determine current palliative care training at the undergraduate level, in multiple professions, in recognising and communicating dying.
Methods: Current UK undergraduate courses in medicine, adult nursing, occupational therapy, social work and physiotherapy were included. All courses received an email asking what training is currently offered in the recognition and communication of dying, and what time was dedicated to this.
Results: A total of 73/198 (37%) courses responded to the request for information. 18/20 medical courses provided training in recognising when patients were dying (median 2 hours), and 17/20 provided training in the communication of dying (median 3 hours). 80% (43/54) of nursing and allied health professional courses provided some training in EOLC. Many of the course organisers expressed frustration at the lack of resources, funding and time to include more training. Those courses with more palliative care provision often had a ‘champion’ to advocate for it.
Conclusions: Training in EOLC was inconsistent across courses and professions. Further research is needed to understand how to remove the barriers identified and to improve the consistency of current training.
Background: Recognising dying is a key clinical skill for doctors, yet there is little training.
Aim: To assess the effectiveness of an online training resource designed to enhance medical students’ ability to recognise dying.
Design: online multicentre double-blind randomised controlled trial (NCT03360812). The training resource for the intervention group was developed from a group of expert palliative care doctors’ weightings of various signs/symptoms to recognise dying. The control group received no training.
Setting/participants: Participants were senior UK medical students. They reviewed 92 patient summaries and provided a probability of death within 72 hours (0% certain survival – 100% certain death) pre, post, and 2 weeks after the training. Primary outcome: (1) Mean Absolute Difference (MAD) score between participants’ and the experts’ scores, immediately post intervention. Secondary outcomes: (2) weight attributed to each factor, (3) learning effect and (4) level of expertise (Cochran–Weiss–Shanteau (CWS)).
Results: Out of 168 participants, 135 completed the trial (80%); 66 received the intervention (49%). After using the training resource, the intervention group had better agreement with the experts in their survival estimates (dMAD = -3.43, 95% CI -0.11 to -0.34, p = <0.001) and weighting of clinical factors. There was no learning effect of the MAD scores at the 2-week time point (dMAD = 1.50, 95% CI -0.87 to 3.86, p = 0.21). At the 2-week time point, the intervention group was statistically more expert in their decision-making versus controls (intervention CWS = 146.04 (SD 140.21), control CWS = 110.75 (SD 104.05); p = 0.01).
Conclusion: The online training resource proved effective in altering the decision-making of medical students to agree more with expert decision-making.
Objectives The aims of this study were (1) to document the clinical condition of patients considered to be in the last 2 weeks of life and (2) to compare patients who did or did not survive for 72 hours.
Design A prospective observational study.
Setting Two sites in London, UK (a hospice and a hospital palliative care team).
Participants Any inpatient, over 18 years old, English speaking, who was identified by the palliative care team as at risk of dying within the next 2 weeks was eligible.
Outcome measures Prognostic signs and symptoms were documented at a one off assessment and patients were followed up 7 days later to determine whether or not they had died.
Results Fifty participants were recruited and 24/50 (48%) died within 72 hours of assessment. The most prevalent prognostic features observed were a decrease in oral food intake (60%) and a rapid decline of the participant’s global health status (56%). Participants who died within 72 hours had a lower level of consciousness and had more care needs than those who lived longer. A large portion of data was unavailable, particularly that relating to the psychological and spiritual well-being of the patient, due to the decreased consciousness of the patient.
Conclusions The prevalence of prognostic signs and symptoms in the final days of life has been documented between those predicted to die and those who did not. How doctors make decisions with missing information is an area for future research, in addition to understanding the best way to use the available information to make more accurate predictions.
OBJECTIVES: To identify a group of palliative care doctors who perform well on a prognostic test and to understand how they make their survival predictions.
DESIGN: Prospective observational study and two cross-sectional online studies.
SETTING: Phase I: an online prognostic test, developed from a prospective observational study of patients referred to palliative care. Phase II: an online judgement task consisting of 50 hypothetical vignettes.
PARTICIPANTS: All members of the Association of Palliative Medicine (APM) were eligible (n=~1100). 99 doctors completed the prognostic test and were included in the phase I analysis. The top 20% were invited to participate in phase II; 14/19 doctors completed the judgement task and were included in the phase II analysis.
MEASURES: Phase I: participants were asked to give a probability of death within 72 hours (0%–100%) for all 20 cases. Accuracy on the prognostic test was measured with the Brier score which was used to identify the ‘expert’ group (scale range: 0 (expert)–1 (non-expert)). Phase II: participants gave a probability of death within 72 hours (0%–100%). A mixed model regression analysis was completed using the percentage estimate as the outcome and the patient information included in the vignettes as the predictors.
RESULTS: The mean Brier score of all participants was 0.237 (95% CI 0.235 to 0.239). The mean Brier score of the ‘experts’ was 0.184 (95% CI 0.176 to 0.192). Six of the seven prognostic variables included in the hypothetical vignettes were significantly associated with clinician predictions of death. The Palliative Performance Score was identified as being the most influential in the doctors’ prognostic decision making (ß=0.48, p<0.001).
CONCLUSIONS: This study identified six clinical signs and symptoms which influenced the judgement policies of palliative care doctors. These results may be used to teach novice doctors how to improve their prognostic skills.
Les auteurs de l'article discutent à propos de la fatigue liée au cancer, du rôle des interventions médicamenteuses et non-médicamenteuses, ainsi que de la preuve des méta-analyses concernant leur efficacité et l'utilisation potentielle dans la pratique clinique.