UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Accuracy of clinical predictions of prognosis at the end-of-life: evidence from routinely collected data in urgent care records

Orlovic, M; Droney, J; Vickerstaff, V; Rosling, J; Bearne, A; Powell, M; Riley, J; ... Stone, P; + view all (2023) Accuracy of clinical predictions of prognosis at the end-of-life: evidence from routinely collected data in urgent care records. BMC Palliative Care , 22 (1) , Article 51. 10.1186/s12904-023-01155-y. Green open access

[thumbnail of Accuracy of clinical predictions of prognosis at the end-of-life evidence from routinely collected data in urgent care recor.pdf]
Preview
PDF
Accuracy of clinical predictions of prognosis at the end-of-life evidence from routinely collected data in urgent care recor.pdf - Published Version

Download (1MB) | Preview

Abstract

BACKGROUND: The accuracy of prognostication has important implications for patients, families, and health services since it may be linked to clinical decision-making, patient experience and outcomes and resource allocation. Study aim is to evaluate the accuracy of temporal predictions of survival in patients with cancer, dementia, heart, or respiratory disease. METHODS: Accuracy of clinical prediction was evaluated using retrospective, observational cohort study of 98,187 individuals with a Coordinate My Care record, the Electronic Palliative Care Coordination System serving London, 2010-2020. The survival times of patients were summarised using median and interquartile ranges. Kaplan Meier survival curves were created to describe and compare survival across prognostic categories and disease trajectories. The extent of agreement between estimated and actual prognosis was quantified using linear weighted Kappa statistic. RESULTS: Overall, 3% were predicted to live "days"; 13% "weeks"; 28% "months"; and 56% "year/years". The agreement between estimated and actual prognosis using linear weighted Kappa statistic was highest for patients with dementia/frailty (0.75) and cancer (0.73). Clinicians' estimates were able to discriminate (log-rank p < 0.001) between groups of patients with differing survival prospects. Across all disease groups, the accuracy of survival estimates was high for patients who were likely to live for fewer than 14 days (74% accuracy) or for more than one year (83% accuracy), but less accurate at predicting survival of "weeks" or "months" (32% accuracy). CONCLUSION: Clinicians are good at identifying individuals who will die imminently and those who will live for much longer. The accuracy of prognostication for these time frames differs across major disease categories, but remains acceptable even in non-cancer patients, including patients with dementia. Advance Care Planning and timely access to palliative care based on individual patient needs may be beneficial for those where there is significant prognostic uncertainty; those who are neither imminently dying nor expected to live for "years".

Type: Article
Title: Accuracy of clinical predictions of prognosis at the end-of-life: evidence from routinely collected data in urgent care records
Location: England
Open access status: An open access version is available from UCL Discovery
DOI: 10.1186/s12904-023-01155-y
Publisher version: https://doi.org/10.1186/s12904-023-01155-y
Language: English
Additional information: This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third-party material in this article are included in the Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
Keywords: Advance care planning, Death, Dementia, Heart diseases, Lung diseases, Neoplasms, Palliative care, Prognosis, Humans, Retrospective Studies, Routinely Collected Health Data, Prognosis, Palliative Care, Neoplasms, Death, Dementia
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Division of Psychiatry
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Epidemiology and Health
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Epidemiology and Health > Primary Care and Population Health
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Division of Psychiatry > Marie Curie Palliative Care
URI: https://discovery.ucl.ac.uk/id/eprint/10169626
Downloads since deposit
14Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item