Abstract 1888P
Background
The increasing presence of cancer patients in palliative care within emergency departments (ED) worldwide calls for improved care quality. These patients often undergo unnecessary invasive procedures due to challenges in promptly assessing their treatment needs. We developed PalliScore, a rapid assessment tool aimed at helping medical professionals quickly identify palliative care patients in the ED who are less likely to benefit from invasive procedures or ICU admission.
Methods
We retrospectively analyzed data from cancer patients in palliative care admitted to the ED of our hospital in Southeast Brazil, calculating their PalliScore upon admission. This four-step tool incorporates diagnosis of an incurable and life-threatening disease, special care situations (e.g., family or medical team disagreements, uncontrolled symptoms), the “surprise question” (Would you be surprised if this patient died within the next 12 months?), and performance status (ECOG or PPS). Each criterion is scored to reflect the PalliScore, with a threshold of ≥5 suggesting a need to consider limiting invasive interventions after thorough discussion with the patient and healthcare providers.
Results
From March 2021 to July 2023, we assessed 521 patients; 70 (13.68%) received limited intervention care while 449 received intensive care. The average PalliScore was 6.50 for the limited care group and 2.77 for the intensive care group. Statistical analysis using an unpaired t-test showed a significant difference in PalliScore between the groups (odds ratio 3.73, p < 0.0001). Notably, 16.7% of patients with a PalliScore ≥ 5 still received intensive care treatments, whereas 10% of patients with a PalliScore < 5 received limited intervention care.
Conclusions
PalliScore effectively aids ED physicians in making informed decisions regarding invasive procedures and ICU admissions, thereby potentially improving the quality of care for cancer patients in palliative settings. This tool highlights the complex nature of decision-making in palliative care, emphasizing the need for sensitive and individualized patient assessments.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The authors.
Funding
Has not received any funding.
Disclosure
All authors have declared no conflicts of interest.
Resources from the same session
1832P - Physical condition is associated with quality of life in colorectal cancer survivors: Results from a Portuguese and Spanish cohort of patients
Presenter: Luisa Soares Miranda
Session: Poster session 12
1833P - JUMP_START: Optimization of multiprofessional care for young patients with colorectal cancer
Presenter: Kaiyu Xu
Session: Poster session 12
1834P - Accuracy of recommendations by a conversational Artificial Intelligence (AI) cancer mentor application (app): A multi-disciplinary, multi-institutional evaluation report
Presenter: Talia Golan
Session: Poster session 12
1835P - Multi-centre, randomised controlled trial of digital health cancer solution for cancer patients receiving chemotherapy
Presenter: Agnieszka Michael
Session: Poster session 12
1836P - Patient-reported health behaviors (PRHB) among 1850 patients enrolled in a remote patient monitoring (RPM) pathway
Presenter: Maria Alice Franzoi
Session: Poster session 12
1837P - Assessing care complexity in remote patient monitoring (RPM): A cohort study of 2434 cancer patients across 50 sites in France and Belgium
Presenter: Capucine Baldini
Session: Poster session 12
1838P - AI-based smart oncology follow-up system: Prospective application testing and enhancement of clinical efficacy
Presenter: Chunwei Xu
Session: Poster session 12
1839P - Dynamic reporting of treatment related symptoms via ePROs can reversely identify the type of underlying cancer
Presenter: Andreas Trojan
Session: Poster session 12
1840P - Ready for digital health? A national mirror survey exploring the perspectives of both patients and healthcare professionals
Presenter: Florian Scotté
Session: Poster session 12
1841P - Feasibility of wrist-worn health-tracker data to predict the need for therapy modifications in patients with metastatic cancer
Presenter: Anna Sophie Berghoff
Session: Poster session 12