Advancing screening tool for hospice needs and end-of-life decision-making process in the emergency department

Abstract

Background: Predicting mortality in the emergency department (ED) is imperative to guide palliative care and end-of-life decisions. However, the clinical usefulness of utilizing the existing screening tools still leaves something to be desired.

Methods: We advanced the screening tool with the A-qCPR (Age, qSOFA (quick sepsis-related organ failure assessment), cancer, Performance Status Scale, and DNR (Do-Not-Resuscitate) risk score model for predicting one-year mortality in the emergency department of Taipei City Hospital of Taiwan with the potential of hospice need and evaluated its performance compared with the existing screening model. We adopted a large retrospective cohort in conjunction with in-time (the trained and the holdout validation cohort) for the development of the A-qCPR model and out-of-time validation sample for external validation and model robustness to variation with the calendar year.

Results: A total of 10,474 patients were enrolled in the training cohort and 33,182 patients for external validation. Significant risk scores included age (0.05 per year), qSOFA ≥ 2 (4), Cancer (5), Eastern Cooperative Oncology Group (ECOG) Performance Status score ≥ 2 (2), and DNR status (2). One-year mortality rates were 13.6% for low (score ≦ 3 points), 29.9% for medium (3 < Score ≦ 9 points), and 47.1% for high categories (Score > 9 points). The AUROC curve for the in-time validation sample was 0.76 (0.74-0.78). However, the corresponding figure was slightly shrunk to 0.69 (0.69-0.70) based on out-of-time validation. The accuracy with our newly developed A-qCPR model was better than those existing tools including 0.57 (0.56-0.57) by using SQ (surprise question), 0.54 (0.54-0.54) by using qSOFA, and 0.59 (0.59-0.59) by using ECOG performance status score. Applying the A-qCPR model to emergency departments since 2017 has led to a year-on-year increase in the proportion of patients or their families signing DNR documents, which had not been affected by the COVID-19 pandemic.

Conclusions: The A-qCPR model is not only effective in predicting one-year mortality but also in identifying hospice needs. Advancing the screening tool that has been widely used for hospice in various scenarios is particularly helpful for facilitating the end-of-life decision-making process in the ED.

Keywords: Decision-making; Emergency department; End of life care; Hospice care; Palliative care; Physical performance; Prognosis; Resuscitation orders; Retrospective study.