Usefulness of the Surprise Question on an Inpatient Oncology Service

Outpatient palliative care referral system (PCRS) for patients with advanced cancer: an impact evaluation protocol

INTRODUCTION

Early palliative care (PC) in the clinical pathway of advanced cancer patients improves symptom control, quality of life and has a positive impact on overall quality of care. At present, standardised criteria for appropriate referral for early PC in oncology care are lacking. The aim of this project is to develop a set of standardised referral criteria and procedures to implement appropriate early PC for advanced cancer patients (the palliative care referral system, PCRS) and test its impact on user perception of quality of care received, on patient quality of life and on the use of healthcare resources.

SETTING

Selected oncology clinics and PC outpatient clinic.

METHODS AND ANALYSIS

A scoping literature review and an expert consultation through a nominal group technique will be used to revise existing referral tools and to develop a new one, the PCRS. 25 patients will be enrolled in a pilot study to assess feasibility of the implementation of PCRS; 10 interviews with patients and healthcare professionals will be carried out to evaluate applicability.A pretest-post-test quasiexperimental study involving 150 patients before implementation of the PCRS and 150 patients after implementation will be carried out.Patient satisfaction with care received, quality of life and use of resources, and caregiver satisfaction with care will also be assessed to explore the impact of the intervention.

ETHICS AND DISSEMINATION

Ethical approval for the study has been granted by the Institutional Review board of the Fondazione IRCCS Istituto Nazionale Tumori; approval reference INT201/19.Results will be disseminated through open access publications and through scientific communication presented at national and international conferences.

TRIAL REGISTRATION NUMBER

NCT04936568.

Prospective Comparison of Medical Oncologists and a Machine Learning Model to Predict 3-Month Mortality in Patients With Metastatic Solid Tumors

Importance

To date, oncologist and model prognostic performance have been assessed independently and mostly retrospectively; however, how model prognostic performance compares with oncologist prognostic performance prospectively remains unknown.

Objective

To compare oncologist performance with a model in predicting 3-month mortality for patients with metastatic solid tumors in an outpatient setting.

Design, Setting, and Participants

This prognostic study evaluated prospective predictions for a cohort of patients with metastatic solid tumors seen in outpatient oncology clinics at a National Cancer Institute-designated cancer center and associated satellites between December 6, 2019, and August 6, 2021. Oncologists (57 physicians and 17 advanced practice clinicians) answered a 3-month surprise question (3MSQ) within clinical pathways. A model was trained with electronic health record data from January 1, 2013, to April 24, 2019, to identify patients at high risk of 3-month mortality and deployed silently in October 2019. Analysis was limited to oncologist prognostications with a model prediction within the preceding 30 days.

Exposures

Three-month surprise question and gradient-boosting binary classifier.

Main Outcomes and Measures

The primary outcome was performance comparison between oncologists and the model to predict 3-month mortality. The primary performance metric was the positive predictive value (PPV) at the sensitivity achieved by the medical oncologists with their 3MSQ answers.

Results

A total of 74 oncologists answered 3099 3MSQs for 2041 patients with advanced cancer (median age, 62.6 [range, 18-96] years; 1271 women [62.3%]). In this cohort with a 15% prevalence of 3-month mortality and 30% sensitivity for both oncologists and the model, the PPV of oncologists was 34.8% (95% CI, 30.1%-39.5%) and the PPV of the model was 60.0% (95% CI, 53.6%-66.3%). Area under the receiver operating characteristic curve for the model was 81.2% (95% CI, 79.1%-83.3%). The model significantly outperformed the oncologists in short-term mortality.

Conclusions and Relevance

In this prognostic study, the model outperformed oncologists overall and within the breast and gastrointestinal cancer cohorts in predicting 3-month mortality for patients with advanced cancer. These findings suggest that further studies may be useful to examine how model predictions could improve oncologists' prognostic confidence and patient-centered goal-concordant care at the end of life.

How Well Does the Surprise Question Predict 1-year Mortality for Patients Admitted with COPD?

BACKGROUND

Patients with chronic obstructive pulmonary disease (COPD) often receive burdensome care at end-of-life (EOL) and infrequently complete advance care planning (ACP). The surprise question (SQ) is a prognostic tool that may facilitate ACP.

OBJECTIVE

To assess how well the SQ predicts mortality and prompts ACP for COPD patients.

DESIGN

Retrospective cohort study.

SUBJECTS

Patients admitted to the hospital for an acute exacerbation of COPD between July 2015 and September 2018.

MAIN MEASURES

Emergency department (ED) and inpatient clinicians answered, "Would you be surprised if this patient died in the next 30 days (ED)/one year (inpatient)?" The primary outcome measure was the accuracy of the SQ in predicting 30-day and 1-year mortality. The secondary outcome was the correlation between SQ and ACP (palliative care consultation, documented goals-of-care conversation, change in code status, or completion of ACP document).

KEY RESULTS

The 30-day SQ had a high specificity but low sensitivity for predicting 30-day mortality: sensitivity 12%, specificity 95%, PPV 11%, and NPV 96%. The 1-year SQ demonstrated better accuracy for predicting 1-year mortality: sensitivity 47%, specificity 75%, PPV 35%, and NPV 83%. After multivariable adjustment for age, sex, and prior 6-month admissions, 1-year SQ+ responses were associated with greater odds of 1-year mortality (OR 2.38, 95% CI 1.39-4.08) versus SQ-. One-year SQ+ patients were more likely to have a goals-of-care conversation (25% vs. 11%, p < 0.01) and complete an advance directive or POLST (46% vs. 23%, p < 0.01). After multivariable adjustment, SQ+ responses to the 1-year SQ were associated with greater odds of ACP receipt (OR 2.67, 95% CI 1.64-4.36).

CONCLUSIONS

The 1-year surprise question may be an effective component of prognostication and advance care planning for COPD patients in the inpatient setting.