Identifying Oncology Patients at High Risk for Potentially Preventable Emergency Department Visits Using a Novel Definition.

Abstract

Purpose: Patients with cancer visit the emergency department (ED) frequently. While some ED visits are necessary, others may be potentially preventable ED visits (PPEDs). Reducing PPEDs is important to improve quality of care and reduce costs. However, a robust definition and the characteristics of patients at risk remain unclear. This study aimed to describe oncology-related PPEDs and identify characteristics of patients at the highest risk for PPEDs to help target interventions and minimize avoidable ED visits.

Methods: A retrospective study was conducted using four clinical and administrative databases. All ED visits by oncology patients between April 1, 2019, and April 1, 2021, were identified. A novel definition of PPEDs was explored, specifically visits that resulted in immediate discharge from the ED or admissions <48 hours. Trends in ED use, including PPEDs, were evaluated using descriptive statistics, logistic regression, and machine learning (ML) modeling.

Results: During the 2-year period, 6,689 oncology patients visited the ED (N = 13,415 visits). A total of 62.1% of visits were classified as PPEDs. PPEDs were most common among patients with stage I to III breast cancer and those on systemic therapy. Characteristics of patients at high risk for non-PPEDs included stage IV disease with either lung or GI carcinomas and shorter distances to the ED. The highest-performing ML model yielded an AUC of 0.819.

Conclusion: Our novel definition of PPEDs appears promising in identifying oncology patients who could avoid the ED with targeted interventions. This work demonstrated that patients with early-stage disease, those with breast cancer, and those on systemic therapy are at the highest risk for PPEDs and may benefit from proactive interventions to avoid the ED. Although our definition requires validation, using ML models for more robust predictive modeling appears promising.