Identification of Patient-Reported Outcome Phenotypes Among Oncology Patients With Palliative Care Needs.

PURPOSE: Despite evidence-based guidelines recommending early palliative care, it remains unclear how to identify and refer oncology patients, particularly in settings with constrained access to palliative care. We hypothesize that patient-reported outcome (PRO) data can be used to characterize patients with palliative care needs. To determine if PRO data can identify latent phenotypes that characterize indications for specialty palliative care referral. METHODS: We conducted a retrospective study of self-reported symptoms on the Edmonton Symptom Assessment System collected from solid tumor oncology patients (n = 745) referred to outpatient palliative care. Data were collected as part of routine clinical care from October 2012 to March 2018 at eight community and academic sites. We applied latent profile analysis to identify PRO phenotypes and examined the association of phenotypes with clinical and demographic characteristics using multinomial logistic regression. RESULTS: We identified four PRO phenotypes: (1) Low Symptoms (n = 295, 39.6%), (2) Moderate Pain/Fatigue + Mood (n = 180, 24.2%), (3) Moderate Pain/Fatigue + Appetite + Dyspnea (n = 201, 27.0%), and (4) High Symptoms (n = 69, 9.3%). In a secondary analysis of 421 patients, we found that two brief items assessing social and existential needs aligned with higher severity symptom and psychological distress phenotypes. CONCLUSION: Oncology patients referred to outpatient palliative care in a real-world setting can be differentiated into clinically meaningful phenotypes using brief, routinely collected PRO measures. Latent modeling provides a mechanism to use patient-reported data on a population level to identify distinct subgroups of patients with unmet palliative needs.

Views From Patients With Cancer in the Setting of Unplanned Acute Care: Informing Approaches to Reduce Health Care Utilization.

PURPOSE: New oncology care delivery models that avoid preventable acute care are needed, yet it is unclear which interventions best meet the needs of patients and caregivers. Perspectives from patients who experienced unplanned acute care events may inform the successful development and implementation of care delivery models. METHODS: We performed a qualitative interview study of patients with solid tumors on active treatment who experienced the following 3 types of unplanned acute care events: emergency department visits, first hospitalizations, and multiple hospitalizations. Patients were prospectively recruited within a large academic health system from August 2018 to January 2019. Interviews followed a semi-structured guide developed from the Consolidated Framework for Implementation Research. The constant comparative approach was used to identify themes. RESULTS: Forty-nine patients were interviewed; 51% were men, 75% were non-Hispanic White, and the mean age was 57.4 years (standard deviation, 1.9 years). Fifty-five percent of patients had metastatic disease, and 33% had an Eastern Cooperative Oncology Group performance status of 3-4. We identified the following key themes: drivers of the decision to seek acute care, patients' emotional concerns that influence interactions with the oncology team, and strategies used to avoid acute care. Patients' recommendations for interventions included anticipatory guidance, peer support, improved triage methods, and enhanced symptom management. Patients preferred options for virtual and home-based outpatient care. CONCLUSION: Patient-centered care models should focus on early delivery of supportive interventions that help patients and caregivers navigate the unexpected issues that come with cancer treatment. Patients advocate for proactive, multidisciplinary supportive interventions that enable home-based care and are led by the primary oncology team.