Predictive Analytics and Behavioral Nudges to Improve Palliative Care in Advanced Cancer
NCT05590962 · Status: COMPLETED · Phase: NA · Type: INTERVENTIONAL · Enrollment: 562
Last updated 2025-02-06
Summary
Patients with advanced cancer suffer from high symptom burden and aggressive end-of-life care. Early specialty palliative care is an evidence-based practice that improves symptom burden, quality of life, and survival in advanced cancer. However, over half of patients with advanced cancer die before receiving palliative care. Clinician-level biases and suboptimal identification of high-risk patients are major barriers to palliative care uptake. In this 2-arm pragmatic clinical trial, the investigators will randomize practices within a large community oncology network to receive an intervention consisting of algorithm-based default palliative care referrals. The investigators will study the impact of such an intervention on palliative care utilization and end-of-life outcomes.
Conditions
Interventions
- OTHER
-
EHR Nudge
Clinicians in Arm 1 (intervention) will receive a EHR notification with option to opt-out for palliative care referral for any eligible high-risk patient, defined by a risk score ≥1 for Stage IV cancer patients and ≥2 for Stage III cancer patients. If the risk score is above 8, they will be scheduled within 2 weeks, and all other patients will be scheduled within 4 weeks. Clinician will have the option to opt-out for any patient by responding to the notification which will be sent to the research coordinator. If the clinician does not respond, the research coordinator will approach patient via telephone, explain the rationale for referral based on a predetermined script, and offer and schedule an outpatient or telemedicine palliative care consultation per patient preference. Follow-up visits will occur at the discretion of the palliative care clinician, usually monthly.
Sponsors & Collaborators
-
Tennessee Oncology
collaborator OTHER -
Emerson Collective
collaborator UNKNOWN -
Abramson Cancer Center at Penn Medicine
lead OTHER
Principal Investigators
-
Ravi Parikh · Penn/ACC
-
Sandhya Mudumbi · TennOnc
Study Design
- Allocation
- RANDOMIZED
- Purpose
- HEALTH_SERVICES_RESEARCH
- Masking
- SINGLE
- Model
- PARALLEL
Eligibility
- Min Age
- 18 Years
- Sex
- ALL
- Healthy Volunteers
- No
Timeline & Regulatory
- Start
- 2022-11-09
- Primary Completion
- 2023-06-13
- Completion
- 2023-10-03
Countries
- United States
Study Locations
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