Algorithm-Based Referrals Enhance Palliative Care Access -EMJ

Algorithm-Based Referrals Enhance Palliative Care Access

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ACCORDING to findings from a randomized study presented at the 2024 ASCO Annual Meeting, an algorithm-based default referrals system has led to a fourfold increase in the use of specialty palliative care within a large community oncology network The study also observed reduced end-of-life chemotherapy usage among patients who received these referrals. Early intervention with specialist palliative care can significantly improve outcomes for patients with advanced solid malignancies, who often endure poor quality of life and aggressive end-of-life treatments. Despite this, many advanced cancer patients do not receive timely palliative care referrals due to clinician inertia and challenges in identifying high-risk patients. The study evaluated an algorithm-based default referral on palliative care access and end-of life patient care.  

The BE-a-PAL trial involved 562 adults (mean age, 68.5 years; 79.5% white; 48.8% women), most of whom had stage III or IV lung or noncolorectal gastrointestinal cancer. An automated EHR algorithm, based on NCCN Palliative Care risk factors, was used to assign risk scores to patients. The study included 15 clinics from a large community oncology network, with 296 patients in the intervention arm and 266 in the control arm. In the intervention arm, oncologists received weekly EHR notifications to refer high-risk patients to specialty palliative care, unless they opted out. In contrast, the control arm allowed oncologists to make referrals at their discretion. 

Both arms of the study had similar mean risk scores (3 vs. 3.2). In the intervention arm, 89% of clinicians accepted the default palliative care referrals, resulting in 79% of patients agreeing to palliative care visits. The intervention arm saw a significantly higher rate of completed palliative care visits compared to the control arm (46.6% vs. 11.3%; adjusted OR = 5.4; 95% CI, 3.2–9.2). Additionally, patients in the intervention arm who died during the study were less likely to receive end-of-life chemotherapy (6.5% vs. 16.1%). There were no notable differences in quality of life or hospice stay length between the two groups. Interviews with clinicians indicated that they found the algorithm criteria appropriate, with nurse coordinators effectively introducing palliative care to patients. 

The study demonstrated a substantial increase in specialty palliative care use through an algorithm-based default referral system, while also reducing end-of-life chemotherapy. Researchers highlighted the potential for this scalable framework to enhance palliative care access using automated risk prediction.  



Parikh RB, et al. BE-a-PAL: A cluster-randomized trial of algorithm-based default palliative care referral among patients with advanced cancer. Abstract 12002. ASCO Annual Meeting; May 30–June 3, 2024. 

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