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• W3029860990 abstract "12002 Background: Most patients with cancer die without a documented serious illness conversation (SIC) about prognosis and goals. Interventions that increase SICs between oncology clinicians and patients may improve goal-concordant care and end-of-life outcomes. Methods: In this stepped-wedge cluster randomized trial (NCT03984773), we tested the effect of an intervention delivering machine learning-based mortality estimates with behavioral nudges to oncologists to increase SICs among patients with cancer. The clinician-focused intervention consisted of 1) weekly emails providing individual SIC performance feedback (number of SICs in the past month) and peer comparisons; 2) a list of patients scheduled for the next week with a ≥10% predicted risk of 6 month mortality by a validated machine learning prognostic algorithm, and 3) automated opt-out text prompts on the patient’s appointment day to consider an SIC. Eight medical oncology clinics were randomized to receive the intervention in a stepped-wedge fashion every four weeks for a total of 16 weeks. Medical oncology clinicians were included if they were trained to use the SIC Guide (Ariadne Labs, Boston MA). Patients were included if they had an outpatient encounter with an eligible clinician between June 17 and November 1, 2019. The primary outcome was the percent of patient encounters with a documented SIC. Intention to treat analyses adjusted for clinic and wedge fixed effects and clustered at the oncologist level. Results: The sample consisted of 78 clinicians and 14,607 patients. The mean age of patients was 61.7 years, 55.7% were female, 70.4% were white, and 19.6% were black. The percent of patient encounters with an SIC was 1.2% (106/8536) during the pre-intervention period and 4.0% (401/10,152) during the intervention period. In intention to treat adjusted analyses, the intervention led to a significant increase in SICs (adjusted odds ratio, 3.7; 95% CI, 2.5 to 5.4, P value < 0.0001). Conclusions: An intervention consisting of machine learning mortality estimates and behavioral nudges to oncology clinicians increased SICs by three-fold over 16 weeks, a significant difference.This is one of the first studies evaluating a machine learning-based behavioral intervention to improve serious illness communication in oncology. Secondary analyses (completed April 2020) will clarify whether this intervention leads to a sustained increase in SIC rates and improves goal-concordant care and end-of-life outcomes. Clinical trial information: NCT03984773 ." @default.
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• W3029860990 date "2020-05-20" @default.
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• W3029860990 title "Effect of integrating machine learning mortality estimates with behavioral nudges to increase serious illness conversions among patients with cancer: A stepped-wedge cluster randomized trial." @default.
• W3029860990 doi "https://doi.org/10.1200/jco.2020.38.15_suppl.12002" @default.
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