Using nudges with machine learning algorithms to increase serious illness conversations


Patients with cancer often receive care that is discordant with their wishes, resulting in inappropriate and costly utilization. Evidence demonstrates that having serious illness conversations (SICs) early on can help clinicians align care with patient goals. However, many patients with advanced cancer die without ever having a SIC.  


Our goal is to test whether nudges can be combined with a machine learning algorithm that predicts the risk of 6-month mortality to increase SICs among clinicians and cancer patients. Each week clinicians will be provided with a list of patients they will see the following week who have a high-risk of mortality. Using an opt-out approach, they will be asked to pre-commit to having these conversations and sent a text message reminder on the day of the visit. To assess the impact of these interventions while implementing this throughout Penn Medicine, we have designed a stepped-wedge cluster randomized controlled trial.


This clinical trial is being implemented now. Results are expected in 2020.


Penn Medicine Abramson Cancer Center


Penn Center for Precision Medicine


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