Oncologist phenotypes and associations with response to a machine learning-based intervention to increase advance care planning: Secondary analysis of a randomized clinical trial.

ABSTRACT:

Background

While health systems have implemented multifaceted interventions to improve physician and patient communication in serious illnesses such as cancer, clinicians vary in their response to these initiatives. In this secondary analysis of a randomized trial, we identified phenotypes of oncology clinicians based on practice pattern and demographic data, then evaluated associations between such phenotypes and response to a machine learning (ML)-based intervention to prompt earlier advance care planning (ACP) for patients with cancer.

Methods and findings

Between June and November 2019, we conducted a pragmatic randomized controlled trial testing the impact of text message prompts to 78 oncology clinicians at 9 oncology practices to perform ACP conversations among patien

SUBMITTER: Li E 

PROVIDER: S-EPMC9140236 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature