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Machine-Generated Mortality Estimates and Nudges to Promote Advance Care Planning Discussion Among Cancer Patients

NCT03984773 · Status: COMPLETED · Phase: NA · Type: INTERVENTIONAL · Enrollment: 78

Last updated 2020-04-24

No results posted yet for this study

Summary

This study will use a stepped-wedge cluster randomized trial to evaluate the effect of a health system initiative using machine learning algorithms and behavioral nudges to prompt oncologists to have serious illness conversations with patients at high-risk of short-term mortality.

Conditions

Interventions

BEHAVIORAL

Nudge

Oncology practices will be randomly assigned to receive an intervention, in which individual clinicians will receive a weekly audit email detailing how many serious illness conversations (SIC) they have had compared to the recommended level, and a link to a list of their patients scheduled in clinic next week at high risk of short-term mortality as identified by a mortality prediction algorithm. Clinicians will have the chance to review the opt-out list and pre-commit to a serious illness conversation with appropriate patients. Clinicians will receive nudge on the day of the patient visit via text message reminding them of their pre-commitment to conduct a serious illness conversation.

Sponsors & Collaborators

Principal Investigators

  • Mitesh S Patel, MD · University of Pennsylvania

Study Design

Allocation
RANDOMIZED
Purpose
HEALTH_SERVICES_RESEARCH
Masking
DOUBLE
Model
PARALLEL

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2019-07-15
Primary Completion
2019-11-01
Completion
2020-04-19

Countries

  • United States

Study Locations

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Entities

Diseases
Companies

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT03984773 on ClinicalTrials.gov