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Artificial Intelligence/Machine Learning Modeling on Time to Palliative Care Review in an Inpatient Hospital Population

NCT03976297 · Status: COMPLETED · Phase: NA · Type: INTERVENTIONAL · Enrollment: 2231

Last updated 2020-12-30

No results posted yet for this study

Summary

Investigators are testing whether machine learning prediction models integrated into a health care model will accurately identify participants who may benefit from a comprehensive review by a palliative care specialist, and decrease time to receiving a palliative care consult in an inpatient setting.

Conditions

  • Palliative Care

Interventions

OTHER

Control Tower

A workstation and software tool that extracts medical data from Mayo's data mart and electronic health record, and processes it through a prediction model that determines whether a patient is suited for a palliative care consult.

Sponsors & Collaborators

Principal Investigators

  • Jon O Ebbert, MD · Mayo Clinic

Study Design

Allocation
RANDOMIZED
Purpose
HEALTH_SERVICES_RESEARCH
Masking
NONE
Model
CROSSOVER

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2019-08-19
Primary Completion
2020-11-18
Completion
2020-12-20

Countries

  • United States

Study Locations

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Entities

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 NCT03976297 on ClinicalTrials.gov