Impact of Predictive Modeling on Time to Palliative Care in an Outpatient Primary Care Population

Mayo Clinic127,070 enrolled

Overview

A machine learning algorithm will be used to accurately identify patients in certain primary care units who may benefit from palliative care consults.

A machine learning algorithm will be used to accurately identify patients in certain primary care units who may benefit from palliative care consults. These patients will be presented weekly to a palliative care specialist in a custom user interface. The palliative care specialist will reach out to primary care teams if she determines that the patient would benefit from palliative care. If the primary care provider agrees, he/she would write a palliative care consult order for the patient. The goal is to reduce the time to palliative care for these patients, who may not have been identified as quickly without the algorithm.

Study Type

INTERVENTIONAL

Allocation

RANDOMIZED

Purpose

SCREENING

Masking

NONE

Enrollment

127,070

Conditions

Palliative Care

Interventions

Palliative care contacts primary careOTHER

Palliative care specialist reaches out to primary care to recommend a palliative care consult. If the primary care provider agrees, he/she will write an order for a palliative care consult.

Eligibility

Sex: ALLMin age: 18 Years

Medical Language ↔ Plain English

Inclusion Criteria: * Adult patient assigned to a primary care unit from July 2020 to June 2021. * Weekly the palliative care specialists will select patients by looking at patients in sorted order starting with the highest score and proceeding down the list and evaluating each patient for exclusion criteria. Exclusion Criteria: * Patients that have been seen by Palliative care will be excluded for 75 days * Patients under the age of 18 years. * Patients currently enrolled with hospice

Locations (1)

Mayo Clinic in Rochester

Rochester, Minnesota, United States