NCT04604457

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

• Status: Completed
• Phase: N/A
• Study type: Interventional
• Enrollment: 127,070 (actual)
• Sponsor: Mayo Clinic · Academic / Other
• Sex: All
• Age: 18 Years
• Healthy volunteers: Not accepted

Summary

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

Detailed description

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.

Conditions

• Palliative Care

Interventions

Type	Name	Description
OTHER	Palliative care contacts primary care	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.

Timeline

• Start date: 2020-08-31
• Primary completion: 2021-05-31
• Completion: 2021-05-31
• First posted: 2020-10-27
• Last updated: 2021-06-16

Locations

1 site across 1 country: United States