Impact of Predictive Modeling on Time to Palliative Care in an Outpatient Primary Care Population
Trial Snapshot
- Phase
- Not Applicable
- Status
- Completed
- Sponsor
- Mayo Clinic
- Enrollment
- 127,070
- Locations
- 2
- Primary Endpoint
- Timely identification for need of palliative care
Study Overview
Brief 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.
Study Design
- Study Type
- Interventional
- Allocation
- Randomized
- Intervention Model
- Crossover
- Primary Purpose
- Screening
- Masking
- None
Eligibility Criteria
- Ages
- 18 Years to — (Adult, Older Adult)
- Sex
- All
- Accepts Healthy Volunteers
- No
Inclusion Criteria
- •Adult patient assigned to a primary care unit from July 2020 to June
- •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
Outcomes
Primary Outcomes
Timely identification for need of palliative care
Time Frame: Through study completion, an average of 1 year
Time to electronic record of consult by the palliative care team in the outpatient setting
Secondary Outcomes
- Number of advanced care planning notes documented in the EHR(Through study completion, an average of 1 year)
- Number of billing codes for palliative care(Through study completion, an average of 1 year)
- Number of palliative care consults(Through study completion, an average of 1 year)
- Positive predictive value of screened patients(Through study completion, an average of 1 year)
- Percent of patients who are eligible for ECH based palliative care(Through study completion, an average of 1 year)
- Percent agreement between Palliative Care and Primary Care and average time between Primary Care Contact and Response(Through study completion, an average of 1 year)
Investigators
Rachel D. Havyer
Principal Investigator
Mayo Clinic