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

University of Pennsylvania78 enrolled

Overview

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.

Patients with cancer often undergo costly therapy and acute care utilization that is discordant with their wishes, particularly at the end of life. Early serious illness conversations (SIC) improve goal-concordant care, and accurate prognostication is critical to inform the timing and content of these discussions. 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. Oncology practices will be randomly assigned in sequential four-week blocks to receive the intervention.

Study Type

INTERVENTIONAL

Allocation

RANDOMIZED

Purpose

HEALTH_SERVICES_RESEARCH

Masking

DOUBLE

Enrollment

Conditions

Oncology

Interventions

NudgeBEHAVIORAL

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.

Eligibility

Sex: ALLMin age: 18 Years

Medical Language ↔ Plain English

Inclusion Criteria: * Care for adults with cancer at the following clinics at Perelman Center for Advanced Medicine * Breast Oncology * Gastrointestinal Oncology * Genitourinary Oncology * Lymphoma * Melanoma and Central Nervous System Oncology * Myeloma * Thoracic / Head and Neck Oncology * Care for adults with cancer at the Pennsylvania Hospital Oncology clinic Exclusion Criteria: * Providers who care for only patients with benign hematologic disorders * Providers who see only genetic consults * Providers who see less than 12 high-risk patients in either the pre- or post- intervention periods * Visits for patients with lung cancer who are enrolled in an ongoing palliative care clinical trial that may lead to more SICs * Patient visits that are for oncology genetics consults (such patients may still be included if they see their primary oncologist during the trial) * Providers who have not undergone serious illness conversation program training (SIC)

Locations (1)

Penn Medicine

Philadelphia, Pennsylvania, United States

Outcomes

Primary Outcomes

Change in the proportion of patients with a documented serious illness conversation (SIC)

The change in the proportion of patients that have an outpatient oncology visit with documentation of a serious illness conversation (SIC)

Time frame: 16 weeks

Secondary Outcomes

Change in the proportion of patients with a documented SIC among those identified as high-risk by the algorithm

The change in the proportion of patients who have an outpatient oncology visit and are identified as high-risk by the machine learning algorithm with documentation of a SIC

Time frame: 16 weeks

Change in the proportion of patients with a documented advanced care planning

The change in the proportion of patients with documentation of advanced care planning.

Time frame: 16 weeks

Change in the proportion of patients with a documented serious illness conversation (SIC) including follow-up

The change in the proportion of patients that have an outpatient oncology visit with documentation of a serious illness conversation (SIC) including follow-up

Time frame: 40 weeks

Change in the proportion of patients with a documented SIC among those identified as high-risk by the algorithm including follow-up

The change in the proportion of patients who have an outpatient oncology visit and are identified as high-risk by the machine learning algorithm with documentation of a SIC including follow-up

Time frame: 40 weeks

Change in the proportion of patients with a documented advanced care planning including follow-up

The change in the proportion of patients with documentation of advanced care planning including follow-up

Data from ClinicalTrials.gov

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