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

Study Overview
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Brief Summary
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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.

Detailed Description
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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.

Official Title
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A Stepped-Wedge Cluster Randomized Trial Using Machine-Generated Mortality Estimates and Behavioral Nudges to Promote Advance Care Planning Discussion Among Cancer Patients

Conditions
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Oncology

Intervention / Treatment
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* Behavioral: Nudge


Participation Criteria
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Eligibility Criteria
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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)

Ages Eligible for Study
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Minimum Age: 18 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Design Details

Primary Purpose: Health Services Research
Allocation: Randomized
Intervention Model: Parallel Assignment
Interventional Model Description: Practices will be cluster-randomized in 4-week blocks to the intervention over a 16-week period, after which all practices will receive the email intervention.
Masking: Double


Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| No Intervention: Control<br>Clinicians will receive current standard communications regarding serious illness performance. | |
| Experimental: Mortality Estimates and Nudges<br>Clinicians will receive a weekly email with upcoming patients that have high mortality estimates to consider for a serious illness conversation. Clinicians will have the opportunity to review the list and pre-commit (using an opt-out design) to patients appropriate for a conversation. They will receive a nudge on the day of the patient visit through a text message reminding them of their pre-commitment to conduct a serious illness conversation | Behavioral: Nudge<br>* 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.<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| 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) | 16 weeks | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| 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 | 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. | 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 | 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 | 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 | 40 weeks | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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serious illness conversations, advance care planning, mortality estimates, nudge, pre-commitment, opt-out