An interventional study of Nudge in Oncology, sponsored by University of Pennsylvania. Completed at 1 site in United States. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2020-04-24.
Sponsored by University of Pennsylvania · Not applicable, Interventional, and Health services research
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.
9,365 studies on the registry are indexed under Neoplasms; 2,489 are open to participants now.
This study's enrollment of 78 is above the median of 50 across 7,253 interventional studies indexed under Neoplasms.
Browse Neoplasms studies →University of Pennsylvania is the lead sponsor of 1,635 studies on the registry; 239 are open to participants now.
Of its 154 completed or terminated interventional studies of FDA-regulated products, 104 (68%) have results posted.
Counted across the registry records on this site, refreshed daily.
Care for adults with cancer at the following clinics at Perelman Center for Advanced Medicine
Exclusion Criteria:
Clinicians will receive current standard communications regarding serious illness performance.
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
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.
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
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
Time frame: 40 weeks
Oncology Evaluation Center admissions
The number of Oncology Evaluation Center admissions
Time frame: 40 weeks
Healthcare utilization and receipt of chemotherapy in the last 30 days of life
Healthcare utilization in the last 30 days of life in Penn Medicine facilities including acute care utilization as above and receipt of chemotherapy
Time frame: 40 weeks
Number of Emergency department admissions
The number of emergency department admissions
Time frame: 40 weeks
Inpatient admissions
The number of inpatient hospital admissions
Time frame: 40 weeks
Intensive care unit admissions
The number of intensive care unit admissions
Time frame: 40 weeks
Plan to share: No
This study is completed, as verified in Apr 2020. You cannot join it, but the record below documents what was studied.
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University of Pennsylvania