Oncology Clinical Trial
Official title:
A Stepped-Wedge Cluster Randomized Trial Using Machine-Generated Mortality Estimates and Behavioral Nudges to Promote Advance Care Planning Discussion Among Cancer Patients
NCT number | NCT03984773 |
Other study ID # | 833178 |
Secondary ID | |
Status | Completed |
Phase | N/A |
First received | |
Last updated | |
Start date | July 15, 2019 |
Est. completion date | April 19, 2020 |
Verified date | April 2020 |
Source | University of Pennsylvania |
Contact | n/a |
Is FDA regulated | No |
Health authority | |
Study type | Interventional |
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.
Status | Completed |
Enrollment | 78 |
Est. completion date | April 19, 2020 |
Est. primary completion date | November 1, 2019 |
Accepts healthy volunteers | No |
Gender | All |
Age group | 18 Years and older |
Eligibility |
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) |
Country | Name | City | State |
---|---|---|---|
United States | Penn Medicine | Philadelphia | Pennsylvania |
Lead Sponsor | Collaborator |
---|---|
University of Pennsylvania |
United States,
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Other | Oncology Evaluation Center admissions | The number of Oncology Evaluation Center admissions | 40 weeks | |
Other | 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 | 40 weeks | |
Other | Number of Emergency department admissions | The number of emergency department admissions | 40 weeks | |
Other | Inpatient admissions | The number of inpatient hospital admissions | 40 weeks | |
Other | Intensive care unit admissions | The number of intensive care unit admissions | 40 weeks | |
Primary | 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 | 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 | |
Secondary | 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 | |
Secondary | 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 | |
Secondary | 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 | |
Secondary | 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 |
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