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Completed

NCT Number: NCT03984773

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

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.

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Key information

Conditions

Oncology Neoplasms

Age range

18 year and older

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Penn Medicine

Philadelphia, Pennsylvania, 19103, United States

About this study

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.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

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)

Treatment and study plan

Nudge

Behavioral

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.

Primary outcomes

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

    Time frame: 16 weeks

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

Secondary outcomes

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

    Time frame: 16 weeks

    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

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

    Time frame: 16 weeks

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

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

    Time frame: 40 weeks

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

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

    Time frame: 40 weeks

    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

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

    Time frame: 40 weeks

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

Other outcomes

  1. Oncology Evaluation Center admissions

    Time frame: 40 weeks

    The number of Oncology Evaluation Center admissions

  2. Healthcare utilization and receipt of chemotherapy in the last 30 days of life

    Time frame: 40 weeks

    Healthcare utilization in the last 30 days of life in Penn Medicine facilities including acute care utilization as above and receipt of chemotherapy

  3. Number of Emergency department admissions

    Time frame: 40 weeks

    The number of emergency department admissions

  4. Inpatient admissions

    Time frame: 40 weeks

    The number of inpatient hospital admissions

  5. Intensive care unit admissions

    Time frame: 40 weeks

    The number of intensive care unit admissions

Sponsors and collaborators

Lead sponsor

University of Pennsylvania

Other

Registry information

Official study title

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

Important dates

Study start
2019
Primary completion
2019
Study completion
2020
First posted
Jun 13, 2019
Registry last updated
Apr 24, 2020

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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