OncologyNCT03984773
Machine-Generated Mortality Estimates and Nudges to Promote Advance Care Planning Discussion Among Cancer Patients
A study testing Nudge in people with Oncology, run by University of Pennsylvania at 1 site in United States.
Trial summary
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. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Oncology
- What is being tested?
- Nudge
- Type of treatment
- Lifestyle or therapy programme
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 78 participants
- Where
- 1 siteUnited States
- Study dates
- 15 Jul 2019to 19 Apr 2020
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- 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
Show all 9Show fewer
- Myeloma
- Thoracic / Head and Neck Oncology
- Care for adults with cancer at the Pennsylvania Hospital Oncology clinic
Who cannot join
- 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)
Trial locations and contacts
1 site in 1 country.
About this study
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
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.
Read the detailed description
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.
- Conditions
- Oncology
- Being tested
- Nudge
- Keywords
- serious illness conversations, advance care planning, mortality estimates, nudge, pre-commitment, opt-out
- Medical subject headings
- Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
NudgeBehavioural
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.
| Study group | Role | What they receive |
|---|---|---|
| Control | No intervention | Clinicians will receive current standard communications regarding serious illness performance. |
| Mortality Estimates and Nudges | Experimental | 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 Receives: Behavioral: Nudge |
What is being measured
The primary outcome is the main question the study is designed to answer.
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)
Measured: 16 weeks
Secondary outcomes (5)
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
Measured: 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.
Measured: 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
Measured: 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
Measured: 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
Measured: 40 weeks
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted13 Jun 2019
- Study start15 Jul 2019
- Primary completion1 Nov 2019
- Study completion19 Apr 2020
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (6)Papers the sponsor has linked to this study.
- Other trials for OncologyStudies of the same condition, open and under way.
- More trials run by University of PennsylvaniaThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Health services research
- Allocation
- Randomised
- Intervention model
- Parallel groups
- 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 blind
- Who is masked
- Investigator, Outcomes assessor
- Enrolment
- 78 participants (actual)
Sponsor and investigators
- Lead sponsor
- University of Pennsylvania
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Mitesh S Patel, MD, Principal investigator, University of Pennsylvania
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT03984773
- Sponsor's protocol ID
- 833178
- Status last verified
- Apr 2020
- First submitted
- 10 Jun 2019
- Last updated
- 24 Apr 2020
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Patel TA, Heintz J, Chen J, LaPergola M, Bilker WB, Patel MS, Arya LA, Patel MI, Bekelman JE, Manz CR, Parikh RB. Spending Analysis of Machine Learning-Based Communication Nudges in Oncology. NEJM AI. 2024 Jun;1(6):10.1056/aioa2300228. doi: 10.1056/aioa2300228. Epub 2024 May 15.
PubMed 39036423Manz CR, Zhang Y, Chen K, Long Q, Small DS, Evans CN, Chivers C, Regli SH, Hanson CW, Bekelman JE, Braun J, Rareshide CAL, O'Connor N, Kumar P, Schuchter LM, Shulman LN, Patel MS, Parikh RB. Long-term Effect of Machine Learning-Triggered Behavioral Nudges on Serious Illness Conversations and End-of-Life Outcomes Among Patients With Cancer: A Randomized Clinical Trial. JAMA Oncol. 2023 Mar 1;9(3):414-418. doi: 10.1001/jamaoncol.2022.6303.
PubMed 36633868Parikh RB, Manz CR, Nelson MN, Ferrell W, Belardo Z, Temel JS, Patel MS, Shea JA. Oncologist Perceptions of Algorithm-Based Nudges to Prompt Early Serious Illness Communication: A Qualitative Study. J Palliat Med. 2022 Nov;25(11):1702-1707. doi: 10.1089/jpm.2022.0095. Epub 2022 Aug 18.
PubMed 35984992Li EH, Ferrell W, Klaiman T, Kumar P, O'Connor N, Schuchter LM, Chen J, Patel MS, Manz CR, Parikh RB. Impact of Behavioral Nudges on the Quality of Serious Illness Conversations Among Patients With Cancer: Secondary Analysis of a Randomized Controlled Trial. JCO Oncol Pract. 2022 Apr;18(4):e495-e503. doi: 10.1200/OP.21.00024. Epub 2021 Nov 12.
PubMed 34767481Manz CR, Parikh RB, Small DS, Evans CN, Chivers C, Regli SH, Hanson CW, Bekelman JE, Rareshide CAL, O'Connor N, Schuchter LM, Shulman LN, Patel MS. Effect of Integrating Machine Learning Mortality Estimates With Behavioral Nudges to Clinicians on Serious Illness Conversations Among Patients With Cancer: A Stepped-Wedge Cluster Randomized Clinical Trial. JAMA Oncol. 2020 Dec 1;6(12):e204759. doi: 10.1001/jamaoncol.2020.4759. Epub 2020 Dec 10.
PubMed 33057696Manz CR, Parikh RB, Evans CN, Chivers C, Regli SH, Bekelman JE, Small D, Rareshide CAL, O'Connor N, Schuchter LM, Shulman LN, Patel MS. Integrating machine-generated mortality estimates and behavioral nudges to promote serious illness conversations for cancer patients: Design and methods for a stepped-wedge cluster randomized controlled trial. Contemp Clin Trials. 2020 Mar;90:105951. doi: 10.1016/j.cct.2020.105951. Epub 2020 Jan 23.
PubMed 31982648
Study at a glance
From the registry record, last updated by the sponsor on 24 Apr 2020. Recruitment status is as the sponsor reported it: confirm with the study team.
- 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
- ClinicalTrials.gov ID
- NCT03984773
- Acronym / sponsor ID
- 833178
- Conditions
- Oncology
- Keywords
- serious illness conversations, advance care planning, mortality estimates, nudge, pre-commitment, opt-out
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 78 participants (actual)
- Lead sponsor
- University of PennsylvaniaUniversity, hospital or other
- Study start
- 15 Jul 2019 (actual)
- Primary completion
- 1 Nov 2019 (actual)
- Study completion
- 19 Apr 2020 (actual)
- First posted
- 13 Jun 2019 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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
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 design
- Primary purpose
- Health services research
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Double blind (investigator, outcomes assessor)
- Number of arms
- 2
- 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.
| Arm | Type | Receives |
|---|---|---|
| Control | No intervention | –Clinicians will receive current standard communications regarding serious illness performance. |
| Mortality Estimates and Nudges | Experimental | Behavioral: NudgeClinicians 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 |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (9 listed)
- Care for adults with cancer at the following clinics at Perelman Center for Advanced Medicine
- Care for adults with cancer at the Pennsylvania Hospital Oncology clinic
Key exclusion criteria (6 listed)
- 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)
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| NudgeOncology 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. | Behavioural | Mortality Estimates and Nudges |
Primary outcome
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)
5 secondary outcomes
Change in the proportion of patients with a documented SIC among those identified as high-risk by the algorithm
Time frame: 16 weeks
Change in the proportion of patients with a documented advanced care planning
Time frame: 16 weeks
Change in the proportion of patients with a documented 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
Time frame: 40 weeks
Change in the proportion of patients with a documented advanced care planning including follow-up
Time frame: 40 weeks
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 24 Apr 2020.
- Derived from this study: PubMed 39036423Patel TA, Heintz J, Chen J, LaPergola M, Bilker WB, Patel MS, Arya LA, Patel MI, Bekelman JE, Manz CR, Parikh RB. Spending Analysis of Machine Learning-Based Communication Nudges in Oncology. NEJM AI. 2024 Jun;1(6):10.1056/aioa2300228. doi: 10.1056/aioa2300228. Epub 2024 May 15.
- Derived from this study: PubMed 36633868Manz CR, Zhang Y, Chen K, Long Q, Small DS, Evans CN, Chivers C, Regli SH, Hanson CW, Bekelman JE, Braun J, Rareshide CAL, O'Connor N, Kumar P, Schuchter LM, Shulman LN, Patel MS, Parikh RB. Long-term Effect of Machine Learning-Triggered Behavioral Nudges on Serious Illness Conversations and End-of-Life Outcomes Among Patients With Cancer: A Randomized Clinical Trial. JAMA Oncol. 2023 Mar 1;9(3):414-418. doi: 10.1001/jamaoncol.2022.6303.
- Derived from this study: PubMed 35984992Parikh RB, Manz CR, Nelson MN, Ferrell W, Belardo Z, Temel JS, Patel MS, Shea JA. Oncologist Perceptions of Algorithm-Based Nudges to Prompt Early Serious Illness Communication: A Qualitative Study. J Palliat Med. 2022 Nov;25(11):1702-1707. doi: 10.1089/jpm.2022.0095. Epub 2022 Aug 18.
- Derived from this study: PubMed 34767481Li EH, Ferrell W, Klaiman T, Kumar P, O'Connor N, Schuchter LM, Chen J, Patel MS, Manz CR, Parikh RB. Impact of Behavioral Nudges on the Quality of Serious Illness Conversations Among Patients With Cancer: Secondary Analysis of a Randomized Controlled Trial. JCO Oncol Pract. 2022 Apr;18(4):e495-e503. doi: 10.1200/OP.21.00024. Epub 2021 Nov 12.
- Derived from this study: PubMed 33057696Manz CR, Parikh RB, Small DS, Evans CN, Chivers C, Regli SH, Hanson CW, Bekelman JE, Rareshide CAL, O'Connor N, Schuchter LM, Shulman LN, Patel MS. Effect of Integrating Machine Learning Mortality Estimates With Behavioral Nudges to Clinicians on Serious Illness Conversations Among Patients With Cancer: A Stepped-Wedge Cluster Randomized Clinical Trial. JAMA Oncol. 2020 Dec 1;6(12):e204759. doi: 10.1001/jamaoncol.2020.4759. Epub 2020 Dec 10.
- Derived from this study: PubMed 31982648Manz CR, Parikh RB, Evans CN, Chivers C, Regli SH, Bekelman JE, Small D, Rareshide CAL, O'Connor N, Schuchter LM, Shulman LN, Patel MS. Integrating machine-generated mortality estimates and behavioral nudges to promote serious illness conversations for cancer patients: Design and methods for a stepped-wedge cluster randomized controlled trial. Contemp Clin Trials. 2020 Mar;90:105951. doi: 10.1016/j.cct.2020.105951. Epub 2020 Jan 23.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Mitesh S Patel, MD principal investigator
University of Pennsylvania
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Nudge in people with Oncology, run by University of Pennsylvania at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 9 inclusion and 6 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 24 Apr 2020. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Change in the proportion of patients with a documented serious illness conversation (SIC) (time frame: 16 weeks). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT03984773, which also lists 6 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 24 Apr 2020.