Skip to content

Effect of Behavioral Nudges on Serious Illness Conversation Documentation

Effect of Behavioral Nudges to Clinicians, Patients, or Both on Serious Illness Conversation Documentation for Patients With Cancer

Status
Completed
Phases
NA
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT04867850
Acronym
SPP2
Enrollment
4450
Registered
2021-04-30
Start date
2021-09-09
Completion date
2022-09-09
Last updated
2024-04-18

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Cancer

Keywords

Cancer, Serious Illness Conversation, Machine Learning, Behavioral Economics

Brief summary

The main purpose of this research study is to evaluate the effectiveness of nudges to clinicians, to patients, or to both in increasing Serious Illness Conversation (SIC) documentation; and to identify moderators of implementation effects on SIC documentation. The investigators will employ rapid-cycle approaches to optimize the framing of nudges to clinicians and patients prior to initiating the trial and mixed methods to explore contextual factors and mechanisms. The investigators will conduct a four-arm pragmatic cluster randomize clinical trial to test the effectiveness of nudges to clinicians, nudges to patients, or nudges to both in increasing the frequency and timeliness of SIC documentation in cancer patients vs. usual care (UC). The investigators hypothesize that each of the implementation strategy arms will significantly increase SIC documentation compared to UC and that the combination of nudges to clinicians and to patients will be the most effective.

Detailed description

Patients with cancer often experience physical and emotional distress, utilize unplanned acute care, and undergo medical interventions that are discordant with their wishes. Given the Covid-19 pandemic, these adverse outcomes are amplified, particularly for racial/ethnic minorities. Serious illness conversations (SICs) that elicit patients' values, goals, and care preferences, particularly early in the disease trajectory, are an evidence-based practice, improve patient mood and quality of life, and are recommended by national guidelines. Preliminary data suggests that SICs among patients with cancer are associated with improved quality of life, increased hospice utilization, and decreased acute care utilization. However, most patients with advanced cancer die without a documented SIC and there are well-documented health disparities in implementation for racial and ethnic minorities. Current strategies to promote SICs, including the multi-component strategies of the Serious Illness Conversation Program, focus primarily on clinician education and have marginally increased the timeliness and frequency of SICs and reduced patient anxiety and depression. While core elements of this program are transferable-such as its structured guide-clinical use remains low. For example, even after training, clinicians at Penn Medicine document SICs for fewer than 5% of patients with advanced cancer. There is critical need to develop, test, and disseminate strategies to improve the frequency of SICs. Implementation strategies informed by behavioral economics are ideally suited to address this problem, which is fundamentally one of clinician and patient behavior change. Clinician barriers to initiating SICs include optimism bias, or the belief that one's own patient is unlikely to experience a negative event; uncertainty about prognosis and appropriate timing; and fear that bringing up end-of-life issues may be distressing to patients. Patient barriers to SIC initiation include fear of discussing the end of life and beliefs that SICs are not appropriate until late in the course of cancer. While previous studies have tested financial incentives for SIC documentation, little research has evaluated behavioral economics-informed strategies to align both clinicians and patients towards earlier SICs. By intentionally modifying the way choices are framed, behavioral nudges can lead to desirable changes in clinician behavior while preserving clinician choice. The investigators' preliminary work demonstrates the effectiveness of an implementation strategy focusing on a clinician nudge, consisting of performance feedback and targeted text messages identifying patients at high risk of mortality based on a validated machine learning prognostic algorithm. This strategy led to a threefold increase in SIC documentation for high-risk patients, equitably across racial/ethnic minority subgroups, and is now in routine use across Penn Medicine practice sites. However, clinicians still did not document SICs for over half of patients, illustrating the limitations of a clinician-directed implementation strategy alone. This study will expand on these preliminary findings to evaluate the synergy between clinician- and patient-directed nudges to increase SIC documentation. The main purpose of this research study is to evaluate the effectiveness of nudges to clinicians, to patients, or to both in increasing Serious Illness Conversation (SIC) documentation; and to identify moderators of implementation effects on SIC documentation. The investigators will employ rapid-cycle approaches to optimize the framing of nudges to clinicians and patients prior to initiating the trial and mixed methods to explore contextual factors and mechanisms. The investigators will conduct a four-arm pragmatic cluster randomize clinical trial to test the effectiveness of nudges to clinicians, nudges to patients, or nudges to both in increasing the frequency and timeliness of SIC documentation in cancer patients vs. usual care (UC). Rationale for clinician nudge using mortality prediction and peer comparison: Due to optimism bias, clinicians routinely overestimate the life expectancy of patients with advanced cancer and delay SICs until too late in the disease course. In part because of this, clinicians reinforce a social norm that early SICs are not part of routine oncology care. Providing an objective assessment of predicted mortality risk may help counteract optimism bias among clinicians and help them identify patients most likely to benefit from SICs. Moreover, that individuals desire to conform to an approved behavior (an injunctive norm) and the behavior of others (a descriptive norm) may contribute to low observed SIC rates, and may also afford an opportunity for intervention. The investigators expect that periodically reminding clinicians of their own performance on SIC documentation, while providing both an injunctive norm (citing national and institutional guidelines) and a descriptive social norm (displaying the behavior of their best performing peers), will lead clinicians to conform more closely to these norms, as has been shown in studies conducted in other contexts. Rationale for patient nudge using priming: Priming is a type of nudge that frames information to activate one's self-efficacy and willingness to engage in behavior change. This type of nudge has not previously been evaluated as a tool to promote SICs for patients with cancer. The investigators will test the added impact of a patient nudge designed to prime patients and, in turn, their clinicians to having a SIC.

Interventions

OTHERUsual Care

Individual clinicians will receive an automated weekly email detailing a weekly roster of their upcoming repeat-patient visits (Index Visit) with patients at high risk of 6-month mortality as determined by a validated machine learning prognostic algorithm. Clinicians will receive a HIPAA compliant text message on the morning of the appointment reminding them to consider a serious illness conversation with patients on the list.

Clinicians will receive the usual care weekly email and text message described above under Usual Care. In addition, embedded in the weekly email, clinicians will receive performance feedback information detailing their documented SICs relative to those documented by peers.

Ahead of the Index Visit, high risk patients as identified by the prognostic algorithm will receive a nudge via personal text message and email consisting of a normalizing message prompting patients with a personalized link to a short electronic questionnaire on SIC topics.

Sponsors

National Cancer Institute (NCI)
CollaboratorNIH
Abramson Cancer Center at Penn Medicine
Lead SponsorOTHER

Study design

Allocation
RANDOMIZED
Intervention model
FACTORIAL
Primary purpose
HEALTH_SERVICES_RESEARCH
Masking
SINGLE (Investigator)

Intervention model description

Eligible clinicians and patients will be independently randomized to receive nudges using a 2x2 factorial design.

Eligibility

Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No

Inclusion criteria

Clinician (M.D., P.A., or N.P.) participants must meet the following criteria: 1\. Provide care at least 1 clinic session per week for adult (age\>18 years) patients with solid, hematologic, or gynecologic malignancies at a participating PennMedicine Implementation Lab site Patient participants must meet the following criteria: 1. Receive care for a solid, hematologic, or gynecologic malignancy from an eligible provider at a participating PennMedicine Implementation Lab site 2. Have at least one scheduled Return Patient Visit (either in person or via telemedicine) with an eligible PennMedicine provider during the study period

Exclusion criteria

Clinicians will be ineligible for \*any\* of the following reasons: 1\. Provide exclusively benign hematology, survivorship, and/or genetics care Patients will be ineligible for \*any\* of the following reasons: 1. Previously documented SIC within 6 months 2. Have a non-valid phone number

Design outcomes

Primary

MeasureTime frameDescription
Number of High Risk Patients With Documentation of a Serious Illness Conversation (SIC)Within 6 months of the Index Visit (baseline)Measured at the patient level as a binary outcome (yes/no) among high-risk patients based on date of documented note including the SIC template in the Advanced Care Planning (ACP) section of the electronic medical record by any provider Outcomes were measured for patients only.

Secondary

MeasureTime frameDescription
Number of Patients With SIC Documentation (Out of All Patients, Regardless of Risk Level)Within 6 months of first repeat patient visit during trial periodMeasured at the patient level as a binary outcome (yes/no) among all cancer patients based on date of documented note including the SIC template in the Advanced Care Planning (ACP) section of the electronic medical record by any provider Outcomes were measured for patients only.
Number of High Risk Patients With a Palliative Care ReferralWithin 6 months of the Index Visit (baseline)Measured at the patient level as a binary outcome (yes/no) among high-risk patients based on presence of a scheduled palliative care appointment Outcomes were measured for patients only.
Number of Decedent High Risk Patients Who Received Aggressive End-Of-Life CareWithin 6 months of the Index Visit (baseline)Measured at the patient level as a binary outcome (yes/no) among high-risk patients who die based on the presence of any of the following three criteria: chemotherapy within 14 days before death, hospitalization within 30 days before death, or admission to hospice 3 days or less before death Outcomes were measured for patients only.

Countries

United States

Participant flow

Pre-assignment details

A total of 4,450 patients were included in this study on serious illness conversations (SICs). These patients were seen by 163 clinicians across 65 oncologist-advanced practice provider (APP) clusters. Baseline measures and outcome data were collected for patients only.

Participants by arm

ArmCount
Usual Care
Clinicians and patients will receive no further interventions beyond usual practice. Usual care for clinicians includes a nudge consisting of targeted text messages identifying patients at high risk of predicted 6-month mortality based on a validated machine learning prognostic algorithm. Usual Care: Individual clinicians will receive an automated weekly email detailing a weekly roster of their upcoming repeat-patient visits (Index Visit) with patients at high risk of 6-month mortality as determined by a validated machine learning prognostic algorithm. Clinicians will receive a HIPAA compliant text message on the morning of the appointment reminding them to consider a serious illness conversation with patients on the list.
1,004
Clinician Nudge
Clinicians receive a nudge consisting of targeted text messages identifying patients at high risk of predicted 6-month mortality based on a validated machine learning prognostic algorithm as well as performance feedback compared to peers. Clinician Nudge: Clinicians will receive the usual care weekly email and text message described above under Usual Care. In addition, embedded in the weekly email, clinicians will receive performance feedback information detailing their documented SICs relative to those documented by peers.
1,179
Patient Nudge
Patients receive a nudge consisting of a normalizing message prompting patients to complete an electronic questionnaire designed to prime patients towards having an SIC. Patient Nudge: Ahead of the Index Visit, high risk patients as identified by the prognostic algorithm will receive a nudge via personal text message and email consisting of a normalizing message prompting patients with a personalized link to a short electronic questionnaire on SIC topics.
997
Clinician and Patient Nudge
Both strategies described above will be used. Clinician Nudge: Clinicians will receive the usual care weekly email and text message described above under Usual Care. In addition, embedded in the weekly email, clinicians will receive performance feedback information detailing their documented SICs relative to those documented by peers. Patient Nudge: Ahead of the Index Visit, high risk patients as identified by the prognostic algorithm will receive a nudge via personal text message and email consisting of a normalizing message prompting patients with a personalized link to a short electronic questionnaire on SIC topics.
1,270
Total4,450

Baseline characteristics

CharacteristicUsual CareClinician NudgePatient NudgeClinician and Patient NudgeTotal
Age, Continuous66 years68 years67 years68 years67 years
Ethnicity (NIH/OMB)
Hispanic or Latino
29 Participants29 Participants28 Participants36 Participants122 Participants
Ethnicity (NIH/OMB)
Not Hispanic or Latino
975 Participants1150 Participants969 Participants1234 Participants4328 Participants
Ethnicity (NIH/OMB)
Unknown or Not Reported
0 Participants0 Participants0 Participants0 Participants0 Participants
Predicted odds of 180-day mortality (based on a validated machine learning algorithm; 0-1 scale).18 Avg. predicted probability of mortality.19 Avg. predicted probability of mortality.18 Avg. predicted probability of mortality.19 Avg. predicted probability of mortality.19 Avg. predicted probability of mortality
Race (NIH/OMB)
American Indian or Alaska Native
0 Participants2 Participants1 Participants1 Participants4 Participants
Race (NIH/OMB)
Asian
23 Participants28 Participants43 Participants35 Participants129 Participants
Race (NIH/OMB)
Black or African American
192 Participants206 Participants176 Participants196 Participants770 Participants
Race (NIH/OMB)
More than one race
4 Participants6 Participants10 Participants9 Participants29 Participants
Race (NIH/OMB)
Native Hawaiian or Other Pacific Islander
1 Participants2 Participants2 Participants2 Participants7 Participants
Race (NIH/OMB)
Unknown or Not Reported
48 Participants62 Participants43 Participants64 Participants217 Participants
Race (NIH/OMB)
White
736 Participants873 Participants722 Participants963 Participants3294 Participants
Region of Enrollment
United States
1004 Participants1179 Participants997 Participants1270 Participants4450 Participants
Sex: Female, Male
Female
556 Participants594 Participants558 Participants644 Participants2352 Participants
Sex: Female, Male
Male
448 Participants585 Participants439 Participants626 Participants2098 Participants

Adverse events

Event typeEG000
affected / at risk
EG001
affected / at risk
EG002
affected / at risk
EG003
affected / at risk
deaths
Total, all-cause mortality
162 / 1,004227 / 1,179157 / 997227 / 1,270
other
Total, other adverse events
0 / 1,0040 / 1,1790 / 9970 / 1,270
serious
Total, serious adverse events
0 / 1,0040 / 1,1790 / 9970 / 1,270

Outcome results

Primary

Number of High Risk Patients With Documentation of a Serious Illness Conversation (SIC)

Measured at the patient level as a binary outcome (yes/no) among high-risk patients based on date of documented note including the SIC template in the Advanced Care Planning (ACP) section of the electronic medical record by any provider Outcomes were measured for patients only.

Time frame: Within 6 months of the Index Visit (baseline)

ArmMeasureValue (COUNT_OF_PARTICIPANTS)
Usual CareNumber of High Risk Patients With Documentation of a Serious Illness Conversation (SIC)112 Participants
Clinician NudgeNumber of High Risk Patients With Documentation of a Serious Illness Conversation (SIC)136 Participants
Patient NudgeNumber of High Risk Patients With Documentation of a Serious Illness Conversation (SIC)115 Participants
Clinician and Patient NudgeNumber of High Risk Patients With Documentation of a Serious Illness Conversation (SIC)179 Participants
Secondary

Number of Decedent High Risk Patients Who Received Aggressive End-Of-Life Care

Measured at the patient level as a binary outcome (yes/no) among high-risk patients who die based on the presence of any of the following three criteria: chemotherapy within 14 days before death, hospitalization within 30 days before death, or admission to hospice 3 days or less before death Outcomes were measured for patients only.

Time frame: Within 6 months of the Index Visit (baseline)

Population: Aggressive End-Of-Life Care was only assessed among the 773 decedents.

ArmMeasureValue (COUNT_OF_PARTICIPANTS)
Usual CareNumber of Decedent High Risk Patients Who Received Aggressive End-Of-Life Care76 Participants
Clinician NudgeNumber of Decedent High Risk Patients Who Received Aggressive End-Of-Life Care95 Participants
Patient NudgeNumber of Decedent High Risk Patients Who Received Aggressive End-Of-Life Care62 Participants
Clinician and Patient NudgeNumber of Decedent High Risk Patients Who Received Aggressive End-Of-Life Care97 Participants
Secondary

Number of High Risk Patients With a Palliative Care Referral

Measured at the patient level as a binary outcome (yes/no) among high-risk patients based on presence of a scheduled palliative care appointment Outcomes were measured for patients only.

Time frame: Within 6 months of the Index Visit (baseline)

ArmMeasureValue (COUNT_OF_PARTICIPANTS)
Usual CareNumber of High Risk Patients With a Palliative Care Referral84 Participants
Clinician NudgeNumber of High Risk Patients With a Palliative Care Referral94 Participants
Patient NudgeNumber of High Risk Patients With a Palliative Care Referral81 Participants
Clinician and Patient NudgeNumber of High Risk Patients With a Palliative Care Referral97 Participants
Secondary

Number of Patients With SIC Documentation (Out of All Patients, Regardless of Risk Level)

Measured at the patient level as a binary outcome (yes/no) among all cancer patients based on date of documented note including the SIC template in the Advanced Care Planning (ACP) section of the electronic medical record by any provider Outcomes were measured for patients only.

Time frame: Within 6 months of first repeat patient visit during trial period

Population: Data were not collected for this outcome because it reflected a different patient population than the one in this study. The workflow for identifying patients for this trial was based on patients having a risk score (risk of predicted 180-day mortality based on a validated machine-learning prognostic algorithm) exceeding a certain threshold ahead of their clinical appointment, and it was infeasible to track patients with a risk score below this threshold.

Source: ClinicalTrials.gov · Data processed: Feb 14, 2026