Cancer
Conditions
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
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
Study design
Intervention model description
Eligible clinicians and patients will be independently randomized to receive nudges using a 2x2 factorial design.
Eligibility
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
| Measure | Time frame | Description |
|---|---|---|
| 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
| Measure | Time frame | Description |
|---|---|---|
| Number of Patients With SIC Documentation (Out of All Patients, Regardless of Risk Level) | Within 6 months of first repeat patient visit during trial period | 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. |
| Number of High Risk Patients With a Palliative Care Referral | 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 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 Care | Within 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
| Arm | Count |
|---|---|
| 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 |
| Total | 4,450 |
Baseline characteristics
| Characteristic | Usual Care | Clinician Nudge | Patient Nudge | Clinician and Patient Nudge | Total |
|---|---|---|---|---|---|
| Age, Continuous | 66 years | 68 years | 67 years | 68 years | 67 years |
| Ethnicity (NIH/OMB) Hispanic or Latino | 29 Participants | 29 Participants | 28 Participants | 36 Participants | 122 Participants |
| Ethnicity (NIH/OMB) Not Hispanic or Latino | 975 Participants | 1150 Participants | 969 Participants | 1234 Participants | 4328 Participants |
| Ethnicity (NIH/OMB) Unknown or Not Reported | 0 Participants | 0 Participants | 0 Participants | 0 Participants | 0 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 Participants | 2 Participants | 1 Participants | 1 Participants | 4 Participants |
| Race (NIH/OMB) Asian | 23 Participants | 28 Participants | 43 Participants | 35 Participants | 129 Participants |
| Race (NIH/OMB) Black or African American | 192 Participants | 206 Participants | 176 Participants | 196 Participants | 770 Participants |
| Race (NIH/OMB) More than one race | 4 Participants | 6 Participants | 10 Participants | 9 Participants | 29 Participants |
| Race (NIH/OMB) Native Hawaiian or Other Pacific Islander | 1 Participants | 2 Participants | 2 Participants | 2 Participants | 7 Participants |
| Race (NIH/OMB) Unknown or Not Reported | 48 Participants | 62 Participants | 43 Participants | 64 Participants | 217 Participants |
| Race (NIH/OMB) White | 736 Participants | 873 Participants | 722 Participants | 963 Participants | 3294 Participants |
| Region of Enrollment United States | 1004 Participants | 1179 Participants | 997 Participants | 1270 Participants | 4450 Participants |
| Sex: Female, Male Female | 556 Participants | 594 Participants | 558 Participants | 644 Participants | 2352 Participants |
| Sex: Female, Male Male | 448 Participants | 585 Participants | 439 Participants | 626 Participants | 2098 Participants |
Adverse events
| Event type | EG000 affected / at risk | EG001 affected / at risk | EG002 affected / at risk | EG003 affected / at risk |
|---|---|---|---|---|
| deaths Total, all-cause mortality | 162 / 1,004 | 227 / 1,179 | 157 / 997 | 227 / 1,270 |
| other Total, other adverse events | 0 / 1,004 | 0 / 1,179 | 0 / 997 | 0 / 1,270 |
| serious Total, serious adverse events | 0 / 1,004 | 0 / 1,179 | 0 / 997 | 0 / 1,270 |
Outcome results
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)
| Arm | Measure | Value (COUNT_OF_PARTICIPANTS) |
|---|---|---|
| Usual Care | Number of High Risk Patients With Documentation of a Serious Illness Conversation (SIC) | 112 Participants |
| Clinician Nudge | Number of High Risk Patients With Documentation of a Serious Illness Conversation (SIC) | 136 Participants |
| Patient Nudge | Number of High Risk Patients With Documentation of a Serious Illness Conversation (SIC) | 115 Participants |
| Clinician and Patient Nudge | Number of High Risk Patients With Documentation of a Serious Illness Conversation (SIC) | 179 Participants |
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.
| Arm | Measure | Value (COUNT_OF_PARTICIPANTS) |
|---|---|---|
| Usual Care | Number of Decedent High Risk Patients Who Received Aggressive End-Of-Life Care | 76 Participants |
| Clinician Nudge | Number of Decedent High Risk Patients Who Received Aggressive End-Of-Life Care | 95 Participants |
| Patient Nudge | Number of Decedent High Risk Patients Who Received Aggressive End-Of-Life Care | 62 Participants |
| Clinician and Patient Nudge | Number of Decedent High Risk Patients Who Received Aggressive End-Of-Life Care | 97 Participants |
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)
| Arm | Measure | Value (COUNT_OF_PARTICIPANTS) |
|---|---|---|
| Usual Care | Number of High Risk Patients With a Palliative Care Referral | 84 Participants |
| Clinician Nudge | Number of High Risk Patients With a Palliative Care Referral | 94 Participants |
| Patient Nudge | Number of High Risk Patients With a Palliative Care Referral | 81 Participants |
| Clinician and Patient Nudge | Number of High Risk Patients With a Palliative Care Referral | 97 Participants |
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.