Association of Remote Patient-Reported Outcomes and Step Counts With Hospitalization or Death Among Patients With Advanced Cancer Undergoing Chemotherapy: Secondary Analysis of the PROStep Randomized Trial.

BACKGROUND: Patients with advanced cancer undergoing chemotherapy experience significant symptoms and declines in functional status, which are associated with poor outcomes. Remote monitoring of patient-reported outcomes (PROs; symptoms) and step counts (functional status) may proactively identify patients at risk of hospitalization or death. OBJECTIVE: The aim of this study is to evaluate the association of (1) longitudinal PROs with step counts and (2) PROs and step counts with hospitalization or death. METHODS: The PROStep randomized trial enrolled 108 patients with advanced gastrointestinal or lung cancers undergoing cytotoxic chemotherapy at a large academic cancer center. Patients were randomized to weekly text-based monitoring of 8 PROs plus continuous step count monitoring via Fitbit (Google) versus usual care. This preplanned secondary analysis included 57 of 75 patients randomized to the intervention who had PRO and step count data. We analyzed the associations between PROs and mean daily step counts and the associations of PROs and step counts with the composite outcome of hospitalization or death using bootstrapped generalized linear models to account for longitudinal data. RESULTS: Among 57 patients, the mean age was 57 (SD 10.9) years, 24 (42%) were female, 43 (75%) had advanced gastrointestinal cancer, 14 (25%) had advanced lung cancer, and 25 (44%) were hospitalized or died during follow-up. A 1-point weekly increase (on a 32-point scale) in aggregate PRO score was associated with 247 fewer mean daily steps (95% CI -277 to -213; P<.001). PROs most strongly associated with step count decline were patient-reported activity (daily step change -892), nausea score (-677), and constipation score (524). A 1-point weekly increase in aggregate PRO score was associated with 20% greater odds of hospitalization or death (adjusted odds ratio [aOR] 1.2, 95% CI 1.1-1.4; P=.01). PROs most strongly associated with hospitalization or death were pain (aOR 3.2, 95% CI 1.6-6.5; P<.001), decreased activity (aOR 3.2, 95% CI 1.4-7.1; P=.01), dyspnea (aOR 2.6, 95% CI 1.2-5.5; P=.02), and sadness (aOR 2.1, 95% CI 1.1-4.3; P=.03). A decrease in 1000 steps was associated with 16% greater odds of hospitalization or death (aOR 1.2, 95% CI 1.0-1.3; P=.03). Compared with baseline, mean daily step count decreased 7% (n=274 steps), 9% (n=351 steps), and 16% (n=667 steps) in the 3, 2, and 1 weeks before hospitalization or death, respectively. CONCLUSIONS: In this secondary analysis of a randomized trial among patients with advanced cancer, higher symptom burden and decreased step count were independently associated with and predictably worsened close to hospitalization or death. Future interventions should leverage longitudinal PRO and step count data to target interventions toward patients at risk for poor outcomes. TRIAL REGISTRATION: ClinicalTrials.gov NCT04616768; https://clinicaltrials.gov/study/NCT04616768. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1136/bmjopen-2021-054675.

Effect of Gamification, Financial Incentives, or Both to Increase Physical Activity Among Patients at High Risk of Cardiovascular Events: The BE ACTIVE Randomized Controlled Trial.

BACKGROUND: Physical activity is associated with a lower risk of major adverse cardiovascular events, but few individuals achieve guideline-recommended levels of physical activity. Strategies informed by behavioral economics increase physical activity, but their longer-term effectiveness is uncertain. We sought to determine the effect of behaviorally designed gamification, loss-framed financial incentives, or their combination on physical activity compared with attention control over 12-month intervention and 6-month postintervention follow-up periods. METHODS: Between May 2019 and January 2024, participants with clinical atherosclerotic cardiovascular disease or a 10-year risk of myocardial infarction, stroke, or cardiovascular death of ≥7.5% by the Pooled Cohort equation were enrolled in a pragmatic randomized clinical trial. Participants received a wearable device to track daily steps, established a baseline, selected a step goal increase, and were randomly assigned to control (n=151), behaviorally designed gamification (n=304), loss-framed financial incentives (n=302), or gamification+financial incentives (n=305). The primary outcome of the trial was the change in mean daily steps from baseline through the 12-month intervention period. RESULTS: A total of 1062 patients (mean±SD age, 67±8; 61% female; 31% non-White) were enrolled. Compared with control subjects, participants had significantly greater increases in mean daily steps from baseline during the 12-month intervention in the gamification arm (adjusted difference, 538.0 [95% CI, 186.2-889.9]; P=0.0027), financial incentives arm (adjusted difference, 491.8 [95% CI, 139.6-844.1]; P=0.0062), and gamification+financial incentives arm (adjusted difference, 868.0 [95% CI, 516.3-1219.7]; P<0.0001). During the 6-month follow-up, physical activity remained significantly greater in the gamification+financial incentives arm than in the control arm (adjusted difference, 576.2 [95% CI, 198.5-954]; P=0.0028), but it was not significantly greater in the gamification (adjusted difference, 459.8 [95% CI, 82.0-837.6]; P=0.0171) or financial incentives (adjusted difference, 327.9 [95% CI, -50.2 to 706]; P=0.09) arms after adjustment for multiple comparisons. CONCLUSIONS: Behaviorally designed gamification, loss-framed financial incentives, and the combination of both increased physical activity compared with control over a 12-month intervention period, with the largest effect in gamification+financial incentives. These interventions could be a useful component of strategies to reduce cardiovascular risk in high-risk patients. REGISTRATION: URL: https://clinicaltrials.gov; Unique Identifier: NCT03911141.

Gamification-augmented home-based exercise for peripheral artery disease: Rationale and design of the GAMEPAD Study.

BACKGROUND: Supervised exercise therapy improves walking performance, functional capacity, and quality of life in patients with peripheral artery disease (PAD). However, few patients with PAD are enrolled in supervised exercise programs, and there are a number of logistical and financial barriers to their participation. A home-based walking intervention is likely to be more accessible to patients with PAD, but no fully home-based walking program has demonstrated efficacy. Concepts from behavioral economics have been used to design scalable interventions that increase daily physical activity in patients with atherosclerotic vascular disease, but whether a similar program would be effective in patients with PAD is uncertain. STUDY DESIGN AND OBJECTIVES: GAMEPAD (NCT04536012) is a pragmatic, virtual, randomized controlled trial designed to evaluate the effectiveness of a gamification strategy informed by concepts from behavioral economics to increase daily physical activity in patients with PAD who are seen in cardiology and vascular surgery clinics affiliated with the University of Pennsylvania Health System. Patients are contacted by email or text message, and complete enrollment and informed consent on the Penn Way to Health online platform. A GAMEPAD substudy will evaluate the effectiveness of opt-in versus opt-out framing when approaching patients for study participation. Patients are then provided with a wearable fitness tracker, establish a baseline daily step count, set a goal to increase daily step count by 33%-50%, and are randomized 1:1 to the gamification or control arms. Interventions continue for 16 weeks, including a 4-week period during which goal step count is gradually increased in the gamification arm, with follow-up for an additional 8 weeks to evaluate the durability of behavior change. The trial has met its enrollment goal of 102 participants, with a primary endpoint of change from baseline in daily steps over the 16-week intervention period. Key secondary endpoints include change from baseline in daily steps over the 8-week postintervention follow-up period and changes in patient-reported measures of PAD symptoms and quality of life over the intervention and follow-up periods. CONCLUSIONS: GAMEPAD is a virtual, pragmatic randomized clinical trial of a novel, fully home-based walking intervention informed by concepts from behavioral economics to increase physical activity and PAD-specific quality of life in patients with PAD. Its results will have important implications for the application of behavioral economic concepts to scalable home-based strategies to promote physical activity in patients with PAD and other disease processes where physical activity is limited by exertional symptoms. CLINICAL TRIAL REGISTRATION: clinicaltrials.gov; NCT04536012.

Patient-reported sleep and physical function during and after hospitalization.

PURPOSE: Poor sleep is associated with morbidity and mortality in the community; however, the health impact of poor sleep during and after hospitalization is poorly characterized. Our purpose was to describe trends in patient-reported sleep and physical function during and after hospitalization and evaluate sleep as a predictor of function after discharge. METHODS: This is a secondary analysis of trial data with 232 adults followed for 3months after hospital discharge. Main measures were patient-reported surveys on sleep (Pittsburgh Sleep Quality Index) and physical function (Katz Activities of Daily Living, Lawton Instrumental Activities of Daily Living, and Nagi Mobility Scale) were collected during hospitalization and at 1, 5, 9, and 13weeks postdischarge. RESULTS: Patient-reported sleep declined significantly during hospitalization and remained worse for 3months postdischarge (median Pittsburgh Sleep Quality Index=8 vs. 6, p < .001). In parallel, mobility declined significantly from baseline and remained worse at each follow-up time (median Nagi score=2 vs. 0, p < .001). Instrumental activities of daily living similarly decreased during and after hospitalization, but basic activities of daily living were unaffected. In adjusted time-series logistic regression models, the odds of mobility impairment were 1.48 times higher for each 1-point increase in Pittsburgh Sleep Quality Index score over time (95% CI 1.27-1.71, p < .001). CONCLUSIONS: Patient-reported sleep worsened during hospitalization, did not improve significantly for 3months after hospitalization, and poor sleep was a significant predictor of functional impairment over this time. Sleep dysfunction that begins with hospitalization may persist and prevent functional recovery after discharge. TRIAL REGISTRATION: The primary study was registered at ClinicalTrials.gov NCT03321279.

Remote Patient-Reported Outcomes and Activity Monitoring to Improve Patient-Clinician Communication Regarding Symptoms and Functional Status: A Randomized Controlled Trial.

PURPOSE: Routine collection of patient-generated health data (PGHD) may promote earlier recognition of symptomatic and functional decline. This trial assessed the impact of an intervention integrating remote PGHD collection with patient nudges on symptom and functional status understanding between patients with advanced cancer and their oncology team. METHODS: This three-arm randomized controlled trial was conducted from November 19, 2020, to December 17, 2021, at a large tertiary oncology practice. We enrolled patients with stage IV GI and lung cancers undergoing chemotherapy. Over 6 months, patients in two intervention arms received PROStep-weekly text message-based symptom surveys and passive activity monitoring using a wearable accelerometer. PGHD were summarized in dashboards given to patients' oncology team before appointments. One intervention arm received an additional text-based active choice prompt to discuss worsening symptoms or functional status with their clinician. Control patients did not receive PROStep. The coprimary outcomes patient perceptions of oncology team symptom and functional understanding at 6 months were measured on a 1-5 Likert scale (5 = high understanding). RESULTS: One hundred eight patients enrolled: 55% male, 81% White, and 77% had GI cancers. Patient-reported clinician understanding did not differ between control and intervention arms for symptoms (4.5 v 4.5; P = .87) or functional status (4.5 v 4.3; P = .31). In the intervention arms, combined patient adherence to weekly symptom reports and daily activity monitoring was 64% and 53%, respectively. Intervention patients in the PROStep versus PROStep + active choice arms reported low burden from wearing the accelerometer (mean burden [standard deviation], 2.7 [1.3] v 2.1 [1.3]; P = .15) and completing surveys (2.1 [1.2] v 1.9 [1.3]; P = .44). CONCLUSION: Patients receiving PROStep reported high understanding of symptoms and functional status from their oncology team, although this did not differ from controls.

Association of Time of Day with Delays in Antimicrobial Initiation among Ward Patients with Hospital-Onset Sepsis.

Rationale: Although the mainstay of sepsis treatment is timely initiation of broad-spectrum antimicrobials, treatment delays are common, especially among patients who develop hospital-onset sepsis. The time of day has been associated with suboptimal clinical care in several contexts, but its association with treatment initiation among patients with hospital-onset sepsis is unknown. Objectives: Assess the association of time of day with antimicrobial initiation among ward patients with hospital-onset sepsis. Methods: This retrospective cohort study included ward patients who developed hospital-onset sepsis while admitted to five acute care hospitals in a single health system from July 2017 through December 2019. Hospital-onset sepsis was defined by the Centers for Disease Control and Prevention Adult Sepsis Event criteria. We estimated the association between the hour of day and antimicrobial initiation among patients with hospital-onset sepsis using a discrete-time time-to-event model, accounting for time elapsed from sepsis onset. In a secondary analysis, we fit a quantile regression model to estimate the association between the hour of day of sepsis onset and time to antimicrobial initiation. Results: Among 1,672 patients with hospital-onset sepsis, the probability of antimicrobial initiation at any given hour varied nearly fivefold throughout the day, ranging from 3.0% (95% confidence interval [CI], 1.8-4.1%) at 7 a.m. to 13.9% (95% CI, 11.3-16.5%) at 6 p.m., with nadirs at 7 a.m. and 7 p.m. and progressive decline throughout the night shift (13.4% [95% CI, 10.7-16.0%] at 9 p.m. to 3.2% [95% CI, 2.0-4.0] at 6 a.m.). The standardized predicted median time to antimicrobial initiation was 3.2 hours (interquartile range [IQR], 2.5-3.8 h) for sepsis onset during the day shift (7 a.m.-7 p.m.) and 12.9 hours (IQR, 10.9-14.9 h) during the night shift (7 p.m.-7 a.m.). Conclusions: The probability of antimicrobial initiation among patients with new hospital-onset sepsis declined at shift changes and overnight. Time to antimicrobial initiation for patients with sepsis onset overnight was four times longer than for patients with onset during the day. These findings indicate that time of day is associated with important care processes for ward patients with hospital-onset sepsis. Future work should validate these findings in other settings and elucidate underlying mechanisms to inform quality-enhancing interventions.

Using remotely monitored patient activity patterns after hospital discharge to predict 30 day hospital readmission: a randomized trial.

Hospital readmission prediction models often perform poorly, but most only use information collected until the time of hospital discharge. In this clinical trial, we randomly assigned 500 patients discharged from hospital to home to use either a smartphone or wearable device to collect and transmit remote patient monitoring (RPM) data on activity patterns after hospital discharge. Analyses were conducted at the patient-day level using discrete-time survival analysis. Each arm was split into training and testing folds. The training set used fivefold cross-validation and then final model results are from predictions on the test set. A standard model comprised data collected up to the time of discharge including demographics, comorbidities, hospital length of stay, and vitals prior to discharge. An enhanced model consisted of the standard model plus RPM data. Traditional parametric regression models (logit and lasso) were compared to nonparametric machine learning approaches (random forest, gradient boosting, and ensemble). The main outcome was hospital readmission or death within 30 days of discharge. Prediction of 30-day hospital readmission significantly improved when including remotely-monitored patient data on activity patterns after hospital discharge and using nonparametric machine learning approaches. Wearables slightly outperformed smartphones but both had good prediction of 30-day hospital-readmission.

How Physician Self-Perceptions Affect the Impact of Peer Comparison Feedback on Opioid Prescribing.

Peer comparison feedback is a promising strategy for reducing opioid prescribing and opioid-related harms. Such comparisons may be particularly impactful among underestimating clinicians who do not perceive themselves as high prescribers relative to their peers. But peer comparisons could also unintentionally increase prescribing among overestimating clinicians who do not perceive themselves as lower prescribers than peers. The objective of this study was to assess if the impact of peer comparisons varied by clinicians' preexisting opioid prescribing self-perceptions. Subgroup analysis of a randomized trial of peer comparison interventions among emergency department and urgent care clinicians was used. Generalized mixed-effects models were used to assess whether the impact of peer comparisons, alone or combined with individual feedback, varied by underestimating or overestimating prescriber status. Underestimating and overestimating prescribers were defined as those who self-reported relative prescribing amounts that were lower and higher, respectively, than actual relative baseline amounts. The primary outcome was pills per opioid prescription. Among 438 clinicians, 54% (n = 236) provided baseline prescribing self-perceptions and were included in this analysis. Overall, 17% (n = 40) were underestimating prescribers whereas 5% (n = 11) were overestimating prescribers. Underestimating prescribers exhibited a differentially greater decrease in pills per prescription compared to nonunderestimating clinicians when receiving peer comparison feedback (1.7 pills, 95% CI, -3.2 to -0.2 pills) or combined peer and individual feedback (2.8 pills, 95% CI, -4.8 to -0.8 pills). In contrast, there were no differential changes in pills per prescription for overestimating versus nonoverestimating prescribers after receiving peer comparison (1.5 pills, 95% CI, -0.9 to 3.9 pills) or combined peer and individual feedback (3.0 pills, 95% CI, -0.3 to 6.2 pills). Peer comparisons were more impactful among clinicians who underestimated their prescribing compared to peers. By correcting inaccurate self-perceptions, peer comparison feedback can be an effective strategy for influencing opioid prescribing.

Disparities in emergency department and urgent care opioid prescribing before and after randomized clinician feedback interventions.

OBJECTIVES: Racial and ethnic minorities receive opioid prescriptions at lower rates and dosages than White patients. Though opioid stewardship interventions can improve or exacerbate these disparities, there is little evidence about these effects. We conducted a secondary analysis of a cluster-randomized controlled trial conducted among 438 clinicians from 21 emergency departments and 27 urgent care clinics. Our objective was to determine whether randomly allocated opioid stewardship clinician feedback interventions that were designed to reduce opioid prescriptions had unintended effects on disparities in prescribing by patient race and ethnicity. METHODS: The primary outcome was likelihood of receiving a low-pill prescription (low ≤10 pills, medium 11-19 pills, high ≥20 pills). Generalized mixed-effects models were used to determine patient characteristics associated with low-pill prescriptions during the baseline period. These models were then used to determine whether receipt of a low-pill prescription varied by patient race or ethnicity during the intervention period between usual care and three opioid stewardship interventions: (1) individual audit feedback, (2) peer comparison feedback, and (3) combined (individual audit + peer comparison) feedback. RESULTS: Compared with White patients, Black patients were more likely to receive a low-pill prescription during the baseline (adjusted odds ratio [OR] 1.18, 95% confidence interval [CI] 1.06-1.31, p = 0.002) and intervention (adjusted OR 1.43, 95% CI 1.07-1.91, p = 0.015). While combined feedback was associated with an overall increase in low-pill prescriptions as intended (adjusted OR 1.89, 95% CI 1.28-2.78, p = 0.001), there were no significant differences in treatment effects of any of the interventions by patient race and ethnicity. CONCLUSIONS: Combined individual audit and peer comparison feedback was associated with fewer opioid pills per prescription equally by patient race and ethnicity. However, the intervention did not significantly close the baseline disparity in prescribing by race.

A randomized controlled trial of gamification, financial incentives, or both to increase physical activity among patients with elevated risk for cardiovascular disease: rationale and design of the be active study.

BACKGROUND: Higher levels of physical activity are associated with improvements in cardiovascular health, and consensus guidelines recommend that individuals with or at risk for atherosclerotic cardiovascular disease (ASCVD) participate in regular physical activity. However, most adults do not achieve recommended levels of physical activity. Concepts from behavioral economics have been used to design scalable interventions that increase physical activity over short time periods, but the longer-term efficacy of these strategies is uncertain. STUDY DESIGN AND OBJECTIVES: BE ACTIVE (NCT03911141) is a pragmatic, virtual, randomized controlled trial designed to evaluate the effectiveness of 3 strategies informed by behavioral economic concepts to increase daily physical activity in patients with established ASCVD or 10-year ASCVD risk > 7.5% who are seen in primary care and cardiology clinics affiliated with the University of Pennsylvania Health System. Patients are contacted by email or text message, and complete enrollment and informed consent on the Penn Way to Health online platform. Patients are then provided with a wearable fitness tracker, establish a baseline daily step count, set a goal to increase daily step count by 33% to 50%, and are randomized 1:2:2:2 to control, gamification, financial incentives, or both gamification and financial incentives. Interventions continue for 12 months, with follow-up for an additional 6 months to evaluate the durability of behavior change. The trial has met its enrollment goal of 1050 participants, with a primary endpoint of change from baseline in daily steps over the 12-month intervention period. Key secondary endpoints include change from baseline in daily steps over the 6-month post-intervention follow-up period and change in moderate to vigorous physical activity over the intervention and follow-up periods. If the interventions prove effective, their effects on life expectancy will be compared with their costs in cost-effectiveness analysis. CONCLUSIONS: BE ACTIVE is a virtual, pragmatic randomized clinical trial powered to demonstrate whether gamification, financial incentives, or both are superior to attention control in increasing physical activity. Its results will have important implications for strategies to promote physical activity in patients with or at risk for ASCVD, as well as for the design and implementation of pragmatic virtual clinical trials within health systems.

Deploying Digital Health Technologies for Remote Physical Activity Monitoring of Rural Populations With Chronic Neurologic Disease.

Objective: The objective of this pilot study was to examine the feasibility of a remote physical activity monitoring program, quantify baseline activity levels, and examine predictors of activity among rurally residing adults with Parkinson disease (PD) or stroke. Design: Thirty-day observational study. Participants completed standardized assessments, connected a wearable device, and synced daily step counts via a remote monitoring platform. Setting: Community-based remote monitoring. Participants: Rurally residing adults with PD or stroke enrolled in the Veterans Health Administration. Intervention: N/A. Main Outcome Measures: Feasibility was evaluated using recruitment data (response rates), study completion (completed assessments and connected the wearable device), and device adherence (days recording ≥100 steps). Daily step counts were examined descriptively. Predictors of daily steps were explored across the full sample, then by diagnosis, using linear mixed-effects regression analyses. Results: Forty participants (n=20 PD; n=20 stroke) were included in the analysis with a mean (SD) age of 72.9 (7.6) years. Participants resided 252.6 (105.6) miles from the coordinating site. Recruitment response rates were 11% (PD) and 6% (stroke). Study completion rates were 71% (PD) and 80% (stroke). Device adherence rates were 97.0% (PD) and 95.2% (stroke). Participants with PD achieved a median [interquartile range] of 2618 [3896] steps per day and participants with stroke achieved 4832 [7383] steps. Age was the only significant predictor of daily steps for the full sample (-265 steps, 95% confidence interval [-407, -123]) and by diagnosis (PD, -175 steps, [-335, -15]; stroke, -357 steps [-603, -112]). Conclusions: A remote physical activity monitoring program for rurally residing individuals with PD or stroke was feasible. This study establishes a model for a scalable physical activity program for rural, older populations with neurologic conditions from a central coordinating site.

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.

Importance: Serious illness conversations (SICs) between oncology clinicians and patients are associated with improved quality of life and may reduce aggressive end-of-life care. However, most patients with cancer die without a documented SIC. Objective: To test the impact of behavioral nudges to clinicians to prompt SICs on the SIC rate and end-of-life outcomes among patients at high risk of death within 180 days (high-risk patients) as identified by a machine learning algorithm. Design, Setting, and Participants: This prespecified 40-week analysis of a stepped-wedge randomized clinical trial conducted between June 17, 2019, and April 20, 2020 (including 16 weeks of intervention rollout and 24 weeks of follow-up), included 20 506 patients with cancer representing 41 021 encounters at 9 tertiary or community-based medical oncology clinics in a large academic health system. The current analyses were conducted from June 1, 2021, to May 31, 2022. Intervention: High-risk patients were identified using a validated electronic health record machine learning algorithm to predict 6-month mortality. The intervention consisted of (1) weekly emails to clinicians comparing their SIC rates for all patients against peers' rates, (2) weekly lists of high-risk patients, and (3) opt-out text messages to prompt SICs before encounters with high-risk patients. Main Outcomes and Measures: The primary outcome was SIC rates for all and high-risk patient encounters; secondary end-of-life outcomes among decedents included inpatient death, hospice enrollment and length of stay, and intensive care unit admission and systemic therapy close to death. Intention-to-treat analyses were adjusted for clinic and wedge fixed effects and clustered at the oncologist level. Results: The study included 20 506 patients (mean [SD] age, 60.0 [14.0] years) and 41 021 patient encounters: 22 259 (54%) encounters with female patients, 28 907 (70.5%) with non-Hispanic White patients, and 5520 (13.5%) with high-risk patients; 1417 patients (6.9%) died by the end of follow-up. There were no meaningful differences in demographic characteristics in the control and intervention periods. Among high-risk patient encounters, the unadjusted SIC rates were 3.4% (59 of 1754 encounters) in the control period and 13.5% (510 of 3765 encounters) in the intervention period. In adjusted analyses, the intervention was associated with increased SICs for all patients (adjusted odds ratio, 2.09 [95% CI, 1.53-2.87]; P < .001) and decreased end-of-life systemic therapy (7.5% [72 of 957 patients] vs 10.4% [24 of 231 patients]; adjusted odds ratio, 0.25 [95% CI, 0.11-0.57]; P = .001) relative to controls, but there was no effect on hospice enrollment or length of stay, inpatient death, or end-of-life ICU use. Conclusions and Relevance: In this randomized clinical trial, a machine learning-based behavioral intervention and behavioral nudges to clinicans led to an increase in SICs and reduction in end-of-life systemic therapy but no changes in other end-of-life outcomes among outpatients with cancer. These results suggest that machine learning and behavioral nudges can lead to long-lasting improvements in cancer care delivery. Trial Registration: ClinicalTrials.gov Identifier: NCT03984773.

Feasibility and outcomes from using a commitment device and text message reminders to increase adherence to time-restricted eating: A randomized trial.

BACKGROUND: Obesity is strongly associated with cardiovascular disease, particularly through its effects on blood pressure. Though maintaining a negative caloric balance leads to weight loss, many patients struggle to adhere to low calorie diets over the long term. Time-restricted eating, a subtype of intermittent fasting (IF), may be an easier dietary pattern for patients to initiate and maintain. We tested the feasibility of a bidirectional texting strategy to help patients with obesity and hypertension initiate and maintain time-restricted eating, and whether a commitment device, a pledge to behave in a certain way in the future while making nonadherence costlier, would increase adherence beyond bidirectional texting. METHODS: Patients with obesity and hypertension seen in cardiology clinics were provided education on time-restricted eating and randomized to a commitment device versus attention control. Attention control consisted of daily bidirectional text messages asking whether patients adhered to IF and weekly text messages asking participants to send their weight and blood pressure. The commitment device involved the same text messages as attention control, plus a commitment contract, setting of implementation intentions with respect to details of time-restricted eating, and involvement of a support partner who received weekly updates on the participant's adherence to time-restricted eating. The intervention lasted 12 weeks, followed by a 6-week follow-up period. The primary outcome was days per week adherent to time-restricted eating over the 18-week study period, measured by daily self-report. We also compared change from baseline weight and blood pressure between randomized groups. RESULTS: A total of 37 patients were randomized and started the study-20 to attention control and 17 to the commitment device. Mean age was 60 years old, and mean BMI was 38.4 kg/m2. Over the 18-week study period, the mean ± standard deviation (SD) number of days per week adherent to time-restricted eating was 4.7 ± 1.9 in the control arm and 5.4 ± 1.7 in the intervention arm (P = .23). Mean systolic blood pressure declined from 135 to 128 mm Hg among all participants (P = .006) with no difference between groups in change from baseline blood pressure (P = .74). Weight decreased from 229 to 223 pounds among all participants (P = .25) with no significant difference between groups in change from baseline weight (P = .84). CONCLUSIONS: A bidirectional texting strategy was feasible for helping patients with obesity and hypertension initiate and adhere to time-restricted eating. Adding a commitment device to bidirectional texting did not increase adherence to time-restricted eating compared with attention control, nor were there significant between group changes in blood pressure or weight, but these comparisons were underpowered. A larger randomized trial of the effect of this scalable intervention, compared with usual care, on blood pressure and weight among patients with obesity and hypertension is warranted. CLINICAL TRIALS REGISTRATION: clinicaltrials.gov; unique identifier: NCT04836312.

Clinician Perceptions of Receiving Different Forms of Feedback on their Opioid Prescribing.

Opioid misuse represents a major public health issue in the United States. One driver is overprescription for acute pain, with the size of initial prescription associated with subsequent long-term use. However, little work has been done to elicit clinician feedback about interventions to reduce opioid prescribing. To address this knowledge gap, qualitative analyses were conducted with clinicians who participated in a randomized controlled trial in which clinicians received monthly emailed feedback notifications about their opioid prescribing behaviors. Semistructured telephone interviews were conducted (N = 12) with urgent care (N = 7) and emergency department (N = 5) clinicians who participated in the trial between November 2020 and April 2021. Clinicians appreciated feedback about their prescribing behavior and found comparative data with peer clinicians to be most useful. Sharing opioid prescribing feedback data with clinicians can be an acceptable way to address opioid prescribing among emergency and urgent care clinicians.

Effect of Nudges to Clinicians, Patients, or Both to Increase Statin Prescribing: A Cluster Randomized Clinical Trial.

Importance: Statins reduce the risk of major adverse cardiovascular events, but less than one-half of individuals in America who meet guideline criteria for a statin are actively prescribed this medication. Objective: To evaluate whether nudges to clinicians, patients, or both increase initiation of statin prescribing during primary care visits. Design, Setting, and Participants: This cluster randomized clinical trial evaluated statin prescribing of 158 clinicians from 28 primary care practices including 4131 patients. The design included a 12-month preintervention period and a 6-month intervention period between October 19, 2019, and April 18, 2021. Interventions: The usual care group received no interventions. The clinician nudge combined an active choice prompt in the electronic health record during the patient visit and monthly feedback on prescribing patterns compared with peers. The patient nudge was an interactive text message delivered 4 days before the visit. The combined nudge included the clinician and patient nudges. Main Outcomes and Measures: The primary outcome was initiation of a statin prescription during the visit. Results: The sample comprised 4131 patients with a mean (SD) age of 65.5 (10.5) years; 2120 (51.3%) were male; 1210 (29.3%) were Black, 106 (2.6%) were Hispanic, 2732 (66.1%) were White, and 83 (2.0%) were of other race or ethnicity, and 933 (22.6%) had atherosclerotic cardiovascular disease. In unadjusted analyses during the preintervention period, statins were prescribed to 5.6% of patients (105 of 1876) in the usual care group, 4.8% (97 of 2022) in the patient nudge group, 6.0% (104 of 1723) in the clinician nudge group, and 4.7% (82 of 1752) in the combined group. During the intervention, statins were prescribed to 7.3% of patients (75 of 1032) in the usual care group, 8.5% (100 of 1181) in the patient nudge group, 13.0% (128 of 981) in the clinician nudge arm, and 15.5% (145 of 937) in the combined group. In the main adjusted analyses relative to usual care, the clinician nudge significantly increased statin prescribing alone (5.5 percentage points; 95% CI, 3.4 to 7.8 percentage points; P = .01) and when combined with the patient nudge (7.2 percentage points; 95% CI, 5.1 to 9.1 percentage points; P = .001). The patient nudge alone did not change statin prescribing relative to usual care (0.9 percentage points; 95% CI, -0.8 to 2.5 percentage points; P = .32). Conclusions and Relevance: Nudges to clinicians with and without a patient nudge significantly increased initiation of a statin prescription during primary care visits. The patient nudge alone was not effective. Trial Registration: ClinicalTrials.gov Identifier: NCT04307472.

A Randomized Trial of Behavioral Nudges Delivered Through Text Messages to Increase Influenza Vaccination Among Patients With an Upcoming Primary Care Visit.

PURPOSE: To evaluate if nudges delivered by text message prior to an upcoming primary care visit can increase influenza vaccination rates. DESIGN: Randomized, controlled trial. SETTING: Two health systems in the Northeastern US between September 2020 and March 2021. SUBJECTS: 74,811 adults. INTERVENTIONS: Patients in the 19 intervention arms received 1-2 text messages in the 3 days preceding their appointment that varied in their format, interactivity, and content. MEASURES: Influenza vaccination. ANALYSIS: Intention-to-treat. RESULTS: Participants had a mean (SD) age of 50.7 (16.2) years; 55.8% (41,771) were female, 70.6% (52,826) were White, and 19.0% (14,222) were Black. Among the interventions, 5 of 19 (26.3%) had a significantly greater vaccination rate than control. On average, the 19 interventions increased vaccination relative to control by 1.8 percentage points or 6.1% (P = .005). The top performing text message described the vaccine to the patient as "reserved for you" and led to a 3.1 percentage point increase (95% CI, 1.3 to 4.9; P < .001) in vaccination relative to control. Three of the top five performing messages described the vaccine as "reserved for you." None of the interventions performed worse than control. CONCLUSIONS: Text messages encouraging vaccination and delivered prior to an upcoming appointment significantly increased influenza vaccination rates and could be a scalable approach to increase vaccination more broadly.

Oncologist Perceptions of Algorithm-Based Nudges to Prompt Early Serious Illness Communication: A Qualitative Study.

Background: Early serious illness conversations (SICs) about goals of care and prognosis improve mood, quality of life, and end-of-life care quality. Algorithm-based behavioral nudges to oncologists increase the frequency and timeliness of such conversations. However, clinicians' perspectives on such nudges are unknown. Design: Qualitative study consisting of semistructured interviews among medical oncology clinicians who participated in a stepped-wedge cluster randomized trial of Conversation Connect, an algorithm-based intervention consisting of behavioral nudges to promote early SICs in the outpatient oncology setting. Results: Of 79 eligible oncology clinicians, 56 (71%) were approached to participate in interviews and 25 (45%) accepted. Key facilitators to algorithm-based nudges included prompting documentation of conversations, peer comparisons, performance reports, and validating norms around early conversations. Barriers included cancer-specific heterogeneity in algorithm performance and the frequency and tone of text messages. Areas of improvement included utilizing different information channels, identifying patients earlier in the disease trajectory, and incorporating patient-targeted messaging that emphasizes the value of early conversations. Conclusions: Oncology clinicians identified key facilitators and barriers to Conversation Connect. These insights inform future algorithm-based supportive care interventions in oncology. Controlled trial (NCT03984773).

Effect of Text Message Reminders and Vaccine Reservations on Adherence to a Health System COVID-19 Vaccination Policy: A Randomized Clinical Trial.

Importance: Many organizations implemented COVID-19 vaccination requirements during the pandemic, but the best way to increase adherence to these policies is unknown. Objective: To evaluate if behavioral nudges delivered through text messages could accelerate adherence to a health system's COVID-19 vaccination policy. Design, Setting, and Participants: This randomized clinical trial was conducted within Ascension health system from October 11 to November 8, 2021. Participants included health system employees in the Midwest or South US who were not adherent with the vaccination policy 1 month before its deadline. Data were analyzed from November 17, 2021, to February 25, 2022. Interventions: Participants were randomly assigned to control or to receive a text message intervention that stated a vaccine had been reserved for the participant, with a scheduled date for vaccination within a 2-week period. Participants could reschedule to a different date within the period or upload a copy of their vaccination card. Follow-up text message reminders were sent the day before and the day of the appointment. Main Outcomes and Measures: The primary outcome was adherence to the health system's vaccination policy during the 2-week intervention. Secondary outcomes included time to vaccination during a 4-week follow-up period. Results: The sample included 2000 participants (mean [SD] age, 36.4 [12.3] years; 1724 [86.2%] women), with 1000 participants randomized to the control group and 1000 participants randomized to the intervention group. Overall, there were 164 Hispanic participants (8.2%), 46 non-Hispanic Asian participants (2.3%), 202 non-Hispanic Black participants (10.1%), and 1418 non-Hispanic White participants (70.9%). By the end of the 2-week intervention, 363 participants in the text message nudge group (36.3%) and 318 participants in the control group (31.8%) were adherent with the vaccination policy, representing a significant increase of 4.9 (95% CI, 0.8 to 9.1) percentage points in adjusted analyses comparing the nudge group with the control group (P = .02). Among participants who became adherent by the end of the 4-week follow-up period, the text message nudge significantly reduced time to adherence by a mean of 2.4 (95% CI, 2.1 to 4.7) days (P < .001) and a median of 5.0 (95% CI, 2.5 to 7.7) days (P < .001) compared with the control group. At 4 weeks, overall vaccination adherence was no longer different between groups (control: 477 participants [47.7%]; intervention: 472 participants [47.2%]). Conclusions and Relevance: This randomized clinical trial found that a behavioral nudge delivered through text messages accelerated adherence to a health system's COVID-19 vaccination policy but did change overall adherence by the time of the policy deadline. Trial Registration: ClinicalTrials.gov Identifier: NCT05037201.

Patient and clinician nudges to improve symptom management in advanced cancer using patient-generated health data: study protocol for the PROStep randomised controlled trial.

INTRODUCTION: Patients with advanced cancers often face significant symptoms from their cancer and adverse effects from cancer-associated therapy. Patient-generated health data (PGHD) are routinely collected information about symptoms and activity levels that patients either directly report or passively record using devices such as wearable accelerometers. The objective of this study was to test the impact of an intervention integrating remote collection of PGHD with clinician and patient nudges to inform communication between patients with advanced cancer and their oncology team regarding symptom burden and functional status. METHODS AND ANALYSIS: This single-centre prospective randomised controlled trial randomises patients with metastatic gastrointestinal or lung cancers into one of three arms: (A) usual care, (B) an intervention that integrates PGHD (including weekly text-based symptom surveys and passively recorded step counts) into a dashboard delivered to oncology clinicians at each visit and (C) the same intervention as arm B but with an additional text-based active choice intervention to patients to encourage discussing their symptoms with their oncology team. The study will enrol approximately 125 participants. The coprimary outcomes are patient perceptions of their oncology team's understanding of their symptoms and their functional status. Secondary outcomes are intervention utility and adherence. ETHICS AND DISSEMINATION: This study has been approved by the institutional review board at the University of Pennsylvania. Study results will be disseminated using methods that describe the results in ways that key stakeholders can best understand and implement. TRIAL REGISTRATION NUMBERS: NCT04616768 and 843 616.

Oncologist phenotypes and associations with response to a machine learning-based intervention to increase advance care planning: Secondary analysis of a randomized clinical trial.

BACKGROUND: While health systems have implemented multifaceted interventions to improve physician and patient communication in serious illnesses such as cancer, clinicians vary in their response to these initiatives. In this secondary analysis of a randomized trial, we identified phenotypes of oncology clinicians based on practice pattern and demographic data, then evaluated associations between such phenotypes and response to a machine learning (ML)-based intervention to prompt earlier advance care planning (ACP) for patients with cancer. METHODS AND FINDINGS: Between June and November 2019, we conducted a pragmatic randomized controlled trial testing the impact of text message prompts to 78 oncology clinicians at 9 oncology practices to perform ACP conversations among patients with cancer at high risk of 180-day mortality, identified using a ML prognostic algorithm. All practices began in the pre-intervention group, which received weekly emails about ACP performance only; practices were sequentially randomized to receive the intervention at 4-week intervals in a stepped-wedge design. We used latent profile analysis (LPA) to identify oncologist phenotypes based on 11 baseline demographic and practice pattern variables identified using EHR and internal administrative sources. Difference-in-differences analyses assessed associations between oncologist phenotype and the outcome of change in ACP conversation rate, before and during the intervention period. Primary analyses were adjusted for patients' sex, age, race, insurance status, marital status, and Charlson comorbidity index. The sample consisted of 2695 patients with a mean age of 64.9 years, of whom 72% were White, 20% were Black, and 52% were male. 78 oncology clinicians (42 oncologists, 36 advanced practice providers) were included. Three oncologist phenotypes were identified: Class 1 (n = 9) composed primarily of high-volume generalist oncologists, Class 2 (n = 5) comprised primarily of low-volume specialist oncologists; and 3) Class 3 (n = 28), composed primarily of high-volume specialist oncologists. Compared with class 1 and class 3, class 2 had lower mean clinic days per week (1.6 vs 2.5 [class 3] vs 4.4 [class 1]) a higher percentage of new patients per week (35% vs 21% vs 18%), higher baseline ACP rates (3.9% vs 1.6% vs 0.8%), and lower baseline rates of chemotherapy within 14 days of death (1.4% vs 6.5% vs 7.1%). Overall, ACP rates were 3.6% in the pre-intervention wedges and 15.2% in intervention wedges (11.6 percentage-point difference). Compared to class 3, oncologists in class 1 (adjusted percentage-point difference-in-differences 3.6, 95% CI 1.0 to 6.1, p = 0.006) and class 2 (adjusted percentage-point difference-in-differences 12.3, 95% confidence interval [CI] 4.3 to 20.3, p = 0.003) had greater response to the intervention. CONCLUSIONS: Patient volume and time availability may be associated with oncologists' response to interventions to increase ACP. Future interventions to prompt ACP should prioritize making time available for such conversations between oncologists and their patients.