Patients with cancer spend considerable time commuting to, waiting for, and receiving health care. Patient-reported outcomes have been collected electronically to monitor patients for toxicity related to treatment, but, to the authors' knowledge, they have not been used as a strategy to minimize patients' time spent on cancer care by streamlining care delivery. Researchers at Penn Medicine set an objective to assess the effectiveness and implementation of a text message-based symptom reporting electronic triage (e-triage) versus usual care to minimize the time toxicity associated with ambulatory cancer care. The methods employed included a hybrid type 1 effectiveness-implementation, unblinded, randomized controlled trial and sequential mixed-methods study, which was conducted between December 1, 2021, and December 31, 2022, with a follow-up period of 3 months or three visits (whichever came first, but all within the 2-year window). Adult patients with solid tumors receiving single-agent immune checkpoint inhibitors (ICIs) with access to a text-messaging device were enrolled, with a target sample size of 176. The intervention was a symptom-based e-triage via mobile text messaging combined with routine laboratory testing. Participants in the e-triage group with normal bloodwork and no symptoms of drug toxicity on e-triage were eligible to fast-track to ICI infusion, bypassing the pretreatment office visit. The primary end point was total time per ambulatory encounter; secondary end points included wait time, ED or hospital visits, health-related quality of life, patient satisfaction, and implementation (reach and fidelity). Implementation readiness (acceptability, appropriateness, and feasibility), barriers, and facilitators were evaluated in a mixed-methods analysis among treating oncologists, measured via surveys and focus groups. For the study, 40 patients were randomly assigned, of which 31 were evaluated for the primary end point; the median age among the 40 participants was 67.5 years of age (interquartile range 59.5-71.5 years of age), 80.0% were male, and 84.6% were white. Those randomly assigned to the e-triage group of the pilot randomized controlled trial (n=19, n=16 evaluable) had an average of 66.0 minutes less total time (95% confidence interval [CI], -123.7 to -8.08 minutes; P=0.03) and 30.1 minutes less wait time (95% CI, -60.9 to 1.1 minutes; P=0.08) per encounter, than those in usual care (n=21 randomly assigned, n=15 evaluable). ED or hospital visits, health-related quality of life, and patient satisfaction scores were similar. In the mixed-methods study, oncologists (n=31, 17 completed the survey) found the e-triage acceptable (mean 3.8, standard error [SE] 0.1), appropriate (mean 3.8, SE 0.1), and feasible (mean 3.9, SE 0.1) on a 5-point Likert scale of agreeability. Perceived barriers to uptake included challenges in patient identification, potential for drug toxicity underreporting, and reimbursement concerns. The authors conclude that the results of this pilot randomized controlled trial of a text message-based e-triage supports further investigation into the use of text message-based symptom reporting by patients as a strategy to safely assess readiness for treatment and thus reduce the time toxicity associated with cancer care.

223 Background: Serious illness conversations (SICs) about patients’ values and care preferences are tied to improved outcomes and quality of life. However, SICs can be hard to implement early in the cancer care journey, and questions remain about how and when to start. Following a pragmatic trial testing behavioral nudges to promote SICs in oncology (NCT04867850), we used an explanatory-sequential mixed methods design to gauge patient and clinician perspectives on the best communication strategy for SICs. Methods: Thirty patients with cancer at high mortality risk and 16 oncology clinicians were recruited from our academic cancer center. Guided by the Consolidated Framework for Implementation Research, our interviews systematically assessed multi-level factors shaping SIC implementation. In addition to interviews, patients completed a structured survey with validated measures on patient-focused communication and care planning. Survey data were studied descriptively, interviews were analyzed thematically, and both were integrated to triangulate qualitative and quantitative results. Results: Participants described two SIC types, which we classified as event-triggered and phased . Clinicians identified event-triggered SICs as prompted by acute incidents (e.g., disease stage transition) and more likely to lead to EHR documentation. However, they were seen as prohibitively time-consuming, and as such, did not become a top priority until a crisis arose. Patients were also uncomfortable with extensive early SICs, wanting to keep hope and avoid information overload soon after a diagnosis. They preferred not to discuss “turns for the worse” until they faced an acute challenge, at which point they valued thorough SICs. In surveys, almost all patients reported asking about benefits (96%), risks (93%), and quality of life (81%) tied to treatment, but few raised sensitive topics like planning for if things got worse (44%). By contrast, phased SICs were described as ongoing, progressive conversations not prompted by specific events and that arose early but deepened over time as a patient and care team nurtured their relationship. Patients and clinicians described phased SICs as better at promoting person-centered care and an essential foundation for SICs prompted by potential transitions. However, since these discussions occur gradually, clinicians reported challenges documenting them, reducing their value at informing future decisions and the ability to know whether conversations occurred at all. Conclusions: Interventions to increase SICs often focus on acute moments in the care trajectory. However, our study suggests that ongoing, staged approaches to SICs are vital for goal-concordant care as well and may be more easily integrated into busy clinical workflows. Further work should investigate ways to support clinicians in both SIC types, such as flexible documentation tools aligned with each approach.

ImportanceSerious illness conversations (SICs) that elicit patients' values, goals, and care preferences reduce anxiety and depression and improve quality of life, but occur infrequently for patients with cancer. Behavioral economic implementation strategies (nudges) directed at clinicians and/or patients may increase SIC completion. ObjectiveTo test the independent and combined effects of clinician and patient nudges on SIC completion. Design, Setting, and ParticipantsA 2 x 2 factorial, cluster randomized trial was conducted from September 7, 2021, to March 11, 2022, at oncology clinics across 4 hospitals and 6 community sites within a large academic health system in Pennsylvania and New Jersey among 163 medical and gynecologic oncology clinicians and 4450 patients with cancer at high risk of mortality (>= 10% risk of 180-day mortality). InterventionsClinician clusters and patients were independently randomized to receive usual care vs nudges, resulting in 4 arms: (1) active control, operating for 2 years prior to trial start, consisting of clinician text message reminders to complete SICs for patients at high mortality risk; (2) clinician nudge only, consisting of active control plus weekly peer comparisons of clinician-level SIC completion rates; (3) patient nudge only, consisting of active control plus a preclinic electronic communication designed to prime patients for SICs; and (4) combined clinician and patient nudges. Main Outcomes and MeasuresThe primary outcome was a documented SIC in the electronic health record within 6 months of a participant's first clinic visit after randomization. Analysis was performed on an intent-to-treat basis at the patient level. ResultsThe study accrued 4450 patients (median age, 67 years [IQR, 59-75 years]; 2352 women [52.9%]) seen by 163 clinicians, randomized to active control (n = 1004), clinician nudge (n = 1179), patient nudge (n = 997), or combined nudges (n = 1270). Overall patient-level rates of 6-month SIC completion were 11.2% for the active control arm (112 of 1004), 11.5% for the clinician nudge arm (136 of 1179), 11.5% for the patient nudge arm (115 of 997), and 14.1% for the combined nudge arm (179 of 1270). Compared with active control, the combined nudges were associated with an increase in SIC rates (ratio of hazard ratios [rHR], 1.55 [95% CI, 1.00-2.40]; P = .049), whereas the clinician nudge (HR, 0.95 [95% CI, 0.64-1.41; P = .79) and patient nudge (HR, 0.99 [95% CI, 0.73-1.33]; P = .93) were not. Conclusions and RelevanceIn this cluster randomized trial, nudges combining clinician peer comparisons with patient priming questionnaires were associated with a marginal increase in documented SICs compared with an active control. Combining clinician- and patient-directed nudges may help to promote SICs in routine cancer care. Trial RegistrationClinicalTrials.gov Identifier: NCT04867850

PURPOSE Few cancer centers systematically engage patients with evidence-based tobacco treatment despite its positive effect on quality of life and survival. Implementation strategies directed at patients, clinicians, or both may increase tobacco use treatment (TUT) within oncology. METHODS We conducted a four-arm cluster-randomized pragmatic trial across 11 clinical sites comparing the effect of strategies informed by behavioral economics on TUT engagement during oncology encounters with cancer patients. We delivered electronic health record (EHR)-based nudges promoting TUT across four nudge conditions: patient only, clinician only, patient and clinician, or usual care. Nudges were designed to counteract cognitive biases that reduce TUT engagement. The primary outcome was TUT penetration, defined as the proportion of patients with documented TUT referral or a medication prescription in the EHR. Generalized estimating equations were used to estimate the parameters of a linear model. RESULTS From June 2021 to July 2022, we randomly assigned 246 clinicians in 95 clusters, and collected TUT penetration data from their encounters with 2,146 eligible patients who smoke receiving oncologic care. Intent-to-treat (ITT) analysis showed that the clinician nudge led to a significant increase in TUT penetration versus usual care (35.6% v 13.5%; OR = 3.64; 95% CI, 2.52 to 5.24; P < .0001). Completer-only analysis (N = 1,795) showed similar impact (37.7% clinician nudge v 13.5% usual care; OR = 3.77; 95% CI, 2.73 to 5.19; P < .0001). Clinician type affected TUT penetration, with physicians less likely to provide TUT than advanced practice providers (ITT OR = 0.67; 95% CI, 0.51 to 0.88; P = .004). CONCLUSION EHR nudges, informed by behavioral economics and aimed at oncology clinicians, appear to substantially increase TUT penetration. Adding patient nudges to the implementation strategy did not affect TUT penetration rates.

1514 Background: Early serious illness conversations (SICs) elicit patients’ values, goals, and care preferences and have been shown to improve outcomes and reduce end-of-life healthcare utilization for patients with cancer. However, most patients with cancer die without a documented SIC. Given prior evidence that strategies informed by behavioral economics (“nudges”) increase SIC rates, our objective was to test the independent and additive effects of clinician- and patient-directed nudges to increase SIC completion. Methods: We conducted a 2 × 2 factorial, cluster-randomized pragmatic trial (NCT04867850) to test the effects of nudges to clinicians, patients, or both, compared to usual care, on SIC completion. Usual care was an active control consisting of clinician-directed text messages sent before routine clinic sessions, identifying patients at high risk of 6-month mortality as predicted by a validated machine-learning prognostic algorithm. The clinician nudge additionally included weekly peer comparisons on clinician-level SIC completion rates. The patient nudge consisted of a patient-facing message sent electronically before an index clinic visit, asking a 3-question survey designed to prime patients for an SIC with their oncology team. Participants included medical/gynecologic oncologists and advanced practice providers (APPs) within a large academic health system and their high-risk patients. We independently randomized oncologist/APP clusters and patients to receive nudges vs. usual care. The primary outcome was a documented SIC in the electronic health record within 6 months of enrollment. Using a Cox proportional hazards model with cluster robust standard errors, we performed a time-to-event analysis and tested for heterogeneity of effect across prespecified subgroups. Results: From September 2021 to March 2022, the study accrued 4,450 patients (median age 67, 52.9% female, 17.3% Black, 2.7% Hispanic) seen by 166 clinicians across 4 hospitals and 6 community sites, randomized to clinician nudge (n=1,179), patient nudge (n=997), both (n=1,270), or active control (n=1,004). Overall patient-level rates of 6-month SIC completion were: 11.5% (clinician nudge), 11.5% (patient nudge), 14.1% (both), and 11.2% (active control). Compared to the active control, participants in the combination nudge arm were more likely to engage in SICs (hazard ratio [HR] 1.55, 95% confidence interval [CI] 1.00-2.40), whereas those in the clinician (HR 0.95, 95% CI 0.64-1.41) and patient (HR 0.99, 95% CI 0.73-1.33) nudge arms were not. There was no effect heterogeneity across age and race subgroups. Conclusions: Clinician- and patient-directed nudges may be synergistic in promoting serious illness communication at scale and equitably in routine cancer care. Effects on end-of-life care among decedents are forthcoming. Clinical trial information: NCT04867850 .

301 Background: Innovative strategies to mitigate the time toxicity of cancer therapy are desperately needed. We have shown that a text-based e-triage can utilize patient-reported outcomes to identify patients without immune checkpoint inhibitor (ICI) toxicity who could safely fast-track to ICI infusion without a pre-infusion office visit. We report the efficacy of e-triage versus usual care to minimize the time toxicity of cancer care. Methods: This hybrid type 1 effectiveness-implementation randomized controlled trial was conducted at Penn Medicine between December 2021 and December 2022. Eligible patients spoke English, were receiving single agent ICI for a solid tumor, and had access to a mobile device with text messaging. The e-triage arm included ICI toxicity symptom assessment via two-way text messaging 96 hours prior to scheduled ICI and routine laboratory testing. Patients on the e-triage arm with normal bloodwork and no symptoms identified by the e-triage were eligible to fast-track to ICI infusion, bypassing the pre-treatment office visit. Usual care was standard office visits. Primary endpoint was care time (total time per ambulatory encounter including commute-, wait-, infusion-, and lab-times). Secondary endpoints were patient wait time per encounter, incident emergency department (ED) or hospital visits during follow-up, health related quality of life (HRQOL) measured by The Functional Assessment of Cancer Therapy-General, and patient satisfaction measured by PSQ-18. Differences in proportions of ED or hospital visits between arms were evaluated by the Fisher’s exact test. Linear mixed-effects models with random intercepts for each individual evaluated differences in all other endpoints between arms, accounting for within-patient correlation. Implementation outcomes were adoption (# patients who participated in the trial out of # approached) and fidelity (# patients on the intervention arm who followed their triage assignment). Acceptability, feasibility, and appropriateness outcomes were reported previously. Results: Among 152 eligible patients, 51 consented onto study (adoption rate 33.6%) and 40 were randomized (n=21, usual care; n=19, e-triage). Patient characteristics will be presented. Of 52 encounters on the e-triage arm, 23 adhered to their e-triage assessment (fidelity rate 44.2%). Compared with the usual care arm, patients on the e-triage arm had an average of 70 minutes less care time per encounter (95% CI -123.7 to –8.08 minutes, p=0.03) and 30.1 minutes less wait time (95% CI -61 to 1.1 minutes, p=0.08). The incidence of ED or hospital visits did not differ by treatment arm (usual care, n=2, 12.5% vs. intervention, n=3, 20%, p=0.65). HRQOL and patient satisfaction scores were similar by treatment arm. Conclusions: Results from this pilot trial support further work to optimize the design and implementation of a mobile e-triage program to personalize cancer care delivery and minimize time toxicity. Clinical trial information: NCT05134636 .

1537 Background: Patients spend substantial time receiving cancer care, and innovative strategies to decrease time toxicity are needed. We have shown that a text-based triage can identify patients tolerating checkpoint inhibitors (ICI) without toxicity who could safely fast-track directly to ICI infusion. However, oncologists’ readiness to implement this strategy is unknown. Methods: This sequential mixed-methods study included oncologists treating solid-tumor patients with ICIs at Penn Medicine. In phase 1, participants completed a 26-item survey assessing readiness to implement a digital strategy, using the Acceptability, Appropriateness, and Feasibility of Intervention Measures (AIM, IAM, and FIM), as well as perspectives of time toxicity. Each measure consisted of 4 items on a 5-point Likert scale for which means (M) and standard errors (SE) were calculated. In phase 2, a focus group (FG) was led by Penn’s Mixed Methods Research Lab to better understand the barriers and facilitators to implementing a digital strategy among oncologists. The FG transcript was reviewed and coded in NVivo with identification of emerging themes. Results: 32 faculty members were eligible, of whom 17 (53%) completed the survey and 14 (44%) participated in the FG. Respondents were 53% (n=9) female, 65% (n=11) White, and 53% (n=9) full-time clinicians (non-research faculty); 41% (n=7) reported > 10 years in practice. Quantitative analysis identified infusion (n=11, 65%), commuting (n=11,65%), and waiting for the physician (n=8, 47%) as the top 3 sources of time toxicity among oncologists. Most agreed that novel interventions are needed to improve the patient-experience (M=4.9, SE=0.08) on a Likert scale of agreeability (1-5, 5=strongly agree). On this scale, our text-based digital strategy to allow patients to fast-track care was found to be acceptable (M=3.8, SE =0.1), appropriate (M=3.8, SE=0.1), and feasible (M=3.9, SE=0.1). Qualitative analysis revealed the following major themes: 1) barriers to implementing a text-based digital strategy including a) health system built for clinician convenience, b) concern with being viewed as “slackers” by administration, c) concerns about overlooking symptoms, d) difficulties identifying appropriate patients, and e) communication issues; and 2) facilitators to adopting this new strategy including a) openness to change, 2) utilizing strengths of care team, and 3) optimism of this digital tool. Conclusions: Oncologists recognize time toxicity is a common complication of cancer care. Digital interventions to triage patients who are not experiencing treatment toxicity–thereby reducing time toxicity–were deemed acceptable, appropriate, and feasible. To integrate this technology, further research is required to address key barriers to uptake in routine care.

6527 Background: Patients with cancer spend substantial time receiving cancer care. There is a need for innovative strategies to decrease the time burden of cancer therapy. The current care model consists largely of in-person visits to assess treatment toxicity. Most patients treated with immunotherapy, however, do not experience substantial toxicity. We designed and evaluated a text-based instrument to identify patients without symptoms of immunotherapy toxicity. This instrument has the potential to be combined with lab assessment to identify individuals who can safely proceed directly to treatment, lessening the need for in-person office visits. Methods: This cross-sectional study evaluated the performance characteristics of a text-based instrument to identify patient-reported immunotherapy toxicity, against the gold standard in-person provider assessment documented in the electronic medical record (EMR). Those eligible for inclusion spoke English, were receiving single agent immune checkpoint blockade for a solid tumor, and had access to a mobile device with text messaging capabilities. The instrument contained 16 questions adapted from the NCI Pro-CTCAE and was administered via text-message 96 hours prior to the patient’s scheduled infusion visit. Patient perspectives were quantified via a 13-item questionnaire. Results: Between October 1 and November 25, 2021, 50 patients enrolled in the study, and 45 patients completed the instrument (90% response). The median age was 68 (IQR 60-72), 31 (62%) were male, and 44 (88%) were white. Most patients received either pembrolizumab (n=27, 54%) or nivolumab (n=17, 34%) in the palliative setting (n=37, 74%) for genitourinary (n=15, 30%), lung (n=13, 26%), or skin (n=11, 22%) cancer. Patients who completed the instrument were younger (median age 67 vs 76) than those who did not complete the instrument. The prevalence of immune related toxicity documented in the EMR was 57.8%. The sensitivity and negative predictive value of the instrument was 100% (95% CI 0.87-1.00) and 100% (95% CI 0.664-1.00), respectively; other accuracy parameters are presented in the Table. The patient user questionnaire revealed that visual impairment, lack of access to a smart phone, and lack of recognition of the instrument were barriers to completion. Conclusions: A text-based platform is both feasible and effective at identifying patients who are not experiencing symptoms of immune toxicity, and when combined with lab assessment, can eliminate office visits for up to 47% of patients. A prospective clinical trial to assess this is underway (NCT05134636). [Table: see text]