Understanding the financial cost of cancer clinical trial participation.

BACKGROUND: Though financial hardship is a well-documented adverse effect of standard-of-care cancer treatment, little is known about out-of-pocket costs and their impact on patients participating in cancer clinical trials. This study explored the financial effects of cancer clinical trial participation. METHODS: This cross-sectional analysis used survey data collected in December 2022 and May 2023 from individuals with cancer previously served by Patient Advocate Foundation, a nonprofit organization providing social needs navigation and financial assistance to US adults with a chronic illness. Surveys included questions on cancer clinical trial participation, trial-related financial hardship, and sociodemographic data. Descriptive and bivariate analyses were conducted using Cramer's V to estimate the in-sample magnitude of association. Associations between trial-related financial hardship and sociodemographics were estimated using adjusted relative risks (aRR) and corresponding 95% confidence intervals (CI) from modified Poisson regression models with robust standard errors. RESULTS: Of 650 survey respondents, 18% (N = 118) reported ever participating in a cancer clinical trial. Of those, 47% (n = 55) reported financial hardship as a result of their trial participation. Respondents reporting trial-related financial hardship were more often unemployed or disabled (58% vs. 43%; V = 0.15), Medicare enrolled (53% vs. 40%; V = 0.15), and traveled >1 h to their cancer provider (45% vs. 17%; V = 0.33) compared to respondents reporting no hardship. Respondents who experienced trial-related financial hardship most often reported expenses from travel (reported by 71% of respondents), medical bills (58%), dining out (40%), or housing needs (40%). Modeling results indicated that respondents traveling >1 h vs. ≤30 min to their cancer provider had a 2.2× higher risk of financial hardship, even after adjusting for respondent race, income, employment, and insurance status (aRR = 2.2, 95% CI 1.3-3.8). Most respondents (53%) reported needing $200-$1000 per month to compensate for trial-related expenses. Over half (51%) of respondents reported less willingness to participate in future clinical trials due to incurred financial hardship. Notably, of patients who did not participate in a cancer clinical trial (n = 532), 13% declined participation due to cost. CONCLUSION: Cancer clinical trial-related financial hardship, most often stemming from travel expenses, affected almost half of trial-enrolled patients. Interventions are needed to reduce adverse financial participation effects and potentially improve cancer clinical trial participation.

Trajectories of Health Care Contact Days for Patients With Stage IV Non-Small Cell Lung Cancer.

Importance: Patients with stage IV non-small cell lung cancer (NSCLC) experience substantial morbidity and mortality. Contact days (ie, the number of days with health care contact outside the home) measure how much of a person's life is consumed by health care, yet little is known about patterns of contact days for patients with NSCLC. Objective: To describe the trajectories of contact days in patients with stage IV NSCLC and how trajectories vary by receipt of cancer-directed treatment in routine practice. Design, Setting, and Participants: A retrospective, population-based decedent cohort study was conducted in Ontario, Canada. Participants included adults aged 20 years or older who were diagnosed with stage IV NSCLC (January 1, 2014, to December 31, 2017) and died (January 1, 2014, to December 31, 2019); there was a maximum 2-year follow-up. Data analysis was conducted from February 22 to August 16, 2023. Exposure: Systemic cancer-directed therapy (yes or no) and type of therapy (chemotherapy vs immunotherapy vs targeted therapy). Main Outcomes and Measures: Contact days (days with health care contact, outpatient or institution-based, outside the home) were identified through administrative data. The weekly percentage of contact days and fitted models with cubic splines were quantified to describe trajectories from diagnosis until death. Results: A total of 5785 decedents with stage IV NSCLC were included (median age, 70 [IQR 62-77] years; 3108 [53.7%] were male, and 1985 [34.3%] received systemic therapy). The median overall survival was 108 (IQR, 49-426) days, median contact days were 36 (IQR, 21-62), and the median percentage that were contact days was 33.3%. A median of 5 (IQR, 2-10) days were spent with specialty palliative care. Patients who did not receive systemic therapy had a median overall survival of 66 (IQR, 34-130) days and median contact days of 28 (IQR, 17-44), of which a median of 5 (IQR, 2-9) days were spent with specialty palliative care. Overall and for subgroups, normalized trajectories followed a U-shaped distribution: contact days were most frequent immediately after diagnosis and before death. Patients who received targeted therapy had the lowest contact day rate during the trough (10.6%; vs immunotherapy, 15.4%; vs chemotherapy, 17.7%). Conclusions and Relevance: In this cohort study, decedents with stage IV NSCLC had a median survival in the order of 3.5 months and spent 1 in every 3 days alive interacting with the health care system outside the home. These results highlight the need to better support patients and care partners, benchmark appropriateness, and improve care delivery.

Dedicated financial hardship screening adds value to routine distress screening among gynecologic cancer patients.

OBJECTIVES: To evaluate existing distress screening to identify patients with financial hardship (FH) compared to dedicated FH screening and assess patient attitudes toward FH screening. METHODS: We screened gynecologic cancer patients starting a new line of therapy. Existing screening included: (1) Moderate/severe distress defined as Distress Thermometer score ≥ 4, (2) practical concerns identified from Problem Checklist, and (3) a single question assessing trouble paying for medications. FH screening included: (1) Comprehensive Score for Financial Toxicity (COST) tool and (2) 10-item Financial Needs Checklist to guide referrals. FH was defined as COST score < 26. We calculated sensitivity (patients with moderate/severe distress + FH over total patients with FH) and specificity (patients with no/mild distress + no FH over total patients with no FH) to assess the extent distress screening could capture FH. Surveys and exit interviews assessed patient perspectives toward screening. RESULTS: Of 364 patients screened for distress, average age was 62 years, 25% were Black, 45% were Medicare beneficiaries, 32% had moderate/severe distress, 15% reported ≥1 practical concern, and 0 reported trouble paying for medications. Most (n = 357, 98%) patients also completed FH screening: of them, 24% screened positive for FH, 32% reported ≥1 financial need. Distress screening had 57% sensitivity and 77% specificity for FH. Based on 79 surveys and 43 exit interviews, FH screening was acceptable with feedback to improve the timing and setting of screening. CONCLUSIONS: Dedicated FH screening was feasible and acceptable, but sensitivity was low. Importantly, 40% of women with FH would not have been identified with distress screening alone.

Learning to Overcome Barriers to Electronic Patient-Reported Outcome Implementation: Lessons From the Field.

#Implementation of #ePROs in real world settings, lessons learned.

Health Care Contact Days Among Older Cancer Survivors.

PURPOSE: Health care contact days-days spent receiving health care outside the home-represent an intuitive, practical, and person-centered measure of time consumed by health care. METHODS: We linked 2019 Medicare Current Beneficiary Survey and traditional Medicare claims data for community-dwelling older adults with a history of cancer. We identified contact days (ie, spent in a hospital, emergency department, skilled nursing facility, or inpatient hospice or receiving ambulatory care including an office visit, procedure, treatment, imaging, or test) and described patterns of total and ambulatory contact days. Using weighted Poisson regression models, we identified factors associated with contact days. RESULTS: We included 1,168 older adults representing 4.51 million cancer survivors (median age, 76.4 years, 52.8% women). The median (IQR) time from cancer diagnosis was 65 (27-126) months. In 2019, these adults had mean (standard deviation) total contact days of 28.4 (27.6) and ambulatory contact days of 24.2 (23.6). These included days for tests (8.0 [8.8]), imaging (3.6 [4.1]), visits with any clinicians (12.4 [11.5]), and visits with primary care clinicians (4.4 [4.7]), and nononcology specialists (7.1 [9.4]) specifically. Sixty-four percent of days with a nonvisit ambulatory service (eg, a test) were not on the same day as a clinician visit. Factors associated with more total contact days included younger age, lower income, more chronic conditions, poor self-rated health, and tendency to "go to doctor as soon as feel bad." CONCLUSION: Older adult cancer survivors spent nearly 1 month of the year receiving health care outside the home. This care was largely ambulatory, often delivered by nononcologists, and varied by factors beyond clinical characteristics. These results highlight the need to recognize patient burdens and improve survivorship care delivery, including through care coordination.

Consuming Patients' Days: Time Spent on Ambulatory Appointments by People With Cancer.

BACKGROUND: In qualitative work, patients report that seemingly short trips to clinic (eg, a supposed 10-minute blood draw) often turn into "all-day affairs." We sought to quantify the time patients with cancer spend attending ambulatory appointments. METHODS: We conducted a retrospective study of patients scheduled for oncology-related ambulatory care (eg, labs, imaging, procedures, infusions, and clinician visits) at an academic cancer center over 1 week. The primary exposure was the ambulatory service type(s) (eg, clinician visit only, labs and infusion, etc.). We used Real-Time Location System badge data to calculate clinic times and estimated round-trip travel times and parking times. We calculated and summarized clinic and total (clinic + travel + parking) times for ambulatory service types. RESULTS: We included 435 patients. Across all service day type(s), the median (IQR) clinic time was 119 (78-202) minutes. The estimated median (IQR) round-trip driving distance and travel time was 34 (17-49) miles and 50 (36-68) minutes. The median (IQR) parking time was 14 (12-15) minutes. Overall, the median (IQR) total time was 197 (143-287) minutes. The median total times for specific service type(s) included: 99 minutes for lab-only, 144 minutes for clinician visit only, and 278 minutes for labs, clinician visit, and infusion. CONCLUSION: Patients often spent several hours pursuing ambulatory cancer care on a given day. Accounting for opportunity time costs and the coordination of activities around ambulatory care, these results highlight the substantial time burdens of cancer care, and support the notion that many days with ambulatory health care contact may represent "lost days."

Simulating the population impact of interventions to reduce racial gaps in breast cancer treatment.

BACKGROUND: Inequities in guideline-concordant treatment receipt contribute to worse survival in Black breast cancer (BCa) patients. Inequity-reduction interventions (eg, navigation, bias training, tracking dashboards) can close such treatment gaps. We simulated the population-level impact of statewide implementation of inequity-reduction interventions on racial BCa inequities in North Carolina. METHODS: Using registry-linked multi-payer claims data, we calculated Black/White inequities in endocrine (ET; n = 12,033) and chemotherapy (CTx; n = 1,819) receipt. We then built cohort- (ET and CTx), and race-stratified Markov models to simulate the potential increase in the proportion of patients receiving ET or CTx and subsequent improvements in BCa outcomes if inequity-reducing intervention were implemented statewide. We report uncertainty bounds representing 95% of simulation results. RESULTS: 75.6% and 72.1% of Black patients received ET and CTx over the 2006-2015 and 2004-2015 periods (vs 79.3 and 78.9% of White patients, respectively). Inequity-reduction interventions could increase ET and CTx receipt among Black patients to 89.9% (85.3, 94.6%) and 85.7% (80.7, 90.9%). Such interventions could also decrease 5-and 10-year BCa mortality gaps from 3.4 to 3.2 (3.0, 3.3) and from 6.7 to 6.1 (5.9, 6.4) percentage points in the ET cohorts and from 8.6 to 8.1 (7.7, 8.4) and from 8.2 to 7.8 (7.3, 8.1) percentage points in the CTx cohorts. CONCLUSIONS: Inequity-focused interventions could improve cancer outcomes for Black patients. However, they would not fully close the racial BCa mortality gap. Addressing other inequities along cancer continuum (eg, screening, pre-and post-diagnosis risk factors) is required to achieve full equity in BCa outcomes.

Measures of functional status in older patients treated with palbociclib for advanced breast cancer.

INTRODUCTION: Limited data are available on the effects of treatment for advanced breast cancer (ABC) in older patients because this population has limited enrollment in clinical trials. Data generated from the prospective, noninterventional POLARIS study of patients with hormone receptor-positive/human epidermal growth factor receptor 2-negative ABC may help bridge the gap in our understanding of the tolerability and outcomes in this vulnerable population. MATERIALS AND METHODS: We evaluated measures of geriatric impairments and activities of daily living in patients with ABC aged ≥70 years in POLARIS to evaluate the change within six months of palbociclib initiation. Geriatric impairments and activities of daily living (functional) status were assessed using the Geriatric 8 (G8) and Activities of Daily Living (ADL) screening tools. The G8, ADL, and Eastern Cooperative Oncology Group performance status (ECOG PS) scores were assessed at baseline and month six through end of treatment with palbociclib. ECOG PS scores were also stratified by G8 and ADL score severity subgroups (G8: ≤14 = impaired subgroup; >14 = not at all impaired subgroup; ADL: <18 = dependent subgroup, 18 = independent subgroup). RESULTS: At data cutoff in November 2020, of 1282 POLARIS patients of all ages, 287 (22.4%) were ≥ 70 years old and completed ≥6 months of palbociclib therapy. At baseline, 117 (45%; n = 260) of these patients had an ECOG PS score of 0, 143 (55%; n = 260) had ECOG PS score > 0, 248 (86%) had G8 scores (mean [SD] 13.6 [2.14]), and 256 (89%) had ADL scores (17.7 [1.03]) among the available 287 patients. At six months, 102 (40%; n = 255) had an ECOG PS score of 0, 153 (60%; n = 255) had ECOG PS score > 0, 198 (69%) had G8 scores (13.6 [1.99]), and 211 (74%) had ADL scores (17.6 [1.22]) among the 287 available patients. There was no mean change (standard deviation) from baseline to 6 months in mean ECOG PS scores (0.0 [0.61], P = 0.24), G8 scores (0.0 [2.17], P = 0.89), or ADL scores (0.0 [1.00], P = 0.62). DISCUSSION: In this subgroup analysis of older patients with ABC from POLARIS, functional status and impairment outcomes were preserved in older patients receiving palbociclib. G8, ADL, and ECOG PS scores were generally maintained during the first six months of palbociclib therapy. CLINICALTRIALS: govidentification number. NCT03280303.

Physicians' Hierarchy of Tumor Biomarkers for Optimizing Chemotherapy in Breast Cancer Care.

BACKGROUND: Tumor biomarkers are regularly used to guide breast cancer treatment and clinical trial enrollment. However, there remains a lack of knowledge regarding physicians' perspectives towards biomarkers and their role in treatment optimization, where treatment intensity is reduced to minimize toxicity. METHODS: Thirty-nine academic and community oncologists participated in semi-structured qualitative interviews, providing perspectives on optimization approaches to chemotherapy treatment. Interviews were audio-recorded, transcribed, and analyzed by 2 independent coders utilizing a constant comparative method in NVivo. Major themes and exemplary quotes were extracted. A framework outlining physicians' conception of biomarkers, and their comfortability with their use in treatment optimization, was developed. RESULTS: In the hierarchal model of biomarkers, level 1 is comprised of standard-of-care (SoC) biomarkers, defined by a strong level of evidence, alignment with national guidelines, and widespread utilization. Level 2 includes SoC biomarkers used in alternative contexts, in which physicians expressed confidence, yet less certainty, due to a lack of data in certain subgroups. Level 3, or experimental, biomarkers created the most diverse concerns related to quality and quantity of evidence, with several additional modulators. CONCLUSION: This study demonstrates that physicians conceptualize the use of biomarkers for treatment optimization in successive levels. This hierarchy can be used to guide trialists in the development of novel biomarkers and design of future trials.

Cancer-Related Financial Hardship Screening as Part of Practice Transformation.

BACKGROUND: Data on financial hardship, an "adverse event" in individuals with cancer, are needed to inform policy and supportive care interventions and reduce adverse economic outcomes. METHODS: Lay navigator-led financial hardship screening was piloted among University of Alabama at Birmingham oncology patients initiating treatment in October 2020. Financial hardship screening, including reported financial distress and difficulty, was added to a standard-of-care treatment planning survey. Screening feasibility and completion and proportions of reported financial distress and difficulty were calculated overall and by patient race and rurality. The risk of financial distress by patient sociodemographics was estimated. RESULTS: Patients who completed a treatment planning survey (N=2741) were 18% Black, Indigenous, or persons of color (BIPOC) and 16% rural dwelling. The majority of patients completed financial hardship screening (90%), surpassing the target feasibility completion rate of 75%. The screening revealed 34% of patients were experiencing financial distress, including 49% of BIPOC and 30% of White patients. Adjusted models revealed BIPOC patients had a 48% higher risk of financial distress compared with those who were White (risk ratio 1.48, 95% CI, 1.31-1.66). Large differences in reported financial difficulties were seen comparing patients who were BIPOC and White (utilities: 33% vs. 10%, upfront medical payments: 44% vs. 23%, transportation: 28% vs. 12%, respectively). CONCLUSIONS: The collection of patient-reported financial hardship data via routine clinical care was feasible and identified racial inequities at treatment initiation. Efforts to collect patient economic data should support the design, implementation, and evaluation of patient-centered interventions to improve equity and reduce the impact of financial hardship.

"Clinical trials are space travel": Factors of psychological response to recurrence among oncologists enrolling patients in treatment optimization trials.

BACKGROUND: Cancer recurrence after treatment is a concern for patients and oncologists alike. The movement towards treatment optimization, with trials testing less than the current standard of care (SoC), complicates this experience. Our objective was to assess oncologists' psychological response to patient recurrence on optimization-focused trials and identify factors that influence those experiences. METHODS: Clinical oncologists participated in a semi-structured interview regarding patient enrollment in treatment optimization trials. We identified factors that influence the degree of psychological response that the oncologist may feel after patient recurrence. Residual agreement analysis was used to identify whether differences in reported psychological response was associated with alternative emphases on identified factors. RESULTS: Thirty-six oncologists identified 20 factors spanning five major themes that affected their psychological response to patient recurrence. All oncologists expressed willingness to enroll patients in treatment optimization clinical trials; however, half indicated that they were more likely to experience a negative psychological response after a treatment optimization trial than after a traditional intensification trial, and a quarter reported that patient recurrence on an optimization trial would impact their recommendations for future trial enrollment. Oncologists who reported more negative psychological responses to patient recurrence after participation in an optimization trial were more likely to emphasize introspective factors, while those who reported no difference in response emphasized patient- and process-focused factors. CONCLUSIONS: Although most oncologists recognize the importance of treatment optimization trials, a significant proportion indicated a greater potential for psychological distress following patient recurrence in such trials and offered insight into how trial design and the process of patient enrollment can be improved to minimize those negative psychological responses.

Health Care Contact Days Experienced by Decedents With Advanced GI Cancer.

PURPOSE: Frequent visits to health care facilities can be time intensive and all-consuming for people with cancer. We measured health care contact days (days with healthcare contact outside the home) among decedents with advanced GI cancer and examined sources of contact days, their associations with demographic and clinical factors, and their temporal patterns over the course of illness. METHODS: We conducted a retrospective cohort study using a tumor registry and electronic medical record data for decedents with stage IV GI cancer between 2011 and 2019 in a large health care network in MN. We determined contact days from diagnosis to death using chart review. Using multivariable beta regression adjusted for sociodemographic and clinical characteristics offset by survival, we calculated adjusted estimates of contact days and determined patient-level factors associated with percentage of contact days. RESULTS: We identified 809 patients eligible for analysis (median [IQR] age at diagnosis, 65 [56-73] years). The median (IQR) overall survival was 175 (56-459) days. Patients spent a median (IQR) of 25.8% (17.4%-39.1%) of these as contact days. Of these days, 83.6% were spent on outpatient visits. In the multivariable analysis, older age, Black race, and never receiving systemic cancer-directed treatment were associated with a higher percentage of contact days. The percentage of contact days was highest in the first month after diagnosis (39.6%) and before death (32.2%), with a more moderate middle phase (U-shaped curve). CONCLUSION: Decedents with advanced GI cancer spend 1 in 4 days alive with health care contact, despite a median survival of under 6 months. This is even higher immediately postdiagnosis and near death. These findings highlight the need to understand sources of variation, benchmark appropriate care, and deliver more efficient care for this vulnerable population with limited time.

Enhancing Efficiency and Reach Using Facebook to Recruit Breast Cancer Survivors for a Telephone-Based Supportive Care Randomized Trial During the COVID-19 Pandemic.

PURPOSE: Evidence supporting social media-based recruitment of cancer survivors is limited. This paper describes how we used Facebook during the COVID-19 pandemic to augment our recruitment of breast cancer survivors for our two-site telephone-based randomized clinical trial (RCT) at Dartmouth-Hitchcock Medical Center and the University of Alabama at Birmingham. METHODS: Originally a two-site RCT of a telephone-delivered breast cancer survivorship intervention, we extended our clinic-based recruitment to Facebook. Participant characteristics, geographic reach, and baseline outcomes were compared across recruitment sources (ie, two clinics and Facebook) using descriptive statistics and effect sizes. RESULTS: Enrollment rates (20%-29%) were comparable across recruitment sources. The 21-month Facebook marketing campaign accounted for 59% (n = 179/303) of our total sample and had the greatest geographic reach, recruiting women from 24 states. The Facebook campaign reached a total of 51,787 unique individuals and cost $88.44 in US dollars (USD) per enrolled participant. Clinic samples had a greater proportion of women who were widowed (8% v 1%; P = .03) and Facebook had a higher proportion of women with a household income over $40,000 USD (83% v 71%; P = .02). There were no statistically significant differences between Facebook and the two clinics on baseline survey scores. CONCLUSION: Augmenting traditional recruitment with Facebook increased our RCT's geographic and sociodemographic reach and supported meeting recruitment goals in a timely way. In the wake of the COVID-19 pandemic, cancer survivorship researchers should consider using social media as a recruitment strategy while weighing the advantages and potential biases introduced through such strategies.

Family caregiver roles and challenges in assisting patients with cancer treatment decision-making: Analysis of data from a national survey.

BACKGROUND: We aimed to describe the roles and challenges of family caregivers involved in patients' cancer treatment decision-making. METHODS: Family caregiver-reported data were analyzed from a national survey conducted in the United States by CancerCare® (2/2021-7/2021). Four select-all-that-apply caregiver roles were explored: (1) observer (patient as primary decision-maker); (2) primary decision-maker; (3) shared decision-maker with patient and (4) decision delegated to healthcare team. Roles were compared across five treatment decisions: where to get treatment, the treatment plan, second opinions, beginning treatment and stopping treatment. Ten challenges faced by caregivers (e.g., information, cost, treatment understanding) were then examined. χ2 and regression analyses were used to assess associations between roles, decision areas, challenges and caregiver sociodemographics. RESULTS: Of 2703 caregiver respondents, 87.6% reported involvement in patient decisions about cancer treatment, including 1661 who responded to a subsection further detailing their roles and challenges with specific treatment decisions. Amongst these 1661 caregivers, 22.2% reported an observing role, 21.3% a primary decision-making role, 53.9% a shared decision-making role and 18.1% a role delegating decisions to the healthcare team. Most caregivers (60.4%) faced ≥1 challenge, the most frequent being not knowing how treatments would affect the patient's physical condition (24.8%) and quality of life (23.2%). In multivariable models, being Hispanic/Latino/a was the strongest predictor of facing at least one challenge (b = -0.581, Wald = 10.69, p < .01). CONCLUSIONS: Most caregivers were involved in patients' cancer treatment decisions. The major challenge was not understanding how treatments would impact patients' physical health and quality of life. Challenges may be more commonly faced by Hispanic/Latino/a caregivers. PATIENT OR PUBLIC CONTRIBUTION: The CancerCare® survey was developed in partnership with caregiving services and research experts to describe the role of cancer family caregivers in patient decision-making and assess their needs for support. All survey items were reviewed by a CancerCare advisory board that included five professional patient advocates and piloted by a CancerCare social worker and other staff who provide counselling to cancer caregivers.

Evaluating Nurses' Time to Response by Severity and Cancer Stage in a Remote Symptom Monitoring Program for Patients With Breast Cancer.

PURPOSE: Remote symptom monitoring (RSM) using electronic patient-reported outcomes enables patients with cancer to communicate symptoms between in-person visits. A better understanding of key RSM implementation outcomes is crucial to optimize efficiency and guide implementation efforts. This analysis evaluated the association between the severity of patient-reported symptom alerts and time to response by the health care team. METHODS: This secondary analysis included women with stage I-IV breast cancer who received care at a large academic medical center in the Southeastern United States (October 2020-September 2022). Symptom surveys with at least one severe symptom alert were categorized as severe. Response time was categorized as optimal if the alert was closed by a health care team member within 48 hours. Odds ratios (ORs), predicted probabilities, and 95% CIs were estimated using a patient-nested logistic regression model. RESULTS: Of 178 patients with breast cancer included in this analysis, 63% of patients identified as White and 85% of patients had a stage I-III or early-stage cancer. The median age at diagnosis was 55 years (IQR, 42-65). Of 1,087 surveys included, 36% reported at least one severe symptom alert and 77% had an optimal response time by the health care team. When compared with surveys that had no severe symptom alerts, surveys with at least one severe symptom alert had similar odds of having an optimal response time (OR, 0.97; 95% CI, 0.68 to 1.38). The results were similar when stratified by cancer stage. CONCLUSION: Response times to symptom alerts were similar for alerts with at least one severe symptom compared with alerts with no severe symptoms. This suggests that alert management is being incorporated into routine workflows and not prioritized based on disease or symptom alert severity.

Leveraging Goals of Care Interventions to Deliver Personalized Care Near the End of Life.

This Viewpoint discusses barriers to and opportunities for incorporating goal of care communications into end-of-life care.

Structure and integration of specialty palliative care in three NCI-designated cancer centers: a mixed methods case study.

INTRODUCTION: Early access to specialty palliative care is associated with better quality of life, less intensive end-of-life treatment and improved outcomes for patients with advanced cancer. However, significant variation exists in implementation and integration of palliative care. This study compares the organizational, sociocultural, and clinical factors that support or hinder palliative care integration across three U.S. cancer centers using an in-depth mixed methods case study design and proposes a middle range theory to further characterize specialty palliative care integration. METHODS: Mixed methods data collection included document review, semi-structured interviews, direct clinical observation, and context data related to site characteristics and patient demographics. A mixed inductive and deductive approach and triangulation was used to analyze and compare sites' palliative care delivery models, organizational structures, social norms, and clinician beliefs and practices. RESULTS: Sites included an urban center in the Midwest and two in the Southeast. Data included 62 clinician and 27 leader interviews, observations of 410 inpatient and outpatient encounters and seven non-encounter-based meetings, and multiple documents. Two sites had high levels of "favorable" organizational influences for specialty palliative care integration, including screening, policies, and other structures facilitating integration of specialty palliative care into advanced cancer care. The third site lacked formal organizational policies and structures for specialty palliative care, had a small specialty palliative care team, espoused an organizational identity linked to treatment innovation, and demonstrated strong social norms for oncologist primacy in decision making. This combination led to low levels of specialty palliative care integration and greater reliance on individual clinicians to initiate palliative care. CONCLUSION: Integration of specialty palliative care services in advanced cancer care was associated with a complex interaction of organization-level factors, social norms, and individual clinician orientation. The resulting middle range theory suggests that formal structures and policies for specialty palliative care combined with supportive social norms are associated with greater palliative care integration in advanced cancer care, and less influence of individual clinician preferences or tendencies to continue treatment. These results suggest multi-faceted efforts at different levels, including social norms, may be needed to improve specialty palliative care integration for advanced cancer patients.

Associations Between Patient-Perceived Cancer Curability and Advance Directive Completion.

Background: Despite Advance Care Planning recommendations for patients with cancer, many lack Advance Directives (ADs). AD disparities persist among Black, Indigenous, or People of Color (BIPOC) patients. Based on a hypothesized correlation, we examined the association between patient-perceived cancer incurability and AD completion. Methods: This cross-sectional study obtained self-reported AD completion and incurability perception from routine care surveys. AD completion by incurability perception was estimated using modified Poisson regression. Subgroup analyses examined patients who were BIPOC, White, and had solid organ malignancies. Results: Our sample (N = 1209) was predominantly female (70%), White (73%) with early-stage disease (60%), and solid organ malignancies (82%). AD completion was 42%, and 40% of patients reported their cancer incurable. Patient-perceived incurability was not associated with increased AD completion (likelihood ratio 0.94, 95% confidence interval 0.78-1.13) in overall or subgroup analyses. Conclusion: Patient-perceived cancer incurability was not associated with AD completion, even accounting for race/ethnicity and cancer type.