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Clinical trial participants do not reflect the racial and ethnic diversity of people with cancer. ASCO and the Association of Community Cancer Centers collaborated on a quality improvement study to enhance racial and ethnic equity, diversity, and inclusion (EDI) in cancer clinical trials. The groups conducted a pilot study to examine the feasibility, utility, and face validity of a two-part clinical trial site self-assessment to enable diverse types of research sites in the United States to (1) review internal data to assess racial and ethnic disparities in screening and enrollment and (2) review their policies, programs, procedures to identify opportunities and strategies to improve EDI. Overall, 81% of 62 participating sites were satisfied with the assessment; 82% identified opportunities for improvement; and 63% identified specific strategies and 74% thought the assessment had potential to help their site increase EDI. The assessment increased awareness about performance (82%) and helped identify specific strategies (63%) to increase EDI in trials. Although most sites (65%) were able to provide some data on the number of patients that consented, only two sites were able to provide all requested trial screening, offering, and enrollment data by race and ethnicity. Documenting and evaluating such data are critical steps toward improving EDI and are key to identifying and addressing disparities more broadly. ASCO and Association of Community Cancer Centers will partner with sites to better understand their processes and the feasibility of collecting screening, offering, and enrollment data in systematic and automated ways.

PURPOSE: Cancer trial participants do not reflect the racial and ethnic diversity in the population of people with cancer in the United States. As a result of multiple system-, patient-, and provider-level factors, including implicit bias, cancer clinical trials are not consistently offered to all potentially eligible patients. MATERIALS AND METHODS: ASCO and ACCC evaluated the utility (pre- and post-test knowledge changes) and feasibility (completion rates, curriculum satisfaction metrics, survey questions, and interviews) of a customized online training program combined with facilitated peer-to-peer discussion designed to help research teams identify their own implicit biases and develop strategies to mitigate them. Discussion focused on (1) specific elements of the training modules; (2) how to apply lessons learned; and (3) key considerations for developing a facilitation guide to support peer-to-peer discussions in cancer clinical research settings. We evaluated discussion via a qualitative assessment. RESULTS: Participant completion rate was high: 49 of 50 participating cancer programs completed training; 126 of 129 participating individuals completed the training (98% response rate); and 119 completed the training and evaluations (92% response rate). Training increased the mean percentage change in knowledge scores by 19%-45% across key concepts (eg, causes of health disparities) and increased the mean percentage change in knowledge scores by 10%-31% about strategies/actions to address implicit bias and diversity concerns in cancer clinical trials. Knowledge increases were sustained at 6 weeks. Qualitative evaluation validated the utility and feasibility of facilitated peer-to-peer discussion. CONCLUSION: The pilot implementation of the training program demonstrated excellent utility and feasibility. Our evaluation affirms that an online training designed to raise awareness about implicit bias and develop strategies to mitigate biases among cancer research teams is feasible and can be readily implemented in cancer research settings.

A concerted commitment across research stakeholders is necessary to increase equity, diversity, and inclusion (EDI) and address barriers to cancer clinical trial recruitment and participation. Racial and ethnic diversity among trial participants is key to understanding intrinsic and extrinsic factors that may affect patient response to cancer treatments. This ASCO and Association of Community Cancer Centers (ACCC) Research Statement presents specific recommendations and strategies for the research community to improve EDI in cancer clinical trials. There are six overarching recommendations: (1) clinical trials are an integral component of high-quality cancer care, and every person with cancer should have the opportunity to participate; (2) trial sponsors and investigators should design and implement trials with a focus on reducing barriers and enhancing EDI, and work with sites to conduct trials in ways that increase participation of under-represented populations; (3) trial sponsors, researchers, and sites should form long-standing partnerships with patients, patient advocacy groups, and community leaders and groups; (4) anyone designing or conducting trials should complete recurring education, training, and evaluation to demonstrate and maintain cross-cultural competencies, mitigation of bias, effective communication, and a commitment to achieving EDI; (5) research stakeholders should invest in programs and policies that increase EDI in trials and in the research workforce; and (6) research stakeholders should collect and publish aggregate data on racial and ethnic diversity of trial participants when reporting results of trials, programs, and interventions to increase EDI. The recommendations are intended to serve as a guide for the research community to improve participation rates among people from racial and ethnic minority populations historically under-represented in cancer clinical trials. ASCO and ACCC will work at all levels to advance the recommendations in this publication.

Background: Oncology advanced practitioners (APs), including nurse practitioners, clinical nurse specialists, physician assistants, and clinical pharmacists contribute significantly to quality cancer care. Advanced practitioners enhance value across the spectrum of cancer care. Research is an underdeveloped component of quality care, as well as an underdeveloped component of AP practice. Understanding research-related attitudes and roles of APs could lead to enhanced clinical trial accrual, conduct, and protocol development. Methods: A nationwide survey addressing attitudes, beliefs, and roles of APs regarding clinical research was distributed by the Association of Community Cancer Centers (ACCC) and Harborside in early 2020. Results: 408 oncology APs completed the survey. Thirty-five percent practice in an academic setting and 62% in the community. Nearly all respondents believe clinical trials are important to improve care, and over 90% report clinical trials are available at their practice. About 80% report being comfortable discussing the topic of clinical trials with patients and are involved in the care of trial participants. Sixty percent are comfortable discussing available trials, and 38% routinely explore available trials with patients. While 70% report approaching eligible patients about trials, only 20% report doing so “a great deal” or “a lot.” Ninety percent report that APs should play a role in clinical research, and 73% want to be more involved. Barriers identified to greater AP clinical trial involvement include lack of time, inadequate awareness of trial specifics, and a lack of a formal role in protocol development and leadership. Conclusions: Advanced practitioners are engaged and interested in clinical trials and believe clinical research is important to improve cancer care. Multidisciplinary team integration, trials-related education, and policy change are needed to employ APs to their full potential within cancer clinical trials.

Patients with cancer have high mortality from coronavirus disease 2019 (COVID-19), and the immune parameters that dictate clinical outcomes remain unknown. In a cohort of 100 patients with cancer who were hospitalized for COVID-19, patients with hematologic cancer had higher mortality relative to patients with solid cancer. In two additional cohorts, flow cytometric and serologic analyses demonstrated that patients with solid cancer and patients without cancer had a similar immune phenotype during acute COVID-19, whereas patients with hematologic cancer had impairment of B cells and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-specific antibody responses. Despite the impaired humoral immunity and high mortality in patients with hematologic cancer who also have COVID-19, those with a greater number of CD8 T cells had improved survival, including those treated with anti-CD20 therapy. Furthermore, 77% of patients with hematologic cancer had detectable SARS-CoV-2-specific T cell responses. Thus, CD8 T cells might influence recovery from COVID-19 when humoral immunity is deficient. These observations suggest that CD8 T cell responses to vaccination might provide protection in patients with hematologic cancer even in the setting of limited humoral responses.

Patient-centered care that is accessible, affordable, evidence based, and well coordinated is integral to high-quality cancer care delivery.1 Medicaid and other socioeconomically disadvantaged pati...

Advances in cancer care have led to improved survival, which, coupled with demographic trends, have contributed to rapid growth in the number of patients needing cancer care services. However, with increasing caseload, care complexity, and administrative burden, the current workforce is ill equipped to meet these burgeoning new demands. These trends have contributed to clinician burnout, compounding a widening workforce shortage. Moreover, family caregivers, who have unique knowledge of patient preferences, symptoms, and goals of care, are infrequently appreciated and supported as integral members of the oncology “careforce.” A crisis is looming, which will hinder access to timely, high-quality cancer care if left unchecked. Stemming from the proceedings of a 2019 workshop convened by the National Cancer Policy Forum of the National Academies of Sciences, Engineering, and Medicine, this commentary characterizes the factors contributing to an increasingly strained oncology careforce and presents multilevel strategies to improve its efficiency, effectiveness, and resilience. Together, these will enable today’s oncology careforce to provide high-quality care to more patients while improving the patient, caregiver, and clinician experience.

The care of patients with cancer occurs in a fast-moving, high-pressure, and high-stakes ecosystem. Early in 2020, that complex ecosystem was further complicated by the advent of the COVID-19 pandemic. We address actions taken by care providers and systems during the initial phases of the pandemic, and how those actions preserved lifesaving and life-sustaining cancer care despite severely constrained resources. We outline cancer care principles and guidelines that were developed, shared, and adopted by cancer care organizations across the country. Care delivery concerns that arose during the pandemic, including equipment and personnel shortages, moral distress for care providers, and exacerbation of health care inequities are addressed. Process and operations changes taken by payers to serve their clients are described. Lessons learned are highlighted, along with a call to action that we learn from the experience, broaden our cancer care delivery mission, and commit to structural changes that will permanently improve the capacity of cancer care teams.

Digital health advances have transformed many clinical areas including psychiatric and cardiovascular care. However, digital health innovation is relatively nascent in cancer care, which represents the fastest growing area of health-care spending. Opportunities for digital health innovation in oncology include patient-facing technologies that improve patient experience, safety, and patient-clinician interactions; clinician-facing technologies that improve their ability to diagnose pathology and predict adverse events; and quality of care and research infrastructure to improve clinical workflows, documentation, decision support, and clinical trial monitoring. The COVID-19 pandemic and associated shifts of care to the home and community dramatically accelerated the integration of digital health technologies into virtually every aspect of oncology care. However, the pandemic has also exposed potential flaws in the digital health ecosystem, namely in clinical integration strategies; data access, quality, and security; and regulatory oversight and reimbursement for digital health technologies. Stemming from the proceedings of a 2020 workshop convened by the National Cancer Policy Forum of the National Academies of Sciences, Engineering, and Medicine, this article summarizes the current state of digital health technologies in medical practice and strategies to improve clinical utility and integration. These recommendations, with calls to action for clinicians, health systems, technology innovators, and policy makers, will facilitate efficient yet safe integration of digital health technologies into cancer care.

1AbstractPurposePredicting 30-day readmission risk is paramount to improving the quality of patient care. Previous studies have examined clinical risk factors associated with hospital readmissions. In this study, we compare sets of patient, provider, and community-level variables that are available at two different points of a patient’s inpatient encounter (first 48 hours and the full encounter) to train readmission prediction models in order to identify and target appropriate actionable interventions that can potentially reduce avoidable readmissions.MethodsUsing EHR data from a retrospective cohort of 2460 oncology patients, two sets of binary classification models predicting 30-day readmission were developed; one trained on variables that are available within the first 48 hours of admission and another trained on data from the entire hospital encounter. A comprehensive machine learning analysis pipeline was leveraged including preprocessing and feature transformation, feature importance and selection, machine learning modeling, and post-analysis.ResultsLeveraging all features, the LGB (Light Gradient Boosting Machine) model produced higher, but comparable performance: (AUROC: 0.711 and APS: 0.225) compared to Epic (AUROC: 0.697 and APS: 0.221). Given features in the first 48-hours, the RF (Random Forest) model produces higher AUROC (0.684), but lower AUPRC (0.18) and APS (0.184) than the Epic model (AUROC: 0.676). In terms of the characteristics of patients flagged by these models, both the full (LGB) and 48-hour (RF) feature models were highly sensitive in flagging more patients than the Epic models. Both models flagged patients with a similar distribution of race and sex; however, our LGB and random forest models more inclusive flagging more patients among younger age groups. The Epic models were more sensitive to identifying patients with an average lower zip income. Our 48-hour models were powered by novel features at various levels: patient (weight change over 365 days, depression symptoms, laboratory values, cancer type), provider (winter discharge, hospital admission type), community (zip income, marital status of partner).ConclusionWe demonstrated that we could develop and validate models comparable to existing Epic 30-day readmission models, but provide several actionable insights that could create service interventions deployed by the case management or discharge planning teams that may decrease readmission rates over time.

PURPOSE: CMS' Oncology Care Model (OCM) is an episode-based alternative payment model designed to incent high-value care through the use of monthly payments for enhanced services and performance-based payments on the basis of decreases in spending compared with risk-adjusted historical benchmarks. Transitioning from a fee-for-service model to a value-based, alternative payment model in oncology can be difficult; some practices will perform better than others. We present detailed experiences of four successful OCM practices, each operating under diverse business models and in different geographic areas. METHODS: Practices that achieved success in OCM, on the basis of financial metrics, describe pathways to success. The practices represent distinct business models: a medium-sized community oncology practice, a large statewide community oncology practice, a hospital-affiliated practice, and a large academic medical center. RESULTS: Practices describe effective changes in practice culture such as new administrative flexibilities, physician champions, improved communication, changes in physician compensation, and increased physician-level transparency. New or improved clinical services include acute care clinics, care coordination, phone triage, end-of-life care programs, and adoption of treatment pathways that identify high-value drug use, including better use of supportive care drugs. CONCLUSION: There is no one thing that will ensure success in OCM. Success requires whole practice transformation, encompassing both administrative and clinical changes. Communication between administrative and clinical teams is vital, along with improved data sharing and transparency. Clinical support services must expand to manage problems and symptoms in a timely way to prevent costly emergency department visits and hospitalizations, while constant attention must be paid to making high-value therapeutic choices in both oncolytic and supportive drug categories.

Cancer patients have increased morbidity and mortality from Coronavirus Disease 2019 (COVID-19), but the underlying immune mechanisms are unknown. In a cohort of 100 cancer patients hospitalized for COVID-19 at the University of Pennsylvania Health System, we found that patients with hematologic cancers had a significantly higher mortality relative to patients with solid cancers after accounting for confounders including ECOG performance status and active cancer status. We performed flow cytometric and serologic analyses of 106 cancer patients and 113 non-cancer controls from two additional cohorts at Penn and Memorial Sloan Kettering Cancer Center. Patients with solid cancers exhibited an immune phenotype similar to non-cancer patients during acute COVID-19 whereas patients with hematologic cancers had significant impairment of B cells and SARS-CoV-2-specific antibody responses. High dimensional analysis of flow cytometric data revealed 5 distinct immune phenotypes. An immune phenotype characterized by CD8 T cell depletion was associated with a high viral load and the highest mortality of 71%, among all cancer patients. In contrast, despite impaired B cell responses, patients with hematologic cancers and preserved CD8 T cells had a lower viral load and mortality. These data highlight the importance of CD8 T cells in acute COVID-19, particularly in the setting of impaired humoral immunity. Further, depletion of B cells with anti-CD20 therapy resulted in almost complete abrogation of SARS-CoV-2-specific IgG and IgM antibodies, but was not associated with increased mortality compared to other hematologic cancers, when adequate CD8 T cells were present. Finally, higher CD8 T cell counts were associated with improved overall survival in patients with hematologic cancers. Thus, CD8 T cells likely compensate for deficient humoral immunity and influence clinical recovery of COVID-19. These observations have important implications for cancer and COVID-19-directed treatments, immunosuppressive therapies, and for understanding the role of B and T cells in acute COVID-19.

e18599 Background: Low participation of Black, Hispanic, Latinx and other underrepresented racial/ethnic groups in clinical research remains a problem across the U.S. Recent studies have highlighted that stereotypes, assumptions, and bias play a role in lack of diversity in cancer trial participation. To help address this, the Association of Community Cancer Centers (ACCC) and American Society of Clinical Oncology (ASCO) piloted an implicit bias training program for clinical research teams. Methods: Adapted from the Duke University Just Ask™ program, the pilot program is comprised of eLearning modules which can be completed in about 60 minutes. Features include education on diversity, equity, and bias in clinical trial participation, case vignettes, and strategies to mitigate disparities. A call was issued to members of both organizations. After completing the training, all individual participants were asked to complete a retrospective pre/post survey to assess change in knowledge and attitude. Focus groups explored participants’ experience with the training. Another survey was administered 6 weeks later to assess sustainability of changes. Results: Research teams from 50 programs were selected for the pilot. 129 individuals consented, and 126 completed the training and evaluations (98% response rate). 48% of participants reported that they had completed training on implicit bias and/or related topics prior to the pilot. Increased levels of knowledge were reported across all key training concepts, with an average % increase from 19% to 45%. Similar increases were observed for strategies for addressing implicit bias, with an average % increase from 10% to 31%. At 6 weeks post-training, there was a slight decrease in knowledge across most items, from -1% to -8%. Most (92%) participants reported satisfaction with the course, and most (92%) indicated they would recommend it to a colleague and would recommend implementing it at their program. Suggestions to improve the course included streamlining content and providing additional tools and resources. Conclusions: Pilot findings support the feasibility and utility of the training, which can help cancer programs to address disparities in clinical research. Next steps include modifying the course based on participant feedback, disseminating the training and supplementary resources, and exploring options for assessing the impact on upstream outcomes such as diversity in trial participation.[Table: see text]

6530 Background: Only a small fraction of patients with cancer participate in treatment trials. Patients identifying as members of racial and ethnic minority groups are consistently underrepresented in these trials. A recent systematic review reported that patients, regardless of race and ethnicity, are willing to enroll in trials if asked to participate by their treating clinician. Prospective and longitudinal data and metrics at the site- and clinician-level are necessary to understand whether patients are equitably considered for clinical trials. Methods: ASCO and Association of Community Cancer Centers (ACCC) developed a self-assessment for trial sites to record and gauge the number of patients across races and ethnicities screened, offered, and enrolled into clinical trials. Research sites, from across the US, were recruited through an open call to apply to participate in the ASCO-ACCC Pilot Project. There were 65 sites assigned to this pilot study, which tested the feasibility and utility of the site assessment. Sites were asked to enter 2019 and 2020 aggregate data for each step along the clinical trial enrollment continuum by select races and ethnicities (Black, Hispanic/Latinx, White) and overall. Results: 62 of 65 sites completed the study and represented a range of settings and practice types (61% academic, 26% hospital/health system, 13% independent). Only 2 sites (3%) were able to provide the data requested at each enrollment step in the assessment (table). Sites that collected the data did not do so routinely (table) and most had to compile data through multiple sources and/or manual extraction (40-100% across enrollment steps). Sites with missing data reported they did not collect data at all (36-64% across enrollment steps), did not collect data in a systematic way (0-29% across enrollment steps), or stated it would be too burdensome to manually review charts to extract data (12-29% across enrollment steps). Conclusions: Data collection and routine evaluation of participation metrics, by race and ethnicity, are necessary to assess and monitor equity and diversity in clinical trials. Most sites in this study did not collect, or routinely collect, data for screening, offering, and consenting patients to clinical trials. Without these data, sites are unable to evaluate and monitor whether their patients have equitable access to clinical trials or establish strategies to address any inequities. ASCO and ACCC will continue to partner with sites to better understand their processes and the feasibility of collecting such data in a systematic and automated way, such as through electronic health record systems. [Table: see text]

Gastrointestinal (GI) malignancies are among the most commonly diagnosed cancers worldwide. Despite the introduction of targeted and immunotherapy agents in the treatment landscape, cytotoxic agents, such as fluoropyrimidines and irinotecan, remain as the cornerstone of chemotherapy for many of these tumors. Pharmacogenetics (PGx) is a rapidly evolving field that accounts for interpatient variability in drug metabolism to predict therapeutic response and toxicity. Given the significant incidence of severe treatment-related adverse events associated with cytotoxic agents, utilizing PGx can allow clinicians to better anticipate drug tolerability while minimizing treatment interruptions or delays. In this review, the PGx profiles of drug-gene pairs with potential impact in GI malignancy therapy - DPYD-5-fluorouracil/capecitabine and UGT1A1-irinotecan - and the available clinical evidence of their roles in reducing severe adverse events are discussed. Considerations for clinical implementation, such as optimal laboratory workflows, electronic health record integration, and stakeholder engagement, as well as provider education, are addressed. Last, exploratory PGx markers in GI malignancy treatment are described. As the PGx knowledge base rapidly evolves, pharmacists will be vital in leveraging their pharmacology knowledge and clinical skills to implement PGx testing in the clinic.

236 Background: Older adults are more likely to be diagnosed with cancer than their younger counterparts. Because the underlying health status of older adults with cancer is generally heterogeneous, geriatric assessment (GA) is helpful for uncovering age-related vulnerabilities and guiding subsequent care planning. GA provides multidimensional, multidisciplinary evaluations of pertinent health domains. When used to evaluate an older adult with cancer prior to initiating therapy, GA and screening tools can help oncologists differentiate between fit and frail patients and tailor their treatment accordingly. Methods: The Association of Community Cancer Centers (ACCC) conducted a 4-round Delphi method to achieve expert consensus (≥75%) related to 9 domains of geriatric oncology care from a multidisciplinary perspective. A survey was conducted with 70 international clinicians working in geriatric oncology to assess perspectives on guideline-recommended GA tools in clinical practice. Facilitator led focus groups were conducted to review the results in a large group format and come to consensus. Aggregated results were shared back with the group to ensure effective capture of group discussion regarding validated clinical practice tools to include as resources in the gap assessment instrument. Results: A 32 question geriatric oncology gap assessment was developed in an online survey platform. This tool was beta tested by 30 individuals at cancer programs of various types and regions across the US. A final version was published and made accessible for multidisciplinary teams to self-assess care delivery for older adults with cancer in 9 domains: Functional Status; Cognition; Comorbidities; Decision Making: Screening, Life Expectancy, Chemo Toxicity; Pharmacy/Medication Management; Psychological Health; Nutrition; Patient Goals and Needs; and Communication and Workforce Training. Within each domain, respondents select the level (see Table) that most closely represents the practice(s) at their institution. A personalized report is generated. Sample Question. Conclusions: The ACCC geriatric oncology gap assessment offers cancer programs a validated way to evaluate care delivery for older adults with cancer. To optimize workflow, cancer programs should consider utilizing gap assessment results to develop and advance scalable quality improvement programs at their institution, taking into consideration resource level and infrastructure.[Table: see text]

Introduction: Studies have shown aggressive cancer care at the end of life is associated with decreased quality of life, decreased median survival, and increased cost of care. This study describes the patients most likely to receive systemic anticancer therapy at the end of life in a community cancer institute. Materials and Methods: We performed a retrospective cohort study of 201 patients who received systemic anticancer therapy in our institution and died between July 2016 and April 2017. Data collected included primary malignancy, hospice enrollment, healthcare utilization, Oncology Care Model (OCM) enrollment, and clinical assessments at last office visit prior to a treatment decision before death. We defined our outcome variable as the receipt of anticancer treatment in the last 14 days of a patient’s life. We evaluated 20 clinical exposure variables with respect to the outcome classes. Risk ratios along with their associated confidence intervals and P values were calculated. Significance was determined using the Benjamini-Hochberg procedure to account for multiple testing. Results: Of the 201 patients who died of cancer, 36 (17%) received anticancer therapy within the last 14 days of life. Several risk factors were significantly positively associated with receiving anticancer therapy at the end of life including hospitalization within 30 days of end of life, number of hospitalizations per patient (≥2), death in hospital, enrollment in OCM, and a diagnosis of hematologic malignancy. Conclusion: Our findings demonstrate those enrolled in the OCM and those with hematologic malignancies have a higher risk of receiving anticancer therapy in the last 14 days of life. These observations highlight the need for better identifying the needs of high-risk patients and providing good quality care throughout the disease trajectory to better align end-of-life care with patients’ wishes.

The Oncology Care Model (OCM) is a 5-year model developed and tested by the Centers for Medicare & Medicaid Services that uses an episode-based payment model triggered by the receipt of chemotherapy to test if changing payment mechanisms, in conjunction with a requirement for enhanced patient services, can generate clinical transformation that will orient practices toward more patient-centered, high-value care to reduce expenditures and preserve or enhance quality of care for beneficiaries. The model is geographically diverse with practices in 34 states and encompasses practices ranging in size from 1 to more than 400 practitioners, with a multitude of business structures. Given these varied clinical and business environments, we believe that OCM-participating practices will have different opportunities and challenges as they work toward practice transformation, but they will likely share similarities with other practices in similar clinical and business settings. This commentary shares the experiences of four diverse groups participating in OCM—three practices and one network of practices—halfway through the model’s projected 5-year life cycle in the expectation that these experiences will be of value to other practices embarking toward patient-centered, high-value practice transformation.

I’d like to start my last column by thanking ACCC, its board of trustees, and all of you for allowing me to serve as president of this collaborative, forward‐thinking association. Assuming the ACCC...

54 Background: Pharmacogenetic (PGx) testing for germline variants in the DPYD and UGT1A1 genes can be used to guide fluoropyrimidine and irinotecan dosing, respectively. Despite the known association between PGx variants and chemotherapy toxicity, preemptive testing prior to chemotherapy initiation is rarely performed in routine practice. Methods: We conducted a multi-site mixed-methods study to understand clinician attitudes toward PGx testing and to identify facilitators and barriers to using preemptive testing to guide chemotherapy dosing in patients with gastrointestinal malignancies. Each participant completed a demographic survey and semi-structured interview informed by the Consolidated Framework for Implementation Research. Interviews were analyzed using a modified grounded theory approach. Results: A total of 16 medical oncologists and 9 oncology pharmacists from one academic medical center and two community hospitals participated. Fifteen (60%) participants reported feeling comfortable or very comfortable with interpreting PGx test results. While clinicians expressed generally favorable attitudes toward PGx testing, many were hesitant to use it to preemptively guide chemotherapy dosing due to a perceived lack of evidence for this practice. They cited a lack of consensus chemotherapy dosing recommendations in response to PGx test results, as well as concerns about decreased drug efficacy, especially in patients treated with curative intent. Additional barriers included 1) a low prevalence of actionable PGx variants; 2) lengthy PGx test turnaround time; 3) concerns about testing costs and lack of insurance coverage; and 4) burdensome integration of PGx testing into clinical workflows. The electronic health record emerged as a potential tool for the unobtrusive integration of PGx testing into clinical practice–suggested applications included default PGx test orders for eligible patients, discrete reporting of PGx variant results, and clinical decision support to guide subsequent chemotherapy dosing. Conclusions: Successful adoption of preemptive PGx-guided chemotherapy dosing in patients with gastrointestinal malignancies will require a multi-level effort to demonstrate clinical effectiveness while addressing the contextual factors identified in this study. The electronic health record should be explored as a tool to integrate PGx testing into routine practice.

ACCC members enter 2021 with much to consider—both professionally and personally. Fortunately, we are a resilient and committed group. With the enormous pressures of COVID-19, the ever-increasing c...

Greetings from ACCC. With so many challenges occupying our minds, our time, and our activities, I’d like to pause and reflect on the importance of connectivity. During times of extreme stress (what...

105 Background: Medicaid patients with lung cancer have poorer outcomes than non-Medicaid patients, partly because of suboptimal care quality. The Association of Community Cancer Centers (ACCC) launched a project to develop, test, and refine an OCCM. Methods: The OCCM comprised 13 areas, spanning care access to supportive care/survivorship. Using the OCCM, 7 cancer programs in 6 US states conducted self-assessments of care delivery systems and implemented quality improvement projects. Sites worked with ACCC to conduct data benchmarked projects. Data collection and analysis were centralized. Statistical analyses used Kruskal−Wallis and chi-squared tests. Results: There were 926 patients (257 Medicaid/dual eligible; 669 non-Medicaid) across 7 sites. Medicaid/dual eligible patients were 52% male, 69% Caucasian, 48% active smokers, and 45% clinical stage III/IV. Prospective multidisciplinary case planning (PMCP), patient care access, and tobacco cessation were commonly selected for projects. PMCP evaluation used fortnightly tumor board (FTB), virtual tumor board (VTB), and multidisciplinary team huddle (MTH). Presentation of eligible patients was higher for VTB and MTH (FTB: 23%, VTB: 100%, MTH: 100%, p < 0.0001). While FTB and MTH discussed all cases prospectively, VTB achieved 80%. Median days (d) from diagnosis to presentation were 18 (FTB), 14 (VTB), and 9 (MTH, p = 0.14). Patient care access was evaluated with timeliness metrics at 2 sites. Site 1: Medicaid patients had a median of 13 d from lesion discovery to diagnosis and 21 d from diagnosis to treatment (not different from non-Medicaid; p = 0.96 and 0.38). 94% met the goal of treatment initiation within 45 d. Site 2: Medicaid patients had a median of 16 d from discovery to diagnosis and 27 d from diagnosis to treatment (not different from non-Medicaid; p = 0.68 and 0.83). Similar benchmarks were collected and compared for other assessment areas. Sites identified enhanced collaboration and improved programming (e.g., patient navigation) as successes. Challenges at project start included inadequate staffing and lack of centralized data collection and benchmarking. Importance of lung cancer–dedicated navigation, PMCP, and Medicaid patient needs were key transferable lessons. Conclusions: The OCCM is useful for cancer programs’ self-assessment of care delivery to Medicaid patients across 13 high-impact areas. Dissemination can advance multidisciplinary coordinated care delivery, but sites may need additional resources to evaluate outcomes.

95 Background: Oncology Advanced Practitioners (APs), including Nurse Practitioners, Physician Assistants, Clinical Nurse Specialists, and Pharmacists are highly trained health care providers that contribute significantly to quality cancer care. Given low clinical trial enrollment among adult oncology patients, understanding current research responsibilities of APs could lead to identification of opportunities to leverage this workforce to enhance accrual and conduct of clinical trials. Methods: A 65-item validated survey addressing attitudes, beliefs and responsibilities of oncology APs participating in clinical research was distributed from January 22 through March 6, 2020. Outreach via the Association of Community Cancer Centers (ACCC) and Harborside was utilized to reach a sample set of 14,601 oncology APs’ emails. The survey was administered and data were analyzed using Survey Monkey. Results: 408 U.S. oncology APs completed the survey. Respondents were primarily white (83%), female (92%) and nurse practitioners (71%). Thirty-five percent practiced in an academic setting and 62% practiced in a community setting. Nearly all respondents believed that clinical trials are important to improve oncology care standards and more than 90% reported that clinical trials were available at their practice. Nearly 80% reported that they are comfortable discussing treatment options with patients, discussing clinical trials in general, and know where to find clinical trials. Furthermore, 80% participate in the care of patients enrolled on clinical trials. Only 60%, however, are comfortable discussing trials available at their practice and only 38% routinely explore whether a clinical trial is available for their patients. While 70% of APs approach eligible patients about clinical trials at their practice, only 20% reported doing so “a great deal” or “a lot”. Ninety percent of APs reported that they should play a role in clinical research and 75% would like to be more involved in the clinical trial process. Barriers to greater involvement in clinical trials include lack of time, inadequate awareness of clinical trial specifics, and under-representation on research committees. Conclusions: The majority of oncology APs are engaged and interested in clinical trials and believe that research is important to improve cancer care. However, they are not being utilized to their full scope. Multidisciplinary team integration, trials-related education, and policy change is needed to allow this group of skilled professionals to realize their full potential within cancer clinical trials.

104 Background: In 2016, the Association of Community Cancer Centers (ACCC) launched a 3-year initiative to design, test, and refine an OCCM for Medicaid patients with lung cancer. The aim was to help cancer programs identify and reduce the barriers experienced by Medicaid patients by strengthening lung cancer care delivery systems. Methods: Phase I included Model development. Phases II and III included selection of 7 community-based cancer programs as testing sites to implement quality improvement projects, utilizing qualitative and quantitative assessments. Beta testing demonstrated the Model’s ability to offer practical guidance on improving care coordination to achievable target levels in high-impact areas such as patient access to care, prospective multidisciplinary case planning, and tobacco cessation. Opportunities were identified to improve care coordination beyond lung cancer to other tumor sites. Refinements for clarity of intent, ease of use, specificity, and uniformity across assessment areas were implemented, based on feedback from testing sites. Members of the Technical Expert Panel and the Advisory Committee, ACCC staff, and consultants revised the Model using consensus decision-making. Results: The final OCCM is composed of 12 inter-related assessment areas: patient entry into lung cancer program; multidisciplinary treatment planning; clinical trials; supportive care; survivorship care; financial, transportation, and housing needs; tobacco education; navigation; treatment team integration; physician engagement; electronic health records and patient access to information; and quality measurement and improvement. Each assessment area has 5 levels and corresponding metrics—level 1 represents the most basic provision of care, and level 5 represents optimal care coordination, which may be attainable for some cancer programs and aspirational for others. Progress implies cumulative and sustained fulfillment of lower level criteria. The OCCM can be deployed by cancer programs, regardless of size, setting, resource level, or cancer type. Dissemination to promote wider use is planned through an online benchmarking tool, blogs, a brochure, podcasts, and other resources. Conclusions: The OCCM can be utilized by cancer programs for objective self assessments of care delivery capabilities across 12 high-impact areas. Dissemination can advance multidisciplinary coordinated care delivery and improve clinical outcomes for patients nationwide, regardless of cancer type.

66 Background: Studies have shown that aggressive cancer care at end of life is associated with decreased quality of life, decreased median survival, and increased cost of care. This study describes the patients most likely to receive aggressive anti-cancer therapy at the end of life in a community cancer institute. Methods: We performed a retrospective review of 213 patients who received anti-cancer therapy in our institution and died between July 2016-April 2017. Data collected included primary malignancy, death date, date of last anti-cancer treatment, hospice enrollment, healthcare utilization, Oncology Care Model (OCM) enrollment, and clinical assessments at last office visit prior to a treatment decision before death. Data were analyzed using univariate logistic regression to determine feature importance. Results: Of the 201 patients who died of cancer, 36 (17%) received anti-cancer therapy within the last 14 days of life. Several factors were significantly positively correlated with receiving anti-cancer therapy at end of life, including enrollment in OCM (p < 0.001), frequency of hospital utilization (p < 0.001), death in hospital (p

Tuberculosis exerts a dazzling variety of hematologic effects (Table 23.1). These abnormalities involve both cell lines and plasma components. Also, antituberculous therapy has its own spectrum of hematologic toxicity. This chapter reviews and summarizes the known hematologic effect of tuberculosis and its therapy.