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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.

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.

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]