Large Community Oncology Practice Research Articles

Differences in the utilization of palliative care support services among patients with metastatic solid tumor cancer in a community oncology setting: A retrospective review.

82 Background: Palliative care has been underutilized in the setting of advanced cancer despite its established benefit in improving the quality of life in cancer patients. Few studies have evaluated socioeconomic disparities in receiving palliative care in the outpatient oncology setting. We aimed to evaluate for disparities in utilization of palliative care among patients with metastatic solid tumor malignancies at Tennessee Oncology, a large outpatient community oncology practice with an established palliative care program. Methods: We completed a retrospective review of medical records of 1513 patients that were seen in Tennessee Oncology clinics from 12/2020 to 12/2021. We compared the baseline characteristics of patients with metastatic solid tumor malignancies who did and did not receive palliative care. Chi-square and two-sample t-tests were used for data analysis with the 5% significance level using R statistical software. Results: Male patients utilized palliative care less often than female patients (17% versus 24% for females, p =.0002; 95% CI,.05-1.0). Of payer types, Medicare had the least palliative care utilization (14%) compared to commercial (25%) and other payers (23%). Utilization also varied by cancer type, with melanoma (9%), lung cancer (15%) and renal cancer (21%) being least likely to receive palliative care (p <.00005; 95% CI,.19-1.0). We did examine racial differences in palliative care utilization, but those did not reach statistical significance. Conclusions: There are multiple disparities in the utilization of on-site palliative care support services among patients with metastatic solid tumor cancer in this outpatient community oncology setting. Further research is needed to gain insight into why this is, including an in-depth analysis of both patient and provider utilization/referral practices.[Table: see text]

Development of a Standardized Bone Marrow Procedure Training and Competency Toolkit for Advanced Practice Providers in a Large Community Oncology Practice.

Bone marrow procedures are a common diagnostic tool utilized in hematology/oncology and can be completed in the office by trained clinicians. Currently, there are limited guidelines for appropriate training and competency for bone marrow procedures performed by advanced practice providers (APPs) in a community oncology practice setting. The need to create a standardized training and competency protocol for APPs in this setting was recognized. A comprehensive, standardized educational and procedural toolkit was created. The creation of a comprehensive training toolkit for APPs in the community oncology practice setting helps to ensure a high standard of procedural proficiency and consistency among individual providers and practices. The creation of such an extensive toolkit is time consuming. By adopting and standardizing toolkits such as this one, community hematology/oncology practices can ensure the delivery of high-quality patient care by highly trained and proficient APPs.

Analyzing patient engagement with digital health tools to facilitate equity across a large statewide community oncology practice.

1575 Background: Digital health solutions (DHS) allow for enhanced remote communication between patients and clinical staff and the COVID-19 pandemic has brought these tools to the forefront of care delivery. Once adopted, barriers to adequate utilization still exist. Given the important need to decrease digital divides, and the diversity of patients and care settings across our clinic’s 220 sites of service, we sought to understand how utilization of oncology DHS may be limited among certain populations. Methods: We investigated utilization among cancer patients who enrolled and engaged with a portfolio of DHS between March 1, 2019 and January 15, 2022. This portfolio includes three tools: (1) an electronic patient-reported outcomes (ePRO) remote monitoring program for tracking symptoms and oral adherence, (2) a patient portal (PP) for securely accessing patient health records, and (3) digital education (DE) for patients regarding disease and treatments. ePRO completion rate, average number of PP logins, and DE read rate were used as measures of utilization for each tool, respectively, and compared among patients with different age (< 65 and ≥65 years), language preference [English (EL) or Spanish (SL)], and distance from clinic (non-rural: < 20 miles OR rural: ≥20 miles). Mann-Whitney U and Chi-Square tests were used to compare continuous and categorical variables, respectively. Results: This study included a total of 77,347 unique patients representing 651,004 digital encounters. 9,938 patients engaged in ePRO, 49,771 patients in PP, and 12,044 patients in DE. Engagement across all DHS was high in patients of age group < 65 (ePRO: 72.7%, PP: 79.67% and PE 54.7%) as compared to ≥65 years, but the ePRO completion rate is high in ≥65 age group (59.0% vs 55.6%), whereas no significant difference was observed in the PP login activity and DE read rate. EL patients were significantly (p-value < 0.01) more engaged (ePRO 68% vs. 54%, PP: 80% vs. 62%, DE: 57% vs. 37%) and had higher digital utilization (ePRO completion rate: 57.31% vs 53.23%, average PP logins: 7.48 vs 7.14 and DE read rate: 96.2% vs 90.8%) than SL patients across the DHS. Patients living in rural areas comprised roughly 25% of the population and participated across tools similarly as patients living in non-rural areas (ePRO 67% vs. 69%, PP: 79% vs. 79%, DE: 56.9% vs. 56.8%). Utilization of the portfolio was variable based on rural vs non-rural status (ePRO completion rate: 56.3% vs. 57.4%, average PP logins: 7.9 vs. 7.3, DE read rate: 96.02.7% vs 96.3%). Conclusions: Despite variable engagement based on age, language, and rural status across the portfolio, patients within these populations continue to utilize the DHS. How we understand and explore enhancements to DHS remain under investigation for tool optimization for patient-specific barriers to care.

Evaluating mass implementation of digital health solutions to improve quality and reduce disparities in a large multisite community oncology practice.

1507 Background: There is a priority to accelerate the delivery of digital health solutions (DHS) to provide patients with enhanced means for accessing care, but lack of understanding of their utility in certain populations. There are concerns that equitable adoption translate into disparities. We sought to implement a portfolio of DHS across a large practice and characterize engagement across populations to enhance clinical informatics solutions that support care delivery. Methods: This is a retrospective evaluation of cancer patients who engaged with a portfolio of DHS between March 1, 2019 and January 15, 2022. We included four tools with opt-in and opt-out functionality: (1) a care management (CM) platform utilized by clinical staff to manage patient activities, (2) an electronic patient-reported outcomes (ePRO) remote monitoring program for tracking symptoms and oral adherence, (3) a patient portal (PP) for securely accessing patient health records, and (4) digital education (DE) for patients regarding disease and treatments. The engaged population was defined as the number of enrolled patients with at least one (1) record of triage activity, (2) completed ePRO assessment, (3) PP login, and (4) DE read activity, for each tool, respectively. The start of the index period was adjusted based on the first go-live date of each tool. We evaluated factors (age, gender, race/ethnicity, preferred-language, marital status, and distance from clinic) associated with patient engagement using Chi-Square test and multivariate logistic regression. Results: This analysis included a total of 267,375 unique patients. Of the enrolled population per tool, 172,840 (73.6%), 9,938 (67.7 %), 49,771 (79.2%), and 12,044 (56.9%) patients were engaged in CM, ePRO, PP and DE, respectively. The majority (>50%) of engaged patients were female, White and non-Hispanic/Latino, English-language, and aged 61-80 yrs. After adjusting for covariates, we observed that White and non-Hispanic/Latino [(CM: OR 1.15, ePRO OR 1.46, PP: OR 1.48, and DE: OR 1.36) and English-language (CM: OR 1.2, ePRO OR 1.67, PP: OR 1.8 and DE: OR 1.89) patients were significantly (p-value <0.001) more engaged compared to their counterparts. Male patients were less likely to be engaged in CM (OR: 0.79) and ePRO (OR: 0.65) but more engaged in PP (OR: 1.1) compared to females. No significant difference was observed in engagement between non-rural (<20 mile) vs. rural (≥ 20 miles) and in all age groups 21-40, 41-60, 61-80 and >80 years as compared to reference age of 0-20 years for any digital tools except CM. Conclusions: DHS can be used to support the cancer patient journey and we demonstrated high utilization in an array of sociodemographic variables in our population. However, tools designed and implemented with different populations in mind to reduce staff burden and lessen the digital divide should be further explored.

Real-world biomarker testing trends in metastatic non-small cell lung cancer (NSCLC).

e18728 Background: NSCLC is now recognized as not one disease, but many—differentiated by an increasing number of molecular targets. About 50% of patients with advanced nonsquamous NSCLC have a targetable driver mutation. We retrospectively assessed biomarker testing trends in a large community oncology practice to identify evolving real-world testing rates and patterns in the areas of methodology, specimen types, and vendors. Methods: Natural-language processing queries were used to extract data from biomarker testing reports of patients diagnosed with stage IV NSCLC in 2015-2019. Tests were included if done within 1 year of diagnosis and were classified as NGS panels (20+ genes) or targeted single-gene tests. Results: Records of 587 patients were included. Over the 5-year study window, testing rates increased for all 6 mutations analyzed (Table). In 2015, only ALK, ROS1, and EGFR were profiled in our data (n = 20 patients), all using targeted single-gene tests. The use of multigene panels increased steadily over time, constituting the majority by 2019. MET, RET, and NTRK were tested almost exclusively using NGS panels (data beginning in 2016). Tissue-only specimens were used for 93.8% of patients diagnosed in 2015, while tissue plus blood were used in 6.3%. Blood-only samples began appearing in our data in 2016, making up 7% of patients. By 2019, the use of blood tests had increased substantially, to 47% of patients, although tissue-only remained the most common type (54%). While blood testing has become more popular, it is often still performed with tissue tests. The primary testing methods used in 2015-2017 were FISH for ALK and ROS1; NGS for MET, NTRK, and RET; and Sanger or NGS for EGFR. By 2018, NGS had become the predominant test method across all 6 biomarkers. During 2015-2016, several vendors were used for testing, with a very segmented market for ALK and EGFR tests. By 2019, the market had aligned to a few key vendors for the majority of tests. In 2016, the top 5 vendors did 76% of 180 total tests, which increased to 93% of 1880 tests in 2019. Almost all blood testing in our data was performed by a single vendor. Conclusions: Testing rates for ALK, ROS1, and EGFR were more consistent than those for MET, RET, and NTRK throughout the study window, possibly because of earlier availability of tests and treatments for these biomarkers. NGS was more available by the time MET, RET, and NTRK became established as actionable biomarkers, explaining the earlier use of panels. A limitation is that nearly 75% of the data are from the final 2 years. These results, however, represent notable testing trends from a large practice and illustrate the expanding application of molecular testing in community oncology.[Table: see text]

Implementation of Electronic Patient-Reported Outcomes for Symptom Monitoring in a Large Multisite Community Oncology Practice: Dancing the Texas Two-Step Through a Pandemic.

Among patients receiving chemotherapy, symptom monitoring with electronic patient-reported outcomes (ePROs) is associated with improved clinical outcomes, satisfaction, and compliance with therapy. Standard approaches for ePRO implementation are not established, warranting evaluation in community cancer practices. We present implementation findings of ePRO symptom monitoring across a large multisite community oncology practice network. Patients initiating a new systemic therapy at one of the 210 practice sites at Texas Oncology were invited to use the Navigating Cancer ePRO platform, with stepped-wedge implementation from July to December 2020. Participating patients received a weekly prompt by text message or e-mail to self-report common symptoms and well-being. Severe self-reported symptoms triggered a real-time notification to nursing triage to address the symptom. Enrollment and compliance were systematically tracked weekly with evaluation of barriers and facilitators to adoption and sustainability. Four thousand three hundred seventy-five patients planning systemic treatment were enrolled and participated. Seventy-three percent (1,841 of 2,522) of enrolled patients completed at least one ePRO assessment. Among these individuals, 64% (16,299 of 25,061) of available weekly ePRO assessments were completed. Over a 10-week period, compliance declined from 72% to 52%. Barriers currently being addressed include lack of a second reminder text or e-mail prompt, inconsistent discussion of reported ePROs by clinicians at visits, and COVID-related changes in workflow. Facilitators included ease of use and patient and staff engagement on the importance of PROs for symptom management. ePROs can be effectively implemented in community oncology practice. Utilization of ePROs is high but diminishes over time without attention to barriers. Ongoing work to address barriers and optimize compliance are underway.

Secret Sauce-How Diverse Practices Succeed in Centers for Medicare & Medicaid Services Oncology Care Model.

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. 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. 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. 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.

Virtual psychosocial services for the adult population in a large community oncology practice.

283 Background: Psychological and social supports are essential to address the emotional impact of cancer. The Covid-19 pandemic exacerbated emotional distress for patients with cancer and impeded many of the traditional service delivery models for supportive services. An increase in patient reported distress from routine distress screenings highlighted the need to transition to virtual Social Work (SW) services. Methods: Patients were referred to virtual SW services three ways: self-referral, distress screenings, and clinic staff. A virtual support group registration site was created to increase awareness which was promoted by our marketing team. Three different SW facilitated virtual support groups were offered: Stronger Together, Empower Your Recovery: A Program for Healing and Growth for Living Beyond Cancer©*, and Paving the Way for Your Journey: A Cancer Support Program (PTW). Of note, the PTW six-week psychoeducation support group curriculum was developed by six employed SW facilitators. Groups included closed and open formats with scheduled frequencies. In addition to virtual support groups, standard social support including, psychosocial assessments, Advance Care Planning, virtual counseling visits were offered virtually with patients via the VSee telemedicine platform. Results: Social Work referrals increased by 154% from 949 in 2019 to 2413 in 2020 due to positive distress screening. From March 2020-21, 14,948 patients received SW services which was an increase from 10,208 seen from March 2019-20. Of these, 372 received virtual psychosocial telemedicine services from March 2020-21. There were 4092 unique webpage views to the support group information and registration website. Total number of all virtual registrants in the 3 groups from May 2020 to February 2021 was 326. Conclusions: The COVID19 pandemic required us to use, technology and virtual tools to ensure continued patient access to psychosocial services and expand access to support groups, in addition to the in-person SW services that remained. Limitations of virtual support groups and telemedicine included lack of internet access felt to be from socioeconomic barriers. Further research is needed to evaluate the benefits of providing structured psychoeducational virtual support groups to patients with cancer. Virtual counseling and support groups may continue to benefit patients with cancer.

Establishing the need for provider education on cancer and nutrition (PECAN): Survey results on nutrition practices at a large community oncology practice.

49 Background: Oncology providers and patients benefit from evidence-based nutritional resources to support cancer care. For patients, proper nutrition care can prevent inappropriate weight loss, improve treatment tolerance, and improve quality of life. Recent literature has noted the lack of both adequate dietitian resources at outpatient centers and comprehensive nutrition guidelines in cancer care. At a large community practice with 210 locations across Texas and Oklahoma, a survey was developed and administered to assess nutrition practices. Methods: Clinic directors in the practice completed a survey to assess for the presence or absence of a malnutrition screen; how nutrition concerns are addressed; and the availability of a dietitian. Results: A total of 26 responses detailed the nutrition processes at 50 unique locations. At 37 (74%) locations, a malnutrition screening tool was utilized and of these, 30 (81%) locations reported utilizing the Malnutrition Screening Tool (MST), a brief, validated tool for outpatient settings including oncology. Seven (19%) sites did not specify what tool was used. Of the clinics that reported completing a malnutrition screen for patients, the screen was completed by the advanced practice provider (APP)/physician in 18 (49%) clinics, a nurse in 4 (11%) clinics, a dietitian in 4 (11%) clinics and a medical assistant in 1 (3%) clinic. At 10 sites more than one provider type was responsible for completing the screen. Nutrition issues were addressed by physicians, APPs, and nurses in 15 (50%), 35 (70%), and 9 (14%) sites respectively (see table). Twenty-two locations (44%) reported referring patients to a dietitian and 10 sites (20%) had a dietitian available in clinic. Forty-one (82%) clinics employed more than one method for addressing nutrition issues. Sixteen of 26 respondents (62%) reported that increased dietitian access would be helpful; this included respondents whose locations already had a dietitian available. Conclusions: Overall, 74% of reporting locations used a malnutrition screening tool and 20% had access to a dietitian on site. Forty-four percent of sites referred to a dietitian if there was a need. This indicates that multiple providers are involved in the nutritional care of oncology patients. In response to these findings, the multidisciplinary PECAN Taskforce was created to develop comprehensive malnutrition screening, implement a referral process for all at-risk patients, enhance nutrition education, and expand dietitian services. Further study will measure the impact of expanded nutrition access on patient outcomes.[Table: see text]

Strategic integration of genetic testing and counseling in patients with breast cancer in an oncology care model (OCM) multisite community-based practice.

231 Background: Despite consensus driven recommendations, data suggests significant non-compliance in breast cancer genetic screening and testing. In the US nearly 300,000 patients are diagnosed with breast cancer annually, of whom approximately one-third are estimated to be BRCA-testing eligible by NCCN guidelines. Of this cohort of patients eligible for testing, it is estimated that again only one-third are ultimately being referred for genetic counseling and testing. Ideally, every patient who is guideline-eligible for testing should be tested, if they consent. The purpose of this project was to integrate and universally apply NCCN genetic breast cancer testing guidelines, building off current OCM processes, to all new breast and/or metastatic breast cancer patients within a large multi-site community oncology practice setting. Methods: Providers utilized directed EHR templates in the setting of an initial diagnosis visit or a treatment planning “OCM visit”. Discreet data fields were created in the EHR to streamline, prompt, and automate this process. Following provider education and uniform physician pre-approval, appropriate patients were reflexively referred to the genetics team for further evaluation and BRCA testing. Adherence to the plan was maintained and measured using data analytic reports and chart audits. Results: OHC’s pre-project eligible patient testing rate (2018) was found to be 20%. Between 1/2019 to 1/2021 1,203 new breast and/or metastatic breast cancer patients were seen and deemed eligible for inclusion, fully 1,200 were screened using NCCN guidelines (99%). Of those screened, 631 patients met the NCCN testing criteria (52.5%). 585 of the 631 were referred to a genetic specialist (92.7%), of those 449 patients were tested (76.7%), 136 patients refused (30%). 22 patients were found to have a BRCA 1 or 2 mutation (5.3%). An additional “halo” effect on other cancer diagnoses was also observed. Screening newly diagnosed breast cancer and metastatic breast cancer patients resulted in a 163% increase in genetic referrals aside from those with breast cancer. Conclusions: Our results suggest a significant overall improvement in breast cancer genetic testing rates. Implemented methods of provider education and awareness of NCCN guidelines imbedded within provider notes, together with discreet data fields in the EHR, proved to be highly effective at screening appropriate patients and ordering subsequent genetic testing; ensuring nearly 100% compliance with current NCCN guidelines for genetic testing. The workflow also resulted in a favorable increase in genetic referrals and testing across other cancers. The patient refusal rate for testing merits further investigation. This structured workflow with reflex genetics referral was effective, scalable, and financially viable to overall genetic and practice growth.

Practice patterns among oncologists participating in the oncology care model after three years

BackgroundThe Oncology Care Model (OCM) incentivized care coordination and cost-efficiency and has been associated with short-term care reductions, but its multi-year associations are less well-studied. MethodsWe used monthly provider-level claims data spanning nearly five years between July 1 st, 2014 and May 30th, 2019 from a large community oncology practice network where roughly half of the practices participated in the OCM. The key outcome measures were monthly mean office visits, costs, and buy-and-bill drug costs among prostate, colon, breast, and lung cancers. We conducted two quasi-experimental analyses: an event study, which measures the monthly association of providing care in an OCM relative to a non-participating practice, and a difference-in-differences model, which summarizes the event study results into post-launch average estimates. We controlled for mean differences between practices, providers, and patient. ResultsThe event study analysis shows similar pre-period estimates and trends for each cancer. The difference-in-differences estimates for office visits are statistically significant for each cancer: 33 percentage point reductions in prostate cancer (95 % CI: -0.66 to 0.00; p = 0.05), 22 percentage point reductions in colon cancer (95 % CI: -0.48 to 0.04; p = 0.09), 21 percentage point reductions in breast cancer (95 % CI: -0.45 to 0.02; p = 0.08), and 24 percentage point reductions in lung cancer (95 % CI: -0.49 to 0.00; p = 0.05). Monthly prostate cancer costs also reduced by $505 (95 % CI: -$1108 to $99; p = 0.10). ConclusionOur results suggest that the OCM was associated with relative reductions in office visits and, for prostate cancer, in overall costs too. These associations generally decreased within the first year of launch and sustained through roughly two years. Policy summaryNovel payment models that incentivize care coordination and cost-efficiency like the OCM may modestly yet sustainably reduce office visits and overall costs.

Implementation of electronic patient-reported outcomes for symptom monitoring in a large multi-site community oncology practice.

12103 Background: Among patients receiving chemotherapy, symptomatic adverse event monitoring with electronic patient-reported outcomes (ePRO) is associated with improved clinical outcomes, satisfaction, and compliance with therapy. Standard approaches for ePRO implementation are not established warranting evaluation in community cancer practices. Objective: Evaluate implementation of ePRO symptom monitoring across a large multi-site community oncology practice network. Methods: Patients initiating a new systemic therapy at one of 210 practice sites in the Texas Oncology Practice were invited to use in the Navigating Cancer ePRO platform, with rolling implementation from July-December 2020. Participating patients received a weekly prompt by text message or email (patient choice) to self-report common symptoms and well-being via web or smartphone. Severe self-reported symptoms triggered a real-time notification alert to nursing triage to address the symptom. Enrollment and compliance were systematically tracked weekly with evaluation of barriers and facilitators to adoption and sustainability. Results: 4375 patients planning systemic treatment enrolled and participated, with baseline characteristics are shown in Table 1. 73% (1841/2522) of enrolled patients with follow up completed at least one ePRO assessment, and among these individuals, 65% (8762/25061) of all available weekly ePRO assessments were completed. Over a 10-week period, compliance with weekly symptom reporting declined from 72% to 52%. Patients on oral therapy had higher compliance rates overall. Barriers currently being addressed include lack of a second reminder text/email prompt, inconsistent discussion of reported ePROs by clinicians at visits, and COVID-related changes in workflow. Facilitators included patient and staff engagement on the importance of PROs for symptom management. Conclusions: ePROs can be effectively implemented in community oncology practice. Utilization of ePROs is high, but diminishes over time without attention to barriers. Ongoing work to address barriers and optimize compliance are underway.[Table: see text]

Bundling cancer subtypes in value-based care: A pilot analysis of lymphoma episodes in the Oncology Care Model.

e18850 Background: Value based models (VBMs) in which cancers are bundled are a growing alternative to fee for service, as in the Oncology Care Model (OCM). However, bundles in OCM may not capture the clinical granularity needed to predict resource utilization for cancer subtypes. One such bundle is lymphoma, which groups highly heterogeneous diseases with distinct treatments and differing intensity of care. Here, we compare OCM predicted episode costs (targets) to actual episode costs by lymphoma subtype. Methods: Our cohort study used OCM data from a large academic medical center (AMC) and large community oncology practice (COP). Six-month episodes of lymphoma beginning between July 2016 and June 2019 were categorized based on ICD-10 diagnoses on antineoplastic infusions and E&M visits, as well as disease and data modeling. Episodes were subdivided into follicular (FL), diffuse large B (DLBCL), small B (SBCL), mantle (MCL), Hodgkin (HL), Waldenstrom macroglobulinemia (WM), mature T/NK (T/NK), and Other. The distributional consistency of episode costs and targets for each subtype relative to the rest of the episodes was evaluated by Kolmogorov-Smirnov tests. We also compared the proportion of subtypes contributing to episodes in the AMC vs. COP. Results: A total of 1801 lymphoma episodes were identified (44% in AMC, 56% in COP). The most common subtypes (DLBCL and FL) contributed a larger proportion of episodes in the COP, while less frequent subtypes (T/NK, WM) were more prevalent at the AMC. Further, episode costs are significantly different across individual subtypes. Target variance was significantly lower than cost variance across subtypes. For example, the average target for WM was $50.4K, average costs were $40.2K, with 26% of episodes over target. In contrast, the average target for T/NK was $55.9K, average costs were $72.7K, with 64% of episodes over target. Conclusions: VBMs such as OCM currently aggregate cancer types and lack clinical granularity. Our evaluation of OCM episodes at an AMC and COP found considerable differences in lymphoma populations and in costs by subtype. Failure to account for clinical features (i.e. lymphoma history) could lead to inappropriate shifts of risk from payers to providers in VBMs.[Table: see text]

Implementation of electronic patient-reported outcomes for symptom monitoring in a large multisite community oncology practice: Dancing the texas two-step through a pandemic

Implementation of electronic patient-reported outcomes for symptom monitoring in a large multisite community oncology practice: Dancing the texas two-step through a pandemic

Telemedicine for cancer care: implementation across a multicenter community oncology practice.

To describe onboarding and utilization of telemedicine across a large statewide community oncology practice and to evaluate trends, barriers, and opportunities in care delivery during the coronavirus disease 2019 pandemic. We describe telemedicine onboarding and utilization across a statewide oncology practice, covering 221 sites of service and more than 650 practitioners. We describe qualitatively the onboarding process of a diverse set of administrative, technical, and clinical partners. We describe quantitatively utilization throughout the practice. We describe a survey conducted to enlighten barriers and opportunities for optimal utilization. Multistakeholder education was directed to clinical teams, administrative and technical support staff, and patients through webinars and team meetings. Utilization was high from April through October 2020, representing 15% to 20% of new-patient visits and 20% to 25% of established-patient visits. In a survey offered to all clinicians, 96% of respondents indicated they are using telemedicine, with 33% using it for more than 25% of patient encounters. Among respondents, 59% reported that the use of telemedicine helps expedite diagnosis and treatment more than seeing patients in person in the clinic, 55% of respondents managed urgent issues by telemedicine, 80% believed that patients benefited From urgent assessment by telemedicine, and 57% believed an emergency department visit or a hospitalization was avoided because of a telemedicine visit. Most clinicians reported that patients enjoy benefits of telemedicine because of decreased exposure risk, decreased transportation requirements, and ease of including caregivers in the visit with the treating clinician. The most common barriers to patients accessing telemedicine were technical challenges and broadband access. Despite this, less than 5% of respondents routinely use telephone-only communication, as most typically use bimodal audio/video communication. Many clinicians have expansion ideas on how telemedicine can further expand the longitudinal care delivery for our patient population. Telemedicine can be implemented successfully across a large statewide oncology practice and service a high volume of patients. Clinicians utilize telemedicine for new and established patients with minimal dysfunction. Clinicians believe patients benefit From telemedicine For new, established, and urgent care visits. Broadband access functionality should be explored to optimally serve our patient population.

Utilization of telemedicine to meet the demand throughout the COVID-19 pandemic at a community oncology practice.

263 Background: A large community oncology practice in Tennessee participates in value-based payment arrangements, the success of which depends on close patient monitoring. Telemedicine as an innovative solution was initiated in 2017. The service was limited, due to regulation, licensure requirements, and lack of reimbursement, to survivorship visits, clinical trial consent visits, rural hospital consults and genetic counseling. During the COVID pandemic and loosening of restrictions, telemedicine services were expanded. Methods: We identified a cloud-based platform that allowed patients to use any device with a camera and microphone and required no software downloads. On-line training sessions were provided to clinical staff. All training and workflow implementation were completed in a 2-week time frame. Telemedicine was expanded to include surveillance, urgent care, psychology, palliative care and post-BMT visits as well as new patient consults for medical, radiation and gynecologic oncology patients. Patient satisfaction surveys were administered. Results: Our telemedicine visits increased weekly beginning March 1, peaking in the month of April with an average of 77 scheduled telemedicine visits per day across the practice. During the month of April, our practice saw a record clinical trial accrual in our Phase-1 Drug Development Unit with a 22% increase over the previous average. Patients who responded to a satisfaction survey were highly satisfied with the telemedicine visit with a 73% positive response rate. Nearly half of our eligible patients did not have the technology or broad-band access to be able to participate in telemedicine. Conclusions: Our prior experience with telemedicine, though limited, facilitated the development of an infrastructure that provided adequate number of devices and internet bandwidth capacity to support rapid expansion of telemedicine. We were able to maintain high quality care and access to clinical trials during the pandemic and see the value of this service long-term. We hope to add tele-pharmacy and care coordination services. Political leadership and patient advocacy groups should explore ways to ensure that all patients may benefit from this technology, especially those in under-served areas.

Real world experience of poly (ADP-ribose) polymerase inhibitor use in a community oncology practice

ObjectiveThis study aims to describe the real-world experience, including the clinical and financial burden, associated with PARP inhibitors in a large community oncology practice. MethodsRetrospective chart review identified patients prescribed olaparib, niraparib or rucaparib for maintenance therapy or treatment of recurrent ovarian, primary peritoneal or fallopian tube cancer across twelve gynecologic oncologists between December 2016 and November 2018. Demographic, financial and clinical data were extracted. One PARP cycle was defined as a single 28-day period. For patients treated with more than one PARPi, each course was described separately. ResultsA total of 47 patients and 506 PARP cycles were identified (122 olaparib, 24%; 89 rucaparib, 18%; 294 niraparib, 58%). Incidence of grade ≥ 3 adverse events were similar to previously reported. Toxicity resulted in dose interruption, reduction and discontinuation in 69%, 63% and 29% respectively. Dose interruptions were most frequent for niraparib but resulted in fewer discontinuations (p-value 0.01). Mean duration of use was 7.46 cycles (olaparib 10.52, rucaparib 4.68, niraparib 7.34). Average cost of PARPi therapy was $8018 per cycle. A total of 711 phone calls were documented (call rate 1.4 calls/cycle) with the highest call volume required for care coordination, lab results and toxicity management. ConclusionsAlthough the toxicity profile was similar to randomized clinical trials, this real-world experience demonstrated more dose modifications and discontinuations for toxicity management than previously reported. Furthermore, the clinical and financial burden of PARP inhibitors may be significant and future studies should assess the impact on patient outcomes.

Utilization of liquid biopsy in a large community oncology practice.

e19150 Background: Analysis of tumor cell free DNA, or liquid biopsy, is emerging as a useful adjunct to tissue biopsies in advanced solid tumors. These tests may reduce the need for repeating invasive biopsies, and may be performed serially with minimal risk to patients.The purpose of our study is to document how liquid biopsies are being used in a large, diverse community based practice in Long Island, NY and how often the results lead to changes in treatment. The aim is to derive guidelines within the practice for appropriate use of liquid biopsies going forward. Methods: The practice electronic medical record (EMR) was retrospectively examined for the first 100 patients with solid tumors who had a specimen sent to a commercial laboratory for a liquid biopsy. The EMR was also reviewed to establish the treatment regimens each patient was receiving prior to the liquid biopsy, as well as any changes to the regimen based on liquid biopsy results. Results: This analysis was based on 100 patients: 11 out of 100 patients (11%) were excluded due to loss of follow up and 89 out of 100 (89%) patients were included, 59% female and 41% male. 11 out of 100 patients (11%) were not found to have any tumor alterations on liquid biopsy. The most prevalent cancers were lung (40.4%), ovarian (17.0%), breast (6.4%), colon (5.3%) and prostate (5.3%). Treatment was changed 43% of the time after liquid biopsy results were obtained and there was no change in 57% of the time see Table. This change was irrespective of type of cancer, gender, or types of current regimen. Conclusions: Liquid biopsy has proven to be a useful adjunct to molecular testing of tumor tissue in a large community oncology practice, but ongoing examination of our results should better define its optimal use. [Table: see text]

Impact of embedded palliative care providers compared to externally available palliative care services on the number of patients receiving palliative care referrals in a large community oncology practice.

12103 Background: Palliative care improves quality of life and may increase overall survival in patients with solid tumor malignancies. Despite having the ability to refer patients to in-home and external palliative care services, we observed low palliative care referral rates in our practice of 90 oncologists across 30 clinics. We tested whether embedding palliative care providers directly in clinic would improve palliative care referral rates for solid tumor patients. Methods: Between 2017 and 2020, we embedded an independent palliative care provider into five clinics across middle Tennessee. Access to external palliative care services was present both before and after the intervention. Using data from our EHR and billing systems, we performed a pre-post analysis measuring palliative care referrals in the six-month periods immediately before (pre-intervention period) and after (post-intervention period) a palliative care provider was embedded in each clinic. Statistical significance was assessed using Welch’s two sample t-test. Results: 8,636 unique solid tumor patients were seen in the five clinics during the study periods (Table). Despite having the ability to refer patients to external palliative care services in the pre-intervention period, the placement of a palliative care provider into clinic increased the number of solid tumor patients that received a palliative care referral per month at all clinics (min.: 200%; max.: 990%; median: 600%). Four of the five increases were statistically significant (p-values < 0.05). Conclusions: Even when external palliative care services are available, embedding palliative care providers into community oncology clinics significantly increases the rate of palliative care referrals for solid tumor patients. [Table: see text]

Impact of augmented intelligence (AI) on utilization of palliative care (PC) services in oncology.

12015 Background: Timely integration of palliative care in the management of patients with advanced cancer is a quality benchmark in oncology. However, PC is often underutilized as evidenced by delays in identification of appropriate patients, in referrals to a PC service, and in enrollment to hospice. Jvion has developed a prescriptive analytics solution, the Machine, which combines AI algorithms with machine learning techniques and applies them to clinical and exogenous datasets to identify patients with a propensity for poor outcomes. The Machine was applied to risk for patients’ mortality within next 30 days, and recommended patient-specific, dynamic, and actionable insights. Use of the Machine requires no additional documentation within the electronic health record (EHR) and the insights generated can be integrated back in to any EHR to help inform the care plan. Herein, we report the results of a study evaluating the impact of AI-driven insights on PC utilization at a large community oncology practice. Methods: All patients were scored weekly using the Machine PC vector. The Machine risk stratified the patients and generated recommendations for the provider to consider as they developed a care plan. Patients identified as “at risk” by the Machine were assessed for a supportive care visit (PC referral) and then were referred as deemed clinically appropriate. The average monthly rates of PC consults and hospice referrals were calculated 5 months prior to and for 17 months after the launch of the Machine in the practice. Results: The oncology practice has 21 providers managing an average of 4329 unique patients per month (PPM). The mean rate of PC consults increased from 17.3 to 29.1 per 1000 PPM pre and post Machine deployment respectively (+168%). The mean monthly rate of hospice referrals increased by 8-fold from 0.2 to 1.6 per 1000 PPM pre and post deployment respectively. Eliminating the first 6 months of Machine deployment to account for user learning curve, the mean rates of monthly PC consults nearly doubled over baseline to 33.0, and hospice referrals rose 12-fold to 2.4 per 1000 patients in months 7-17 post Machine deployment. Conclusions: This oncology practice found deployment of this novel AI solution to be feasible and effective at generating actionable insights. These AI driven insights could be incorporated into workflow and improved the decision-making for whether and when a patient should be referred to PC and/or hospice services for end of life care. Further study is needed to confirm the value of AI for management of cancer patients at end of life.