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]

Utilizing data and artificial intelligence to optimize treatment room scheduling and staffing

436

Background: Tennessee Oncology is a large community oncology practice with over 30 clinics providing 89,000 treatments per year across Tennessee and northern Georgia. Tennessee Oncology’s scheduling application was unable to optimally schedule treatment appointments. This scheduling gap was causing frequent patient delays and employee extended hours. Tennessee Oncology partnered with Smirta, Inc., to develop a data and artificial intelligence (AI) driven scheduling overlay platform that would optimize and simplify cancer treatment scheduling as well as predict scheduling patterns and resource needs. Methods: Named OncoSmart, the scheduling optimization platform ingests historic scheduling data, detailed clinic configuration data including provider and nursing schedules, and available resource data such as treatment room chairs. Utilizing AI, the platform generates optimal scheduling recommendations matching the specific set of services that need to be scheduled. The platform overlays the current scheduling app and provides dynamic, real-time recommendations based on current resource (treatment room, provider, etc.) schedule availabilities and bookings. Tennessee Oncology piloted the scheduling optimization platform at 1 clinic and has currently expanded the pilot to 12 additional clinics. Results: After various ranges of clinic pilot times (6 months to 2 years), Tennessee Oncology treatment volumes have increased by 7%. In parallel to this increase, the optimization platform has helped decrease extended hours by over 32%. The original pilot site has shown major improvement in all 4 primary key performance indicators (KPI): treatment volume +12%; Chair utilization +12%; treatment delay -9%; extended hours -82%. Additionally, using the platform’s predictive analytics capabilities, analyses have been completed to generate optimal treatment scheduling patterns as well as optimal treatment nursing staffing models. Conclusions: Within a short period after deployment, Smirta Inc’s OncoSmart has helped Tennessee Oncology identify better treatment scheduling options for these 13sites. The scheduling optimization platform has proven to be very effective in identifying optimal treatment scheduling strategies and in identifying critical resource bottlenecks. The platform’s clinic management, optimization, nurse assignment, business intelligence, and resource management modules has empowered Tennessee Oncology to better manage critical clinical resources and reduce staff overtime during a period of growth.

Provider-led advance care planning in community oncology: A successful multidisciplinary quality improvement intervention

209

Background: Advanced care planning (ACP) is an important aspect of shared decision making in cancer treatment. Due to its importance, in 2016, Medicare expanded coverage and reimbursement for advance care planning (ACP) services (CPT codes 99497 and 99498). Despite this, ACP has been underutilized in practice. Methods: Tennessee Oncology aimed to increase knowledge and utilization of this service by medical oncologists and advance practice providers and corresponding CPT codes through an educational and quality improvement project. We formed a multidisciplinary team with individuals representing medical oncology providers, palliative care team, billing and accounting, information technology and informatics, nursing, navigation team, and operations. This team created an educational video, incorporating the “PAUSE” framework for addressing advance care planning and its role in community oncology, and details of documentation and billing. We also built in documentation templates into the medical oncology note and created a process to automate the charge capture to avoid additional steps for oncology providers. Results: Prior to this initiative, there was no baseline method to measure ACP and corresponding documentation. After two months of launching our educational video and new documentation templates, 120 documented ACP discussions were completed. ACP documentation was performed by 61 total providers practicing across 16 clinics. Providers completing documentation included both medical oncology (n = 53, 86%) and palliative care (n = 8). Of medical oncology providers, 39 (73%) were physicians and 14 (27%) were advanced practice providers. The three most common cancer diagnoses in ACP encounters were lung (20%), breast (13%), and prostate (8%). Conclusions: This combination of education and automation with multidisciplinary team input helped establish a baseline for ACP measurement that will help identify gaps and improve ACP discussions and documentation in our practice going forward.

Electronic patient-reported outcomes (ePRO) platform engagement in cancer patients during COVID-19

172

Background: Tennessee Oncology partnered with an ePRO platform solution to support patients during their cancer care journey. This cloud-based ePRO platform is designed to assist in improving the management of symptoms. Providing two core pieces of functionality allow both the patient and care teams to retrieve information quickly and communicate effectively. The patient portal is patient input driven and allows the patient to communicate with their care team, track symptoms, and access their health records via website or mobile app. The clinician portal provides multiple care teams the ability to manage and prioritize patient needs as well as communicate directly with patients. In March 2020, due to the pandemic, patients needed a convenient and remote way to communicate with the care team. Our communication plan had to be nimble and provide immediate updates to our large patient population. We leveraged our ePRO platform to meet this need. Methods: We focused efforts on increasing patient engagement by educating them on the benefits of this communication platform. We utilized secure messaging to send appointment details and for Telehealth visits a link to the visit was sent. We were able to provide weekly updates outlining our latest information regarding our safety protocols. Results: We noted an increase in the activation of patient accounts and patient-initiated messages in our ePRO platform. We saw an average of 1,000 new patient accounts activated each month during March, April and May. We saw that patient-initiated messages through the platform showed a 15% increase from February to March. The response rate for patients completing post-treatment questionnaires increased 8% from February to May. Conclusions: By providing patients with a single communication platform to contact their care teams outside of their office visits, patients become an active part of their care journey. As an organization, we continue to identify ways to connect our patients to their care team in a meaningful way through technology. Whether during normal business hours or after-hours, patients need a simple, reliable and consistent way to engage with their care team.

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.

Partnership with an independent genetic counselor and standardized screening: Effect on the identification, referral, and genetic testing of eligible patients in a community oncology clinic

138

Background: A nine provider, community oncology clinic had limited local access to genetic counseling. Additionally, the practice had no process for identifying appropriate patients for genetic counseling or testing and no method to track referrals and test results. The practice partnered with a contracted genetic counselor and a study was completed to standardize screening and follow-up and to increase referrals and testing. Methods: Baseline data on genetic testing performed in 2018 was obtained from three major genetic testing labs. Based on the NCCN guidelines for genetic assessment, the practice created automated screening reports from the EMR, supplemented by manual chart review, to identify appropriate patients for genetic counseling. Front office, clinical and billing workflows were created. Patients were scheduled to see the counselor via in-person appointments or remotely via a HIPAA compliant telemedicine platform. The genetic counseling sessions included education and consent for testing followed by review and discussion of results. Consultations and genetic testing results were documented in the practice’s EMR. Results: Baseline data showed that the clinic tested 7 patients in 2018; 2 patients in the first quarter. During the pilot from Jan-Mar 2019, 34 patients were referred for genetic counseling; 30 consented to testing. This is a 329% increase over 2018; 1400% for the first quarter. Of the 30 patients tested during the pilot, 6 were positive for a pathogenic mutation. Conclusions: By contracting with a genetic counselor, and establishing procedures for screening, counseling, consenting, testing and follow-up, the practice was able to increase the number of appropriate genetic testing considerably. This process will be scaled to multiple sites of a community practice.

Care coordination for oral oncolytics through pharmacy integration and cycle 1-day 1 documentation

260

Background: The growing number of oral oncolytic therapies (OOTs) necessitates a standardized EMR workflow that integrates pharmacy activities for dispense and patient management and standardizes cycle-1/day-1 (C1D1) documentation. Our practice’s treatment plans contain appropriately timed OOT follow-up activities including labs, physician follow-up visits, and pharmacy calls for toxicity and adherence checks, however complications in prescription fulfillment such as prior authorization, co-pay assistance, or inability of in-practice pharmacy to dispense limit the predictability of C1D1 dates of OOTs. Methods: An EMR query identified patients at a single clinic location of 5-medical oncologists (MDs) for whom oral oncolytic treatment plans were entered from January 1 to June 30, 2018. C1D1 date entered by the MD in the EMR was compared to the pharmacy processing system dispense date. Ten patients were identified, and 10% (1/10) had an accurate C1D1 documented within the EMR. As part of the ASCO Quality Training Program, to improve the accuracy of C1D1 documentation, a new workflow was implemented whereby: (1) a “hold” activity was added to new EMR treatment plans so that C1D1 remained pending until patients had received medication; (2) clinic checkout staff provided patients with information on the in-practice pharmacy and expectations for next steps; (3) pharmacists utilized existing reporting tools to identify newly entered treatment plans and transcribed orders into e-prescriptions sent to our practice pharmacy; (4) the pharmacy workflow ensued with pharmacy staff leading patient engagement, drug counseling; (5) pharmacists confirm C1D1, document within EMR (6) subsequent treatment plan activities were scheduled. Results: Following education and process changes within the clinic and pharmacy, accurate C1D1 documentation occurred in 90% (9/10) of patients initiating OOTs. Conclusions: Including pharmacy fulfillment time in EMR workflow can improve C1D1 documentation accuracy and associated management of OOTs. Education regarding roles and processes of prescribing MDs, pharmacy staff and clinic staff will be required to scale this process improvement throughout the organization.