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Fifteen years ago, the Institute of Medicine (IOM) issued a report that defined Survivorship Care as a distinct phase of the cancer care continuum. The required domains to meet the health needs of cancer survivors were outlined in the report: cancer surveillance and screening, cancer prevention and lifestyle counseling, management of treatment related persistent or late effects, coordination of care, and psychosocial support services. In response to that report, The University of Texas MD Anderson Cancer Center implemented a tiered survivorship care model that is risk based. The core principle is that cancer survivors’ health needs will depend on the cancer treatment and disease-specific risks. We here describe this model for low-, intermediate-, and high-risk cancer survivors, in which comanagement between oncology and primary care providers is risk dependent. Our clinical model defines transition as appropriate when there is a minimal risk of primary cancer relapse, which is specific to each cancer type and disease stage. This model is embedded into disease-specific clinical practice algorithms, aligned with the IOM domains of care. Over the past 10 years, we have successfully transitioned nearly 25 000 patients to disease-specific survivorship clinics, providing care based on the IOM domains. We have learned from our process that expansion of survivorship care into established clinical settings requires engagement of champions and key clinical stakeholders. Future directions for survivorship care should explore the application and potential benefits of telemedicine as a care delivery system to meet the needs of cancer survivors.

335 Background: The recent pandemic led to an untypical demand for virtual care visits in our comprehensive cancer center. Our institution responded to this paradigm shift by offering virtual care to all cancer patients, including cancer survivors. In place of an in-person visit, patients were offered a live video or telephone (audio) appointment for their survivorship clinic visit. We conducted a quality improvement study to identify patterns in the type of virtual visits preferred by patients scheduled for appointments in eight dedicated survivorship clinics. Methods: We conducted a retrospective review of 4784 patients’ medical records who were seen in eight site-specific survivorship clinics from April 2020 – April 2021. Variables reviewed included type of visit, i.e. telephone, live video, or in-person, and patient characteristics such as age, gender, clinic, and distance from cancer center. Descriptive statistics were performed to assess for patterns of virtual care. The review was approved by the Quality Improvement Assessment Board. Results: Virtual care visits varied by clinic (0-86%). Five clinics ((breast, lymphoma, sarcoma, melanoma, and gynecological) performed < 3% of visits using virtual format. A sub-analysis of the 8 clinics performing virtual visits demonstrates 59.5% virtual activity (19.23% phone compared to 39.3% video). Older patients were more likely to use any form of virtual visit compared to in-person (58.9% for those ≥ 65 vs. 54.9% for 18-39). Older patients were more likely to prefer phone visits (25.5% for ≥ 65 vs. 11.2% for 18-39). Local patients were more likely to utilize virtual visits (63% for patients < 75 miles vs. 45% for patients > 500 miles). Patients who lived furthest from the cancer center were more likely to travel in for their appointment, though this population contained fewer patients than those within 75 miles. Use of virtual visits for survivorship care varied, depending on the types of clinical diagnostic tests or examinations required for an annual visit. Conclusions: Our results indicate the use of virtual care was optimal when only lab testing was ordered by their provider. Older adults, with no or limited access to and knowledge of digital technology (computers, smartphones, and others similar tools) may need additional support to engage in video visits. Our findings suggest virtual care can be successfully implemented in the care of survivors. Further research would help determine best-practice approaches to facilitating patient engagement in virtual visits since telemedicine continues to evolve as a standard method to deliver safe and optimal cancer care.

334 Background: Standard methods for implementation of electronic patient reported outcomes (ePROs) in the routine care of cancer survivors remain unclear. To address this gap, we assessed the technical and operational feasibility of implementing ePROs into the clinical workflow of four survivorship clinics, Genitourinary (GU), Head & Neck (HN), Thyroid (THY), and Stem Cell Transplant (SCT). Methods: This quality improvement study was conducted from 9/1/2019 to 4/30/2021. Benchmarks of ≥ 50% were established for two outcomes including: (1) Delivery Rate - percentage of patients who received the ePRO prior to their clinic visit and (2) Adherence Rate - percentage of patients who completed one ePRO. Data were collected at T0 (Baseline) (09/01/2019 to 12/31/2020) and T1 (1/1/2021 to 4/30/2021). Patients completed the survey 3-7 days prior to a clinic visit. The timing to capture ePROs’ data was tailored to the specific cancer site. Operational steps were: 1) questionnaire was ordered for scheduled survivorship appointment; 2) electronic medical record system (EMRS) pushed the questionnaire to the patient portal app with a message asking the patient to complete and submit the ePROs survey, 3) data was pushed back to the provider by the EMRS; and 4) results stored in the medical record were accessed by the provider prior to or on the day of the patient’s visit. Data were collected and stored using the EPIC Data Universes and reported through Microsoft Power BI. This institutional Quality Improvement Assessment Board approved this study. Results: The Table shows the improvement in the benchmark for sent and adherence rates between T0 and T1. A few clinics showed room for improvement. Patient engagement facilitators included being scheduled for a virtual visit and having staff sent prompts prior to visits. Challenges were: (1) variation in the time ePROs were available in the medical records, 2) inconsistent linking of scheduled visits and prompt to send the survey, and 3) patients’ not opening, completing, or submitting the survey even when prompted to do so. Opportunities included (1) developing a patient education flyer describing ePROs’ role in patient care, (2) providing instruction on the completion and completion of how to complete the ePRO, and (3) conducting staff education sessions on how to link scheduled visits with ePROs’ patient prompts. Conclusions: Our preliminary results indicate that integration ePROs can be considered an acceptable approach to improve follow-up care of cancer survivors but with room for improvement in some clinics. Future evaluation will further explore patients’ ePROs’ impact on clinical outcomes and patient engagement.[Table: see text]

Introduction: In 2009, our institution's leadership supported the creation of the Cancer Survivorship Program founded on core elements from the 2006 Institute of Medicine report “From Cancer Patient to Cancer Survivor: Lost in Transition.” These elements align with those recently posited in the 2019 Commission on Cancer (CoC) Standard 4.8. to establish and monitor a Survivorship Program. Here we describe our program model and present data collected over a decade to evaluate the program's outcomes. Procedures: Six key components guided the program's implementation and sustainability. These factors included: 1) inclusion of patients treated with curative intent, 2) recruitment of a transdisciplinary program staff, 3) delivery of clinical services based on 4 domains of survivorship care, 4) provision of consultative services available on-site or through referrals, 5) use of a quality improvement plan to monitor services provided, and 6) the creation and dissemination of treatment summaries and survivorship care plans. We reviewed electronic health records (EHR) of patients seen in the 12-survivorship clinics between 2009 and 2019. Data sources consisted of OneConnect, EPIC universes, and a departmental database. Data elements collected on arrived or missed appointments, no-show rate, and completion rates for the treatment summary and 30-day Passport (Survivorship Care Plans). Descriptive statistics summarized metrics per clinic and as a group. Results: Twelve site-specific cancer survivorship clinics scheduled appointments for survivors who had completed their curative treatment. A medical and operations director led the 6-member team who coordinated and monitored program activities. Patients had access to consultative services (i.e. cardiologists, nutritionists, social workers, etc.) provided by the institution or through community referrals. Table 1 summarizes data related to clinic visits for 10 years. In FY 2019, clinics with the highest number of arrived appointments included breast (4985), GU (1709), and head and/neck (1175). Clinics with the highest treatment summary compliance rates were lymphoma (97%), thyroid (77%), and stem cell transplant (72%). Each year, about 20% of patients scheduled are being seen for the first time in a survivorship clinic (rates vary by clinic). Conclusions: Results from our 10-year program experience suggest the newly proposed CoC survivorship program model can be practical and successful. Citation Format: Guadalupe Palos, Katherine R. Gilmore, Weiqi Bi, Patricia Hansberry Chapman, Kathy Carpenter, Maree Joy Pancho-Acorda, Maria Alma Rodriguez. A single center's ten-year experience in sustaining a cancer survivorship program [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 5747.

e21602 Background: We developed institutional algorithms for cancer survivors that are site specific. However, little data exists regarding concordance with these clinical management tools. Our aim was to evaluate concordance rates with our Head and Neck (H/N) survivorship algorithms. Methods: We reviewed electronic health records (EHR) of patients seen in the H/N Survivorship Clinic between 9/01/2011 and 8/31/2014. Eligibility included: diagnosis of primary head and neck cancer, ≥ 18 years of age, no active disease, and alive at time of abstraction. Data were collected at baseline (V1) and visits 9-15 months after prior visits (V2 and V3). Data were obtained from tumor registry, a departmental database and the EHR. Twelve data elements were grouped as: 1) lab/diagnostic tests, 2) physical and psychological late effects, and 3) history and physical exams. Concordance rate (%) for each element was defined as a clinical action or recommendation aligned to the standards outlined in the H/N algorithms. Descriptive statistics were used to summarize clinical, demographic, and concordance rates. Results: Included in this analysis were patients with primary H/N malignancies of oropharynx, oral cavity, larynx, and hypopharynx, and who had completed 3 visits (V1-3). 53 patients were evaluable for concordance analyses. Compliance ranged from 55% to 100%, with lowest rates for: CT scans (55.6%), distress screening (75.5%), T4/TSH level (78.4%) and laryngoscopy (79.2%). Highest rates were noted for full physical exam (100%), chest x-ray (97.5%), dental exam (95.9%), and dysphagia evaluation (95.1%). Assessments for lymphedema and xerostomia were similar (91.8%). Conclusions: High compliance ( > 90%) occurred when elements of the algorithm relied on the clinician’s assessment, whereas lower levels of compliance were seen with elements that required orders (CTs and labs), or reliance on others’ actions (i.e. distress screening by nursing). Concordance can be improved using best practice advisories in the EHR to remind providers of orders, and by fostering strong inter-professional communication on the elements of care.

93 Background: A core measure of the ASCO Quality Oncology Practice Initiative and Commission on Cancer Program Standard is adherence to use of written treatment summaries (TSs) and care plans (CPs) for cancer survivors. Previous data from ASCO’s quality improvement (QI) studies indicate inconsistent use and distribution of treatment summaries and care plans. Audits conducted of adherence rates among our survivorship providers indicated use varied across clinics. We developed a plan to improve use of TSs and CPs among providers and improve survivors’ outcomes. Methods: The Plan-Do-Study-Act QI model was used to identify gaps in performance and process failures that led to those gaps. The project used stratified purposive sampling to select clinics. Based on the disease site, staffing structure, and clinical infrastructure, the breast, genitourinary, and head/neck survivorship clinics were chosen. First, we identified primary elements of the processes detailed in clinical practice algorithms specific to each site. Next qualitative interviews were conducted with providers to identify strengths and barriers to the use of TSs and CPs. Interviews were audio-recorded, transcribed verbatim and analyzed to confirm themes. Descriptive statistics were used to summarize demographic and clinical data. Results: A total of 16 members of the 3 clinics were interviewed. Of these, 37.5% were providers, 31.3% administrators, 18.8% support staff, and 12.4% faculty champions. Major themes identified as hindering adherence rates centered on cumbersome scheduling processes i.e. “there’s so many people that have to “touch an order” to get it to happen”, fragmentation among electronic medical records systems, i.e. “the way to fix it would be if it was a smart automated document that took the information…there in the chart," limited support among other health care professionals about survivorship care, i.e. “when push comes to shove Survivorship gets pushed. That’s the nature of the beast.” Conclusions: The barriers identified can be used to develop feasible solutions to improve adherence rates among survivorship clinic providers. Findings from this QI project contribute to deeper understanding of the complex issues involved in improving outcomes for survivors.

Purpose: To assess providers’ concordance with surveillance and risk reduction recommendations for colorectal cancer (CRC) survivors after completion of their curative treatment. Patients and Methods: This was a longitudinal study of survivors who met the following eligibility criteria: diagnosed with a primary colon or rectal cancer before their first visit (V) to the CRC Survivorship Clinic, adult survivor ≥ 18 years old, no evidence of disease, alive at the time of data abstraction, and 1-3 clinic visits between 9/01/2011 and 8/31/2014. Data were collected at V1 scheduled between 9/1/2011 and 8/31/2012. V2 was scheduled 9-15 months after the first visit. V3 was also scheduled 9-15 months after V2. Data sources were survivorship care plans, electronic medical records, and CRC survivorship algorithms. For an annual visit, CRC algorithms recommended history/physical exams (H & PEs), carcinoembryonic antigen (CEA) testing when previously elevated, and colonoscopies for surveillance of cancer recurrence. Concordance rates (CR) were measured as the percent of yes/no responses to whether the providers followed minimum standards for the 3 procedures. Demographic and clinical characteristics were also collected. Descriptive statistics were used to summarize all data. Results: 81 of 117 CRC survivors who met all eligibility criteria were included in this sub-analysis. The number of survivors visits varied across time, V1 = 81, V2 = 56, and V3 = 36. Most survivors were male (51.9%) and Caucasian (66.7%). 67.9% reported being 5-8 years post-treatment. 58% were diagnosed with colon cancer and of those 61.7% were Stage IIIA-IV compared to 55.8% of rectal cancer survivors with advanced disease. Table 1 summarizes the percentage of CR rates across the 3 visits. Conclusion: CRs for H & PEs and colonoscopies remained high across the 3 visits. CRs were lowest for CEA recommendations. These low rates suggest further work is needed to determine barriers in clinical practice that limit use of CEA tumor marker monitoring in CRC survivors. Percent of Providers ConcordanceAlgorithm RecommendationVisit 1Visit 2Visit 3H & PE100100100CEA53.338.322.2Colonoscopy97.598.2100 Citation Format: Guadalupe Palos, Katherine R. Gilmore, Patricia Chapman, Paula Lewis-Patterson, Weiqi Bi, Maria Alma Rodriguez. Low concordance with CEA tumor marker monitoring in colorectal cancer survivors. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3464.

245 Background: Clear patient-centered recommendations for follow-up and health maintenance is a primary goal of ASCO’s model for survivorship and palliative care. The Commission on Cancer also sought to improve the quality of survivorship care by requiring accredited programs to implement survivorship care plans (SCPs) and treatment summaries by 2015. Our aim is to describe the SCP's components and metrics collected in 12 survivorship clinics of an academic cancer center. Methods: A multidisciplinary team was convened to develop clinical practice tools to guide providers on transitioning patients to a survivorship clinic. These tools were based on 4 IOM's domains: surveillance, risk reduction, late effects management, and emotional function.Algorithms are supported with a Passport Plan for Health (Passport) specifically designed for each disease. These clinical tools allowed clinicians to provide recommendations for each survivor. Tools were electronically available to survivors and their primary care providers. Descriptive statistics were used to summarize metrics in this analysis. Results: To date, 44 cancer-site specific algorithms and 19 Passports have been launched and used by clinicians in 12 survivorship clinics.Metrics collected are: a) number of Passports completed, b) providers’ completion of SCPs, and c) dates with counseling recommendations outlined in the treatment pathways. Since FY08, 25,912 Passports were distributed to 13,105 survivors. In FY14, 6,160 Passports were issued (80.7% provider completion rate). Passport completion varied by provider (7%-97%). Survivors were counseled for recommendations related to colonoscopy (97% of the time), skin screening (98%), mammogram (97%), gynecological screening (95%), and prostate screening (74%). Conclusions: Algorithms and SCPs serve as clinical tools to help providers and survivors manage physical and emotional issues. These tools increase standardization in the delivery of survivorship care, safety, quality, and promote communication among survivors and providers across clinical settings.

242 Background: Late effects, such as pain and fatigue, increase a cancer survivors' risk to psychosocial distress. Assessment and identification of distress and other risk factors can be integrated into survivorship care. Yet, clinical tools and processes needed to coordinate these efforts are severely limited. Here we describe the processes and metrics used to assess and document distress in the survivorship care plans (SCPs) of survivors diagnosed with colon and rectal cancers (CC and RC). Methods: Eligibility criteria for this longitudinal analysis included being: ≥ 18 years, diagnosed with a primary colon/rectal cancer, no evidence of disease ≥ 5 years, seen between 09/01/2011 - 8/31/2014, and alive at time of data abstraction. 117 survivors met these criteria and the first 50 sequential cases were included in this sub-analysis. Data were collected at Visits 1, 2, and 3 within specific time parameters. Data sources included the SCP, electronic medical records (EMRs), and CC/RC algorithms. Variables included demographic/clinical characteristics and standards of care (SOC) elements embedded in the algorithm related to distress, fatigue, pain, and social support. Compliance with SOC were measured using a “yes/no” response format. Results: Of 50 survivors, 58% were diagnosed with CC and 42% with RC. 52% were male, 64% Caucasian, 54% age 65-89 years, and 68% were 5-9 years from diagnosis. 52% of CC survivors were Stage IIIA-C or IV and 57% of RC were Stage 1-IIB. Documentation and metrics for each element indicated a total of 111 visits over the course of the analysis, 59% were CC and 42% RC. Provider's compliance rates (PCRs) were: distress (65%), fatigue (32%), pain (68%), and social support (46%). The pain element was not included in the CC algorithm. PCRs for each element varied by site. Evidence that providers followed algorithms' recommdendations to assess survivors current risk of distress was found in the EMRs, SCPs. Conclusions: We found cancer survivorship clinical algorithms and care plans can guide assessment, documentation, and monitoring of psychosocial assessment. Screening for risk factors to distress in cancer survivors can be done in real time and help identify at-risk survivors during their visit.

e20596 Background: Advances in the treatment of colorectal carcinoma (CRC) have contributed to an increase in long-term survivors. Despite the advances made in this cancer, there is relatively litt...

112 Background: The Institute of Medicine noted cancer survivors’ care may be improved by providing each with a cancer survivorship care plan (CSCP). Recently, numerous versions of CSCPs have emerged; however, evidence-based processes to evaluate their use and quality in providing personalized survivorship care have yet to be implemented. Here, we describe our efforts to use the approach recommended by the American Society of Clinical Oncology (ASCO) Quality Oncology Practice Initiative (QOPI) to track and report the compliance rate for using electronic CSCPs in our survivorship clinics. Methods: The criteria used to conduct our audit evolved from the QOPI template, which included selection of survivors seen in 7 different out-patient survivorship clinics within a specific 6-month period, identification of denominators and numerators unique to each clinic, and determination of the number of records to audit based on the number of full-time providers in each clinic. Next, we established the target condition, method(s) used for data collection, appropriate measures, and other criteria used in the QOPI. All data were obtained from our CSCPs’ mined data, institutional electronic medical records, and scheduling systems. Results: From December 1, 2011, to May 31, 2012, we conducted an electronic medical records audit to determine the compliance rate for issuing survivorship care plans in 7 clinics. The survivorship clinics included breast, colorectal, endocrine (thyroid), genitourinary, gynecology, head/neck, and melanoma. A total of 3,274 electronic medical records were reviewed. 40 providers issued a total of 2,761 electronic CSCPs within 30 days of the arrived appointment. The compliance rate per clinic ranged from 64.5% to 94.7% (X=84.5%). Conclusions: We found the QOPI process to be user-friendly and applicable to our compliance monitoring effort. All data were extracted from electronic tools, thus ensuring the processes used were reliable, reproducible, and reasonably consistent across clinics. Further examination is warranted to determine characteristics of clinics with high- vs. low-compliance rates and their impact on survivors’ outcomes as related to specific CSCP recommendations.

e16594 Background: The aim of this study is to define the content domain for a patient-reported outcome (PRO) measure of gastrointestinal stromal tumor (GIST) symptom burden. Symptom burden, defined as the combined impact of symptoms and treatment on daily functioning, can be an effective endpoint in clinical trials to establish treatment benefits. Methods: This is Part 1 of a study to develop a PRO GIST symptom-burden measure. Twenty patients with GIST, recruited from a clinic at MD Anderson Cancer Center, described symptoms over their disease courses in single qualitative interviews. After the interviews, patients reported symptoms experienced in the last 24 hours on the core MD Anderson Symptom Inventory (MDASI) to provide context for the analysis. Content analysis was used to identify symptoms and define content domain. Results: Mean patient age was 57.9 (standard deviation [SD] = 13.1) years, 55% were male, 40% were employed, 85% were receiving tyrosine kinase inhibitor therapy, 25% had surgery withi...