bluuebunny/crossref_metadata_2025_split huggingface dataset:
The optimal living and wellness program: Piloting a novel survivorship care model.
Authors: Corcoran Stacie , Russell John , Smith Andrea , Kelly Bridget , Clayton Jill , Stein Bennet , Keenan Kathleen , Robson Mark E. , Iyengar Neil M. 
Published: May 2020

e14003 Background: Multiple national agencies define cancer survivorship as beginning at the time of cancer diagnosis. However, traditional care models deliver “survivorship care” months or years after diagnosis, which can lead to disruption in care and “transition anxiety”. We hypothesized that an approach centered around wellbeing could be applied across the cancer continuum (starting at diagnosis) and serve as a novel survivorship care model. Methods: We developed the Optimal Living and Wellness Program, a multilevel intervention with 3 key components: 1) a centralized model that provides coordinated multidisciplinary care; 2) an individualized Wellness Plan (WP); and 3) enrollment at the time of cancer diagnosis in order to mitigate the experience of post-treatment transition. Participants complete a digital wellness questionnaire (WQ) prior to the first medical oncology consult, receive a validated algorithm-based WP reviewed by a Wellness Coordinator, and meet with a Wellness Advanced Practice Provider (WAPP) via tele-medicine. The WP consists of individualized education and referrals to indicated supportive services (e.g., nutrition, exercise physiology, financial counseling, integrative medicine). The WAPP will ultimately assume care of the patient in the post-treatment (“survivorship”) phase. We piloted this approach in patients diagnosed with breast cancer beginning in November 2019. The primary outcome is feasibility defined by completion of the WQ. Secondary outcomes include participation in the WAPP visits, attendance at referral appointments, and quality of life (QOL). Results: As of January 31, 2020, a total of 39 eligible patients with newly diagnosed breast cancer were approached. Of these, 36 (92%) have completed the WQ. All 36 participants received a WP with indicated supportive referrals and educational resources. Initial WAPP tele-visits will begin in May 2020. Qualitative data regarding patient experience and QOL will be obtained via focused interviews and feedback will be categorized in thematic domains. Conclusions: In this pilot, the majority of patients with newly diagnosed breast cancer completed a WQ in advance of their initial medical oncology visit, indicating preliminary feasibility. Patient enrollment is ongoing, and updated data including additional feasibility metrics and QOL will be presented. Earlier patient engagement and incorporation of wellness and supportive services from time of diagnosis may significantly improve the transition to post-treatment care.
Utilizing an advanced practice provider (APP) led acute care clinic to improve access to high quality, patient centered, cost effective cancer care.
Authors: Spradlin Megan , Bowden Kasey , Zabilla Sarena , Kessler Elizabeth R 
Published: May 2020

e14007 Background: The medical oncology patient population is at high risk for adverse effects and complications related to anti-cancer treatments. The cost of oncology care is projected to reach almost $160 billion in 2020. The ongoing cost trajectory has placed a significant financial burden on patients, families, and society as a whole. The Centers for Medicare and Medicaid Service (CMS) has developed a new payment and delivery model that identifies potentially preventable conditions for ED visits/rehospitalizations among patients that are receiving anti-cancer therapies. Proposed CMS changes have created increased urgency around avoiding preventable ED visits/rehospitalizations. In response to the need for high quality, patient centered, cost effective care, we have established an APP-led acute care clinic that specializes in oncology care. Methods: The Clinical Assessment and Rapid Evaluation (CARE) Clinic offers acute care and symptom management catered to the oncology population. Patients are able to receive lab and imaging work up in addition to intervention with IV fluids, anti-emetics, opioids, electrolytes or antibiotics, as well as blood/platelets as warranted. To assess patient satisfaction, we created an anonymous four question survey delivered to CARE clinic patients over a two month period. Results: Seventy five surveys were collected. Pain and nausea were the leading reasons for encounters. 91% of patients rated their care as excellent, while 9% of patients rated their care as good. 33% of patients reported they would have been seen in the ED if the CARE Clinic was not available. Conclusions: The CARE Clinic represents a unique, one of the first of its kind, acute care and symptom management entity that utilizes an APP model to provide high quality care at a low cost. More research is needed to identify if this model can create statistically significant reduction in ED visits and rehospitalizations, however current data suggests that patients are highly satisfied with this unique method of care delivery. Sources Handley NR, Schuchter LM, Bekelman JE. Best Practices for Reducing Unplanned Acute Care for Patients With Cancer. Journal of Oncology Practice. 2018;14(5):306-313. doi:10.1200/jop.17.00081.
An optimal care coordination model for Medicaid patients with lung cancer: Lessons learned from the beta testing phase of a multisite initiative in the United States.
Authors: Smeltzer Matthew , Boehmer Leigh , Kramar Amanda , Asfeldt Thomas , Faris Nicholas Ryan , Ray Meredith , Lathan Christopher S. , Osarogiagbon Raymond U. 
Published: May 2020

e14010 Background: Medicaid patients with lung cancer often have less favorable outcomes than non-Medicaid patients, which, given provision of care is typically comparable, may be due to socioeconomic disparities between these populations. In 2016, the Association of Community Cancer Centers (ACCC) embarked on a 3-year initiative to develop and test the Optimal Care Coordination Model (OCCM) to improve care coordination for Medicaid patients with lung cancer. A framework of 13 independent care delivery areas, spanning access to care to survivorship and supportive care, aids cancer programs in identifying barriers to access and use of their care, with a focus on Medicaid patients, and therefore enables optimal care coordination. Methods: Seven community-based healthcare systems in 6 U.S. states were selected as OCCM beta testing sites and then supported by the ACCC via site visits and biweekly calls. Sites self-assessed the quality of their care in selected OCCM areas to identify relevant quality improvement projects and improve understanding of needs specific to Medicaid patients. Results: Total patient enrollment across all sites was 926 (257 Medicaid; 669 non-Medicaid). Each site selected 1–2 priority OCCM areas, including patient access to care, prospective multidisciplinary case planning, or tobacco cessation, for projects. Enhanced collaboration, improved programming (e.g., patient navigation and formation of lung health leadership team), and organic programmatic changes due to the OCCM work were identified as successes. Site-specific challenges included inadequate staffing at project start and lack of centralized data collection and coordination. The importance of lung cancer–dedicated navigation, multidisciplinary conference use for treatment planning, and understanding needs specific to Medicaid patients were key transferable lessons. Examples of institutional support received by sites during the project included opportunities for staff training and leadership commitment from other hospital departments to assist with care delivery improvements. Use of the existing OCCM framework; increased staffing, particularly for lung cancer navigation; and expanded community outreach were identified in the sustainability plans. Conclusions: OCCM beta testing helped sites self-assess care delivery and identify areas for improvement. Ultimately, it was apparent that Medicaid patients need to be treated differently to obtain equity of outcomes with non-Medicaid patients.
Provider and patient insights into the cancer care journey.
Authors: McLarty Sarah , Johnson Kjel , Francis Ann , Johlie Melissa , Sawicki Christine , Johnson Kjel Andrew 
Published: May 2020

e14019 Background: Research regarding primary care physicians’ (PCPs) involvement in the cancer treatment journey is limited. When a patient is first diagnosed with cancer, navigating healthcare can be confusing without the proper guidance. We conducted this study to understand a PCP’s involvement in the cancer care journey and how to optimize a patient’s journey through healthcare once diagnosed with cancer. Methods: We conducted a cross-sectional survey of 53 PCPs who have practiced over two years and have had at least one patient referred to an oncologist in the past year. We asked PCPs their method of oncologist referral, utilization of an oncologist selection tool that directs patients to high-quality and low-cost oncologists, and when an advanced directive should be established. We conducted a second survey with 112 current and previous cancer patients over the age of 25 who had received chemotherapy. We asked participants to reflect upon their oncologist’s referral, utilization of an oncologist selection tool that identifies high-quality and low-cost providers, participation in clinical trials, and guidance in creating an advanced directive during their cancer care journey. We conducted both surveys through online survey panels in June 2019. Results: PCPs tend to refer patients to oncologists that are part of their health system (67.9%) and who they know through networking (39.6%). While the majority of PCPs (79.2%) were not currently utilizing an oncology selection tool, the majority (77.3%) expressed a willingness to use such a tool for their newly diagnosed cancer patients. The majority of PCPs (69.8%) believe that cancer diagnosis is the best time to talk about establishing an advance directive, which should be initiated by the patient’s PCP (64.2%) or oncologist (56.6%). Patients ranked a PCP referral (52.7%) as “very important” when selecting an oncologist. One-third of patients used an oncology selection tool; 65.2% responded that a tool to understand true quality and cost of an oncologist would be “somewhat important” or “very important.” Most (71.4%) patients reported that it would be “somewhat important” or “very important” to participate in a clinical trial even though none participated in one. Most patients (54.5%) had an advance directive, although most (54.1%) had completed one before their cancer diagnosis. Conclusions: These results present a compelling rationale for developing a data-driven oncologist selection tool, optimize clinical trial involvement and expand the portion of patients who have an advanced directive at the start of their cancer care.
Patterns in detection of recurrence among patients treated for breast cancer.
Authors: Saltbæk Lena , Horsbøll Trine Allerslev , Offersen Birgitte Vrou , Andersson Michael , Friberg Anne Sofie , Skriver Signe Korsgaard , Bidstrup Pernille , Overgaard Jens , Johansen Christoffer , Dalton Susanne Oksbjerg 
Published: May 2020

e14020 Background: Follow-up programs for breast cancer should according to ASCO and ESMO consist of regular visits including anamnestic screening for symptoms of recurrence and physical examination for ten years in addition to regular mammography. Recently, the Danish guideline for follow-up after early breast cancer was revised. Today most patients are offered open access to an outpatient clinic, but no scheduled visits following the first year after surgery. This strategy has been studied in regards to psychological and health related quality of life outcomes, but not in regards to detection of recurrence and survival. The aim of this study was to quantify the recurrences detected at scheduled outpatient visits in Denmark before the implementation of revised follow-up guidelines. Furthermore, we aimed to assess whether the duration of symptoms prior to recurrence detection differed depending on type of visit when recurrence was detected. Methods: We conducted a cross-sectional study among 310 patients with recurrent breast cancer. Through medical records, we retrieved information on type of visit when recurrence was detected, localization of recurrence, symptoms reported, and duration of symptoms. Tumor characteristics were obtained from the Danish Breast Cancer Group database. Results: Among the 310 breast cancer recurrences, more than half were distant (59%), 26% were loco-regional, and 15% loco-regional and distant. Among the 199 patients still in outpatient follow-up at time of recurrence, recurrence was detected at a scheduled outpatient visit (21%), at a patient-requested extra outpatient visit (15%), by the general practitioner or other specialist (47%), or on a scheduled mammography (11%). Among patients with recurrence detected at a scheduled outpatient visit, the majority (88%) reported symptoms related to the recurrence. Patients who waited for the scheduled outpatient visit despite symptoms had a markedly longer duration of symptoms (median 21 weeks) prior to detection of recurrence than patients who requested an extra visit (median 8 weeks). Conclusions: One-fifth of recurrences among patients attending outpatient follow-up were detected at scheduled outpatient visits. The majority was symptomatic, but the patients had not altered their scheduled appointment. Whether recurrences like these will be detected in follow-up without scheduled visits is unknown. Some recurrences may be detected earlier, if patients can be educated to react on relevant symptoms, but some recurrences may be detected with further delay. Thus, more research in this area is needed.
A dedicated lung cancer immunotherapy outpatient clinic: The first experience in China.
Authors: Xu Chongrui , Tu Hai-Yan , Sun Yueli , Li Yang-Si , Xu Bing-Fei , Wang Bin-Chao , Chen Hua-Jun , Wang Zhen , Zhou Qing , Yang Jin-Ji , Li Chanchan , Wu Yi-Long 
Published: May 2020

e14022 Background: Immunotherapy (IO) has become the fourth pillar of clinical cancer care. There is an increasing need to the treatment of more patients for a longer period with acceptable cost and risk. We here described the development and operationalization of the first dedicated lung cancer IO outpatient clinic in China using an iterative process. Methods: The clinic is staffed by one attending physician, one medical oncologist, several nurses, and medical assistants along with a dedicated care coordinator. Patients (pts) were scheduled to visit every Thursday morning for the treatment and then visit every 2-4 weeks as per IO regimen. Written informed consent were obtained after well-informing about the IO and possible side-effects, and administration of self-purchased drugs. The minimum workup including routine general physical examinations or tests along with tests specific for IO, and toxicities was undertaken during the clinic visits. Treatments response, adverse events (AE), quality of life (QOL), and patient reported outcomes were measured/reviewed by the oncologist accordingly (CTCAE 5.0, RECIST 1.1, and iRECIST criteria). Pts can report their symptoms and be noticed/alerted during the clinic visits or between visits via electronic interfaces. All these data were integrated into the EMR database (LinkDoc) and valued as continuous documentation to support clinical decisions making, so as to improve clinical symptom management and overall QOL. Also, the pts were coached about possible symptoms and corresponding self-monitoring and management strategies. A standardized workflow was established, as well as staff education and training programs. Results: During May to December 2019, 99 pts presented at our IO clinic, and 79 received IO therapy (46 pembrolizumab, 32 nivolumab, and 1 camrelizumab). Pts on average received 3 cycles (Total: 280; range 1-11 cycles). AE were noted in 57 (72.2%) pts. All pts were well. Conclusions: This study demonstrates that our dedicated lung cancer IO clinic worked well. Therapeutic alliance of IO clinics has already been established with primarily 15 hospitals participated in. The design process and standardized workflow components will be further expanded to other cancers or conditions.
Single-institutional analysis of clinicopathologic features and overall survival (OS) in melanoma patients (pts).
Authors: Wang Ding , Wang Jonathan , Krajenta Richard , Zhu Liping 
Published: May 2020

e14023 Background: Melanoma is ranked 5th commonest malignancy in United States and SEER has projected 3,290 new skin melanoma cases in Michigan in 2020. Diagnosis of recurrent & metastatic melanoma has associated with poor prognosis and survival. Henry Ford Cancer Institute (HFCI) is a tertiary cancer care facility serves cancer patients from communities throughout metropolitan Detroit tri-county areas where a higher melanoma presentation (1.56%) in black pts than this group at national database (0.6%). A subgroup of white Michiganders travel to Southern sunshine states in winter months known as “snowbirds” have contributed to melanoma incidences in Michigan. We aim to review our institute tumor registry data to analyze the clinicopathological features, care pattern and correlated survival outcomes. Methods: We have identified adult melanoma pts through institute tumor registry between 2007 – 2017, who had demographics, initial diagnosis, recurrence, then death or last follow-up for overall survival (OS) outcome. Data were analyzed using IBM SPSS, R-statistical and log-rank test. Results: Of 1327 eligible pts, median age was 63, and 874 (65.86%) pts were invasive at onset diagnosis. 1298 (97.81%) pts were white, 23 (1.73%) pts were black. Slightly more females (55.54%) over males and overall 301 deaths (22.68%) were observed. 1277 pts with cutaneous melanoma had better 5- and 10-year (yr) OS at 78.14%, and 68.32% compared to 50 (3.77%) non-cutaneous pts at 13.31% and 8.87%, respectively. Black pts carried a poor 5-yr OS at 34.68% vs white at 76.4%. 116 (17.9%) pts presented with recurrences, had 5-yr OS at 34.58%. Of 121 (9.1%) pts who never had been disease-free, showed worse 5-yr OS at 15.87%, with trend of improvement since FDA-approval of immune checkpoint inhibitor therapies. Conclusions: We have analyzed our melanoma care pattern, experience and survival outcomes at 5-yr and/or 10-yr from a tertiary community cancer care facility. We have assessed our current practice benchmarks with plan to improve our care delivery by having built a multidisciplinary team, and launched Melanoma & Skin Cancer Clinical Care Pathway through Tumor Board to improve care access, to decrease care disparity, then to standardize quality of care including encouraging clinical trial enrollments which will enhance quality of melanoma care and survival outcomes of advanced and metastatic cases.
Optimizing infusion wait time: Redesigning medication order verification/approval at a comprehensive cancer center.
Authors: Hashemi-Sadraei Neda , Dayao Zoneddy R. , Sasankan Shenthol , Cox Andrea , Peacock Sandra , Abernathy Janet , Kittson Ronald , Tawfik Bernard , Crozier Nick , Lauer Richard C. 
Published: May 2020

e14042 Background: Nationwide, many cancer centers experience challenges with infusion center efficiency while maintaining high safety standards. Many factors contribute to long wait times for patients on the day of their infusion appointments. At University of New Mexico Comprehensive Cancer Center (UNMCCC), a contributing factor is the delays in verification or approval of medications. We conducted a project to improve order verification/approval workflow within a Plan-Do-Study-Act (PDSA) framework with the objective to decrease the infusion wait time. Methods: A multidisciplinary working group was formed consisting of the infusion floor physician lead, nurse lead, pharmacy lead, and analytics and process improvement leads. Upon exploring the infusion workflow database, disruptions in verification or approval of orders had a large impact on wait times. Order verification workflow was broken down into 3 steps: 1) physician assessment of patient and approval of orders, 2) infusion nurse assessment of patient, 3) pharmacist verification of order. Beginning Feb 2019, the following interventions were implemented in each section: 1) once patient was assessed by physician and orders approved, the patient was marked as “ready-to-treat”. 2) Pharmacist verified the order once “ready-to-treat” was communicated and initiated preparation of medications prior to arrival of patient to the infusion suit. 3) Infusion nurse assessment occurred once patient was seated on infusion chair. 4) Physicians were encouraged to pre-approve selected injections by the morning of patient appointment. Results: Prospective wait time was gathered for May 2019 using the real-time data available in the electronic medical record. Wait times were analyzed for patients receiving chemotherapy or flat dose injections. By marking appropriate patients “ready-to-treat” and moving pharmacist verification prior to infusion nurse assessment, there was an immediate decrease in wait time from 79 to 60 min. Selected injections which did not require mixing were pre-approved by the physician and stored in the medication dispensing system (Pyxis). This resulted in decrease in the injection wait time by 8.5 minutes, without wasting of drugs. Conclusions: Redesigning the medication order verification/approval workflow resulted in reduced wait times for patients receiving infusions or injections. We aim to further refine our PDSA cycles and ensure sustainability of change.