bluuebunny/crossref_metadata_2025_split huggingface dataset:
Incremental benefit of interdisciplinary care in resource identification in an adolescent and young adult (AYA) oncology care model.
Authors: Parkes Amanda Marie , Lee-Miller Cathy 
Published: September 2021

228 Background: Conventional health care models inadequately address the complex needs of adolescents and young adults (AYAs, defined as patients aged 15-39) with cancer, thus necessitating AYA programs. While grounded in the integration of medical and psychosocial care, the best AYA care model has not been identified. We sought to evaluate the comparative impact of one-on-one AYA clinic visits versus interdisciplinary team care on AYA-specific resource identification. Methods: We identified patients seen at the University of Wisconsin (UW) AYA Oncology program between 1/21/2021-5/13/2021. Patients in this program have a one-on-one clinic visit with an AYA physician followed four days later by case presentation at an AYA interdisciplinary team (IDT) meeting. We conducted retrospective chart review to evaluate novel resources identified by the AYA IDT meeting versus those previously identified during the one-on-one AYA clinic visit. Resources identified had to be novel from those already used by or identified for the patient. Results: We identified 32 patients seen by the UW AYA Oncology program. Prior to their AYA clinic visit, patients saw an average of 2.0 AYA-specific services (range 0-6, defined as those services listed in table). As seen in table, an average of 2.8 novel AYA-specific resources were identified for each patient (range 0-5) during the one-on-one AYA clinic visit. Following the AYA IDT meeting, additional novel resources were identified in 100% of patients, with an average of 2.6 additional resources identified per patient (range 1-7). Considering all resources identified by the AYA Oncology program (clinic visit + IDT), an average of 5.4 novel resources were identified per patient (range 2-10). AYA-Specific Resource Identification (n=32). Conclusions: Supporting the importance of dedicated AYA care models, we found that all patients in our study had novel AYA-specific resources identified by the UW AYA Oncology program. Resources identified by the physician-led one-on-one AYA clinic visit were not comprehensive as additional resources were identified for each patient at the AYA IDT meeting only four days later. These objective data support the critical importance of AYA interdisciplinary care as well as the use of an AYA IDT meeting model as a method to include interdisciplinary team care in AYA programs despite possible resource constraints.[Table: see text]
Examining patient specific factors associated with inpatient hospital length of stay for solid tumor oncology patients from low socioeconomic communities in Milwaukee, WI.
Authors: Kamaraju Sailaja , Canales Bethany , Wright Tamiah , Charlson John A. , Szabo Aniko , Lee Donggwan , Wetzel Thomas , Richardson Kevin , Jensik Kathleen , Power Steve , Campbell Grace 
Published: September 2021

232 Background: In a retrospective analysis at the Medical College of Wisconsin’s Cancer Center, we identified longer inpatient length of stay (LOS) for patients residing in low-socioeconomic (SES) ZIP Codes in Milwaukee County compared to their high-SES counterparts in 2020 (7.3 days compared to 7.1 days). Under the auspices of American Society of Clinical Oncology’ Quality Training Program (QTP) initiative, this study examined specific factors related to prolonged LOS for solid tumor oncology patients. Methods: This analysis includes initial CY20 LOS medical record data for select patient service areas. Supplemental data includes disease registry data, diagnostic data, and SES data determined by patient ZIP Code. We identified patients 18 years and older with a diagnosis of common oncologic malignancies from 1/1/2020-12/31/2020 (breast, gastrointestinal (GI), genitourinary (GU), gynecologic (GYN), head and neck (H&N), and lung cancers). Poisson regression models with robust standard errors were used to compare the LOS index (LOSi) between groups of patients based on race, SES group, primary payer, and BMI. Results: A total of 1,637 patients with solid tumor diagnosis admitted to hematology and oncology units were identified. The LOSi did not vary significantly by race (range 0.95 – 1.07, p = 0.40) or primary payer (range 0.99 – 1.04, p = 0.59), but lower SES groups tended to have longer LOSi, with LOSi ratio above 1 compared to high SES (low SES: 1.16, p = 0.2; medium-low SES: 1.24, p = 0.06). Among patients with breast cancer diagnosis, Black (LOSi = 1.24, p = 0.01), medium-low SES (LOSi = 1.46, p = 0.02), Medicaid (LOSi = 1.40, p = 0.00), underweight (LOSi = 1.66, p = 0.00), and overweight (LOSi = 1.23, p = 0.01) patients had slightly longer LOSi, with LOSi ratio above 1. Among patients with H&N cancer diagnosis, Black patients (LOSi = 0.77, p = 0.02) had slightly shorter LOSi, with LOSi ratio below 1. The LOSi did not vary significantly by other factors for patients with H&N cancer diagnosis or the other common oncologic malignancies evaluated. Conclusions: This study shows how patient-specific factors such as race, SES, primary payer, and BMI contribute to inpatient LOS. Healthcare systems may benefit by addressing patient-specific barriers and factors such as body mass index, SES and SDH, to reduce hospital LOS.
Improving time to molecular testing results in patients with newly diagnosed, metastatic non-small cell lung cancer (NSCLC).
Authors: Ossowski Stephanie , Neeman Elad , Borden Charles , Lin Amy Ying Ju , Liu Raymond 
Published: September 2021

244 Background: Next generation sequencing (NGS) is a crucial component of evaluation of newly diagnosed patients with metastatic non-small cell lung cancer (NSCLC) to determine appropriate first line treatment. Delays in NGS can lead to psychologic distress for patients and can affect choices in first line therapy, especially for patients with underlying targetable mutations. While more data is needed to benchmark turnaround time for NGS results, guidelines and expert consensus suggest time from diagnosis to treatment should be 15 days and turnaround time for genomic testing 10-14 days. This study was aimed at reducing time to NGS results in a large integrated health care system. Methods: Through the ASCO Quality Training Program, we reviewed electronic medical records of 25 patients with newly diagnosed, untreated metastatic NSCLC from 12/2018 to 9/2020 and determined number of days from pathological diagnosis to NGS results. We reviewed process maps for oncology, pathology, the internal data management division, and a genomic testing company to determine factors leading to significant preventable delays. Since 11/2020, we created an automated weekly report using CoPath to identify new pathological diagnoses of potential metastatic NSCLC. The oncology department reviewed these cases weekly and NGS orders were placed for patients with metastatic NSCLC. Eleven additional patients with newly diagnosed metastatic NSCLC were included in the prospective cohort. Results: Demographic characteristics are noted in Table. Our intervention reduced median time from pathological diagnosis to NGS results from 24 to 19 days. Median time from biopsy results to NGS order was reduced from 7 to 1 day. Time from specimen being sent from pathology to NGS vendor was a median of 6 days in both cohorts. Total time from pathological diagnosis to appropriate treatment was reduced from a median of 33 to 25 days. Conclusions: Delays in time to NGS results can be reduced by improved communication between departments and simple, automated interventions to ensure results are efficiently released to an oncologist. Additional Plan-Do-Study-Act cycles are currently being developed to further reduce time from biopsy results to NGS results. [Table: see text]
Safety and efficacy of COVID-19 vaccination in patients receiving systemic anticancer therapy.
Authors: Khan Mahir , Nguyen Ryan Huu-Tuan , Love James , Krule Alexander , Weinfeld Michael , Abraham Kristy , Eisenberg Amy , Horowitz Joseph , Raju Prianka , Ramadan Amina , VanOverloop Jack , Jain Shikha 
Published: September 2021

245 Background: Patients with cancer who have been treated with systemic anticancer therapy are at increased risk of morbidity and mortality from COVID-19 and have been considered a high-priority group for COVID-19 vaccination in the United States. There is limited guidance and data on the appropriate timing of COVID-19 vaccination relative to receipt of systemic anticancer therapy. Methods: We queried the electronic medical record at the University of Illinois Hospital for patients with gastrointestinal, breast, lung, genitourinary, and head and neck tumors who had received intravenous systemic anticancer therapy between January 1, 2021 and May 25, 2021. Baseline variables were obtained as well as details of cancer treatment, vaccination timing relative to cancer treatment, and clinical outcomes. Results: A total of 274 patients received intravenous systemic anticancer therapy during the study period, of which 161 (58.8%) received at least one vaccine dose, and 138 (42.7%) were fully vaccinated. Of the 122 patients who received cancer treatment within 30 days of any vaccine dose, the median age was 64, and 72 (59%) were female gender. Race distribution was 50% Black, 15.6% White, 3.3% Asian; ethnicity was 24.6% Hispanic and 73% not-Hispanic. Treatment regimens consisted of 37.7% chemotherapy, 25.4% immunotherapy, 27.9% combination therapy, and 9.0% targeted therapy. For those who received anticancer therapy within 30 days of a vaccine, median time between any vaccination and treatment was 10 days (range 0-29 days). For those who had at least 60 days of follow-up after first vaccination, all-cause hospitalization rate was 22.4% (23/106). There was no statistical difference in all-cause 60-day hospitalization rate between those who received vaccination within 5 days of anticancer therapy versus those who received it between 6 and 30 days from anticancer therapy (14.3% vs 28.1%, p = 0.1). One patient (0.8%) developed a COVID-19 illness after any vaccine and did not require hospitalization. Conclusions: We observed safe and efficacious COVID-19 vaccination of patients with cancer receiving systemic IV anticancer therapy. COVID-19 infection after vaccination was rare, with no cases requiring hospitalization for COVID-19 illness post-vaccination in this cohort. All-cause hospitalization rates were similar among patients who received a vaccine within or after 5 days of receiving systemic anticancer therapy, suggesting vaccination side effect tolerability. Further quality improvement studies are needed on interventions to increase vaccination rates in this vulnerable population.
Recovery of a quality improvement project during the COVID pandemic.
Authors: Powis Melanie Lynn , Macedo Alyssa , Krzyzanowska Monika K. , Kukreti Vishal , Ma Lucy Xiaolu , Hack Saidah , Dara Celina 
Published: September 2021

246 Background: Prior to COVID we undertook a QI project with the aim improving the documentation of a best possible medication history (BPMH) or medication reconciliation (MedRec) for patients initiating systemic therapy (ST) in ambulatory oncology, where care spans multiple providers and patients may be at increased risk of adverse drug events. While initial improvements were realized (16.7% and 3.9% increases for BPMH and MedRec, respectively), completion rates returned to baseline following the start of the COVID pandemic. Methods: Guided by the four-phase Quality Implementation Framework we sought to recover implementation of MedRec. We initially undertook a purposeful re-examination of the MedRec process (Phase 1) to identify barriers to conducting MedRec during COVID. This guided the tailored selection of Expert Recommendations for Implementing Change (ERIC) implementation strategies utilized during the successive phase of the project. During each phase the proportion of patients with documented BPMH or MedRec within 30 days of initiating ST out of those eligible was calculated. Results: Major barriers to conducting MedRec during COVID included reduced resources (time, human resources and physical resources), loss of dedicated staff, and change in workflow/ clinical models brought on by the introduction of virtual care. This informed our strategy to improve capacity to conduct MedRec (Phase 2) through the development and distribution of educational materials, revisions of professional roles, and creation of a new dedicated clinical team consisting of existing modified duty nurses to conduct MedRec. To support ongoing implementation (Phase 3), additional implementation strategies included the staged implementation scale-up, conduct of educational meetings/ outreach visits, facilitation, and provision of clinical supervision. The impact of each phase of implementation on BPMH and MedRec completion rates is summarized in Table. Conclusions: Recovery of a quality improvement intervention during COVID was realized through the utilization of a structured, implementation process model approach to identify and address barriers to implementation. Future work will focus on improvement of MedRec completion rates by clinicians, and on embedding processes into practice (Phase 4) to support sustainability of the intervention.[Table: see text]
Optimizing active surveillance for low-risk prostate cancer: Characterizing provider and patient perspectives.
Authors: Radhakrishnan Archana , Subramanian Lalita , Rankin Aaron , Skolarus Ted A. , Wittmann Daniela , Hawley Sarah T. , Fetters Michael 
Published: September 2021

250 Background: The number of men on active surveillance (AS) for low-risk prostate cancer is rapidly increasing. While AS requires routine clinical exams, labs, imaging, and prostate biopsies, many men do not receive all recommended components. Understanding the perspectives of key stakeholders regarding recommended surveillance is critical to ensuring the optimization of AS as a management strategy. Methods: We conducted in-depth, semi-structured, virtual interviews with a purposive sample of 15 men with low-risk prostate cancer who were on AS as their primary management strategy and their partners, and 15 urologists and 19 primary care providers (PCPs) with experience in AS management between June 2020 and March 2021. We used the Theoretical Domains Framework (TDF), an implementation science framework developed to understand determinants of behaviors and to inform the design of interventions, to guide our interview guide. Questions assessed knowledge, barriers and facilitators, and preferences for provider roles in AS management. Interviews were recorded, transcribed, and deductively coded into TDF domains and constructs. Three independent coders iteratively developed and used a shared coding framework. Participant recruitment continued until data saturation by group. Results: Our study included 15 men (on AS between 1-16 years), 5 partners, 15 urologists (3 female, 5 in private practice, 3 in academic medical centers), and 19 PCPs (9 female, 4 in community practices, 15 in academic medical centers). The TDF domain of “knowledge” and the construct, “barriers and facilitators” were most commonly reported as factors impacting receipt of recommended surveillance across all groups. While urologists were most knowledgeable about AS, PCPs noted limitations in understanding for whom AS is recommended, and what it entails. Patients who had made an effort to research or learn about AS found that this knowledge enabled them to be proactive about receiving all recommended components. Urologists and patients noted several common procedural barriers to receiving recommended surveillance, including pain with repeated biopsies, and becoming lost to follow-up. Patients and PCPs were uncertain about what tests were needed and when. Urologists were concerned about PCP knowledge while PCPs described insufficient communication from urologists as barriers to shared care. Procedural facilitators included electronic medical records (EMR) to remind providers and patients of frequency and timing of tests. Conclusions: Key opportunities for optimizing AS include improving patient and PCP knowledge about the components and delivery of AS, facilitating communication between providers, and leveraging EMR to ensure those on AS are followed. The development of an intervention that combines several of these components will be critical to ensuring men on AS receive the recommended surveillance.
Piloting the REDUCE score to decrease acute care utilization.
Authors: Csik Valerie Pracilio , Li Michael , Waldman Lauren , Worster Brooke , Binder Adam F , Handley Nathan 
Published: September 2021

252 Background: Emergency department visits and hospitalizations are common in patients with cancer, with nearly three quarters of patients with advanced disease hospitalized at least once in the year after their diagnosis. Efforts to prospectively identify patients at highest risk for this acute care utilization (ACU) are needed. While many risk scoring systems have been developed for this purpose, few have been effectively integrated into clinical practice. We piloted a prospective risk assessment tool using a quality improvement framework. Methods: We utilized our previously published REDUCE score (Reducing ED Utilization in the Cancer Experience) to pilot clinical interventions to reduce ACU using PDSA cycles. Cycle 1 included a chart review and targeted outreach by a nurse navigator to high risk patients identified by REDUCE. Outreach resulted in communication of patient needs to the care team, which may or may not have resulted in additional interventions. Cycle 2 involved initial identification by REDUCE followed by further assessment with a distress screening. Those who were high risk and had high distress (score ≥4) were discussed by an interdisciplinary team (including supportive medicine physicians, social work, nurses, nurse practitioners) to determine an appropriate intervention. Results: Of the patients in Cycle 1 (N = 138), 26.1% had ACU after outreach by a nurse navigator, while in Cycle 2 (N = 169) 7.1% had ACU after the intervention determined by the interdisciplinary team. The average distress score among all patients in Cycle 2 was 6.0 and the REDUCE score was 2.87, while the subset of patients who experienced ACU had an average distress score of 6.4 and a REDUCE score of 3.22. Conclusions: The REDUCE score may be a valuable tool to assist in identifying patients at risk for ACU. We found that combining the risk score with a biopsychosocial screening tool and multidisciplinary team discussion may prove more valuable than the risk score alone, with Cycle 2 findings suggesting that there is a directional correlation between REDUCE score and distress screening results. More work is needed to understand the relative impact of the REDUCE score and the biopsychosocial screening and team discussion on decreasing ACU.
A quality improvement initiative to increase screening for financial coverage for breast cancer patients to decrease financial toxicity.
Authors: John Preethi , Hodges Mary P. , Shah Gaurav , Dickerson Umber , Dreadin-Pulliam Julie , Smith Julie , Hendricks Carolyn B. , Mohamed Ashraf Mahmoud 
Published: September 2021

259 Background: In April 2021, it was found that 35% of our breast cancer patients seen in the breast surgery and medical oncology clinics had no financial coverage leading to significant financial toxicity at Parkland Memorial Hospital, a safety net hospital for Dallas county in Texas. In addition, only 8% of all our breast cancer patients were financially screened in April 2021. We aimed to increase pre-visit phone calls to financially screen patients within a week of their subsequent visit with a provider from a baseline rate of 8% to 20% for all breast cancer patients in hopes of capturing more unfunded patients and providing appropriate resources. Methods: We used the Institute for Health Improvement (IHI) model as our quality improvement framework. Based on our fish bone and pareto chart analysis, it was discovered that the lack of consistent financial screening was likely due to lack of standardized training across our ancillary staff, lack of standardized processes for financial screening, and lack of education of both providers and patients regarding the financial coverage process. To address these issues, we created a standardized process of financial screening called “pre-visit planning (PVP)” involving a telephone call by our schedulers to breast oncology patients within 1 week of their next visit. Screening included checking financial application status and educating patients on methods of application submission including epic my-chart enrollment. Screening also included checking financial coverage status and if unfunded, a referral to a financial counselor was made. Formal training of staff was performed with mock trial phone calls. We initiated implementation in the breast surgery clinic initially with plans to expand to the medical oncology clinic. Results: At baseline, in April 2021, 300 patients were seen in the breast surgery clinic of which 19 were financially screened (6.3%). Implementation of PVP for all patients in the breast surgery clinic began in May 2021 with data representing 2 weeks of financial screening by our staff. Total number of patients seen over the span of 2 weeks in the breast surgery clinic was 165 of which 59 were financially screened making up 36% of patients. In addition, 8 patients in the breast surgery clinic were screened by a financial counselor increasing the rate of financial screening to 40.6%. Conclusions: We successfully implemented PVP to better assist our patients in several ways including updating their financial coverage, educating them on the financial process, as well as referring them to a financial counselor for additional aid. Increased follow up time is needed to assess the downstream effects of PVP such as increase in financial counselor visits and decrease in unfunded patients.