bluuebunny/crossref_metadata_2025_split huggingface dataset:
Enhancing precision medicine testing process in a breast cancer population of a community oncology practice: Use of oncology patient navigators (OPN) and a molecular processing team (MPT) to improve germline testing.
Authors: Cruz-Tanner Melissa , Canavan Jake , Kiley Lauren , Montes Rosemary , Ronnen Ellen A. 
Published: October 2023

559 Background: In 2021, universal germline testing was recommended to breast cancer patients. Historically, germline testing has been ordered using manual paper requisition forms or via molecular vendor portal input with no capabilities of follow-up to ensure timely results. There are few reports of how to optimize universal germ line testing; we endeavored to determine benefit of OPN and a MPT in a breast cancer population in the private practice setting. Methods: For the baseline population, using the Electronic Health Record (EHR), a report was generated to identify breast cancer patients seen that were eligible for germline testing. The patient records from the report were manually reviewed to identify germline testing completed. In the intervention arm, OPN would review provider schedules in real time to identify any newly diagnosed breast cancer pts. Concurrently the pts were offered the opportunity for germline testing along with education by providers during their visit. Certified Medical Assistants (CMAs) placed all orders via vendor portals using OPN supplied templates completed by providers. The MPT would follow orders placed to confirm specimen procurement, receipt by vendor and collaboratively resolve any delays in specimen processing, insurance challenges and test selection revisions. Tracking activities were implemented within the EHR to document all progress in testing and to quantify the volume of tests. Results: For the baseline population, between 1/1/21-3/31/21, 29 (24%) of 120 breast cancer patients received germ line testing. Post intervention, between 1/1/22-3/31/22, 70 (45%) of 155 patients had germline testing. The mean turnaround time (TAT) for germline results for the baseline population was 12 days, and 44% percent were over 11 days. In the intervention arm, the mean TAT was 10 days and 20% were over 11 days. Conclusions: Our results illustrate the early benefit of OPN and a MPT in expediting result obtainment and increasing utilization of germline testing. Enhancing cohesion with the vendors and our MPT and more automated use of the EHR will further improve utilization. Continued practice wide education of providers in the necessity of germline testing in a breast cancer population is also essential.
Results of a quality improvement program to increase complete lung cancer biomarker testing rates.
Authors: Heron Dwight Earl , Blair Jean , Francis Jawad Elias , Stoeppler-Biege Kristina , Simpson Lijo , Stapp Jeremy , Kim Joseph 
Published: October 2023

57 Background: Biomarker testing is the standard of care for patients with advanced lung adenocarcinoma, but limited tissue samples may lead to incomplete testing. Especially if quantity is not sufficient (QNS) requiring additional samples, a prolonged time-to-initiation of treatment (TTT) has been shown to negatively impact clinical outcomes. Bon Secours Mercy Health (BSMH) Youngstown, Ohio reviewed biomarker testing data and found: 1) only 41% of patients received complete biomarker testing, and 2) in the case of QNS when liquid biopsies were utilized, the time from diagnosis to results took an average of 42 days. BSMH worked in collaboration with OncoLens and Q Synthesis to address these issues and reduce the TTT. Methods: A multidisciplinary team developed a new workflow for patients diagnosed with advanced NSCLC. The pilot involved collecting both tissue and blood at the time of needle biopsy and working with a single reference lab for testing. Physicians and nurses in radiology and pulmonology were in-serviced on the new workflow. As patients were being prepared for a biopsy procedure, nurses collected two tubes of blood for liquid biopsy. After the procedure, both the tissue and blood were sent to pathology and if pathology confirmed an advanced lung adenocarcinoma diagnosis, both samples were sent to the reference lab for testing. The lab developed a new process to hold blood and test it only when the tissue was QNS. If QNS, tissue testing for PD- L1 was prioritized and additional biomarker tests were completed with the blood sample. If tissue quantity was sufficient, unused blood was discarded. The lab charged for a single test regardless of whether the test was performed on tissue and/or blood. Results: The QI project ran from Sept 2021 - Dec 2022 and achieved two improvements: 1) a 39.6% increase in complete biomarker testing in patients with advanced lung adenocarcinoma (80.6% post-intervention) and 2) a decrease of 15.7 days from diagnosis to complete liquid biopsy test results (27.2 days post-intervention). Conclusions: This QI project demonstrated a significant improvement in overall biomarker testing rates and a nearly 50% reduction in the time to completion of testing. It also demonstrated how hospitals and reference labs may coordinate efforts to streamline biomarker testing with the aim of improving clinical outcomes through reductions of TTT.
Virtual easy-to-access hematology tumor boards: Scaling disease expertise across multiple sites of care across urban and rural Tennessee.
Authors: Schneider Christy L. , Senneke Kimberly , Abbas Jonathan , Anz Bertrand Marquess , Allen Mary-Margaret , Donnellan William Bruce , Strickland Stephen Anthony , Dickson Natalie R. , Hamilton Katherine , Flinn Ian W. , Hsiao Mindy , Schleicher Stephen Matthew , Byrne Michael 
Published: October 2023

570 Background: Tennessee Oncology is a community oncology practice with 90 medical oncologists practicing at 35 urban and rural clinical sites across Tennessee and Northern Georgia. In January 2023, we launched a virtual malignant hematology tumor board (MHTB) to allow the review of patient cases by a centralized collaborative team of physicians with expertise in malignant hematology and hematopathology who are located at four sites of care. Methods: Any provider within the practice can submit a case to the MHTB through the electronic medical record. Cases are reviewed twice monthly via scheduled Zoom meetings. Providers are invited but not expected to attend the scheduled conferences. A summary of the discussion, link to the recording, and time stamp is emailed to the referring providers within 3 days of the discussion. After 6 months of use, an electronic anonymous survey was sent to providers to gauge satisfaction. Results: From January 1 to May 31, 2023, 85 patient cases were submitted for review by the MHTB (average 8.5 cases/conference). Approximately one-third (29/90) of oncologists within the practice submitted at least one case and most users (20/29, 69%) had multiple submissions. Since its inception, patients from 21 clinics and 56 different cities in Tennessee and Northern Georgia have been discussed at the MHTB. Many of these patients reside in rural communities. A survey of participating physicians (n=13, 45%) indicated a high level of satisfaction with the process. All respondents (100%) felt the MHTB improved medical decision-making in a meaningful way. The majority (77%) felt that a virtual format of the tumor board improved utilization and was pleased with the format. Conclusions: The development of a virtual MHTB created an avenue for general oncologists across 35 clinical sites of care to request timely review of complex malignant hematology cases by a centralized team of malignant hematology experts. Ease of case submission, a virtual format, and optional attendance have led to a high level of satisfaction among providers and allowed this initiative to be successfully scaled across the practice.
Help us help you using technology to maximize resource response to patient reported SDoH and depression screening.
Authors: LaPolt Donna , Walton Valerie T 
Published: October 2023

576 Background: Social determinants of health (SDoH) are associated with inferior health outcomes, morbidity, life expectancy, and healthcare expenses. Screening for SDoH is increasingly incorporated into routine clinical practice, however clinical decision support and resources addressing positive SDoH screening are less robust. As part of the ASCO PC4, we developed an electronic workflow that utilizes SDoH and depression screening tools with prepopulated referrals to assist the clinician in directing the referral to the most appropriate supportive service. Methods: Smilow Cancer Hospital ASCO Patient Centered Care Certification Implementation Team collaborated with our social work, psycho oncology, and Community Health Worker (CHW) to optimally screen and respond to patients who screened positive for SDoH or depression. A workflow was established using Welcome Web software in combination with Epic to transfer patient results collected in the waiting room via iPad to the patient’s medical record. Positive screening results trigger a best practice advisory when clinician opens chart. The alert links to a Smartset prepopulating an order to the appropriate resource for the reported need. Patients with transportation, food insecurity, or housing concerns were referred to Community Healthcare Worker. Social workers received referrals for patients with social connection concerns and PHQ-9 scores between 9-14. Patients with a PHQ-9 score of 15 and above were referred to the psycho-oncology team. A specialized workflow was created for any patient who responded positively to thoughts of self-harm. These patients received an immediate intervention and were screened using the Columbia Suicide Severity Screening Tool. Results: See table. Conclusions: Incorporating SDoH screening alongside clinical decision support and automated referrals was feasible. Technology enabled screening enhances efficiency and assists clinicians with direct referrals to the appropriate resource, while allowing resources to operate at the top of their licensure and enhance efficiency. Future Directions for Research: 1. Monitor emergency room utilization, admissions, and unplanned visits for patients receiving services from CHW, Social Work, and Psycho-oncology services. 2. Monitor work queue volumes to assess if directed referrals expedite response.[Table: see text]
Management and treatment of patients (pts) with stage III unresected non-small cell lung cancer (NSCLC) at UPMC: A quality initiative by Integra Connect PrecisionQ.
Authors: Petro Daniel P. , Gart Mike , Blanc Simon , Vasudevan Anupama , Li John , Fares Marielle , Choksi Rushir J. 
Published: October 2023

579 Background: In 2019, the University of Pittsburgh Medical Center (UPMC) and Integra Connect (IC) initiated a QI to improve immunotherapy (IO) use post CRT. Baseline analysis assessed scanning and treatment patterns post-CRT and duration of treatment (DOT) with durvalumab (durva). Drawing on this analysis, IC and UPMC conducted a focus group to address gaps in care and initiated improvements. This real-world study aims to assess the change in IO use post-CRT, the time to scan (TTS), time to treatment (TTT), DOT compared to baseline. The DOT of durva was compared between pts initiated <14 days of CRT and those who started ≥14 days. Methods: From the UPMC and IC real-world databases, we identified 555 pts with stage 3 unresectable NSCLC for manual chart abstraction. Pts received CRT between 2/16/2018 and 12/31/2021. TTS was calculated from the last day of CRT to the 1st scan and the TTT obtained from the last day of CRT to the 1st durva dose. The baseline period was from 2/16/2018 to 8/31/2020 and the post-intervention stage from 9/1/2020 to 12/31/2021 based on CRT start date. Pts were excluded if they had no scan data, a 1st scan ≥90 days post CRT (TTS analyses), a duration of zero days (DOT analyses) or a TTT >120 days (TTT analyses). At least 1 yr of follow up was required for DOT comparisons. Descriptive analyses were used. A two-tailed 2 sample z-test was used for proportions and the nonparametric Wilcoxon rank sum test was used for TTS, TTT and DOT comparisons. Results: The baseline pts were 46% female with an average age of 67.7 years; post-intervention patients were 47% female with an average age of 69.4 years. The rate of durva use post CRT in pts who did not progress increased from 66% (n =128/194) at baseline to 83% (n =96/116) post intervention (p < 0.01). The baseline median TTS decreased from 22.5 days (n=174) to 20 days (n=121) post intervention (p <0.05), and median TTT decreased from 35 days (n=121) to 28 days (n=90) (p < 0.05). The median DOT increased from 6 (n=127) to 8.2 months (n=76) (p >0.05). During the study period, 8% (n =17/223) of pts started durva < 14 days post CRT and 92% started ≥14 days (n =206/223). The median DOT in the < 14 days group was 10.8 months versus 6.2 months in ≥14 days (p >0.05). Median overall survival (OS) was 36.5 months in the <14 days vs. 27.8 months in the ≥14 days group (p > 0.05). Conclusions: NSCLC QIs are effective tools to improve IO utilization, TTT, and DOT in eligible pts. Practices that assess clinical performance can identify gaps in care and act. In this Stage III study, a superior OS, though lacking statistical significance, was seen in the group that started IO <14 days post CRT compared to ≥14 days. Further studies with larger sample size are needed to validate these findings.
Integrated oncology operational dashboard for clinical and operational quality improvement.
Authors: Sanyal Amit , Couture Lauren , Cropp Brett F. , Taylor Evie , Bianchi Michael J. , Remick Scot C. 
Published: October 2023

588 Background: MaineHealth Cancer Care Network, comprised of nine member and two affiliate cancer centers, provides care to more than 70% of analytic cancer cases in largely rural south-central Maine and eastern New Hampshire. To drive high quality and performance and harmonize care across the network, an integrated operational dashboard was created. Methods: A team of clinicians, operational leaders and business intelligence analysts identified improvement goals across clinical and operational domains. Using a Microsoft Power BI platform, an integrated dashboard with extracts from various non-interoperable data sources were migrated together to illustrate all relevant metrics. Divided into five pages, the Summary page allowed for a high level visualization of financial improvement metrics across the service line. The Growth page included trends of template utilization, provider access, encounter and financial statistics. The Service Excellence page measured diagnosis to treatment times, new patient volumes, timely chart completion rates and provider net promoter scores. Lastly, the Innovation and Transformation page measured clinical trial accruals, use of Epic TNM staging (Epic Systems, Verona, WI), Clinical Pathways (Elsevier, Amsterdam, NL) and use of NCCN distress thermometer for patient assessment. All data was searchable based on chosen fiscal years, practice locations and provider names with automated monthly data refreshes. Dashboard access to clinical and operational staff with monthly reviews drove performance improvement. Results: Since creation in January 2023, dashboard has been leveraged to improve structured Epic TNM staging by medical oncology providers from 46.9% in FY22 to 53.4% in FY23. Time to treatment data has helped identify process bottlenecks. Provider productivity metrics have been used to launch a compensation reform program incorporating production based incentives and improve patient access. Information transparency has improved team engagement and ownership. Conclusions: High quality cancer care delivery requires equal attention to clinical and operational metrics. In most organizations, this data is siloed across disparate software platforms with limited visibility and access to care team members, impeding quality initiatives. Implementation of the system-wide integrated quality dashboard has led to tangible improvements in care delivery and provider engagement. Additional work to incorporate provider well-being data is underway.
Pan-sarcoma database (PSDB): A model-view-controller framework application utilizing REDCap, shiny, and R to create a continuous pipeline of sarcoma data that can inform the care of current patients.
Authors: Rose Brandon Edward , Barreto Coelho Priscila , Bialick Steven , Patel Pooja , Statz-Geary Kurt , Nunez Osvaldo , Dhir Aditi , Kang Alina , Thornton Mason , Jonczak Emily , D'Amato Gina Z. , Trent Jonathan C. 
Published: October 2023

589 Background: Sarcomas are a rare group of mesenchymal malignancies arising soft tissue and bone, often requiring multidisciplinary care. The Pan-Sarcoma Database (PSDB) is an innovative open-source research application developed to efficiently collect and manage data on sarcoma patients to create a reliable research pipeline by funneling data from multiple sources. This process can be customized to fit other institutions and can be used to explore disparities and improve quality for cancer patients. We will share our data structure, process, and code as an adaptable framework for other multidisciplinary research groups with overlapping patients. Methods: The Model-View-Controller (MVC) framework is a software design pattern used by many modern applications. In this framework, "model" is the database, including the structure and metadata; "view" is the user interface software; "controller" is the coding language used to handle user input, update the model, and interact with the viewer. PSDB uses REDCap, shiny, and R, respectively. We integrated relational database concepts in our design, such as normalization, and utilized standards from Clinical Data Interchange Standards Consortium (CDISC). The database is comprised of 290 data fields to capture demographics, survival data, initial HPI, pathology, stage, grade, detailed location, detailed progression history, and associated treatment data. Results: We captured data from 28,380 candidate sarcoma patients from 2010 to present, including 3,291 confirmed cases, with 751 cases reviewed to date, merging data from multiple databases, pathology, and prior projects. Currently, 30.6% of our cases are metastatic at diagnosis; 57.7% are High grade, 28.9% are Intermediate grade, and 8.9% low grade; the median age at diagnosis is 55; 93.5% of reviewed cases received systemic therapy and 73.1% received radiation. By capturing key data and organizing an open-source code base in R mapped to our “model”, we produced updating tables, statistics, time-to-endpoint analyses, and other modifiable outputs to identify outcome disparities. Conclusions: The PSDB successfully addresses the unique data challenges faced in sarcoma research group. The use of the MVC framework with REDCap, shiny, and R, enabled the creation of an application that is secure, user-friendly, and adaptable, supporting collaborative research efforts. This project also emphasizes the importance of employing appropriate tools for data management and encourages similar initiatives to enhance collaboration and benefit both research teams and the patients they study. Furthermore, because it is open-source it can be used and modified by other research teams to improve the quality of care for cancer patients.
Understanding inpatient mortality and 30-day mortality at a comprehensive cancer center.
Authors: Soucise Allison , Shekher Rohil , Faller Julia , Keppel Daniel , Anthony Greta , Chowdhry Varun 
Published: October 2023

59 Background: Inpatient mortality quality metric for hospital settings. We sought to review instances of inpatient mortality as part of continuing quality improvement (QI) in our pursuit of the Triple Aim of Health care to improve individual and population health, while reducing unnecessary physical harm, psychological harm, and costs. Methods: An interdisciplinary institutional mortality review committee (MRC) was assembled to review all instances of inpatient mortality or 30-day hospital mortality (hospital mortalities). Individual team members reviewed pertinent clinical information, and appropriate instances were discussed during monthly meetings. The purpose is to review the details of the hospitalization and make determinations if any learning opportunities or process improvements were present. Study data were collected and managed using REDCap electronic data capture tools. Approval from the IRB was obtained to conduct this retrospective analysis. Results: Between January 2022 and April 2023, a total of 430 instances of hospital mortalities were identified and reviewed. Of the 421 patients for which data was available, 294 deaths were classified as “Anticipated” while 127 were classified as “Unanticipated”. Out of the 421 patients, 189 (44.9%) were classified as having an improvement opportunity. There was no association between anticipated vs unanticipated death and opportunity for improvement χ2,(1, n=421) =0, p=.998. However, we noted a significant inverse association with prior goals of care conversation and learning opportunity χ2,(3, n=421) =77.2, p<0.001. During the period of this initiative, we have noted an upward trend in the percentage of patients who had a GOC conversation from 83% to 96%. Improvement opportunities and hospital mortalities related to hospital acquired infections, direct surgical complications, and misdiagnosis were rare. Conclusions: Regarding hospital mortality, opportunities for improvement were largely centered around goals of care conversations and advanced care planning. There is a suggestion that MRC may have contributed to the increase in documented Goals of Care conversations. We believe that an MRC can contribute towards a cultural shift to promote Advanced Care Planning. Initiatives to improve goals of care conservations early in a patient’s disease course may have the potential to reduce inpatient mortality and reduce the physical, psychological, and financial toll of disease.