Retrospective Chart Review Assessing Factors that Contribute to Network Leakage in Postoperative Pancreatic Cancer Patients

Introduction: Standard of care for resectable pancreatic cancer includes surgery, chemotherapy, with consideration of radiotherapy. Thomas Jefferson University Hospital (TJUH) is a large volume institution for pancreatectomy. Rate of subsequent in-network adjuvant treatment are far less which may impact outcomes. We will elucidate variables that influence coordinated patient care. Objective: To evaluate variables that correlate with follow up and adjuvant treatment of pancreatic cancer patients at TJUH. Methods: Retrospective medical chart reviews will be performed with data from patients with pancreatic cancer who have undergone resection at TJUH from April 2017 to March 2018. Patient demographics, clinical, and pathologic information will be obtained and a multivariable logistic regression done to identify variables associated with follow up and reception of adjuvant treatment. Results: We hypothesize that distance from TJUH will be the strongest predictor of follow up and adjuvant treatment at TJUH. Discussion: The findings will help us to characterize the quality of follow up and adjuvant treatment at TJUH. Identification of significant variables will help select patients that may benefit most from additional efforts to coordinate follow up. This may benefit patient outcomes as adjuvant treatment at high volume, academic centers have been associated with overall survival outcomes (Mandelson, ASCO 2016, abstract #191). Future projects based on our findings will evaluate the impact of current TJUH efforts such as the in-house inpatient medical and radiation oncology consultation through patient interviews and surveys. The ultimate goal of our work is to optimize current efforts while identifying gaps for innovation to maximize coordinating care

A Telehealth Clinical Workflow for Academic Radiation Oncology Programs During the COVID19 Pandemic

COVID19 has resulted in drastic measures to decrease exposure risks within healthcare systems, with cancer patients at increased risk of infection and death (Liang. Lancet Oncol. 2020). Telehealth is the delivery of medical care via interactive audio and/or video telecommunication services. Telehealth was previously used sparingly within the department of radiation oncology but has suddenly become the preferred method of contact. In order to maintain quality of care, patient satisfaction, resident learning, and reimbursement, a robust telehealth clinical workflow is critical. Our department engaged various stakeholder to quickly develop a clinical workflow

Focused ultrasound for treatment of bone tumours.

PURPOSE: Focused ultrasound (FUS) is a modality with rapidly expanding applications across the field of medicine. Treatment of bone lesions with FUS including both benign and malignant tumours has been an active area of investigation. Recently, as a result of a successful phase III trial, magnetic resonance-guided FUS is now a standardised option for treatment of painful bone metastases. This report reviews the clinical applications amenable to treatment with FUS and provides background on FUS and image guidance techniques, results of clinical studies, and future directions. METHODS: A comprehensive literature search and review of abstracts presented at the recently completed fourth International Focused Ultrasound Symposium was performed. Case reports and older publications revisited in more recent studies were excluded. For clinical studies that extend beyond bone tumours, only the data regarding bone tumours are presented. RESULTS: Fifteen studies assessing the use of focused ultrasound in treatment of primary benign bone tumours, primary malignant tumours, and metastatic tumours meeting the search criteria were identified. For these clinical studies the responders group varied within 91-100%, 85-87% and 64-94%, respectively. Major complications were reported in the ranges 0%, 0-28% and 0-4% for primary benign, malignant and metastatic tumours, respectively. CONCLUSIONS: Image-guided FUS is both safe and effective in the treatment of primary and secondary tumours. Additional phase III trials are warranted to more fully define the role of FUS in treatment of both benign and malignant bone tumours

Effect of bevacizumab in older patients with metastatic colorectal cancer: pooled analysis of four randomized studies

Background: Bevacizumab is frequently combined with 5-fluorouracil-based chemotherapy for patients with metastatic colorectal cancer (mCRC). The relative benefit of bevacizumab in older patients has not been widely studied and is of interest. Patients and methods: This retrospective analysis used data from three first-line randomized controlled studies and one second-line randomized controlled study of bevacizumab plus chemotherapy in medically fit (Eastern Cooperative Oncology Group performance status 0 or 1) patients with mCRC. Overall survival (OS) and on-treatment progression-free survival (PFS) were assessed in patients aged greater than 65, greater than or equal to 65, and greater than or equal to 70 years. Results were compared using unstratified hazard ratios (HRs). Grade 3-5 adverse events were also assessed. Results: Bevacizumab statistically significantly improved PFS [HR 0.58; 95% confidence interval (CI) 0.49-0.68] and OS (HR 0.85; 95% CI 0.74-0.97) in patients aged greater than or equal to 65 years; patients aged greater than or equal to 70 years had similar improvements. Benefits were consistent across the studies, irrespective of setting, bevacizumab dose, or chemotherapy regimen. Increases in thromboembolic events were observed in patients aged greater than or equal to 65 and greater than or equal to 70 years in the bevacizumab group compared with the control group, mainly as a result of increases in arterial thromboembolic events. No other substantial age-related increases in grade 3-5 adverse events were observed. Conclusions: In medically fit older patients, bevacizumab provides similar PFS and OS benefits as in younger patients

Predictive Analytics in Practice: A Novel Simulation Application for Addressing Patient Flow Challenges in Today's Emergency Departments

Abstract Objectives: To develop a flexible software application that uses predictive analytics to enable emergency department (ED) decision-makers in virtually any environment to predict the effects of operational interventions and enhance continual process improvement efforts. To demonstrate the ability of the application's core simulation model to recreate and predict sitespecific patient flow in two very different EDs: a large academic center and a freestanding ED. To describe how the application was used by a freestanding ED medical director to match ED resources to patient demand. Methods: The application was developed through a public-private partnership between University of Florida Health and Roundtable Analytics, Inc., supported by a National Science Foundation Small Business Technology Transfer (STTR) grant. The core simulation technology was designed to be quickly adaptable to any ED using data routinely collected by most electronic health record systems. To demonstrate model accuracy, Monte Carlo studies were performed to predict the effects of management interventions in two distinct ED settings. At one ED, the medical director conducted simulation studies to evaluate the sustainability of the current staffing strategy and inform his decision to implement specific interventions that better match ED resources to patient demand. After implementation of one intervention, the fidelity of the model's predictions was evaluated. Results: A flexible, cloud-based software application enabling ED decision-makers to predict the effects of operational decisions was developed and deployed at two qualitatively distinct EDs. The application accurately recreated each ED's throughput and faithfully predicted the effects of specific management interventions. At one site, the application was used to identify when increasing arrivals will dictate that the current staffing strategy will be less effective than an alternative strategy. As actual arrivals approached this point, decision-makers used the application to simulate a variety different interventions; this directly informed their decision to implement a new strategy. The observed outcomes resulting from this intervention fell within the range of predictions from the model. Conclusion: This application overcomes technical barriers that have made simulation modeling inaccessible to key decision-makers in emergency departments. Using this technology, ED managers with no programming experience can conduct customized simulation studies regardless of their ED's volume and complexity. In two very different case studies, the fidelity of the application was established and the application was shown to have a direct positive effect on patient flow. The effective use of simulation modeling promises to replace inefficient trial-anderror approaches and become a useful and accessible tool for healthcare managers challenged to make operational decisions in environments of increasingly scarce resources