bluuebunny/crossref_metadata_2025_split huggingface dataset:
Implementation of a low-cost standardized handoff system (IPASS) in a pediatric hematology/oncology unit: Lessons from a low-middle income country.
Authors: Pariha Sheri , Saeed Sana , Qureshi Sonia , Altaf Sadaf 
Published: September 2018

278 Background: Communication failure is the most common preventable cause of medical adverse event, and almost half of all sentinel events involve handoff failure. Inefficient handoff is labor intensive and time consuming, impacting the quality of patient care provided. A safe and efficient means of exchange of medical information between care teams via a standardized handoff system is essential, especially in high intensity fields such as Pediatric Hematology/Oncology. Methods: Pre-intervention, handoff entailed the physical handover of handwritten notes, carbon copied for various team members. A standardized electronic handoff tool (IPASS) was identified, and significantly modified to fit our needs, since we do not have a complete electronic medical record (EMR). Microsoft Sharepoint (Microsoft, Redmond, WA) was used to develop a tabulated online portal incorporating patient demographic, clinical and laboratory details with physician remarks. This allowed remote access, multiple simultaneous inputs, authenticated use and user-specific access control. Implementation included sensitizing residents to the IPASS template, hands-on training, weekly feedback from the residents, directly observed hand-off by the chief and/or senior resident. Following a four-week pilot this was expanded to other sub specialties, and a pre and post intervention survey was conducted to assess its impact. Results: Pre-implementation survey revealed 74% resident and 87% faculty dissatisfaction with the current handoff process. Weekly compliance audits after initial pilot demonstrated a 100% compliance. Post-Implementation results showed that the resident dissatisfaction has gone down to less than 5%. Conclusions: Implementation of an electronic handoff tool in the absence of an EMR with minimal resources is a major breakthrough and can be replicated in other low-resource settings. We successfully implemented IPASS without any added infrastructure cost. In the next phase of our project we will be measuring trends in reduction in medical errors since implementation.
Development of the CCRU kit squad: Centralization of biospecimen “kit” management.
Authors: Speers Vanessa 
Published: September 2018

295 Background: Personalized medicine has resulted in a rapid increase in biospecimens collection. Each biospecimen collected requires supplies that are provided in the form of “kits”. The number of kit types per protocol ranges anywhere from 2-60, with an average of 30 different kit types per trial. Historically, each trials nurse has managed their own kits resulting in large amounts of nursing time being spent on kit management. Kits took up a large amount of space in clinical areas, including expired kits, and they were being managed in no standardized fashion. Due to rapidly increasing biospecimen volumes, existing methods of kit management were no longer feasible and the CCRU Kit Squad was developed. Methods: Over the course of 12-mos, an extensive assessment of current kit management practices were reviewed with all disease site groups, including workflows and quantities utilized. An e-commerce software platform was selected, and semi-customized to centralize online ordering and receiving of kits, and the creation of a central location was setup for kit storage and daily operations. On-boarding of each group included retrieving existing kits from each nurse, uploading kits to the software, training each nurse to use the software, setting up accounts with each respective vendor for deliveries and re-supply, and disposing of expired kits. Results: Disease site groups were transitioned to the CCRU Kit Squad stepwise from Oct 2016 to Dec 2017 (15-mos), which included 80 nurses, 16 disease site groups, and over 400 clinical trials. By the end of 2017, the average number of kits ordered per day, and per month were 33 and 1003, respectively. Conclusions: The CCRU Kit Squad developed a centralized online service for kit management, thereby reducing administrative burden on clinical trial nurses. It has streamlined the management of biospecimen kits, eliminated wasted space in clinical areas, and facilitated the selection of the right kit for the right test at the right time.
Improving start-up times in oncology clinical trials: An ASCO quality improvement project.
Authors: Byatt Leslie , Deutsch Kaylee , Dayao Zoneddy R. 
Published: September 2018

297 Background: With the increasing complexity of clinical trials, the UNMCCC and NMCCA are seeing increased delays in study activation. Currently, the average time from protocol receipt to trial activation is 33 weeks. Creating strategies to shorten the timeline where the longest delays occur will expedite patient access to novel therapies and improve patient care. Aims: Define the average activation timelines; Identify the timeline where an intervention will make the most impact in shortening start-up time; Implement an intervention, beginning February 2018; Identify strategies to decrease the longest timeline by 50% by December 2018. Methods: Timelines of 81 clinical trials opened in 2017 were analyzed. Data showed that the longest timeline is IRB approval to activation (12 weeks) and identified this as the focus of intervention to decrease our overall activation time by 50% (6 weeks). Two focus group meetings with involved staff were organized and completed. Interventions were identified. The time to complete activation tasks cannot be shortened due to staffing resources. However, shifting these tasks forward in our timeline could decrease the time to activation by at least 6 weeks. A sponsor survey was created to identify logistical concerns earlier. Regulatory coordinators were provided an email template to request systems access early. Site initiation visits are scheduled earlier. Results: Our data shows that our interventions have had a strong positive impact on our timelines. Conclusions: Since implementation, we have seen an improvement in our study timeline. We will continue to track and analyze our timeline data to determine if these strategies are effective across trials with varying startup complexities.[Table: see text]
Practice transformation: Early impact of OCM on hospital admissions.
Authors: Mendenhall Molly , Bourbeau Brian , Dyehouse Karyn M. , Guinigundo Andrew S , Meyer-Smith Teresa , Waterhouse David Michael 
Published: September 2018

30 Background: The purpose of the Oncology Care Model is to improve quality and reduce cost through practice transformation. A foundational tenant is to reduce avoidable ER visits and hospitalizations. In anticipation of being an OCM participant, we instituted a multidimensional campaign designed to meet these objectives. Methods: Prior Actions: Established phone triage unit. After-hours and weekend call. Instituted weekend urgent care. Year One: Improved education provided by nurse navigators and APPs prior to start of treatment (OCM Treatment Planning visit). Implemented triage pathways: 38 symptom and 27 follow-up pathways (modified COME HOME, Barbara McAneny, M.D.). Proactive symptoms follow-up calls to help circumvent emergent admissions. Increased APP staffing to provide blocked time slots for same day patient visits w/o schedule disruptions. Initiated “Call Us Early – Call Us First” campaign. Incorporated verbal and/or written instructions at all patient touch points, emphasizing patient’s responsibility to call before going to the emergency room. Results: Based on data from the Chronic Condition Warehouse, as provided by CMS, we were successful at reducing the acute care admissions rate by 16 percent. Conclusions: By implementing a cost efficient, reproducible, and scalable campaign targeting ER avoidance and hospitalizations, we were able to decrease hospital admissions. Reported Medicare savings amounted to nearly $798,000 in inpatient cost per quarter over 1,600 patients.[Table: see text]
Real-time assessment of resource utilization and subsequent cost analysis in cancer patients (pts) near the end of life (EOL).
Authors: McPherson Jordan P. , Patel Shiven B. , Igumnova Elena , Pettit Jacob , Ose Dominik , Haydell Tyler , Martineau Jim , Meropol Neal J. , Beck Anna Catherine 
Published: September 2018

303 Background: Aggressive medical interventions and associated high costs of care for cancer pts near the EOL are common. Addressing this issue at the local level requires an accurate, automated process to merge real-time clinical EHR data with cost data for performance reporting. Methods: This was a single-center, observational cohort study of decedents treated with anticancer therapy (antiCT) in the last 6 months of life from January 2016 to October 2017. Pts were stratified by antiCT use in the last 30 days of life. The primary outcome measure was total cost of care. Secondary outcome measures (hospitalizations, ER and ICU utilization, antiCT use, and hospice referral) were obtained through Flatiron Health EHR-based automated data processing. Cost data were merged from the Value-Driven Outcomes analytics framework. Results: 650 pts were included. 228 (35.1%) received antiCT in the 30 days before death. Non-drug costs for pts who received antiCT in the last 30 days of life were higher than those who did not (p < 0.01, median 38X higher). A higher proportion of pts who received antiCT in the last 30 days of life had ≥1 ER visit (29.4% vs 9.5%, p < 0.01) and hospital admission (58.8% vs 27.3%, p < 0.01) during the last 30 days. In addition, more of these pts received ICU care (35.5% vs 11.4%, p < 0.01). AntiCT in the last 30 days was associated with shorter median time from first hospice referral to death (1.4 vs 4.7 weeks; IQR 0.7-2.0 vs 3.14-7.7 weeks, p < 0.01). Distribution of antiCT types administered to pts in the last 30 days versus those given antiCT > 30 days from the EOL was significantly different, with the most substantial difference seen in the proportion of pts receiving immunotherapy (20.2% vs 12.6%, p = 0.04). Conclusions: Real-time assessment of EOL outcomes shows antiCT in the last 30 days of life is associated with aggressive medical interventions and increased total cost of care. Future research should identify pts who are unlikely to benefit from aggressive care, and whether performance reporting to oncologists will reduce futile interventions near the EOL.
The Quality Oncology Practice Initiative program: Experience in Spain.
Authors: Lopez Rafael , Anton Antonio , Aranda Enrique , Carrato Alfredo , Constenla Manuel , Cruz Juan Jesús , Díaz Rubio Eduardo , Feyjoo Margarita , García Foncillas Jesús , Gascon Pedro , Guillem Vicente , Lugo Ilse , Camps Carlos 
Published: September 2018

310 Background: Patient care quality is a discipline with enormous relevance in today’s healthcare. Quality Oncology Practice Initiative (QOPI) is a referral worldwide in quality for oncology practices. ECO Foundation is a collaboration of experts representing the major Spanish hospitals involved in the treatment of cancer patients. ECO reached an agreement with QOPI to involve Spanish hospitals in the QOPI program. Methods: Six rounds of data collection have taken place (Fall 2015 to Round 1 2018). Practices had to register online and submit data into the QOPI platform, and ECO Foundation offered all centers the necessary support. 17 Spanish hospitals have participated in the six rounds, and 7 of them have repeated participation. Core and Lung Cancer modules were completed. Results: During the six rounds, 1877 charts were submitted by the Spanish practices. In most of the rounds, the highest scores were: Pathology report confirming malignancy, Number of chemotherapy cycles documented, Patient consent for chemotherapy and 5 measures of the Lung Cancer module. The lowest scores were: Chemotherapy treatment summary provided to patient within 3 months of chemotherapy end, Chemotherapy treatment summary provided or communicated to practitioner(s) within 3 months of chemotherapy end, Smoking/tobacco use cessation counselling recommended to smokers/tobacco users in past year and Tobacco cessation counselling administered or patient referred in past year. The percentage of participating practices that presented results higher than 70% was successively 64%, 50%, 75% and 100% in the last three rounds. For the 7 hospitals that repeated participation, 3 reported an improvement of their global scores. Regarding QOPI Certification, three Spanish hospitals received this accreditation in September 2017 and one in June 2018. Conclusions: These preliminary results are a good starting point for the continued implementation of the QOPI program in Spain, thus providing a well-structured approach to analyze cancer care. ECO Foundation will continue pursuing excellence and quality with further activities like the QOPI Certification program and Quality Training Program, these being performed for the first time in Spain in 2017 and 2018 respectively.
Employing electronic health record data to predict risk of emergency department visits for new patients.
Authors: Daly Robert Michael , Gorenshteyn Dmitriy , Gazit Lior , Sokolowski Stefania , Nicholas Kevin , Perry Claire , Adams Lynn , Baldwin Abigail , Katzen Lauren L. , Chiu Yeneat O. , Reidy Diane Lauren , Simon Brett A , Perchick Wendy , Wagner Isaac 
Published: September 2018

314 Background: Acute care accounts for half of cancer expenditures and is a measure of poor quality care. Identifying patients at high risk for ED visits enables institutions to target symptom management resources to those most likely to benefit. Risk stratification models developed to date have not been meaningfully employed in oncology, and there is a need for clinically relevant models to improve patient care. Methods: We established a predictive analytics framework for clinical use with attention to the modeling technique, clinician feedback, and application metrics. The model employs EHR data from initial visit to first antineoplastic administration for new patients at our institution from January 2014 to June 2017. The binary dependent variable is occurrence of an ED visit within the first 6 months of treatment. From over 1,400 data features, the model was refined to include 400 clinically relevant ones spanning demographics, pathology, clinician notes, labs, medications, and psychosocial information. Clinician review was performed to confirm EHR data input validity. The final regularized multivariate logistic regression model was chosen based on clinical and statistical significance. Parameter selection and model evaluation utilized the positive predictive value for the top 25% of observations ranked by model-determined risk. The final model was evaluated using a test set containing 20% of randomly held out data. The model was calibrated based on a 5-fold cross-validation scheme over the training set. Results: There are 5,752 antineoplastic starts in our training set, and 1,457 in our test set. The positive predictive value of this model for the top 25% riskiest new start antineoplastic patients is 0.53. The 400 clinically relevant features draw from multiple areas in the EHR. For example, those features found to increase risk include: combination chemotherapy, low albumin, social work needs, and opioid use, whereas those found to decrease risk include stage 1 disease, never smoker status, and oral antineoplastic therapy. Conclusions: We have constructed a framework to build a clinically relevant model. We are now piloting it to identify those likely to benefit from a home-based, digital symptom management intervention.
Performance on cancer quality measures: Ethnicity, insurance, and census division disparities.
Authors: Browner Amanda , Palis Bryan E. , Gay E. Greer , Mallin Katherine , McCabe Ryan M. , Facktor Matt , James Ted , Shulman Lawrence N. 
Published: September 2018

34 Background: Since enactment of Healthy People 2000 (ODPHP.gov, nd), a focus has been to reduce disparity by achieving health equity across all people. We examined disparity for five cancer quality measures with high performance rates (PRs) ( > 85%). Methods: Five measures developed by the Commission on Cancer and endorsed by the National Quality Forum were evaluated for potential ethnicity, insurance, and Census Division disparities. Data from the National Cancer Database were used to examine hospital-level PRs on adjuvant chemotherapy for ER neg breast ca (MAC), hormone therapy for ER+ breast ca (HT), resection of at least 12 nodes in a colon resection (12RLN), and adjuvant chemotherapy for stage III colon ca (ACT) measures for patients diagnosed in 2015. Patients receiving radiation after breast conservation surgery (BCSRT) were diagnosed in 2014 to ensure complete treatment follow-up. Results: Significant disparities exist for all measures on ethnicity between non-Hispanic whites and Hispanics. The least variation of ethnicity occurred within 12RLN (non-significant). Variability within insurance was found most frequently with HT and BCSRT measures, not insured/Medicaid versus Medicare, and not insured/Medicaid versus Private respectively. Location disparity exists for all measures, with South Central states’ significantly lower PRs. Further investigation should focus on access, insurability, and delivery of care to better understand and eliminate disparities. Conclusions: Cancer quality measures, which show high performance nationally, show significant performance variability reflective of on-going disparities of care. [Table: see text]
Cancer survival outcomes in Ontario, Canada: Significant unexplained variation.
Authors: Brundage Michael Donald , Groome Patti , Hanna Timothy , Booth Christopher M. , Kong Weidong , Dyer Tina , Carter Brenda , Mackillop William J. 
Published: September 2018

36 Background: Cancer-specific outcomes are critical for assessing quality of care, and are key quality indicators for cancer control programs. Previous analyses of Ontario (Canada) data show that regional survival differences at the Local Health Integrated Network (LHIN) level exist for relative survival, overall survival, cancer-specific survival (CSS), and mortality rates.We sought to describe: 5-year cancer-specific survival (5Y-CSS) rates among Ontario LHINs; the impact of adjusting for known patient factors; and 5Y-CSS rates among patients diagnosed at Ontario's 50 largest cancer diagnosing hospitals. Methods: Newly diagnosed cases (colorectal, lung, breast, or prostate cancer) were identified in the Ontario Cancer Registry. Records were linked to data from CIHI and Statistics Canada, to identify date of diagnosis, cause-specific vital status, diagnosing hospital, and other reported variables. Cox regression models were used, and all models were adjusted for age and sex. Results: N = 498,382 incident cases (2007-2013) were included. 5Y-CSS varied across LHINs for all patients combined (range 62%-72%; p < 0.0001). Considering colorectal cancer cases as illustrative (N = 57,927), 5Y-CSS varied among LHINs from 58.4%-66.4% (p < 0.0001). Further adjusting for socioeconomic and urban-rural status minimally reduced that variation. Limiting the analysis cohort to patients diagnosed in one of Ontario's 50 largest hospitals (N = 43,245), 5Y-CSS ranged from 52% to 72% (p < 0.0001) among hospitals, and from 55% to 63% (p < 0.0001) among the hospitals affiliated with regional cancer centres. Comparable findings were seen for patients diagnosed with lung, breast, or prostate cancer. Collaborative staging data were available for a subset of patients; 5Y-CSS within all stage III patients (N = 5,360) ranged from 72% to 87%. Conclusions: Important, highly significant differences in cancer survival outcomes exist across Ontario. These are of great interest to patients, health-care providers, system administrators, and policy makers, and are not explained by adjusting for the variables included in these analyses.
Expansion of high-quality specialized services: The gynecologic oncology experience in Ontario hospitals.
Authors: Gilbert Julie , Wheeler Sarah , D'Souza Junell , Irish Jonathan Crawford , Meertens Elaine , Simanovski Vicky , Matheson Garth 
Published: September 2018

39 Background: In Ontario’s publicly funded cancer system, patient access to Gynecological Oncology (GyneOnc) care is threatened by growing demand, waiting times and need for lengthy patient travel. Cancer Care Ontario has published organizational standards that lay out the minimum clinical elements and infrastructure needed for a high quality program. Capacity planning and readiness assessments were used to guide GyneOnc expansion into non-academic regional cancer centres to alleviate system pressure. We evaluated early expansion activities to learn about critical factors and generate recommendations for future growth of this specialized oncology service. Methods: Capacity planning for new centres factored health human resources (HHR), patient volume and travel distances, ensuring that existing programs maintain critical mass. Evaluation included review of documents and readiness assessments related to the expansion projects undertaken to date. Interviews were done with GyneOncologists and administrators working at local and provincial levels to discover areas of risk, key factors for success, and recommended strategies for future expansion. Results: Gyne Onc programs need adequate resourcing (minimum 3 GyneOncs) to meet patient demand, support on-call and offer resilience to parental/medical leaves. Programs need engagement from other surgical and medical subspecialties, and clinical services (e.g. pathology, diagnostic imaging) for integrated, multidisciplinary care. Academic appointments, residencies, fellowships, and support for research provide links with universities, important for credibility. Endorsement by senior leadership - both management and clinical - is crucial. Organizational standards need specificity around the infrastructure and multidisciplinary environment needed for program success. Conclusions: HHR planning and readiness assessment are critical enablers in the expansion of specialized services like GyneOnc beyond academic centres. New programs need to consider the adequacy and appropriateness of staffing models, broad engagement of the clinical team, and linkages to academia, in order to ensure program sustainability and acceptability.