bluuebunny/crossref_metadata_2025_split huggingface dataset:
Treatment-related costs of pediatric acute lymphoblastic leukemia.
Authors: Kaul Sapna , Lemons Richard S. , Korgenski Kent , Ng Christi , Nelson Richard , Raetz Elizabeth A. , Fluchel Mark , Kirchhoff Anne C. 
Published: February 2017

23 Background: Few studies have examined costs of pediatric cancer care and we lack a clear understanding of cost trends. In this study, we examined longitudinal treatment- and patient-related hospitalization costs within 5 years of diagnosis of acute lymphoblastic leukemia (ALL), the most common childhood cancer in the United States. Methods: We used data on N=555 patients diagnosed with pediatric ALL from 1998 to 2013 identified through the Intermountain Healthcare System in UT. The majority of these patients (>95%) were diagnosed and treated at the Primary Children’s Hospital (PCH) in Salt Lake City, UT. PCH encompasses the largest coverage area in the continental U.S. served by a single children’s hospital. We computed the average annual per patient hospitalization cost (aggregate and by components such as room, care and nursing cost, pharmacy cost, therapy and diagnostics costs). We used the generalized estimating equations (GEE) regression framework to identify patient characteristics (sex, age, race, rural/urban residence, insurance, high vs. standard risk, relapse, bone marrow transplant (BMT), and year of diagnosis) associated with hospital-related treatment costs (total cost per encounter). Results: Annual average cost of per patient hospitalization increased by 26% from 1998-2005 to 2006-2013. Most of this increase was driven by annual increases in room, care and nursing costs (increased by 29%) and pharmacy cost (increased by 79%). Our GEE models indicated the greatest costs among relapsed patients (average difference (δ) =$15,507 vs. those without relapse), BMT patients (δ=$15,184 vs. no transplant) and patients older than 10 years at diagnosis (δ=$8,539 vs. patients younger than 10 years at diagnosis). Publically insured patients had per encounter hospitalization costs that were greater (δ=$931) than privately insured. Conclusions: Average annual cost of hospitalization for pediatric ALL care has increased over the past fifteen years. Management of room, care and nursing, and pharmacy costs need to be considered in efforts to address the cost burden. In addition, patient-centered strategies to manage higher costs, such as better management of patients who are older at diagnosis or publically insured, may be warranted.
A model to optimize treatment case-to-machine assignment in radiation oncology.
Authors: Kukshtel Nicholas Carl , Mersereau Robert , Kadish Sarah , Potiris Spyros , Vivenzio Todd , Martin Neil E. 
Published: February 2017

231 Background: The department of Radiation Oncology at the Dana-Farber/Brigham and Women’s Cancer Center operates seven linear accelerators treating approximately 200 patients per day. These machines are regularly shut-down for upgrades, requiring the redistribution of patients to available machines. Previous machine downtimes have caused disruptions to patient care and required extended operating hours to accommodate displaced patient volume. For the next machine downtime, we sought to create a model to optimize the reassignment of patients to available machines, maximizing treatment type-machine compatibility while minimizing overtime, costs, and patient care impact. Methods: This collaboration between Radiation Oncology and the Process Improvement team retooled the Assignment Problem Method, an Industrial Engineering technique used to assign tasks, in order to solve for case allocation to radiation machines. A spreadsheet model was developed to optimize the allocation of treatment cases for each machine, without violating working hours or treatment type-machine constraints. Input data included case duration, radiation technique, daily demand, and machine compatibility for each treatment type. In addition to finding an optimal case allocation, department administrators created “what-if” scenarios to identify how demand fluctuations would shift cases across machines. Proposed solutions were validated by comparing the model’s output to feasible treatment volumes identified by department administrators. Results: The model revealed that under idealized conditions, the current daily patient volume can be accommodated with two fewer machines and 1.5 fewer operating hours each day. The time it took department administrators to prepare for the next downtime was reduced from several weeks of manual planning, to a few days using the model. Conclusions: Simple industrial engineering tools can help solve complex problems. Developing optimization models can eliminate complex calculations, allowing end-users to refine and implement a suitable solution without fear of mathematical error. A robust model can provide end users the ability to assess the impact of future changes in capacity or demand.
Improving advance care planning for UICC Oncology patients.
Authors: Ramadas Gowri , Golick Janet , Gorodinsky Polina , Jayakumar Udai , Dumayas Neriza , Branen Greg , Quinones Lydia , Engeseth Hope , Venepalli Neeta K. 
Published: February 2017

234 Background: Advance care planning (ACP) in the ambulatory setting is underutilized and poorly documented at the University of Illinois Cancer Center (UICC). A baseline 8 week review noted 8.8% of metastatic solid tumor patients had ACP documentation in the electronic medical record (EMR) by the third visit and 23% in the previous two visits. Our aim was to increase ACP documentation to 75% of UICC metastatic solid tumor patient charts by the third visit through development of a standardized process for ACP discussion and documentation. Methods: A multidisciplinary team of oncology physicians, nurses, social workers (SW), and palliative care created a process map of ACP discussion. A new process for SW consults was piloted over 6 weeks. Additionally, all clinic staff participated in a standardized curriculum for ACP discussions. Post intervention data was prospectively collected over six weeks. Results: Total 94 encounters occurred during the pilot evaluating ACP in metastatic solid tumor patients of which 37/55 (39.4%) had documented ACP discussion. SW consults occurred in 18/94 (19.1%), leading to 18/18 (100%) with Power of Attorney (POA) forms in EMR. Evaluation by tumor subtypes showed 14/21 (66.7%) of gastrointestinal patients had ACP documentation with 9/21 (42.9%) with SW consults leading to 11/21 (52.4%) with POA forms in EMR. Of 39 total thoracic patients, 19/39 (48.7%) had ACP documentation of which 9/39 (23%) with SW consults and 7/39 (17.9%) with POA forms in EMR. Conclusions: UICC successfully piloted the creation and implementation of a process for ACP consults and standardization of ACP discussion and EMR documentation. While our initial aim of 75% a chart was not reached, the piloted process increased SW consults and completion of POA forms, as well as greater multidisciplinary effort and patient engagement. Compared to the pilot period, a multidisciplinary approach and use of the new process did improve ACP documentation. We plan to expand to all metastatic patients. [Table: see text]
Surveillance and evidence-based safety initiatives in radiation medicine.
Authors: Kapur Ajay , Potters Louis 
Published: February 2017

247 Background: Moving towards safer radiation medicine requires an active surveillance of associated failures, their causes and effects, and evidence-based approaches for mitigation. In this study, by using retrospective and prospective surveillance, we have implemented evidence-based risk mitigation strategies in our radiation medicine practice. Methods: Incident learning has shown us that failures occur due to delays or defects in the radiation medicine process and that cultural error-provoking conditions raise these risks. Our initiatives were directed towards mitigation of defects in the high-risk process steps identified through a planning process FMEA. These included the standardization of care pathways and grading scale for assessing toxicity; pre-planning contour, directive peer review; electronic whiteboard for planning coordination and incident reporting, a process interlock policy to thwart delay-rushed processes; and the use of 6 sigma metrics to monitor individual staff operational efficiencies. Results: There has been a 3-fold increase over a 9 month period in incident reporting relative to the previous 6 previous years, by the peer group historically least likely to report, with no increase in adverse events. Evidence-based care pathways have been used with under 5% clinical non-compliance rates. The implementation of contour and directive pre-planning peer review has enhanced early defect detection. There has been a twofold drop in the occurrence of high-risk procedural delays. Patient treatment start delays are routinely enforced on cases that would have historically been rushed. Temporal trends demonstrate over 30% improvement in process Z-scores over the past three years. Conclusions: Driving these risk mitigation initiatives has challenged traditional norms such as expediting treatment initiation in delay-rushed environments or sustaining care pathways that are more experience rather than evidence-based. Therefore their implementation has met with substantial barriers. It is the focus on patient safety, statistical process control, policy enforcement, regular incident reviews, and use of quantitative metrics that has been instrumental in realizing these changes and crossing barriers.
Operational improvements to clinic flow.
Authors: Gross Katherine , Jacobs Kelli , Romano Michael 
Published: February 2017

253 Background: With expanding clinic volume and future growth potential, we face an issue of limited physical clinic capacity. This has resulted in extended patient wait times, physician idle time, and longer clinics days. Each of these issues adds to both provider and patient dissatisfaction and operational inefficiencies. Methods: Key operational metrics and through put data was analyzed with the oncology team. Agreements and goals for the process improvement were: no provider would be told they could not see a sick patient, patient’s time would be respected and maximize provider productivity. Data demonstrated that the current state would not accommodate future growth. Several operational changes were agreed upon by physician and administrative leadership: level load the days of the week, require several providers to move their clinic days; place structure and real-time discussion into how we manage same day and future “add-on” patients though setting clear expectations around clinician template times; assign a full time staff member to function as a “clinic flow coordinator" to triage same day add-ons, and facilitate provider room assignments, communicate with providers, and identify system or people barriers to clinic flow; provide each of the patients a “restaurant style” pager that will light up when they are ready to be taken to a room, allowing them the freedom to leave the waiting room without fear of missing their appointment time; implement a room-utilization manager software program allowing staff to see and collectively manage real time clinic flow and room utilization. Results: Provider feedback was very positive related to the flow and utilization of clinic rooms. The check-in staff described a less full waiting room even though volumes remained constant. We will monitor patient perception by patient satisfaction scores. Conclusions: To date, much of the results have been anecdotal. In order for these changes to become practice there is a clear need to tie in satisfaction and operational efficiency metrics. There will be ongoing coaching and feedback with providers and staff related to adherence to the new processes. As new providers are added to the practice, we will be very purposeful when adding their creating their templates and adding their clinic days.
Cancer care transparency: Trying to move the dial in California.
Authors: Teleki Stephanie 
Published: February 2017

256 Background: Each year in California, about 150,000 patients (more than 16 each hour) are diagnosed with cancer. Yet there is little useful information about the quality of cancer care to help patients, providers and payers make decisions about care. Methods: In 2012, the California HealthCare Foundation, an Oakland-based independent nonprofit philanthropy, launched an initiative focused on improving cancer care quality measurement and public reporting in the State. Since then, the Foundation has funded a number of projects aimed at filling information gaps; 2014 highlights include: (1) development of a Consumer Assessment of Healthcare Providers and Systems (CAHPS) patient experience of cancer care survey (with NCI and AHRQ). CHCF is now funding 6 community oncology test sites in California; (2) analytic work to measure and report the number of cancer procedures performed by hospitals using State discharge data, for procedures where there is an established volume-outcome link; public reporting by hospital expected by early 2015 (with Stanford University); (3) a feasibility study of measuring cancer care quality at the medical group level in California using claims data combined with California Cancer Registry data (with Integrated Healthcare Association); (4) a report on cancer care spending in California, publication expected Winter 2014 (with Dana Farber); (5) a workgroup of State and national thought leaders to contemplate and articulate the challenges and opportunities of leveraging the California Cancer Registry for quality measurement and public reporting; Sacramento briefing to state legislators in Winter 2014 (with UCSF). Results: Significant challenges exist at the state level to provide information for improved decision-making about cancer care. Among them: access to data, especially cancer registry data that importantly includes detailed diagnostic information; lack of clinical outcome and patient experience measures; time needed to engage partners; and costs of carrying out quality measurement projects. Conclusions: This presentation will provide a 2014 update on efforts underway in California, focused especially on the challenges and opportunities at the state level for cancer quality measurement and public reporting.
Identifying targets for outpatient palliative care wait times in Ontario.
Authors: Zwicker Victoria , Buchman Sandy , Marshall Denise , Urowitz Sara 
Published: February 2017

258 Background: A wait time indicator is being developed for outpatient palliative care services for cancer patients in Ontario. Once developed, this indicator will become the first palliative performance measure for Regional Cancer Centres (RCCs) across the province. The wait time indicator will serve as one measure of accessibility, a key dimension of health care quality. However, in order to create this indicator, it is first necessary to identify targets against which current performance can be compared. Methods: A systematic review of the academic literature was conducted to a) identify existing palliative care wait time standards, and b) to gather evidence on how delays in care impact patient outcomes. An environmental scan was also conducted to identify wait time standards and benchmarks used in other Canadian provinces or territories. In addition, existing palliative care triaging tools and wait time standards from Ontario RCCs were collected. A consensus panel comprised of palliative clinicians, patient and family advisors, and administrators was convened to articulate a maximum acceptable wait time and a provincial target for the percentage of patients who should be seen within the maximum acceptable wait time. Results: The environmental scan and literature review found no existing standards or benchmarks for outpatient palliative care services. However, there are a number of triaging tools and wait time standards in use at Ontario RCCs for these services. Taking these tools and standards into consideration, the consensus panel identified a wait time benchmark and a provincial target for Ontario RCCs. Conclusions: This foundational work will help to highlight gaps and variation in timely access to palliative care services in Ontario. The benchmarks and targets identified through this process as well as the methods used can be useful for other jurisdictions seeking to measure and improve wait times for these services. Next steps include ensuring that data is of sufficient quality, identifying incremental improvement targets for the province based on current performance, and further refining the implementation of a palliative care wait time indicator for quality improvement.
A patient-centered outcome measurement approach for bundled payments in cancer care.
Authors: Spinks Tracy , Lee Seohyun , Shah Kevin , Guzman Alexis B. , Feeley Thomas W. 
Published: February 2017

266 Background: The project aims are to: 1) apply a patient-centered approach to evaluate quality of care in a bundled payment pilot for head & neck cancer; and, 2) measure quality at the condition-level; and, 3) incorporate patient-reported outcomes (PRO) in routine quality assessments. A three-tiered outcomes hierarchy developed by Michael Porter of Harvard Business School is used to define outcome measures, to be used for quality improvement and reporting during the pilot. Porter’s model evaluates outcomes over the full cycle of care, examining: (1) health status achieved/retained; (2) recovery process; and, (3) health sustainability. [Porter, M.E. (2010). What is value in health care? N Engl J Med, 363(26), 2477-2481. doi: 10.1056/NEJMp1011024.] Methods: An 11-member team of clinical, quality, data, and IT experts identified measure concepts, developed measure specifications, and implemented reporting. The project lead interviewed clinical experts to gain consensus around a focused set of measures and benchmarks. Measures were evaluated for importance to patients using feedback from patient focus groups. The team defined the measure specifications (numerator, denominator, etc.), selected a validated PRO instrument, and developed the work flow and tools for data collection and reporting. Process maps were created for training and reference purposes, and clinic staff trained. Testing was completed prior to implementation, with periodic process checks and additional staff training, as needed. Results: Measure development and implementation were completed using a streamlined approach over a 6-month period and required 12 team meetings before implementation. The project leveraged existing data streams, where possible, and IT development focused on quick-turnaround solutions. Conclusions: The project demonstrated that patient-centered outcomes measures can be developed and implemented in a compressed time frame. With provider and patient input, the measures focused on outcomes that are important to patients and actionable by clinicians. This created a scalable framework to be implemented in other disease sites and integrated into our EHR.
Treatment patterns of patients with metastatic colorectal cancer in a large national U.S. claims-based data.
Authors: Zhong Yue , Kamalakar Rajesh , Asche Carl V , Anderson Sibyl , Seal Brian S. 
Published: February 2017

268 Background: FDA approved therapeutic choices for patients with metastatic colorectal cancer (mCRC) have evolved, including cytotoxic agents such as 5-fluorouracil (5-FU)/ leucovorin or levoleucovorin (LV), capecitabine, oxaliplatin, and irinotecan, biological agents such as bevacizumab, cetuximab, panitumumab, and aflibercept, as well as regorafenib, an oral multi-kinase inhibitor. The present study examined treatment patterns among patients with mCRC. Methods: We identified patients aged 18 or older with at least one primary CRC diagnosis between 01/01/2008 and 03/31/2012 in the MarketScan databases. mCRC patients were identified if claims indicated the presence of distant metastases (ICD-9-CM codes: 196.x, 197.0 to 197.4, 197.6 to 197.8, 198.x, and 199.0). All systemic treatment claims were extracted during 60 days after initiation of treatment. Patients were followed for more than 6 months, until end of enrollment or study end date (03/01/2013) to capture type and number of treatment lines (TLs). We also assessed regimen compliance to the current National Comprehensive Cancer Network (NCCN) treatment standards. Results: Of the total 2,934 mCRC patients retained, 2,046 (69.7%) received at least one TL: 801 (39.1%) patients with one TL, 679 (33.2%) with two TLs, and 566 (27.7%) with three or more TLs. For patients receiving first-line treatment, the most common regimens prescribed were FOLFOX (19.1%), FOLFOX+ bevacizumab (18.6%), and 5-FU/LV (17.8%). For patients receiving second-line treatment (60.9%), FOLFOX (14.1%), FOLFOX+ bevacizumab (11.0%), and FOLFIRI+bevacizumab (11.0%) were most frequently prescribed. Treatment regimens varied in patients receiving three or more TLs. FOLFIRI + bevacizumab was most frequently prescribed in the third TL (16.8%). Proportion of patients receiving NCCN-recommended regimens was 81.7% for first TL, 54.4% for second TL, and 25.3% for third TL. Conclusions: About one third of mCRC patients didn’t receive any treatment. Among mCRC patients with treatment, two thirds received at least two TLs. FOLFOX (+/-biologics) was the most frequently prescribed first and second TL. Only a quarter of patients received NCCN-recommended regimens in the third TL.
Quality measures that focus on patient and family engagement in oncology.
Authors: Song Kyung Min , Mitchell Kristi 
Published: February 2017

270 Background: National Quality Strategy set forth by the Department of Health and Human Services emphasizes that each person and family is engaged as partners in their care. Appropriate use of quality measures can serve as a means of achieving this. Studies have shown that patient engagement can lead to improved healthcare outcomes, lower resource utilization, and reduced costs. As such, Avalere sought to identify oncology-related quality measures that address patient and family engagement, and determine ways to advance engagement in oncology through the use of quality measures. Methods: Avalere assessed publicly available sources to identify person and family engagement measures related to oncology, including measures related to patient education, care preferences, and care planning. Avalere also assessed the current use of these measures in CMS’ quality programs. Results: Avalere identified six oncology-specific measures related to person and family engagement. One of the measures is included in CMS’ Physician Quality Reporting System and the Electronic Health Record Incentive Programs. Three measures identified are related to documenting patients’ preferences during end of life care, two are related to care planning for pain and depression, respectively, and one is related to patient education on treatment. None of the measures are related to specific cancers. Conclusions: Avalere found lack of measures related to patient and family engagement in oncology. Given the importance of patient and family engagement during the course of disease management, opportunity exists to improve oncology care quality through measurement and evaluation of engagement. Oncology patients’ quality of care can be improved through data support, stakeholder buy-in, standardized methodology for measuring engagement, evidence linking engagement and outcomes, and implementation measures in incentive programs.