bluuebunny/crossref_metadata_2025_split huggingface dataset:
A methodology for integrating unconventional geologic and engineering data into a geocellular model
Authors: Tamulonis Kathryn 
Published: October 2019

Unconventional field development and well performance analysis encompass multiple disciplines and large data sets. Even when seismic and other data sets are not available, geologists can build geocellular models to determine factors that improve operational efficiency by incorporating well log, geosteering, stratigraphic, structural, completion, and production data. I have developed a methodology to integrate these data sets from vertical and horizontal wells to build a sequence stratigraphic and structurally framed geocellular model for an unconventional Marcellus Formation field in the Appalachian Basin, USA. The model would benefit from additional data sets to perform a rigorous investigation of performance drivers. However, the presented methodology emphasizes the value of constructing geocellular models for fields with sparse data by building a geologically detailed model in a field area without seismic and core data. I used third-order stratigraphic sequences interpreted from vertical wells and geosteering data to define model layers and then incorporate completion treating pressures and proppant delivered per stage into the model. These data were upscaled and geostatistically distributed throughout the model to visualize completion trends. Based on these results, I conclude that geologic structure and treating pressures coincide, as treating pressures increase with stage proximity to a left-lateral strike-slip fault, and completion trends vary among third-order systems tracts. Mapped completion issues are further emphasized by areas with higher model proppant values, and all treating pressure and proppant realizations for each systems tract have the greatest variance away from data points. Similar models can be built to further understand any global unconventional play, even when data are sparse, and, by doing so, geologists and engineers can (1) predict completion trends based on geology, (2) optimize efficiency in the planning and operational phases of field development, and (3) foster supportive relationships within integrated subsurface teams.
Metrics to evaluate the performance of cancer center leadership.
Authors: Halpern Michael T. , Gasoyan Hamlet , Aaronson William E. 
Published: October 2019

10 Background: Cancer centers are diverse health care organizations that involve clinicians and researchers focused on understanding, treating, and controlling cancer in the populations they serve. While there are many metrics used to evaluate cancer center performance, few standardized measures have been identified to evaluate the performance of cancer center leadership. The goal of this manuscript is to systematically identify, compare, and categorize metrics used to evaluate the leadership of U.S. cancer centers. Methods: We performed a structured, systematic electronic search of peer-reviewed journals using Medline to identify English language articles discussing metrics used to evaluate cancer center leadership. Identified studies were reviewed by two independent reviewers to determine appropriateness for inclusion. Metrics were classified using ten a priori-defined categories of evaluation for data abstraction. Results: We included 34 manuscripts in this review. The most commonly-discussed evaluation metric category is organizational strategy/planning (31 of the 34 papers), followed by leader characteristics (25 papers), clinical performance (21), and facility characteristics (20). Organizational strategy/planning include governance structure; strategic development; quality assurance/improvement; mission/vision; business planning; and program development. Leader characteristic metrics include communication; vision/strategic thinking; personal skills; team coordination; leadership style; and staff development. Clinical Performance metrics focus on delivery of and outcomes from clinical services while facility characteristics include space allocation and access to support services. Conclusions: The metrics reviewed and synthesized in this report may be considered measurable outcomes to evaluate whether cancer center leadership demonstrates key competencies. Additional research is needed to explore the link between metrics used to evaluate cancer center leaders, the desired competencies for healthcare leaders, and objective measures of whether a cancer center is “successful”.
Comparing health utility scores, treatments, and outcomes in lung cancer patients with rare EGFR mutations with those with exon 19 deletion (del) and L858R mutations.
Authors: Dodbiba Lorin , Hueniken Katrina , Jiang Shirley Xue , Chan Sze Wah Samuel , Smith Elliot Charles , Eng Lawson , Patel Devalben , Razooqi Maryam , Brown M. Catherine , Shepherd Frances A. , Leighl Natasha B. , Bradbury Penelope Ann , Xu Wei , Sacher Adrian G. , Liu Geoffrey 
Published: October 2019

102 Background: Precision oncology divides patients into smaller cohorts each with unique characteristics, treatment and outcomes. Cost-effectiveness assessments that rely on quality-adjusted life years will require mutation-specific health utility scores (HUS). We assessed the impact of having exon 19 del, L858R and rare EGFR mutations on outcomes and HUS. Methods: From a retrospective database of 719 patients with EGFR mutations, specific baseline EGFR mutations, clinicodemographic and treatment characteristics, and outcomes (overall survival, OS; progression-free survival, PFS) were analyzed using Cox models (adjusted hazard ratios, HR). In a subset of 289 patients with metastatic disease, serial HUS data collected through EQ-5D-5L at clinic visits were compared by mutation using t-tests. Results: Of 380 (53%) patients with exon 19 del, 288 (40%) with L858R, and 51 (7%) with rare mutations (mostly G719A/C, Exon 18 or 20 insertion, L861Q, compound mutations): 68% were female; median age was 74 years; 51% were Asian; and 74% were never smokers. In 334 Stage I-III pts, recurrence-free survival was not associated with specific mutations. In contrast, among 365 stage IV pts on TKIs, when compared to a reference of patients with exon 19 del, outcomes were worse in patients with L858R mutations (PFS: 1.35, 95% CI 1.1-1.7; OS: HR 1.39, 95% CI 1.0-1.9) and for rare mutations (PFS: 1.16 95% CI 0.7-1.9; OS: 1.45 95% CI 0.7-2.9). From an analysis of 1064 clinic encounters, different TKIs were used in similar proportions by mutation. In stable disease, mean HUS [SEM] were 0.80 [0.008] (exon 19), 0.81 [0.009] (L858R), and 0.82 [0.02] (rare mutation). Progressive disease led to significant drops in mean HUS for exon 19 (0.76 [0.01]; p = 0.01 compared to stable disease) and L858R, mean HUS = 0.74 [0.02] p < 0.001, but less so for rare mutations, mean HUS = 0.79 [0.05] p = 0.65. Conclusions: Patients in this EGFR mutated cohort had similar exposures of different TKI therapy regardless of specific EGFR mutation. L858R and rare mutations had inferior survival outcomes but similar HUS as patients with exon 19 del mutations.
Evaluating end-of-life (EOL) care at the University of Rochester Medical Center (URMC) using quality oncology practice initiative (QOPI) metrics.
Authors: Banerjee Titas , Mendler Jason Harold , Badri Nabeel , Hettler Dwight , Berkhof Julie Ann , Abbas Karen J. , Lekkala Manidhar Reddy , Moftakhar Bahar , Welaya Karim , Treptow Carissa , Babu Dilip Sankar , Baumgart Megan 
Published: October 2019

12 Background: Inpatient mortality, defined as death within 30 days of an acute hospital admission, is often used as a quality benchmark for healthcare institutions and is an important metric for evaluating quality of care of patients with advanced malignancies. In this study we aimed to utilize QOPI performance data to identify areas of weakness in our practice that may contribute to inpatient mortality. Methods: We analyzed 11 EOL measures within the QOPI database which we collected between 2015 and 2018. These included all EOL measures related to hospice enrollment (measure IDs 42-47), chemotherapy administered within the last 2 weeks of life (ID 48), percentage of patients who died from cancer with at least one emergency department (ED) visit in the last 30 days of life (ID 49ed), and the percentage of patients who died from cancer admitted to the Intensive Care Unit (ICU) in the last 30 days of life (ID 49icu). Our rate was calculated for each measure and compared against QOPI aggregate data. We used a fisher’s exact test to determine statistical significance for each metric. Results: The number of patients from our institution included in each analysis ranged from 27 to 46. Compared to our peers, patients treated at our institution were more likely to visit an ED in the last 30 days of life (68% vs. 32%; P < 0.0001), more likely to be admitted to the ICU in the last 30 days of life (29% vs. 9%; P = 0.0003), and more likely to be enrolled on hospice within the last 7 days of death (63% vs. 32%; P = 0.001). Conclusions: Analysis of QOPI EOL performance scores identified several metrics that may contribute to inpatient mortality at URMC. Ongoing participation in QOPI with a focus on EOL metrics will strengthen this analysis. We plan to use this data to guide quality improvement initiatives aimed at reducing impatient mortality and improving end of life care at our institution.
Costs after incident breast cancer diagnosis among high-deductible health plan members.
Authors: Wharam James , Wallace Jamie , Lu Christine , Wagner Anita K. , Soumerai Stephen , Earle Craig , Nekhlyudov Larissa , Ross-Degnan Dennis , Zhang Fang 
Published: October 2019

120 Background: High-deductible health plans (HDHP) are associated with breast cancer treatment delays of up to 10 months, but their impact on health outcomes is unknown. We hypothesized that, compared with women in generous plans, HDHP members would present with more advanced disease and thus experience higher total costs of early care. Methods: We studied 2004-2014 claims data from a large US health insurer. We included women aged 25-64 who were in traditional low-deductible (≤$500) health plans for 1 baseline year then experienced either an employer-mandated switch to HDHPs (≥$1000) for up to 4 or years or an employer-mandated continuation in low deductible plans. We defined the HDHP switch date as the index date. We then restricted to women who developed incident breast cancer after the index date. Using baseline characteristics, we closely matched HDHP members with incident breast cancer to contemporaneous women with incident breast cancer who remained in low-deductible plans. We measured total costs of all health care services in the 60 days after incident breast cancer diagnosis as a proxy for the intensity of incident breast cancer care. We used negative binomial regression adjusted for baseline characteristics to compare total 60-day costs among HDHP and control members. We also subset analyses to low-income women. Results: We included 1514 HDHP members and 9283 matched controls. 60-day costs after incident breast cancer diagnosis were $24,151 (95% CI: $22,766, $25,535) among HDHP members and $22,474 ($21,952, $22,996) among controls, an absolute difference of $1677 ($197, $3156) and a relative difference of 7.5% (8.1%, 14.1%). Low-income HDHP members had corresponding absolute and relative differences of $2653 ($368, $4939) and 12.5% (1.5%, 23.5). Conclusions: HDHP members with incident breast cancer had 7.5% higher health care costs in the 60 days after incident breast cancer than women with more generous coverage, a finding driven 12.5% higher costs among low-income HDHP members. Results raise concerns that delays in breast cancer care among HDHP members are associated with more advanced disease and adverse outcomes.
The association between health insurance coverage disruptions and access to care and affordability among cancer survivors in the United States.
Authors: Zhao Jingxuan , Han Xuesong , Nogueira Leticia Maciel , Jemal Ahmedin , Yabroff K Robin 
Published: October 2019

121 Background: Having health insurance is a strong predictor of access to care and affordability. To date, most studies evaluating the effects of insurance coverage measured it only at a single time point. Little is known about the effects of coverage disruptions. This study aims to assess associations of a health insurance coverage disruption with access and affordability among cancer survivors in the United States. Methods: We identified 6476 cancer survivors aged 18-64 years with current health insurance coverage from the 2011-2017 National Health Interview Survey. Coverage disruption was measured by the question “In the past 12 months, was there any time when you did not have any health insurance or coverage?”. Access to care and affordability was measured by: 1) preventive services use (e.g. blood pressure check); and 2) forgoing care because of cost, respectively, in the past 12 months. We used separate multivariable logistic models to evaluate the associations between a coverage disruption and healthcare access and affordability, by current health insurance coverage. Results: Among survivors with current health insurance coverage, 3.7% of those with private and 8.1% with public insurance reported a coverage disruption in the past 12 months. Among survivors with current private coverage, those with a recent coverage disruption reported lower likelihood of any preventive services use (OR = 0.1, 95% CI: 0.1-0.3) and higher likelihood of forgoing any care because of cost (OR = 6.0, 95% CI: 3.9-9.5) compared to those with continuous private coverage. Among survivors with current public coverage, those with a recent coverage disruption reported lower likelihood of any preventive services use (OR = 0.4, 95% CI: 0.2-0.9) and higher likelihood of forgoing any care because of cost (OR = 4.3, 95% CI: 2.5-7.3) compared to those with continuous public coverage. Conclusions: Currently insured cancer survivors with a recent health insurance coverage disruption were more likely to report problems in access to care and affordability compared to the continuously insured. Improving private and public insurance coverage continuity may be effective in addressing these problems.
Barriers and facilitators to the implementation of routine ototoxicity screening for head and neck cancer patients.
Authors: Bapat Priya , Chow Pansy , Hueniken Katrina , Mahler Mary , Brown M. Catherine , Falls Carolyn , Hope Andrew J. , Hansen Aaron Richard , Goldstein David Paul , Rutka John , Howell Doris , Xu Wei , Liu Geoffrey 
Published: October 2019

127 Background: Ototoxicity after cisplatin +/- radiation occurs in 22-58% of patients with head and neck cancers. Routine post-treatment hearing tests are useful in the early detection of hearing loss, allowing for possible early intervention. This study aimed to identify current hearing screening practices for follow-up, barriers to screening, and recommendations for its implementation. Methods: Stakeholders (physicians, nurses, coordinators, audiologists) identified barriers and facilitators to the implementation of a routine hearing screening follow-up program at Princess Margaret Cancer Centre. Themes were identified using an inductive approach and mapped to the Knowledge to Action (KTA) framework, which guides the implementation of new clinical practices. Results: The problem: While all patients received baseline hearing tests, follow-up testing was inconsistently performed in asymptomatic patients. Patients may also lack awareness of subclinical hearing loss. A formalized follow-up hearing test program was identified as the best approach by stakeholders. Barriers: Individual-level barriers included limited knowledge about intervals for hearing testing and lack of time during clinic visits. Institutional-level factors included personnel, financial resources and logistical supports. Patient travel distances and times were barriers, as well as scheduling tests on the same day as other clinic visits. Societal stigma of hearing loss was a possible barrier. Facilitators: These included greater staff and patient education, and designating a local clinic champion. Instructions for follow-up after identifying hearing loss was deemed essential. Adapting to the local context: Automated flagging post-treatment and auto-referrals to the Hearing Clinic through the electronic medical record system could facilitate increased rates of participation. Mail/phone reminders could be useful adjuncts. Conclusions: Participants supported a formal post-treatment hearing test program for patients with head and neck cancers treated with cisplatin +/- radiation. Individual and institutional barriers were identified, but could be mitigated by appropriate facilitators.
Patterns of palliative symptom management (PSM) medication use at end-of-life (EoL) among Medicare beneficiaries with advanced lung cancer (advLC).
Authors: Davidoff Amy J. , Prsic Elizabeth Horn , Saphire Maureen , Canavan Maureen , Wang Shi-Yi , McCorkle Ruth , Presley Carolyn J 
Published: October 2019

130 Background: Patients with advLC experience high symptom burden; undertreatment may result in poor quality of life for patients and caregivers. Hospice enrollment often happens late or not at all, yet little is known about EoL outpatient PSM medication use in the non-hospice setting. Methods: Using SEER-Medicare linked registry and claims data, we selected decedents diagnosed with advLC between 2008-2013 who survived ≥6 months (death between 2008-2014). Using non-hospice claims, we identified receipt of oral and parenteral medications to manage symptoms such as pain (any pain medications, any opioids), nausea/ vomiting and dyspnea at 6 (EoL-6) and 1 (EoL-1) months prior to death. Antiemetics were excluded if concurrent with chemotherapy (CTx). T-tests compared sample proportions receiving PSM between EoL-6 and EoL-1. Logistic regression estimated associations between PSM medication receipt at EoL-1 and patient demographic characteristics, comorbidity, and ongoing CTx or radiation. Results: We identified 16,246 decedents: mean age 77 years, 50% male, and 81% non-Hispanic white. PSM medication for individual symptom areas increased from EoL-6 to EoL-1 [Table]. Adjusted results indicate that pain medication receipt was higher for females, and patients with multimorbidity, dual Medicare/Medicaid, higher poverty, living in rural areas, and receiving concurrent radiation but lower among those with increasing age and for non-white race/ethnicity groups. We saw similar trends for PSM using opioids, and for emotional distress, and dyspnea. Conclusions: Among patients with advLC at EoL, medication use for symptom relief was common and increasing toward EoL-1. Lower use by males, older adults, and non-whites may reflect poor access or poor patient-provider communication. Further research is needed to assess adequacy of PSM in the outpatient setting. [Table: see text]
Specialized new patient scheduling unit to improve patient access.
Authors: Philip Tony , Gleason Karen , Weisman Rosemarie 
Published: October 2019

131 Background: New patient unit is responsible for scheduling initial appointment, obtaining pertinent medical records and pathology slides prior to initial visit. Original workflow utilized dedicated schedulers to answer new patient appointment phone calls and emails, obtain patient demographics, brief medical history, and financial counseling referral. A separate chart preparation team gathered records for clinical review by two nurse navigators the day prior to the appointment. There were on average 6 patients/day waiting for appointments on the Pending List and phone wait times were thought to contribute to abandoned call rate and missed appointments. Methods: A workgroup of administrators, schedulers and clinicians was formed to redesign the workflow. The new workflow, starting April 2018, combined new patient and chart preparation team and divided them into three disease specific scheduling teams. Based on appointment volume, there is Team 1 Breast/GYN, Team 2 GI/GU/Thoracic/Head & Neck, Team 3 Malignant/Benign Hematology. Team members are responsible for answering phones, completing intake, and gathering records customized to needs of the specific care teams and enabled nurse navigator to be deployed elsewhere. Results: New workflow has reduced call volume, wait time, call abandonment and no show rates with increased new patient visits. Conclusions: Creating sub-specialty based scheduling teams to work with the clinical team has improved patient access to cancer care and reduced wait time. Further steps are being taken to further streamline process. [Table: see text]
Financial hardship associated health care utilization among cancer survivors in the United States.
Authors: Zheng Zhiyuan , Tucker-Seeley Reginald , Han Xuesong , Zhao Jingxuan , Banegas Matthew P. , Rai Ashish , Jemal Ahmedin , Yabroff K Robin 
Published: October 2019

133 Background: A cancer diagnosis is associated with medical financial hardship in the U.S. However, little is known about health consequences associated with financial hardship. This study examines associations between medical and non-medical financial hardship on healthcare utilization among cancer survivors. Methods: We used the National Health Interview Survey (2013-2017) to identify cancer survivors (18-64 years: n = 5200; 65+ years: n = 7326). Medical financial hardship included material (e.g., problems paying medical bills), psychological (e.g., worry about medical bills), and behavioral (e.g., forgoing care due to cost) domains, and non-medical financial hardship included food hardship and worry for other financial needs (e.g. retirement, monthly bills, standard of living, and housing costs). We compared cancer survivors by intensities of medical and non-medical financial hardships in: 1) emergency department (ED) visits; 2) preventive services use (receipt of influenza vaccine, and blood pressure/cholesterol screenings); and 3) cervical/breast/colorectal cancer screenings among eligible cancer survivors. We used generalized ordinal logistic regressions, controlling for demographic characteristics, time since diagnosis, number of cancer diagnoses, insurance, income, and comorbidities. Results: Across age groups, both higher medical and non-medical hardship intensities were associated with higher ED visits and lower use of preventive services. Compared to cancer survivors with lowest intensity, higher percentages of ED visits were observed among those with highest medical hardship intensity (ages 18-64: 42% vs 26.2%; ages 65+: 37.2% vs 27.9%, all p < .01) and highest non-medical hardship intensity (ages 18-64: 37.6% vs 24.3%, p = .01). Moreover, compared to lowest intensity, highest medical hardship intensity was associated with lower influenza vaccination (ages 18-64: 45.6% vs 52.5%; ages 65+: 64.6% vs 75.6%, p < .05) and breast cancer screening (54.4% vs 65.9%, p < .05). Conclusions: Cancer survivors with higher medical and non-medical financial hardships have more ED visits and medical financial hardship was also associated with less use of preventive services and some cancer screening.