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Vertical heterogeneity in the physical characteristics of lakes and oceans is ecologically salient and exploited by a wide range of taxa through diel vertical migration to enhance their growth and survival. Whether analogous behaviors exploit horizontal habitat heterogeneity in streams is largely unknown. We investigated fish movement behavior at daily timescales to explore how individuals integrated across spatial variation in food abundance and water temperature. Juvenile coho salmon made feeding forays into cold habitats with abundant food, and then moved long distances (350-1300 m) to warmer habitats that accelerated their metabolism and increased their assimilative capacity. This behavioral thermoregulation enabled fish to mitigate trade-offs between trophic and thermal resources by exploiting thermal heterogeneity. Fish that exploited thermal heterogeneity grew at substantially faster rates than did individuals that assumed other behaviors. Our results provide empirical support for the importance of thermal diversity in lotic systems, and emphasize the importance of considering interactions between animal behavior and habitat heterogeneity when managing and restoring ecosystems.

The root causes of regional variation in medical spending are poorly understood and vary by clinical condition. To identify drivers of regional spending variation for Medicare patients with advanced cancer, we used linked Surveillance, Epidemiology, and End Results program (SEER)-Medicare data from the period 2004-10. We broke down Medicare spending into thirteen cancer-relevant service categories. We then calculated the contribution of each category to spending and regional spending variation. Acute hospital care was the largest component of spending and the chief driver of regional spending variation, accounting for 48 percent of spending and 67 percent of variation. In contrast, chemotherapy accounted for 16 percent of spending and 10 percent of variation. Hospice care constituted 5 percent of spending. However, variation in hospice spending was fully offset by opposing variation in other categories. Our analysis suggests that the strategy with the greatest potential to improve the value of care for patients with advanced cancer is to reduce reliance on acute hospital care for this patient population.

Background Loot boxes are randomized reward mechanics in modern video games that share features with conventional gambling products. Research studies have begun to test longitudinal patterns (“migration”) from engagement with loot boxes to gambling behavior. This study investigated such effects at a 6-month follow-up in an online sample of young adults that play video games (aged 19—25) from British Columbia, Canada. Methods Participants were stratified into two subgroups at their baseline assessment: 83 reported they did not currently gamble and 43 reported they currently gamble, after cleaning. At baseline, participants provided responses to the Risky Loot Box Index (RLI) and estimates of their past year spending on both randomized (i.e., loot boxes) and non-randomized (“direct purchase”) microtransactions. Microtransaction spending and RLI scores at baseline were tested as predictors of self-identified gambling initiation and spend at follow-up. We tested a set of frequentist regressions and a corresponding set of Bayesian regressions. Results At baseline, participants who reported gambling showed higher levels of engagement with both randomized and non-randomized microtransactions. Among non-gambling participants at baseline, loot box spending and RLI predicted gambling initiation at the follow-up, in a Bayesian logistic regression with informed priors. Loot box spending and RLI at baseline predicted gambling expenditure at follow-up, in both the frequentist and Bayesian linear regressions. Spending on direct purchase microtransactions did not predict gambling initiation in either set of models when controlling for loot box spending, underscoring the role of randomized rewards. Conclusions These data provide further prospective evidence for gambling ‘migration’ in a sample recruited in Western Canada, indicating that young adults who spend money on loot boxes are at elevated risk for real-money gambling.

ObjectiveMeasures of variation in end-of-life (EOL) care intensity across hospitals are typically summarised using unidimensional measures. These measures do not capture the full dimensionality of complex clinical care trajectories over time that are needed to inform quality improvement efforts. The objective is to develop a novel visual map of EOL care trajectories that illustrates multidimensional utilisation over time.SettingUnited States’ National Cancer Institute or National Comprehensive Cancer Network (NCI/NCCN)-designated hospitals.ParticipantsWe identified Medicare claims for fee-for-service beneficiaries with poor prognosis cancers who died between April and December 2016 and received the preponderance of treatment in the last 6 months of life at an NCI/NCCN-designated hospital.DesignFor each beneficiary, we transformed each Medicare claim into two elements to generate a two-dimensional individual-level heatmap. On the y-axis, each claim was classified into a categorical description of the service delivered by a healthcare resource. On the x-axis, the date for each claim was converted into the day number prior to death it occurred on. We then summed up individual-level heatmaps of patients attributed to each hospital to generate two-dimensional hospital-level heatmaps. We used four case studies to illustrate the feasibility of interpreting these heatmaps and to shed light on how they might be used to guide value-based, quality improvement initiatives.ResultsWe identified nine distinct EOL care delivery patterns from hospital-level heatmaps based on signal intensity and patterns for inpatient, outpatient and home-based hospice services. We illustrate that in most cases, heatmaps illustrating patterns of multidimensional healthcare utilisation over time provide more information about care trajectories and highlight more heterogeneity than current unidimensional measures.ConclusionsThis study illustrates the feasibility of representing multidimensional EOL utilisation over time as a heatmap. These heatmaps may provide potentially actionable insights into hospital-level care delivery patterns, and the approach may generalise to other serious illness populations.

Background Oncology outreach is a common strategy for increasing rural access to cancer care, where traveling oncologists commute across healthcare settings to extend specialized care. Examining the extent to which physician outreach is associated with timely treatment for rural patients is critical for informing outreach strategies. Methods We identified a 100% fee-for-service sample of incident breast cancer patients from 2015 to 2020 Medicare claims and apportioned them into surgery and adjuvant therapy cohorts based on treatment history. We defined an outreach visit as the provision of care by a traveling oncologist at a clinic outside of their primary hospital service area. We used hierarchical logistic regression to examine the associations between patient receipt of preoperative care at an outreach visit (preoperative outreach) and > 60-day surgical delay, and patient receipt of postoperative care at an outreach visit (postoperative outreach) and > 60-day adjuvant delay. Results We identified 30,337 rural-residing patients who received breast cancer surgery, of whom 4071 (13.4%) experienced surgical delay. Among surgical patients, 14,501 received adjuvant therapy, of whom 2943 (20.3%) experienced adjuvant delay. In adjusted analysis, we found that patient receipt of preoperative outreach was associated with reduced odds of surgical delay (odds ratio [OR] 0.75, 95% confidence interval [CI] 0.61–0.91); however, we found no association between patient receipt of postoperative outreach and adjuvant delay (OR 1.04, 95% CI 0.85–1.25). Conclusions Our findings indicate that preoperative outreach is protective against surgical delay. The traveling oncologists who enable such outreach may play an integral role in catalyzing the coordination and timeliness of patient-centered care.

BackgroundDelays between breast cancer diagnosis and surgery are associated with worsened survival. Delays are more common in urban-residing patients, although factors specific to surgical delays among rural and urban patients are not well understood.MethodsWe used a 100% sample of fee-for-service Medicare claims during 2007–2014 to identify 238,491 women diagnosed with early-stage breast cancer undergoing initial surgery and assessed whether they experienced biopsy-to-surgery intervals > 90 days. We employed multilevel regression to identify associations between delays and patient, regional, and surgeon characteristics, both in combined analyses and stratified by rurality of patient residence.ResultsDelays were more prevalent among urban patients (2.5%) than rural patients (1.9%). Rural patients with medium- or high-volume surgeons had lower odds of delay than patients with low-volume surgeons (odds ratio [OR] = 0.71, 95% confidence interval [CI] = 0.58–0.88; OR = 0.74, 95% CI = 0.61–0.90). Rural patients whose surgeon operated at ≥ 3 hospitals were more likely to experience delays (OR = 1.29, 95% CI = 1.01–1.64, Ref: 1 hospital). Patient driving times ≥ 1 h were associated with delays among urban patients only. Age, black race, Hispanic ethnicity, multimorbidity, and academic/specialty hospital status were associated with delays.ConclusionsSociodemographic, geographic, surgeon, and facility factors have distinct associations with > 90-day delays to initial breast cancer surgery. Interventions to improve timeliness of breast cancer surgery may have disparate impacts on vulnerable populations by rural-urban status.

Stream-dwelling fishes inhabit river networks where resources are distributed heterogeneously across space and time. Current theory emphasizes that fishes often perform large-scale movements among habitat patches for reproduction and seeking refugia, but assumes that fish are relatively sedentary during growth phases of their life cycle. Using stationary passive integrated transponder (PIT)-tag antennas and snorkel surveys, we assessed the individual and population level movement patterns of two species of fish across a network of tributaries within the Wood River basin in southwestern Alaska where summer foraging opportunities vary substantially among streams, seasons, and years. Across two years, Arctic grayling (Thymallus arcticus) and rainbow trout (Oncorhynchus mykiss) exhibited kilometer-scale movements among streams during the summer growing season. Although we monitored movements at a small fraction of all tributaries used by grayling and rainbow trout, approximately 50% of individuals moved among two or more streams separated by at least 7 km within a single summer. Movements were concentrated in June and July, and subsided by early August. The decline in movements coincided with spawning by anadromous sockeye salmon, which offer a high-quality resource pulse of food to resident species. Inter-stream movements may represent prospecting behavior as individuals seek out the most profitable foraging opportunities that are patchily distributed across space and time. Our results highlight that large-scale movements may not only be necessary for individuals to fulfill their life-cycle, but also to exploit heterogeneously spaced trophic resources. Therefore, habitat fragmentation and homogenization may have strong, but currently undescribed, ecological effects on the access to critical food resources in stream-dwelling fish populations.

PurposeClinical trials in oncology evaluating the effects of patient-reported outcomes (PRO) collection have found that monitoring of symptoms with PROs is associated with improved clinical care through reduced acute care utilization and decreased patient symptom burden. This educational review will evaluate strategies for systematic PRO integration into everyday oncology clinical practice.MethodsWe outline key considerations for using PROs in clinical practice, highlighting evidence from published studies. We also discuss the benefits and challenges of PRO implementation in oncology.ResultsImplementing PRO collection in clinical practice can improve care delivery and facilitate patient-centered clinical research. Considerations for using PROs in clinical practice include choice of instrument, method of delivery, and frequency of query. Challenges with implementing systematic PRO collection include the costs and resources needed for implementation, impact on clinical workflow, and controlling/monitoring physician burnout.ConclusionsWhile challenges exist in terms of financial resources and staff participation/burnout, patient-reported outcomes in clinical practice provide a number of benefits, including symptom monitoring, clinical research, and potential real-time personalized clinical-decision support.

Oncology outreach is a common strategy for addressing cancer workforce shortages, where traveling oncologists commute across healthcare settings to extend specialized care. However, methods for evaluating and optimizing outreach strategies are limited. We developed a simulation framework for evaluating and optimizing potential outreach strategies and applied it to two test cases within Dartmouth Health's hub-and-spoke cancer system. Our approach involved sampling incident patients and visit capacity across oncologist/site pairs, assigning patients to oncologist/site pairs, and estimating the total patient travel time incurred across two groups: (1) where a portion of patient visits is shifted from the hub facility to a satellite, and (2) where the original distribution of patient visits is retained. After 5000 simulations, the mean difference in patient travel time among groups was computed to estimate patient travel time savings. We identified the optimal number of new patient visits to reallocate from the hub to satellite that maximized patient travel time savings. We identified satellites in St. Johnsbury, VT and Manchester, NH as candidates for increased medical and radiation oncology outreach, respectively. At St. Johnsbury, we found that reallocating 45% of new medical oncology visits resulted in 140 (95% CI: 97-174) total hours saved. For patients whose care was shifted, this corresponded to an average of 1.07 (95% CI: 0.75-1.34) hours saved per visit. At Manchester, we found that reallocating 50% of new radiation oncology visits resulted in 55 (95% CI: 34-71) total hours saved. For patients whose care was shifted, this corresponded to an average of 1.13 (95% CI: 0.70-1.44) hours saved per visit. Simulations offer a valuable means to assess the effectiveness and uncertainty of potential outreach strategies. Such approaches are well positioned to provide administrative decision support for health systems and can be leveraged to inform directional investments in outreach policies.

Cancer care relies on effective coordination within a multidisciplinary care team. Changes to teams due to departures remain understudied despite rising oncologist turnover in the United States. In this study, we aimed to investigate the impact of oncologist departures on the remaining care team members. We used Medicare claims associated with beneficiaries aged 66–99 to identify physicians involved in care for common cancer types (i.e., breast, lung, and colorectal cancer). We restricted our analysis to medical oncologists, radiation oncologists, and surgeons specializing in oncology (collectively, “oncologists”). We identified oncologists who left a practice location in 2017–2019 using the Medicare Carrier file and linked them to retained oncologists based on shared patients. Multivariable hierarchical linear regression was used to investigate how retained oncologists’ patient-sharing patterns changed after a colleague’s departure. Our results support that retained rural-practicing oncologists experienced an expansion and restructuring of their patient-sharing ties following oncologist departures while retained urban-practicing oncologists experienced a consolidation. Network restructuring may demonstrate an adaptive response that ensures patient continuity of care, but it may also reflect unique challenges faced by oncologists practicing in rural versus urban settings.