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Clinical studies have linked usage of progestins (synthetic progesterone) to breast cancer risk. However, little is understood regarding the role of native progesterone (P4), signaling through the progesterone receptor (PR), in breast tumor formation. Recently, we demonstrated that P4 treatment or PR overexpression can drive changes in immune cell populations in the murine mammary gland and that PR overexpression leads to increased development of mammary gland tumors in mice. Given these findings, we sought to investigate whether P4 impacts tumor growth and immune cell infiltration of mammary gland tumors. We utilized syngeneic mammary gland tumor models to evaluate the effect of P4 on PR+ mammary gland tumor growth, which revealed that P4 promoted tumor growth and impacted immune cell infiltration of PR+ mammary gland tumors. Of note, numbers of tumor-infiltrating dendritic cells were decreased and exhausted T cells and regulatory T cells were increased with P4 treatment in PR+ tumors. To determine if anti-progestin therapies could reverse the growth-promoting effect of P4 on mammary gland tumors, mice bearing PR+ mammary gland tumors were treated with the anti-progestin onapristone. Onapristone treatment led to significantly decreased tumor volumes in two syngeneic mammary gland tumor models and reversed the effect that P4 had on tumor-infiltrating regulatory T cells. To determine if inhibition of tumor growth by onapristone was immunologically mediated, SCID mice bearing PR+ mammary gland tumors were treated with onapristone. Results revealed a decreased ability of onapristone to inhibit tumor growth in SCID mice compared to immunocompetent mice, suggesting that inhibition of tumor growth is, in part, immunologically mediated. These findings offer a novel mechanism of P4-driven mammary gland tumor development and provide rationale in investigating the usage of anti-progestin therapies to promote immune-mediated elimination of mammary gland tumors. Citation Format: Lauryn R Werner, Dominika E. Helm, Julio Tinoco, Eilidh I Chowanec, Sean M Holloran, Richard C Hastings, Junping Wei, Gangjun Lei, Xiao-Yi Yang, Mary A Markiewicz, Prabhakar Chalise, Justin Balko, Zachary C Hartman, Christy R Hagan. Progesterone impacts the growth and immune cell infiltration of murine mammary gland tumors [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P2-20-11.

Hospitalists are medical doctors that specialize in the care of hospitalized patients, a role that until recently belonged to primary care physicians. We develop an operational model of hospitalist-patient interactions with rounding and responding service modes, optimizing hospitalist caseload and case-mix to achieve the maximal reduction in patient length of stay (LOS). We show that hospitalists are effective at reducing LOS for patients with complex conditions, corroborating intuitive reasoning. However, the optimal hospitalist case-mix also includes “simple” patients with few interventions and short LOS, as they can effectively reduce discharge delays. This actionable insight is particularly salient for small community hospitals with simple, short-stay patients, where hospitalists may be undervalued due to the prevailing belief that they are primarily effective for complex patients. We conduct a comparative case study of a small community hospital and a large academic hospital, drawing a stark contrast between the two in terms of ideal caseload and patient coverage. Despite the fact that the academic hospital treats higher complexity patients, hospitalists at the community hospital should actually have a lower caseload than hospitalists at the academic hospital due to shorter stays in the community hospital. We find that both hospitals are understaffed but for different reasons: the academic hospital needs to staff more hospitalists to reduce the current caseload of its hospitalists, whereas the community hospital needs to staff more hospitalists to expand its hospitalist coverage to more patients. We estimate that these hospitals can save on average $1.5 million annually by implementing the optimal staffing policies. This paper was accepted by Stefan Scholtes, healthcare management. Funding: This work was supported by a PSC-CUNY Award, jointly funded by The Professional Staff Congress and The City University of New York. Supplemental Material: The e-companion and data files are available at https://doi.org/10.1287/mnsc.2022.4342 .

One of the most important decisions a hospitalist makes at the intersection of cost and quality of care is when to discharge a patient from the hospital. Keeping patients longer (shorter) increases (decreases) overcrowding and hospital costs but also decreases (increases) readmission risk. Here a long-run average cost optimization problem for determining on each day who and how many patients to discharge is developed. The authors combined structural properties of the model with an analytical solution for a special cost structure to approximately solve the high-dimensional Markov decision process. This transformed the originally intractable problem into a simple univariate optimization problem that can be solved efficiently yet allowed capture of time nonstationarity and fully heterogeneous inpatient populations, where each patient has a personalized risk trajectory. Moreover, the authors took one step beyond theory and implemented their discharge decision support tool in a partner hospital. For the tool to be properly parametrized and implementable, the authors developed a model to predict readmission risk as a function of length of stay that integrated several statistical methods in a novel manner. The resulting implementation was described as a showcase, demonstrating the tool’s applicability for integration with general hospital data systems and workflows.

Principles required for secure electronic voting using the Internet are known and published. Although the Internet voting functionalities and technologies are well-defined, none of the existing state-sponsored Internet voting approaches in use incorporate a total Internet-based system approach that includes voter registration, the voting process, and vote counting. The distributed Internet voting architecture concept discussed in this article uses a novel thin client approach to Internet voting. The architecture uses existing technologies and knowledge to create a viable whole system approach to Internet voting. This article describes various aspects and processes necessary to support an integrated approach. The application programming interface software for many of the critical functions was developed in Python and functionality tested. A virtual network, including a cloud-based functionality, was created and used to evaluate the various conceptual aspects of the proposed architecture. This included the concepts associated with programming and accessing smart cards, capturing and saving fingerprint data, structuring virtual private networks using tunneling and Internet Protocol Security, encrypting ballots using asymmetric encryption, using symmetric encryption for secret cookies, thin client interaction, and creating hash functions to be used within a blockchain structure in a Merkle tree architecture. The systems’ primary user targets are individuals remotely located from their home voting precincts and senior citizens who have limited mobility and mostly reside in assisted living facilities. The research supports the contention that a cybersecure Internet voting system that significantly reduces the opportunity for mail-in voter fraud, helps to ensure privacy for the voter, including nonrepudiation, nonattribution, receipt freeness, and vote acknowledgment can be created using existing technology.

Background: Cancer rehabilitation often includes manual assessment and interventions to address cancer treatment related side effects The effect of reduced access to rehabilitative care due to COVID-19 is currently unknown Objective/Purpose: To assess distress and quality of life (QOL) for women receiving care for breast cancer related impairments during closure of rehabilitation services due to COVID-19 Methods: Preexisting patients returning to rehabilitation services after a COVID-19 associated interruption of treatment were asked to complete a survey regarding their distress, function, and QOL levels at the suspension of rehabilitation services and at the resumption of those services Setting and Patients: Outpatient cancer rehabilitation clinic treating breast cancer survivors at an accredited cancer center Measurements: Distress thermometer, FACT-G (Functional Assessment of Cancer Therapy General) survey, and visual analog scale questions regarding sleep, fatigue, and physical activity as part of reassessment by the clinician Utility of telehealth was also explored Results: Fifteen women (age range, 38-76 years) with primary complaints of shoulder stiffness, pain, and lymphedema completed surveys, and 33% received telehealth Reported distress levels at the time of closure were significantly higher than self-reported levels at reopening (t14 = 4 69, P = 000) Increases in distress at the time of closure were correlated with reduced physical activity (r = -0 602, P = 018) Reduced levels of distress following return to rehabilitation were correlated with reduced levels of fatigue (r = 0 575, P = 025) No statistically significant relationships between distress and sleep quality were found Limitations: Self-report via surveys, recall bias, and the multifactorial characteristics of distress limit study findings Conclusion: Closure of rehabilitation services during COVID-19 created distress, resulting in reduced physical activity and QOL in breast cancer survivors Cancer survivorship communities will need to assess the effect of disrupted service across cancer rehabilitation centers Further research is needed to validate optimal interventions including telehealth best practice to manage distress and QOL in a COVID-19 context

OBJECTIVE To better understand the financial implications of readmission after radical cystectomy, an expensive surgery coupled with a high readmission rate. Currently, whether hospitals benefit financially from readmissions after radical cystectomy remains unclear, and potentially obscures incentives to invest in readmission reduction efforts. MATERIALS AND METHODS Using a 20% sample of national Medicare beneficiaries, we identified 3544 patients undergoing radical cystectomy from January 2010 to November 2014. We compared price-standardized Medicare payments for index admissions and readmissions after surgery. We also examined the variable financial impact of length of stay and the proportion of Medicare payments coming from readmissions based on overall readmission rate. RESULTS Medicare patients readmitted after cystectomy had higher index hospitalization payments ($19,164 readmitted vs $18,146 non-readmitted, P = .03) and an average readmission payment of $7356. Adjusted average Medicare readmission payments and length of stay varied significantly across hospitals, ranging from $2854 to $15,605, and 2.0 to 17.1 days, respectively (both P

BackgroundClinical studies have linked usage of progestins (synthetic progesterone [P4]) to breast cancer risk. However, little is understood regarding the role of native P4, signaling through the progesterone receptor (PR), in breast tumor formation. Recently, we reported a link between PR and immune signaling pathways, showing that P4/PR can repress type I interferon signaling pathways. Given these findings, we sought to investigate whether P4/PR drive immunomodulation in the mammary gland and promote tumor formation.MethodsTo determine the effect of P4 on immune cell populations in the murine mammary gland, mice were treated with P4 or placebo pellets for 21 days. Immune cell populations in the mammary gland, spleen, and inguinal lymph nodes were subsequently analyzed by flow cytometry. To assess the effect of PR overexpression on mammary gland tumor development as well as immune cell populations in the mammary gland, a transgenic mouse model was used in which PR was overexpressed throughout the entire mouse. Immune cell populations were assessed in the mammary glands, spleens, and inguinal lymph nodes of 6-month-old transgenic and control mice by flow cytometry. Transgenic mice were also monitored for mammary gland tumor development over a 2-year time span. Following development of mammary gland tumors, immune cell populations in the tumors and spleens of transgenic and control mice were analyzed by flow cytometry.ResultsWe found that mice treated with P4 exhibited changes in the mammary gland indicative of an inhibited immune response compared with placebo-treated mice. Furthermore, transgenic mice with PR overexpression demonstrated decreased numbers of immune cell populations in their mammary glands, lymph nodes, and spleens. On long-term monitoring, we determined that multiparous PR-overexpressing mice developed significantly more mammary gland tumors than control mice. Additionally, tumors from PR-overexpressing mice contained fewer infiltrating immune cells. Finally, RNA sequencing analysis of tumor samples revealed that immune-related gene signatures were lower in tumors from PR-overexpressing mice as compared with control mice.ConclusionTogether, these findings offer a novel mechanism of P4-driven mammary gland tumor development and provide rationale in investigating the usage of antiprogestin therapies to promote immune-mediated elimination of mammary gland tumors.

Clinical studies have linked usage of progestins (synthetic progesterone) to breast cancer risk. However, little is understood regarding the role of native progesterone (P4), signaling through the progesterone receptor (PR), in breast tumor formation. Recently, we reported a link between PR and immune signaling pathways, showing that P4/PR can repress type I interferon signaling pathways. Given these findings, we sought to investigate whether P4/PR drive immunomodulation in the mammary gland and promote tumor formation. To determine the effect of P4 on immune cell populations in the murine mammary gland, mice were treated with P4 or placebo pellets for 21 days. We found that mice treated with P4 exhibited changes in the mammary gland indicative of an inhibited immune response compared to placebo-treated mice. To assess the effect of PR overexpression on mammary gland tumor development as well as immune cell populations in the mammary gland, a transgenic mouse model was used in which PR is overexpressed throughout the entire mouse. Immune cell populations were assessed in the mammary glands by flow cytometry, which revealed decreased numbers of various immune cell populations. Transgenic mice were also monitored for mammary gland tumor development over a 2-year timespan. Following development of mammary gland tumors, immune cell populations in the tumors and spleens of transgenic and control mice were analyzed by flow cytometry. Upon long-term monitoring, we determined that multi-parous PR overexpressing mice developed significantly more mammary gland tumors than control mice. Additionally, tumors from PR overexpressing mice contained fewer infiltrating immune cells, and RNA sequencing analysis of tumor samples revealed that immune-related gene signatures were lower in tumors from PR overexpressing mice as compared to control mice. Finally, we utilized syngeneic mammary gland tumor models to evaluate the effect of P4 on the growth of PR+ mammary gland tumors in vivo, which revealed that P4 promoted tumor growth and decreased immune cell infiltration of PR+ mammary gland tumors. Together, these findings offer a novel mechanism of P4-driven mammary gland tumor development and provide rationale in investigating the usage of anti-progestin therapies to promote immune-mediated elimination of mammary gland tumors. Citation Format: Lauryn Rose Werner, Katelin A. Gibson, Merit L. Goodman, Dominika E. Helm, Katherine R. Walter, Sean M. Holloran, Gloria M. Trinca, Richard C. Hastings, Howard H. Yang, Ying Hu, Junping Wei, Gangjun Lei, Xiao-Yi Yang, Rashna Madan, Alfredo A. Molinolo, Mary A. Markiewicz, Prabhakar Chalise, Margaret L. Axelrod, Justin M. Balko, Kent W. Hunter, Zachary C. Hartman, Carol A. Lange, Christy R. Hagan. Lauryn Werner [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1351.

At the onset of the COVID-19 pandemic, hospitals were in dire need of data-driven analytics to provide support for critical, expensive, and challenging decisions. Yet, the majority of analytics being developed were targeted toward state- and national-level policy decisions, with little availability of actionable information to support tactical and operational decision making and execution at the hospital level. To fill this gap, we developed a multi-method framework leveraging a parsimonious design philosophy that allows for rapid deployment of high-impact predictive and prescriptive analytics in a time-sensitive, dynamic, limited data environment such as a novel pandemic. Our framework integrates disease progression models tailored to data availability during different stages of the pandemic with a stochastic network model of patient movements among units within individual hospitals to forecast time-varying patient workload and demand for critical resources. Both components employ adaptive tuning to account for hospital-dependent, time-varying parameters that provide consistently accurate predictions as changes in system dynamics are learned over time. The product of this research is a workload prediction and decision support framework customized to individual hospital that specifically targets actionable information based on hospital needs. Yet, by design, our framework is portable across hospital data-systems and easily implementable for expeditious expansion. This work was contextually grounded in close collaboration with IU Health, the largest health system in Indiana with 18 hospitals serving over 1 million residents. Since April 2020, we have implemented our framework to support decisions from operational to strategic made by multiple departments at IU Health as well as the executive leadership team during the course of the COVID-19 pandemic.

BACKGROUND: Payment models, including the Hospital Readmissions Reduction Program and bundled payments, place pressures on hospitals to limit readmissions. Against this backdrop, we sought to investigate the association of post-acute care after major surgery and readmission rates. METHODS: We identified patients undergoing high-risk surgery (abdominal aortic aneurysm repair, coronary bypass grafting, aortic valve replacement, carotid endarterectomy, esophagectomy, pancreatectomy, lung resection, and cystectomy) from 2005 to 2010 using the Healthcare Cost and Utilization Project’s State Inpatient Database. The primary outcome was readmission rates after major surgery. Secondary outcome was readmission length of stay. RESULTS: We identified 135,523 patients of whom 56,720 (42%) received post-acute care. Patients receiving post-acute care had higher readmission rates than those who were discharged home (16% versus 10%, respectively; p

Major hospitals frequently lack adequate space to accommodate emergency patients. Managers can take actions to create surge capacity, an immediate additional supply of medical services to accommodate increased demand. We study operational strategies that improve surge capacity, and we identify how they can be deployed most effectively based on the characteristics of individual hospitals.Recent government regulations in the United States have increased pressure on hospitals to improve emergency preparedness. Specifically, hospitals must be able to show that they have taken adequate measures to manage surge capacity. We formulate an optimization model of early disposition actions that can be used to create surge capacity in a hospital. We analyze the model to understand its structural properties and compare two strategies to improve surge capacity: coordinated early discharge, which occurs during the response, and inpatient workload smoothing, which can help mitigate the need for response actions. We show analytically that without coordination, hospitals always act too conservatively in discharging patients to accommodate surge arrivals, and that smoothing the elective inpatient workload reduces the expected cost of surge response. In the numerical study, we find a utilization sweet spot in which smoothing is best at increasing surge capacity, and we show coordination increases the number of surges and number of early discharges, while smoothing mitigates these effects, making surges less frequent and less costly. Coordination is effective at increasing surge capacity for all types of hospitals, but when considering the holistic impact to the hospital, coordination and workload smoothing are often complementary strategies for improving surge response. Moreover, hospitals with sufficiently many electives and moderately high utilization should prioritize mitigation efforts when planning for emergencies.

Background The Comprehensive Care for Joint Replacement bundle was created to decrease total knee arthroplasty (TKA) cost. To help accomplish this, there is a focus on reducing TKA readmissions. However, there is a lack of national representative sample of all-payer hospital admissions to direct strategy, identify risk factors for readmission, and understand actual readmission cost. Methods We used the Nationwide Readmission Database to examine national readmission rates, predictors of readmission, and associated readmission costs for elective TKA procedures. We fit a multivariable logistic regression model to examine factors associated with readmission. Then, we determined mean readmission costs and calculated the readmission cost when distributed across the entire TKA population. Results We identified 224,465 patients having TKA across all states participating in the Nationwide Readmission Database. The mean unadjusted 30-day TKA readmission rate was 4%. The greatest predictors of readmission were congestive heart failure (odds ratio [OR] 2.51, 95% confidence interval [CI] 2.62-2.80), renal disease (OR 2.19, 95% CI 2.03-2.37), and length of stay greater than 4 days (OR 2.4, 95% CI 2.25-2.61). The overall median cost for each readmission was $6753 ± 175. Extrapolating the readmission cost for the entire TKA population resulted in the readmission cost being 2% of the overall 30-day procedure cost. Conclusions A major focus of the Comprehensive Care for Joint Replacement bundle is improving cost and quality by limiting readmission rates. TKA readmissions are low and comprise a small percentage of total TKA cost, suggesting that they may not be the optimal measure of quality care or a significant driver of overall cost.

Hospital readmissions affect hundreds of thousands of patients every year, negatively impacting patients and placing a tremendous burden on the national healthcare system. Post‐discharge checkup policies can reduce readmissions through early detection of health conditions, however, the methods behind designing effective checkup policies are poorly understood. Under current practice, up to 67% of readmitted patients return to the hospital before their first scheduled office visit. This work aims to develop effective checkup plans to monitor patients following hospital discharge, using a variety of checkup methods, including phone calls and office visits. We develop and analyze a new delay‐time analysis model to identify the optimal type and timing of checkups to implement post‐discharge monitoring plans. By analyzing the structure of optimal policies, we develop checkup schedules that can detect up to 43.7% more readmission‐causing conditions experienced by readmission‐bound patients. Further, we uncover simple rules of thumb that can help doctors design and improve monitoring plans even in the absence of advanced computer software or complex computations.

Clinical studies have linked usage of progestins (synthetic progesterone) to breast cancer risk. However, little is understood regarding the role of native progesterone (P4), signaling through the progesterone receptor (PR), in breast tumor formation. Recently, we reported a link between PR and immune signaling pathways, showing that P4/PR can repress type I interferon signaling pathways. Given these findings, we sought to investigate whether P4/PR drive immunomodulation in the mammary gland and promote tumor formation. To determine the effect of P4 on immune cell populations in the murine mammary gland, mice were treated with P4 or placebo pellets for 21 days. We found that mice treated with P4 exhibited changes in the mammary gland indicative of an inhibited immune response compared to placebo-treated mice. To assess the effect of PR overexpression on mammary gland tumor development as well as immune cell populations in the mammary gland, a transgenic mouse model was used in which PR is overexpressed throughout the entire mouse. Immune cell populations were assessed in the mammary glands by flow cytometry, which revealed decreased numbers of various immune cell populations. Transgenic mice were also monitored for mammary gland tumor development over a 2-year timespan. Following development of mammary gland tumors, immune cell populations in the tumors and spleens of transgenic and control mice were analyzed by flow cytometry. Upon long-term monitoring, we determined that multi-parous PR overexpressing mice developed significantly more mammary gland tumors than control mice. Additionally, tumors from PR overexpressing mice contained fewer infiltrating immune cells, and RNA sequencing analysis of tumor samples revealed that immune-related gene signatures were lower in tumors from PR overexpressing mice as compared to control mice. Finally, we utilized syngeneic mammary gland tumor models to evaluate the effect of P4 on the growth of PR+ mammary gland tumors in vivo, which revealed that P4 promoted tumor growth and decreased immune cell infiltration of PR+ mammary gland tumors. Together, these findings offer a novel mechanism of P4-driven mammary gland tumor development and provide rationale in investigating the usage of anti-progestin therapies to promote immune-mediated elimination of mammary gland tumors. Citation Format: Lauryn R Werner, Katelin A Gibson, Merit L Goodman, Dominika E Helm, Katherine R Walter, Sean M Holloran, Gloria M Trinca, Richard C Hastings, Howard H Yang, Ying Hu, Junping Wei, Gangjun Lei, Xiao-Yi Yang, Rashna Madan, Alfred A Molinolo, Mary A Markiewicz, Prabhakar Chalise, Margaret L Axelrod, Justin M Balko, Kent W Hunter, Zachary C Hartman, Carol A Lange, Christy R Hagan. Progesterone promotes immunomodulation and tumor development in the murine mammary gland [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P4-04-07.

Malaria is a major health concern for many developing countries. Designing strategies for efficient distribution of malaria medications, such as Artemesinin Combination Therapies, is a key challenge in resource constrained countries. This paper develops a solution methodology that integrates strategic†level and tactical†level models to better manage pharmaceutical distribution through a three†tier centralized health system, which is common to sub†Saharan African countries. At the strategic level, we develop a two†stage stochastic programming approach to address the problem of demand uncertainty. In the first stage, an initial round of shipments is sent before the malaria season to each local clinic from district hospitals, which receive medications from regional warehouses. After the malaria season begins, a recourse action is triggered to avoid shortages in the form of (i) lateral transshipment or (ii) delayed shipment. The optimal solutions developed by the strategic model identify small clinic clusters possessing exclusive transshipment policies. Therefore, we decompose the problem at the tactical level, solving each clinic cluster independently using a Markov decision process approach to determine optimal periodic transshipment policies. A case study of our proposed distribution system is performed for 290 facilities controlled by the Malawi Ministry of Health. Numerical analysis of Malawi's distribution system indicates that our proposed cluster†based decomposition method could near optimally reduce shortage incidents. Moreover, such an approach is robust to challenges of developing countries such as slow paper†based inventory review, uncertain transportation infrastructure, the need for equitable distribution, and seasonal and correlated demand associated with malaria transmission dynamics.

BACKGROUND: People post-stroke can learn a novel locomotor task, but require more practice to do so. Implementing an approach that can enhance locomotor learning may therefore improve post-stroke locomotor recovery. In healthy adults, an acute high-intensity exercise bout before or after a motor task may improve motor learning and has thus been suggested as a method that could be used to improve motor learning in neurorehabilitation. However, it is unclear whether an acute high-intensity exercise bout, which stroke survivors can feasibly complete in neurorehabilitation session, would generate comparable results. OBJECTIVE: To determine a feasible, high-intensity exercise protocol that could be incorporated into a post-stroke neurorehabilitation session and would result in significant exercise-induced responses. METHODS: Thirty-seven chronic stroke survivors participated. We allocated subjects to either a control (CON) or one of the exercise groups: treadmill walking (TMW), and total body exercise (TBE). The main exercise-induced measures were: average intensity (% max intensity) and time spent (absolute: seconds; normalized: % total time) at target exercise intensity, and magnitudes of change in serum lactate (mM/L) and brain-derived neurotrophic factor (BDNF; ng/ml). RESULTS: Compared to CON, both exercise groups reached and exercised longer at their target intensities and had greater responses in lactate. However, the TBE group exercised longer at target intensity and with greater lactate response than the TMW group. There were no significant BDNF responses among groups. CONCLUSIONS: An acute high-intensity exercise bout that could be incorporated into a neurorehabilitation learning-specific session and results in substantial exercise-induced responses is feasible post-stroke.

In recent years, many urban areas have established healthcare coalitions composed of autonomous (and often competing) hospitals, with the goal of improving emergency preparedness and response. We study the role of such coalitions in the specific context of response to multiple-casualty incidents in an urban setting, where on-scene responders must determine how to send casualties to medical facilities. A key function in incident response is multi-agency coordination. When this coordination is provided by a healthcare coalition, responders can use richer information about hospital capacities to decide where to send casualties. Using bed availability data from an urban area and a suburban area in the United States, we analyze the response capability of healthcare infrastructures under different levels of coordination, and we develop a stress test to identify areas of weakness. We find that improved coordination efforts should focus on decision support using information about inpatient resources, especially in urban areas with high inter-hospital variability in resource availability. We also find that coordination has the largest benefit in small incidents. This benefit is a new value proposition for healthcare coalitions, which were originally formed to improve preparedness for large disasters. This article is protected by copyright. All rights reserved.

Background and aims: Wastewater-based epidemiology is an additional indicator of drug use that is gaining reliability to complement the current established panel of indicators. The aims of this study were to: (i) assess spatial and temporal trends of population-normalized mass loads of benzoylecgonine, amphetamine, methamphetamine and 3,4-methylenedioxymethamphetamine (MDMA) in raw wastewater over 7 years (2011–17); (ii) address overall drug use by estimating the average number of combined doses consumed per day in each city; and (iii) compare these with existing prevalence and seizure data. Design: Analysis of daily raw wastewater composite samples collected over 1 week per year from 2011 to 2017. Setting and Participants: Catchment areas of 143 wastewater treatment plants in 120 cities in 37 countries. Measurements: Parent substances (amphetamine, methamphetamine and MDMA) and the metabolites of cocaine (benzoylecgonine) and of Δ9-tetrahydrocannabinol (11-nor-9-carboxy-Δ9-tetrahydrocannabinol) were measured in wastewater using liquid chromatography–tandem mass spectrometry. Daily mass loads (mg/day) were normalized to catchment population (mg/1000 people/day) and converted to the number of combined doses consumed per day. Spatial differences were assessed world-wide, and temporal trends were discerned at European level by comparing 2011–13 drug loads versus 2014–17 loads. Findings: Benzoylecgonine was the stimulant metabolite detected at higher loads in southern and western Europe, and amphetamine, MDMA and methamphetamine in East and North–Central Europe. In other continents, methamphetamine showed the highest levels in the United States and Australia and benzoylecgonine in South America. During the reporting period, benzoylecgonine loads increased in general across Europe, amphetamine and methamphetamine levels fluctuated and MDMA underwent an intermittent upsurge. Conclusions: The analysis of wastewater to quantify drug loads provides near real-time drug use estimates that globally correspond to prevalence and seizure data. © 2019 The Authors. Addiction published by John Wiley & Sons Ltd on behalf of Society for the Study of Addiction

Coordinated care is a burgeoning paradigm where patients receive diagnosis and treatment planning involving collaboration between two or more medical specialties to facilitate rapid and effective solutions to complex conditions. A key service metric for coordinated care organizations is how quickly they can move patients through their sequence of appointments at multiple clinical services in the network. Each patient's care path is uncertain when the appointment capacities are being planned, because information about the patient's condition evolves over the course of the patient's care process. Hence, the planning of root (first) appointments is the primary operational lever, as the other appointments evolve stochastically. In this work, we develop a discrete-time queueing network to optimize this root appointment allocation over a cyclic time horizon to maximize the proportion of patients that can complete their care by a class-dependent deadline. The model accounts for several salient features of coordinated care networks, including parallel appointment requests, stochastic paths, and time-varying features. We provide an {exact} characterization of the sojourn time in the network with a doubly-stochastic phase-type distribution and leverage a mean-field model with convergence guarantees to address intractability. We then develop a policy improvement framework that approximates the original stochastic optimization by a sequence of linear programs (LP), where the sojourn time model is parameterized in the policy evaluation step. The LPs are computationally efficient, and our algorithm can solve large-scale stochastic optimization for networks of realistic sizes (e.g., 26 service stations). In a case study of the Mayo Clinic, our solution improves on-time completion to more than 93\%, from 60\% under the current plan. We demonstrate that this is a multifaceted problem, and that ignoring any those facets can lead to poor performance. Simultaneously accounting for all these complexities makes manual template design challenging and highlights the practical significance of our optimization algorithm.

When patients leave the hospital for lower levels of care, they experience a risk of adverse events on a daily basis. The advent of value-based purchasing among other major initiatives has led to an increasing emphasis on reducing the occurrences of these post-discharge adverse events. This has spurred the development of new prediction technologies to identify which patients are at risk for an adverse event as well as actions to mitigate those risks. Those actions include pre-discharge and post-discharge interventions to reduce risk. However, traditional prediction models have been developed to support only post-discharge actions; predicting risk of adverse events at the time of discharge only. In this paper we develop an integrated framework of risk prediction and discharge optimization that supports both types of interventions: discharge timing and post-discharge monitoring. Our method combines a kernel approach for capturing the non-linear relationship between length of stay and risk of an adverse event, with a Principle Component Analysis method that makes the resulting estimation tractable. We then demonstrate how this prediction model could be used to support both types of interventions by developing a simple and easily implementable discharge timing optimization.

BACKGROUND Readmissions after cardiac surgery are common and associated with increased morbidity, mortality and cost of care. Policymakers have targeted coronary artery bypass grafting to achieve value-oriented health care milestones. We explored the causes of readmission following cardiac surgery among a regional consortium of hospitals. METHODS Using administrative data, we identified patients readmitted to the same institution within 30 days of cardiac surgery. We performed standardized review of readmitted patients' medical records to identify primary and secondary causes of readmission. We evaluated causes of readmission by procedure and tested for univariate associations between characteristics of readmitted patients and nonreadmitted patients in our clinical registry. RESULTS Of 2218 cardiac surgery patients, 272 were readmitted to the index hospital within 30 days for a readmission rate of 12.3%. Median time to readmission was 9 days (interquartile range 4-16 days) and only 13% of patients were evaluated in-office before readmission. Readmitted patients were more likely to have had valve surgery (31.3% vs 22.7%) than patients not readmitted. Readmitted patients were also more likely to have preoperative creatinine more than or equal to 2 mg/dL (P = .015) or congestive heart failure (CHF) (P = .034), require multiple blood transfusions or sustained inotropic support (P

Still considered a "hot topic" 4 years later, JIN is pleased to reprint this classic article from May/June 2015, Issue 3. Since publication, "Accepted but Unacceptable: Peripheral IV Catheter Failure" has been downloaded nearly 400 times and cited dozens of times in other related research. Based on these data, we asked the lead author to update readers on the status of catheter failure and what has been improved since 2015.

Peripheral intravenous (IV) catheter insertion, the most common invasive hospital procedure performed worldwide, is associated with a variety of complications and an unacceptably high overall failure rate of 35% to 50% in even the best of hands. Catheter failure is costly to patients, caregivers, and the health care system. Although advances have been made, analysis of the mechanisms underlying the persistent high rate of peripheral IV failure reveals opportunities for improvement.

Background and purpose The optimal characteristics of learning to promote recovery of walking have yet to be defined for the poststroke population. We examined characteristics of task practice that limit or promote learning of a novel locomotor pattern. Methods Thirty-two persons with chronic hemiparesis were randomized to 2 conditions (constant and variable practice) and participated in two 15-minute sessions of split-belt treadmill walking. On day 1, subjects in the constant condition walked on the split-belt treadmill at a constant 2:1 speed ratio, while subjects in the variable condition walked on the split-belt treadmill at 3 different speed ratios. On day 2, both groups participated in 15 minutes of split-belt treadmill walking at the 2:1 speed ratio. Step length and limb phase symmetry metrics were measured to assess within-session learning (ie, adaptation) on day 1 and the ability to retain this new pattern of walking (ie, retention) on day 2. Results The amount of adaptation on day 1 did not differ depending upon practice structure (constant and variable) for step length or limb phase (a)symmetry. The magnitude of reduction in asymmetry from day 1 to day 2 did not differ between groups for step and limb phase (a)symmetry. Discussion and conclusions The results suggest that variable practice utilizing alternating belt speed ratios does not influence the ability of those with chronic stroke to adapt and retain a novel locomotor pattern. The effects of other forms of variable practice within other locomotor learning paradigms should be explored in those with chronic hemiparesis after stroke.Video Abstract available for more insights from the authors (see the Video, Supplemental Digital Content 1, available at: http://links.lww.com/JNPT/A257).

Objective Many studies have examined the relationship between worry and cancer screening. Due to methodological inconsistencies, results of these studies have varied and few conclusions can be made when generalizing across studies. The purpose of the current study was to better understand the worry-cancer screening relationship using a prospective research design. Method 180 women enrolled in an annual ovarian cancer (OC) screening clinic completed surveys at three time points—pre-screening, day of screening, and post-screening—using three measures of cancer-specific worry. Results OC worry was highest in the weeks prior to screening and mere presentation at a screening clinic was associated with a significant worry decline. Observed elevations in worry following abnormal screening were not universal and varied by the instrument used to measure worry. Conclusions In contrast to our hypotheses, it appears that mere presentation at a cancer screening clinic may be a worry-reducing event. Receipt of abnormal results was not necessarily associated with increased worry.

Hospitalists are medical doctors that specialize in the care of hospitalized patients, a role that until recently belonged to primary care physicians. We develop an operational model of hospitalist-patient interactions with rounding and responding service modes, optimizing hospitalist caseload and case-mix to achieve the maximal reduction in patient length of stay (LOS). We show that hospitalists are effective at reducing LOS for patients with complex conditions, corroborating intuitive reasoning. However, the optimal hospitalist case-mix also includes "simple" patients with few interventions and short LOS, as they can effectively reduce discharge delays. This actionable insight is particularly salient for small community hospitals with simple, short-stay patients, where hospitalists may be undervalued due to the prevailing belief that they are primarily effective for complex patients. We conduct a comparative case study of a small community hospital and a large academic hospital, drawing a stark contrast between the two in terms of ideal caseload and patient coverage. Despite the fact that the academic hospital treats higher complexity patients, hospitalists at the community hospital should actually have a lower caseload than hospitalists at the academic hospital due to shorter stays in the community hospital. We find that both hospitals are understaffed but for different reasons: the academic hospital needs to staff more hospitalists to reduce the current caseload of its hospitalists, whereas the community hospital needs to staff more hospitalists to expand its hospitalist coverage to more patients. We estimate that these hospitals can save on average $1.5 million annually by implementing the optimal staffing policies.

Purpose: Early discontinuation or non-adherence of AI therapy occurs in 25-50 % of patients due to treatment associated toxicities, including musculoskeletal symptoms such as arthralgias and myalgias. The goal of this pilot study is to evaluate the effect of a directed physical therapy regimen including joint mobility and stretching exercises on musculoskeletal symptoms resulting from AI therapy, in comparison to normal physical activity alone. Patients and methods: Eligibility criteria included post-menopausal women with histological evidence of hormone receptor positive breast cancer who were currently receiving adjuvant AI therapy and experiencing significant joint discomfort/stiffness when attempting activities of daily living which began or significantly increased after initiation of AI therapy. Patients were excluded if they had preexisting rheumatoid arthritis or fibromyalgia, systemic metastasis or ECOG performance status of greater than 2. Patients were randomly assigned to an 8 week directed exercise program under the supervision of a physical therapist (Group A, n=15) or were told to participate in moderate physical activity (walking) (Group B, n=12). Before beginning the study and at the end of the 8 week intervention, patients in both groups underwent a physical therapy evaluation including performance based measures such as functional lower extremity strength and grip strength and a Patient Specific Functional Scale (PSFS) to assess functional ability to complete specific activities. Additionally, all patients answered a series of questionnaires including a pain disability index (PDI), pain scale (PS) and the PHQ4 depression scale. Effects of the directed exercise regimen were evaluated using non-parametric analysis to determine differences between the two groups. Results: Significant improvement was observed in both left and right grip strength and right pinch in the intervention group (Group A) as compared to the control group (Group B). Additionally, significant improvement in lower body measures including 2-minute step tests and chair raises were observed in patients who underwent the directed exercise program compared to the control group. No significant differences were observed in PS, PDI or PHQ4 between the groups. However, Group A showed a slight improvement on the PS and PDI. Conclusions: Directed exercise regimens involving joint mobility and stretching exercises may have benefits over moderate physical activity alone for joint pain and arthralgia associated with AI therapy. Citation Format: Varadarajan R, Helm E, Arnold C, Huelsenbeck-Dill L, Ingraham-Lopresto B, Sonaad S, Swanson P, Sims-Mourtada J, Dickson-Whitmer D. Directed exercise intervention in breast cancer patients with arthralgias receiving aromatase inhibitors: A randomized pilot study. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P5-12-04.

Background Serum levels of hepcidin-25, a peptide hormone that reduces blood iron content, are elevated when patients with cystic fibrosis (CF) develop pulmonary exacerbation (PEx). Because hepcidin-25 is unavailable as a clinical laboratory test, we questioned whether a one-time serum iron level was associated with the subsequent number of days until PEx, as defined by the need to receive systemic antibiotics (ABX) for health deterioration. Methods Clinical, biochemical, and microbiological parameters were simultaneously checked in 54 adults with CF. Charts were reviewed to determine when they first experienced a PEx after these parameters were assessed. Time to ABX was compared in subgroups with and without specific attributes. Multivariate linear regression was used to identify parameters that significantly explained variation in time to ABX. Results In univariate analyses, time to ABX was significantly shorter in subjects with Aspergillus-positive sputum cultures and CF-related diabetes. Multivariate linear regression models demonstrated that shorter time to ABX was associated with younger age, lower serum iron level, and Aspergillus sputum culture positivity. Conclusions Serum iron, age, and Aspergillus sputum culture positivity are factors associated with shorter time to subsequent PEx in CF adults.

Although significant effort is concentrated toward gait retraining during stroke rehabilitation; 33% of community-dwelling individuals following stroke continue to demonstrate gait asymmetries following participation in conventional rehabilitation. Recent studies utilizing the split-belt treadmill indicate that subjects after stroke retain the ability to learn a novel locomotor pattern. Through the use of error augmentation, this locomotor pattern can provide a temporary improvement in symmetry, which can be exploited through repetitive task specific locomotor training. This article reviews findings from this experimental paradigm in chronic stroke survivors and discusses the future questions to be addressed in order to provide optimal rehabilitation interventions.

In managing chronic diseases such as glaucoma, the timing of periodic examinations is crucial, as it may significantly impact patients’ outcomes. We address the question of when to monitor a glaucoma patient by integrating a dynamic, stochastic state space system model of disease evolution with novel optimization approaches to predict the likelihood of progression at any future time. Information about each patient’s disease state is learned sequentially through a series of noisy medical tests. This information is used to determine the best time to next test based on each patient’s individual disease trajectory as well as population information. We develop closed-form solutions and study structural properties of our algorithm. While some have proposed that fixed-interval monitoring can be improved upon, our methodology validates a sophisticated model-based approach to doing so. Based on data from two large-scale, 10+ years clinical trials, we show that our methods significantly outperform fixed-interval schedules and age-based threshold policies by achieving greater accuracy of identifying progression with fewer examinations. Although this work is motivated by our collaboration with glaucoma specialists, the methodology developed is applicable to a variety of chronic diseases.

This article develops the construct of consumer cynicism, characterized by a perception of a pervasive, systemic lack of integrity in the marketplace and investigates how cynical consumers behave in the marketplace. The construct was developed based on a qualitative study and triangulated through developing a scale and investigating antecedents and consequential marketplace behaviours. The cynicism construct is uniquely suited to explain the underlying psychological processes hinted at in practitioner perceptions of the growing mistrust and consumer research about rebellion behaviours, as well as to offer insight on consumers’ response to the increasingly sophisticated market. Previous research has offered a glimpse of extreme rebellion behaviours such as culture jamming, anti-market rallies and movements and anti-consumerist festivals such as Burning Man explored through qualitative research. [Drawing audiences around 50 000 and running annually near San Francisco since 1986, the Burning Man festival lists decommodification among its 10 core principles, prohibits commercial sponsorships, exchange transactions and advertising, and culminates in burning a 40-foot effigy of ‘the man’.] This research builds on that through both qualitative and quantitative approaches to empirically demonstrate that the cynical attitudes underlying such behaviours are widespread and have a subtle and pervasive effect on more everyday consumption behaviours as well as high-profile activist behaviours. Cynical consumers see consumers (not just activists but also ordinary consumers) as players in a marketplace system, and they believe that role comes with the responsibility to make socially conscious choices. The consumer marketplace system is so pervasive that simple apathy or avoidance is rarely possible. Cynical consumers are forced to continually interact with a system they mistrust, and they use various coping strategies. The consumer cynicism construct was initially developed through a grounded theory study of in-depth interviews. Interview analysis showed these consumers share a consistent, complex network of marketplace beliefs and negative affect, which shapes their behaviour in the marketplace. Based on the qualitative study, consumer cynicism is defined as a stable, learned attitude towards the marketplace characterized by the perception that pervasive opportunism among firms exists and that this opportunism creates a harmful consumer marketplace. A series of studies was conducted to develop a scale to measure consumer cynicism. A large-scale national survey provided the final scale validation sample and primary research instrument for testing hypotheses, and additional studies were conducted for a rigorous scale development process, establishing internal consistency, invariant unidimensional factor structure, scale norms, test–retest reliability as well as face validity, known-groups validity, convergent validity, discriminant validity and nomological validity. Consumer cynicism is shown to impact marketplace behaviours and perceptions, leading to marketplace shaping or consumer activism and criticism behaviours, and marketplace withdrawal behaviours such as voluntary simplicity lifestyles.

Hospital readmissions present an increasingly important challenge for health-care organizations. Readmissions are expensive and often unnecessary, putting patients at risk and costing $15 billion annually in the United States alone. Currently, 17% of Medicare patients are readmitted to a hospital within 30 days of initial discharge with readmissions typically being more expensive than the original visit to the hospital. Recent legislation penalizes organizations with a high readmission rate. The medical literature conjectures that many readmissions can be avoided or mitigated by post-discharge monitoring. To develop a good monitoring plan it is critical to anticipate the timing of a potential readmission and to effectively monitor the patient for readmission causing conditions based on that knowledge. This research develops new methods to empirically generate an individualized estimate of the time to readmission density function and then uses this density to optimize a post-discharge monitoring schedule and staffing plan to support monitoring needs. Our approach integrates classical prediction models with machine learning and transfer learning to develop an empirical density that is personalized to each patient. We then transform an intractable monitoring plan optimization with stochastic discharges and health state evolution based on delay-time models into a weakly coupled network flow model with tractable subproblems after applying a new pruning method that leverages the problem structure. Using this multi-methodologic approach on two large inpatient datasets, we show that optimal readmission prediction and monitoring plans can identify and mitigate 40–70% of readmissions before they generate an emergency readmission.

Hospital readmissions after radical cystectomy vary with respect to intensity in terms of impact on patients and health care systems. Therefore, we conducted a population based study to examine factors associated with increasing readmission intensity after radical cystectomy for bladder cancer.Using SEER (Surveillance, Epidemiology, and End Results)-Medicare data we identified 1,782 patients who underwent radical cystectomy from 2003 to 2009. We defined readmission intensity in terms of length of stay (days) divided into quartiles of less than 3 (lowest), 3 to 4, 5 to 7 and more than 7 (highest). We used logistic regression to examine factors associated with readmission intensity.More than half of the patients with the highest intensity readmissions were readmitted within the first week and 77% were readmitted within 2 weeks of discharge. Patients with the highest intensity readmissions were similar in age, gender, race, socioeconomic status, pathological stage, comorbidity, neoadjuvant chemotherapy use and urinary diversion type compared to patients with the lowest intensity readmissions. After multivariable adjustment, complications during the index cystectomy admission (p0.001), readmission week (p=0.04), and the interaction between index length of stay and discharge to a skilled nursing facility (p=0.04) were associated with the highest readmission intensity.Readmission intensity differs widely after discharge following radical cystectomy. As postoperative efforts to minimize the readmission burden increase, a better understanding of the factors that contribute to the highest intensity readmissions will help direct limited resources (eg telephone calls, office visits) toward high yield areas.

When to discharge a patient plays an important role in hospital patient flow management as well as the quality of care and patient outcomes. In this work, we develop and implement a data-integrated decision support framework to aid hospitals in managing the delicate balance between readmission risk at discharge and ward congestion. We formulate a large-scale Markov Decision Process (MDP) that integrates a personalized readmission prediction model to dynamically prescribe both how many and which patients to discharge on each day. Due to patient heterogeneity and the fact that length-of-stay is not memoryless, the MDP suffers the curse of dimensionality. We leverage structural properties and analytical solutions for a special cost setting to transform the MDP into a univariate optimization; this leads to a novel, efficient dynamic heuristic. Further, for our decision framework to be implementable in practice, we build a unified prediction model that integrates several statistical methods and provides key inputs to the decision framework; existing off-the-shelf readmission prediction models alone could not adequately parametrize our decision support. Through extensive counterfactual analyses, we demonstrate the value of our discharge decision tool over our partner hospital's historical discharge behavior. We also obtain generalizable insights by applying the tool to a broad range of hospital types through a high-fidelity simulation. Lastly, we showcase an implementation of our tool at our partner hospital, to demonstrate broader applicability through our framework's "plug-and-play" design for integration with general hospital data-systems and workflows.

Hospital readmissions are burdensome and costly to healthcare systems. To incentivize the reduction of unnecessary readmissions, penalty programs and payment models have been created. These models typically define a period of time, a.k.a. an episode of care (EOC), within which hospitals are accountable for readmissions (e.g., 30-day readmission penalty and 90-day bundled payment EOC). This paper studies the policy-levels decisions in the design of EOC-based readmission reduction policies, considering three key policy levers: 1) EOC length, 2) readmission penalty, and 3) readmission avoidance subsidy. Our model provides a simple yet powerful condition for policy design, capturing the interplay between policy levers and hospital’s readmission reduction programs. We argue that EOC length may be the long-missing piece to the puzzle - it has a strong impact on the incentives but it has not received much attention in previous works. Specifically, EOC length has an exponential impact on the cost of readmission reduction programs, whereas the other two policy levers have linear effects. Our findings suggest that the 30-day and 90-day EOCs may be too long to incentivize readmission reduction for any but the low-risk patients, even under additional penalty or subsidy. This may explain the stalled readmission reduction after the implementation of the 30-day Medicare readmission penalty program. Though payers want long EOC to ensure hospitals cover more readmissions, long windows lead to smaller programs as hospitals "give up" on risky patients, whereas a shorter EOCs can encourage hospitals to expand readmission programs to include more and riskier patients.

After passage of the Patient Protection and Affordable Care Act, more children and young adults have become insured and have benefited from health care coverage than at any time since the creation of the Medicaid program in 1965. From 2009 to 2015, the uninsurance rate for children younger than 19 years fell from 9.7% to 5.3%, whereas the uninsurance rate for young adults 19 to 25 years of age declined from 31.7% to 14.5%. Nonetheless, much work remains to be done. The American Academy of Pediatrics (AAP) believes that the United States can and should ensure that all children, adolescents, and young adults from birth through the age of 26 years who reside within its borders have affordable access to high-quality and comprehensive health care, regardless of their or their families’ incomes. Public and private health insurance should safeguard existing benefits for children and take further steps to cover the full array of essential health care services recommended by the AAP. Each family should be able to afford the premiums, deductibles, and other cost-sharing provisions of the plan. Health plans providing these benefits should ensure, insofar as possible, that families have a choice of professionals and facilities with expertise in the care of children within a reasonable distance of their residence. Traditional and innovative payment methodologies by public and private payers should be structured to guarantee the economic viability of the pediatric medical home and of other pediatric specialty and subspecialty practices to address developing shortages in the pediatric specialty and subspecialty workforce, to promote the use of health information technology, to improve population health and the experience of care, and to encourage the delivery of evidence-based and quality health care in the medical home, as well as in other outpatient, inpatient, and home settings. All current and future health care insurance plans should incorporate the principles for child health financing outlined in this statement. Espousing the core principle to do no harm, the AAP believes that the United States must not sacrifice any of the hard-won gains for our children. Medicaid, as the largest single payer of health care for children and young adults, should remain true to its origins as an entitlement program; in other words, future fiscal or regulatory reforms of Medicaid should not reduce the eligibility and scope of benefits for children and young adults below current levels nor jeopardize children’s access to care. Proposed Medicaid funding “reforms” (eg, institution of block grant, capped allotment, or per-capita capitation payments to states) will achieve their goal of securing cost savings but will inevitably compel states to reduce enrollee eligibility, trim existing benefits (such as Early and Periodic Screening, Diagnostic, and Treatment), and/or compromise children’s access to necessary and timely care through cuts in payments to providers and delivery systems. In fact, the AAP advocates for increased Medicaid funding to improve access to essential care for existing enrollees, fund care for eligible but uninsured children once they enroll, and accommodate enrollment growth that will occur in states that choose to expand Medicaid eligibility. The AAP also calls for Congress to extend funding for the Children’s Health Insurance Program, a plan vital to the 8.9 million children it covered in fiscal year 2016, for a minimum of 5 years.

Brain-derived neurotrophic factor (BDNF) has been directly related to exercise-enhanced motor performance in the neurologically injured animal model; however literature concerning the role of BDNF in the enhancement of motor learning in the human population is limited. Previous studies in healthy subjects have examined the relationship between intensity of an acute bout of exercise, increases in peripheral BDNF and motor learning of a simple isometric upper extremity task. The current study examined the role of high intensity exercise on upregulation of peripheral BDNF levels as well as the role of high intensity exercise in mediation of motor skill performance and retention of a novel locomotor task in neurologically intact adults. In addition, the impact of a single nucleotide polymorphism in the BDNF gene (Val66Met) in moderating the relationship between exercise and motor learning was explored. It was hypothesized that participation in high intensity exercise prior to practicing a novel walking task (split-belt treadmill walking) would elicit increases in peripheral BDNF as well as promote an increased rate and magnitude of within session learning and retention on a second day of exposure to the walking task. Within session learning and retention would be moderated by the presence or absence of Val66Met polymorphism. Fifty-four neurologically intact participants participated in two sessions of split-belt treadmill walking. Step length and limb phase were measured to assess learning of spatial and temporal parameters of walking. Serum BDNF was collected prior to and immediately following either high intensity exercise or 5 minutes of quiet rest. The results demonstrated that high intensity exercise provides limited additional benefit to learning of a novel locomotor pattern in neurologically intact adults, despite increases in circulating BDNF. In addition, presence of a single nucleotide polymorphism on the BDNF gene did not moderate the magnitude of serum BDNF increases with high intensity exercise, nor did it moderate the relationship between high intensity exercise and locomotor learning.

Folate is an important B vitamin naturally found in the human diet and plays a critical role in methylation of nucleic acids. Indeed, abnormalities in this major epigenetic mechanism play a pivotal role in the pathogenesis of cognitive deficit and intellectual disability in humans. The most common cause of cognitive dysfunction in children is Down syndrome (DS). Since folate deficiency is very common among the pediatric population, we questioned whether chronic folate deficiency (CFD) exacerbates cognitive dysfunction in a mouse model of DS. To test this, adult Ts65Dn mice and their disomic littermates were chronically fed a diet free of folic acid while preventing endogenous production of folate in the digestive tract for a period of 8 weeks. Our results show that the Ts65Dn mouse model of DS was significantly more vulnerable to CFD in terms of plasma homocysteine and N5-methyltetrahydrofolate (5-MTHF) levels. Importantly, these changes were linked to degenerative alterations in hippocampal dendritic morphology and impaired nest building behavior in Ts65Dn mice. Based on our results, a rigorous examination of folate intake and its metabolism in individuals with DS is warranted.

Objective To inform whether readmission reduction strategies should consider surgical approach, we examined readmission differences between open and robotic-assisted radical cystectomy (RARC) using population-based data. Methods We identified patients who underwent cystectomy between January 2010 and September 2013 based on International Classification of Diseases-9th edition codes and administrative claims from a large, national US health insurer (Clinformatics Data Mart Database, OptumInsight, Eden Prairie, MN). We assessed post-discharge health system utilization and tested for differences in readmissions after the 2 surgical approaches. Results We identified 935 patients treated with cystectomy: open = 785 (84%) and RARC = 150 (16%). Patients undergoing RARC were slightly older, male, had more ileal conduit urinary reconstruction, and less need for intensive care. Index length of stay was shorter for RARC than for open surgery (7 days vs 8 days, P

EDITOR'S NOTE Still considered a "hot topic" 4 years later, JIN is pleased to reprint this classic article from May/June 2015, Issue 3. Since publication, "Accepted but Unacceptable: Peripheral IV Catheter Failure" has been downloaded nearly 400 times and cited dozens of times in other related research. Based on these data, we asked the lead author to update readers on the status of catheter failure and what has been improved since 2015.