Project description:BackgroundEAACI guidelines emphasize the importance of patient history in diagnosing food allergy (FA) and the need for studies investigating its value using standardized allergy-focused questionnaires.ObjectiveTo determine the contribution of reaction characteristics, allergic comorbidities and demographics to prediction of FA in individuals experiencing food-related adverse reactions.MethodsAdult and school-age participants in the standardized EuroPrevall population surveys, with self-reported FA, were included. Penalized multivariable regression was used to assess the association of patient history determinants with "probable" FA, defined as a food-specific case history supported by relevant IgE sensitization.ResultsIn adults (N = 844), reproducibility of reaction (OR 1.35 [95% CI 1.29-1.41]), oral allergy symptoms (OAS) (4.46 [4.19-4.75]), allergic rhinitis (AR) comorbidity (2.82 [2.68-2.95]), asthma comorbidity (1.38 [1.30-1.46]) and male sex (1.50 [1.41-1.59]) were positively associated with probable FA. Gastrointestinal symptoms (0.88 [0.85-0.91]) made probable FA less likely. The AUC of a model combining all selected predictors was 0.85 after cross-validation. In children (N = 670), OAS (2.26 [2.09-2.44]) and AR comorbidity (1.47 [CI 1.39-1.55]) contributed most to prediction of probable FA, with a combined cross-validation-based AUC of 0.73. When focusing on plant foods, the dominant source of FA in adults, the pediatric model also included gastrointestinal symptoms (inverse association), and the AUC increased to 0.81.ConclusionsIn both adults and school-age children from the general population, reporting of OAS and of AR comorbidity appear to be the strongest predictors of probable FA. Patient history particularly allows for good discrimination between presence and absence of probable plant FA.
Project description:The mobile ad hoc communication in highly dynamic scenarios, like urban evacuations or search-and-rescue processes, plays a key role in coordinating the activities performed by the participants. Particularly, counting on message routing enhances the communication capability among these actors. Given the high dynamism of these networks and their low bandwidth, having mechanisms to predict the network topology offers several potential advantages; e.g., to reduce the number of topology propagation messages delivered through the network, the consumption of resources in the nodes and the amount of redundant retransmissions. Most strategies reported in the literature to perform these predictions are limited to support high mobility, consume a large amount of resources or require training. In order to contribute towards addressing that challenge, this paper presents a history-based predictor (HBP), which is a prediction strategy based on the assumption that some topological changes in these networks have happened before in the past, therefore, the predictor can take advantage of these patterns following a simple and low-cost approach. The article extends a previous proposal of the authors and evaluates its impact in highly mobile scenarios through the implementation of a real predictor for the optimized link state routing (OLSR) protocol. The use of this predictor, named OLSR-HBP, shows a reduction of 40-55% of topology propagation messages compared to the regular OLSR protocol. Moreover, the use of this predictor has a low cost in terms of CPU and memory consumption, and it can also be used with other routing protocols.
Project description:The U.S. federal government is spending billions of dollars to test a multitude of new approaches to pay for healthcare. Unintended consequences are a major consideration in the testing of these value-based payment (VBP) models. Since participation is generally voluntary, any unintended consequences may be magnified as VBP models move beyond the early testing phase. In this paper, we propose a straightforward unsupervised outlier detection approach based on ranked percentage changes to identify participants (e.g., healthcare providers) whose behavior may represent an unintended consequence of a VBP model. The only data requirements are repeated measurements of at least one relevant variable over time. The approach is generalizable to all types of VBP models and participants and can be used to address undesired behavior early in the model and ultimately help avoid undesired behavior in scaled-up programs. We describe our approach, demonstrate how it can be applied with hypothetical data, and simulate how efficiently it detects participants who are truly bad actors. In our hypothetical case study, the approach correctly identifies a bad actor in the first period in 86% of simulations and by the second period in 96% of simulations. The trade-off is that 9% of honest participants are mistakenly identified as bad actors by the second period. We suggest several ways for researchers to mitigate the rate or consequences of these false positives. Researchers and policymakers can customize and use our approach to appropriately guard VBP models against undesired behavior, even if only by one participant.Supplementary informationThe online version contains supplementary material available at 10.1007/s10742-021-00253-9.
Project description:The value-based payment (VBP) system aims to improve the quality of healthcare while enhancing cost-efficiency, delivering better patient outcomes without increasing overall healthcare costs. It has been proposed as an alternative payment system to help sustain national insurance systems in response to the social and economic challenges posed by rising healthcare expenditures. Radiology plays a crucial role in disease prevention, diagnosis, and treatment; however, it is often undervalued. This review explores how radiology can be fully recognized for its inherent value in the VBP system and continue to enhance patient outcomes and societal value.
Project description:ObjectivesIn the move toward value-based payment, new payment models have largely been designed by payers and focused on the role of primary care providers. We examine a new phase of payment reform wherein providers, mostly specialists, are designing alternative payment models (APMs) for their own practices through a task force, called the Physician-Focused Payment Model Technical Advisory Committee, created by the Medicare Access and CHIP Reauthorization Act of 2015. Although it is a potentially notable shift in payment reform, little is known about the content of these proposals to date.Study designQualitative systematic review of physician-focused payment model proposals submitted to CMS.MethodsWe analyzed the first wave of new payment models proposed. For each of the 24 proposals submitted by physicians and physician groups, we assessed the models on their 10 key dimensions and evaluated underlying themes across all or many of the models to gain insights into what providers are looking for in APMs within the constraints of the rules established by the HHS secretary.ResultsKey features of the models and our analysis include bearing financial risk, a reliance on case management, embrace of new technologies, and consideration of legal barriers.ConclusionsWe discuss how specialists may help lead in the evolving payment landscape and recommend how these models might be improved. Payers and policy makers could benefit from our findings, which reflect how providers view financial risk in APMs and provide guidance on the types of payment reforms that they may embrace in the journey toward value.
Project description:BackgroundWhen risk adjustment is inadequate and incentives are weak, pay-for-performance programs, such as the Value-Based Payment Modifier (Value Modifier [VM]) implemented by the Centers for Medicare & Medicaid Services, may contribute to health care disparities without improving performance on average.ObjectiveTo estimate the association between VM exposure and performance on quality and spending measures and to assess the effects of adjusting for additional patient characteristics on performance differences between practices serving higher-risk and those serving lower-risk patients.DesignExploiting the phase-in of the VM on the basis of practice size, regression discontinuity analysis and 2014 Medicare claims were used to estimate differences in practice performance associated with exposure of practices with 100 or more clinicians to full VM incentives (bonuses and penalties) and exposure of practices with 10 or more clinicians to partial incentives (bonuses only). Analyses were repeated with 2015 claims to estimate performance differences associated with a second year of exposure above the threshold of 100 or more clinicians. Performance differences were assessed between practices serving higher- and those serving lower-risk patients after standard Medicare adjustments versus adjustment for additional patient characteristics.SettingFee-for-service Medicare.PatientsRandom 20% sample of beneficiaries.MeasurementsHospitalization for ambulatory care-sensitive conditions, all-cause 30-day readmissions, Medicare spending, and mortality.ResultsNo statistically significant discontinuities were found at the threshold of 10 or more or 100 or more clinicians in the relationship between practice size and performance on quality or spending measures in either year. Adjustment for additional patient characteristics narrowed performance differences by 9.2% to 67.9% between practices in the highest and those in the lowest quartile of Medicaid patients and Hierarchical Condition Category scores.LimitationObservational design and administrative data.ConclusionThe VM was not associated with differences in performance on program measures. Performance differences between practices serving higher- and those serving lower-risk patients were affected considerably by additional adjustments, suggesting a potential for Medicare's pay-for-performance programs to exacerbate health care disparities.Primary funding sourceThe Laura and John Arnold Foundation and National Institute on Aging.
Project description:BackgroundAchieving ≥90% improvement in Psoriasis Area and Severity Index (PASI90) is achievable with newer biologic therapies, such as ixekizumab. Standard of care payment systems such as the Merit-based Incentive Payment System (MIPS) responder criteria could lead to under treatment and lower quality of life (QoL) outcomes compared with PASI90.ObjectiveShow PASI90 is a higher standard than MIPS and is associated with greater improvements in QoL and other PRO outcomes.MethodsPatients with moderate-to-severe psoriasis meeting PASI90 and MIPS criteria were compared in 3 phase 3 clinical trials of the interleukin-17A inhibitor ixekizumab (pooled UNCOVER-2/3 and IXORA-S). Patients satisfying MIPS criteria met either static Physician Global Assessment score ≤2, body surface area <3%, PASI <3, or Dermatology Life Quality Index ≤5. Improvements in QoL were compared between patients meeting PASI90 and MIPS criteria.ResultsAll PASI90 responders were also MIPS responders (PASI90 responders). Not all MIPS responders met PASI90 (MIPS-only responders). Significantly larger change from baseline improvements for all health (skin pain, Itch NRS, DLQI, PtGA, WPAI-PsO work productivity loss, and WPAI-PsO activity impairment) and quality of life (EQ-5D 5L VAS and acute SF-36 PCS/MCS) outcome measures were observed in the PASI90 responders vs the MIPS-only responders.ConclusionPASI90 is a higher standard of response than MIPS and is associated with greater improvements in health and quality of life outcome measures.
Project description:Coral reefs provide important economic benefits to coastal businesses, supporting recreation and tourism and protecting property from storms. Yet, these benefits are at risk worldwide as corals decline rapidly, and investment in restoration is lacking. With their direct dependence on coral health, coastal businesses may represent an important sector for funding coral restoration; however, it is unclear whether businesses perceive coral reef services as valuable or themselves as reef stewards. We measured business perceptions of coral health and value in Hawai'i and identified traits correlated with business decisions to participate in coral restoration at three payment thresholds. We found that businesses see limited economic value in coral reefs. In areas where corals provide substantial ecosystem services (flood protection, tourism revenue), businesses did not consistently rate coral value as high. Nonetheless, businesses showed strong willingness to pay for coral restoration, which was linked to pro-nature motives, reputation, and Native Hawaiian ownership. Results highlight key strategies for engaging private entities in coral restoration.
Project description:BackgroundUncertainty about the benefits new cancer medicines will deliver in clinical practice risks delaying patient access to new treatment options in countries such as England, where the cost effectiveness of new medicines affects reimbursement decisions. Outcome-based payment (OBP) schemes, whereby the price paid for the drug is linked to patients' real-world treatment outcome(s) has been put forward as a mechanism to accelerate access. Although OBP schemes have generally focused on clinical outcomes to determine reimbursement, the degree to which these represent the outcomes that are important to patients is unclear.ObjectiveTo advance the application of OBP we ask, what outcomes do patients with cancer value (most) that might form a practical basis for OBP?MethodsA review of the literature on outcomes in cancer produced a long list of candidates. These were evaluated in a focus group with patients with cancer and were then, in a second focus group, distilled to a shortlist of ten outcomes using a card sort method. The ten outcomes were included in an online survey of patients with cancer and carers, who were asked to rank the importance of each outcome.ResultsThe focus groups identified a range of both clinical and functional outcomes that are important to patients. Analyses of the 164 survey responses suggested that the four most important outcomes to patients and carers are survival; progression, relapse or recurrence; post-treatment side effects; and return to normal activities of daily life.ConclusionCommissioners of cancer services wishing to instigate an OBP scheme should prioritise collecting data on these outcomes as they are important to patients. Of these, only mortality data are routinely collected within the national health service (NHS). Progression and some morbidity data exist but are not currently linked, creating a challenge for OBP.
Project description:BackgroundWaiting for a long time to make payments in outpatient wards and long queues of insured patients at the checkout window are common in many hospitals across China. To alleviate the problem of long queues for payment, many hospitals in China have established various mobile apps that those without health insurance can use. However, medically insured outpatients are still required to pay manually at the checkout window. Therefore, it is urgent to use information technology to innovate and optimize the outpatient service process, implement mobile payment for medically insured outpatients, and shorten the waiting time for outpatients, especially in the context of the COVID-19 epidemic. Furthermore, smartphone-based mobile payment for outpatients with health insurance could be superior to on-site cashier billing.ObjectiveThis study aimed to investigate the impact of smartphone-based mobile payment in relation to different aspects, such as waiting time, satisfaction with patients' waiting time, payment experience, the proportion of those dissatisfied with payment, total outpatient satisfaction, and outpatient volume, and compare mobile payment with on-site payment.MethodsThis was a historically controlled study. This study analyzed the outpatients' waiting time to make a medical insurance payment, their satisfaction with the waiting time and payment experience, the proportion of those dissatisfied with payment, and the outpatient volume of patients at Guangzhou Women and Children's Medical Center 1 year before and after the implementation of mobile payment for medical insurance in January 2021. An independent sample 2-tailed t test was used to compare waiting time, satisfaction with waiting time, and overall satisfaction. Paired sample 2-tailed t test was used to compare monthly outpatient visits. The chi-square test was used to compare the percentages of patients dissatisfied with payment.ResultsAfter the implementation of mobile payment for medical insurance outpatients, the patients' payment waiting time was significantly shortened (mean 45.28, SD 10.35 min vs mean 1.02, SD 0.25 min; t9014=53.396; P<.001), and satisfaction with waiting time and payment experience were significantly improved (mean 82.08, SD 3.17 vs mean 90.36, SD 3.45; t9014=-118.65; P<.001). Dissatisfaction with payment significantly decreased (10.27%, SD 2.18% vs 1.19% vs SD 0.30%; P<.001). The total satisfaction of outpatients significantly improved (mean 86.91, SD 3.23 vs mean 89.98, SD 3.31; t9014=-44.57; P<.001), and the outpatient volume increased (248,105.58, SD 89,280.76 vs 303,194.75, SD 53,773.12; t11=2.414; P=.03). Furthermore, payment efficiency improved, and the number of the on-site cashiers substantially decreased.ConclusionsMobile payment for health insurance significantly shortened patients' payment waiting time; improved patient satisfaction on waiting time and payment experience and overall satisfaction; reduced the proportion of patients who were dissatisfied with payment and the cashier at the hospital; and increased monthly outpatient volume. This approach was effective and thus worthy of promoting.