Parents’ Perspectives on Shared Decision Making for Children With Solid Organ Transplants

Introduction The Institute of Medicine prioritizes active family and clinician participation in treatment decisions, known as shared decision making (SDM). In this article we report the decision-making experiences for parents of children who had a solid organ transplant. Method We performed a prospective longitudinal mixed methods study at five major U.S. children\u27s medical centers. Qualitative interview data were obtained at 3 weeks, 3 months, and 6 months after hospital discharge following the child\u27s transplant. Results Forty-eight parents participated in the study. Three themes were identified: (a) Parents expect to participate in SDM; (b) parents seek information to support their participation in SDM; and (c) attributes of providers\u27 professional practice facilitates SDM. SDM was facilitated when providers were knowledgeable, transparent, approachable, accessible, dependable, and supportive. Conclusions Parents expect to participate in SDM with their transplant team. Health care providers can intentionally use the six key attributes to engage parents in SDM. The results provide a framework to consider enhancing SDM in other chronic illness populations

Getting Obligations Right: Autonomy and Shared Decision Making

Shared Decision Making (‘SDM’) is one of the most significant developments in Western health care practices in recent years. Whereas traditional models of care operate on the basis of the physician as the primary medical decision maker, SDM requires patients to be supported to consider options in order to achieve informed preferences by mutually sharing the best available evidence. According to its proponents, SDM is the right way to interpret the clinician-patient relationship because it fulfils the ethical imperative of respecting patient autonomy. However, there is no consensus about how decisions in SDM contexts relate to the principle of respect for autonomy. In response, I demonstrate that in order to make decisions about what treatment they will or will not receive, patients will be required to meet different conditions depending on the approach proponents of SDM take to understanding personal autonomy. Due to the fact that different conceptions of autonomy yield different obligations, I argue that if physicians and patients satisfied all the conditions described in standard accounts of SDM, then SDM would undermine patient autonomy

Super-Droplet Method for the Numerical Simulation of Clouds and Precipitation: a Particle-Based Microphysics Model Coupled with Non-hydrostatic Model

A novel simulation model of cloud microphysics is developed, which is named Super-Droplet Method (SDM). SDM enables accurate calculation of cloud microphysics with reasonable cost in computation. A simple SDM for warm rain, which incorporates sedimentation, condensation/evaporation, stochastic coalescence, is developed. The methodology to couple SDM and a non-hydrostatic model is also developed. It is confirmed that the result of our Monte Carlo scheme for the coalescence of super-droplets agrees fairly well with the solution of stochastic coalescence equation. A preliminary simulation of a shallow maritime cumulus formation initiated by a warm bubble is presented to demonstrate the practicality of SDM. Further discussions are devoted for the extension and the computational efficiency of SDM to incorporate various properties of clouds, such as, several types of ice crystals, several sorts of soluble/insoluble CCNs, their chemical reactions, electrification, and the breakup of droplets. It is suggested that the computational cost of SDM becomes lower than spectral (bin) method when the number of attributes $d$ becomes larger than some critical value, which may be $2\sim4$

Software Defined Media: Virtualization of Audio-Visual Services

Internet-native audio-visual services are witnessing rapid development. Among these services, object-based audio-visual services are gaining importance. In 2014, we established the Software Defined Media (SDM) consortium to target new research areas and markets involving object-based digital media and Internet-by-design audio-visual environments. In this paper, we introduce the SDM architecture that virtualizes networked audio-visual services along with the development of smart buildings and smart cities using Internet of Things (IoT) devices and smart building facilities. Moreover, we design the SDM architecture as a layered architecture to promote the development of innovative applications on the basis of rapid advancements in software-defined networking (SDN). Then, we implement a prototype system based on the architecture, present the system at an exhibition, and provide it as an SDM API to application developers at hackathons. Various types of applications are developed using the API at these events. An evaluation of SDM API access shows that the prototype SDM platform effectively provides 3D audio reproducibility and interactiveness for SDM applications.Comment: IEEE International Conference on Communications (ICC2017), Paris, France, 21-25 May 201

A generalized matrix profile framework with support for contextual series analysis

The Matrix Profile is a state-of-the-art time series analysis technique that can be used for motif discovery, anomaly detection, segmentation and others, in various domains such as healthcare, robotics, and audio. Where recent techniques use the Matrix Profile as a preprocessing or modeling step, we believe there is unexplored potential in generalizing the approach. We derived a framework that focuses on the implicit distance matrix calculation. We present this framework as the Series Distance Matrix (SDM). In this framework, distance measures (SDM-generators) and distance processors (SDM-consumers) can be freely combined, allowing for more flexibility and easier experimentation. In SDM, the Matrix Profile is but one specific configuration. We also introduce the Contextual Matrix Profile (CMP) as a new SDM-consumer capable of discovering repeating patterns. The CMP provides intuitive visualizations for data analysis and can find anomalies that are not discords. We demonstrate this using two real world cases. The CMP is the first of a wide variety of new techniques for series analysis that fits within SDM and can complement the Matrix Profile

The 2016 Academic Emergency Medicine Consensus Conference, Shared Decision Making in the Emergency Department: Development of a Policy-relevant Patient-centered Research Agenda Diagnostic Testing Breakout Session Report.

Diagnostic testing is an integral component of patient evaluation in the emergency department (ED). Emergency clinicians frequently use diagnostic testing to more confidently exclude worst-case diagnoses rather than to determine the most likely etiology for a presenting complaint. Increased utilization of diagnostic testing has not been associated with reductions in disease-related mortality but has led to increased overall healthcare costs and other unintended consequences (e.g., incidental findings requiring further workup, unnecessary exposure to ionizing radiation or potentially nephrotoxic contrast). Shared decision making (SDM) presents an opportunity for clinicians to discuss the benefits and harms associated with diagnostic testing with patients to more closely tailor testing to patient risk. This article introduces the challenges and opportunities associated with incorporating SDM into emergency care by summarizing the conclusions of the diagnostic testing group at the 2016 Academic Emergency Medicine Consensus Conference on SDM. Three primary domains emerged: 1) characteristics of a condition or test appropriate for SDM, 2) critical elements of and potential barriers to SDM discussions on diagnostic testing, and 3) financial aspects of SDM applied to diagnostic testing. The most critical research questions to improve engagement of patients in their acute care diagnostic decisions were determined by consensus

Micromachined vibratory gyroscopes controlled by a high order band-pass sigma delta modulator.

Abstract—This work reports on the design of novel closed-loop control systems for the sense mode of a vibratory-rate gyroscope based on a high-order sigma-delta modulator (SDM). A low-pass and two distinctive bandpass topologies are derived, and their advantages discussed. So far, most closed-loop force-feedback control systems for these sensors were based on low-pass SDM’s. Usually, the sensing element of a vibratory gyroscope is designed with a high quality factor to increase the sensitivity and, hence, can be treated as a mechanical resonator. Furthermore, the output characteristic of vibratory rate gyroscopes is narrowband amplitude- modulated signal. Therefore, a bandpass M is a more appropriate control strategy for a vibratory gyroscope than a low-pass SDM. Using a high-order bandpass SDM, the control system can adopt a much lower sampling frequency compared with a low-pass SDM while achieving a similar noise floor for a given oversampling ratio (OSR). In addition, a control system based on a high-order bandpass SDM is superior as it not only greatly shapes the quantization noise, but also alleviates tonal behavior, as is often seen in low-order SDM control systems, and has good immunities to fabrication tolerances and parameter mismatch. These properties are investigated in this study at system level

Do Community-Level Models Account for the Effects of Biotic Interactions? A Comparison of Community-Level and Species Distribution Modeling of Rocky Mountain Conifers

Community-level models (CLMs) aim to improve species distribution modeling (SDM) methods by attempting to explicitly incorporate the influences of interacting species. However, the ability of CLMs to appropriately account for biotic interactions is unclear. We applied CLM and SDM methods to predict the distributions of three dominant conifer tree species in the U.S. Rocky Mountains and compared CLM and SDM predictive accuracy as well as the ability of each approach to accurately reproduce species co-occurrence patterns. We specifically evaluated the performance of two statistical algorithms, MARS and CForest, within both CLM and SDM frameworks. Across all species, differences in SDM and CLM predictive accuracy were slight and can be attributed to differences in model structure rather than accounting for the effects of biotic interactions. In addition, CLMs generally over-predicted species cooccurrence, while SDMs under-predicted cooccurrence. Our results demonstrate no real improvement in the ability of CLMs to account for biotic interactions relative to SDMs. We conclude that alternative modeling approaches are needed in order to accurately account for the effects of biotic interactions on species distributions