Using a multidisciplinary data approach to operationalize an experience framework

Like many healthcare organizations, Baylor Scott & White Health (BSWH) is awash with data. Often, this data is used in siloed departments to monitor safety and quality, make local business decisions, and motivate staff to improve processes to achieve sustained excellence and market share. As margins get thinner and competition from various disrupters increases, organizations have tried to improve the patient experience to remain viable as part of a calculated strategy. Nevertheless, these entities have struggled to focus limited resources for sustained improvement in patient experience. This article details how a large Texas-based healthcare system operationalized The Beryl Institute\u27s Experience Framework via a multidisciplinary data approach. Key gaps that negatively impact the patient experience were identified using 99 data elements from common, readily available sources. Demonstrating the interconnected nature of the data has proven to be essential in engaging leaders to view the patient experience as an essential component to providing quality care. This crucial support from senior leaders drives efforts to safety, quality, and experience. A plan for how this approach can be implemented in any organization is shared, along with a discussion on sustainability, the use of these tools in an organization\u27s improvement journey, and how it can help create higher-performing care teams. Limitations and future opportunities for enhancements to the approach are also provided. Experience Framework This article is associated with the Policy & Measurement lens of The Beryl Institute Experience Framework. (https://www.theberylinstitute.org/ExperienceFramework). Access other PXJ articles related to this lens. Access other resources related to this lens

Adapting the Own Children Method to allow comparison of fertility between populations with different marriage regimes.

The Own Children Method (OCM) is an indirect procedure for deriving age-specific fertility rates and total fertility from children living with their mothers at a census or survey. The method was designed primarily for the calculation of overall fertility, although there are variants that allow the calculation of marital fertility. In this paper we argue that the standard variants for calculating marital fertility can produce misleading results and require strong assumptions, particularly when applied to social or spatial subgroups. We present two new variants of the method for calculating marital fertility: the first of these allows for the presence of non-marital fertility and the second also permits the more robust calculation of rates for social subgroups of the population. We illustrate and test these using full-count census data for England and Wales in 1911

Study of ice cloud properties using infrared spectral data

The research presented in this thesis involves the study of ice cloud microphysical and optical properties using both hyperspectral and narrowband infrared spectral data. First, ice cloud models are developed for the Infrared Atmospheric Sounding Interferometer (IASI) instrument onboard the METOP-A satellite, which provide the bulk-scattering properties of these clouds for the 8461 IASI channels between 645 and 2760 cm-1. We investigate the sensitivity of simulated brightness temperatures in this spectral region to the bulk-scattering properties of ice clouds containing individual ice crystal habits as well as for one habit distribution. The second part of this thesis describes an algorithm developed to analyze the sensitivity of simulated brightness temperatures at 8.5 and 11.0 µm to changes in effective cloud temperature by adjusting cloud top height and geometric thickness in a standard tropical atmosphere. Applicability of using these channels in a bi-spectral approach to retrieve cirrus cloud effective particle size and optical thickness is assessed. Finally, the algorithm is applied to the retrieval of these ice cloud properties for a case of single-layered cirrus cloud over a tropical ocean surface using measurements from the Moderate Resolution Infrared Spectroradiometer (MODIS). Cloud top height and geometric thickness in the profile are adjusted to assess the influence of effective cloud temperature on the retrieval

Assimilating GCOM-W1 AMSR2 and TRMM TMI Radiance Data in GEOS Analysis and Reanalysis

The Tropical Rainfall Measurement Mission (TRMM) Microwave Imager (TMI) observed the Earth in lower latitudes between 1997 - 2015. Its conical-scan radiometer has nine channels and measured microwave radiances between 10 and 89 GHz. These data provide information on atmospheric temperature, humidity, clouds, precipitation, as well as sea surface temperature. Radiance data from other microwave radiometers such as Special Sensor Microwave Imager (SSM/I) and Special Sensor Microwave Imager Sounder (SSMIS) onboard various Defense Meteorological Satellite Program (DMSP) satellites are assimilated in clear-sky conditions in the Modern-Era Retrospective analysis for Research and Applications (MERRA) and its version 2 (MERRA-2) data sets at the Global Modeling and Assimilation Office (GMAO) at NASA Goddard Space Flight Center. The GMAO's Hybrid 4D-EnVar-based Atmospheric Data Assimilation System (ADAS) is enhanced with an all-sky microwave radiance data assimilation capability in the real-time GEOS-Forward Processing (FP) system. Currently, the FP system assimilates Global Precipitation Measurement (GPM) microwave imager (GMI) radiance data utilizing this all-sky capability, and is being extended to use more all-sky data from other microwave radiometers. In this presentation, we will focus on impacts of all-sky TMI radiance data on GEOS analyses of atmospheric moisture, precipitation and other fields, and discuss their applications for future GEOS reanalyses

The Grizzly, December 5, 2019

Ursinus Cancels Swimming Seasons After Hazing Investigation • Students Detail Harassment on Main Street • Summer Internship Tips with CPD • Get to Know: Spring Break Service Trip • Opinion: Ursinus\u27 Judicial System is Broken • Q&A with Senior Linebacker Jake McCain • Women\u27s Basketball Walk-on Proves She is More Than Just a Ballerhttps://digitalcommons.ursinus.edu/grizzlynews/1597/thumbnail.jp

Assimilating GCOM-W AMSR2 Radiance Data in Future GEOS Reanalysis

Surface and atmospheric radiation are being measured by space-borne conical scanning microwave radiometers with high accuracy and spatial resolution since 1980s'. These radiometers include Special Sensor Microwave Imager (SSM/I) onboard various NOAA's polar-orbiting satellites, Special Sensor Microwave Imager Sounder (SSMIS) onboard Defense Meteorological Satellite Program (DMSP) satellites, and Advanced Microwave Scanning Radiometer for EOS (AMSR-E), Advanced Microwave Scanning Radiometer 2 (AMSR2), Tropical Rainfall Measurement Mission (TRMM) Microwave Imager (TMI), and Global Precipitation Measurement (GPM) Microwave Imager (GMI) onboard NASA and JAXA's satellites. Atmospheric temperature, humidity, clouds, and precipitation are retrieved using brightness temperature data at frequencies between 22 GHz 183 GHz. Some of the brightness temperature and retrieved rain rate data made by these imagers are assimilated in NASA Global Modelling and Assimilation Office (GMAO)'s weather and climate data sets including the Modern-Era Retrospective analysis for Research and Applications (MERRA) and its version 2 (MERRA-2) data sets. However, those radiance data are assimilated with the Goddard Earth Observing System model, version 5 (GEOS-5) only in clear-sky conditions. Recently, we started assimilate GPM/GMI radiance data with GEOS-5's atmospheric data assimilation system GSI under all-sky conditions in order to have better constraints in analyzed hydrological properties. GMAO plans to assimilate more microwave radiometers' brightness temperature data in its analyses. In this talk, we will discuss TMI and AMSR2 data's impact in temperature, humidity, clouds and precipitation under all-sky conditions in future GEOS reanalysis

ACAS-Xu Run 5 HITL (June 2019) SC-228 WG 1.3 Results Outbrief

This presentation provides an overview of a recently completed human-in-the-loop simulation, conducted as part of the Unmanned Aircraft Systems (UAS) Integration in the National Airspace System (NAS) Project. This study examined how to present resolution advisories (RAs) issued by Airborne Collision Avoidance System (ACAS) Xu, which can be in the vertical dimension, the horizontal dimension, or both (i.e., blended). The study varied the location of the ACAS Xu traffic information - it was either presented within an 'integrated' display or a 'standalone' display, where the traffic information was separated from the vehicle control interfaces and navigational information. Results revealed generally positive feedback on the visual and aural presentation of RAs, with special considerations and performance implications noted throughout

Impact of Arsenic Species on Self-Assembly of Triangular and Hexagonal Tensile-Strained GaAs(111)A Quantum Dots

We use dimeric arsenic (As2) or tetrameric arsenic (As4) during molecular beam epitaxy to manipulate the structural and optical properties of GaAs(111)A tensile-strained quantum dots (TSQDs). Choice of arsenic species affects nucleation and growth behavior during TSQD self-assembly. Previously, epitaxial GaAs(111)A TSQDs have been grown with As4, producing TSQDs with a triangular base, and \u27A-step\u27 edges perpendicular to the three 1̅1̅2 directions. We demonstrate that using As2 at low substrate temperature also results in triangular GaAs(111)A TSQDs, but with \u27B-step\u27 edges perpendicular to the three 112̅ directions. We can therefore invert the crystallographic orientation of these triangular nanostructures, simply by switching between As4 and As2. At higher substrate temperatures, GaAs(111)A TSQDs grown under As2 develop with a hexagonal base. Compared with triangular dots, the higher symmetry of hexagonal TSQDs may reduce fine-structure splitting on this (111) surface, a requirement for robust photon entanglement. Regardless of shape, GaAs(111)A TSQDs grown under As2 exhibit superior optical quality

A Detect and Avoid System in the Context of Multiple-Unmanned Aircraft Systems Operations

NASA's Unmanned Aircraft Systems Integration into the National Airspace System (UAS in the NAS) project examines the technical barriers associated with the operation of UAS in civil airspace. For UAS, the removal of the pilot from onboard the aircraft has eliminated the ability of the ground-based pilot in command (PIC) to use out-the-window visual information to make judgements about a potential threat of a loss of well clear with another aircraft. NASA's Phase 1 research supported the development of a Detect and Avoid (DAA) system that supports the ground-based pilot's ability to detect potential traffic conflicts and determine a resolution maneuver, but existing display/alerting requirements did not account for multiple UAS control (1:N). Demands for increased scalability of UAS in the NAS operations are expected to create a need for simultaneous control of UAs, and thus, a new DAA HMI design will likely be necessary. Previous research, however, has found performance degradations as the number of vehicles under operator control has increased. The purpose of the current human-in-the-loop (HITL) simulation was to examine the viability of 1:N operations with the Phase 1 DAA alerting and guidance. Sixteen UAS pilots flew three scenarios with varying number of UAs under their control (1:1, 1:3, 1:5). In addition to their supervisory and sensor mission responsibilities, pilots were to utilize the DAA system to remain DAA well clear (DWC) during scripted conflicts of mixed severity. Measured response times, separation performance, mission task data, and subjective feedback were collected to assess how the multi-UAS control configuration impacted pilots' ability to maintain DAA well clear and perform the mission tasks. Overall, the DAA system proved surprisingly adaptive to multi-UAS control for preventing losses of DAA well clear (LoDWC). The findings suggest that, while multi-UAS operators are able to maintain safe separation (DWC) from other traffic, their ability to efficiently perform missions drastically decreases with their number of controlled vehicles. Pilot feedback indicated that, for this context, the use of automation support tools for completing and managing mission tasks would be appropriate and desired, especially for ensuring efficient use of assets. Finally, human-machine interface (HMI) design considerations for multi-UAS operations are discussed