Abstract P847: Exploring the Perspective of Patient Recipients of a Provider and Systems-Level Intervention - A Mixed Methods Analysis From the Care Transitions and Hypertension Management (catch) Program for Ischemic Stroke Study

Introduction: The CAre Transitions and Hypertension management (CATcH) program was developed using Lean Six Sigma methodology and is a bundled, multi-faceted, provider- and healthcare systems-level pilot-intervention designed to enhance care coordination. Components of the intervention included: education delivered during the hospitalization, increased utilization of clinical pharmacy and home telehealth for blood pressure (BP) monitoring, and a patient care navigator. Hypothesis: Recipients of CATcH will find the program valuable though engaging with additional care providers may be deemed onerous. Methods: Twenty-eight semi-structured qualitative interviews were conducted between June 2018 and June 2019 among CATcH recipients. Interviews were audio-recorded, transcribed, and entered into an ATLAS.ti. project file. Thematic Content Analysis was used to analyze coded data, generate, and validate findings. Themes related to the overall impression of CATcH and its individual components were investigated across all patients and stratified by age, race, sex, and when they were discharged in relation to beginning of CATcH implementation. Results: A total of 108 Veterans were the recipients of CATcH. All patients received education, patient care navigator services, and offered both clinical pharmacy and telehealth services, with 52/108 (48.1%) attending clinical pharmacy appointments and 37/108 (34.3%) utilizing telehealth services within 6-months post-discharge. Subjects interviewed were on average 68.6±8.2 years of age, predominantly male (26/28; 92.9%) and equally distributed among black and non-black races. Themes were largely positive with patients expressing they were unaware that they were the recipients of an enhanced care program, and that CATcH. Patients who received CATcH in the second half of the program reported better care collaboration and more useful educational materials that those enrolled earlier in the project. Conclusions: Patients found the CATcH program and its component parts useful in the ongoing management of post-stroke BP control. Continuous self-evaluation and refinement of the program throughout the intervention period likely contributed to improvements in care collaboration and education.

Penggunaan Geoda untuk Pemetaan Bencana Alam di Kabupaten Karanganyar

Kemampuan mengolah data menjadi kebutuhan di masa kini, apalagi dengan banyaknya data yang tersedia yang dapat diakses secara bebas. Statistika dapat digunakan untuk membantu masyarakat dalam menjelaskan dan memahami gambaran tentang kejadian bencana alam. Karanganyar, yang terletak di Provinsi Jawa Tengah, merupakan salah satu kabupaten di Indonesia yang rawan bencana alam. Oleh karena itu, diperlukan visualisasi data sebagai upaya untuk memberikan pemahaman kepada masyarakat tentang bencana alam yang terjadi di wilayah Kabupaten Karanganyar. Pemetaan bencana alam dengan Geoda dapat memberikan informasi kondisi kecamatan-kecamatan di Karanganyar yang rawan bencana alam. Untuk menyusun peta, diperlukan data bencana alam serta file peta wilayah. Setelah program Geoda terinstal, peta dapat disusun melalui menu toolbar, mengurutkan kolom kode kabupaten, create project file, dan map. Peta spasial menunjukkan bahwa tanah longsor sering terjadi di wilayah Kabupaten Karanganyar bagian timur yang berbatasan dengan Kabupaten Magetan di Jawa Timur, kebakaran di bagian tengah, dan angin ribut di bagian utara.

Roads Detection and Parametrization in Integrated BIM-GIS Using LiDAR

Building Information Modeling (BIM) has a crucial role in smart road applications, not only limited to the design and construction stages, but also to traffic monitoring, autonomous vehicle navigation, road condition assessment, and real-time data delivery to drivers, among others. Point clouds collected through LiDAR are a powerful solution to capture as-built conditions, notwithstanding the lack of commercial tools able to automatically reconstruct road geometry in a BIM environment. This paper illustrates a two-step procedure in which roads are automatically detected and classified, providing GIS layers with basic road geometry that are turned into parametric BIM objects. The proposed system is an integrated BIM-GIS with a structure based on multiple proposals, in which a single project file can handle different versions of the model using a variable level of detail. The model is also refined by adding parametric elements for buildings and vegetation. Input data for the integrated BIM-GIS can also be existing cartographic layers or outputs generated with algorithms able to handle LiDAR data. This makes the generation of the BIM-GIS more flexible and not limited to the use of specific algorithms for point cloud processing.

Abstract WP320: Uncertainty: A Key Influence in the Decision to Admit Patients With Transient Ischemic Attack

Introduction: Hospitalization of TIA patients has been shown to improve the timeliness and quality of TIA care yet admission rates for patients presenting with TIA vary considerably across centers. Methods: We sought to identify patient and system level factors linked to the decision to admit a patient with TIA. Trained interviewers conducted face-to-face semi-structured interviews with staff involved in TIA care at diverse Veterans Administration (VA) sites. All transcripts were de-identified and imported into a single NVivo10 project file for data coding and analysis. Results: 70 audiotaped interviews of multidisciplinary clinical staff took place at 14 Veterans Administration Medical Centers (VAMCs). We identified emergent themes and patterns in providers’ decision making. Uncertainty was a key theme in factors that staff reported as an influence in providers’ decisions to admit including: lack of guidance at sites without a facility TIA-specific policy, diagnostic uncertainty related to the TIA event (versus stroke or stroke mimic), general lack of confidence in the ability to complete a timely workup, and specific concerns about patients living a long distance from a VAMC or lacking a support system. Overall, the ABCD 2 score was reported by participants not as a rationale for decisions to admit, but rather for decisions not to admit. Other reported factors related to the decision not to admit included: longer period of time since symptom onset, lack of symptoms, confidence in the ability to get a timely workup as an outpatient, recent evaluation for a prior TIA or stroke event, close proximity of the patient’s residence to a VA facility, strong patient support at home, currently maximized medical management, and availability of observation beds. Conclusions: Issues related to uncertainty were reported as key factors in clinical decisions concerning admittance of patients presenting with TIA. Quality improvement interventions for TIA care may need to take into consideration how factors like uncertainty relate to the TIA admission decision-making process.

General Equivalent Magnetic Circuit Calculation Software Based on the Quasi-Newton Algorithm

Equivalent magnetic circuit method is a rapid calculation method used in magnetic circuit simulation. But for a long time this method can’t be used widely because the algorithm is not general and there is no commercial software developed for this method. In this paper, general software for magnetic circuit calculation was developed using LabVIEW language. Quasi-Newton algorithm was used in solving nonlinear Kirchhoff equation of magnetic circuit in this software. The project file in this software can be shared freely in different calculations. This software is expected to save the time-cost in the design of new product.

DSP Transplantation of Motion Object Detection Algorithm Based on TMS320DM642

To build motion object detection system based on DSP (Digital Signal Processor), the motion object detection algorithm by existing is transplanted to the DSP development environment based on adopted DSP hardware system.DSP migration process of the moving object detection algorithm is expounded. First of all, Real-time Workshop tool module in Simulink to establish CCS project file which can be identified by TMS320DM642, then testis processor in the loop (PIL) to verify its correctness. Create system model by Simulink instead of the traditional programming to create DSP project files shorten the development cycle and improve the enforceability of the program. Theresults show that the project files generated by the Simulink can meet the requirements in terms of complete moving object detection.

JSim, an open-source modeling system for data analysis

JSim is a simulation system for developing models, designing experiments, and evaluating hypotheses on physiological and pharmacological systems through the testing of model solutions against data. It is designed for interactive, iterative manipulation of the model code, handling of multiple data sets and parameter sets, and for making comparisons among different models running simultaneously or separately. Interactive use is supported by a large collection of graphical user interfaces for model writing and compilation diagnostics, defining input functions, model runs, selection of algorithms solving ordinary and partial differential equations, run-time multidimensional graphics, parameter optimization (8 methods), sensitivity analysis, and Monte Carlo simulation for defining confidence ranges. JSim uses Mathematical Modeling Language (MML) a declarative syntax specifying algebraic and differential equations. Imperative constructs written in other languages (MATLAB, FORTRAN, C++, etc.) are accessed through procedure calls. MML syntax is simple, basically defining the parameters and variables, then writing the equations in a straightforward, easily read and understood mathematical form. This makes JSim good for teaching modeling as well as for model analysis for research. For high throughput applications, JSim can be run as a batch job. JSim can automatically translate models from the repositories for Systems Biology Markup Language (SBML) and CellML models. Stochastic modeling is supported. MML supports assigning physical units to constants and variables and automates checking dimensional balance as the first step in verification testing. Automatic unit scaling follows, e.g. seconds to minutes, if needed. The JSim Project File sets a standard for reproducible modeling analysis: it includes in one file everything for analyzing a set of experiments: the data, the models, the data fitting, and evaluation of parameter confidence ranges. JSim is open source; it and about 400 human readable open source physiological/biophysical models are available athttp://www.physiome.org/jsim/.

JSim, an open-source modeling system for data analysis

JSim is a simulation system for developing models, designing experiments, and evaluating hypotheses on physiological and pharmacological systems through the testing of model solutions against data. It is designed for interactive, iterative manipulation of the model code, handling of multiple data sets and parameter sets, and for making comparisons among different models running simultaneously or separately. Interactive use is supported by a large collection of graphical user interfaces for model writing and compilation diagnostics, defining input functions, model runs, selection of algorithms solving ordinary and partial differential equations, run-time multidimensional graphics, parameter optimization (8 methods), sensitivity analysis, and Monte Carlo simulation for defining confidence ranges. JSim uses Mathematical Modeling Language (MML) a declarative syntax specifying algebraic and differential equations. Imperative constructs written in other languages (MATLAB, FORTRAN, C++, etc.) are accessed through procedure calls. MML syntax is simple, basically defining the parameters and variables, then writing the equations in a straightforward, easily read and understood mathematical form. This makes JSim good for teaching modeling as well as for model analysis for research. For high throughput applications, JSim can be run as a batch job. JSim can automatically translate models from the repositories for Systems Biology Markup Language (SBML) and CellML models. Stochastic modeling is supported. MML supports assigning physical units to constants and variables and automates checking dimensional balance as the first step in verification testing. Automatic unit scaling follows, e.g. seconds to minutes, if needed. The JSim Project File sets a standard for reproducible modeling analysis: it includes in one file everything for analyzing a set of experiments: the data, the models, the data fitting, and evaluation of parameter confidence ranges. JSim is open source; it and about 400 human readable open source physiological/biophysical models are available at http://www.physiome.org/jsim/.

JSim, an open-source modeling system for data analysis

JSim is a simulation system for developing models, designing experiments, and evaluating hypotheses on physiological and pharmacological systems through the testing of model solutions against data. It is designed for interactive, iterative manipulation of the model code, handling of multiple data sets and parameter sets, and for making comparisons among different models running simultaneously or separately. Interactive use is supported by a large collection of graphical user interfaces for model writing and compilation diagnostics, defining input functions, model runs, selection of algorithms solving ordinary and partial differential equations, run-time multidimensional graphics, parameter optimization (8 methods), sensitivity analysis, and Monte Carlo simulation for defining confidence ranges. JSim uses Mathematical Modeling Language (MML) a declarative syntax specifying algebraic and differential equations. Imperative constructs written in other languages (MATLAB, FORTRAN, C++, etc.) are accessed through procedure calls. MML syntax is simple, basically defining the parameters and variables, then writing the equations in a straightforward, easily read and understood mathematical form. This makes JSim good for teaching modeling as well as for model analysis for research. For high throughput applications, JSim can be run as a batch job. JSim can automatically translate models from the repositories for Systems Biology Markup Language (SBML) and CellML models. Stochastic modeling is supported. MML supports assigning physical units to constants and variables and automates checking dimensional balance as the first step in verification testing. Automatic unit scaling follows, e.g. seconds to minutes, if needed. The JSim Project File sets a standard for reproducible modeling analysis: it includes in one file everything for analyzing a set of experiments: the data, the models, the data fitting, and evaluation of parameter confidence ranges. JSim is open source; it and about 400 human readable open source physiological/biophysical models are available at http://www.physiome.org/jsim/.