723 research outputs found

    Systematic review of hospital readmissions in stroke patients

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    Background Previous evidence on factors and causes of readmissions associated with high-impact users of stroke is scanty. The aim of the study was to investigate common causes and pattern of short- and long-term readmissions stroke patients by conducting a systematic review of studies using hospital administrative data. Common risk factors associated with the change of readmission rate were also examined. Methods The literature search was conducted from 15th February to 15th March 2016 using various databases, such as Medline, Embase, and Web of Science. Results There were total of 24 studies (n=2,126,617) included in the review. Only 4 studies assessed causes of readmissions in stroke patients with the follow-up duration from 30 days to 5 years. Common causes of readmissions in majority of the studies were recurrent stroke, infections and cardiac conditions. Common patient-related risk factors associated with increased readmission rate were age and history of coronary heart disease, heart failure, renal disease, respiratory disease, peripheral arterial disease and diabetes. Among stroke-related factors, length of stay of index stroke admission was associated with increased readmission rate, followed by bowel incontinence, feeding tube and urinary catheter. Conclusion Although risk factors and common causes of readmission were identified, but none of the previous studies investigated causes and their sequence of readmissions among high-impact stroke users

    A data warehouse environment for storing and analyzing simulation output data

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    Discrete event simulation modelling has been extensively used in modelling complex systems. Although it offers great conceptual-modelling flexibility, it is both computationally expensive and data intensive. There are several examples of simulation models that generate millions of observations to achieve satisfactory point and confidence interval estimations for the model variables. In these cases, it is exceptionally cumbersome to conduct the required output and sensitivity analysis in a spreadsheet or statistical package. In this paper, we highlight the advantages of employing data warehousing techniques for storing and analyzing simulation output data. The proposed data warehouse environment is capable of providing the means for automating the necessary algorithms and procedures for estimating different parameters of the simulation. These include initial transient in steady-state simulations and point and confidence interval estimations. Previously developed models for evaluating patient flow through hospital epartments are used to demonstrate the problem and the proposed solutions

    An OLAP-enabled software environment for modelling patient flow

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    On-Line Analytical Processing (OLAP) tools use multidimensional views to provide quick access to information. They have become the de facto standard in the business world for analytical databases. In health care, care givers and managers could benefit from being able to perform interactive data exploration, ad-hoc analysis and possibly discover hidden trends and patterns in health data. However, health data have unique characteristics that distinguish them from common business examples, an aspect that makes the direct adaptation of the already established business oriented solutions difficult. In this paper we report the development of an OLAP system for analyzing hospital discharge data and for modeling hospital length of stay

    Agent-based models for community care systems analysis and design

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    In recent years, the providers of public and private sector health care services have been faced with some radical changes in the society they serve, and more importantly, development in the way that traditional health care is delivered to Information Technology (I.T) based communities. It is widely believed by health care professionals that the better health care results really come from the improved healthcare systems and more effective health care services' management. This paper focuses on using an agnet-based software engineering approach and design models to the development of an appropriate agent-based healthcare software system is described in which software researchers collaborate with environment builders to enhance the levels of cooperation and support provided within an integrated agent-based community healthcare system

    iPath3.0: interactive pathways explorer v3

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    iPath3.0 (http://pathways.embl.de) is a web-application for the visualization and analysis of cellular pathways. It is freely available and open to everyone. Currently it is based on four KEGG global maps, which summarize up to 158 traditional KEGG pathway maps, 192 KEGG modules and other metabolic elements into one connected and manually curated metabolic network. Users can fully customize these networks and interactively explore them through its redesigned, fast and lightweight interface, which highlights general metabolic trends in multi-omics data. It also offers navigation at various levels of details to help users further investigate those trends and ultimately uncover novel biological insights. Support for multiple experimental conditions and time-series datasets, tools for generation of customization data, programmatic access, and a free user accounts system were introduced in this version to further streamline its workflow

    Statistical Shape Modelling for the Levator Ani

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    Defective pelvic organ support due to injuries of the levator ani is a common problem in women and its intervention requires a thorough understanding of the structure. Three-dimensional surfaces of the levator ani have proved to be a promising method of studying this. In this paper, we propose to build a statistical shape model (SSM) of the levator ani and describe a segmentation technique based on a limited number of control points with the SSM. The SSM was achieved by the use of harmonic shape embedding with the MDL objective function to optimise parameterisation while segmentation was performed by fitting the model to a user defined set of control points. The value of the technique was demonstrated with data acquired from a group of 11 asymptomatic subjects.Accepted versio

    Data warehouses-TOLAP-decision making

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    Data warehouses (DWH) have been established as the core of decision support systems. On top of a DWH, different applications can be realised with regard to conventional reporting. On line Analytical Processing (OLAP) has reached the maturity as an interactive and explorative way of analysing DWH data. However DWH are mostly organised as snapshot databases. For this reason important tasks like "how many times have products of a specific brand been sold in the "past?" cannot be answered successfully - in order to control the success of reshuffling the product range it is necessary to compare the sales of "old" and "new" products. The same applies in cases where the seasonality aspect for a particular range of products has to be answered. On the other hand, temporal databases allow a valid time to be assigned to data. In this manner, a past state can be reconstructed during retrieval. In this paper, we address the integration of DWH and OLAP with temporal database semantics
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