Stakeholders increasingly expect their healthcare providers to be involved with programs for quality improvement. The purpose of this paper is to discuss my organization’s quality program goals‚ how the quality management is structured‚ and who holds responsibility for the organization. This paper will also discuss how my facility selected improvement projects as well as quality methodology‚ tools and techniques for project management. Furthermore I will include nursing’s role‚ communication‚ and
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Consulting approaches to process improvement Bain & Co. Kai A. Simon Viktoria Institute Author’s Note: This is a part of an early draft of my doctoral dissertation that was shortened considerably for the final version. Nevertheless‚ it might be a useful collection of insight for organizations that face a need for redesigning their business processes and wish to learn more about the basic concept and how some major consulting firms approach it methodologically. The series consists of 7 parts
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Lecture Notes 1 Data Modeling ADBMS Lecture Notes 1: Prepared by Engr. Cherryl D. Cordova‚ MSIT 1 • Database: A collection of related data. • Data: Known facts that can be recorded and have an implicit meaning. – An integrated collection of more-or-less permanent data. • Mini-world: Some part of the real world about which data is stored in a database. For example‚ student grades and transcripts at a university. • Database Management System (DBMS): A software package/ system to facilitate
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Data Collection: Data collection is the heart of any research. No study is complete without the data collection. This research also includes data collection and was done differently for different type of data. TYPES OF DATA Primary Data: For the purpose of collecting maximum primary data‚ a structured questionnaire was used wherein questions pertaining to the satisfaction level of the customer about pantaloons product(apparel)‚ the quality‚ color‚ variety of products‚ the availability of different
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Research methods: Data analysis G Qualitative analysis of data Recording experiences and meanings Distinctions between quantitative and qualitative studies Reason and Rowan’s views Reicher and Potter’s St Paul’s riot study McAdams’ definition of psychobiography Weiskrantz’s study of DB Jourard’s cross-cultural studies Cumberbatch’s TV advertising study A bulimia sufferer’s diary G Interpretations of interviews‚ case studies‚ and observations Some of the problems involved in drawing
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Topic 1: The Data Mining Process: Data mining is the process of analyzing data from different perceptions and summarizing it into useful evidence that can be used to increase revenue‚ cut costs or both. Data mining software is one of a number of analytical tools for analyzing data. It allows users to analyze data from many different dimensions or angles‚ categorize it and summarize the relationships identified. Association‚ Clustering‚ predictions and sequential patterns‚ decision trees and classification
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Data Mining Assignment 4 Shauna N. Hines Dr. Progress Mtshali Info Syst Decision-Making December 7‚ 2012 Benefits of Data Mining Data mining is defined as “a process that uses statistical‚ mathematical‚ artificial intelligence‚ and machine-learning techniques to extract and identify useful information and subsequent knowledge from large databases‚ including data warehouses” (Turban & Volonino‚ 2011). The information identified using data mining includes patterns indicating trends‚ correlations
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1 Secondary data analysis: an introduction All data are the consequence of one person asking questions of someone else. (Jacob 1984: 43) This chapter introduces the field of secondary data analysis. It begins by considering what it is that we mean by secondary data analysis‚ before describing the type of data that might lend itself to secondary analysis and the ways in which the approach has developed as a research tool in social and educational research. The second part of the chapter considers
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goal of this project is to identify areas of improvement at the University of Kentucky’s Markey Cancer Center’s Comprehensive Breast Care Center (CBCC) on managed quality workflow. The CBCC ultimately aspires to provide breast care patients with reduced procedure times‚ and transparent cohesive patient location. This project will display an overview of the process; the communication difficulties‚ challenges faced with morale‚ and provided recommendations for improvement. The information collected
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MEASUREMENT It tells us whether there has been a change in performance. Change is a constant. Before we measure we need standards‚ targets‚ requirements etc. we can use to judge the results of measurement‚ in fact there is little point measuring anything unless we have a clear idea of what we are looking for. Three states of nonconformity: Potential Nonconformity – is when conditions are present that may cause nonconformity if no action is taken. Actual Nonconformity - is a verified non-fulfillment of
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