Prevention of Medication Errors Medication administration is one of the highest risks in health care‚ and the errors can occur in many ways. Medication errors occur at points of transition in care: admission to the hospital‚ transfer from department to another‚ and at discharge home or to another facility (Taylor‚ Lillis‚ & LeMone‚ 2015). It is at these times we see the greatest room for errors from communication between other departments and facilities. In 1999‚ medication errors were the 8th leading
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Process in Houston CIVT 301 Outline Wastewater collection data in Houston What is sewage treatment? Where does wastewater come from? Factors that affect the flow of pipelines Industrial wastewater? Storm water/ Data The treatment plant operator Sources of wastewater Why treat wastes Waste water treatment facilities Treatment processes Drinking water What can be done to help? Wastewater collection data in Houston 640 square miles area 3 million citizens served 6‚250 miles
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Error Analysis Lab By: Lab Team 5 Introduction and Background: In the process of learning about the importance of measurement and data processing‚ lab teams were given prompts to design experiments as well as address the precision‚ accuracy‚ and error analysis within the experiment. Lab teams collaborated their data to find similarities and differences within their measurements. Through this process‚ students learned the importance of the amount of uncertainty as well as the different
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Data Warehousing‚ Data Marts and Data Mining Data Marts A data mart is a subset of an organizational data store‚ usually oriented to a specific purpose or major data subject‚ that may be distributed to support business needs. Data marts are analytical data stores designed to focus on specific business functions for a specific community within an organization. Data marts are often derived from subsets of data in a data warehouse‚ though in the bottom-up data warehouse design methodology the data
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DataBig Data and Future of Data-Driven Innovation A. A. C. Sandaruwan Faculty of Information Technology University of Moratuwa chanakasan@gmail.com The section 2 of this paper discuss about real world examples of big data application areas. The section 3 introduces the conceptual aspects of Big Data. The section 4 discuss about future and innovations through big data. Abstract: The promise of data-driven decision-making is now being recognized broadly‚ and there is growing enthusiasm
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Medication errors are made time and time again by health care professionals all around the world. Although these errors are accidental they can be life-threatening. There are several types of medication errors that can occur‚ such as prescribing errors‚ transcription errors‚ dispensing errors‚ administration errors‚ and monitoring errors (Clayton and Willihnganz‚ p. 73). In this reading‚ it will specifically talk about an administration error and how it ended the life of a mother-of-four. Arsula
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Background‚ Medication error is common place in healthcare practice; however‚ medication errors are often under-reported. The purpose of this study is twofold; to assess hospital staff’s perceptions of organizational culture of safety in both hospitals‚ and to assess the impact of the organizational safety culture on error reporting. Methods‚ this is a cross-sectional survey conducted among 1300 of hospital staff members in the National Centre for Cancer Care and Research‚ and Heart Hospital‚ from
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Prevalence of Medical Errors Medical errors are currently the 3rd leading cause of death in the United States. These errors happen around us everyday even when we may not notice‚ which has made medical errors the silent killer in medicine. In todays society we must use manpower and our resources to deliver safer care as well as lead with accountability and help our providers to become more engaged. Every healthcare professional should listen to their patients and document care like we would want
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Components of DSS (Decision Support System) Data Store – The DSS Database Data Extraction and Filtering End-User Query Tool End User Presentation Tools Operational Stored in Normalized Relational Database Support transactions that represent daily operations (Not Query Friendly) Differences with DSS 3 Main Differences Time Span Granularity Dimensionality Operational DSS Time span Real time Historic Current transaction Short time frame Long time frame Specific Data facts Patterns Granularity Specific
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Case Study #2- Medication Error 1. Define “overdose.” What are some symptoms of overdose and statistics? Contrast accidental and intentional overdoses. An overdose is when a dangerous dosage of a drug is ingested. Fluctuation vital signs‚ exhaustion‚ dizziness‚ and chest‚ hear‚ and lung pain are all symptoms of overdose. Prescription drugs are the largest cause of deaths from overdose. In 2005‚ out of the 22‚400 overdoses‚ 38.2% were the result of pain killers. Intentional overdose is the misuse
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