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Data presentation architecture weds the science of numbers, data and statistics in discovering valuable information from data and making it usable, relevant and actionable with the arts of data visualization, communications, organizational psychology and change management in order to provide business intelligence solutions with the data scope ...
Healthcare quality and safety require that the right information be available at the right time to support patient care and health system management decisions. Gaining consensus on essential data content and documentation standards is a necessary prerequisite for high-quality data in the interconnected healthcare system of the future.
Visual analytics seeks to marry techniques from information visualization with techniques from computational transformation and analysis of data. Information visualization forms part of the direct interface between user and machine, amplifying human cognitive capabilities in six basic ways: [2] [5] by increasing cognitive resources, such as by ...
Health care analytics is the health care analysis activities that can be undertaken as a result of data collected from four areas within healthcare: (1) claims and cost data, (2) pharmaceutical and research and development (R&D) data, (3) clinical data (such as collected from electronic medical records (EHRs)), and (4) patient behaviors and preferences data (e.g. patient satisfaction or retail ...
This fundamental change in health care (pay for performance) means that hospitals and other health care providers will need to develop, adapt and maintain all of the technology necessary to measure and improve on quality. Physicians have traditionally lagged behind in their use of technology (i.e., electronic patient records).
Tukey defined data analysis in 1961 as: "Procedures for analyzing data, techniques for interpreting the results of such procedures, ways of planning the gathering of data to make its analysis easier, more precise or more accurate, and all the machinery and results of (mathematical) statistics which apply to analyzing data." [3]
Hands-On Data Visualization details design methods for interactive charts and customized maps, starting with drag-and-drop tools including Google Sheets, Datawrapper, and Tableau Public. It progresses to detail methods for editing source code templates built with Chart.js, Highcharts, and Leaflet on GitHub.
Data exploration can also refer to the ad hoc querying or visualization of data to identify potential relationships or insights that may be hidden in the data and does not require to formulate assumptions beforehand. [1] Traditionally, this had been a key area of focus for statisticians, with John Tukey being a key evangelist in the field. [5]
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