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EpiData is widely used by organizations and individuals to create and analyze large amounts of data. The World Health Organization (WHO) uses EpiData in its STEPS method of collecting epidemiological , medical, and public health data, for biostatistics , and for other quantitative-based projects.
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 ...
Although intervention mapping is presented as a series of steps, the authors see the planning process as iterative rather than linear. [1] Program planners move back and forth between tasks and steps. The process is also cumulative: each step is based on previous steps, and inattention to a particular step may lead to mistakes and inadequate ...
Video Data Analysis (VDA) is a curated multi-disciplinary collection of tools, techniques, and quality criteria intended for analyzing the content of visuals to study driving dynamics of social behavior and events in real-life settings. It often uses visual data in combination with other data types.
The defining functional effect of these technical approaches is that predictive analytics provides a predictive score (probability) for each individual (customer, employee, healthcare patient, product SKU, vehicle, component, machine, or other organizational unit) in order to determine, inform, or influence organizational processes that pertain ...
For example, geographic analysis of health care data from North Carolina showed that just over 40% of the records contained errors of some sort in the geographic information (city, county, or zip code), errors that would have gone undetected without the visual displays provided by GIS. [3]
Data analysis focuses on the process of examining past data through business understanding, data understanding, data preparation, modeling and evaluation, and deployment. [8] It is a subset of data analytics, which takes multiple data analysis processes to focus on why an event happened and what may happen in the future based on the previous data.
Data mining is a particular data analysis technique that focuses on statistical modeling and knowledge discovery for predictive rather than purely descriptive purposes, while business intelligence covers data analysis that relies heavily on aggregation, focusing mainly on business information. [4]