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Medical data, including patients' identity information, health status, disease diagnosis and treatment, and biogenetic information, not only involve patients' privacy but also have a special sensitivity and important value, which may bring physical and mental distress and property loss to patients and even negatively affect social stability and national security once leaked.
Statistics, when used in a misleading fashion, can trick the casual observer into believing something other than what the data shows. That is, a misuse of statistics occurs when a statistical argument asserts a falsehood. In some cases, the misuse may be accidental. In others, it is purposeful and for the gain of the perpetrator.
He found four types of variation: the underuse of effective care, variations in outcomes attributable to the quality of care, the misuse of preference-sensitive treatments and overuse of supply-sensitive services. [7] According to Health Dialog, a privately held, for-profit disease-management company which was established to address unwarranted ...
Data dredging (also known as data snooping or p-hacking) [1] [a] is the misuse of data analysis to find patterns in data that can be presented as statistically significant, thus dramatically increasing and understating the risk of false positives.
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Unnecessary health care (overutilization, overuse, or overtreatment) is health care provided with a higher volume or cost than is appropriate. [1] In the United States, where health care costs are the highest as a percentage of GDP, overuse was the predominant factor in its expense, accounting for about a third of its health care spending ($750 billion out of $2.6 trillion) in 2012.
• Fake email addresses - Malicious actors sometimes send from email addresses made to look like an official email address but in fact is missing a letter(s), misspelled, replaces a letter with a lookalike number (e.g. “O” and “0”), or originates from free email services that would not be used for official communications.
In statistics, a misleading graph, also known as a distorted graph, is a graph that misrepresents data, constituting a misuse of statistics and with the result that an incorrect conclusion may be derived from it. Graphs may be misleading by being excessively complex or poorly constructed.