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Additionally, the availability of information on DNA sequences of diseases or the chemical makeup of toxins could lead to adversarial hazards, as bad actors could use this information in order to recreate these biohazards on their own. [4] In 2018, a research paper led to media coverage by explaining how to synthesize a poxvirus. [5] [6] [7]
In cases in which a physician has difficulty explaining complicated medical concepts to a patient, that patient may be inclined to seek information on the internet. [8] A consensus exists that patients should have shared decision making, meaning that patients should be able to make informed decisions about the direction of their medical treatment in collaboration with their physician. [9]
Health data are classified as either structured or unstructured. Structured health data is standardized and easily transferable between health information systems. [4] For example, a patient's name, date of birth, or a blood-test result can be recorded in a structured data format.
Data quality refers to the state of qualitative or quantitative pieces of information. There are many definitions of data quality, but data is generally considered high quality if it is "fit for [its] intended uses in operations, decision making and planning ".
The 2018 Verizon Protected Health Information Data Breach Report (PHIDBR) examined 27 countries and 1368 incidents, detailing that the focus of healthcare breaches was mainly the patients, their identities, health histories, and treatment plans. According to HIPAA, 255.18 million people were affected from 3051 healthcare data breach incidents ...
Health information technology (HIT) is "the application of information processing involving both computer hardware and software that deals with the storage, retrieval, sharing, and use of health care information, health data, and knowledge for communication and decision making". [8]
Data manipulation is a serious issue/consideration in the most honest of statistical analyses. Outliers, missing data and non-normality can all adversely affect the validity of statistical analysis. It is appropriate to study the data and repair real problems before analysis begins.
Due to the complexity and variability of public health data, like health care data generally, the issue of data modeling presents a particular challenge. While a generation ago flat data sets for statistical analysis were the norm, today's requirements of interoperability and integrated sets of data across the public health enterprise require ...