Both Big Data and Visual Analytics can contribute significantly to improving the quality of health care. A key tenet in quality improvement (QI) is to measure the process where improvement is sought, which can often be a single measure such as time for a patient to receive a specific treatment. However, each data point contains a large amount of supporting information (i.e. a wide dataset), which can include: patient demographic information; patient co-morbidities; time of day that the treatment happened; the specific diagnoses; text-based physician notes; the physician(s) and healthcare professionals that were involved in the care; the prescriptions that the patient was taking; imaging data etc.

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There is no shortage of evidence to show that, in nearly every decision point in life, analytical decision-making is more accurate and produces better decision outcomes. Conversely hunches, intuition, guesstimates, and conjecture based decision making provide for below average performance, and remove the possibility of improved decision making.

Read more: Define and Use Analytics