Health care and health care informatics have an annual ‘buzz-word’. Physicians in clinical practice are bombarded with may medical terms which are fairly well mastered during the course of a career. Their has been many advances in science, biology, medicine and healthcare.
During the pre-clinical years students and physicians use some statitical means to measure probabilities, media, means, averages, standard deviations to determine risks and benefits of treatments. Statistics were taught as a separate free standing course, however unless one was going to be a researcher it was rarely used in every day practice.
In the current environment it has become vital to understand what informaticists learn and teach. Future practice patterns and evidence based medicine will be based on these studies.
In the past clinical situations have been measured fairly subjectively. Now with electronic data storage the data is much more objective, measured and quantified to be recorded. Whether what we are measuring and recording are accurate is another story. However it is the best we have for now.
The tools we use now are far more advanced and capable of storing almost an infinite numbe of data points. Complex algorithms can be derived for calculating multi-factoral variables and to extract hidden relationships in a blizzard of seemingly unintelligible data.
Physicians and patients are just beginning to benefit from these new tools. The evolution of ‘preferred practice patterns’, the cochrane studies, present more objective evidence based studies for clinicians. Meta-studies aggregate multiple related studies to build a greater and/or more diverse cohort.
Medical students and trainees are learning these techniques during their formal education. However the current generation of clinicians have been left behind, as the current knowledge base explodes in size and in methodology.
The growth is fueled by connectivity and also studies done in the late 20th century indicating the exponential growth of information and the technology to run it.
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