Health Data Standards and Terminologies A Tutorial

Health Data Standards and Terminologies A Tutorial

Imagine…

Drawing of a doctor and the nurses analyze the patient's medical data.

(Image Source: iStock Photos, Nadezhdu Fedrunova©)

…having your medical information (health patterns, test results, diagnoses, medications, treatments) secure and at the ready to be analyzed and understood by your entire healthcare team and others you choose to share them with.

…that every patient and health professional has access to the best and latest reference, diagnostic, and treatment information the moment they need it.

…that researchers have access to health data so that they can readily explore connections between biology, environment, behavior, disease, and health; and that we can track health and disease trends locally, regionally, globally, in real time, while protecting everyone’s privacy.

How can we go from imagining to reality?

Health Data Standards and Terminologies logo

One great hurdle in realizing a vision of seamless and responsive information systems is that many of our systems don’t connect with each other in useful ways. In a sense, different systems speak different languages. To make these connections happen in the world of health information and have systems work together effectively and securely, we need health data standards.

For software, standards are a set of rules that ensure information is shared uniformly and consistently. Health data standards allow health information systems to share information in such a way that the context and meaning of the information is retained across systems. The National Library of Medicine® (NLM) supports health data standards in several ways, and we are striving to increase adoption of standards in research and healthcare settings.

If you support research or the delivery of health care at any level, this course is for you. This course will introduce you to the fundamentals of health data standards so that you can identify ways that you may already be using standards and consider ways that you can adopt or better implement health data standards into your systems, workflows, and practices.



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