Medical informatics must translate data into actionable, meaningful knowledge. By harnessing the intuitive nature of search engine algorithms and real time data analytics, we can transform how clinicians address patient conditions and determine diagnoses and treatments. Giving the clinician information at the point of care significantly enhances customization of patient treatment plans and promotes population health.

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The secondary use of medical data residing in the vast databases of Health Information Exchanges can empower clinicians to receive decision support closely tailored to patients’ unique medical characteristics. Nonetheless, the method for secondary use of data must protect the privacy and security of all individuals.

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Health Information Exchanges must go beyond the role of serving as surrogates for archived paper records. When we normalize data and share knowledge with providers about complex patients who are very similar to those examined or treated at the point of care, we enable clinicians to make patient specific, rational decisions for their most complicated patients. Natural language processing (NLP) will simplify the provider’s documentation process, while incorporation of artificial intelligence (AI) and large language models (LLM) will play decisive roles in supporting predictive modeling and data analytics.