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In today's healthcare IT world, predictive models—which learn from past data and generate forecasts or suggestions—are typically mentioned when people talk about artificial intelligence (AI). Machine learning (ML) methods, like those used by the Criterions EHR system, are frequently the driving force behind these models.

There are tremendous opportunities for AI, ML, and similar technologies in the realm of healthcare due to the enormous flexibility that gives ML its power. A model can forecast quite accurate predictions and provide suggestions, and we have seen it change many industries. Read some of the examples below of how AI and ML are affecting the healthcare industry.

Automation Return

The return of an EHR investment is guaranteed with machine learning (ML) and other forms of artificial intelligence (AI). It can automate and improve repetitive tasks to assist office staff, automate processes to help increase communication between patients and providers, and suggest treatments for a better patient experience leading to optimized workflow and increased revenue.

Data Analysis

Another advantage is that AI can sift through vast volumes of data to locate specific points that humans can't find or would take years to uncover. Humans can get previously unattainable insights into diagnosis, care procedures, treatment variability, and patient outcomes because of the potential of learning algorithms to become more exact and accurate as they interact with training data.

Staff Shortage

One of the main difficulties that public health professionals face is the issue of personnel shortages, which has affected healthcare providers for many years now. By taking over some of the diagnostic tasks traditionally assigned to humans, artificial intelligence (AI) could assist to offset the effects of this significant shortage of skilled clinical staff. AI imaging technologies, for instance, may frequently achieve a level of accuracy equivalent to people when screening chest x-rays for indications of tuberculosis. A qualified diagnostic radiologist wouldn't necessarily need to be present if this capability could be implemented efficiently.


One of the most interesting future directions for these ground-breaking methods of data analysis and data automation is the use of AI and ML for clinical decision support, risk rating, and early alerting. AI and ML will usher in a new era of clinical excellence and exciting advancements in patient care by powering a new generation of tools and systems that make doctors more aware of nuances, more efficient when providing care, and more likely to get ahead of developing problems.

If you would like more information on how to set up automations within the Criterions EHR system to assist your office staff, please email SUPPORT HERE or fill out the form below and we'll be in touch shortly.

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