How AI Benefits EHR Systems

As AI continues to make waves across the medical ecosystem, its foray into the world of EHR has been interesting. This is obviously because of the countless benefits both systems offer. Now, imagine you use a basic EHR for patients. One patient is administered an MRI contrast agent before the scan. What you may not know is that they are prone to an allergy or conditions that could cause the dye to negatively affect the patient. Perhaps the data was in the patient’s EHR but was buried so deep that it would have been impossible to look for it specifically.

An AI-enabled EMR, on the other hand, would have been able to analyze all records and determine if there was a possibility of any conditions that may render the patient susceptible to adverse reactions and alert the lab before any such dyes are administered.

Here are other benefits of AI-based EHR to help you understand how they contribute to the sector.

  1. Better diagnosis: Maintaining extensive records is extremely helpful for making a better, more informed diagnosis. However, with AI in the mix, the solution can then identify even the most nominal changes in health stats to help doctors confirm or disprove it. Furthermore, such systems can also alert doctors about any anomalies and straight away link them to reports and conclusions submitted by doctors, ER staff, etc.
  2. Predictive analytics: Some of the most important benefits of AI-enabled EHRs is that they can analyze health conditions, flag any risk factors and automatically schedule appointments. Such solutions are also able to help doctors corroborate and correlate test results and help set up treatment plans or further medical investigations to deliver better and more robust conclusions about patients’ well-being.
  3. Condition mapping: Countless pre-existing conditions may impede medical diagnosis and procedures challenging or even dangerous. This can be easily tended to by AI-enabled EHRs that can help doctors rule out any such possibilities based on factual information.

Now, let’s look at some of its challenges.

  1. Real-time access: For data to be accessible by AI, the vast amounts of data generated by a hospital daily are stored in proper data centers.
  2. Data sharing: Of course, the entire point of EHRs is to make data accessible. Unfortunately, that isn’t exactly possible until you have taken care of the storage and that it is in the requisite formats. Unprocessed data is not impossible for AI to sift through but it does count up as a completely different task — one that takes a toll on the time taken to execute AI’s other, more important objectives in this context.
  3. Interoperability of data: It is not enough to just be able to store data; the said data must be also readable across a variety of devices and formats.

Artificial intelligence has a lot to offer when it comes to electronic health records and the healthcare sector in general. If you too want to put this technology to work for you, we recommend looking up a trusted custom EHR system development service provider right away and get started on the development project ASAP.

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