The Potential of AI in Electronic Health Records (EHRs)  

 According to one recent study, the global market value of artificial intelligence tools in healthcare was valued at $16.3 billion in 2022. The only thing more impressive than that is that it is expected to hit $173.55 billion by as soon as 2029, representing an annual growth rate of about 40.2%.  Even though it seems like the discussion of “AI” as we currently know it has only just started, there’s already been an enormous surge in popularity. 
  • It’s been estimated that AI has the potential to lower the cost of developing new drugs and medications by as much as 70%. 
  • Predictive artificial intelligence tools can potentially reduce the cost of hospital admissions by as much as 50%. 
  • Right now, about 22% of hospitals or health systems in the United States alone are in the process of “early stage” AI initiatives. That number will explode over the next few years. 
But for as much potential as artificial intelligence in this context seems to have, it’s important to remember that you’re still talking about exactly that: potential.  Right now, the reality of the situation is still a far cry from what many in the healthcare field are being promised. That’s why, when you’re discussing where things are in terms of AI in healthcare and where it all might be headed, there are a number of key things to keep in mind. 

Market Overview and Role of AI

Overall, the global market for artificial intelligence tools in general is expected to hit $184 billion by as soon as the end of 2024. Every year, that will grow by over 28%. By 2030, the market is expected to be valued at more than $826 billion.  Right now, spending in the healthcare sector takes up about 17% of that number. This, too, will continue as adoption in the sector skyrockets. In addition to helping to streamline and optimize administrative workflows, AI in healthcare is being used for tasks like: 
  • Health monitoring. 
  • Imaging. 
  • Clinical trial participation. 
  • Image analysis. 
  • Digital consultations. 
  • Illness detection. 
  • Diagnostics. 
  • Error reduction. 
  • And more. 

Unlocking the Potential of AI in Electronic Health Records

But one of the more fascinating uses of AI in healthcare has to do with its role in electronic health records, or EHR systems for short. 

Many smaller healthcare organizations in particular are finding AI useful in terms of diagnostics support, for example. AI-powered suggestions can help quickly identify diseases that a human might miss or take too long to understand. These artificial intelligence tools can even predict the side effects of certain treatment paths, allowing professionals to arrive at the best outcome far faster. 

AI-powered algorithms are also invaluable in terms of treatment personalization. In a perfect world, every doctor would have the time to come up with a fully personalized treatment plan that is specific to every person that walks through their door. Unfortunately, we don’t live in a perfect world. 

Thanks to artificial intelligence, however, we can get close. AI can quickly identify trends and patterns in symptoms that likely would have taken far longer to recognize. They can predict patient outcomes and even suggest more personalized treatment options based on available accurate data.

Benefits of AI in EHR Systems

Benefits of AI in EHR Systems

Artificial intelligence tools can take an already robust EHR system and make it even better by unlocking additional features like: 

  • Speeding up the management of patient records through features like speech recognition and even AI-powered suggestions for data entry. 
  • Fully automating administrative tasks like appointment scheduling or the creation of clinical documentation. 
  • Providing assistance in diagnostics with an accuracy rate of up to 98.7% in some cases. 
  • Improving patient care by enhancing treatment planning, creating more robust (and accurate) medical records, and more. 

But regardless of which specific use cases you’re talking about, the core benefits are actually straightforward. 

AI can help streamline and improve the efficiency of a healthcare practice, especially on the administrative side. This frees up valuable money that can be funneled back into the practice where it can do the most good. 

It also helps free up the valuable time of medical professionals so they can provide more care and a deeper level of attention-to-detail to patients. This improves patient outcomes, while also improving the quality of the patient experience. 

Collectively, these benefits pave the way for a practice that deals with fewer retention issues and that is able to grow and scale at whatever rate they desire. 

Overcoming Challenges and Ensuring Success
in AI Implementation

The heavy use of an autonomous system like AI in healthcare does present some significant challenges, however, particularly in terms of data privacy and security. 

  • Access controls still need to be in place and strong encryption is not a recommendation, but a requirement. 
  • According to one recent study, the average cost of a healthcare data breach hit $11 million in 2023. Failing to address AI in healthcare from a data privacy and security point of view exposes organizations to that type of financial risk. 

There’s also the matter of data quality and standardization. Remember that all AI tools ingest massive amounts of data to function. If the quality of that data is questionable, the results will be, too. In other words, this is one of those scenarios where the old saying of “garbage in, garbage out” very much applies. 

  • Because of that, standard data formats and coding systems must be implemented to enhance interoperability. 
  • Practices will also need to invest in things like data cleansing to help make sure data quality is where it needs to be to begin with. 

Legal Issues of AI Use in EHR

Another one of the more significant challenges of AI in EHR has to do with the potential legality of it all. 

All EHR systems (and the AI tools that are a part of them) must be HIPAA and/or GDPR-compliant. The fact that humans have a diminished (or at least different) role to play in the management of patient records changes absolutely nothing. 

It’s never been more important for healthcare organizations to work with both legal and compliance experts to make sure that any artificial intelligence tools they implement are up-to-date with ever-changing compliance laws and regulations. 

  • Remember that the penalty for violating HIPAA, even if you had no knowledge of the violation, comes with a minimum penalty of $100 per incident. 
  • It will be very difficult to argue that you had “no knowledge” that the AI-powered EHR your practice was built on was not in compliance with HIPAA. 

How Much Does a Custom AI-Based EHR Cost?

The cost of a fully custom AI-based EHR solution will vary wildly depending on factors like: 

  • The size of your healthcare organization. 
  • The total number of users you have. 
  • Exactly what you need that EHR to be able to do. 
  • The partner you’ve chosen to work with. 

Some estimate that the software development costs start at between $400,000 and $450,000 for the inclusion of basic AI features like dictation or smart suggestions. 

Naturally, the price will only increase from there as more robust features are included. 

EHR Vendors Are Leveraging Generative AI

Another interesting facet of the AI in healthcare discussion has to do with generative A. This is a technology that can create content (including text, images, audio, and video) when prompted by the user. 

Generative AI systems take in massive amounts of data and use it as the basis for creating content that is “similar” based on whatever you prompt it to do. That content is created using machine learning algorithms and statistical models. 

  • Generative AI can be used to quickly summarize new information since a doctor last saw a patient, for example. Rather than spending the time to review someone’s file, you can simply prompt an artificial intelligence tool to tell you exactly what you need to know. You’ll be presented with an accurate, bullet point list from which to draw conclusions from. 
  • Based on all available data like treatment plans and visit records, generative AI can quickly draft a version of a discharge summary when someone leaves the hospital, for example. A human can then quickly review it and make changes as necessary, arriving at essentially the same conclusion in a fraction of the time usually required. 

These are just a few basic examples. From that perspective, AI in healthcare isn’t just a tool that saves time measured in minutes. You’re talking about hours or even days that you can devote to more important matters. 

Start with Expert Guidance for Your AI-Powered EHR

Truly, one of the great things about AI in EHR solutions is that the technology itself is malleable. It can mean a lot of different things to a lot of different practices depending on exactly what they need to accomplish. 

Some simply need something that gives them better control and visibility over patient data. Others will use it to write faster and more accurate clinical notes. Others still need full-fledged clinical decision support. 

But because the possibilities are practically limitless, knowing exactly where to begin on your own AI-powered digital transformation journey can sometimes feel daunting. That’s why things need to begin in the same basic place: with the right partner by your side. 

At Bizmatics, our mission has always been to deliver the best user experience possible to our community of providers. This is true regardless of whether you’re talking about a “straightforward, traditional EHR” or one powered by artifical intelligence tools. 

  • We provide rich features that are tailored to your specific workflows, playing to all the strengths that make you unique. 
  • But more than anything, we take the time to learn as much about your practice and your goals as possible. We want to provide you with the tools and ongoing support you need to play to the strengths that make you unique. 

We’d never tell you that your path towards an AI-powered EHR must start with us. But it absolutely should start with a partner you trust. One capable of providing you with the expert guidance you need to break free of the “one size fits all” approach to technology, for now and for all-time. 

Electronic health records and even AI in EHR are just tools – the same as anything else. What that tool can do means less than what you can do with it under the right circumstances. That’s why, more than anything, we want to help you get the most out of your investment at all times. Not only at the point of initial deployment, but every day thereafter. 

If you’d like to find out more information about the potential of AI in electronic health records, or if you’d just like to see what a tool like PrognoCIS can do for your organization, please don’t delay - contact us today. 


The biggest risk when it comes from the implementation of AI in EHR solutions has to do with data privacy and security. AI systems rely heavily on patient data and that sensitive information has long been a target of hackers and others with malicious intentions. If those AI systems aren’t properly protected, the data inside them could become compromised – causing an untold amount of damage to patients everywhere. 

Other inherent risks that could arise from the implementation of AI in electronic health records include: 

  • An inherent bias and inequality in AI algorithms, as they’re only as unbiased as the data they’re being trained on. 
  • A lack of accountability and transparency. When an AI system makes an error, who is responsible? 
  • An over-dependence on technology. AI isn’t infallible, but if healthcare professionals start to treat it that way, what new risks are we all exposed to?

While there will undoubtedly be some organizations that attempt to use AI in healthcare to replace human professionals in the short-term, there is virtually no risk of this in the long-term. Those organizations will learn a very important lesson the hard way: that artificial intelligence tools aren’t about replacing humans at all. 

In fact, it’s been estimated that as many as 90% of nursing tasks in particular will still be performed by humans in 2030. 

Instead, they’re about supporting and empowering them. Artificial intelligence tools can and should be used to improve the entirety of the healthcare system. They do this in a way that frees up the valuable time of professionals to focus on more important matters. 

The number one way that AI-powered EHRs can benefit small healthcare facilities in particular has to do with enabling improved patient outcomes. 

Artificial intelligence tools can not only support more accurate diagnoses, but can do so earlier as well. They also free up the valuable time of professionals to work on more personalized, patient-specific treatment plans. They can even help predict patient responses to certain types of treatment, increasing the effectiveness of the process overall. 

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