The introduction of Electronic Medical Records software systems has undeniably been revolutionary for many practices in the US; however, it definitely did not come without its up and downs. The prospect of digitizing patient records made a lot of sense in the modern age, especially considering the potential aspects of automation and processing data.
Though in the beginning, some EMR solutions seemed to fall short of this apparent expectation, with recent developments in Artificial Intelligence (i.e. ChatGPT) there appears to be a new aspect that could completely change healthcare IT. So, the question arises, is this new technology sure to enhance and boost the health industry, or does this too have its own hidden downsides?
Processing Big Data in EMR Software
One of the most powerful applications for Artificial Intelligence in Electronic Medical Records Software is predictive analytics. Artificial Intelligence can potentially find patterns in a patient’s medical history and then identify patients who may be at risk.
Additionally, Natural Language Processing (NLP) is another feature that could potentially enhance the physicians’ experience using EMRs. NLP can enable EMR software to interpret human language, making it easier to input patient information and data.
This technology could even potentially analyze clinicians’ notes and automatically make diagnoses, and suggest medications and treatment plans. Healthcare practices amass large amounts of data in their EMR systems, so it’s clear that finding a way to smartly process such huge amounts of data quickly can be invaluable to the physician.
The Risks of Artificial Intelligence in Electronic Health Records Systems
As with anything, AI is not without its downsides. With the use of algorithms, we inevitably run some risk that such pattern-detecting algorithms can lead to potential biases. Just recently, two researchers from the University of Virginia received $5.9 million dollars to analyze if AI in health IT solutions could lead to care disparities. The study aimed to account for living factors such as race, geographic data, and other socioeconomic factors.
One of the more controversial talking points of AI could be what an over-reliance on AI-EMR systems could lead to for the average practitioner. Spending less time on administrative work and more time with patients, undeniably has been something even the best EMR software systems struggle with. However, whilst AI appears to provide the perfect solution, an over-reliance on such technology could lead to irresponsible practice – and artificial intelligence certainly is not perfect.
Some other problems of AI could include security and privacy risks, costs of implementing such technology, and potential hardware limitations too.
Artificial Intelligence in Current Electronic Medical Records Software
As the Health IT landscape continues to shift towards promoting interoperability and increasing the amount of data available to practitioners and clinicians, the prospect of artificial intelligence in these EMR software systems only proves to be more attractive.
Microsoft recently announced a new completely AI clinical documentation app, which can automatically draft notes after patient visits and even telemedicine visits.
Conclusion
Whilst AI can be leveraged to reduce administrative burdens, generate insights, and automate tasks, it’s important that we also consider its potential drawbacks, especially in medical settings. We should take steps to mitigate risks such as bias and privacy concerns. As AI continues to evolve and is adopted into more clinical settings, careful consideration should be taken to ensure responsible implementation in healthcare.
