Healthcare has been in the spotlight for technological innovation and digital transformation in recent years. First came digital records, then came electronic medical records (EMR), then came electronic health record (EHR) systems. We are now seeing implementations of IoT, Machine Learning, Blockchain, and AI in EHRs and healthcare operations in general. For now, we will be focusing on how AI has and will improve and transform Electronic Health Records (EHR).
What is EHR?
The electronic health record is a collection of patient’s health records. It is continuously synced across various departments and is a real-time collection of complete patient records. In short, EHR is a real-time superset of all medical records of the patient, from various providers, test labs, imagining labs, pharmacies, etc.
What role does EHR and AI-assisted EHR play in improving healthcare?
EHR and AI play a significant role in delivering quality healthcare. They together enable a no error environment, saving lives and improving patient’s experience. To have a better view of how AI and EHRs can do, let’s take in a real-world example.
For example, preventative check-ups are necessary, and many radio scans require a special dye. In normal circumstances, the dye flushes out within a day or two, but it can permanently damage kidneys and even lead to loss of life for someone with kidney conditions. All this could be avoided when an EHR for the patient is maintained. An AI-based EHR software can automatically check the cases with prevailing conditions and notify the lab about it.
Case 1: The use cases when a normal EMR is used, would yield the same consequences as the first part, as the health records might not be searchable by the untrained testing laboratory staff.
Case 2: Since a normal EHR without AI would only have the information fed somewhere in the sheet, there is a considerable possibility for unintended human error, leading to significant damage the same as the example.
Artificial intelligence in EHR has life-saving potential and should be highly considered by healthcare enterprises. AI has huge potential for mapping abilities, and with how complex our bodies are, it should be a top priority to keep the patients safe.
Implementation of AI in EHR systems
With the above example, it might already be clear how AI can aid healthcare and EHRs, but there are many more ways AI can help. Now that we know the importance of EHR and AI let’s find out how AI can further improve EHR.
- Predictive analysis
- Data visualization
- Natural language processing
- Security and privacy
- Pre-existing condition mapping
- Prognosis and diagnosis
- Data fetching from wearables
Let’s begin with a brief explanation of each feature that AI enables in EHR systems.
1. Predictive Analysis
Artificial intelligence plays a major role in predictive analysis in multiple industries at the current time. Almost the same goes for healthcare, but the advantages? Way more when we consider the lives being saved. A powerful AI integrated with a robust EHR can identify risks, evaluate health conditions, and even book auto appointments and call emergency services.
The AI will be able to correlate every test result and suggest a predictive analysis or investigations that need to be done to draw out conclusions. You can leverage the healthcare technology consulting services and explore how next-gen technology is improving with wearables as the Apple watch focuses on health. Technology is improving with wearables as the Apple watch focuses on health. Such data can be directly integrated into EHR, and AI can act as a real-time predictive health analyst and assistant.
2. Data Visualization
Medical records can get vast, even for someone with normal health. With devices like watches generating data each second, it is obvious that large data sets would be present, but the problem with generic EHRs is to navigate them. With AI, this data traversing becomes more straightforward, even in the large EHR environment, and a spotlight option can fetch data required in seconds.
Apart from a spotlight search, normal dataset visualization and correlation can be automatically enabled with a pre-implemented AI. Data visualization is a basic necessity for healthcare professionals and was the main reason why EMRs and EHRs were created. AI takes it much further by enabling dynamic data visualization for which all metrics can be updated each second.
3. Natural Language Processing
What could be worse than asking healthcare professionals to learn accessing complex EHR software? Since they are doing important things like saving lives, the answer is nothing. AI enables searching for the complete database using Natural language processing. Anything can be accessed with queries written in English.
Chatbots are uncommon in generic EHRs, but including AI In EHR software development can make NLP Chatbot integration much easier. Staff wanting to access the data can simply put queries on the chatbot and get results or links to the dashboard in seconds. It enables faster and easier searching through important documents, test reports, and patient history.
4. Security and Privacy
AI-enabled EHR software can make patient health records more secure and safe from intrusions by hackers. Safety protocols can be implemented to ensure zero data leak chances and be governed on lower levels, with the only access point being artificial intelligence.
A standalone EHR system cannot be governed by such security measures, and they have to be built into the system for everyone, while an AI-enabled one can be easily secured and protected from attacks. In the case of health records, security and privacy are top concerns and should be considered while planning the EHR.
5. Pre-existing Condition Mapping
Think of this feature as a life-changing one, and one of the features we have been longing to fully achieve in EHRs. Just like the example we mentioned above, there are thousands of pre-existing conditions that can make further medical procedures dangerous for the patient. An AI-enabled EHR from a good EHR software development company can essentially rule out possibilities based on facts.
For example, someone might have got an allergy test done years ago, and a procedure can complicate the pre-existing condition. While with EHR, the test report would be logged somewhere, it is a long process to go and find it, let alone map it to the procedure in plans. AI-enabled EHR can notify medical practitioners about the allergy based on the procedure to be done as a pre-existing condition, and save the disaster from happening.
6. Prognosis and Diagnosis
Electronic health records serve a great purpose for diagnosis and prognosis, which can be mapped to see if similar conditions existed in the past. AI-assisted EHR systems can essentially draw out even slight general health changes to justify or condemn the said prognosis or diagnosis. Along with the features stated above, AI-enabled EHR will be able to draw out anomalies from data of multiple dimensions and map it directly to the conclusion drawn by doctors, test labs, or ER staff.
7. Data fetching from wearables
We have come very far in terms of continuous health monitoring, almost every health care development solution is shifting focus on it. Wearables generate a lot of data on a daily basis, which can almost become impossible to keep track of for humans. An AI system in EHR can essentially check anomalies that can be missed from the naked eye and present it to the medical practitioner.
Wearables nowadays are capable of recognizing patterns, varying from sleep to waking, and do it very precisely. Even though these may not come in handy in extreme cases, they can really help improve day-to-day life quality for people with life-long diseases. These devices can measure heart rate, blood oxygen, REM sleep continuously, and feed them to the EHR, and we need AI to make sense of it when we need it.
Also Read- A Comprehensive Guide to Electronic Health Record Implementation
Conclusion
We at Matellio believe in taking health care much further than it is, we are continuously improving our development strategies to make the most out of EHR systems. Our AI team is researching more use cases with EHRs and EMRs while considering things which can be implemented in PHRs. AI implementation in EHRs can be truly life-saving on many levels and is our primary focus as healthcare software developers.
We hope we were able to give you an idea of how AI aided EHR systems can essentially save lives and improve healthcare as a whole. IF you are planning a healthcare system or software for your business, feel free to contact us, and we would love to have a chat on how we can improve healthcare together.
