The Role of Artificial Intelligence in Enhancing Custom EHR Functionality

While researching this topic over the internet, I came across thousands of articles that explained the potential applications of artificial intelligence. Though there were some articles that also highlighted some challenges of AI in healthcare, it can be said that the world is expecting AI to be included in healthcare.

However, how the application of AI will come in front of us will be quite hard to predict as of now. Having said that, looking at the current AI landscape many have predicted some of the applications of AI in healthcare and how it can change the way we receive or look at healthcare.

If we have to make the use of AI a norm in healthcare the inception of that has to be sown today. And the process has somewhere begun with a drastic rise in custom healthcare software development.

But this article is not about AI in any generic healthcare software, instead it is about the inclusion of AI in the epicenter of healthcare software systems, the Electronic Health Records.

Seeing the parabolic curve rise in custom EHR software development, it is the right time to build AI-driven custom EHR systems and enhance EHR functionalities with AI.

On that note, let’s explore the different facets of the AI-driven custom EHR system and how it can be the genesis of the future of AI in EHRs and healthcare delivery. So, without further ado, let’s get started.

AI-Driven Data Management & Organization

Let’s begin with the basic functionality of EHR, which is the data management of patients and also the healthcare organization or practice. By enhancing the basic or core EHR functionality with AI, you can put all AI inclusion into action in your practice.

1. Intelligent Data Categorization: AI works on data and till now it has been trained to identify patterns and trends in the data that it is trained on. For your practice which has tons and tons of patient data, it can easily help you categorize the data base on its type. For instance, it can categorize lab results, medical history and medications apart from each other in different categories.

2. Data Normalization: Clean, well-organized data is essential for achieving interoperability. With the use of AI to standardize data from different sources, your system can easily communicate with other systems and exchange data in a way that only makes sense to your software system but also the user.

3. Reducing Data Entry Errors: Medical data entry is one of the reasons why many care plans fail across the globe. However, with an AI-powered EHR solution, this problem can be reduced significantly, if not eliminated.

The collaborative use of custom EHRs and AI can revolutionize care delivery. Though for the moment it will remain the same for patients, but for providers they will have more time to spend on patient care activities with very little chance of committing an error and sharing data effectively and efficiently.

Predictive Analytics & Decision Support with Custom EHR

As we discussed earlier, AI models are basically trained on data, and their algorithms are great at finding patterns that exist in data, right? Well, let’s apply this to clinical practice on patient data. In short, here is how personalized patient care through AI in EHR can be provided:

1. Risk Prediction: As a healthcare provider, you must know that before any major mishap, the body gives you the signal that something is wrong. And as discussed earlier, AI algorithms are great at finding patterns and trends; you can utilize that for predicting patient risks, like which patients are likely to develop chronic conditions or which patients would shortly require readmission. This would help your healthcare providers to make informed decisions and provide better predictive care.

2. Clinical Decision Support: Due to the growing pressure on healthcare providers, there is a high chance that they can miss a crucial pattern in patient data. In such cases, AI can offer decision support to healthcare providers by flagging potential issues and suggesting best possible treatment for the same.

2. Personalized Care: Every patient responds to every disease and medication in a different way. This can be easily observed in patient health records. Here, AI can suggest personalized treatment based on their data, which will further empower healthcare providers to make better and more informed decisions.

AI-powered custom EHRs can personalize the experience for patients and, at times, can even alert clinicians of potential issues such as medication errors and critical lab values and improve patient safety immensely.

AI for Natural Language Processing (NLP) in Custom EHR

Natural language processing is one of the first widely used applications of AI and has been in the landscape of various industries lately. On that note, here are some in which the inclusion of custom EHRs and AI with natural language processing can enhance the quality of your care delivery.

1. Voice Recognition and Documentation: In a scenario where you are consulting with the patient, there can be a chance where you do not understand what the patient is saying. Here with AI, the spoken words can be easily converted into the text format. It not only helps in documentation but also helps in better understanding, improving the clinical efficiency of healthcare providers.

2. Text Mining for Clinical Insights: While the above scenario can be an additional task for your healthcare providers, there is a way which you can use to get know exactly what you want to know from those notes. By using AI to extract meaningful insights from unstructured data such as physician notes or discharge summaries, you get a brief idea about the patient’s health status and enhance the care delivery process.

3. Reducing Documentation Burden: A stat says that 34% of the healthcare providers spend their time on EHRs for documentation processes. To avoid that, AI-powered transcription can automate the documentation process in real time and significantly reduce the documentation time of healthcare providers.

There are various ways in which you can use the full potential of Natural Language Processes in your AI-driven custom EHR system. For instance, it can allow your providers to interact with the software through voice commands and improve efficiency during consultations. However, the primary benefit of AI-powered custom EHRs is that they help to reduce provider burnout and save significant amounts of time for doctors that they spend on documentation and other processes.

AI in Enhancing EHR Interoperability

If you are still reading this, then at the start, we discussed enhancing EHR functionality with AI with data normalization, data categorization, and overcoming data entry challenges. Well all these factors strengthen the base of enhancing EHR interoperability. Here let’s see in detail how it can improve interoperability for your custom EHR software systems.

1. Real-time Data Exchange: Using AI for data normalization, categorization and manual data entry challenges, AI can facilitate seamless integration with other desperate healthcare systems. Once the systems are integrated it can easily be used for data exchange with increased accuracy and privacy.

2. Improved Data Standardization: HL7 FHIR are the industry standards that promote interoperability between healthcare systems. However, different healthcare systems use different standards and formats. In such cases, AI can ensure that the data shared between systems are consistent and align with the standard requirements of HL7 FHIR.

3. Interfacing with Third-Party Applications: Last but not least, establishing integration with external systems like lab services, imaging, and telemedicine platforms can be promoted with AI again on the ground, as we discussed at the start.

The inclusion of AI with custom EHRs can ensure the continuity of care by not only supporting smooth data exchange but also allowing the systems to make sense of the data.

Enhancing Patient Engagement & Experience with AI

Since your custom EHR software will be the point of contact for many of your patients for receiving care, here are some of the ways in which AI-driven custom EHR systems can be used to enhance the overall patient experience and empower them to proactively engage with their care activities.

1. AI-Powered Patient Portals: Patient portals are basically the point of contact for almost everything for patients, from booking appointments to requesting medication refills. Here, including AI-driven tools to provide personalized health insights, reminders, and recommendations can empower patients to proactively participate in making informed decision decisions and stay updated with every activity that is done in their care journey.

2. Virtual Health Assistants: Healthcare providers are already burdened by a huge number of patients. And patients—especially chronic patients—are likely to connect with doctors for even minor inconveniences. In such cases, virtual health assistants such as chatbots powered by AI can help patients book their appointments, provide basic health recommendations, etc. AI-powered EHR solution with chatbots is one of the powerful tools that can revolutionize patient engagement and experience.

3. Improving Patient Communication: Reminders and personalized messages to patients about their health condition can do wonders for engagement and experience. And rather than allowing your healthcare providers to do that, you can integrate those features into your AI-powered custom EHRs. This would streamline the care journey for patients, including follow-ups and other intercassies.

Continuous Learning & System Improvements Through AI

Last but not least, your custom EHR software system will be used for years, and during that time, you will have to make several changes and improvements to the system to enable you to provide better care. In this process, you have to depend on your healthcare IT vendor, but to make their process easier, you can use AI effectively to continuously improve your system and allow it to learn from itself. Here are some of the things that you need to consider in this:

1. AI for Continuous Monitoring: Rather than increasing the burden of your healthcare providers to continuously monitor patients, use the ability of AI to do that. It will not only learn from that data but will also enable real-time patient health monitoring for you. And since it will learn from itself, it will also improve system recommendations and contribute to improving patient health outcomes effectively.

2. Machine Learning Algorithms: Machine learning algorithms are some of the best applications of AI and custom EHRs. After its implementation into your healthcare software, it can easily adapt to the changing nature of the healthcare landscape and help you enhance your workflows. This would significantly reduce the decision-making time and improve the overall quality of care.

3. Leveraging AI for System Updates: The ability of AI that you have to leverage the most is its ability to easily identify patterns and trends. Since it will crawl your entire system, it can easily identify and suggest improvements for you. This way, it can streamline the process of continuous updates and optimize your entire healthcare software system, setting it right for future reference.

Frequently Asked Questions