The healthcare and medical industry can vastly benefit from adopting advanced technologies like AI, ML, NLP, etc. Here, we’ll discuss AI agents in healthcare and the role of artificial intelligence in boosting the sector in various ways.
Artificial intelligence has become a part of many industries, including healthcare. In fact, AI has many uses in the medical and healthcare sector. According to Grand View Research, the global AI healthcare market is estimated to grow at a CAGR (compound annual growth rate) of 38.5% between 2024 and 2030. The AI healthcare market shot up by a whopping 233% between 2020 and 2023, the Covid-19 pandemic and post-pandemic years.
Another report shows that over 60% of people from healthcare in South America and the Asia Pacific regions believe AI will play a prominent role in decision-making in the next ten years, with the Middle East in the third place. The clinicians from North America and Europe aren’t as convinced but AI is majorly used (at 29%) in clinical decision support tools in the US.
AI in healthcare is helpful for doctors, surgeons, patients, medical/ lab technicians, and administrative teams. The popularity of generative AI and the development of AI agents has enhanced the use of new technologies in the industry. In this blog, we will read more about the uses, benefits, and need for AI agents in healthcare as well as the role of artificial intelligence in the medical sector.
An AI agent in healthcare is an intelligent software program trained on patient and medical data to provide virtual assistance by processing input and delivering relevant outcomes.
The AI agents’ framework consists of five key components listed below:
AI agents use machine learning algorithms to identify patterns and discover trends or correlations in historical data to predict outcomes, diagnose diseases, recommend treatments, or determine the risk factors when considering a treatment/ surgery.
By using NLP, the AI agents can accurately understand and interpret human languages. This reduces the risk of error caused by misunderstanding the content or context. NLP helps in answering queries by patients, filling their forms/ medical records, and generating reports.
The AI agents’ architecture also includes technology to process audiovisual content like images and videos, X-rays, CT and MRI scan reports, etc., to identify patterns, detect early signs of diseases, and more. Tumors or cancerous cells can be identified before they affect the patient’s health adversely. Computer vision is also used when performing surgeries.
Another role of AI agents is to regularly interact with humans (be it doctors, nurses, admin staff, or patients) and assist them however necessary. For this, the software is trained to have a user-friendly interface with adaptability and responsiveness.
AI agents can be used to analyze datasets and derive actionable insights, future predictions, etc. From identifying the appropriate treatment method to post-care planning, the AI agent can help at every stage. It can provide the required insights and reports for the concerned parties to make the right decisions.
Medical treatments are diverse and personalized based on the patient’s medical history and overall health condition. Moreover, concerns like allergies to active ingredients in drugs should be considered when prescribing medication. By digitalizing patient records, hospitals can use AI agents to create a quick and accurate report about the patient’s condition and provide it to the doctor. This allows the doctor to prescribe an appropriate drug or a treatment plan. Even if the patient forgets to inform during the appointment, the AI agent can ensure the doctor has all the necessary information to make the right decision.
IoT (Internet of Things) devices like sensors on wearables can be used to collect patient data in real-time and send alerts as necessary. For example, a patient recovering from a surgical procedure can be monitored through the AI agent that tracks their vitals like heartbeat, blood pressure, etc. The nurses can be quickly alerted in case of emergencies. Furthermore, patients recovering at home can also be monitored remotely through AI agents. The hospital can send someone to treat the patient or contact them immediately to provide support.
Administrative processes and revenue cycle management (RCM) can be streamlined using AI agents in healthcare. From automatically updating patient records in the central database to scheduling appointments and follow-ups, sending alerts to reduce waiting time, and tracking appointments to provide a better experience, AI agents have varied roles in increasing operational efficiency. The admin staff can use AI agents to ensure the claim submissions are accurate and get quick reimbursements from payers. Generating invoices and printing bills is also easier.
Sometimes, healthcare providers may have to come up with new treatments or drug combinations based on the patient’s condition and medical history. They can use AI agents to analyze the data and predict the possible outcomes of using a particular drug or procedure. This reduces the risk factor as they don’t have to rely only on guesswork or trial and error. It may lead to new discoveries and help more patients with similar conditions. Similarly, AI agents can provide insights about the benefits and potential side effects of a medicine on a patient.
AI agents can assist surgeries in many ways. One method is the support provided to robotic arms. Another method is through read-aloud devices or communicator tools that list the patient’s history to the surgeon and help them make proactive decisions during emergency situations. Instead of waiting for someone to gather the information, the AI virtual assistant will deliver the reports in real time. Saving a few precious minutes during complex surgical processes is a matter of life and death.
We cannot ignore the importance of providing mental health support to patients and medical staff. There are quite a few AI agents built on conversational AI that act as chatbots and virtual counselors. Patients can interact with these AI agents to share their worries/ troubles or get advice on how to improve their mental health. Moreover, the AI agents can detect early signs of mental health decline and recommend ways to tackle the situation.
Since AI agents are powered by ML and NLP algorithms, they can seamlessly optimize the workflows in various departments and ensure real-time access to data and insights from personalized dashboards. By eliminating unwanted steps and manual permissions, the staff can save time and provide better administrative services to patients. This also reduces operational costs over time.
All decisions made in the healthcare center can be based on data-driven insights instead of guesswork. Be it administrative choices or medical treatments, AI agents can process the information in the central database and generate relevant reports. Additionally, health trends can be predicted in advance to hire more staff, outbreaks can be handled effectively by taking appropriate measures in advance, and high-risk patients can be identified early.
AI agents built on NLP algorithms are capable of understanding numerous human languages. They can process voice and text content, understand the context, convert speech to text or text to speech, and do much more. This allows patients from diverse lingual and social backgrounds to communicate with the AI agent in a language of their choice. Healthcare centers with a global network can vastly benefit from this.
Personalization is one of the biggest benefits of artificial intelligence. Instead of providing pre-written answers to every patient, AI agents use the patient’s records to understand their input and provide a response. They can track previous messages and appointments and recognize repeat patients. This prevents the AI agent from making incorrect recommendations to patients.
AI agents are built to be adaptable and scalable. They can handle heavy workloads when necessary and deliver consistent performance. Healthcare centers can rely on AI agents to handle extra work instead of hiring more employees. Despite the need for initial investment, AI agents can be a cost-effective solution in the long term. Moreover, the service providers ensure the software follows the security and privacy regulations to protect confidential data.
AI agents are developed for a variety of uses and can be broadly classified into the following five types:
As the name suggests, the AI agents follow the simplest process. They use only the current or real-time information and ignore the rest. Simple reflex agents have highly limited intelligence skills and cannot adapt to changing environments.
For a model-based reflex agent, the AI agent builder uses a specific model to develop the tool/ chatbot to perform the actions for the given input. These AI agents can partially track the situation and observe the environment to an extent.
A goal-based agent can be termed as an extension of a model-based agent where the action is decided based on the required/ pre-defined goals. The agents can consider a longer sequence of actions and choose the best from those.
Utility-based agents are one step ahead of goal-based agents as they consider not only the goal but also the best way to achieve the goal. These are proactive and useful when the AI agent has to choose an appropriate action from many alternatives.
A learning AI agent has learning capabilities and processes historical data to adapt to changing environments and conditions. They can analyze performance and find new ways to deliver better results based on the insights.
Though we use an umbrella term, Artificial intelligence (AI), it includes advanced technologies like machine learning (ML), deep learning, natural language processing (NLP), computer vision, etc. The predictive abilities and the capacity to process large amounts of data in a short time have been helping healthcare professionals effectively manage patient records, provide quicker and more accurate diagnoses, and reduce the risk of uncertainties.
Here are a few uses of artificial intelligence in healthcare:
Developing new drugs is a time-consuming and cost-intensive process. It requires tremendous amounts of research and human expertise. The cost of running clinical trials is also high. By using AI in drug discovery, scientists and researchers can speed up the process of creating new combinations of ingredients and predicting the side effects. It can also help in identifying the target groups for clinical trials and recording observations more efficiently.
Diagnosing the symptoms correctly is necessary to provide suitable treatment and save a patient’s life. However incomplete patient records, human error, and other factors can lead to incorrect diagnosis or wrong treatment. With AI agents, healthcare centers can streamline data collection and maintain patient records in a secure cloud platform. Computer vision technology is used to compare images (X-rays, scans, etc.) and identify diseases in their early stages. Critical conditions like tumors and cancers can be detected early and accurately.
AI agents in healthcare are just as helpful in the administrative, financial, sales, and billing departments. The non-medical staff can save time and energy by using AI-powered dashboards and automated tools to update patient records, generate bills, submit claims, and close payments. Artificial intelligence can redefine RCM (revenue cycle management) in hospitals and provide in-depth analytical insights to fine-tune the system and provide seamless services to patients.
A hospital and clinic’s responsibilities are not limited to providing treatments. Patient care has to be a complete and holistic experience. From the moment the patient contacts the hospital to post-treatment care and timely alerts for follow-ups, the healthcare center has to provide guidance, assurance, and support to patients. AI can enhance this process by sending automated alerts, scheduling appointments, simplifying the billing process, etc. This not only increases patient satisfaction but also allows hospitals to treat more people every day.
AI and robotics are used to provide assistance to surgeons in the operation theatre. The robotic arms are more flexible and can perform tricky surgeries or provide a 360-degree view of the surgical site to help doctors be more precise and efficient. Surgeries performed with assistance from robotic arms can be completed quickly and also result in a faster recovery time as smaller cuts/ incisions are made on the patient’s body.
AI agents in healthcare have been revolutionizing the industry by providing support for data-driven decision-making, efficient patient management, and controlling automated workflows. Being trained on large amounts of healthcare data makes AI agents useful in identifying patterns and unlocking meaningful insights.
Healthcare centers can partner with AI service providers to build tailored AI agents for their establishments. From patient registration to post-treatment support, hospitals can use AI agents for diverse purposes. Improve the quality of patient care by investing in robust artificial intelligence agents.
AI agents can be customized or built from scratch by artificial intelligence product development companies. Be it conversational AI or generative AI, the agent can be designed based on your specifications and long-term goals. Integrating AI agents into the internal processes is a great way to optimize resources, assist doctors, increase system efficiency, enhance patient experience, and increase ROI.
Read the following links to learn more about AI in healthcare.
Several AI tools are used in healthcare, depending on the requirements and other factors. For example, Microsoft Azure AI can be used to quickly gather credible patient information from cloud records while DAX (Nuance Dragon Ambient eXperience) is a smart assistant developed for doctors to record and covert patient conversations into medical notes.
There is no single AI tool that’s used the most in the industry. The AI agents’ marketplace has many advanced chatbots, applications, and virtual assistants for the healthcare industry. For example, Lindy’s AI Medical Scribe reduces 80% of charting time and provides 99% accuracy. The da Vinci Surgical System by Intuitive Surgical has already supported over 14 million surgeries around the globe.
You can find many examples of AI agents in healthcare. Agentic AI by Cognigy is one such example. This AI agent can be used for making appointments, updating insurance details, providing referrals, engaging with patients post-discharge, etc. It also has voice assistance to provide patient-friendly services.
Fact checked by –
Akansha Rani ~ Content Creator & Copy Writer
