5 Artificial Intelligence Trends in Healthcare to Follow
The healthcare industry is always incorporating new technologies into clinician workflows. Many organizations utilize artificial intelligence (AI) to improve treatment efficiency and accuracy. Recent artificial intelligence trends in healthcare reveal how these innovative technologies can improve access to care, enhance disease detection, and optimize health outcomes.
You may be wondering how AI can improve patient care at your facility. In this article, we’ll introduce the concept of artificial intelligence in healthcare and explain how these technologies have the potential to elevate care quality. Then, we’ll list five popular AI healthcare trends you should watch out for to stay ahead of the curve.
What Is Artificial Intelligence?
Artificial intelligence involves the use of algorithms to develop human-like cognition and language. These algorithms enable learning, comprehension, problem-solving, decision-making, and autonomous acts to complete tasks.
What Are Some Examples of Different AI Subfields?
There are multiple artificial intelligence domains, commonly referred to as subfields. Each AI subfield uses unique, tailor-made algorithms to compute different tasks. The following table lists some of the most commonly discussed AI subfields, which should give you an idea of how these technologies work in practice.
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|---|---|
| Artificial Neural Networks (ANNs) | Inspired by the structure of the human brain to enable computers to learn algorithms and solve complex problems |
| Robotics | Helps machines complete tasks accurately and efficiently by allowing them to learn and adapt autonomously |
| Recommendation Engines | Suggests personalized content based on a user’s preferences and behaviors |
| Natural Language Processing (NLP) | Uses machine learning to comprehend and generate human language |
| Generative AI | Enables a computer to develop original content (audio, video, images) in response to a user prompt |
What Is the Role of Artificial Intelligence in Healthcare?
Healthcare organizations are always looking for ways to enhance treatment accuracy, predict patient health trends, and reduce medical errors. Artificial intelligence has the potential to answer many of these problems. Specifically, AI has been known to help facilities:
- Diagnose disease quickly and accurately.
- Predict risks and minimize patient harm.
- Develop personalized treatment plans.
- Streamline administrative tasks and workflows.
- Reduce staffing costs.
- Improve patient engagement.
- Provide higher quality care to a greater number of patients.
5 Artificial Intelligence Trends in Healthcare
Curious about the future of AI in healthcare? Take a look at the following five trends to get a sense of how these technologies will impact patient care efforts in the coming years.
1. Remote Patient Monitoring
Remote patient monitoring (RPM) allows healthcare providers to monitor and treat a patient’s condition from a remote location. This is one of the artificial intelligence trends in healthcare that could have an especially positive impact on rural and underserved communities. When executed appropriately, RPM can help facilities reduce operational costs, improve access to care, enhance patient outcomes, and prioritize in-person care for patients with the most critical needs.
What to Look Out for:
- Use of virtual healthcare assistants for non-emergent patient questions
- Increases in the availability of telehealth provider training
- Advancements in wearable healthcare tracker technology (wireless electrocardiogram devices, continuous blood glucose monitors, etc.)
2. Robotics
Advancing the use of robotics is one of the most commonly discussed artificial intelligence trends in healthcare, especially among surgical experts and biochemical engineers. Recent studies show that the use of robotic surgical equipment can shorten surgical wait times, improve procedural accuracy, and reduce surgical errors.
In addition to the potential benefits of AI robotics in surgical departments, some organizations are also incorporating robots into their nursing workflows. Teams that utilize artificial intelligence in nursing are able to combat persistent staffing shortages by automating tasks like patient teaching and vital sign documentation.
What to Look Out for:
- Use of AI drones to carry out healthcare supply chain deliveries
- Advancements in unmanned and minimally-invasive surgical tools
- Deployment of artificial intelligence “nurses” to carry out basic patient care tasks
3. Clinical Decision Support Systems
Clinical decision support systems (CDSS) develop personalized care recommendations based on a patient’s diagnosis and clinical findings. CDSS has been shown to improve the timeliness of essential medical interventions and reduce errors during diagnosis and treatment.
What to Look Out for:
- Automating radiology scan (X-Ray, CT scan, MRI, etc.) interpretation
- Increasing the use of computer-based provider order entry (CPOE) systems
- Incorporating local/state/federal clinical practice guidelines into CDSS algorithms
4. Drug Development
Artificial intelligence can help scientists speed up the process of drug development by computing large amounts of data quickly and efficiently. Studies that previously took decades to fund and execute can now be completed in a few short years.
AI can also aid in the process of clinical trial design, stratifying patients and identifying population subgroups likely to respond to a particular medication. This is one of the most exciting artificial intelligence trends in healthcare as it hints at the potential for improved global health outcomes.
What to Look Out for:
- Growth of AI in healthcare research topics like precision oncology and new molecule development
- Experiments designed to improve drug potency and life-cycle
- Heavier reliance upon relevant modeling studies
5. Data Management and Analytics
Artificial intelligence is able to recognize patterns and relationships in large sets of data quicker and more accurately than humans. This can help facilities predict trends like:
- How quickly a disease will progress in a certain gender or age group.
- The likelihood that a particular individual will survive an acute illness.
- The approximate length of time it will take a patient to recover from an operation.
Ultimately, automated data management and predictive analytics can help providers efficiently diagnose and pursue treatment options that are best for each patient. Data management AI in nursing can also help clinicians chart patient assessment and vital sign findings quicker and more accurately, allowing them to dedicate more of their time to meaningful patient care.
What to Look Out for:
- Streamlined electronic health record (EHR) management
- Automated coding for medical billing tasks
- Enhanced health data encryption and HIPAA compliance programs
Stay Informed of the Latest Healthcare Innovations
Familiarizing yourself with the latest artificial intelligence trends in healthcare can help you provide innovative patient care. Want to stay informed on other industry changes? Our team of clinical and legal experts has developed hundreds of free healthcare resources and guides to keep you in the know.