Artificial intelligence—also referred to as augmented intelligence or AI—has exploded in popularity. People across many professions are incorporating it into their workdays, including health practitioners.
AI for medical professionals differs from the models used in smartphones and search engines. But the appropriate tools have proven useful in a variety of healthcare applications.
Below, explore the role of AI in healthcare with five unique applications and tips for determining if it’s right for your practice.
1. Disease Detection
Many AI tools have proven helpful in disease detection, often before symptom onset. When combined with human oversight, these systems may help patients receive a diagnosis and start treatment faster.
Additionally, AI can help increase the accuracy and speed of medical image interpretation. In doing so, these tools can flag early signs of cancer, tumors, chronic pulmonary disease, and diabetic retinopathy.
Overall, healthcare AI can serve as a diagnostic aid, helping reduce medical errors and improve case prioritization efforts.
2. Population Health Management
Generative AI could also play a role in population health management by predicting health trends and analyzing data. For example, AI can help determine which populations are at risk for specific diseases.
With that information, providers can create comprehensive intervention and resource plans. In the same vein, some AI tools can recommend proactive measures that protect patient well-being.
3. Personalization
When an AI tool has access to patient data, it has been shown to predict a person’s response to medications, treatments, or therapies.
Doctors can also use AI to tailor treatment plans to each person through modeling, predictions, and care plan suggestions.
4. Clinical Knowledge Queries
Providers have begun using AI tools to engage with clinical knowledge. With the appropriate prompts, AI can explain standards of care, medical research, and guidelines.
AI can also answer specific questions about or summarize research papers and journal articles. In fact, a recent American Medical Association (AMA) survey found that four out of 10 physicians use AI for this purpose.
5. Ambient Listening
When you think of AI in a clinical context, ambient listening is often among the first things that come to mind. That’s because taking notes during appointments can hinder the patient-provider connection, lower patient satisfaction, and increase provider burnout.
However, ambient listening technology can transcribe conversations and draft clinical notes. As a result, clinicians can be more attentive, which helps build better connections with patients and improve provider well-being.
Top AI Applications in Healthcare for Physicians
Although AI is a controversial topic, it can help enhance accuracy and efficiency when used appropriately. Here are some of the most common reasons providers use AI:
- To summarize health research or standards of care
- To add documentation to patient charts, visit notes, or billing codes
- To develop discharge instructions, care plans, or progress notes
- To generate draft responses to messages
- To summarize medical charts or provide translation services
- To assist in diagnosis
With that said, not all AI tools are created equal, nor are they all appropriate for a clinical setting. Providers need to know how to determine whether a potential addition will truly be useful to their practice.
How to Determine If an AI Tool Will Benefit Your Practice
The AMA suggests developing an “AI framework” to help you determine if a new tool is right for your practice. Here are three questions to consider:
- Does it work? Examine the evidence behind the AI tool. Determine if it’s effective, equitable, and designed with patient safety and medical ethics in mind.
- Does it benefit patients? Ensure that the AI system is supported by evidence that it can improve care for patient populations like yours. Additionally, check that your team has the resources to implement it ethically.
- Does it enhance health outcomes? Providers should review the tool’s case studies, research, and evidence for proof that it can improve outcomes.
As with any new technology, health leaders must do their due diligence before deciding to implement an AI tool.
