AI's role in smarter care guidance

Many of us have experienced moments of uncertainty after noticing troubling health symptoms, wondering if you should wait and see or seek immediate medical care. Do you stay at home, make an appointment with your PCP, or go straight to the ER? This is a common dilemma that we address using triage.

Triage involves assessing and categorizing patients based on the severity and urgency of their symptoms. Triage will tell you whether you need medical attention ASAP – or if a doctor’s appointment can wait.

But not all triage is good triage. Accurate triage is essential to preventing delays and misallocation of resources and improving outcomes. And AI has become an emerging solution with the potential to improve triage and outcomes across the board.

What does AI virtual triage mean?

In a clinical setting, triage refers to categorizing patients based on their presentation, which helps providers to prioritize which patients to see first and what type of care patients require. Patients are triaged to different types of care depending on the severity of their injuries or illness.

For example, if a patient presents with symptoms of a common cold, such as some sniffles and a cough, a provider will likely advise the individual to self-treat at home. On the other hand, if the patient is presenting with more serious symptoms such as shortness of breath, they may recommend the patient to visit the emergency department. These are two very different scenarios, and thus clinicians would triage the patients differently.

While traditional triaging requires provider assessment and allocation, AI triage can do this independently. AI triage intakes a patient’s symptoms through a self-reported patient survey that inquires about the patient’s current state of health. It then analyzes these symptoms alongside health indicators, demographic data, risk factors, and its medical knowledge database. With these inputs, the AI triage follows a decision tree that categorizes the patient, generating a triage recommendation.

The value of accurate triage

If you’ve ever had a long wait time at the emergency department (ED), you will understand the importance of accurate triage. The ED is notoriously overused, meaning that many patients come in with symptoms that are not necessarily serious and requiring urgent attention. Such cases would be more suitable for an urgent care or primary care visit. But because of ED overuse, hospitals are overburdened with patients and wait times are long. The reverse can also happen, where some individuals are “under triaged”, meaning they don’t seek emergency care when it is warranted. As such, their health outcomes may be poor.

Aside from minimizing wait times, accurate triage also saves providers time. If patients are triaged correctly, ED providers can dedicate more time and energy to serious cases while primary and urgent care providers can dedicate more time to acute conditions. Doing such enables a more efficient and productive health system.

In general, accurate triage has the potential to minimize costs to both the patient and health system, increase patient satisfaction, and improve health outcomes. With AI virtual triage specifically, you can even further optimize patient care through more accurate triage. When patients receive faster and more relevant care guidance, this builds their trust in both digital care pathways and the health systems.

How AI enhances triage

Now that we understand the benefits of accurate triage, let’s discuss the specifics of how AI can further enhance triage efforts:

• Advanced AI. Traditional treatment algorithms are rather rigid and follow rule-based logic. However, AI leverages machine learning to analyze data more dynamically, allowing for more accurate and individualized recommendations.
• Training. AI can be trained on large-scale clinical data, which may include things like electronic health records, diagnostic results, and outcomes. Thus, the dataset it pulls from is likely far larger than a provider’s individual clinical experience.
• Objective data. AI triage can collect and assess objective data. For example, Shen AI measures vital signs such as heart rate and blood pressure, which can provide valuable information on someone’s health aside from just patient-reported symptoms.
• Symptoms alone are not enough. Patient-reported symptoms can vary widely depending on the individual, as symptoms are both subjective and dependent on health literacy. Thus, collection of other health indicators with AI can enhance a patient assessment and triage.

Because of these benefits, AI health monitoring provides an opportunity to strengthen triage. For example, let’s say a user reports experiencing chest tightness. AI health monitoring may also detect an elevated heart rate and blood pressure, indicating a potentially serious condition. AI virtual triage could then provide a recommendation for an ER visit.

Guiding users to the right level of care

Accurate triage is more than just figuring out what’s wrong, it’s about recommending the right level of care at the right time. Different conditions and presentations will necessitate different recommendations, and the range is widespread. Someone may be able to self-treat at home, or they could require a teleconsult, primary care appointment, urgent care visit, or ED visit. 

Because of this, precision matters. Over-triaging can lead to ED overuse, resource strain, and increased costs. Under-triaging could lead to missed diagnoses and poorer health outcomes. Thus, comprehensive and accurate assessments and triage is essential to improving health and optimizing outcomes across the board.

There are several different applications of AI virtual triage, including:

• Health insurers. Insurers can utilize AI-powered triage to direct patients to care that is both high-quality and cost-effective.
• Telemedicine platforms. Telehealth providers can leverage AI-based triage to minimize misuse while maximizing clinician time.
• Remote monitoring programs. Programs for chronic diseases can use AI monitoring and triage to continuously track health indicators, provide alerts, and recommend appropriate next steps.

Wrap Up

In summary, effective triage is essential to ensuring that health outcomes are optimized, hospital systems are not over-burdened, and costs are kept low. AI has the potential to enhance triage through remote health monitoring and leveraging machine learning to triage patients with greater accuracy and precision.