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AI in Nurse Triage: Patient-Facing Applications vs. Nursing Solutions

If you’ve been experiencing staff shortages, you may have considered using technology solutions to fill that gap. Often powered by artificial intelligence (AI), these tools tend to fall into two main groups: patient-facing symptom screening, where patients or nonmedical staff can input symptoms themselves; and nurse triage, where nurses have access to modules that can reduce the time it takes to evaluate patient symptoms and document them more thoroughly. Learn why the latter of these is preferable for better patient outcomes.

AI in Patient Symptom Screening

An AI screening tool looks at patterns and associations from a vast dataset in order to arrive at decisions about what conditions a patient could be experiencing. While this might sound good in theory, we often find that this isn’t the best approach.

For instance, think about a person experiencing chest pain. When using a screening tool, will that patient really know how severe their pain is, and will they trust the disposition generated by the software? They could just as easily (and unnecessarily) end up in the ER by overthinking, panicking, and questioning the results of the screening tool.

AI doesn’t have real-world clinical experience or medical training. Its responses are based on statistical probabilities derived from its training data. This also means that it has no real accountability or responsibility for the outcomes of that data, and cannot be held liable for medical advice or decisions. 

Meanwhile, doctors are trained professionals with medical education, clinical training, as well as hands-on experience. They can use their diagnostics skills and clinical judgment, coupled with their knowledge of each patient’s history, tests, and examinations, to arrive at the appropriate diagnoses. They’re also invested in their patients, responsible for their care, and liable for the accuracy and appropriateness of their treatments.

AI in Nurse Triage

Rather than help patients self-diagnose, use AI in nurse triage to give your medical team tools that can improve their abilities to evaluate symptoms and respond. TriageLogic has developed several that can complement both clinical and nonclinical staff in order to streamline the nurse triage process.

MedMessage Assist™ (MMA). This tool augments patient information gathered by nonclinical operators during the initial phase of a triage call. Using AI technology, this module helps indicate the urgency of calls and increases accuracy and consistency of care.

History Assist. Accurate patient history is crucial in making informed decisions. This module supports nurses in gathering and documenting patient information more efficiently, allowing them to document their triage encounter in minutes.

Quality Assurance (QA) Assist. Quality assurance is an essential aspect of nursing care. QA Assist evaluates the expected protocol and disposition made during every call, comparing them to the selected protocol and disposition utilization. This gives the QA team more comprehensive data, helping to identify improvement areas and celebrating success.

AI Should Complement Your Expertise — Not Replace

While AI has brought many new solutions to the healthcare market, we need to remember that patients are not clinicians and do not have the knowledge and experience to evaluate themselves.

AI may provide information and suggest possible actions based on probabilistic patterns, but it’s better suited as a complement to the expertise of your medical professionals.

Let AI in nurse triage help you improve patient care and health outcomes through the solutions above! Contact us today to talk about a program.

About TriageLogic

TriageLogic is a URAC-accredited, physician-led provider of top-quality nurse telehealth technology, remote patient monitoring, and medical call center solutions. Founded in 2007, the TriageLogic Group now serves more than 22,000 physicians and covers over 42 million lives nationwide.

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