A patient stops by a busy urgent care center for concerning flu-like symptoms. Rather than waiting a couple hours just to start being seen by the nurse, the patient sits at a kiosk and interacts with an artificial intelligence (AI) assistant that asks the patient some questions tailored to the signs and symptoms. The patient can even follow easy instructions to take her own temperature, capture pictures of her ear drums using a digital otoscope and record her heart and lung sounds. The AI system then records this information, infers a probable diagnosis of influenza and sends the information to the clinician’s electronic medical records (EMR) with the Subjective Objective Assessment Plan (SOAP) note mostly filled out. Now, when the patient sees the clinician, most of the work is done and the time can be spent between the patient and clinician discussing the diagnosis and treatment plan.
Another busy patient is on a ranch and has developed a rash. It’s an hour drive to the nearest doctor or urgent care. So instead, the patient uses his phone and sets up a telehealth visit with a doctor right then. The doctor can review the patient’s previous history obtained from the medical record, look at an uploaded picture of the rash sent by the patient and converse with the patient over video. The document note would then be sent back to the EMR along with the rest of the patient’s record. The patient’s regular primary care provider can now access this encounter for follow up.
A busy doctor is seeing 30 patients a day in the clinic. Documentation and order entry is time consuming, but this doctor uses her phone and a special app to record the patient/physician encounter and use natural language processing and machine learning to turn this recording into a SOAP note. In addition, orders for labs and x-rays are captured during the encounter and sent to the EMR along with the SOAP note.
These scenarios are not science fiction. They represent new modalities of capturing patient information outside of the typical workflow—which I will call external apps for now. These modalities are working to be interoperable with the rest of the patient’s health information, which is typically stored in the medical record and claims databases. As their prevalence grows within the health IT ecosystem, it is important to understand how standards are being leveraged to integrate these applications.
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