Harnessing the Power of AI Agents in Clinics

McKinsey and Company found that leveraging AI agents in healthcare can save $150 billion in cost annually by automating up to 45% of administrative tasks. Clinics have plenty of time-consuming action items that cost valuable time which could be spent with patients, from long hours of charting to appointment scheduling at the front desk. Here is how AI can play a role in each component of your clinic’s workflow.

Step One: Appointment Scheduling and Patient Intake

Patient intake sounds straightforward, but AI agents can make it smarter.

Speeding Up Intake: According to the American Academy of Family Physicians in 2022, the average wait time to book new appointments for non-urgent primary care has increased to 26 days, up 8% from 2017. Also, patient intake consists of complicated, messy paperwork. AI can be critical to streamlining this process by using voice AI agents and digitized forms to collect answers to HPI and Review of Systems questions. These agents can also ask follow-up questions pertaining to specific clinical presentations so doctors can access this information prior to the visit, saving time. For instance, if a patient is presenting with fever, chills, and cough, a helpful question to ask would be, “have you recently traveled outside of the country?”

EHR Integration: Instead of requiring human intervention to enter answers to intake questionnaires into a patient’s chart, AI agents can integrate with your EHR to enter information free of human error. This also allows for automatic scheduling, as agents can peek into the EHR to find available appointment slots, removing the need for human intervention.

Triaging Appointments: Given the long wait times for primary care, it is helpful for clinics to triage patients based on priority. By fine-tuning agents to identify higher priority cases, clinics can bolster patient satisfaction and avoid overwhelming emergency care systems.

Mental Health Screenings:

Step Two: Pre-Visit Summary Dashboard

Synthesizing Information: Before patient visits, physicians spend hours combing through patient histories for information relevant to the case. Fine-tuned AI agents have the capability to pull out critical information from the patient chart, such as relevant family history or recent irregular lab results and display it in an easy to read, digestible manner. Having the entirety of the relevant details available in a single place can save time and frustration.

Improving Billing: According to the American Academy of Family Physicians in 2016, many clinics miss key billing codes that could increase revenue. Examples include billing for Transitional Care Management, Chronic Care Management, and Advance Care Planning. The pre-visit summary can offer physicians suggested additional services to bill for that may be relevant to the case, ensuring that the physician has a conversation with the patient about these services during the visit.

Step Three: Visit Scribing and SOAP Note Generation

Visit Scribe: While transcribing information from a visit can appear straightforward, AI agents can be critical to ensure that transcription captures complex medical terminology in a precise manner.

SOAP Note Generation: Clinicians spend anywhere from 25 to 47 minutes transferring notes and orders to the chart for each patient, according to the American Medical Association in 2024. SOAP notes (Subjective, Objective, Assessment, Plan) are the standard format for writing patient notes. By summarizing the visit transcript through key word search, agents can generate SOAP notes and transfer them directly to the EHR.

Step Four: Post-Visit Follow Ups and Billing

Answering and Making Administrative Calls: Many clinics offer a messaging or calling service to address patient questions after hours. Instead of requiring a receptionist handling these calls, a voice AI agent can answer these calls and alert the physician on call if relevant.

Improving Billing: To ensure CPT codes are documented for each billable service, either providers, administrative staff, or medical coders need to correctly document services in the EHR. Leveraging input from the care provider, AI agents can correctly bill for services provided during the appointment. What’s critical here is how time sensitive billing can be. If a service is not billed within a few days, it may not generate revenue for the clinic.

What does Execution Look Like

This seems like a lot of different use cases. The good news? ParatusHealth’s EHR-integrated platform offers a solution at every step outlined above in just one packaged service. Book a demo here.