How to do patient intake automatically

Here’s how you can do patient intake in Amazon Connect and reduce your patient wait times (get better reviews)

Categorized as Technology Tagged

Patient intake doesn’t get enough attention whereas it should.

Think about how much time your technicians spend “working up” patients and doing medication reconciliation for each patient visit.

If you could save 10-15 mins per patient work up, how many more patients could you see per day?

Or, how much faster could you get done in a day?

How much could you reduce your patient wait times by?

We recommend that you get patient intake done before the patient comes in for the visit.

You can get this done very easily by using a combination of Amazon Connect, Amazon Transcribe and Amazon Comprehend Medical.

You can integrate these services and use them in conjunction with services like AWS Lambda, Amazon S3 , Amazon Pinpoint, Amazon DynamoDB, and Amazon SQS to create a serverless healthcare solution, completely on top of AWS.

There’s a wonderful blog here that can be modified to implement this solution (Enabling efficient patient care using Amazon AI services | Amazon Web Services)

Here’s what needs to be done:

  1. Use Amazon Pinpoint to run a campaign that sends an SMS to each patient with an upcoming appointment asking them if they’re ready for their intake call. If they’re ready, they can respond with a SMS “CALL” OR “YES”
  2. Use Amazon Pinpoint and Amazon SNS to capture this response and trigger off an Amazon Lambda call. This Amazon Lambda calls Amazon Connect and calls the patient to start the patient intake.
  3. When the patient picks up / answers the call, Amazon lambda still authenticates the patient by asking them to verify at least 2 pieces of PHI. For this, Amazon Lambda does data dips into your EMR. If the patient has successfully authenticated, the patient proceeds with the patient intake.
  4. Now, the fun part begins. Let’s say that the patient has not provided a chief complaint yet. The patient intake process asks the patient for the chief complaint. The patient records an audio clip describing their ailment on the phone that is recorded and uploaded to an AWS S3 bucket by Amazon Lambda function called from Amazon Connect contact flow.
  5. This triggers another AWS Lambda function that initiates a transcription job converting the patient’s audio clip into a transcript. This transcript contains the patient’s chief complaint.
  6. This job is monitored by AWS CloudWatch, which triggers another Lambda function once the transcription job is completed.
  7. The second Lambda function is in charge of passing the raw text of the patient’s chief complaint transcript through Amazon Comprehend Medical (ACM).
  8. Amazon Comprehend Medical typically helps extract medical entities, symptoms, dosage forms and their frequencies and presents them in an HTML format. For the first step, you’ve collected the chief complaint and maybe even the history of present illness over the phone.
  9. These entities are then being stored in a DynamoDB table that can be then used for entering data into your EMR.
  10. Next, let’s say you ask the patient about their medical history, social history, surgical history etc and followed the same steps to enter data the same way into your EMR.
  11. Next, the painful medication reconciliation part. Amazon comprehend medical does a fantastic job of tying in with the RxNorm database so you could have patients rattle off the medications they’re taking and the dosages. Amazon comprehend medical will transcribe all those into medications, dosage forms and frequencies. You can safely record these into your EMR.
  12. This is how you save a solid 10-15 Mins per patient per visit per day 😉