Skip to content

Latest commit

 

History

History
162 lines (117 loc) · 9.3 KB

README.md

File metadata and controls

162 lines (117 loc) · 9.3 KB
Raw

Voice enabled patient outcome reporting

This repo contains a sample application to show how to build a voice interface for patient outcome reporting (PRO) by leveraging NLP capabilities provided by Amazon Lex and its integration with AWS's cloud contact center offering, Amazon Connect. The hands-free nature of a voice interface make patient diary reporting more accessible to a broader set of patients who may not be able to use a mobile app due to physical constraints such as vision or motion impairments.

Architecture

The application supports three different ways for patients to reach the patient diary voice reporting interface:

  • Making an inbound call through their smart phone or landline
  • Making an inbound call through a smart speaker such as Amazon Echo
  • Receiving an outbound call on their smart phone or landline – initiated by an automated patient outreach scheduler that leverages the StartOutboundContact API of Amazon Connect

Deployment and Testing Instructions

Prerequisites

Ensure you have the following in place before deploying the application

Setup steps

  1. Clone this Github repo using git clone

  2. In the cloned code directory, install python dependencies using pipenv:

    pipenv --three shell
pipenv install --dev

  3. This deployment is configured to run with the default CLI profile. Please ensure your default profile is pointing to the account you wish to deploy to.

  4. Ensure you have CDK installed by running

    cdk --version

    If you don't have it installed, follow documentation here to install it.

    It's recommended to update CDK to the latest version. Use npm update -g aws-cdk to do so.

    Note: Make sure that all the cdk libaries in the package.json file matches your cdk version. Edit the package.json file to match.

    Install npm dependencies to make sure the cdk dependencies work:

    npm install

  5. Deploy the backend AWS Lambda functions, DynamoDB database tables, and Amazon Lex bots by running the make commands:

    make init

    Then

    make deploy

  6. Log into the Amazon Connect management console and create an Amazon Connect contact center instance

  7. Claim a phone number by following instructions here, and note down the number for later

  8. Open a new tab, go to Amazon Connect management console, under the Contact flows tab of the Amazon Connect instance, add the 4 Amazon Lex Bots and the “CheckIncomingNumber” AWS Lambda function deployed in step#3

    Screenshot of adding Lex bots and Lambda functions in Connect contact flow

  9. Create the Amazon Connect contact flow:

    1. Back in the Amazon Connect contact center instance, choose Routing → Contact Flows → Create contact flow, and use the Import flow (beta) button on the upper right corner to upload to import this flow definition

    2. Find the Invoke AWS Lambda function block and update the associated Lambda function to the CheckIncomingNumber function you added to the contact flow in step # 6

      Screenshot of updating the AWS lambda function referenced by Connect contact flow

    3. Click Save and then Publish the contact flow

      Screenshot of contact flow edtior

    4. Go to Routing → Phone Numbers and click on the phone number you claimed in step #5 and change the contact flow to point to the ePRO contact flow you just created

      screenshot of linking the contact flow to contact phone number

Running the application

  1. You can call the phone number you provisioned for Amazon Connect at this stage. However, you'll probably get a message that you've completed all the surveys. This is expected behavior.

  2. We need add some sample data to our for our DynamoDB tables. In the DynamoDB console, find the PatientProfile Table. This table is used to look up the patient's profile data. Create an entry with your information you'd like to test the application with. Especially note to fill in the Phone_Num field with number of the phone you'd like to test calling the patient diary app with. Also, make sure to take note of the Patient_ID value, this is referenced by the SurvayCompletion table where patients are associated with trials.

    example entry:

    [
  {
    "Patient_ID": "07071969",
    "First_Name": "Paul",
    "Phone_Num": "+15556667788",
    "Time_Zone": "US/Eastern",
    "Auth_Code": "123456"
  }
]

  3. Now locate the "TrialConfig" table and make an entry for a Test Clinical trial configuration. Example :

       "Participants": [
         {
           "EndDate": "2023/02/01",
           "ID": "07071969",
           "StartDate": "2022/02/01"
         }
       ],
       "Surveys": {
         "Medication": {
           "BotName": "Medication",
           "Frequency": "DAILY",
           "Priority": 0
         },
         "Symptoms": {
           "BotName": "SymptomReport",
           "Frequency": "DAILY",
           "Priority": 1
         }
       },
       "Trial_ID": "VACCINE_TRIAL_2022"
     }

  1. The reporting sample application uses a DynamoDB table SurveyCompletion to keep track of the surveys each patient needs to complete for a given day and their completion status. To hydrate this table, you need to run the SurveyCompletionScanner AWS Lambda function, which performs the following:

    • scans the TrialConfig DynamoDB table for a list of trials, the surveys required for that trial, and a list of participant IDs (assume each patient only participate in one trial at a given point)
    • for each participant, add an entry to the SurveyCompletion DynamoDB table for today's date.

    To run this function, head to the AWS Lambda console and find the Lambda function with SurveyCompletionScanner in its name. Use an empty {} as the test input data, and click the Test button to run the function

  2. You can check the SurveyCompletion DynamoDB table to see the entry added by the function you just run

  3. Now, call the phone number you provisioned for Amazon Connect and test the reporting workflow.

  4. A separate Lambda function InitiateOutboundCall is provided to show an example how to use the Amazon Connect API to automate patient outreach by scheduling to call them. In the test input event, specify the UserId (you can find it in the PatientProfile table):

{
  "UserId": "07071969",
  "Date": "2022/02/11"
}

Development

The AWS Lambda functions and DynamoDB tables in the application is defined by AWS Cloud Development Kit (CDK). The cdk.json file tells the CDK Toolkit how to deploy the app

Content Security Legal Disclaimer

The sample code; software libraries; command line tools; proofs of concept; templates; or other related technology (including any of the foregoing that are provided by our personnel) is provided to you as AWS Content under the AWS Customer Agreement, or the relevant written agreement between you and AWS (whichever applies). You should not use this AWS Content in your production accounts, or on production or other critical data. You are responsible for testing, securing, and optimizing the AWS Content, such as sample code, as appropriate for production grade use based on your specific quality control practices and standards. Deploying AWS Content may incur AWS charges for creating or using AWS chargeable resources, such as running Amazon EC2 instances or using Amazon S3 storage.

Operational Metrics Collection

This solution collects anonymous operational metrics to help AWS improve the quality and features of the solution. Data collection is subject to the AWS Privacy Policy (https://aws.amazon.com/privacy/). To opt out of this feature, simply remove the tag(s) starting with “uksb-” or “SO” from the description(s) in any CloudFormation templates or CDK TemplateOptions.