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Start Medical Scribe Job

transcribeservice_start_medical_scribe_job R Documentation

Transcribes patient-clinician conversations and generates clinical notes

Description

Transcribes patient-clinician conversations and generates clinical notes.

Amazon Web Services HealthScribe automatically provides rich conversation transcripts, identifies speaker roles, classifies dialogues, extracts medical terms, and generates preliminary clinical notes. To learn more about these features, refer to Amazon Web Services HealthScribe.

To make a start_medical_scribe_job request, you must first upload your media file into an Amazon S3 bucket; you can then specify the Amazon S3 location of the file using the Media parameter.

You must include the following parameters in your start_medical_transcription_job request:

  • DataAccessRoleArn: The ARN of an IAM role with the these minimum permissions: read permission on input file Amazon S3 bucket specified in Media, write permission on the Amazon S3 bucket specified in OutputBucketName, and full permissions on the KMS key specified in OutputEncryptionKMSKeyId (if set). The role should also allow transcribe.amazonaws.com to assume it.

  • Media (MediaFileUri): The Amazon S3 location of your media file.

  • MedicalScribeJobName: A custom name you create for your MedicalScribe job that is unique within your Amazon Web Services account.

  • OutputBucketName: The Amazon S3 bucket where you want your output files stored.

  • Settings: A MedicalScribeSettings obect that must set exactly one of ShowSpeakerLabels or ChannelIdentification to true. If ShowSpeakerLabels is true, MaxSpeakerLabels must also be set.

  • ChannelDefinitions: A MedicalScribeChannelDefinitions array should be set if and only if the ChannelIdentification value of Settings is set to true.

Usage

transcribeservice_start_medical_scribe_job(MedicalScribeJobName, Media,
  OutputBucketName, OutputEncryptionKMSKeyId, KMSEncryptionContext,
  DataAccessRoleArn, Settings, ChannelDefinitions, Tags)

Arguments

MedicalScribeJobName

[required] A unique name, chosen by you, for your Medical Scribe job.

This name is case sensitive, cannot contain spaces, and must be unique within an Amazon Web Services account. If you try to create a new job with the same name as an existing job, you get a ConflictException error.

Media

[required]

OutputBucketName

[required] The name of the Amazon S3 bucket where you want your Medical Scribe output stored. Do not include the ⁠S3://⁠ prefix of the specified bucket.

Note that the role specified in the DataAccessRoleArn request parameter must have permission to use the specified location. You can change Amazon S3 permissions using the Amazon Web Services Management Console. See also Permissions Required for IAM User Roles.

OutputEncryptionKMSKeyId

The KMS key you want to use to encrypt your Medical Scribe output.

If using a key located in the current Amazon Web Services account, you can specify your KMS key in one of four ways:

  1. Use the KMS key ID itself. For example, ⁠1234abcd-12ab-34cd-56ef-1234567890ab⁠.

  2. Use an alias for the KMS key ID. For example, alias/ExampleAlias.

  3. Use the Amazon Resource Name (ARN) for the KMS key ID. For example, ⁠arn:aws:kms:region:account-ID:key/1234abcd-12ab-34cd-56ef-1234567890ab⁠.

  4. Use the ARN for the KMS key alias. For example, arn:aws:kms:region:account-ID:alias/ExampleAlias.

If using a key located in a different Amazon Web Services account than the current Amazon Web Services account, you can specify your KMS key in one of two ways:

  1. Use the ARN for the KMS key ID. For example, ⁠arn:aws:kms:region:account-ID:key/1234abcd-12ab-34cd-56ef-1234567890ab⁠.

  2. Use the ARN for the KMS key alias. For example, arn:aws:kms:region:account-ID:alias/ExampleAlias.

If you do not specify an encryption key, your output is encrypted with the default Amazon S3 key (SSE-S3).

Note that the role specified in the DataAccessRoleArn request parameter must have permission to use the specified KMS key.

KMSEncryptionContext

A map of plain text, non-secret key:value pairs, known as encryption context pairs, that provide an added layer of security for your data. For more information, see KMS encryption context and Asymmetric keys in KMS.

DataAccessRoleArn

[required] The Amazon Resource Name (ARN) of an IAM role that has permissions to access the Amazon S3 bucket that contains your input files, write to the output bucket, and use your KMS key if supplied. If the role that you specify doesn’t have the appropriate permissions your request fails.

IAM role ARNs have the format arn:partition:iam::account:role/role-name-with-path. For example: ⁠arn:aws:iam::111122223333:role/Admin⁠.

For more information, see IAM ARNs.

Settings

[required] Makes it possible to control how your Medical Scribe job is processed using a MedicalScribeSettings object. Specify ChannelIdentification if ChannelDefinitions are set. Enabled ShowSpeakerLabels if ChannelIdentification and ChannelDefinitions are not set. One and only one of ChannelIdentification and ShowSpeakerLabels must be set. If ShowSpeakerLabels is set, MaxSpeakerLabels must also be set. Use Settings to specify a vocabulary or vocabulary filter or both using VocabularyName, VocabularyFilterName. VocabularyFilterMethod must be specified if VocabularyFilterName is set.

ChannelDefinitions

Makes it possible to specify which speaker is on which channel. For example, if the clinician is the first participant to speak, you would set ChannelId of the first ChannelDefinition in the list to 0 (to indicate the first channel) and ParticipantRole to CLINICIAN (to indicate that it's the clinician speaking). Then you would set the ChannelId of the second ChannelDefinition in the list to 1 (to indicate the second channel) and ParticipantRole to PATIENT (to indicate that it's the patient speaking).

Tags

Adds one or more custom tags, each in the form of a key:value pair, to the Medica Scribe job.

To learn more about using tags with Amazon Transcribe, refer to Tagging resources.

Value

A list with the following syntax: 

list(
  MedicalScribeJob = list(
    MedicalScribeJobName = "string",
    MedicalScribeJobStatus = "QUEUED"|"IN_PROGRESS"|"FAILED"|"COMPLETED",
    LanguageCode = "en-US",
    Media = list(
      MediaFileUri = "string",
      RedactedMediaFileUri = "string"
    ),
    MedicalScribeOutput = list(
      TranscriptFileUri = "string",
      ClinicalDocumentUri = "string"
    ),
    StartTime = as.POSIXct(
      "2015-01-01"
    ),
    CreationTime = as.POSIXct(
      "2015-01-01"
    ),
    CompletionTime = as.POSIXct(
      "2015-01-01"
    ),
    FailureReason = "string",
    Settings = list(
      ShowSpeakerLabels = TRUE|FALSE,
      MaxSpeakerLabels = 123,
      ChannelIdentification = TRUE|FALSE,
      VocabularyName = "string",
      VocabularyFilterName = "string",
      VocabularyFilterMethod = "remove"|"mask"|"tag"
    ),
    DataAccessRoleArn = "string",
    ChannelDefinitions = list(
      list(
        ChannelId = 123,
        ParticipantRole = "PATIENT"|"CLINICIAN"
      )
    ),
    Tags = list(
      list(
        Key = "string",
        Value = "string"
      )
    )
  )
)

Request syntax

svc$start_medical_scribe_job(
  MedicalScribeJobName = "string",
  Media = list(
    MediaFileUri = "string",
    RedactedMediaFileUri = "string"
  ),
  OutputBucketName = "string",
  OutputEncryptionKMSKeyId = "string",
  KMSEncryptionContext = list(
    "string"
  ),
  DataAccessRoleArn = "string",
  Settings = list(
    ShowSpeakerLabels = TRUE|FALSE,
    MaxSpeakerLabels = 123,
    ChannelIdentification = TRUE|FALSE,
    VocabularyName = "string",
    VocabularyFilterName = "string",
    VocabularyFilterMethod = "remove"|"mask"|"tag"
  ),
  ChannelDefinitions = list(
    list(
      ChannelId = 123,
      ParticipantRole = "PATIENT"|"CLINICIAN"
    )
  ),
  Tags = list(
    list(
      Key = "string",
      Value = "string"
    )
  )
)