Get started with Azure Health Data Services Microsoft Quiz Answers

Get Get started with Azure Health Data Services Microsoft Quiz Answers

Azure Health Data Services is a managed platform as a service (PaaS) based on OpenAPI standards and frameworks that enable more secure and scalable health data solutions. Azure Health Data Services empowers Microsoft Cloud for Healthcare and other health workloads by enabling more secure and compliant paths to ingest, persist, and connect health data in the cloud.

In this Learning Path, you’ll gain a foundational understanding of Azure Health Data Services and its core components. You’ll be guided through use cases as you explore interoperability challenges of health and life sciences data, examine the tools and connectors of Azure Health Data Services and their benefits, review the data architecture of FHIR and the details of how the FHIR API is implemented, explore the DICOM standards and DICOM service using the use case for radiology data in cancer treatment and how to enable IoT data scenarios for remote patient monitoring.

Prerequisites:

  • None

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Module 1: Introduction to Azure Health Data Services

Azure Health Data Services is a managed platform as a service (PaaS) based on OpenAPI standards and frameworks that enable more secure and scalable health data solutions. Azure Health Data Services empowers Microsoft Cloud for Healthcare and other health workloads by enabling more secure and compliant paths to ingest, persist, and connect health data in the cloud. Azure Health Data Services is a set of tools and connectors that enable organizations to bring health data to the Microsoft Cloud and improve health through insights.

Learning objectives:

In this module, you’ll:

  • Explore interoperability challenges of health and life sciences data.
  • Describe the core global health data standards that Azure Health Data Services supports today.
  • Examine the tools and connectors that comprise Azure Health Data Services and the benefits that they provide.

Prerequisites:

None

This module is part of these learning paths:

Quiz 1: Check your knowledge

Q1. Information that is personal and includes data, such as vitals or care plans, is considered to be what?

  • Preferred health information
  • Protected health information
  • Platform health integration
  • Patient health integration

Q2. Which of the following options is not part of the initial configuration of an Azure Health Data Services workspace?

  • Azure Subscription
  • Azure Resources group
  • Currency
  • Workspace name

Q3. In Azure Health Data Services, FHIR, DICOM, and MedTech are deployed into what?

  • Workspace
  • Package
  • Observation
  • Database

Module 2: Health data and FHIR®

This module covers the data architecture of Fast Healthcare Interoperability Resources (FHIR) and the details of how the FHIR API is implemented in the FHIR service in Azure Health Data Services.

Learning objectives:

In this module, you’ll:

  • Identify types of FHIR resources.
  • Identify resource elements, structures, and hierarchy.
  • Learn about the FHIR RESTful API framework.

Prerequisites:

None

This module is part of these learning paths:

Quiz 1: Check your knowledge

Q1. What is an implementation guide?

  • A user training manual
  • A resource that contains a set of logical statements that implementations must conform to
  • An API specification for exchanging health data between systems

Q2. What type of API does FHIR Service use for exchange of HL7 FHIR data?

  • ws-trust
  • SOAP
  • RESTful HTTP
  • RPC

Q3. Which of the following options is a mandatory data element that must be present in a patient profile?

  • Patient name
  • Contact details
  • Address
  • None of these options are mandatory, but all are recommended

Module 3: Work with medical imaging data and DICOM

DICOM® (Digital Imaging and Communications in Medicine) is the international standard for medical images, imaging formats, and related information. It’s the ISO 12052 standard that defines the data quality and exchange specifications for images to meet clinical use requirements. Digitization of medical imaging data by using the DICOM standard will enable health data interoperability. Microsoft cloud is equipped to ingest, persist, and connect DICOM imaging data to help improve patient outcomes.

Learning objectives:

In this module, you’ll:

  • Learn why DICOM standards are important.
  • Explore the DICOM standards and DICOM service.
  • Review the use case for radiology data in cancer treatment with examples.

Prerequisites:

None

This module is part of these learning paths:

Quiz 1: Check your knowledge

Q1. What is DICOM?

  • Digital Imaging and Communications in Medicine
  • All of these answers
  • The international standard for medical images, imaging formats, and related information
  • ISO 12052 recognized standard

Q2. When DICOMcast is set up, as an image enters the DICOM service, DICOMcast detects changes in the image and matches it to a patient record. What is the expected outcome if no patient match is found?

  • An error is thrown, and a developer must intercept it to resolve
  • An administrator can set up the resolution to this issue on setup of the service
  • You can create a new patient record
  • You’ll need to manually create the patient record and manually set up the connection between image and patient

Q3. Which of the following isn’t part of the DICOM data model?

  • Electronic health records
  • Patient
  • Study
  • Images

Module 4: MedTech service with IoT devices

In this module, you’ll learn how to enable IoT data scenarios for remote patient monitoring.

Learning objectives:

In this module, you’ll:

  • Enable IoT data scenarios for remote patient monitoring.
  • Ingest data from devices.

Prerequisites:

None

This module is part of these learning paths:

Quiz 1: Check your knowledge

Q1. The data from weekly weigh-ins, which is automatically reported by scales with IoT connectivity, would be considered what type of health data?

  • High velocity data
  • Low velocity data
  • Neither of these options

Q2. Which one of the following options is a benefit of IoT devices?

  • Improved doctor/patient engagement
  • Patient accountability
  • Increased patient compliance with treatment plans
  • All of these options

Q3. How does IoT device data become useable data?

  • Device data is normalized and transformed into a FHIR Observation resource that is useable by your custom, or industry, healthcare apps.
  • Making device data useable is dependent on the intended outcome/use case.
  • Normalizing and transforming data is only possible with high-code proprietary offerings.
Conclusion:

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