Use case 7 - Population health management
Gain full visibility into your population’s health data to improve care outcomes
Healthcare organizations are struggling to gain clear visibility across the populations they serve due to siloed, legacy systems spanning an array of standards and protocols. Without a comprehensive view of their community’s health information, these organizations encounter challenges to drive meaningful change and improve health outcomes.
This solution provides healthcare organizations with assets to power their population health initiatives by unlocking critical data for analysis and action.
Use case description
This use case is designed to accelerate key integrations for healthcare organizations seeking to use Amazon HealthLake and Salesforce Data Cloud for their population health management initiatives. The components supporting Amazon HealthLake enable the conversion of valuable clinical data across a variety of standards into FHIR R4 and ingestion into the Amazon data store. The Data Cloud related assets provide a reference implementation to surface clinical patient information (such as conditions and immunizations) from an EHR-produced flat file and web engagement data to create robust patient segments.
|HIPAA-eligible service offering healthcare and life sciences companies a complete view of individual or patient population health data for query and analytics at scale.
|Fast Healthcare Interoperability Resources is an HL7 specification for healthcare interoperability. It is a JSON-based standard describing data formats, elements and an application programming interface for exchanging electronic health records. FHIR R4 is the first normative version of the standard.
|Consolidated Clinical Document Architecture is an HL7 specification for healthcare interoperability. It is an XML-based markup standard which provides a library of CDA formatted documents.
|A predecessor to C-CDA and FHIR, HL7 v2 is an HL7 specification for healthcare interoperability. It remains the most widely used messaging standard in the healthcare industry, but has its limitations and often requires significant customization to function.
|X12 is an EDI standard established to govern the use of EDI to electronically exchange information between organizations across multiple industries today.
Ingest data into Amazon HealthLake
The Population Health Management Process API orchestrates the following:
- Consume HL7 v2 events, C-CDA documents and X12 EDIs sent from various systems via Anypoint MQ
- Transform clinical data from all sources to FHIR R4 Bundles
- Retrieve patient demographics and related clinical data on a scheduled interval via FHIR Bulk Export System API
- Store the FHIR R4 Bundles in Amazon HealthLake data store using the Amazon HealthLake System API
Ingest data into Salesforce Data Cloud using ingestion APIs
The Patient Segmentation Process API orchestrates the following for both web engagement and patient clinical data:
- A scheduled process is triggered to initiate the flow
- The source system is polled for new or updated data
- Metadata of the data object is loaded into Anypoint Object Store to avoid creating multiple jobs with open state in Data Cloud
- Data is transformed into canonical format
- A job is created in Data Cloud for bulk ingestion via Salesforce Data Cloud System API
- Data is pushed to Data Cloud via Salesforce Data Cloud System API
- Update the status of the job to
UploadCompleteupon completion of data load via Salesforce Data Cloud System API
This diagram illustrates the steps in the orchestration of data via the Population Health Management Process API, FHIR converter System APIs and Amazon HealthLake System API.
This diagram illustrates the steps in the orchestration of data via the Patient Segmentation Process API, Azure Web Engagement and Salesforce Data Cloud System APIs.
Assumptions and constraints
- Leveraged existing Accelerator converter capabilities to convert C-CDA, HL7 v2 and X12 to FHIR R4 Bundles
- Amazon HealthLake only supports the
- Amazon HealthLake System API matches Patients using Patient MRN and Practitioners using Practitioner NPI provided by the source system to avoid generation of duplicate entries
- Amazon HealthLake can ingest up to 160 individual resource types in a single Bundle operation
- Patient profiles from Salesforce Health Cloud will be ingested directly via a Data Cloud data stream
- Data Cloud Bulk Ingestion API has been leveraged to ingest both web engagement and patient clinical data
- Data Cloud Bulk Ingestion API allows creation of only one open job for each data object
- Salesforce Data Cloud bulk ingestion job accepts up to 150 MB payload (csv file) per API call and up to 100 files for each job
- Web engagement data is consolidated on content and type viewed by an individual
Before you begin
|The Getting Started with MuleSoft Accelerators guide provides general information on getting started with the accelerator components. This includes instructions on setting up your local workstation for configuring and deploying the applications.
- Population Health Management Process API | Implementation Template
- Patient Segmentation Process API | Implementation Template
- Amazon HealthLake System API | API Specification | Implementation Template
- HL7 v2 to FHIR System API | API specification | Implementation Template
- C-CDA to FHIR System API | API Specification | Implementation Template
- X12 to FHIR System API | API Specification | Implementation Template
- FHIR Bulk Export System API | API Specification | Implementation Template
- Salesforce Data Cloud System API | API Specification | Implementation Template
- Azure Web Engagement System API | API Specification | Implementation Template
Here are some links to related and supporting documentation.
- Amazon HealthLake Introduction
- Managing FHIR R4 Resources in Amazon HealthLake
- Data Cloud Bulk Ingestion