Data 360 for unifying patient data across external systems

Key Takeaway

A Data 360 identity resolution ruleset merges separate records about the same person into one unified profile for segmentation and activations, but the data must be mapped first.

Patient data is often split across different, incompatible EHRs, so one person can exist as separate records in several systems. Data 360 takes raw data from many systems, maps it to a common data model, and uses identity resolution to merge records about the same person into one unified profile. A consultant needs to know how this unification works and how it fits alongside the other ways Agentforce Health connects to external data.

Analyze the data first

Understanding your data is key to a successful Data 360 implementation, so analyze the data before you build anything. Questions to answer include:

Where is the data located?
How are individuals identified in each source?
What data is shared across systems?
What does the customer journey look like?
How good is the data quality in each source?

Salesforce Accredited Agentforce Health Professional Study Guide

Checklist progressProgress

0/167Learned

Checklist progressProgress

0/167Learned

Given customer requirements, determine how to create the solution for Agentforce Health features according to best practices

0/2

Given customer requirements, understand how to model patients, providers, healthcare facilities, etc., using the appropriate Agentforce Health objects

0/14

Given customer requirements, determine how to create the proper application solution design leveraging Agentforce Health best practices

0/5

Given customer requirements, determine when to use specific Agentforce Health capabilities

0/8

Given customer requirements, determine how to create the design solution for a specific Agentforce Health vertical to meet those requirements

0/6

Given the business processes/requirements, determine how to create the solution design utilizing best practices and Agentforce Health modules

0/5

Given a customer's business objectives and goals, define success-metrics/KPIs and configure Salesforce to enable reporting on these metrics

0/5

Given a customer's security/compliance requirements, design and implement the appropriate organizational security and data access considerations

0/8

Given a customer's external systems and data requirements, determine the optimal integration strategy for the customer's Salesforce org

0/7

Integration pattern selection for health data exchange

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Middleware versus point-to-point integration in a multi-system health landscape

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EHR clinical data integration into the FHIR-aligned clinical data model

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Omnistudio Integration Procedures for server-side calls to external systems

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Salesforce Connect data virtualization versus copying external health data into the org

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Data 360 for unifying patient data across external systems

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Securing integrations that exchange protected health information

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Given a customer's business requirements, design the future state business processes

0/4

Given the data requirements, create a migration strategy considering the legacy /future state system landscape ensuring accuracy and integrity

0/9

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Data 360 for unifying patient data across external systems

Key Takeaway

A Data 360 identity resolution ruleset merges separate records about the same person into one unified profile for segmentation and activations, but the data must be mapped first.

Analyze the data first

Understanding your data is key to a successful Data 360 implementation, so analyze the data before you build anything. Questions to answer include:

Where is the data located?
How are individuals identified in each source?
What data is shared across systems?
What does the customer journey look like?
How good is the data quality in each source?