AWS for Industries

Unlock the potential of patient 360 with Salesforce and AWS

In the era of digital health transformation, patient 360 has emerged as a cornerstone approach for modernizing healthcare services. Consolidating comprehensive patient information into a single, accessible format, across various healthcare providers and settings, enables healthcare professionals to make more informed decisions. It also streamlines care coordination and delivers more personalized patient journeys. NHS England notes, “High-quality patient records are the foundation of good clinical care delivery.”

Amazon Web Services (AWS) cloud-native services and AWS Partner solutions, like Salesforce, offer a scalable, compliant solution to implement patient 360 capabilities. They provide a resilient infrastructure for unifying data, managing patient relationships, and leveraging advanced artificial intelligence and machine learning (AI/ML) models for healthcare insights.

We will explore how Salesforce and AWS are transforming patient care by enabling true longitudinal patient records and supporting more efficient, patient-centric healthcare delivery.

Tailoring the approach and services for key stakeholders

The joint approach by Salesforce and AWS to patient 360 recognizes the diverse needs of healthcare stakeholders and offers tailored touch points for different personas. Salesforce and AWS offer capabilities for diverse healthcare stakeholders, including patient-centric interfaces, data unification and analytics tools, advanced AI/ML services, and a secure, scalable infrastructure with streamlined integration.

Patients and providers
Patients and providers need quick, secure access to comprehensive health information. They seek user-friendly, mobile-accessible interfaces with multiple engagement channels. Intuitive patient portals and provider dashboards should consolidate data from various sources, offering a holistic view of the patient journey and facilitating seamless communication and care management.

This screenshot shows Salesforce Health Cloud's patient 360 interface, demonstrating a comprehensive longitudinal patient record view. The interface is divided into three main sections: The Left Panel: Shows a "Patient Card" for a patient, including basic demographics and collapsible sections for medications and health conditions. The Center Panel: Displays detailed patient information across multiple tabs (Details, Determinants, Health, Wellness Programs). The Details tab shows account information and adherence scores, including key metrics like total appointments, missed appointments, and an admission risk score. The Right Panel: Features a timeline/activity view showing upcoming and past health events, including a scheduled health check and completed blood tests.

Figure 1 – Example of a unified patient view in Salesforce Health Cloud showing clinical and engagement data

  • Salesforce Health Cloud provides no-code/low-code applications for patients and providers to access comprehensive health records, schedule appointments, and communicate securely.
  • Salesforce Marketing Cloud enables personalized patient engagement and outreach.

These services combine to create a seamless, patient-centric experience that aligns with the objectives of easy access to information and improved care coordination, without the need for infrastructure investments.

Business users
Business users at healthcare organizations focus on optimizing operations, improving patient outcomes, and ensuring regulatory compliance. Their objectives include streamlining workflows, reducing administrative burden, and enhancing patient satisfaction.

  • Salesforce Data Cloud provides the ability to unify data from all your sources and activate it across apps and experiences.
  • Tableau offers a unified analytics platform and trusted AI for performance tracking and data-driven decision-making.

The data unification and harmonization performed by Salesforce Data Cloud allows data from AWS and non-AWS data sources to be accessed when building the patient 360 data model. With the Zero Copy integration, Data Cloud allows data to be seamlessly accessed from, and shared with Amazon Redshift without physically moving it. Amazon Redshift is a managed, cloud-native data warehouse solution.

Data scientists
Data scientists in healthcare analyze diverse patient data to improve care quality, efficiency, and population health management. They need advanced analytics tools, machine learning capabilities, and secure storage solutions. Their goals include identifying trends, predicting outcomes, and supporting evidence-based decisions. Critically, they aim to integrate these insights seamlessly into healthcare workflows.

  • Purpose-built storage, analytics and AI/ML services of AWS provide data scientists with advanced tools for data storage, analysis, predictive modeling and development of AI-powered applications.

According to the US Bipartisan House Task Force Report on Artificial Intelligence, “Artificial intelligence (AI) technologies have the potential to improve multiple aspects of healthcare research, diagnosis, and care delivery.”

Using AWS managed services, data engineers, analysts and AI/ML practitioners can use the services that they are most familiar with to drive actionable insights from the data at scale. Salesforce Data Cloud bring your own model (BYOM) with Amazon SageMaker AI and bring your own large language model (BYOLLM) with Amazon Bedrock allow insights from domain-specific predictive and large language models to be surfaced back into line of business applications.

Technology departments
Healthcare IT professionals implement, maintain, and secure the technology supporting patient care and operations. They focus on system reliability, scalability, and security while managing costs and regulatory compliance. Their goals include streamlining IT operations, reducing complexity, and enabling innovation without compromising performance or security.

  • AWS infrastructure provides IT professionals with a scalable, secure, and compliant foundation for healthcare applications.
  • MuleSoft simplifies system integration and API management, which reduces complexity. Built-in AWS connectors, and out-of-the-box integration capabilities, between Salesforce and AWS allow all layers to be tightly integrated without writing complex data engineering pipelines or integration code.

Solution overview

Following is a high-level diagram of the Salesforce and AWS reference architecture for patient 360.

This joint reference architecture diagram shows the integration between AWS and Salesforce for the patient 360 use case. The diagram is organized in layers: Patient 360, Data Model and Reporting, Integration, and Data Sources. It illustrates how data flows from various healthcare systems through AWS services (including AWS HealthLake, Amazon Redshift, and Amazon SageMaker AI) into Salesforce's products (Marketing Cloud, Health Cloud, and Data Cloud). The system includes MuleSoft Accelerator for Healthcare as a key integration component, Tableau for operational reporting, and supports both data scientists and healthcare providers as end users. The architecture demonstrates how patient data is unified, analyzed, and made accessible through no-code/low-code applications while maintaining data governance through AWS Lake Formation and Amazon DataZone.Figure 2 – Salesforce and AWS reference architecture for patient 360

AWS services used
The following AWS services collectively form the health data foundation for storage, analytics, and machine learning in this patient 360 approach:

  • AWS HealthLake: A HIPAA-eligible service for storing and analyzing health data in FHIR format. It can be used to create a centralized repository for trusted patient data, supporting the patient 360 view.
  • Amazon Comprehend Medical: A natural language processing service that can extract medical information from unstructured text. It can be used to analyze clinical notes and generate structured data for the patient 360 view.
  • Amazon Redshift: A fully managed data warehouse that can store and analyze large volumes of healthcare data. It can serve as a central repository for aggregated patient data and support complex analytics for population health management.
  • Amazon Simple Storage Service (Amazon S3): A scalable object storage service that can securely store large amounts of healthcare data. It can act as a data lake for raw patient data from various sources, including the staging of structured, semi-structured and unstructured data such as telemetry from healthcare devices, medical images, and scans of forms.
  • Amazon Athena: A serverless query service that allows analysis of data stored in Amazon S3. It can be used to run ad-hoc queries on patient data for research or reporting purposes.
  • AWS Glue: A fully managed extract, transform, and load (ETL) service. It can be used to prepare and transform healthcare data from a wide range of sources for analysis and integration into the patient 360 view, after ingestion, transformation, aggregation and validation.
  • Amazon SageMaker AI: A fully managed machine learning service. It can be used to develop and deploy predictive models for patient outcomes or risk quantification based on the comprehensive data that resides in the data lake. SageMaker AI facilitates responsible development and operationalization of AI/ML workloads that addresses potential risks like bias, privacy, and accuracy.
  • Amazon Bedrock: A fully managed service that provides a way to build and scale generative AI applications with foundation models from leading AI companies. It can be used to power advanced generative-AI applications for healthcare.

Following is a list of AWS services that collectively enhance the health data foundation by facilitating seamless data migration, improving data discovery and governance. They streamline the creation and management of secure data lakes:

  • AWS Lake Formation: A service that makes it quick to set up, secure, and manage data lakes. It can automate the process of collecting and organizing healthcare data from multiple sources into a centralized data lake while implementing fine-grained access controls to protect sensitive patient information.
  • Amazon DataZone: A data management service that helps discover, catalog, share, and govern data across the organization. It can create a unified catalog of healthcare data assets and implement comprehensive access controls to facilitate compliance with healthcare data regulations.
  • AWS Database Migration Service (AWS DMS): A service that enables quick and secure migration of healthcare data to AWS. It can be used to migrate existing healthcare databases to the cloud and continuously replicate data from on-premises systems.

An architecture similar to this can be deployed automatically using the AWS Health Data Accelerator project, which provides infrastructure-as-code templates and deployment automation for a number of these services. This open-source solution can significantly reduce the time and complexity of implementing a healthcare data platform.

Potential use cases

Chronic disease management
A large healthcare system can implement a patient 360 solution to improve care for patients with chronic conditions like diabetes. Using AWS Lake Formation, the organization can securely consolidate diverse patient data sources into a unified data lake. Amazon DataZone can facilitate data discovery and governance across these sources. Using Salesforce Health Cloud, providers can access comprehensive patient histories, including medication adherence, appointments data, lifestyle factors, and previous treatments.

SageMaker AI can be used to develop domain-specific ML models, for example to predict probability of patient hospital admissions, using patient 360 data and datasets from other sources. The system can use unified data, and segmentation of patient population using developed ML models, to trigger personalized interventions through Salesforce Marketing Cloud, such as medication reminders or lifestyle advice.

Care teams can use Tableau dashboards to monitor patient populations and identify those at risk of complications. This integrated approach can improve patient care coordination, reduce hospital readmissions and improve patient outcomes.

Hospital operations optimization
A multi-facility hospital network can leverage the approach to streamline operations and enhance patient experiences. MuleSoft can integrate data from various hospital systems, for example, electronic healthcare records (EHR) systems, billing, and scheduling, into a unified view in Salesforce Health Cloud. Data stored in AWS data, analytics and storage services, such as Redshift and Amazon S3, can be unified with Customer Relationship Management (CRM) data. Salesforce Data Cloud can be used to provide a holistic picture of the estate. Business users can utilize Salesforce’s process automation tools to optimize patient flow, from admission to discharge.

ML models, developed using SageMaker AI, can be used by data scientists to analyze historical data to predict patient volumes and optimize staffing levels. Patients can benefit from shorter wait times and smoother experiences, while the hospital sees improved resource utilization and cost savings.

Population health management
A regional or national health authority can implement patient 360 using AWS and Salesforce solutions to improve population health, for example by screening for cancer or abdominal aortic aneurysm (AAA). AWS services such as AWS Glue, Athena, Redshift, and Amazon S3 can aggregate and analyze data from clinical records, social determinants of health, and public health databases. Salesforce Data Cloud can provide a unified view that allows healthcare organizations to create highly targeted segments that incorporate AI derived healthcare insights from SageMaker AI without writing code. Salesforce Health Cloud can support targeted interventions enrolling cohorts into tailored programs designed to support the individual through the screening journey. Salesforce Marketing Cloud can deliver public health campaigns through any channel including mobile apps. This approach allows proactive addressing of community health needs, improving outcomes and resource efficiency.

Benefits

By implementing this approach, organizations can realize the following benefits:

  • Deliver comprehensive patient view: Seamlessly unify data from cloud and non-cloud sources using open and interoperable standards, such as HL7 FHIR R4, and built-in connectors and integration points.
  • Personalize patient engagement using AI/ML: Combine Salesforce’s marketing and service automation and domain-specific AI/ML models trained on the organization’s data using AWS to drive targeted, timely patient interactions and improvement to patient outcomes.
  • Drive advanced analytics and insights: Integrate Salesforce’s reporting capabilities with the advanced analytics tooling and purpose-built data storage capabilities of AWS to drive actionable healthcare insights at scale.
  • Innovate quickly using scalable and secure infrastructure: Build on the robust, compliant cloud infrastructure of AWS integrated with Salesforce’s platform. Provides flexibility to buy and build new capabilities using a highly integrated joint solution.
  • Reduce total cost of ownership: Leverage cloud-native, pay-as-you-go services that eliminate upfront infrastructure investments, minimize ongoing maintenance expenses, and provide elasticity to optimize resource utilization and operational costs.

Conclusion

The patient 360 approach represents a transformative strategy for healthcare data management, leveraging the combined capabilities of Salesforce and AWS. By bringing together cloud-native services, advanced analytics, and secure infrastructure, healthcare organizations can streamline operations, enhance patient care, and facilitate data-driven decision-making.

Learn more from Salesforce or contact an AWS Representative to know how we can help accelerate your business.

Further reading

Richard Boyd

Richard Boyd

Richard is a CTO for Public Sector Health (EMEA) at Salesforce with over 25 years of experience in software development and architecture, holding multiple Salesforce certifications and specializing in digital transformation for healthcare organizations.

Alan Peaty

Alan Peaty

Alan is a Senior Partner Solutions Architect helping Global Systems Integrators (GSIs), Global Independent Software Vendors (GISVs) and joint customers adopt AWS services and partner solutions. Outside of work, Alan is a keen hiker and runner who loves to hit the trails of the English and European countryside.

Bryan Marsh

Bryan Marsh

Bryan is a Principal Solutions Architect for Public Sector Healthcare and Life Sciences at Amazon Web Services. He has expertise in enterprise architecture with a focus on data strategy and AI. He is passionate about using technology to improve the healthcare experience and patient outcomes.

Steve Johnston

Steve Johnston

Steven is a Principal Solutions Architect in World Wide Public Sector, Solutions Architecture at AWS working with UK Healthcare customers. Steven has been at AWS for over 5 years providing technical and strategic leadership to healthcare customers building their solutions on AWS.