Data Aggregation in Healthcare: Expert Guide From Segment

Discover how Segment's HIPAA-compliant platform can help enhance patient care, improve data management, and support real-time decision-making.

When it comes to analytics, data aggregation plays a key role. It’s a process that merges and summarizes large volumes of data, which is then stored in a central repository such as a data warehouse.

From finance to e-commerce, businesses across industries use aggregated data to support product development, launch better marketing campaigns, and get real-time insights into operations. In the healthcare industry, the use cases encompass patient care, clinical research, and much more.

The role of data aggregation in healthcare

In healthcare, data aggregation is a process that unifies health data from different systems. It might include patient data from electronic health records (EHR) systems, wearables, healthcare apps, and claims data.

Healthcare organizations rely on data aggregation tools to run this process. This type of software connects to various data sources and then retrieves and processes the datasets.

Aggregated data helps healthcare organizations:

  • Accelerate clinical research. Retrieving and combining data from siloed systems on a case-by-case basis could take days or even weeks. With access to aggregated data, researchers can immediately find the information they need and move forward with analysis.

  • Improve the quality of care. Doctors can make better treatment plans with a holistic overview of their patient’s health. Aggregating data from smart devices, medical records, and other health-related sources also provides granular insights into how the patient is responding to their treatment. This allows clinicians to spot and handle any side effects proactively.

  • Optimize resources. Aggregating historical data enables predictive analytics, which can forecast when there will be an increase in patient demand. This allows healthcare organizations to prepare for periods of high demand, preventing long waiting times. 

  • Personalize marketing outreach. When healthcare companies reach out to doctors and other medical staff, they’ll have a higher chance of success if they tailor their outreach to the person’s interests. Personalization is only possible at scale by aggregating customer data.

  • Improve population health management. Real-time data analytics help clinicians understand different groups' health, allowing for better population health management through prevention or targeted interventions.

Why data aggregation in healthcare is challenging

Healthcare organizations are prone to data silos – or storing data in disconnected systems and often in different formats (e.g., physician notes, diagnostic imaging, etc.). Silos lead to inconsistencies, duplication, and overall poor quality of data that needs to be addressed for successful data aggregation.

At the same time, healthcare providers can’t lose sight of data privacy. Sensitive patient data must be protected under regulations such as the Health Insurance Portability and Accountability Act (HIPAA).

For example, you need to sign a business associate agreement (BAA) with any software vendor that you use for aggregating protected health information (PHI). And you need to de-identify health information according to HIPAA regulations.

As a result, healthcare organizations can’t use just any data aggregation tool. They need one with guardrails in place that support HIPAA compliance.

Security is another significant challenge of data aggregation in healthcare. The industry is a top target among cybercriminals attempting to steal patient data. To complicate things further, criminals are now trying to exploit vulnerabilities in business associates as opposed to going after healthcare organizations directly. 

John Delano, healthcare cybersecurity strategist at Critical Insights, explains, “Hackers are increasingly targeting the weakest links and vulnerable points in the supply chain, specifically business associates or third-party companies that offer services to healthcare organizations, emphasizing the importance of effective incident response planning and proactive defense strategies.” 

Insufficient security measures aren’t just a financial risk but a reputational one, too. A data breach would undoubtedly lead some patients to consider switching care providers and deter new ones from choosing you for their healthcare needs.

How unified data helped Sanofi improve patient outcomes

Sanofi is a global pharmaceuticals company focused on providing life-changing medications, treatments and vaccines. They often work with healthcare providers to provide context on the different treatment options available, to ensure each patient has the best possible care. 

However, they were struggling with fragmented data that was hindering their ability to fully understand patients and their cross-channel journeys. Creating user profiles used to mean using a combination of ETL and batch processing  – and it used to take 24 hours at least to unify and activate this data.

By implementing Segment, Sanofi was able to leverage its event-driven architecture and identity resolution capabilities to create together complete customer profiles that updated in real time. Sanofi could also enrich those profiles in their warehouse (e.g., aggregating online and offline customer data) and then use reverse ETL to send this profiles to any downstream tool for activation.

Rick Troiani, Director of Sanofi’s Omni-Channel Engagement Architecture, said of the switch, “Previously, we would work with our data by moving it, then using it. Now, with Segment, we can use data while we move it.” 

Twilio Segment for enhanced healthcare data aggregation

Twilio Segment’s customer data platform (CDP) helps healthcare providers aggregate data in a compliant and secure way.

Improving patient care with accurate data

Aggregating data can help healthcare providers dig deeper into patient histories, risk factors, and symptoms for better diagnostics and proactive treatment plans. But, that’s only if the data they’re working with is accurate and up to date. 


Especially in healthcare, providers and business associates need to have airtight data governance in place to ensure they’re not counting duplicate records or working with incomplete (or inaccurate) information. With Segment Protocols, organizations can create an internal tracking plan and automatically block any data that doesn’t match. They can also transform data as it flows through the pipeline to ensure that it’s formatted correctly for its target destination. 

Enhanced data privacy and compliance

Segment’s CDP simplifies compliance with privacy regulations such as the GDPR and CCPA by enabling user suppression and “the right to be forgotten” requests at scale. It also offers security features like automatically classifying (and masking) data according to its risk level, and ensuring strict user permissions as to who internally can access what data. 

With Segment, you can automatically classify PII based on its level of risk (i.e, a credit card number would present a higher level of risk than someone’s job title).

Segment is also HIPAA-eligible, which allows us to sign BAAs to manage PHI without violating patients’ privacy.

Unlocking offline patient interaction data

Offline patient data can include a physician’s notes during an in-person visit or the forms you fill out at check-in  (asking about a person’s lifestyle, current symptoms or medications they’re taking, etc.). 

While healthcare has gone digital in many ways, in-person interactions and screenings are still a huge component. Merging this data with digital records is imperative for a complete view of a person’s experience and patient profile. 

Segment offers pre-built connectors to various different data warehouses and lakes, for a seamless integration. (Organizations can also build their own custom integrations.) With Profiles Sync, organizations can connect their customer profiles to their warehouse for enrichment, and then use reverse ETL to activate these profiles in downstream tools.

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