Sharp HealthCare uncovers clinical insights with real-time healthcare data

“With Fivetran’s powerful tools like the EHR connector, we’ve automated the flow of critical clinical data from EHRs into Snowflake, significantly reducing engineering effort and accelerating access to clinical insights. This has empowered our teams to make faster, more informed decisions, ultimately supporting better care for our patients.”
— Clay Townsend, Principal Enterprise Data Solutions Architect at Sharp HealthCare

Sharp HealthCare is one of Southern California’s largest and most respected healthcare systems. With over 18,000 employees, 2,600 affiliated physicians, and 7 hospitals and medical groups, Sharp provides high-quality care to more than 1 million patients each year across the San Diego region.

Behind the scenes, Sharp was facing mounting challenges across its data ecosystem. Data was dispersed across on-premise systems, SharePoint folders, SaaS tools, and third-party vendor portals — each requiring its own lengthy process to extract and use. Critical sources like EHR data, ServiceNow, Microsoft System Center Configuration Manager (SCCM), and HR systems like Workday all lived in silos, often requiring time-intensive workarounds that strained engineering capacity.

In some cases, teams had to wrangle with unstructured formats — like nested JSON logs when extracting data from Workday — just to get what they needed. At the same time, Sharp’s engineering team was tied up maintaining custom-built pipelines that were fragile, time-consuming to fix, and prone to breaking. In a healthcare setting, where timely, accurate data can directly impact patient outcomes, this approach wasn’t sustainable.

Sharp needed a better way — a data movement solution that could replace fragmented pipelines with automated workflows, reduce manual data wrangling, and make reliable, up-to-date data easily available across the organization. Most importantly, Sharp wanted to enable faster insights to improve operational efficiency and support better patient care.

That’s when they turned to Fivetran.

Simplifying complexity across teams at Sharp

Fivetran has had a measurable impact across multiple teams at Sharp by streamlining how data moves across the organization — all while maintaining the high level of security required to protect sensitive healthcare data.  With automated connectors and change data capture (CDC), Fivetran ingests data directly from on-premise databases, SaaS applications, and cloud services into Sharp’s centralized Snowflake warehouse — eliminating the need for manual extraction and custom-built scripts. This shift has directly empowered teams across engineering, security, and workforce technology in meaningful, measurable ways.

The engineering team has moved from reactive pipeline maintenance to proactive platform development. With Fivetran’s automated data movement, Sharp has reduced pipeline maintenance from 90% of engineering time to just 10%. Instead of spending hours monitoring jobs and troubleshooting broken connections, they now focus on building scalable infrastructure and enabling self-service analytics across departments.

“We’ve gone from constantly triaging broken pipelines and manually pushing data, to a system that’s hands-off and just works. Now we can focus on delivering insights, not fixing the plumbing.”
— Clay Townsend, Principal Enterprise Data Solutions Architect at Sharp HealthCare

Security teams now have reliable, near real-time access to critical data like device telemetry, login activity, and threat detection logs — enabling faster incident response and improved visibility. Before Fivetran, these data sources were either inaccessible or required time-consuming extraction. Now, that data flows automatically into Snowflake and is query-ready.

Workforce technology teams use real-time usage data to identify underutilized hardware, spot software licensing gaps, and resolve issues before they become service disruptions without submitting ad hoc data requests or relying on outdated reports. Meanwhile, analysts across Sharp are empowered with consistent, trustworthy data and spend far less time tracking down issues with broken pipelines.

“The ability to offer a franchised model of analytic platform empowerment across diverse teams has allowed for governance and sanity in a highly matrixed environment. Fivetran has unlocked data at velocity and scale to create an ecosystem of productive use without compromising on providence or expense.”
— Jon McManus, Vice President Chief Data, AI, and Development Officer Sharp HealthCare

By automating data recovery and pipeline optimization with Fivetran, Sharp avoided the need to build and maintain new data pipelines in-house — a move that would have cost nearly 4x more than their Fivetran investment. In just the first 90 days, Sharp saved $287,760, with annual savings totaling over $1.15 million. These cost reductions enabled Sharp to transition from legacy on-premise tools to the cloud without expanding its overall data budget. With less time spent on pipeline maintenance, Sharp’s engineering team has been able to shift its resources toward higher-value work: supporting clinical and business initiatives, AI and advanced analytics, and ultimately driving better patient outcomes.

Unlocking clinical insights

Sharp’s electronic health record (EHR) system is a critical source of clinical and operational data. However, accessing and analyzing this data had long been a complex and time-consuming task. With Fivetran’s EHR connector Sharp now replicates both Clarity and Caboodle data directly into Snowflake — automatically, securely, and in real time. This has dramatically improved how quickly and reliably data gets into the hands of analysts and decision makers.

The connector enables Sharp to support downstream analytics use cases like performance improvement, operational reporting, and clinical insights — all without overburdening the engineering team. Instead of maintaining custom pipelines, engineers can rely on Fivetran’s fully managed integration to ensure data is accurate, secure, and always available.

The impact has been significant:

• Faster data access enables more responsive reporting across clinical and operations teams.
• Reduced engineering overhead has freed up time for higher-value initiatives, including building out new use cases in the data platform.
• Improved data quality and trust ensures stakeholders can make decisions based on consistent, reliable information.

By automating the movement of EHR data with Fivetran, Sharp has transformed how it delivers insights from its EHR — turning a once-complex integration into a streamlined foundation for deeper insights into clinical operations — driving more responsive, patient-centered care.

“Extracting healthcare data used to take a lot of time and manual effort — and even then, it wasn’t always reliable or easy to scale. With Fivetran’s EHR connector, that entire process is now automated. We’re delivering data to Snowflake faster, with far less overhead, and it’s enabled us to support analytics use cases that just weren’t feasible before.”
— Clay Townsend, Principal Enterprise Data Solutions Architect at Sharp HealthCare

With Fivetran automating and standardizing data movement, Sharp has laid the groundwork for a modern, secure, and scalable analytics environment. Their team can now spin up new data sources with minimal overhead, freeing up engineering time to focus on higher-impact projects; for example, Sharp is advancing its internal AI capabilities with Sharp AI, a custom GPT-4o implementation hosted in Azure. The team is developing RAG-based use cases to improve access to payer policies for medical coders and integrating healthcare-specific search enhancements — all aimed at delivering faster, more accurate information across the organization.

This foundation supports Sharp’s broader data strategy: delivering timely, trustworthy insights that help clinicians and staff improve patient outcomes. From reducing pipeline maintenance to unlocking EHR data, Fivetran has become a key enabler in Sharp’s mission to deliver exceptional care.

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