U.S. healthcare providers, like many large organizations, are quickly realizing that data can propel them forward or hold them back. Healthcare organizations, in particular, have an immense amount of data. According to an IDC report, approximately 30% of the world’s data volume is generated by the healthcare industry.

Hospital systems and other large integrated health networks are especially affected by this data burden. Many of them have consolidated, resulting in one large entity with multiple disparate systems for clinical, financial, and HR data management.

Lots of data but no real use. Lacking a strong, central data platform is greatly impeding healthcare organizations from better understanding today’s environment, much less providing guidance for future planning. Because the data is inaccessible, integrated healthcare networks can lack a single view at the enterprise level for even the most basic metrics.

Data often is old and poor quality. Waiting for data to be refreshed impacts when and how key business decisions are made. Old data erodes trust in the findings, especially for providers seeking reliable, relevant information for their patients.

Security is always top of mind. Data security and privacy regulations have always been a crucial concern for healthcare providers. Legacy systems have become a prime target for cybersecurity attacks. In fact, in 2024, two of the largest data attacks happened to healthcare providers, one where an entire network was brought down.

Healthcare organizations know they must move towards a consolidated data platform. The question is how to get there.

EXL along with our partner Databricks, has worked with many U.S. healthcare organizations to modernize their data management operations. We have determined these key features to ensure success in developing a strong data platform, no matter where your organization is on this journey:

• Focus on data governance as a critical built-in component
• Take an incremental approach, driven by business use cases
• Rely on a partner with real-world healthcare operations experience

Focus on data governance as a critical built-in component

It is critical for healthcare organizations to view their data platform from a governance perspective from the very start. In many legacy systems, governance was an after-thought, one component of many that was not implemented appropriately, nor with sufficient access controls. That model is both ineffective and counterproductive for today’s security and accessibility needs.

Instead, integrated healthcare networks should look for a data management solution with governance component embedded into it. The governance layer should be viewed holistically so that data governance and data security are part of the design itself. Further, a governance model should be viewed to support not only current use cases but also to meet future needs.

Data governance is now even more pertinent as organizations are moving their data management platforms to the cloud. Data governance is becoming more transparent and with the cloud imperative, and its regulatory requirements, healthcare organizations must have a tight governance framework. The result: the right person has access to the right information at the right time.

Take an incremental approach, driven by business use cases

Integrated health networks should work with partners that take an incremental approach to building data platforms. Technology projects historically derail or run significantly over budget because the approach was too encompassing.

A proven approach is to start first with building the data foundation and onboarding data sources incrementally. From this foundation, organizations then can determine appropriate analytics and use cases and then build out a solution. As the data sources added to the ecosystem increase, the number of user cases also increases. Using this use-case-driven approach, healthcare organizations can more clearly define success criteria and KPIs, from improving the speed of data to delivering enterprise-level business metrics.

Rely on a partner with real-world healthcare operations experience

When building a data platform, organizations might see this work as a technical issue that requires a technology solution. In reality, the challenge is a domain problem, especially for the healthcare industry. It is imperative that technology partners provide professional staff who understand healthcare data, speak the language of healthcare provider, and know the most critical business use cases. The team should have real-world experience in day-to-day operations of a healthcare organization to provide a top-down perspective on business use cases.

Working together, EXL and Databricks. As a leading data and AI company, EXL brings together the power of data, AI and deep industry knowledge to transform healthcare organizations. Working with the Databricks Intelligent Data Platform, we implement governance-driven, unified data management systems that have transformed healthcare operations.

Recently, a healthcare provider partnered with EXL and Databricks to undertake a significant data transformation initiative aimed at resolving issues with its outdated infrastructure. The organization was dealing with siloed data from multiple Electronic Medical Record (EMR) systems. The data processing pipelines took over eight hours to process batch data files, and the data warehouse lacked enterprise-level insights due to non-standard data layouts and poor data quality.

EXL and Databricks collaborated to design a future target architecture, implementing Databricks’ Data Intelligence Platform to address the customer's major challenges.

EXL adopted a phased approach for the data transformation initiative. The initial 12-week phase involved setting up Azure Databricks, establishing the Lakehouse architecture, and building pipelines to source data from a single EMR into an enterprise-level common data foundation within Databricks. This phase also included developing key components such as data governance using Unity Catalog, a configurable data quality framework, and a reference data management framework to address quality issues and eliminate data silos.

EXL leveraged its healthcare domain expertise to define data quality rules and data standardization business logic, ensuring the solution's effectiveness. As a result, the customer was able to build a configurable and scalable solution with a high-quality, enterprise-level common data foundation. This standardized dataset was available for downstream analytics, reducing processing time to 10 minutes with a refresh every 30 minutes. This improvement enabled the customer to integrate newly acquired physician networks within weeks, rather than the months it previously took.

The result. A strong data management platform can greatly improve an organization’s data frequency, quality and availability. Better data can drive an improved member experience with your integrated health network, from timely access to clinical information to hospital/member scheduling coordination to billing.

Healthcare providers will build increased trust to rely on the data being shared with them. Clinical nursing staff will spend less time doing administrative work, allowing them to be significantly more productive. With ongoing staffing shortages in healthcare, increasing employee satisfaction can improve retention in dramatic new ways.

And finally, there is AI. As healthcare organizations look to leverage this major technology innovation, any AI solution will rely on having a strong underlying data foundation. Realizing the benefits of advanced analytics or automation simply will not be feasible without a solid data management system.

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