Insight
Your Guide to Building a Proactive Healthcare Data Strategy
Healthcare organizations are centered around providing care, not managing data. So it’s no surprise that, while healthcare generates 30% of the world’s data, an astonishing 97% goes unused. A striking 76% of enterprises admit to making business decisions without consulting available data because it was too difficult to access, highlighting a widening gap between data availability and data usability that healthcare leaders can’t ignore.
This guide is designed for healthcare IT, data, and operations leaders who are responsible for aligning data strategy with organizational goals. We explore why a proactive approach is essential, the foundational pillars of success, common roadblocks, and a practical roadmap for transformation.

Why a Proactive Data Strategy Matters
A proactive data strategy empowers healthcare organizations to improve care, operate efficiently, and stay competitive in a dynamic industry. The shift toward value-based care and population health underscores the need for real-time, trustworthy data. Value-based models depend on tracking outcomes and interventions, while population health strategies rely on analyzing data across demographics and risk factors to close gaps in care.

The cornerstone of this approach is real-time data. It allows organizations to make agile, evidence-based decisions that enhance clinical, operational, and financial outcomes. Conversely, reactive or ad-hoc approaches to data result in missed insights, inefficient operations, and fragmented care.
Evolving CMS regulations such as the Proposed Interoperability and Prior Authorization Rule (CMS-0057) make compliance more than a checkbox—it's a strategic imperative. A strong data governance framework ensures compliance, maintains data integrity, and builds the foundation for advanced analytics and innovation.

Four Key Pillars of a Proactive Data Strategy
A robust data strategy is not solely an IT initiative; it should be championed by leaders across the organization. These four pillars provide the foundation for a true enterprise-wide transformation:
1. Strategic Alignment
Every department touches data. Strategic alignment ensures that clinical, operational, and IT teams work from a shared vision. Engaging stakeholders early prevents silos, encourages collaboration, and aligns data initiatives with top-line goals like reducing readmissions or improving access.
Action Steps:
- Establish cross-functional data strategy councils
- Align KPIs with strategic initiatives
- Highlight quick wins to build buy-in

2. Data Governance
Data governance defines how data is managed, accessed, and used. It includes policies, processes, and people—particularly data stewards—who ensure data accuracy, availability, and consistency across the enterprise.
Action Steps:
- Appoint departmental data stewards
- Standardize definitions and quality rules
- Implement escalation and accountability structures
The hardest architecture challenge healthcare organizations face today isn’t just choosing the right tech stack—it’s figuring out how to scale it and upskill their teams. We’re helping clients build scalable environments that support modern use cases like task automation, process flow mapping, and using LLMs for clinical workflow optimization. The time to tackle these challenges is now.
PHIL HEFFLEYManaging Director, Analytics & Insights
3. Scalable Architecture
As healthcare data volumes skyrocket, scalable architecture is vital. Cloud-native platforms and flexible data lakehouses support both structured and unstructured data and enable advanced analytics, AI, and ML.
Action Steps:
- Inventory legacy systems and assess cloud readiness
- Choose scalable platforms (e.g., Azure, Snowflake, Databricks)
- Enable API-based interoperability for rapid innovation
4. Advanced Analytics Readiness
Advanced analytics and AI can identify at-risk patients, improve staffing models, and reduce readmissions—but only if the data is reliable and accessible. Equipping end users with self-service analytics and improving data literacy accelerates decision-making and fosters innovation.
Action Steps:
- Evaluate tools like Power BI, Tableau, or Looker
- Promote role-based access and training
- Establish data literacy programs with internal champions
- Evaluate tools and technology to support enterprise initiatives, KPI metrics, and data consumption
- Identify skill gaps in your current BI, data science, and engineering teams
- Establish data literacy programs with internal champions that promote a data-driven culture
Valleywise Health needed a partner with data-based analytics and governance expertise, as well as specific and deep Epic EHR knowledge to install and operationalize the HEDIS module. Tegria brought the leadership, technical skills, and experience we needed to manage the implementation from start to finish.
KELLY SUMMERSSVP, Chief Information Officer, Valleywise Health
Common Challenges and How To Overcome Them
Challenge 1: Siloed Data and Inconsistent Definitions
Problem: Disconnected systems and varying definitions prevent a single source of truth.
Solution: Implement an integrated data platform and promote enterprise-wide governance. Empower data stewards to unify definitions and champion interoperability standards.
Challenge 2: Lack of Organizational Alignment
Problem: Data initiatives are seen as extra work and struggle to gain momentum.
Solution: Create a data strategy council with representatives from clinical, IT, legal, and operations. Showcase early wins to demonstrate value and drive adoption.

Challenge 3: Technical Debt and Outdated Infrastructure
Problem: Legacy systems hinder integration while increasing cost and complexity.
Solution: Migrate to cloud-native platforms that support analytics and real-time decision-making. Prioritize flexible, scalable solutions to future-proof your strategy.
Challenge 4: Low Data Literacy
Problem: Staff lack the confidence and skills to interpret and act on data.
Solution: Invest in a thriving data culture via targeted training, appoint data champions, document data lineage, and create intuitive dashboards.
Your Roadmap to a Proactive Data Strategy

Step 1: Assess Your Current State
Interview key stakeholders, map your data environment, and evaluate your current analytics maturity.
Step 2: Define Goals and KPIs
Establish short-term wins and long-term metrics aligned with organizational priorities.
Step 3: Develop a Scalable Architecture Plan
Ensure your infrastructure can grow and adapt to future demands.
Step 4: Implement a Governance Framework
Clarify roles and responsibilities, assign data ownership, and embed accountability mechanisms.
Step 5: Build a Data-Driven Culture
Promote enterprise-wide data literacy, democratize access, and celebrate success stories.
Step 6: Monitor, Refine, and Scale
Adopt a continuous improvement mindset with regular reviews, feedback loops, and scalability planning.
How Tegria Can Help
Tegria takes a proactive, partnership-based approach to data transformation. Our experts work closely with stakeholders across clinical, operational, and IT departments to design strategies that align with your unique goals.
We specialize in healthcare data and hold certifications in Epic Cogito, Azure, AWS, Databricks, Snowflake, and Power BI. From modernizing legacy infrastructure to implementing governance and analytics platforms, we guide clients from quick wins to long-term success.
Client Success
St. Luke’s University Health Network transitioned to an Azure data lakehouse with Tegria’s support, ahead of schedule and under budget. The result? Reduced costs, improved compliance, and accelerated innovation.
Conclusion
Healthcare data is more than a byproduct of care—it’s a strategic asset. Yet managing that asset can feel like trying to file thousands of new documents each day into an already overflowing file cabinet. The result? Disorganization, duplication, and missed opportunities.

A proactive data strategy replaces the outdated, overflowing file cabinet with a scalable, intelligent system so that the right information is easily available to the right people at the right time. This shift allows healthcare professionals to spend less time hunting for data and more time delivering care.
By investing in a proactive data strategy that includes strong governance, scalable infrastructure, and enterprise-wide engagement, healthcare leaders can transform data from a burden into a catalyst for growth and return their focus to what matters most: patient care.