Fed initiatives heighten need for organizations to address data strategies
Mandatory submissions of reporting data will place more emphasis on standards and providers’ capabilities to revamp data approaches.
Healthcare organizations are starting to see the shift within programs of the Centers for Medicare & Medicaid Services from optional to mandatory electronic submissions of reporting data.
Aligning an organization’s data with emerging reporting standards, such as the Fast Healthcare Interoperability Resources (FHIR) standard for demographic reporting or electronic clinical quality measures (eCQMs), is complex and requires an all-in approach for whole-system transformation.
A data strategy that addresses integration, value-based care contracts, and data quality will empower clinicians and administrative leaders with trusted, timely data assets that drive informed decisions for better outcomes.
A focus on high-value data as the foundation of an integrated data strategy ensures providers are maximizing their reimbursement today and into the future.
What Is high-value data?
High-value data aligns across multiple source systems for reuse and is accessible, timely and actionable. High-value data standardizes the data shape, or attributes of the patient, encounter or order. It looks for those attributes across other electronic sources of patient information to normalize the terminology and meaning on a health system scale. High-value data can operate in downstream analytics faster and more cost efficiently, and conforms to CMS standards.
What the Return on Data should look like
A strategic approach to data alignment starts with high-value data that benefits program objectives in many ways. The approach:
Adopting a high-value data strategy doesn’t just become a reporting exercise; it becomes a fundamental change to how a clinician or organization provides care equitably and efficiently.
Why value-based care needs integrated data
Healthcare organizations are investing heavily in VBC and commercial programs that reward high-quality and cost-effective care delivery. For these programs to succeed, health systems must first have a clear picture of how to measure performance across investments in payer contracts or quality programs.
For example, does the healthcare system have a sustainable competitive advantage in treating diabetic patients? Furthermore, can the healthcare system leverage that advantage to grow revenue based on cost advantages and superior quality of care?
Providers understand but may not have the technical means to acquire, integrate or share high-quality and timely data. Struggles with existing data models can cause clinicians and care teams to spend more of their time managing data complexity and not enough time managing data insights.
Federal reporting and data-sharing guidelines are requiring health systems to assess the viability of their infrastructure when many are facing budget and resource constraints. However, the compounded value of integrated data has a ripple effect throughout a healthcare organization by reaching stakeholders in contracting, quality and administration to ensure programs are financially viable. Healthcare organizations that adopt high-value data as the foundation for an integrated data strategy will meet value-based expectations in care delivery and reporting outcomes.
Core principles of developing an integrated data strategy
Principle 1: Developing an integrated data strategy with an emphasis on critical use cases for each healthcare organization’s unique needs will ensure the strategy utilizes high-quality data that can be monitored continuously and proactively.
Principle 2: An expansive data model supports the overall concept of high-value data and combines clinical and financial data to drive the highest levels of outcomes improvement. This type of data management strategy delivers data to the hands of people best equipped to make decisions and interact with that information, decentralizing analytics for the organization.
Principle 3: An integrated data management strategy should aim to decentralize the data management function and generate unique data products to enable cross-domain decision making that affects cost, quality and revenue.
Principle 4: Clinical and financial data collection abilities reduce the reliance on source data. To meet emerging federal standards and prepare for high-value performance, time-to-value data accessibility matters for faster results and increased productivity. Lower barriers to data access through data integration and normalization create high-value, reusable data assets.
Future-proofing data strategies
CMS is evolving its programs to align with standardization on interoperability, clinical decision support and clinical quality reporting. Healthcare organizations that can achieve program and reporting requirements will see participation opportunities increase, while those that lag with insufficient data models could struggle.
Finding the right technology partner to implement an integrated data strategy at a more effective cost and reach economies of scale is crucial. Third-party experts in data management can help with cost control and accelerate speed to market in response to mounting pressure to meet federal electronic reporting requirements.
Meeting CMS reporting and interoperability standards is the tip of the iceberg in how an integrated data strategy achieves optimal reimbursement. Federal incentives will continue to persuade healthcare organizations to modernize their technologies, so now is the time to make fundamental data changes.
TJ Elbert is senior vice president and general manager of data at Health Catalyst.