CMS healthcare programs are shifting from an optional data reporting submissions to mandatory electronic submissions. To meet these requirements, healthcare organizations need to align their organization’s data with evolving standards, which can require a whole-system transformation.
This is the first of three articles that stress the urgent need for healthcare systems to take an all-in approach to data and analytics, starting with the need for and benefits of high-value data.
High-value data has been standardized and can be used to identity standardized attributes across previously siloed systems. It enables: faster downstream analytics, aggregated benchmarking, novel data combinations that produce exponential value.
Organizations that make high-value data the foundation of an integrated data strategy, can supply providers, clinicians, and administrative leaders with the trusted, timely data they need to maximize reimbursement and drive informed decisions for better outcomes.
Download
In 2023, the Centers for Medicare & Medicaid Services (CMS) are increasing electronic data reporting requirements for many programs and instituting mandatory electronic submissions. This update signals the federal government’s growing attention toward initiating industry-wide healthcare data reporting standards requiring organizations to reassess their data management and capture strategies.
Aligning a health system’s data strategies with continually evolving federal standards, such as the Fast Healthcare Interoperability Resources (FHIR) standard for demographic reporting or the electronic clinical quality measures (eCQMs), is a complex undertaking. Health systems would benefit from an all-in approach to healthcare data reporting, recognizing that high-value data and advanced data analytics are critical to providing the right data to the right person at the right time. This series of three articles identifies three components for aligning an organization’s data reporting with these standards, starting with the need to unlock high-value data.
The technological complexity of healthcare today demands data integration across multiple source systems for reuse, generating high-value data. Turning raw data into high-value data requires standardizing the data shape, including the attributes of the patient, encounter, or order, so the identified attributes can be located across previously siloed sources, normalizing terminology and meaning on a health-system scale.
High-value data:
With high-value data as the foundation of an integrated data strategy, organizations can supply providers, clinicians, and administrative leaders with the trusted, timely data they need to maximize reimbursement and drive informed decisions for better outcomes.
One such organization, Community Health Network (CHNw), elevated its healthcare data reporting through high-value data. CHNw pursued its vision to transform into an analytics-informed organization by enriching and normalizing previously siloed data from multiple source systems into transparent, trusted, high-value data. To do this, CHNw partnered with Health Catalyst to develop and implement solutions across the health system and realized a 4X return on their investment.
Committing to a high-value data strategy across the system benefits healthcare organizations in many ways. This strategic approach:
Adopting a high-value data strategy can be more than a healthcare data reporting exercise; it can aid clinicians and organizations in providing care equitably and efficiently.
Since value-based Care (VBC) programs reward high-quality and cost-effective care delivery, organizations committed to these programs need a clear picture of measured performance. High-value data can aid organizations in their efforts to measure performance across their investments in payer contracts or quality programs so they can make informed, timely decisions.
In addition, high-value data can support providers in their work to provide value-based care. Currently, providers may not have the technical means to acquire, integrate or share data with their clinicians and care teams in a timely manner. Such struggles with existing data models can cause providers to spend more time managing data complexity, impacting the time they could spend leveraging data insights to improve care outcomes.
Implementing data strategies that generate and leverage high-value data is foundational to any health organization’s ability to provide clinicians and leaders with real-time insights to maximize the quality of care and reimbursement. As CMS reporting and data-sharing guidelines shift from optional to mandatory, health systems will benefit from updating their existing infrastructure and data strategies.
Up Next: In the next article, we will cover four principles for developing an integrated data strategy.
