How Health Information Exchanges (HIEs) Serve as Today’s Population Health Enablers

Summary

The health information exchange landscape is evolving, transitioning from essential data providers to proactive advocates for community health and strengthening the public health infrastructure. Beyond traditional healthcare roles, Health Information Exchanges (HIEs) are recognized as critical partners in comprehensive health data and analytics networks, facilitating the safe sharing of health information for various purposes. Seen as an indispensable public resource, HIEs are poised to further enhance population health outcomes. Learn how.

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Health Information Exchanges (HIEs) play a critical role in enabling population health initiatives by facilitating the seamless exchange of clinical data across healthcare organizations. This interconnected system allows for a more comprehensive view of public health information, enabling providers and regulatory bodies to analyze trends, identify high-risk populations, and tailor interventions to address targeted community health needs.

Their role in securely exchanging health data for diverse applications is likened to that of a vital public utility, with an expanding number of stakeholders recognizing their far-reaching benefits.

HIEs serve 92 percent of Americans, delivering more than one billion clinical alerts annually, according to Strategic Health Information Exchange Collaborative (SHIEC) survey data. In addition, 89 percent of providers believe HIEs help facilitate improved care quality.

There is growing recognition as to how these organizations actively contribute to public health efforts by enabling officials to monitor disease patterns and outbreaks. However, their role extends beyond emergency response  as HIEs are instrumental in driving value-based care transformation initiatives nationwide.

Truly, HIEs have evolved into an essential component of the healthcare system by acting as a secure conduit for exchanging patient data. Yet, HIEs are also being called to adjust to the current demand, as stakeholders are urgently focused on achieving improved population health management. With advancements in healthcare technology and an increasing volume of digital health records, conventional methods to share clinical data may no longer suffice; they present challenges related to interoperability, security, and scalability.

Fortunately, the ongoing shift towards value-based care and rapid technological advancements in healthcare present opportunities for HIEs to showcase their unique value. HIEs must deliver unified and reliable data analytics by leveraging scalable technology infrastructure and innovation to remain viable and maintain high-quality data.

How HIEs Can Establish Data Quality Standards to Advance Operations Amid Value-Based Care Models

Initiating this work begins by implementing a data quality improvement strategy. This also serves as a means for HIEs to safeguard and expand their market presence. When formulating a data quality improvement strategy, HIEs should consider the following:

  • Modern technology foundation. Data and analytics technology should be flexible and designed to scale to support new users, data sources, and locations with population health analytics. The technology must detect and notify when data deviates from the expected standard for completeness and accuracy, enabling real-time evaluation and understanding of any gaps in data exchange.
  • Community-based use cases. It is essential for HIEs to grasp the importance of meeting cost containment and outcomes improvement requirements so that its participants can maintain their operations. When selecting a technology partner, it is crucial for HIEs to find a vendor capable of creating systems for evaluating, overseeing, and enhancing data accuracy across different healthcare delivery and reimbursement models based on the communities served.
  • Data normalization capabilities. HIEs must offer a unified data model structure that accounts for data variability and flexible collection methods as needs evolve. An integrated data model design prevents fragmented data storage and enhances compatibility by establishing a shared structure for uniform data sharing and understanding among applications, systems, and advanced machine learning tools.
  • Regulatory and industry standards compliance. HIEs can streamline data acquisition and reporting processes by aligning with industry standards in data quality, including the National Committee for Quality Assurance (NCQA) Data Aggregator Validation (DAV). NCQA DAV validation offers a stamp of credibility and trustworthiness and underscores an HIE’s commitment to excellence and quality.  What’s more, information from data streams that have been verified by NCQA is eligible to serve as standard supplementary data for Healthcare Effectiveness Data and Information Set (HEDIS) reporting.

Adhering to these standards better positions HIEs to support industry data connectivity efforts at the state and federal levels by providing secure, high-quality, and accurate data, leading to improved patient care and safety.

Moreover, teaming up with a Certified Data Partner can provide an efficient way to simplify the data aggregation complexity and validate data streams, resulting in faster value delivery no matter where an organization is in its level of data aggregation and transformation. Accordingly, an NCQA DAV Certified Data Partner like Ninja Universe™  by Health Catalyst™ can extend the highly-regarded designation to HIEs.

One of the First HIEs to Gain NCQA DAV Status Demonstrates Positive Outcomes Thanks to Certified Data Partner

DAV data is highly valuable to health plans and providers as it eliminates the need for primary source verification (PSV), thereby saving time and resources required for data validation and compliance with quality reporting guidelines. Providing validated data to health plans provides significant value when evaluating the return on investment for HIE services.

For example, by adopting Ninja Universe™, WISHIN became one of the first HIEs in the nation to achieve NCQA DAV status. The Ninja Universe platform comprises modular components that cater to WISHIN’s diverse data needs and quality use cases. With over 40 ingestion sites and NCQA validation, WISHIN has enhanced the value of its data for its health plan participants, resulting in the following positive outcomes:

  • Manual chart reviews now require significantly fewer labor hours, resulting in a positive impact on the documentation of Healthcare Effectiveness Data and Information Set (HEDIS) performance.
  • Health plan participants expected a 10 percent increase in performance measures related to blood pressure control and hemoglobin A1C control leveraging validated, automated data.
  • Using this improved data, WISHIN’s health plan participants could improve their NCQA star rating.

HIEs: Claiming Their Stake in the Future of Population Health Management and Value-Based Care

The importance of health information exchanges cannot be overstated. With providers, health systems, and public health officials relying on insights from extensive data sets, these exchanges play a crucial role in helping them address pressing public health issues and the industry’s continual shift toward value-based care models and more robust population health management.

The question arises: can HIEs remain relevant in this time of significant change? The answer lies in their ability to offer comprehensive and compelling data, expand their extensive experience managing diverse data sources, and standardize vast data using a unified data capture model. To be sure, these capabilities, when done with fidelity, will only serve to solidify their position in the ever-evolving healthcare data and analytics ecosystem.

Additional Reading

Would you like to learn more about this topic? Here are some articles we suggest:

HIE Adopt Data Quality Standards for Long-Term Success

NCQA Data Aggregator Validation (DAV): An ROI Analytics for HIEs

Population Health Success: Three Ways to Leverage Data