Dirty Data Muddies Future of Health Information Exchanges (HIEs)

Health information exchanges (HIEs) enable data sharing among neighboring healthcare organizations such as hospitals, labs, pharmacies, and clinics – helping ensure that clinicians have access to the information they need to make informed decisions. By improving care coordination and operational efficiencies, HIEs help clinicians focus more of their time on patients.

The eHealth Initiative (eHI) recently published a report on the status of HIEs to address the industry’s technology challenges and priorities. 

While progress has been painfully slow over the past decade, HIEs have shown flashes of promise as a model for sharing patient information across hospitals and health systems. The recent growth of HIEs has been attributed to several factors including the rapid advancement of health information technologies, federal regulations, incentives promoting interoperability, and the rise of value-based care.

The data-rich eHI report surveyed a total of 53 U.S. based HIEs in 35 states across the country. The 2020 survey examined HIE perspectives and the associated challenges in four key areas:

  1. Adoption of new technology
  2. Integrating clinical and claims data
  3. Types of data being exchanged
  4. Business drivers and priorities


The report concluded that the top drivers for technology adoption include:

  • Desire of stakeholders to manage risk and deliver value-based care contacts 
  • Easier integration using APIs, FHIR, etc. 
  • Clearer value (care transition management and medication reconciliation) 
  • Incentives from government agencies including state and local authorities, and CMS
  • The increased demand for population health analytics tools 

The report also detailed the top business priorities for the next two years, which included:

  • Enhancing interoperability 
  • Supporting value-based care 
  • Integrating EHR and HIE workflows 
  • Integrating non-traditional types of data like genomics and social 
  • Enhancing care coordination 
  • Maintaining sustainability and financial viability for the long-term

Overall, HIEs report that payer participation is trending upward due to:

  • Increased interoperability

An increasing number of HIEs say their interoperability platforms can now extract, aggregate, and normalize data from a variety of systems. Natural language processing engines that can read and organize unstructured data like clinical notes and summaries have also matured.

  • Comprehensive clinical information

Many HIEs report providing more comprehensive data to satisfy a variety of payer use cases including risk stratification, quality measurement, and payer-led care management programs. 

  • Strengthened desire by Providers to collaborate with Payers 

Providers now want the payers involved. Spurred by the rise of value-based contracts, providers need claims data to understand how their care management programs and interventions impact the cost of care. 

Data Quality Limits Payer Participation

Another key finding from the eHI study is payers’ reported interest in obtaining more clinical data. According to the survey, 67% of HIEs reported seeing a significant or very significant increase in payers asking for more access to clinical data.

However, the ability for HIEs to integrate clinical and claims data is still a work in progress. Approximately 60% of respondents reported having the capability to integrate clinical and claims data. While 85% of HIEs with 3 million or more members reported having the ability to integrate clinical and claims data, only 50% with less than 3 million members reported having this capability.

The most significant challenges HIEs face when it comes to integrating clinical and claims data include:

  • Data quality issues 
  • Cost of technology
  • Availability of qualified staff 
  • Claims data not available 
  • Privacy/security policies that limit transactions 

To support value-based care, HIEs must have the ability to integrate clinical and claims data. Hamstrung by limited resources, tools, quality data, and access to claims data, many HIEs aren’t able to integrate this data effectively.

Another study by the Journal of the American Medical Informatics Association (JAMIA) supported these findings and posed offered additional insights.  

JAMIA Study Reflects Payer Perspective on HIEs

Payers have access to clinical and claims data, but many are still undecided about whether to join the HIEs. According to research published in the Journal of the American Medical Informatics Association (JAMIA), the need for better data is not the only factor keeping many payers on the fence. The JAMIA survey identified multiple barriers to participation including:

  • HIEs were developed around communities, states, and regions, requiring prospective payers to support numerous HIE efforts fragmented by geography.
  • HIEs were developed in a provider-centric way, primarily around provider data and use cases versus payer data and use cases. As a result, many payers feel excluded from the exchange of data.
  • Many payers say they would like to see broader participation and sharing of data between all HIE members, payers, and providers.
  • Many payers indicated they want to see HIEs frame their value propositions around the triple aim of improving the patient experience of care, improving the health of populations, and reducing the per capita cost of health care.
  • Concerns remain about HIEs’ ability to collect both clinical and claims data in a wide range of formats.

Interoperability and a Lack of Clean Data Remain the Biggest Barriers

Despite the promise of providers and payers working together to address gaps in care, the road to true collaboration is rife with challenges. Bringing claims data into an HIE, for instance, can be a difficult proposition. That’s because clinical and revenue cycle management systems were never intended to integrate with each other, creating significant technical barriers. Additionally, state laws, provider membership, and contractual agreements create differences in patient participation and consent models. 

Just as important as an HIEs’ ability to ingest and share data is the quality of the data they receive in the first place. With so much attention paid to the use of artificial intelligence, machine learning and other advanced technologies, the fundamental need for the original data to be complete, accurate and clean is often overlooked. If it’s dirty going in, everything derived from it will be fundamentally flawed coming out. 

What can be done to close the gap? 

The best way to reach an effective level of real-time data sharing and analytics is to normalize, standardize, and enrich the data they’re working with – before the data gets pulled into the systems doing all the advanced predictive analytics.

The need for quality actionable data at the point of service continues to be a major issue in healthcare and a pain point for patients, payers, and providers. It threatens the progress of interoperability and data sharing and the sustainability of HIEs, particularly when the data lives in different EMR systems. Since data serves as the foundation for decision making in an industry that deals in life and death, it must be clean at the point of ingestion.

Verinovum’s Data Curation as a Service (DCaaS) platform uniquely solves the data quality problem between disparate systems. The reason it works is that Verinovum starts curating data at the point of ingestion. The platform cleans and standardizes data for payers’ and providers’ most pressing use cases.

Verinovum facilitates data extraction, standardization, normalization, and management. Our solutions for ACOs, CINs, and payers focus on three core principles:

  • Data fidelity – Perpetual storage of raw messages coupled with the use of proprietary content blocking hash technique and configurable administrative tools allow for rapid onboarding of clinical data.
  • Data transparency – Ingested data is then interrogated for quality against desired customer use cases and normalization techniques are deployed to maximize the efficacy of the data asset available.
  • Data flexibility – As market goals change, the platforms normalization rules and maps can be modified on the fly, with only the data deltas being reprocessed – the byproduct of our propriety data hashing technique. This maximizes time to value without sacrificing long-term flexibility.

If HIEs are to prove sustainable and demonstrate their full potential, the data they’re collecting and putting into their systems must be clean. At Verinovum, we are confident that our unique, end-to-end approach to data enrichment is the tool that providers, HIEs and payers have been waiting for to solve their interoperability challenges.