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Data Silos: Together, We Can Bust Them

One of the biggest issues in healthcare research is the ability of researchers to obtain healthcare record data. Information silos of healthcare data exist across both private and public sectors. Working with some of the largest clinical data warehouses and clinical outcomes data in the government – including the U.S. Department of Veteran Affairs’ (VA), Veterans Informatics and Computing Infrastructure (VINCI) – is a good start, but what about Centers for Medicare and Medicaid (CMS) or Department of Defense (DoD) or Indian Health Service (IHS) collective data to support research? Yes, they have their own research arms, but what about an environment for all of them to work together to improve patient outcomes?

Issues and Challenges around Busting Data Silos

To dismantle these information silos, we need legislative directives that allow and encourage data sharing across both the federal and commercial healthcare environments, and include security requirements to protect personally identifiable information (PII) and protected health information (PHI). Even with these directives, issues will remain with information exchange, data quality, data mapping, data pedigree, etc.

Even with state and private sector exchange solutions, such as health information networks (HINs), impediments to data access for researchers still exist. Without timely and quality research, innovations to healthcare and disease management stall, which in turn, directly impede improving quality patient care. Ongoing initiatives to overcome these obstacles improve slowly. For example, the Moonshot Initiative raises awareness on the need to support research for cancer and chronic conditions for our aging population.

Data Silo-Busting Examples

Within the government, one disconnect appears between the federal and state systems that support military service men and women retiring as veterans. For example, the DoD’s Clinical Data Repository (CDR), Department of VA’s Corporate Data Warehouse (CDW), and data from the State Veterans Homes do not connect directly with each other, nor share entire records at this time. Approximately 25% of the entire U.S. population patient records are within the federal and state health electronic health records (EHR)/health information systems (HIS) (commercial and federal EHRs).

However, initiatives underway for over a decade to support some exchange across government entities are beginning to pull information from community care organizations and other third-party groups. Some of the initiatives between VA, DoD and private sector include:

Steps to Bust Data Silos

Sharing complete patient records across the VA and DoD in real time is one of the first steps we can take to remove information silos. To facilitate this information flow, we must implement a more collaborate data strategy.

Here are a few steps to inform that strategy:

  1. document current systems;
  2. meet with all stakeholders and form focus groups to develop a strategy;
  3. document past and current challenges facing data exchange; and
  4. facilitate and encourage negotiation/solution development to resolve challenges between VA and DOD third parties.

I’ve compiled recommended strategies (Table 1) to bridge information silos across federal organizations that addresses uncertainties, challenges and possible resolutions to move forward.

ChallengesResolutions
VA and DOD have relied on a patchwork of initiatives involving their health information systems to achieve electronic health record interoperability with little or no oversight on standards used.Leverage the work already done within VA to support initiative which will harmonize across the department standards for interoperability
Lack of a well-defined requirements and architecture for describing the interface for a common health information exchange between VA/DoD,Standards requirements should be published for internal and external use by projects as well as vendors to support interoperability much like Technical Reference Model (TRM) is published today.
Application and infrastructure architectural enhancements (like caching, scalability, etc.) need to be put in place to make the applications robust, highly available, scalable, and performant to meet the requirements defined in VA CONOPS.Move away from rack and stack solutions and into commodity based hosting of data to focus VA back to its mission.
Requirements to achieve interoperability come from policy as well as market forces to include the National Defense Authorization Act (NDAA), Presidential Mandates, Meaningful Use and the HITECH ACT that are not always be implemented consistently.Align these requirements based on “what works” within each policy and publish them for Congress to consider as well as all vendors and projects across the enterprise.
As both VA and DoD modernize their health records over the next several years, a well-documented, coordinated and implementable interoperability roadmap will help both Departments achieve their interoperability mission.Cross coordinate themes and understanding as both departments move toward a common goal. Silo development of modernization will not yield the results expected by Congress.

Table 1

While this example specifies data silo issues between the VA and DoD, the steps and solutions apply to other silo instances.

The Data Silo-Busting Challenge for You

  • As a healthcare leader who advocates for data quality, what are other resolutions that can overcome these challenges?
  • If you are not a current HIMSS member, consider joining our organization to collaborate with other leaders and help guide government and the public healthcare community to develop standards and exchange across both commercial, state, and federal instances.

Join the HIMSS C&BI Community today to stay up to date and learn more about the tools and educational opportunities focused on policies to remove silos, secure exchange of data, quality of data, and other critical topics that will help you on your journey to Turn Data to Action.

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Keywords: 
Data Silos; data exchange; Clinical & Business Intelligence; HIMSS