The push to make Healthcare Information more portable has been an ongoing battle for the last few decades. A variety of factors, including evolving federal legislation and the regulatory framework, the spike in mergers and acquisitions as well as the general need for bigger and better analytics drive this push. Over $US 500 million dollars has already been allocated to help assist with the setup and deployment of existing Health Information Exchanges nationwide. Over the last four years, we have noted a considerable upward trend towards the consolidation merger and acquisitions of hospitals. cites acquisitions as one strategy to meet the demands of new health care rules. With the mergers of clinics and hospitals, comes the rather daunting and labor intensive task of consolidating disparate E.H.R. systems. With dozens of different vendors using a variety of back end databases and systems, such consolidation efforts generally involve complex data warehousing projects that are expensive and time consuming, not to mention painful for the providers and, on occasion, the patients. Currently, the process of providing a federated view into healthcare informatics is very vendor specific and consolidating the myriad of vendor data can be challenging for an individual location. With the need to do this across multiple interface vendors and multiple hospitals the challenge becomes exponentially greater.

Enter Extrahop:
ExtraHop creates a logical layer between the various HL7 vendors thereby “agnostifying” (judging by spellcheck, that isn’t even a word) the HL7 data. The data can then be put into a relational database in parallel to your existing HIS system(s). With ExtraHop, this data can now be leveraged by ‘Big Data’ solutions that utilize a relational database back end. By providing a parallel path to Big Data, ExtraHop allows you to continue with your existing EMR/HIS investment while writing the metrics to a big data back end for you at the same time.

How does it work?
ExtraHop is a completely agentless, passive monitoring solution that spans the network traffic and observes the HL7 as it traverses the wire. In doing so, it makes the HL7 data agnostic as the specific segments are parsed into a more database friendly format and stored appropriately. ExtraHop is unique in that it allows you to exclude specific patient data segments to ensure that no sensitive data is saved while populating a second data store that can be safely used for B2B partners, state and federal agencies as well as third parties.


Use Cases: (All Real-Time):
My first job after college was as an Environmental Health Specialist for Maricopa County. One of my duties was to investigate foodborne illnesses. I wish I could have had access to real-time HL7 data to allow quick visibility into issues such as a (hypothetical) rise in Hepatitis A diagnosis or demand in gamma-globulin shots after a state fair or food festival. Currently public health surveillance systems struggle to get access to real-time data due to costs and complexities around consolidating information. ExtraHop’s Wire Data Analytics Engine gives healthcare providers the ability to securely, inexpensively and quickly provide this information in real time. This gives public health officials ready-access to information without the hospital or clinic being forced to share sensitive or business critical or competitive information. It also positions large healthcare organizations to be able to leverage the same agility regardless of the myriad of back end HIS/EMR systems that may exist throughout their own enterprises. Most importantly, hospitals and clinics have the ability to share aggregate data that does not contain personally identifiable information on patients. Long term, this potentially positions Quality Assurance (QA) teams to oversee specific Diagnosis (DG1), Demographic and Pharmaceutical (RXE|RXR|RXC) combinations that can indicate risk and potentially provide better oversight of patient care.

Other Potential Real-Time Use Cases:

  • Tracking prescriptions by physician
  • Geospatially track DG1 (Diagnosis) and OBX/OBR (Observations) records (PAN FLU Surveillance)
  • Federate patient data for large hospital organizations
  • Correlate external events with hospital visits (Flooding impact on water quality by checking GI admission data)
  • Catch potential fraud and duplicate billing incidents
  • Track insurance information to allow for indigent care planning
  • Audit Meaningful Use Compliance

Mergers and Acquisitions:
We have all observed a rise in mergers and acquisitions in healthcare the last few years. While companies may decide to merge for financial reasons, often little consideration is given to the effort needed to integrate existing, disparate information systems. In addition, large hospital conglomerates simultaneously have integration challenges and the need to provide a federated view into their healthcare data often through an Healthcare Information Exchange. Even if every hospital has the exact same HIS/EMR system, providing a centralized view can be very challenging. ExtraHop offers the ability to federate all HL7 transactions into a parallel data store that can be leveraged to facilitate auditing, HIE participation and streamlining workflows. There is always a market for better data, ExtraHop’s Wire Data Analytics provides the ability to centralize information and position IT to be a profit center with data as its currency.

Important HL7 data can be intercepted off the wire and populated to a centralized, parallel data store in real-time using a number of methods.

  • Syslog transactions to a centralized back end like Splunk
  • Push the data securely over HTTPs using a RESTFUL push
  • Write the data directly to a big data (MongoDB) back end

This allows healthcare companies and agencies to securely send data over the internet via HTTPs or directly to a back end Syslog or MongoDB server. This makes the ExtraHop solution a very multi-tenant and multi-topology friendly solution.

Example: Large Conglomerate setting up a parallel system by harvesting HL7 data directly off the wire.


Health Information Exchanges:

Three of the critical roadblocks HIE’s face, according to GovHealthIT include: Data Sharing, Complexity Costs and Competition. ExtraHop’s wire data analytics platform addresses each one of these roadblocks and can offer a secure, standardized and practical solution for healthcare information sharing.

Data Sharing:
Much of our healthcare data exists in silos and data exchanges between EHRs and HIE’s uneven across states and regions. By collecting and parsing the data directly off the wire the clinic or hospital is no longer tethered to their incumbent EHR/HIS system for sharing data. This allows for data to be written to an external data store at the same time it is written to the EHR/HIS system.

Complexity Costs:
The article cites complexity as the “most cutting criticism of HIEs”, they point out that a wide variety of state and regional HIEs operate at different scales, this puts the owner of the data in a difficult position. Healthcare providers also struggle to implement “scores of software systems”. Despite all of this, data remains in silos and largely unavailable. ExtraHop’s wire data analytics platform resolves this issue by taking the data directly off the wire. The data can then be parsed, normalized in a manner that suits any downstream HIEs receiving the data. Again, by providing a logical layer between the messages and the EHRs we can seamlessly integrate HL7 data without labor intensive data warehousing projects.

The article states that hospitals that routinely compete for patients are being asked to share data with their competitors. This is something that is outright blasphemy in any industry. ExtraHop can allow the HL7 owner to dictate which fields and segments are shared with the HIE and potentially assuage any concerns about business specific data being made available to competitors. With ExtraHop’s HL7 protocol analysis, the data owner can choose what data is sent and what data is not sent to the HIEs.

I would also cite a quote from the following paper from the University of Chicago:

“As a rapidly increasing number of health care providers adopt electronic health records (EHRs), the benefits that can be realized from these systems is substantially greater when patient data is not trapped within individual institutions. The timely sharing of electronic health information can improve health care quality, efficiency, and safety by ensuring that healthcare providers have access to comprehensive clinical information”

Using wire data to set up a parallel environment can position healthcare providers to leverage an extremely robust solution (40gb/s) that will allow you to write data to a parallel system with absolutely zero impact on your incumbent EMR/HIS systems. This opens up the possibility of sharing information across multiple state and local partners, B2B partners and can allow you to make secure data available to third parties with assurances that no patient information is written. By taking the data directly off the wire, incumbent systems are not subject to the data warehousing processes and procedures that could impact performance and since the data is written completely parallel to these systems, it can be made available in real-time.

Click the Image below to Enlarge

With the ability to geo-code where the messages are coming from PHIN’s can track ambulatory care in real-time. Below is a fictitious example of what that might look like in ExtraHop. We basically log wire data transactions, weather it is an XML field, Database query or HL7 diagnosis (DG1) segment.


The ability to share information has benefits beyond just the consolidation of data across multiple healthcare providers. Leveraging wire data analytics with ExtraHop positions your company or agency to be able to engage in big data solutions, write to a parallel data store or even securely share non-patient data with third parties with no impact on your existing systems. By providing an abstraction layer between the back end data stores and the HL7 messages themselves we are able to securely, efficiently and quickly make healthcare information considerably more portable. This has benefits for public health institutions such as my former employer, the Centers for Disease Control, state and local health departments and centralized healthcare providers overseeing hundreds of hospitals and thousands of patients.

This opens up healthcare informatics to new tools and new ways to perform analytics and provides the same level of integration across healthcare providers regardless of how complex their back end EMRs and HIS systems are. By leveraging wire data we have a chance to take healthcare into the next phase of informatics without impacting the providers, practitioners and most importantly, the patients.

Thanks for reading

John M. Smith





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