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In a typical client server environment data resides in a traditional, direct-attached storage model, randomly distributed across the enterprise. The result is silos of information that function sufficiently, but only when proximity and connectivity to the feeder systems is maintained. Healthcare institutions are forced to plan on ways to communicate patient administrative data, orders and results (i.e. laboratory, radiology, pharmacy and clinical documentation) across the enterprise using existing disparate systems as the clinician conduit.

In today's fragmented environments however, there are multiple points of data capture and input channels, which makes it difficult to administer storage while applying consistent data governance policies. In addition, with a wide variety of storage platforms and configurations all served by different management tools, the result is often the duplication of data which in turn leads to versioning, transfer, and synchronization challenges.

This article tries to determine the organizational and clinical aspects of data storage consolidation. Rather than focusing on technology, the following will consider these points:

  1. Why you should consolidate from an organizational point of view
  2. What does Clinical Collaboration mean
  3. Standards as the basis for all consolidation
  4. How only proper data consolidation enables true data mining
  5. What should a Data centre look like
  6. Dealing with Multiple Patient ID domains
  7. Reducing Duplication of Orders
  8. What to do after the consolidation is done
  9. Practical Advices on how to approach such a project

WHY CONSOLIDATE

The name of the game is consolidating clinical data for cost control and data availability for aggregation, mining and distribution. Healthcare organizations are implementing consolidation strategies to help rationalize IT infrastructure investments, reduce IT cost, and take advantage of newer innovative technologies. The challenge today is not the storage technology, but is getting data where it needs to be and managing it in such a way that the data can be distributed across the enterprise to the clinicians at the point of care.

CLINICAL COLLABORATION

At its most basic level, Clinical collaboration must allow healthcare systems to share lab results, radiology diagnostic reports, clinical documentation and images across disparate systems. Only then can facilities see greater efficiencies and provide better care for their patient population.

Data that is clinically relevant can be classified and act on rules that provide the logic as to where and when this data should be available. The issue of course is where this data should be available. The point of care is different for every clinician, depending upon where they are practicing the art of medicine. The data must be stored in a centralized place where EMR, EHR or HIS systems can easily retrieve via queries, and distributed to the clinician wherever it is needed.

Today this can be achieved within a single vendor solution that uses an interface engine; utilizing a communication protocol called HL7. The complexity of this simple communication concept becomes evident when the clinician needs data from disparate systems. However, trying to offer a transparent interoperable solution usually requires complicated and inconvenient uses of multiple logins, in combination with fax machines, phone calls and communication protocols. This combination of manual workarounds interrupts the continuity of care, and is one of the reasons why adoption rates remain low.

Ideally, the clinician wants to login into a single system, to view a patient's continuum of care, be it episodic or historical. This point of care access is where automation and adoption is realized, and until vendors can provide this type of solution, healthcare will continue to invest in hybrid solutions and workarounds that exacerbate the problem rather than solving it.

Breaking down these barriers can only be achieved when a consolidated hub - a Data Center where all clinical data is stored and managed - can be queried, mined and accessed across the enterprise, at the point of care.

Instead of providing non-collaborative solutions, vendors should be working on standards based solutions that offer interoperable communication with a variety of systems to allow disparate data query from wherever the clinician needs access.

STANDARDS LEAD THE WAY

How clinical data benefits the clinician and administrators continues to change. National, regional and local organizations are in need of data warehouses where data can be stored, in a redundant fashion and inevitably shared across the enterprise. This can only be done by embracing standards.

However Data is not always stored or distributed using any standard. Therefore proprietary and non-standard data can and will require a significant effort to standardize it for management, indexing and distribution.

Standards that indicate easier interoperability are key for sites that have already invested in multiple interdependent systems. The fact remains that these systems need a common consolidated point of data management and exchange.

The degree of maturity of interoperable standards i.e. HL7, XML, DICOM and ANSI X12 are leading the way in discovering better ways to understand and aggregate clinical data and images into functional data warehouse and repositories. The latest wave of standards (i.e. LOINC, RxNORM, SNOMED CT) coupled with lexicology projects like MeSH & UMLS are allowing for differences in terminology, and disparate systems to be more interoperable using a common medical vocabulary and standard based framework. This allows data from disparate systems to be brought down to its lowest common denominator, be it a result, a test, a procedure, an image or a clinical note. From here, classification can occur to allow seamless and transparent distribution to existing systems.

Imagine sharing medication information, lab results, radiology diagnostic reports, nurse documentation, clinical notes, assessments, allergies and images from all affiliated and non-affiliated sites. Today, by using security laden web-based portals clinicians can access most of their patient's relevant clinical data.

EMR & EHR vendors espouse the unified view, but for many that view is relegated to source data from their own applications. So the greatest challenge is to find the right partner to share clinically relevant data, no matter its enterprise source.

XDS (Cross-Enterprise Document Sharing)

One of the most important advances in proving a standards-based specification to sharing of clinical documents is the work done by Integrating the Healthcare Enterprise (IHE www.ihe.net). The Cross-Enterprise Document Sharing (XDS) IHE Integration Profile facilitates the registration, distribution and access across health enterprises of patient electronic health records. XDS is focused on managing the sharing of documents between any healthcare enterprise, ranging from a private physician office to a clinic to an acute care in-patient facility. The XDS IHE Integration Profile assumes that these enterprises belong to one or more clinical affinity domains. A clinical affinity domain is a group of healthcare enterprises that have agreed to work together using a common set of policies and share a common infrastructure.

Examples of affinity domains include:

  • Community of Care supported by a regional health information organizations (RHIO)in order to serve all patients in a given region.
  • Nationwide EHR
  • Specialized or Disease-oriented Care
    • Cardiology Specialists and an Acute Cardiology Center
      • Oncology network
      • Diabetes network
      • Federation of enterprises
    • A regional federation made up of several local hospitals and healthcare providers
      • Government sponsored facilities (e.g., VA or Military)
  • Insurance Provider Supported Communities

Within a clinical affinity domain, certain common policies and business rules must be defined. They include how patients are identified, consent is obtained, and access is controlled, as well as the format, content, structure, organization and representation of clinical information.

DATA MINING

The benefits of mining clinical data are many but bringing the data together is the hard part.

For example, disease management is a field where there have been multiple articles and many stand alone solutions, and yet deployment is still surprisingly low. The data that is being stored today is often in a variety of locations leaving no real consolidated view to patient findings. Lifestyles and medication compliance can only be utilized when this information has been collected using a PHR (Personal Health Record), and only then can outcomes be determined and the effectiveness of treatment plans, and existing protocols realized.

However: Identifying trends, and providing new innovative services for your patient population makes good business sense.

Therefore, Healthcare IT departments invest with confidence in solutions that make data readily available for aggregation and mining. Better services, intelligent investments in IT go hand in hand.

MULTIPLE PATIENT ID DOMAINS

Unique identification of the patient is crucial to the sharing of personal health information. Accurate matching and linking data through the unique identification of the patient will improve outcomes, support public health efforts and privacy initiatives. An Enterprise Master Patient Index (EMPI) addresses the challenge by utilizing probabilistic-based algorithms to cross-reference patient identifiers, and thereby unifying the management and delivery of patient information across the health network, protecting data privacy and security and provides a crucial foundation for the electronic health record implementations.

REDUCING DUPLICATE ORDERS

An interesting added benefit of data consolidation is the fact that duplicate orders could be reduced. Prevention of duplicate orders saves money; resource time and can also lower the amount of denials.

AFTER CONSOLIDATION

Once you've consolidated your clinical data on to an enterprise data center, the groundwork is now in place to manage the data. Data governance becomes an applicable logic. The next step of course would be dissemination of relevant clinical data thereby enabling multiple systems across your enterprise to use this shared storage as a single logical entity.

The model Agfa HealthCare proposes differs from basic "store and forget" models, in several important ways. First and foremost, no single server "owns" the data. Rather, a distributed, independent intelligent system owns the shared clinical data and manages access between the various disparate systems. Multiple clients (which probably run on different operating system platforms can share concurrent access to clinical data. This is done without compromising the clinical data's integrity.

AN ENTERPRISE DATA CONSOLIDATION APPROACH

Below are the main points that you should consider when taking an integrated approach to data consolidation:

  • Hardware/Software: servers, a functional network infrastructure, disk storage, tape storage, and enabling enterprise storage/archiving and management software. The software provides the ability to manage and distribute the images across the enterprise.
  • Avoid locking into one hardware vendor, and focus on standards
  • Make sure that data protection processes like backups, vaulting, and replication are integrated with your storage system.
  • Consider the importance and relevance of high-availability. With many paths (spokes) to shared clinical data storage, Clustering and failovers become much easier to implement
  • Build your solution with growth in mind; the innovations in imaging require this consideration. Your consolidated solution can grow both in terms of bandwidth and capacity to handle present and future imaging needs
  • Start automating data management immediately. Leveraging your existing knowledge about the clinical data and its usage in active storage helps identify watermarks and even clinical data distribution logic. Knowing that your solution will have to rack data from source through deep permanent archiving of the clinical images will identify risk areas.

The benefits of a clinical data center consolidation include:

  • Improved availability of clinical data; if one server is unavailable, data remains available to other servers. This hub and spoke model offers failovers and secure access to systems that are allowed to access the clinical data.
  • Overall productivity improves in clinical workflow environments; no additional time or logins are necessary transferring data between existing clinical solutions.
  • Network bottlenecks caused by data transfers are eliminated or significantly decreased.
  • Redundant storage is complete; your source systems have their database intact and the enterprise data center is updated real-time. This enterprise data center now is relegated as the exchange tool that makes continuity of care a reality.
  • Simplified data administration is a major benefit of clinical data consolidation. This is made easier by consolidating data into a functional, intelligent file system, specific storage characteristics and clinical data classification can then be assigned to invoke bandwidth and protection requirements, to specific clinically relevant data.

Discuss clinical data consolidation with your local Agfa HealthCare consultant today.