Major shifts within the U.S. healthcare system present new challenges and opportunities for clinical labs and other diagnostic service providers. Changes to healthcare ground rules mandated by payers and the federal government are driving a shift towards value-based care, resulting in changes to the business models under which clinical labs and other diagnostic service providers operate.

In order to negotiate favorable contracts and participate successfully in value-based healthcare organizations, labs must demonstrate their ability to contribute to the business objectives of those organizations.

The data on orders and results collected by diagnostic labs represents a tremendous source of potential value to help value-based healthcare organizations meet their goals of delivering quality care while controlling costs. However, the ability to realize this potential depends on the type, quality and timing of information provided by the IT systems used for electronic lab ordering and results by lab vendors and their clinician customers.

This discussion outlines key capabilities of EHRs (electronic health records system) and lab outreach systems needed for labs to participate successfully in the shift towards value-based healthcare systems.

Understanding the Business Context

Most labs find themselves engaged in multiple contract arrangements with provider organizations and payers. Each of these arrangements requires somewhat different information strategies to assure success.

• Lab Services for ACOs: Whether a lab competes to provide services to an ACO or other value-based organization or the ACO has been formed by a lab’s parent organization, the lab must demonstrate its value in meeting the ACO’s economic and care quality objectives. This goes beyond traditional assessment of testing costs by requiring that the lab contribute to the care program for each patient.
• Narrow Care Networks: Payers will continue to drive toward limiting choice in selection of labs for members within their plans, and labs must compete aggressively to be selected as a preferred lab by these payers. Payers require price concessions and increasingly demand that labs assist providers in measuring and controlling test utilization.
• Traditional Fee-For-Service: Despite the move to value-based models, most labs will continue to provide some fee-for-service lab testing, though the mix of tests is likely to change over time. Low-cost standardized tests will increasingly be provided by non-traditional test facilities such as physician office labs and retail drugstores, while specialty labs will continue to focus on high-end testing.

Winning Information Strategies for Labs

Provide Electronic Orders with Decision Support

Even with the massive shift to EHRs in ambulatory practices, most lab tests are still ordered on paper. Providers often overlook the value of a complete and consistent electronic lab order and thus have not demanded this capability from their EHR vendors. Interoperability challenges with different EHRs have kept interface costs high, especially for bidirectional interfaces that can transmit electronic orders to the lab.

Efficient and easy-to-use lab ordering applications are rare, and those provided by LIS vendors have seen limited adoption in unaffiliated ambulatory practices. Physician adoption represents a major challenge for electronic ordering applications. Smooth integration of electronic ordering into existing EHR workflows provides a significant point of leverage in increasing the value of electronic ordering solutions.

Labs that are leading the way in implementing electronic lab orders with a variety of EHR systems often partner with outreach vendors such as Liaison Healthcare, whose ordering applications can operate as standalone orders/results portals or integrate smoothly with EHRs using a variety of approaches: HL7 messages, demographics-only integration or web service integration.

To meet ACO care quality objectives, electronic ordering applications must help ensure that unnecessary tests are avoided, evidence-based testing protocols are followed, and important routine tests for chronic conditions are not missed. To be effective, these decision-support capabilities must be provided at the point of order.

Additional order management functions such as the following provide significant benefits to labs and providers as well:

• Support for standing and future orders, with the ability to automatically release orders to the lab at the appropriate time
• Improved patient matching of results with the EHR, greatly reducing lab result interface errors
• Medical necessity checking and conformance with other payer-specific rules to assure reimbursement
• Support for both provider-collected specimen workflows and patient service center workflows
• Order management reports, such as open orders and ordering patterns by test and by provider
• Specimen management reports for phlebotomists and couriers

Provide Flexible and Timely Access to Lab Results

The highest priority for the lab’s provider customers is to automate delivery of lab results into the practice EHR, taking into account the great variation among EHRs in their support for HL7 formats, patient and order matching requirements, and handling of discrete data.

Outreach solutions that focus only on HL7 delivery to the EHR are generally limited in their ability to support the flexible access providers need for viewing and sharing lab reports. With the increase in team-based care of ACO and PCMH models, more flexible lab result access is required. Beyond delivery of results to the EHR, labs need to support remote provider access and information sharing with other providers and the patient.

Web access to lab reports is an important first step for providers on rounds, in multiple locations or after hours. Providers increasingly use mobile devices such as smartphones to receive alerts when lab reports return so they can follow up quickly with their staff or the patient. Providers also need to be able to share lab reports with other members of the care team and provide simple, visual lab reports for the patient.

Retain Patient Health Context when Ordering

A key advantage of orders placed from the practice EHR is that patient health context is available to the ordering provider at the point of order. However, with the increase in team-based care as well as the involvement of specialists in treating chronic conditions, information within any single EHR is likely to be incomplete. For example, tests ordered by other providers or medications not in the ordering provider’s medication list can affect the ability to choose the right set of tests.

To provide a more complete test history, some labs aggregate test information across multiple practices for use by the ordering provider, but this still leaves gaps where tests may have been ordered from other labs. Payers generally have a more complete lab test history, but this information is not generally available to the ordering provider, and test results are typically not available from the payer.

If the providers in the patient’s care team are in an affiliated organization such as an ACO or CIN (Clinically Integrated Network), information can be shared among practices and presented to the ordering provider at the time of order, if the lab ordering application has the appropriate interfaces. Some ordering applications can use an HIE or other healthcare data repository to fill in the information gaps about the patient’s condition. To provide this capability, labs should select ordering applications that can provide a rich patient context at the point of order.

Engage the Patient

Changes to CLIA and HIPAA guidelines in 2014 now require that labs provide patients with their lab reports on request. However, labs are not required to interpret this information in the context of the patient’s condition and treatment. Lab reports contain mandated testing information and describe results in terms meaningful to providers, but patients often find these reports confusing or misleading.

A lab that helps engage the patients in their care is more valuable to an ACO. An informed patient is more likely to conform to their treatment plan and stay healthy, limiting their costs to the healthcare organization.

A better approach is for labs to select provider outreach applications that include patient-friendly lab reports, which present important information in terms that patients can understand and act upon. These applications, such as EMR-Link from Liaison Healthcare, can deliver the lab report on paper, through a variety of patient portals and PHRs, and via mobile devices.

Improve Ordering Patterns

The set of available diagnostic tests and guidelines around the best tests for a given condition is continually changing. Value-based care and good medical practice require that tests be chosen for diagnostic effectiveness as well as cost.

Labs can provide important information to providers and other organizations on how tests are being utilized and how ordering patterns can be improved. Practices and ACOs can also put themselves in a stronger position in negotiating payer agreements by showing that they are proactive in helping to control testing costs.

Labs can assist ACOs and practices with reports that show tests ordered by provider and by patient condition, and by providing timely information about new and obsolete tests and changes to testing recommendations. This information should be available online and in real time to the provider organization so that it can be used effectively in decision-making.

Information Technology Requirements

Addressing the variety of requirements across the various business contexts in which the lab participates is difficult for traditional lab outreach vendors, who typically focus on order entry applications and HL7 lab results delivery. Emerging lab network providers that can address this range of requirements typically deploy cloud-based solutions to meet the changing connectivity and application access needs of labs. This approach also greatly simplifies the connectivity management and infrastructure requirements for the lab, allowing them to focus on their core business requirements.

For success in today’s healthcare business climate, labs should evaluate their customer outreach solutions against requirements such as these:

• The lab ordering application’s ability to fit easily into a variety of practice systems and workflows, including EHRs with differing capabilities, different locations of specimen collection and evolving payer requirements for test justification, order splitting, and billing
• The ability to manage and share lab results data by presenting reports in different formats (including patient-oriented formats), patient test history and delivery to mobile devices as well as to the practice EHR
• The ability to connect to patient data repositories such as HIEs, ACO management systems and clinical data repositories to present a broader picture of patient health at the point of order
• The ability to conform to evolving payer requirements such as Medicare and non-Medicare medical necessity checking, as well as complex clinical appropriateness checking now being pilot tested by lab benefit systems (LBS)
• The ability to report on practice ordering patterns, not just at the level of utilization of different tests, but also for patients with specific conditions, ordering patterns of different providers and the ability to meet ACO value-based care goals
• The ability to provide guidance in selecting tests, including the most up-to-date evidence-based guidelines for a variety of chronic conditions

Conclusion

By carefully considering the requirements of the information technology systems used to handle lab ordering and results data, labs can enhance the value they offer to healthcare organizations by giving those organizations the data they need to meet cost and quality objectives. The ability to add value in these ways offers a clear differentiator that helps labs survive and thrive under a market-wide shift towards value-based care.

While admittedly being on the extreme ends of the scale, these numbers are within reach of the average project of switching from paper-based invoicing processes to electronic invoicing. Thus, it’s no wonder that e-invoicing is growing globally at a double digit growth rate, and many and more organizations – companies and government entities alike – are jumping on the band wagon. However, the overall adoption rates of e-invoicing may still seem surprisingly low considering the benefits that are there for the taking. Zooming in on the subject provides insight as to why this is.

Related: The Future of e-Invoicing – What’s Driving It?

A closer look at the overall numbers reveals an interesting array of different market conditions and varying drivers for market growth around the world. For instance, just like we have here in Northern Europe, a high percentage of all invoicing is electronic in South America. The difference is that in South America most governments mandate the use of electronic invoicing for businesses that meet certain criteria in order to enforce adherence to tax legislation, whereas in Northern Europe the primary driver for e-invoicing is achieving greater efficiency and cost savings through process automation and digitalization.

In addition to the market drivers, the ways of doing e-invoicing and the regulations governing it differ across markets. This causes issues especially for multinational companies that need to adhere to the local regulations in all countries they operate in. With many countries figuring out their own approaches to governing how e-invoicing should be done and coming up with legislation to guide and even force behavior, managing e-invoicing across multiple countries is a true challenge.

Regardless of the difficulties, the benefits of e-invoicing are clear and the general development is taking us towards a world where paper invoices are mostly a thing of the past. In order to craft a strategy for keeping up with this development it’s important to understand:

• The past development and why different countries have ended up where they are today
• The current environment and what to consider when utilizing e-invoicing
• What developments are taking place now and what are the most likely paths that the markets are going to follow in the future

As an e-invoice operator, Liaison closely follows the market developments and helps companies in complying with the developing regulations. We are sharing our views on these matters in two upcoming webinars, the first of which discusses the past, present and the future of e-invoicing. You can check out the details and register for the webinar here.

1. Big data meets reality

The excitement around the power of big data has reached a fever pitch. 2015 will be the year when the promise of big data slams into the reality that heavy lifting will be required to make it widely successful. While some may panic at this development, it is really a natural phase in the maturing of any major shift in the information technology paradigm. The visually stunning approaches to intuitively representing and displaying insights gleaned from information will remain—as will the advanced frameworks for processing both structured and unstructured data at scale. The third critical element of success—the ability to effectively integrate, aggregate, and semantically harmonize the information from numerous disparate sources—will rise to the fore in 2015, placing a huge focus on the value of data integration and management.

2. The shift from application-centric to data-centric architectures accelerates

This shift liberates data from the confines of stifling, monolithic applications and the constrained, structured data models which have for years been frustrating users’ attempts to get information as they require it. This new data-centric approach will allow the combination of dissimilar information that was never before viewed as possible to be combined. Enabled by the architectural assumptions (and vendor created realities from AWS, Google, etc.) of unlimited, near free compute and storage, it will lead to creative thinking and exploration in this area —big data as currently envisioned being only the start. This emerging shift is the equivalent (in Internet terms) of ubiquitous, unlimited, high-speed bandwidth in the 1990’s when dial up was still the norm and coverage areas for the Internet were very limited. Some will dare to dream of a data (versus connectivity) based Internet-like utility platform that could provide a revolutionary change not unlike the Internet itself.

3. The strengthening of “platforms” to execute common application services, as the monolithic approach of “applications of record” proves too rigid to keep pace

This is the business equivalent of the Apple IOS and the App Store, and should over time accelerate its threat to monolithic application stacks. Examples of this include key functions of the traditional ERP systems, such as CRM, eProcurement, HR moving to the cloud. This shift should roll out in stages by vertical industry with some industries moving quicker than others. Industries with a real burning platform for change, such as healthcare, will lead.

4. The rise of a trend toward unified data integration and data management platform services

Increasing data variety, both in type and location, as a result of this distributed application innovation will not only enable new business possibilities, such as big data, but also dramatically increase overall IT complexity fueling a trend toward unified/consolidated integration and data management platform services. This is the most promising solution approach, as the alternative of using point integration solutions in this highly fluid emerging environment of distributed data and perishable/transient applications would lead to something that might be called “ChaosNet.”

5. The nature of cloud services will drive providers to specialize in one of two symbiotic camps

The very nature of cloud services should drive provider self selection and optimization determining “who does what” in the ecosystem. With the cloud service domain being a hot bed for innovation and rapidly being fine-tuned to differentiate clusters of specific customer use cases, it is unlike the broad-based applications and mission critical integration and data management platforms of traditional IT. Data management and integration platforms are designed to connect anything to anything and combine, manage, and expose data from the vast array of emerging applications, regardless of the supplier, and in many cases the use for this data is not yet defined. These symbiotic solutions, including applications and integration and data management, must live separate lives but are highly co-dependent. Without integration and data, applications are useless and without application services to consume or produce data, there is no need for integration or data management services. In the end, companies that build and operate cloud applications need to get out of the integration and data management business or lose relevance as they struggle to meet the conflicting requirements of two diverging customer sets.

While apps and processes are the enablers for business users, enterprise data are the assets that drive operational performance. Next to user experience, extracting value from its data should be a strategic missive for all organizations. It is integral to achieving return on investment (ROI) and risk management objectives, strengthening competitiveness and meeting GRC (governance, regulatory, compliance) requirements. The more data-centric a company is the more likely it is to outperform its peer group on financial metrics and market valuation.

Monolithic applications are becoming less relevant to the enterprise. Agile DevOps practices and HTML5 for cross-platform development continue to fuel rapid growth in cloud and mobile applications. While these apps can be launched faster and updated continuously, they increase complexity due to the many disparate components that comprise composite apps. And with more apps, come more sources of data to integrate and manage.

Traditional, on-premises data integration systems are straining under the weight of unabated data growth – from both legacy systems and big data sources. Legacy providers with bolted-on cloud capabilities often make it harder – not easier – for enterprise IT to integrate and manage the unstructured data alongside their conventional structured data.

Meanwhile, users are demanding faster access to more data sources. IT teams face increasing pressure to provide the data sets that business users need in a timely fashion. And it is more likely that these data sets draw on data from OLTP and OLAP systems in combination with newer NoSQL or Hadoop-based formats.

Big data challenges traditional data integration and business intelligence (BI) systems. Capturing and analyzing social media, Web server logs and other forms of machine data add another layer of complexity to the BI data integration process. And while a data lake proposes to help with data management issues, it does not address the potential for new or expanded silos that cloud and mobile apps threaten to perpetuate.

Decision-making is either stalled or flawed, as insufficient – or worse – inaccurate data impedes model building and validation. Time-to-value suffers. Outcomes are sub-optimal at best, and potentially catastrophic in the most latency-sensitive environments, such as high-frequency trading desks or hospital emergency rooms.

It’s Time for Next-Generation Data Integration and Management

More data-driven organizations have recognized the need to speed the availability of data that end-users need for analysis and decision-making. Next-generation BI tools, with easy-to-use data visualization capabilities are becoming more pervasive. By pushing these tools further down into the organization, management hopes to improve business operations at the point of decision – usually where the customer is.

A born-in-the-cloud data integration and management platform is better suited to handle the melding of data from newer composite apps and legacy systems. Such a platform is more scalable and flexible to bridge existing enterprise infrastructure to modern development practices and platforms.

This is not simply an iPaaS platform that facilitates the integration of data among and between clouds – whether private, public or hybrid. While incorporating that functionality, a next-gen data integration platform with data management capabilities not only provides orchestration and adapters for a much broader array of apps and data sources. It also provides a stack to manage the data these different sources generate.

A next-generation data platform that combines integration and management enables IT to improve its service levels to the business. It facilitates the adoption of cloud and mobile apps, enabling the organization to transition to consuming technology as a service. Users get faster access to the data they need, lifting productivity and improving decision outcomes. Customer service and satisfaction rises as a result of more engaged employees.

Unified data integration and data management helps enterprises improve business processes and become more responsive to end-user requirements. Customers gain agility and flexibility using an extensible, high-performance service-oriented platform built on the latest state-of-the-art infrastructure and tools that easily integrates all data sources. By focusing on the data that drives operating metrics, IT can also more closely align with business users to ensure data governance best practices and more efficient application development and service delivery. These are the characteristics of leading data-driven enterprises.

For years, IT professionals have put monolithic applications at the center of their IT solar systems. And just as orbiting planets are bound by the gravitational pull of their sun, application-centric organizations are bound by the constraints of their enterprise application. For example, data integration, data analysis, and even data itself (as an artifact) is largely determined by the applications at play.

In an application-centric IT environment:

• Data is locked up in applications and hard to extract
• Applications drive data models and data integration
• Insights and analysis are artificially constrained
• Specific use cases or functions drive application logic
• Data enrichment must be accomplished through application enhancement
• Applications can’t be easily changed

As data increasingly becomes a business’ most valuable asset, the constraints that application-centric IT models inherently put on data are becoming… constraining. Organizations are realizing that data, not applications, must drive business strategy.

To accommodate this, some businesses have begun realigning their IT architecture to make data the ‘star’ around which everything revolves. Applications, then, become the new planets, existing only because the data—or more precisely, the needs of the data—allow them to exist. This is commonly referred to as a data-centric or information-centric IT model.

In a data-centric IT environment:

• A virtual data factory (ETL, ESB, MDM, registries, etc.) lives at the center
• Many smaller applications take the place of a single enterprise application
• Valuable data can come from any source
• New data sources are assimilated quickly and effectively
• Data models are abstracted from source applications and metadata is the ‘bonding agent’
• Data drives the interactions between applications, not vice versa
• Application functionality is dynamic and transient

If you’re intrigued by this topic, stay tuned for my next post where I’ll discuss how to begin the voyage from an application-centric to a data-centric IT solar system.

In addition, Liaison has a webinar coming up on this topic that I invite you to attend:

• January 14: Put Your Data in the Driver’s Seat with a Data-Centric IT Approach

Besides being home to both the first (and primary) treatment center for Ebola and the Center for Disease Control, Georgia boasts the most health IT companies of any state, according to Technology Association of Georgia and the Atlanta Chamber of Commerce. To prove it, over 1200 people have come together at this year’s Health IT Leadership Summit in Atlanta to network and hear about the latest developments in healthcare challenges and technology solutions.

Day one of the summit brought some interesting insights from two dynamic speakers:

Julie Hollberg, CMIO at Emory Healthcare, kicked off the annual summit talking about how Emory Healthcare is tackling Ebola using EMRs and dashboards to record and evaluate information about patients—first in the emergency department and later in the ambulatory setting. In truth, she mentioned that the process is the same one used for other viruses, but the key to success is having access to the right healthcare information to properly screen patients and make proper treatment decisions.

Jonathan Bush, CEO of athenahealth, spoke on the topic of his new book, titled Where Does It Hurt? An Entrepreneur’s Guide to Fixing Health Care. The premise of the book is that healthcare in the U.S. Is inefficient, complex and, all too often, heartless. Jonathan believes that healthcare is ripe for entrepreneurship and disruptive innovation. If you’ve ever seen him speak, you know he’s humorous, but also realistic. He poked fun at Gartner’s Magic Quadrant by defining Upper Right Quadrant Syndrome (URQS) as an ailment that causes companies in the top right leadership quadrant to move into a “protect and defend” mode. He contrasted this with the “compete and innovate” mode of start-ups and smaller companies in the bottom left quadrant that, he believes, are driving the disruptive technologies needed by the healthcare industry to improve patient outcomes.

Georgia’s not the only place where health IT is vibrant, but it sure is nice to know that Liaison’s hometown is where many companies are making a big difference, both in the U.S. and globally.

Come check out Georgia health IT and see how we’re making a difference.

Until next time,

Gary

Extracting more value from data assets is integral to successful strategy execution. This is all the more important as the sheer volume and complexity of big data challenges traditional practices for discovering, integrating, managing and governing data.

In the age of big data, a data cloud services broker (CSB), such as Liaison Technologies, that unifies data integration and data management can be of great value in helping organizations harness the power of all their data assets. The CSB allows enterprises to expand the scope of integration projects and manage larger data sets while realizing faster time to value.

Enterprises can use the CSB’s infrastructure to scale with greater flexibility as their data volumes and formats continue to expand. The CSB assumes the capex burden of assuring service level agreements (SLAs), as well as the responsibility for maintenance and upgrades. The CSB also integrates seamlessly with diverse architectures and technologies, from data marts, data warehouse appliances and in-memory systems, to relational and NoSQL databases, and Hadoop data lakes.

A unified platform helps streamline the complexity of matching, cleaning and preparing all data – including big data – for business intelligence (BI) applications. Tools and processes maintain a high quality, consistent set of master data to provide a common point of reference. This is also known as the golden record or file or profile. Data cleansing tools and a specialized matching engine helps find and fix data quality issues. Versions and hierarchies are maintained to ensure that data remains in sync at all times.

Agile enterprise-class data integration helps overcome the challenges posed by data silos across the organization. A registry of all corporate data sources maps data to its location, applications and owners to assure adherence with formal data governance and compliance practices. In this capacity, the platform can help identify, assess and manage the many different kinds of risks that lurk within different data silos. It supports the data governance council and data stewards to assure that the master data is properly maintained, what it contains, how long it is retained and how changes are authorized and audited.

Better Data for Better Outcomes

Centralized management extends data governance throughout the organization. It facilitates best practices for all application and data constituents – from data entry to analysis. End-users gain greater confidence that they can trust the quality of the data they are working with.

Higher quality data allows end-users to focus on business-critical data elements, such as customer names and addresses. Unifying data integration and data management enables them to more easily identify data sources and monitor interactions between applications that use the data. The context end-users gain shortens the path to finding patterns and relationships during data analysis. The result is more actionable insights for better informed decisions that can be made faster.

The CSB platform also allows users to perform trends analysis on larger, more disparate data sets covering longer periods of time. Data is integrated from multiple sources, harmonized in a consistent state and then managed to end-user requirements. Then unified approach allows users to more easily run data sets through different scenarios and strategies.

While the platform can handle large volumes of data in motion, such as streaming and social media, more of the data remains at rest. Unifying data integration with data management reduces the need to move data from one infrastructure platform to another. Less data has to traverse the WAN, which may be bandwidth challenged. Data and systems can be more easily monitored to alert for performance issues and assure user experience.

Every organization seeks to improve the quality of its decision outcomes to build customer loyalty, strengthen competitiveness and achieve ROI and risk management objectives. However, ensuring that its data is trustworthy and protected is made exponentially more difficult with big data. Delivering a single, consistent set of data policies and processes improves data analysis and results in actionable business intelligence.

A strong data governance program that promotes collaboration and input from both IT and business users, coupled with a unified CSB platform that understands and provides context to diverse data sets can be the foundation for data strategy. Through unified data integration and data management enterprises can successfully support the operational and analytics systems that drive the business. They can realize lower costs and increased operational efficiencies, improve agility and business processes, and more closely align IT with business users and corporate objectives.

Manish Gupta is Chief Marketing Officer of Liaison Technologies, a leading global Data Cloud Services Broker.