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Connecting the Data: Three Steps to Meet Digital Transformation Goals

Posted on July 16, 2018 I Written By

The following is a guest blog post by Gary Palgon, VP Healthcare and Life Sciences Solutions at Liaison Technologies.

A white paper published by the World Economic Forum in 2016 begins with the statement, “Few industries have the potential to be changed so profoundly by digital technology as healthcare, but the challenges facing innovators – from regulatory barriers to difficulties in digitalizing patient data – should not be underestimated.”

That was two years ago, and many of the same challenges still exist as the digital transformation of healthcare continues.

In a recent HIMSS focus group sponsored by Liaison, participants identified their major digital transformation and interoperability goals for the near future as:

  • EMR rollout and integration
  • Population health monitoring and analytics
  • Remote clinical encounters
  • Mobile clinical applications

These goals are not surprising. Although EMRs have been in place in many healthcare organizations for years, the growth of health systems as they add physicians, clinics, hospitals and diagnostic centers represents a growing need to integrate disparate systems. The continual increase in the number of mobile applications and medical devices that can be used to gather information to feed into EMR systems further exacerbates the challenge.

What is surprising is the low percentage of health systems that believe that they are very or somewhat well-prepared to handle these challenges – only 35 percent of the HIMSS/Liaison focus group members identified themselves as well-prepared.

“Chaos” was a word used by focus group participants to describe what happens in a health system when numerous players, overlapping projects, lack of a single coordinator and a tendency to find niche solutions that focus on one need rather than overall organizational needs drive digital transformation projects.

It’s easy to understand the frustration. Too few IT resources and too many needs in the pipeline lead to multiple groups of people working on projects that overlap in goals – sometimes duplicating each other’s efforts – and tax limited staff, budget and infrastructure resources. It was also interesting to see that focus group participants noted that new technologies and changing regulatory requirements keep derailing efforts over multi-year projects.

Throughout all the challenges identified by healthcare organizations, the issue of data integrity is paramount. The addition of new technologies, including mobile and AI-driven analytics, and new sources of information, increases the need to ensure that data is in a format that is accessible to all users and all applications. Otherwise, the full benefits of digital transformation will not be realized.

The lack of universal standards to enable interoperability are being addressed, but until those standards are available, healthcare organizations must evaluate other ways to integrate and harmonize data to make it available to the myriad of users and applications that can benefit from insights provided by the information. Unlocking access to previously unseen data takes resources that many health organizations have in short supply. And the truth is, we’ll never have the perfect standards as they will always continue to change, so there’s no reason to wait.

Infrastructure, however, was not the number one resource identified in the HIMSS focus group as lacking in participants’ interoperability journey. In fact, only 15 percent saw infrastructure as the missing piece, while 30 percent identified IT staffing resources and 45 percent identified the right level of expertise as the most critical needs for their organization.

As all industries focus on digital transformation, competition for expert staff to handle interoperability challenges makes it difficult for healthcare organizations to attract the talent needed. For this reason, 45 percent of healthcare organizations outsource IT data integration and management to address staffing challenges.

Health systems are also evaluating the use of managed services strategies. A managed services solution takes over the day-to-day integration and data management with the right expertise and the manpower to take on complex work and fluctuating project levels. That way in-house staff resources can focus on the innovation and efficiencies that support patient care and operations, while the operating budget covers data management fees – leaving capital dollars available for critical patient care needs.

Removing day-to-day integration responsibilities from in-house staff also provides time to look strategically at the organization’s overall interoperability needs – coordinating efforts in a holistic manner. The ability to implement solutions for current needs with an eye toward future needs future-proofs an organization’s digital investment and helps avoid the “app-trap” – a reliance on narrowly focused applications with bounded data that cannot be accessed by disparate users.

There is no one answer to healthcare’s digital transformation questions, but taking the following three steps can move an organization closer to the goal of meaningful interoperability:

  • Don’t wait for interoperability standards to be developed – find a data integration and management platform that will integrate and harmonize data from disparate sources to make the information available to all users the way they need it and when they needed.
  • Turn to a data management and integration partner who can provide the expertise required to remain up-to-date on all interoperability, security and regulatory compliance requirements and other mandatory capabilities.
  • Approach digital transformation holistically with a coordinated strategy that considers each new application or capability as data gathered for the benefit of the entire organization rather than siloed for use by a narrowly-focused group of users.

The digital transformation of healthcare and the interoperability challenges that must be overcome are not minor issues, nor are they insurmountable. It is only through the sharing of ideas, information about new technologies and best practices that healthcare organizations can maximize the insights provided by data shared across the enterprise.

About Gary Palgon
Gary Palgon is vice president of healthcare and life sciences solutions at Liaison Technologies, a proud sponsor of Healthcare Scene. In this role, Gary leverages more than two decades of product management, sales, and marketing experience to develop and expand Liaison’s data-inspired solutions for the healthcare and life sciences verticals. Gary’s unique blend of expertise bridges the gap between the technical and business aspects of healthcare, data security, and electronic commerce. As a respected thought leader in the healthcare IT industry, Gary has had numerous articles published, is a frequent speaker at conferences, and often serves as a knowledgeable resource for analysts and journalists. Gary holds a Bachelor of Science degree in Computer and Information Sciences from the University of Florida.

Improving Data Outcomes: Just What The Doctor Ordered

Posted on May 8, 2018 I Written By

The following is a guest blog post by Dave Corbin, CEO of HULFT.

Health care has a data problem. Vast quantities are generated but inefficiencies around sharing, retrieval, and integration have acute repercussions in an environment of squeezed budgets and growing patient demands.

The sensitive nature of much of the data being processed is a core issue. Confidential patient information has traditionally encouraged a ‘closed door’ approach to data management and an unease over hyper-accessibility to this information.

Compounding the challenge is the sheer scale and scope of the typical health care environment and myriad of departmental layers. The mix of new and legacy IT systems used for everything from billing records to patient tracking often means deep silos and poor data connections, the accumulative effect of which undermines decision-making. As delays become commonplace, this ongoing battle to coordinate disparate information manifests itself in many different ways in a busy hospital.

Optimizing bed occupancies – a data issue?

One example involves managing bed occupancy, a complex task which needs multiple players to be in the loop when it comes to the latest on a patient’s admission or discharge status. Anecdotal evidence points to a process often informed manually via feedback with competing information. Nurses at the end of their shift may report that a patient is about to be discharged, unaware that a doctor has since requested more tests to be carried out for that patient. As everyone is left waiting for the results from the laboratory, the planned changeover of beds is delayed with many knock-on effects, increasing congestion and costs and frustrating staff and patients in equal measure.

How data is managed becomes a critical factor in tackling the variations that creep into critical processes and resource utilization. In the example above, harnessing predictive modelling and data mining to forecast the number of patient discharges so that the number of beds available for the coming weeks can be estimated more accurately will no doubt become an increasingly mainstream option for the sector.

Predictive analytics is great and all, but first….

Before any of this can happen, health care organizations need a solid foundation of accessible and visible data which is centralized, intuitive, and easy to manage.

Providing a holistic approach to data transfer and integration, data logistics can help deliver security, compliance, and seamless connectivity speeding up the processing of large volumes of sensitive material such as electronic health records – the kind of data that simply cannot be lost. These can ensure the reliable and secure exchange of intelligence with outside health care vendors and partners.

For data outcomes, we’re calling for a new breed of data logistics that’s intuitive and easy to use. Monitoring interfaces which enable anyone with permission to access the network to see what integrations and transfers are running in real time with no requirement for programming or coding are the kind of intervention which opens the data management to a far wider section of an organization.

Collecting data across a network of multiple transfer and integration activities and putting it in a place where people can use, manage and manipulate becomes central to breaking down the barriers that have long compromised efficiencies in the health care sector.

HULFT works with health care organizations of all sizes to establish a strong back-end data infrastructure that make front-end advances possible. Learn how one medical technology pioneer used HULFT to drive operational efficiencies and improve quality assurance in this case study.

Dave Corbin is CEO of HULFT, a comprehensive data logistics platform that allows IT to find, secure, transform and move information at scale. HULFT is a proud sponsor of Health IT Expo, a practical innovation conference organized by Healthcare Scene.  Find out more at hulftinc.com