Fragmented CDS Tech Poses Problems for Healthcare Data Interoperability


According to recent estimates, up to 74 percent of healthcare provider organizations use clinical decision support (CDS) technology.

CDS systems are great for helping physicians arrive at appropriate and timely clinical decisions regarding many aspects of patient care. However, in virtual or remote care settings, most if not all of these systems either don’t integrate at all or don’t do it well enough with other systems.

The earliest clinical decision support systems date back to the 1960s, when pharmacists used automated technology to check patient allergies, research dosages, and check for drug-to-drug interactions.(1) Now, according to recent estimates, up to 74 percent of healthcare provider organizations use clinical decision support (CDS) technology.(2) These systems harness the power of artificial intelligence (AI) to help provide clinicians, staff members, patients, and others with person-specific health information. In New Jersey, a CDS system known as Clover Assistant is taking hold as an invaluable resource for physicians—the platform provides clinicians with patient-specific information that is relevant to the visit, as well as providing actionable insights to help improve long-term outcomes and guide preventative care.(3)

But there is still the problem of fragmentation. Stuart Long, CEO of InfoBionic, a leading digital cardiac health company, says, “CDS systems are great for helping physicians arrive at appropriate and timely clinical decisions regarding many aspects of patient care. However, in virtual or remote care settings, most if not all of these systems either don’t integrate at all or don’t do it well enough with other systems, and some are even difficult to incorporate into existing electronic health records systems. That can’t continue if we’re talking about providing the highest level of person-specific health care.”

Fragmentation of CDS systems in a virtual/remote care environment is a problem faced by healthcare entities across the nation. Beyond the problem of integration between CDS systems themselves, many also don’t easily incorporate into a healthcare entity’s existing electronic health records (EHR). Today, about 55 percent of healthcare provider organizations use multiple CDS systems for their current brick and mortar implementations.(2) Up to 48 percent of providers plan to continue to use multiple systems due to the challenges of standardizing CDS systems and EHRs.(2) Given the lack of full adoption for the hospital/health system side of the equation, widely implementing interoperable CDS systems in a virtual care environment is yet to be seen. As of today, no single platform seems to provide clinicians with all the information they need, regardless of patient status.

That’s not to say that CDS systems don’t have benefits. Such tools promote patient safety and better outcomes by providing:

  • Computerized alerts and reminders to care providers and patients
  • Clinical guidelines
  • Condition-specific order sets
  • Focused patient data reports and summaries
  • Documentation templates
  • Diagnostic support
  • Contextually relevant reference information(4)

Virtual care introduces a variety of new challenges to using CDS systems. Users may not be comfortable using the technology, data integration may be interrupted if transmission signal strength declines, and users may rely too heavily on such systems to arrive at a diagnosis. It’s important to keep in mind that all CDS systems aren’t meant to replace the knowledge and expertise of formally trained physicians; instead, these technologies should only augment clinical experience to help clinicians arrive at the best diagnostic and treatment decisions possible.

CDS systems are also different from “telehealth”, or the provision of healthcare services using remote communication technologies. CDS technologies are composed of various AIs which use algorithms created from evidence-based practices and the most current research possible. As the technology continues to improve, AI will become even better at identifying relevant information in near real-time while filtering out irrelevant data that might incorrectly inform clinical decisions.

In the field of cardiology, AI is already improving patient outcomes. A recent study found that AI eliminated nearly two-thirds of false positives in remote monitoring for atrial fibrillation.(5) As remote patient monitoring technologies, such as InfoBionic’s MoMe® Kardia continue to evolve, they can be more easily integrated with AI systems to help create reliable platforms with accurate data collection. This, in turn, will help allow for greater consistency in patient treatment.

While different types of CDS systems may work best for different processes of care in various settings, the full integration of these systems, remote patient monitoring technologies, and electronic health records is key to providing care tailored to individual patients. Intercommunication will be essential for achieving the best patient care outcomes—but AI systems must advance to the point where they can manage multiple data sources and integrate that information into a single point of reference.

Long says, “We’re making progress toward our goal of complete integration, but we’re not there yet. It’s going to take time and dedication to figure out how we can incorporate all patient data points across all patient care platforms to provide one comprehensive resource to support clinician decisions.”

About InfoBionic:

InfoBionic is a digital health company transforming the efficiency and economics of ambulatory remote patient monitoring processes by optimizing clinical and real-world utility for the users that need it most – physicians and their patients. The Massachusetts-based team of seasoned entrepreneurs have had successful careers in healthcare, IT, medical devices and mobile technology, and bring specific expertise in remote monitoring and cardiology. They have seen first-hand the complexities of traditional cardiac arrhythmia detection and monitoring processes and designed the transformative MoMe® Kardia platform to remove the roadblocks hindering faster, more effective diagnosis and decision-making. Frost & Sullivan bestowed the 2019 North American Remote Cardiac Monitoring Technology Leadership Award upon InfoBionic.

Sources

1. Wasylewicz. “Clinical Decision Support Systems.” Fundamentals of Clinical Data Science [Internet]., U.S. National Library of Medicine, 22 Dec. 2018, ncbi.nlm.nih.gov/books/NBK543516/#:~:

2. Siwicki, Bill. “New Study Identifies Top 11 Clinical Decision Support Vendors.” Healthcare IT News, 10 Oct. 2018, healthcareitnews.com/news/new-study-identifies-top-11-clinical-decision-support-vendors.

3. Clover Assistant, cloverassistant.com/.

4. “Clinical Decision Support.” HealthIT.gov, 10 Apr. 2018, healthit.gov/topic/safety/clinical-decision-support.

5. Hmpgloballearningnetwork.com, hmpgloballearningnetwork.com/site/EpLab/new-study-published-validates-cardiologs-ai-eliminates-nearly-two-thirds-false-positives-remote-monitoring-atrial-fibrillation.

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