Robbie Hughes, Chief Executive Officer, Lumeon

Medicine is a science, but the actual practice of medicine across the care continuum is often less consistent and less quantifiable than patients and practitioners would like or expect. Some of this is because treating people is more complex than a standardized production process such as manufacturing or repairing a car. But much of the variance in treatment is because the delivery of healthcare is managed on an ad-hoc and manual basis, even as discrete steps in the process are automated. The result is reduced visibility and ongoing difficulty in measuring both individual patient outcomes and improvements in population health.

A tremendous amount of time and money has been spent automating individual steps in the healthcare delivery process, including not only Electronic Medical Records (EMR) systems, but also scheduling systems, billing systems, and even patient portals. In most cases, multiple software products have been deployed in a single hospital, practice or surgery center, each automating one or more of a provider’s previously manual processes. However, the automation of separate silos leaves process gaps between the different software systems, gaps which are typically bridged using people and paper.

Liora Guy-David, Ph.D., Vice President of Data, medCPU

As long as the healthcare industry lacks true interoperability among dissimilar systems, clinicians will have incomplete patient information at the point of care. This includes gaps over time, as when a clinician is unaware of imaging tests already completed, and gaps across care team members who record documentation in separate systems. Both types of gaps can compromise patient safety.

While we don’t typically think of gap-closing as being a primary clinical decision support (CDS) function, CDS systems do exactly that. Its success in informing decisions depends largely on the ability to analyze information from multiple systems, closing gaps in real-time. As a result, CDS is emerging as an essential tool for improving quality of care.

Decision-making support built with a more complete view of the patient

CDS systems run on top of EMRs, analyzing documentation as it is being entered and issuing alerts in EMR windows when conditions indicate the possibility of a medical error or compromised patient safety. This is often a matter of giving clinicians information of which they were unaware.

To fully inform alerts, advanced CDS systems supplement the structured data in EMRs and pull information retrieved from other systems such as those in labs and imaging departments. CDS leverages its comprehensive patient view by applying rules-based analysis regarding diagnoses and courses of care. By augmenting a physicians’ expertise with real-time information retrieval and gap-closing, CDS systems play a key role in promoting patient safety.

Ami Mayo M.D., Chairman of medCPU’s medical department

A major shortcoming of traditional clinical decision support (CDS) systems is that they operate on highly incomplete patient data, which sets the foundation of the usefulness of the tool. With incomplete data – prompts down the line are guaranteed to be inaccurate. Besides having access to all data, precision of this information is imperative for a CDS system to enhance care delivery and patient outcomes.

Traditional CDS systems can read and utilize only structured data entries in electronic medical records (EMRs) and ancillary systems. However, this portion of the patient’s clinical profile, represents somewhere between 30 and 40 percent of all medical information. If the system doesn’t have complete and accurate data, it’s going to error. Data and data comprehension is key.

Capturing all data and precise comprehension of this information requires the CDS system to function as closely as possible to how a physician thinks. Clinicians communicate patient data primarily through narrative reports, follow-up notes, and summaries of CT scans, X-rays and other imaging reports. In general, dictation, turned later in to free text notes, is how a significant data portion is entered into EMRs.

Approximately, 50 to 70 percent of data in healthcare, if not more, resides in non-retrievable, unusable information embedded in free text communication. This is an enormous amount of vital data that traditional systems simply can’t process because they don’t have the “intelligence”.  Seeing only a small portion of the total clinical picture makes traditional CDS systems prone to error.

Andy Aroditis, Founder, Chief Executive Officer, NextGate

Few things are as simultaneously fascinating and disturbing as going onto a social media application such as Facebook or LinkedIn and seeing it present a suggested list of potential connections. It can be disconcerting to think that a bunch of algorithms could so accurately predict that out of billions of users these are actually people you might consider a friend. Or that because you liked “Whiplash” you might be interested in these other videos that other fans of that movie enjoyed.

Yet the same core social media technology that seems to understand the most intimate details about your childhood, current relationships and other interests holds great promise for transforming healthcare by finally showing how all the data are related. 

It’s called the graph database. Designed specifically to interpret relationships between different sets of data, the graph database is the foundational technology that allows social media applications, as well as companies such as Amazon, to build sophisticated social networks around each account owner. For instance, it’s what enables us to look at our friends’ friends and navigate through their interests and connections.

Capsule Technologie, a provider of medical device integration solutions, announced it has signed a reseller agreement with InterSystems, a provider of software for connected healthcare. Under the terms of the agreement, InterSystems will be authorized to resell Capsule’s SmartLinx Medical Device Information System (MDIS). The two companies’ partnership stems from a shared vision of connected care and strong global market presence.

Capsule’s SmartLinx MDIS is healthcare’s first integrated system to enable hospitals and healthcare delivery organizations to increase efficiency and help improve patient care delivery through the capture of medical device data and context directly at the point of care. The system consolidates clinical workflow and puts data to work by integrating it with both electronic medical records and intelligent systems to drive informed clinical and operational decisions. Connectivity and data capture are achieved through integrated hardware and/or software solutions that meet the requirements of virtually any healthcare environment.

Susan deCathelineau, Vice President of Healthcare Sales and Service, Hyland, creator of OnBase

Dr. John Halamka recently discussed interoperability in his blog, where he said, “It’s time to step back, define our requirements, examine our current state, and then focus on closing any gaps we find.”

I agree with Dr. Halamka.

Interoperability can be daunting without clear definitions and patient-centric goals. However, we can easily identify some gaps and work to solve them now.

Imagine a world where patients enter the waiting room and their consent forms, identification and insurance cards, previous test results, X-rays, MRIs and any other relevant content, were already accessible to the clinicians and staff. It would be a revolutionary turn of events considering healthcare organizations are closely looking at patient satisfaction ratings.