Julia Abrams, Senior Director-Global Solutions and Services Marketing, Laboratory Diagnostics, Siemens Healthineers
Currrent Workflow Management landscape
Within the in-vitro diagnostics (IVD) industry, workflow management is typically associated with all the activities the diagnostics laboratory undertakes to turn patient test orders from the physicians and their corresponding specimen samples into test results. I like to refer to the entire value chain as “from vein to brain”—meaning from the time blood is drawn to the time the reportable result is sent back to the physician.
Within this changing healthcare market, it’s important to consider the entire value chain—from vein to brain—from tube to reportable result.
The workflow consists of three important individual workflows: the flow of the samples, the data flow and the material flow. The laboratory workflow starts with the arrival of the sample tube in the lab and in parallel the data flow starts with the physician’s order of the analytical tests. Lastly there is the flow of material, where reagents—or the substances added to cause chemical reactions, or added to see if reactions occur—and other consumables (quality controls for example) are replenished.
Taking manual steps out of these workflows means reducing errors, decreasing turnaround times and thus, improving clinical outcomes.
Manual workflows can take various forms. They could be related to the physical movement of the test tubes from the patient bedside to the laboratory analyzer. It could involve the workflows related to the validation of the data associated with these orders and results. It also could relate to the workflows associated with physically supplying the lab with the materials needed to keep it running efficiently.
Disruptions that are impacting, and ultimately improving, laboratory workflow include the implementation of automation, the increased use of informatics in the laboratory and the general growth and expansion of IT innovations to support lab operations. Automation—robots and track-based automated conveyer belts—when implemented properly, streamline the movement of tubes to more quickly and efficiently move the tube through the required testing processes. More recently, we see expanded automation capabilities by extending classical automation to all areas of the lab beyond clinical chemistry, immunology, hematology and coagulation into mass spectrometry, specialty testing, and others. The increased use of informatics, or advanced decision making, is shifting decision making from humans to computers through the use of advanced algorithms, rules and calculations to free valuable staff time while maintaining oversight on essential controls. Further, IT innovations such as cloud-based technology and mobile technology are increasing scalability to support growing through more efficient data processing and increased access to information from outside the lab.
Developing a Standardized Process
Our customers demand both—customized solutions that also can support their needs for standardization. Our IT solutions are flexible such that they can be customized to support the needs of the laboratory. Once the solution is customized to meet the lab-specific needs, key performance indicators and local procedures, it can then be replicated (i.e., standardized) to other labs within the same hospital network so the lab is assured their workflows are the same regardless of where the testing occurs.
"The increase in diagnostic testing options and the growing complexity of lab tests are driving the need for clinical decision support"
Standardization also plays a role within the individual lab (independently of it being part of a network). For lab managers it is important that lab operating procedures are being followed no matter if the samples and results are being processed by day or night shift—they must not vary by lab technician. Thus, our customers are looking for IT solutions that support standardization in terms of automating lab operating procedures. We pride ourselves on the fact that no two customer labs are the same, but yet all labs strive for standardization and controlled procedures to support their testing needs. Our IT solutions help them achieve these objectives.
Challenges in Healthcare
Undoubtedly there is an increasing urgency around product security, especially within the last 5-10 years. As with all industries, increasing connectivity brings with it the threat of cyberattacks and malicious software that we’ve seen affecting the Healthcare industry. This is an ongoing challenge that is quickly becoming the “new normal.” Proactive investments in cybersecurity can help prevent these attacks, loss of valued information and even potential patient harm. It is an area of focus we take seriously at Siemens Healthineers. Product security requirements are interwoven into our product development processes and support activities—along with our customer and business requirements—so we can address the needs of our customers as they evolve.
It can be seen that cloud computing will have a permanent impact on Workflow Management within the IVD industry. In our industry, hospital consolidation is a mega-trend impacting the laboratory. This means that five labs that used to serve five hospitals have now consolidated into a single giant lab serving the same patient population and geography. Cloud computing provides the most efficient way to support this consolidation trend and the lab workflows associated with it.
Another trend continues to be around data analytics, with increased capabilities to do advanced business intelligence to identify bottlenecks, measure KPIs and proactively identify bottlenecks in the process. Artificial intelligence and machine learning also will have their deep impact in workflow management, as the internet of things is further evolved in the laboratory environment.
The Future of Workflow Management
A future trend impacting workflow management is the increasing movement towards clinical decision support. The increase in diagnostic testing options and the growing complexity of lab tests are driving the need for clinical decision support. Labs are recognizing this need and incorporating clinical decision support into their workflows. For example, some test results may require a combination of tests. The workflow associated with running these tests can be automated via algorithms and rules to streamline the workflow (e.g., run multiple tests, re-run tests, etc.) to produce the desired test result.
Additionally, clinical decision support can be used to indicate the likelihood or risk for specific disease states and conditions. My advice would be to listen to your customers as they embark on these new trends and try to understand the impact to their customers, and recognize that it might take a few iterations to find the ultimate solution.