
In the world of laboratory management, LIS and LIMS represent distinct yet converging approaches, each grappling with common challenges like Management, Methods, and Matter handling. While LIS emphasizes patient-centric care, LIMS prioritizes productivity and data processing. However, both share a common goal: saving lives. Integration of these approaches is essential for navigating the complexities of modern healthcare effectively.
In good old Europe, laboratory systems are called LIS, while in the USA they are almost always called LIMS. One might think this is a simple regional linguistic tendency, like British “colour” to American “color,” but in fact the explanation goes much deeper.
This difference in names does not reflect regional dialect or even the current state of affairs as much as it does the subject’s history.
Once upon a time, LIS and LIMS were very different.
There were two “sects” that saw the world differently. In one frame of reference, the patient was the focus. That system collected information for making the right decision about treatment. In the other frame, the patient was not present. Everything revolved around a test tube of biomaterial that needed to be processed as efficiently and qualitatively as possible.
After more than fifty years, these “sects” have ceased to be irreconcilable opponents. Approaches have converged, which has brought LIS and LIMS closer together. Both systems are now patient centered and strive to improve laboratory efficiency.
But the internal, metaphysical contradiction between these camps remains.
If the M stands for Management, then what should we manage first?
Managing the patient’s well-being is complicated for a lab. The reasons are numerous.
Tests are called and ordered differently in different systems. Sometimes the clinician even has to go to the lab’s website to fully understand what they will get when they order a test. Labs have different analyzers and options: even a CBC can have anywhere from eighteen to several dozen parameters. That gets confusing.
What is the clinician’s goal when he orders a test? He contemplates how he will interpret the result and how his treatment tactics will change based on it. However, he does not share his hypothesis with the lab. Why is the physician ordering this test in particular? Could it be some other test? If the lab knew the clinician’s goal, it could help them choose the test from the list more precisely. Perhaps there are versions of the test with different sensitivity and specificity, but which one to choose for a particular patient?
The only way to solve this problem is to create a profile of tests for a specific group of patients and order them from the same laboratory. But that requires the clinician to know the ins and outs of one particular lab.. What if the lab updates its technology or the clinician changes labs? Then tests may be ordered that not only don’t help the patient but implicitly mislead the clinician.
Most errors (60-80%) occur in the preanalytical phase, especially before the specimen reaches the laboratory. Patient preparation, biomaterial collection, labeling, shipping, and delivery to the lab – errors are abound in all of these steps. Many believe that clinicians are responsible and that the solutions should reside in the EMRs they use. But it may well be that a separate system or LIS module that automates part of the preanalytical step would save the day. Specimen collection, for example, often takes place in the lab. Good software could help you navigate around these potential pitfalls.
The nature of information in the lab report form has rapidly evolved through the years. The earliest lab reports essentially amounted to, “Take this pill and don’t ask why”. The only person who could make heads or tails of the report was the doctor. Now the medical community has recognized the patient’s right to information about their personal health and to use it as they see fit. Instead of one person making use of this information (the clinician), we now have at least two (the clinician and the patient).
Can we provide them with the same data in different ways?
On the one hand, no: if the information is different, it means we have misled one of them.
On the other hand, the doctor understands more than the patient.
Do we need to cut the crust off the report so the patient can easily digest it? How do we present the information to the doctor in a way that can be quickly processed?
Different markets have different answers. In India, for example, the information is often presented to the patient in graphical form. Elsewhere, some services transcribe lab tests for patients. Recently, AI has been involved in deciphering results. Sometimes patients themselves try to ask the GPT about their situation, but they either cannot make the correct request,the GPT guy is not smart enough to cure diseases, or more than likely both are true. Such initiatives do not help to increase compliance.
However, most LIS vendors include both a clinician and a patient portal. The extent to which a lab can interfere with the interpretation of these tests is debatable. Dialogue is needed between all parties, and preferably not just a conversation between two deaf people.
The LIMS universe has its god: TAT, turnaround time, and its problems with M-words.
Acolytes of the LIMS approach see a laboratory as a mechanism for the digestion of biomaterial into data, or a factory where data is processed into money. Everything in this factory has to speed up and increase productivity, to intensify, to compete.
But there is an unpleasant aspect. Though modern laboratories utilize cutting edge technology, this very complexity can lead to errors. So you must pay attention not only to production speed but also to quality control. If we as a laboratory make an avoidable error, the clinician kills the patient. It happens more often than you might think.
The metaphysical contradiction between the LIS and LIMS schools of thought lies in the following. The highest productivity will come from a lab that always runs the same test. Performance will be lower if you need a large assortment for different patients. You need to forsake batch mode and instead prioritize different patients by running various, specific tests. You also have to change the reagents. And you can’t just prescribe the cheapest, most cost-effective tests to patients: the law ensures that the lab cannot optimize its structures at the expense of the patient.
After COVID-19, the misconception spread that labs were getting greedy. Now, healthcare costs are rising. The public is anxious that medicine might eat up untold amounts of money. There’s a risk that there won’t be enough to go around. The problem LIMS is trying to solve is how to recoup production costs and increase speed within the constraints of a shrinking cash flow. The answer: maximum automation to stay competitive in the marketplace.
COVID-19 was a shock to the LIMS universe. Before Covid, the test suite was virtually unchanged. When COVID-19 burst into this quiet world, the structure of the tests changed dramatically. It turned out that not all labs were ready with suitable strategies to adapt. What if the situation repeats in a more drastic form? (It surely will.)
The problem falls under the purview of the management of the manufacturing processes (and sustainability in the marketplace). How can the management component be strengthened to make the LIMS more flexible and agile? How do cost management, production safety, and quality assessment systems relate to it? Should they be integrated into the LIMS, or remain separate planets in the laboratory management universe?
Since LIS and LIMS are now the same thing, their M-problems are worth solving together.
The best way to solve these problems is to integrate solutions from different issues found within specialized modules on the same platform. Each of these products focuses on a different sticking point. These trouble areas may vary from lab to lab, but some are important to all.
It is a great advantage if a system vendor tries to combine different solutions in its approach. In addition to the LIMS, there is also middleware which is very often used for total automation solutions (another useful M!). They always come with their own software that should interface well with the LIMS.
So check your M’s, look for the Messes and Mix-ups in your lab that need the most attention right now. Plug those holes by discussing them with knowledgeable vendors. Let the LIMS help you solve your problems. Bring your confusing secrets into the light of day. The two approaches – humanistic and productivity – are different sides of the same coin.
Hold to the idea that as important as productivity is to you, your primary goal is to help people. Remember: you can kill a patient with your Mistakes or save them with your Mastery.
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