The importance of new technologies in avoiding both over- and underuse, and the key to finding a balance between costs and benefits
With the constant evolution of technology and the increasing need for laboratory tests to be more accurate and sensitive, algorithms for testing have become more predominant. While performing everyday laboratory testing, many hospital laboratories use algorithms, or follow prescribed sets of rules for procedures, without the knowledge that they are algorithms. One of the simplest algorithms is implemented when a hematology analyzer flags an irregularity for a complete blood count, causing the laboratorian to perform a manual differential blood count. This process automatically causes another test to be performed to verify accuracy and sensitivity (or lack thereof). A slightly more complex algorithm is seen in Figure 1; this algorithm shows a protocol that involves more than one demographic and department.
There are several areas to consider when thinking about how to implement new algorithms in the laboratory. There are costs that are associated with each application of an algorithm. Implementing the algorithms can have a negative effect on older technology that is currently being used. A balance has to be created between the laboratory information systems and the clinical application of the tests. There may be future implications based on the algorithms established, and laboratory personnel should work closely with their physician team and pathologists to determine what works best for their laboratory.
Implementing New Technology
If a laboratory is not fortunate enough to have a robust information technology system, there can be costs associated with purchasing a system that can automatically order tests. Most of the cost is in man- or woman-power expended manually developing algorithms for the laboratory information system, and testing those algorithms to determine their functionality.
Another expense is training the laboratorians. There is a retraining period that has to occur for laboratorians to correctly route the sample through the process. Samples that previously may have been placed in a rack to hold for a week will now be routed to another department, or have an immediate follow-up test by the laboratorian. More training will be required if a new test is performed to accomplish a desired algorithm.
Implementing a new test not only can burden an already depleted workforce, it can create additional costs because of the need to purchase new reagents. It is important to remember that the financial weight of a follow-up procedure or test is not as great as it would be if the test was performed 100% of the time. The secondary or tertiary procedure or test is only compensating for the weaknesses of the existing system and providing confirmation. The precursor tests generally have a high specificity and can be rapidly performed. These tests are less expensive, and they allow for the results to be sent to the clinician in a timely manner, usually before the patient leaves the hospital.
Finding the Balance
The value in setting up an algorithm is within the clinical application. If the test is not important, the doctors will not order it. If there is no clinical justification then there is no a reason to tack on an extra step. Just because an algorithm has dictated a process for years and years does not mean that it is the correct process or an essential one. Finding the balance between cost and benefit and how these algorithms should operate requires a team of frontline employees, ordering physicians, information technology employees, and others, depending on how your organization is set up.
There is something to be said for the correct balance of usage when it comes to these algorithms. When an algorithm is being overused, a few calculations can be done to determine if it would be worth moving past the screening test or first step in the protocol to the confirmation test or second step in the protocol. Overuse can create a situation where it is not cost-effective to have the laboratorian perform the first test because of the large backup of samples downstream in the algorithm.
While overuse is a problem, underuse of an algorithm can be more difficult to overcome. This is because underuse of the algorithm can be due to many more factors. If the test is seasonal, it may be necessary to develop an algorithm that only takes place at a certain time during the year. Evolution of tests, procedures, and knowledge may make the algorithm excessive, redundant, or outright pointless.
The lack of buy-in from the physicians or lack of utilization by the physicians can cause decreased use of algorithms; this can be a great frustration. There may be a general lack of knowledge among the clinicians of how the algorithm works. It is important to internally market algorithm changes to show how they operate. Marketing internally is especially crucial in a teaching hospital, where fellows and residents are in constant rotation. When clinicians discover the usefulness of algorithms, they may be able to help suggest and provide different perspectives to allow the laboratory to expand testing and capabilities.
With any of these problems, it is best to go back to the drawing board. Algorithms can come and go with the ebbs and flows of diseases and physician preferences. It is important not to salvage these algorithms based on the pride one might take in their establishment and previous use. It is important to remember that they are tools. Tools can be sharpened, become dull, or be replaced. Their function is to make getting to the end result more accurate and efficient.
With newer molecular tests being performed clinically, it is becoming increasingly clear that older technologies may not be as accurate as once believed. Many algorithms involving molecular testing show the flaws in older technology. Molecular tests are becoming less expensive, are increasingly simple to set up, and decrease the amount of time required to perform testing. It is easy to see that these reasons will force tests such as rapid immunoassay screening tests out the door, so to speak. There is no need to fear that the use of algorithms will vanish, because there is always new technology on the horizon that will require new algorithms. Eventually, the new rapid test could be a molecular test.