Tatal laboratory automation systems have changed the way people interact with testing. People no longer need to interact with specimens at certain times to perform tests, as automation completes all the work. However, judgment is needed in areas such as releasing test results, monitoring equipment, performing quality control tests, and deciding whether to perform maintenance. Understanding the rhythm of how testing works with this type of equipment can be a challenge, especially when laboratory workflows may change.
Automated laboratory instruments require complex software to track inspection orders, direct specimens in the appropriate direction, maintain patient and quality control results, and observe equipment indicators. Developing a habit of monitoring software may be a challenge, as it requires understanding what automation is doing at the system level and why. For those who have worked manually on a workbench, understanding how to transform it into automation can be a challenge.
For complex automated laboratory systems, understanding what an error means can be a problem. Why some obvious problems can be solved directly, and subtle problems continue to occur over time. This requires tracking and monitoring total laboratory automation systems to stop problems before they start. This also means bringing a different way of thinking to system operations, as well as good communication skills between workers and medical staff, especially those who may work differently, to solve testing problems.
When new technology comes in, old technology will be eliminated. While lab automation equipment does indeed lead to increased productivity, some skills and knowledge of the old system will be lost. As medical services need to be continuous for many years, it is necessary to understand why certain things were done in a certain way in the past in order to ensure that any new information about patient testing is understood in a broader context. Getting rid of old testing technologies makes it a challenge to maintain this level of knowledge accessibility. In addition, old skills may be useful in troubleshooting new equipment, even if these skills are not used frequently.
With the benefits of lab automation equipment, adding some tests internally, while terminating or outsourcing other tests, may be cost-effective. These new tests need to change the supply, which has downstream effects on reagent storage and personnel requirements. Understanding new workflows may create new demands on labor, which may pose personnel configuration challenges as people must adapt to new schedules and responsibilities. Addressing these challenges may create unexpected burdens that make it difficult to convert to laboratory automation.