Laboratory Information System (LIS)

Laboratory Information System (LIS)

Technology has played an incredible role in the medical field in recent years. It has been revolutionizing the way healthcare is delivered and received from the development of manually writing data to type it on computers with systems such as Electronic Health Records (EHR). Technology has enabled healthcare providers to improve patient outcomes, increase efficiency, manage patient information, and reduce costs. One area where technology significantly impacts is the development and use of Laboratory Information Systems (LIS) and Artificial Intelligence (AI). LIS and AI have greatly helped improve the accuracy and efficiency of how medical technologists or doctors conduct medical tests and diagnoses. 

A laboratory information system (LIS) is a type of healthcare software that processes, organizes, and stores patient data related to laboratory operations and testing. Laboratory information systems track, record, and update clinical details about a patient during a provider visit and retain the information in a database for future reference. Moreover, physicians and laboratory professionals utilize laboratory information systems to coordinate the flow of work and quality control of inpatient and outpatient medical tests in the different sections of the laboratory (hematology, chemistry, immunology, microbiology, toxicology, and public health). On the other hand, Artificial Intelligence (AI) replicates human intellectual processes with machines, particularly computer systems. Examples of AI applications are expert systems, natural language processing, speech recognition, and machine vision. AI and LIS are heavily related as AI, through being embedded in the information system of the laboratory, has reduced the burden of the medical technologists or laboratory technicians as it enhances productivity, increases efficiency, and ensures quality by being able to do the easy and some complex tasks in the laboratory.

As technology advances, its capacities also significantly increase. One example of these innovations is robotic-assisted surgery through the da Vinci surgical system. This surgical system enhances the surgeon’s capability by allowing them to execute minimally invasive surgical operations with better precision and accuracy than open surgeries. In the future, as we reach that age, I believe that patient care will be better as AI can easily do some tasks for healthcare workers. Using LIS and AI would greatly benefit us as it would lead to better patient management and treatment for diagnosing. As early as now, we can see the possibilities of the future. With this, the question of humans still being able to work in the future comes to mind. As technology continues to improve, would it be possible to replace humans in the work field? I believe that even with that possibility, in the future, technology wouldn’t be able to make doctors, medical technologists, or healthcare professionals obsolete. It is because even with artificial intelligence or LIS being present, it wouldn’t be possible to duplicate doctor/healthcare professional-patient interactions. It is essential for healthcare professionals to empathize with patients and to deal with them as a person. Moreover, cures for some diseases aren’t assured in the future. With this, all we can offer is patient management in terms of care, and I believe that this is something that artificial intelligence cannot replicate or offer. 

Overall, we cannot stop the advance of technology, especially in our field as healthcare workers. Its advancement would greatly help us deliver better patient care, our primary goal, especially as medical technologists. Being able to have high-tech types of equipment would surely improve laboratory findings, leading to a more effortless and better diagnosis. However, even with all these benefits, doctors, nurses, medical technologists, and other healthcare professionals would continue doing their jobs in the future. One thing AI cannot replicate is having a whole-person relationship with the patients. Having a relationship built on trust and understanding, which is very much needed in treating patients, is something that technology can never replicate.

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