🔬 Laboratory Information Systems

MT14-CC’s Docs 🔬 Laboratory Information Systems

Margarita S. Resuelo

MT 14 – CC 

What is LIS?

The vital system that is designed to oversee the operations of the laboratory, most especially pertaining to the management, storage, and processing of patient data, is attributed to a Laboratory Information System (LIS) (Orchard Software, 2023). As a healthcare software, LIS involves the integration of computers and information technology to interactively manipulate and completely coordinate all work processes in different sections of the clinical laboratory in a structured, organized manner. It contributes to better patient care and boosts efficiency in the workplace it is assimilated in. 

 Uses of LIS

A LIS utilizes computer systems to its advantage by easing the workload and decluttering the processes by which each section interacts with each other to produce precise patient data for improved healthcare (DelVecchio, 2015). Specifically, as it is a system designed to collaboratively facilitate the different functions of the laboratory, it serves as a comprehensive database that simplifies the process of requesting a test, adds to the efficient production of specimen collection sheets/result entries, and contributes to the anonymity of identification labels with regards to patient demographics. Similarly, it also sustains the easy tracking and archiving of patient data which can be referenced for future health outcomes.

 What is the implication of AI in your future work?

I do believe that the prospering use and gradual integration of AI in a myriad of fields for various purposes has indeed paved the way for more efficient and effective work outcomes, easing the burdens of relatively difficult tasks, and especially compressing the duration of arduous methods/processes. Making routine procedures far easier and more methodological, the implications of AI in my future work would surely boost morale within the workplace such that, with proper programming and maintenance, can be used as a supplement for decision-making and quality assurance. Notably, AIs should never be seen as far superior to humans (who have years of experience and training in the field) as they, too, may be subject to certain lapses. In many areas our innate cognitive abilities must always be used as an anchor in the formulation of conclusions and that AIs should always be administered with great responsibility. 

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