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White Papers

Current challenges faced in 

laboratory data management.

 
Product quality, safety and regulatory compliance must be maintained in laboratories responsible for testing, measuring and analysing samples. This spans across scientific sectors such as pharmaceuticals, food safety and diagnostics. Due to the immense responsibility for efficiency and accuracy in the lab, challenges often arise in the day-to-day management of processes and procedures.
 
Regulatory compliances
Adhering to regulations means maintaining stringent quality control, accurate record-keeping and auditable processes. This can have significant impacts on how labs function and the efficiency of their data transfers and workflows.
 
Data security and storage
Confidentiality is essential for laboratory data. Measures must be put in place to safeguard data. Protecting patient data or research findings involves authorised access, disclosure and alteration procedures.

Sample and workflow managment
Several factors including, sample identification, labelling, tracking, data management and resource coordination cause a variety of maintenance challenges, as well as coordination and consistency problems.
 

 

 

Data accuracy and integrity

Between 60-70% of clinical decisions regarding hospital admission and discharge are based on laboratory results, therefore data accuracy and integrity in labs is non-negotiable.

 

Time efficiency

Manual monitoring processes tend to waste time that could be better spent on more productive tasks that add value to a laboratories operations and the services provided to customers. It also increases the risk of human error.

 

Validation and scalable reporting

Without validations, a lab cannot be sure of reliability, however manual data entry can often cause issues such as, inaccurate results, misguided onward decisions, wasted resources and potential harm to finances.

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