Why RPA is Beneficial for Clinical Trial
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Why RPA is Beneficial for Clinical Trial

By Pharma Tech Outlook | Monday, November 09, 2020

Robotic process automation or RPA can help the healthcare sector to conduct clinical trials efficiently. 

FREMONT, CA: Accurate data is crucial for the healthcare sector, and every day, they collect a massive amount of information. They contain data from numerous sources like radiology, insurance portals, lab information systems, clinical applications, application schedules, and ERPs. Implementing the information flow within every channel can be a complicated and labor-intensive task, which increases resource consumption but decreases efficiency. 

Robotic process automation or RPA can help the healthcare sector to solves such problems. For proper functioning of the system, RPA can automate any repetitive tasks. To enhance efficiency, it can reduce the number of errors, decrease workforce utility, and decrease expenses.

Randomized Clinical Trials (RCT) 

RCT is the standard that has to be maintained for testing new therapeutics for safety when it is utilized on humans. Although such testing's success rates are between 40-80 percent during different phases, there can be several failures due to patient recruitment. The difficulties of performing RCTs can result in an extensive research timeline that increases the trials' expense. The primary factors that can impact RCT are patient retention, trial sites, availability of patients, availability of principal investigators, and study design. RPA can increase the efficiency of the procedures while enhancing the success rate of the clinical trials. 

It will also become easy to implement significant pharmaceutical development with quick data integration into complicated environments. Combining RPA with it will enhance and streamline the administrative activities. 

Patient matching

Starting a patient population by utilizing dynamic inclusion and exclusion to evaluate the trial's impact can be a tiring task, but the procedure can be automated with RPA. It will help the study designer quickly modify when necessary to enlarge the population of eligible patients. With the assistance of RPA in the process, it will become easy to search for suitable patients for the trials. The RPA bots can even increase recruitment speed by performing the initial executions with the potential patients before the final communication with the clinic associates. It will help decrease the effort required to do redundant tasks during the process of patient recruitment in a clinical trial. 

 

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