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CASE STUDY: ADVERSE EFFECTS REPORTING

OVERVIEW

An Adverse Event (AE) is described as “any untoward medical occurrence” in a patient receiving a medicine. These events include everything from so called “non-serious” side effects such as nausea to more serious events such as reports of malignancy. Our client dealt with more than 100,000 of these per year, which is a mandatory legal responsibility. The pharmaceutical company had a CRM in place to track input from various devices but this was reliant on humans (doctors, clinical specialists, etc) entering the right amount of detail in cases. This information then needed to be evaluated by specialists every day to determine if a case was deemed to have an adverse effect.

WE DELIVERED

We were able to develop a framework that included keywords often associated with AE cases, as well as background factors such as age, sex, underlying conditions, additional medication, medical history. Each day the bot would extract the information and highlight the cases to the expert that were most likely to be adverse events.

OUR RESULTS

The initial success rate of the bot was 70%, but as more information was fed into the system and the parameters could be adjusted this rose to 89% and meant more of the specialist time was spent dealing with the right cases.

The firm saw a return on investments in 15 months, but this doesn’t convey the true benefits and savings the firm would have seen had their reporting been late and fines applied. This implementation took a large amount of pressure from the team and ensured the most important cases were dealt with first.

89% ACCURACY

ROI IN 15 MONTHS

MACHINE LEARNING