Machine Learning Technology Saves Costs & Identifies Operational Efficiencies for Pharmaceutical Leader

During the unknowns of COVID, VOC Natural Language Processing analysis creates business impact for a healthcare provider.

Business Challenge

As the COVID-19 pandemic took hold in the United States, the safety of in-office doctor visits was uncertain. However, our client provided many injectable medications that people preferred to have administered in a doctor’s office. Our client was concerned that patients would be uncertain and uncomfortable about their ability to self-administer injections, which could potentially lead to incomplete multi-dose series and reduced quality of patient outcomes.

Solution

Further applied machine learning technology and statistical analysis to identify patient sentiment and help decision-makers save hundreds of thousands of dollars.

We were granted access to thousands of anonymized pre- and post-COVID call center transcripts to calls from physicians and patients.
We applied Natural Language Processing (NLP) and statistical analysis techniques to identify patient sentiment about self-administered injections.
We found in the pre-COVID period that patients feared in-home injections in comparison to in-office injections. However, within 90 days of doctors’ offices eliminating non-critical visits, at-home injection sentiment had reached statistical parity with in-office injection sentiment.

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Business Impact

By demonstrating improved patient sentiment, we were able to help our client cease the investment they had allocated to messaging, call center training, and script development for home injections. We also identified ways to help improve call center operations, from staffing need predictions to predicting when agent scripts require change to reduce case resolution time.

$100

Savings of unbudgeted dollars during a period of declining revenue

Potential call center cost savings applications identified from NLP analysis

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