AI Based Patient Sentiment Analysis in Healthcare

Application Screenshots

Technology Stack

Problem Statement

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Reduced patient satisfaction: Without understanding customer experience, it can be difficult to identify and address areas of dissatisfaction, leading to reduced patient satisfaction and potentially causing patients to seek care elsewhere.

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Decreased patient retention: If patients are not satisfied with their experience, they may choose not to return to the clinic, leading to decreased patient retention and a loss of revenue.

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Difficulty in identifying areas for improvement: Without gaining insight into customer experience, it can be difficult to identify and address issues that affect patient satisfaction and clinic growth.

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Lack of trust and credibility: If patients are not satisfied with their experience, they may not recommend the clinic to others, leading to a lack of trust and credibility in the community.

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Difficulty in identifying customer needs: Without understanding customer experience, it can be difficult to identify the needs of patients and how to tailor services to meet those needs.

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Solution Overview

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We collaborated with a healthcare clinic to develop an AI-based solution for understanding patient experience by analyzing feedback gathered from social media and online directories.

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Utilized machine learning to train a sentiment classifier that scores entities as positive, negative, and neutral from historical data.

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Built a custom NLP pipeline to identify and extract hidden entities in the review text and extract the sentences associated with the entities.

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Scored text related to hidden entities using the trained sentiment classifier.

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Trained a model to detect and extract the most common positive and negative attributes that have the highest correlation with review sentiment.

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Business Impact

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Improved patient satisfaction: By using sentiment analysis to understand patient experience, the clinic can identify and address areas of dissatisfaction, leading to improved patient satisfaction and potentially increased patient retention.

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Increased efficiency: Automates the process of gathering and analyzing patient feedback, making it more efficient and cost-effective than manual methods.

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Better understanding of patient needs: Provides insights into patient needs and preferences, helping the clinic tailor services to better meet those needs.

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Increased reputation and credibility: By using sentiment analysis to understand patient experience, the clinic can improve its reputation and credibility in the community by addressing issues and concerns that patients may have.

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Competitive advantage: Gain a competitive advantage over other clinics that are not using this technology.

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Testimonials of Our Happy Clients

Rick Tigges

Rick Tigges

CFO, Bemodo

"They are very responsive and able to shift focus quickly as we have needed it for business reasons."
Ryan McClellan

Ryan McClellan

CEO, iLookin.com, LLC

"They [OptiSol Business Solutions] have been very friendly and they kept up with the work. They did the job as we had discussed and as everything was arranged."
Chris Gordon

Chris Gordon

CEO, Wait for me

“I can't speak enough about how pleased I am with their process; it was seamless and efficient.”
Oli Robinson

Oli Robinson

CEO, Rule:Fresh

"What impressed me the most was their willingness to go above and beyond what was asked."
Dan Talken

Dan Talken

Founder, My Equipment Library, LLC

"We're constantly impressed with their speed and quality of the development that they achieve on a consistent basis."
Ken Kisner

Ken Kisner

Molecule Corp

The best part about working with OptiSol Business Solutions is their commitment to being readily available to their partners. They’re even willing to work into late hours of the night depending on time differences. The solution they produced has already doubled efficiency levels.

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Our Award-Winning Team

A seasoned AI & ML team of young, dynamic and curious minds recognized with global awards for making significant impact on making human lives better

Awarded Bronze Trophy at CII National competition on Digitization, Robotics & Automation (DRA) – Industry 4.0

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5 yrs

in AI & ML
Engineering

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40+

AI & ML
Projects for
reputed Clients

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50+

AI & ML
Engineers

Awarded as Winner among 1000 contestants at TechSHack Hackathon

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