AI Based Patient Sentiment Analysis in Healthcare

Business challenges

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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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Difficulty in understanding patient's perspective: ``Without comprehending customer experience, it can be challenging to grasp the patient's viewpoint and develop strategies to enhance their experience.``

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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Ranked entities based on these common positive and negative attributes.

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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Better patient outcomes: Helps in understanding the patient's perspective and take action to improve the patient's experience and overall outcomes.

Technology Stack

Trusted and Proven Engagement Model

  • A nondisclosure agreement (NDA) is signed to not disclose any sensitive information revealed over the course of doing business together.
  • Our NDA-driven process is established to keep clients’ data and IP safe and secure.
  • The solution discovery phase is all about knowing your target audience, writing down requirements, and creating a full scope for the project.
  • This helps clarify the goals, and limitations, and deliver quality products & services.
  • Our engagement model defines the project size, project development plan, duration, concept, POC etc.
  • Based on these scenarios, clients may agree to a particular engagement model (Fixed Bid, T&M, Dedicated Team).
  • The SOW document shall list details on project requirements, project management tools, tech stacks, deliverables, milestones, timelines, team size, hourly/monthly rate cards, billable hours and invoice details.
  • On signing the SOW, an official project kick-off meeting shall be initiated.
  • Our implementation approach, ecosystem, tools, solutions modelling, sprint plan, etc. shall be discussed during this meeting.

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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