Patient experience (PX) analytics is the computational analysis of patient satisfaction or sentiment data, which is based on the range of interactions patients and caregivers have had with a healthcare provider. Sentiment analysis of patient experience in healthcare provides important insights that hospitals and doctor’s offices can harness to make improvements in their operations. This results in increased customer satisfaction that is driven by data-backed strategies for a better patient experience.

2. Patient Experience
Analytics for Hospitals &
Doctor’s Offices

3. Overview
Patient experience in healthcare should be the main focus of any
healthcare provider, whether it is a hospital chain, private medical practice,
pharmacy, or a lab. Thankfully, medical practices can keep a close eye on
customer satisfaction with the help of AI-driven machine learning
platforms that can analyze patient experience data to give valuable
information. This article details how healthcare organizations can use
patient experience analytics to improve operations, and as a result,
increase growth and revenues.

4. What Is Patient Experience Analytics?
Patient experience (PX) analytics is the computational analysis of patient
satisfaction or sentiment data, which is based on the range of interactions
patients and caregivers have had with a healthcare provider. Sentiment
analysis of patient experience in healthcare provides important insights that
hospitals and doctor’s offices can harness to make improvements in their
operations. This results in increased customer satisfaction that is driven by
data-backed strategies for a better patient experience.
Machine learning (ML) platforms can analyze patient experience reviews from
a variety of sources, such as Google Reviews, patient forums, social media
channels such as Twitter or Facebook, as well as surveys. AI-based platforms
use ML tasks such as natural language processing (NLP), semantic clustering,
sentiment analysis, and others to extract accurate information from sources
of patient voice.

5. How Does Sentiment Analysis Improve
Patient Experience In Healthcare?
An AI-enabled sentiment analysis API processes patient satisfaction data and brings to
notice certain issues and challenges that hospitals may not be aware of but which can
greatly affect patient satisfaction. Through NLP in Healthcare, you can analyze and
extract key information from patient reviews, automatically and with precision, and use
it to improve business processes.
An in-depth analysis of patient opinions in comments and reviews can help you
strategize the following -
● 1. Drive patient satisfaction
● 2. Build trust
● 3. Improve operations
● 4. Expand healthcare offerings
● 5. Monitor brand reputation

6. How Can You Capture Patient Sentiment?
To get a rich view of patient experience performance at your medical center,
you need to conduct sentiment analysis on a large set of patient satisfaction
data. You can capture this data via the following sources.
1. Social media
2. Google Reviews
3. Surveys
4. Patient Forums
5. Healthcare/doctor review websites

7. Conclusion
Repustate’s patient experience analytics solution, Repustate IQ, gives you the
most in-depth sentiment analysis insights from your patient experience data.
The platform is highly customizable so as to fit your requirements in the best
possible manner. Once the model is trained, it becomes smarter every time it
analyzes data and offers insights at speed and scale. Repustate IQ analyzes 23
languages natively through individual speech taggers, which leads to highly
accurate insights. This means, wherever your location may be, or whichever
language your patients prefer to use for their comments and reviews,
Repustate’s solution gives you intelligent results every single time. Improve
your patient experience in healthcare with Repustate’s advanced machine
learning PX analytics platform.

8. Thank you!
Understand your data,
customers, & employees with
12X the speed and accuracy.
Visit: www.repustate.com to
learn more