Effective treatment and efficient practices using text analytics
Some examples of instant insights around Health and Pharma
- Analysis of 480 reviews show that Aspen Dental needs to take better care of their clients
- Our analysis of 705 reviews shows eHealth Insurance can be hard to reach
- Analyzing 924 reviews about Care.com might give an explanation to why users are so dissatisfied
- Analysis of 526 iHerb reviews reveals the need to be more transparent with their customers
- Customers are happy with Jack Black Face Moisturizer
- Analyzing 7 956 reviews about laser eye surgery company Optical Express shows high prices and lack in customer care
- Analysis of 3 840 Affordable Dentures reviews shows long waiting times
- Analysis of 9 930 reviews for 1-800-Dentist shows complaints about insurance
- We analyzed 1 147 reviews about La Roche-Posay Sunscreen
- We analyzed 861 reviews about Oral-B Pro 3000
- We analyzed 3 014 reviews about Amazons Elements baby wipes
- We analyzed 2 000 reviews about Samsung Galaxy Smartwatch
- Hospitality at the hospital – 321 reviews of LAC + USC Medical Center
- We analyzed 5 500 reviews about Vitality Insurance
- We analyzed 2 107 reviews about Summit Professional Education
- Analyzing 2 361 reviews about online medical app Pushdoctor
- Summary of 21 598 reviews on Pharmacy First
- Summarizing 1 130 Reviews about Nextgen Population Health
Patient care and improving treatment effectiveness are some of the most important priorities at hospitals. Many leading hospitals are doing surveys to try and improve the care for patients. However, sometimes the surveys miss important questions because a survey can only have so many questions. Unless you let the patient or healthcare professional answer in an open ended format.
Human error and bias can easily affect analysis of open-ended text data – unless you use the right tools to model the data and process the results.
Quickly find out how to improve your practice and help patients
After collecting open ended questions, the difficult part is analyzing all the text data. In a lot of cases, the text data has deeper insights than a 1 – 10 score rating because the respondents are sharing exactly why they are happy or unhappy. With The Gavagai Explorer you can analyze the text data and find exactly what your patients or healthcare professionals need.
You will be able to discover key topics from the text data that is driving satisfaction. Quickly find new issues to work on or track issues across time. With The Gavagai Explorer you can finally find and analyze text data quickly and easily.
Get Started for Free
Learn about our AI-powered text analysis tool in a Personal Demo.
Then get a Free Trial to test-run Gavagai Explorer using your own data.