Alissa A. Thomas's Online Review Report Card
Alissa A. Thomas
5
Average Star Rating
3
Total Reviews
0
Recent Reviews
4
Review Sites Found
Accepts Medicare
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Medical School
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Graduation Year
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Source: data.cms.gov Check DocInfo.Org for any disciplinary action against this provider.
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Sentiment Analysis
Alissa A. Thomas does not have an adequate amount of comments to generate the sentiment analysis.
Online Reviews Breakdown
Google
WebMD
Yelp
Facebook
RateMDs
List of Alissa A. Thomas's Reviews
I have had an ultra-rare cancer for the past 4 years. I have specialists at Dana Farber, Mass General (both of my specialists are program directors at Harvard Medical School), Memorial Sloan Kettering in NYC AND UVMC, Dr. Alissa Thomas. To say she is an amazing, resourceful, compassionate, qualified, caring, and intune physician, is not only an understatement but almost belittling. I am very much in charge of my healthcare. I shop for the best of the best and simply overlooked what was literally in my back yard. Dr. Thomas cares for not only me but my whole family. She is incredibly compassionate, something that seems to disappearing from our healthcare system. She cares about me and how my illness and treatment affects my family. I am not just a number to her, and if I am you would never know it. It’s not about rushing me in or out, it’s about explaining everything and making sure I understand it. Do yourself a favor, reach out to her!
Reviewed On HealthGrades
Always smiling and friendly. Spends as much time with me answering questions as needed. Has even responded to questions and requests after hours and on weekends. Couldn’t ask for a better oncologist.
Reviewed On Vitals
very nice answered all questions
Reviewed On Vitals
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Selection Criteria
All the information you see here is based on our analysis of internet reviews across the seven major review platforms most used by consumers during their healthcare provider selection. The platforms we selected are Google, WebMD, Yelp, HealthGrades, Facebook, RateMDs, and Vitals. The analysis algorithm uses the compiled data of average score, recency of reviews, number of reviews, and the sentiment expressed in the written comments. It then assigns weight to each parameter based on the available research on how consumers use reviews in their doctor selection process. This report is designed to help identify the doctors with the best overall review score in an area and does not reflect the doctors' competence.
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