Kim Stevens Md's Online Review Report Card
4.5
Average Star Rating
16
Total Reviews
0
Recent Reviews
5
Review Sites Found
Accepts Medicare
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Medical School
-
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
Kim Stevens Md does not have an adequate amount of comments to generate the sentiment analysis.
Online Reviews Breakdown
WebMD
Facebook
RateMDs
Vitals
List of Kim Stevens Md's Reviews
Dr. Kim spent time with me giving me his second opinion for Wet Macular Degeneration (Regeneration). He understands my case, and gave me very good advice based on my tests, history, and conversation. I would highly recommend him and his staff, as they are very knowledgeable and personable.
Reviewed On HealthGrades
Kind n courteous staff and drs kind and patient.
Reviewed On Google
Dr Kim is a nice doctor. This is for the staff who dropped the ball today. Arrived at 2pm for a 2:30 pm appointment. There had been several patients (3) who were called ahead of us even if they have the same appointment time with us but arrived the clinic at a much later time. We were called at 2:59 pm as if no unpleasant incident happened.
Reviewed On Yelp
Highly recommended. Initially eye doctor recommended a well known name in the community. After having the initial interview with the Zeiter Group we became very uncomfortable. In essence the eye doctor told us he could not use laser but he had to cut with the knife. He also warned us that he may have to go twice to the same eye to remove pretty hardened cataract. At such point we conducted an internet search for best eye cataract surgeon and the Valley Laser & Surgery came up as most recommende
Reviewed On HealthGrades
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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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