Kathleen M. Hong's Online Review Report Card
5
Average Star Rating
6
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
Kathleen M. Hong does not have an adequate amount of comments to generate the sentiment analysis.
Online Reviews Breakdown
Google
WebMD
Yelp
Facebook
RateMDs
Vitals
List of Kathleen M. Hong's Reviews
Dr. Kathleen Hong, Nurse Emily and the whole team at RMA were a blessing during our stressful, anxiety-filled journey to parenthood. Dr. Hong is extremely knowledgeable and personable. The RMA team was friendly, comforting and honest. Easy to communicate, efficient with prenatal work-up process and morning monitoring and flexible with telehealth/virtual or in-person appointments during COVID-19. We truly thank you for your help and hope!
Reviewed On HealthGrades
I love Dr. Hong! She has been such a God-send in this already difficult process. She's genuine, caring, and really does try to get you the family you've been dreaming of having. Having her as my doctor in my fertility journey has been one of the best decisions I've made. Working with her and my primary nurse, Michelle, has truly made this experience much more easier to handle. If you are looking for an RE, I would 100% recommend Dr. Hong and her team!!
Reviewed On HealthGrades
Dr Hong is wonderful! She is straight forward and very kind! I never felt rushed or pressured to make decisions right away. She and her team explained everything throughly and worked with our schedule as much as they were able to with adhering to my cycle! I can not recommend her and RMA NJ enough!
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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