# The Interplay Between Online Reviews and Physician Demand

1 Research Highlights October 7, 2020 ![Mor Armony and Anindya Ghose](/sites/default/files/styles/246w/public/assets/images/Untitled%20design%20%2817%29.png?itok=JZCDKjA-)As patients look to the internet and virtual word-of-mouth recommendations to identify healthcare resources throughout the global pandemic, online reviews for doctors are playing an increasingly vital role. Researchers at NYU Stern School of Business and University of Illinois at Urbana-Champaign recently analyzed data from a leading medical appointment booking platform to analyze and better understand patient choices.

> With the uptick in tele-health due to Covid-19, individuals are using digital platforms to choose doctors and healthcare providers more than ever before. Understanding the role that those reviews play in patient choice will be critical for doctors who want to thrive in today’s rapidly changing healthcare landscape.

In the paper, “[The Interplay Between Online Reviews and Physician Demand: An Empirical Investigation](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2778664),” NYU Stern Vice Dean of Faculty [Mor Armony](https://www.stern.nyu.edu/faculty/bio/mor-armony) and Professor [Anindya Ghose](https://www.stern.nyu.edu/faculty/bio/anindya-ghose) and co-author Yuqian Xu (Stern PhD ’17; University of Illinois at Urbana-Champaign) used text-mining and choice-modeling techniques and found that bedside manner, accuracy of diagnosis, waiting time and service time disproportionately affect demand for patient care.

Key takeaways include:

- Patients rely on text reviews of physician service to make their choices
- The paper identified the seven most frequently mentioned service features of physicians and doctors, among patients through text mining, among which (1) bedside manner, (2) accuracy of diagnosis, (3) waiting time, and (4) service time had a statistically significant relationship with patient choices
- Improving predictive models of patient choices can help doctors more efficiently manage the operational aspects of their practice (e.g., service time, waiting time, etc.)
- Using text-mining of online reviews to understand which features affect patient satisfaction can help promote better long-term relationships between patients and healthcare providers

On a broader scale, the co-authors anticipate that this type of predictive modeling of patient choice will play an increasingly important role in the healthcare industry: “With the uptick in tele-health due to Covid-19, individuals are using digital platforms to choose doctors and healthcare providers more than ever before. Understanding the role that those reviews play in patient choice will be critical for doctors who want to thrive in today’s rapidly changing healthcare landscape.”

This research is forthcoming in *Management Science*.

## More from Mor Armony and Anindya Ghose

- [The AI Advertising Paradox](https://www.stern.nyu.edu/experience-stern/faculty-research/ai-advertising-paradox)
- [Only One Left at this Price! The Effects of Nudging on Consumer Behavior](https://www.stern.nyu.edu/experience-stern/faculty-research/only-one-left-price-effects-nudging-consumer-behavior)
- [Can More Lines Really Result in Less Waiting? ](https://www.stern.nyu.edu/experience-stern/faculty-research/can-more-lines-really-result-less-waiting)
- [Fighting for the Greater Good: New Research Shows Democrats and Republicans are Willing to Trade Personal Smartphone Data to Combat COVID-19](https://www.stern.nyu.edu/experience-stern/faculty-research/fighting-greater-good-new-research-shows-democrats-and-republicans-are-willing-trade-personal)
- [Alexa and Other Voice-Activated Shopping Devices Boost Consumer Spending, According to New Research](https://www.stern.nyu.edu/experience-stern/faculty-research/alexa-and-other-voice-activated-shopping-devices-boost-consumer-spending-according-new-research)