Guest post by Dr. Shuting Wang, Assistant Professor, Baruch College, City University of New York (CUNY)
This Success Story is a report on the results of one of the awards in the Northeast Big Data Innovation Hub’s 2021 Seed Fund program.
In this study, the Baruch College team investigated the existence and influence of patients’ preference for local physicians (i.e. home bias) on virtual health platforms by starting with two key questions:
1) Do patients, especially those from medically disadvantaged areas where there is a lack of experienced physicians, have home-bias when selecting online physicians?
2) What is the impact of patients’ home-bias on the propensity of them to obtain definitive diagnoses?
Analysis yields several interesting findings. First, while results suggest the existence of home bias among patients by showing that they are more likely to select physicians from the local city than those from other cities, the magnitude of such home bias is very small among patients from medically disadvantaged cities. Surprisingly, only 3% of patients from medically disadvantaged cities chose local physicians, indicating that the lack of home bias may largely mitigate the healthcare demand away from medically disadvantaged areas and thus, threaten the survival of physician practices in these already underserved areas.
Second, results suggest that patients, especially those from medically disadvantaged areas, are less likely to obtain definitive diagnoses when consulting local physicians, demonstrating that the existence of home bias may prevent patients from choosing the best physicians for their diseases and thus lower the quality of healthcare services they receive on virtual health platforms.
Third, the researchers found that the availability of online reviews of physicians significantly moderates the existence and influence of home bias. Results suggest that the availability of online reviews can enhance the existence of home bias in medically disadvantaged areas and thus, help sustain healthcare demand in these areas, while largely mitigating the negative impact of home bias on reducing patients’ chance to obtain definitive diagnoses.
Considering that millions of people are living in medically disadvantaged areas across the US, an examination of home bias in their choice of physicians on virtual health platforms yields important implications for policymakers, platform managers, and individuals.
The team plans to extend this research by submitting a proposal to early career NSF Computer and Information Science and Engineering (CISE) grants (up to $180,000).
Lead PI: Shuting Wang (Baruch College, CUNY)
Shuting (Ada) Wang (shuting.wang@baruch.cuny.edu) is an assistant professor of Information Systems at Zicklin School of Business, Baruch College, City University of New York. Her research interests include the spread of fake news, the impact of social media on society, and the information system design in different contexts such as online health, Fintech, and e-commerce. Her studies have been mentioned by multiple media and have been published in MIS Quarterly (MISQ) and Journal of Management Information Systems (JMIS). She received her Ph.D. in Management Information Systems from Temple University.