Healthy Reviews! Online Physician Ratings Reduce Healthcare Interruptions

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# Healthy Reviews! Online Physician Ratings Reduce Healthcare Interruptions
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.subtitle[
## Presenter: Danny R. Hughes, Georgia Tech
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.author[
### Discussant: Ian McCarthy, Emory University and NBER
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.date[
### ASHEcon Annual Meeting, June 29, 2022
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# Consumer search
- Highly relevant and underappreciated structure for studying health care decisions
- Basic idea:
  - Patients incur a cost to accessing/assimilating information about physicians
  - Patients have some beliefs about their utilities over all possible options
  - Patients stop searching when costs meet or exceed expected benefits

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# Context
- Physicians retire and patients must find a new physician
- Online reviews lower the cost of this search and increase probability of a more recent visit to a new physician (not sure that the first implies the second, but more on this later)

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# Looking for New PCP

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<img src="ashecon-2022-hughes_files/figure-html/unnamed-chunk-2-1.png" style="display: block; margin: auto;" />
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MedPAC *Report to Congress*, March 2012 and March 2020

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# Finding a PCP among Medicare and MA

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<img src="ashecon-2022-hughes_files/figure-html/unnamed-chunk-3-1.png" style="display: block; margin: auto;" />
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MedPAC *Report to Congress*, March 2012 and March 2020

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# Finding a PCP among Commercial Insurance

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<img src="ashecon-2022-hughes_files/figure-html/unnamed-chunk-4-1.png" style="display: block; margin: auto;" />
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MedPAC *Report to Congress*, March 2012 and March 2020

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# Approach
- Research design: DD
- Sample: Patients of retired physicians in two periods
- Pre period: 2007-2010
- Post period: 2015-2018
- Control (Treatment): 18 (16) top 100 population cities, based on cities with fewest (most) Yelp reviews per capita and nonmissing reviews in pre and post period

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# Some thoughts and questions

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# Practical motivation
- Do people use Yelp to find new PCPs?
- You write, "...a relatively small proportion of patients rely on these platforms for choosing their physicians."
- But some work **does** suggest that patients value online reviews in health care

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# Theoretical motivation
- Really like the idea, but...
- Paper considers search as decision to find a physician today or not
- Are patients "searching" over physicians, or are they just deciding whether to take an action on a given day?
- Is `\(v\)` independent of `\(E[Days]\)`? How?
- Searching for a physician on a given day is not the same as visiting the physician that day
  - Search could *increase* time to visit because patients are drawn to the most capacity-constrained physicians
  - How should I think of waiting time here?
  
  
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# General concern
- Treated cities very different than control cities (e.g., Laredo vs Anaheim), probably not just in levels
- Could relate to practice sizes and consolidation, thereby affecting within-practice referrals
- Null results (using days) when including retirement year/quarter FEs

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# Identification and estimation
- Is 2x2 DD appropriate here? 
  - Treatment/control is continuous (availability of online reviews)
- IV using other Yelp reviews
  - Does this satisfy exclusion restriction? Only conditional on overall use of Yelp
  - Not if early adoption of Yelp (in general) is correlated with unobservables or if Yelp causes additional retirements
- Are cities the right level of treatment/control?
  - Laredo is isolated, Anaheim is right next to LA
  
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# Some potential considerations...
1. More (or fewer) details on model
2. Treatment at county or HRR-level instead of city/zip
3. Measure visits at practice-level instead of physician-level
4. Visualizations of physician markets over time between treatment/control (total retirements, number of physicians, number of practices, size of practices, etc.)

Bonus question: Why do physician's retire and where do they retire most?