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Consumer Decision-making When Shopping for Medical Services
Last registered on November 30, 2020

Pre-Trial

Trial Information
General Information
Title
Consumer Decision-making When Shopping for Medical Services
RCT ID
AEARCTR-0006815
Initial registration date
November 26, 2020
Last updated
November 30, 2020 11:34 AM EST
Location(s)

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Primary Investigator
Affiliation
Stanford University
Other Primary Investigator(s)
Additional Trial Information
Status
In development
Start date
2020-11-28
End date
2021-02-28
Secondary IDs
Abstract
We designed a field experiment in the United States to evaluate how the price sensitivity and sensitivity to provider personal characteristics of consumers of medical care change under an environment with richer information on provider quality compared to an environment without such information. Our motivation stems from the facts that evidence on whether healthcare consumers are price sensitive remain largely equivocal, while the evidence on the nature of consumer racial and gender discrimination of healthcare provider remain scant. More broadly, our study will shed light on the little known aspects of consumer behavior and preferences of the 30M+ uninsured Americans. We will launch a large-scale choice-based conjoint survey experiment with real stakes with actual healthcare consumers. Finally, this experiment will contribute to the important topic if healthcare consumerism.
External Link(s)
Registration Citation
Citation
Chan, Alex. 2020. "Consumer Decision-making When Shopping for Medical Services ." AEA RCT Registry. November 30. https://doi.org/10.1257/rct.6815-1.0.
Sponsors & Partners

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Experimental Details
Interventions
Intervention(s)
We compare consumer behavior with incentivized choice-based conjoint surveys. In the control group, the incentivized choice-based conjoint surveys does not include a provider quality score ("Comprehensive Quality Score") as a feature in the conjoint profiles. In the treatment group, the incentivized choice-based conjoint surveys includes a provider quality score ("Comprehensive Quality Score") as a feature in the conjoint profiles.
Intervention Start Date
2020-11-30
Intervention End Date
2021-02-28
Primary Outcomes
Primary Outcomes (end points)
Patient preferences for providers of medical services measured using discrete choice experiments. A key "outcome" variable is the probability a patient prefers a provider profile.
Primary Outcomes (explanation)
The probability a patient prefers a provider profile includes both (1) provider profiles that are hypothetical in incentivized discrete choice experiments, and (2) provider profiles that are real profiles in actual consumer shopping scenarios
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
We conduct hypothetical discrete choice experiments (choice-based conjoint) to measure the baseline effects of price, distance, provider characteristics (e.g. gender and race) among subjects. A choice-based conjoint in a survey design in which respondents are offered the choice between sets of options represented by combinations of attributes and features. In our design, the choice-based conjoint experiment is incentivized by making the list of 10 actual provider options (out of hundreds) made available to the subject for actual purchasing contingent on the subject's responses to the choice-based conjoint. We conduct information treatments (quality information) to see the effects of differential treatments on consumer preferences overall and the consumer sensitivity of provider features (price, gender/race, distance). Treatment heterogeneity will be investigated along subject characteristics like demographics, socioeconomic status, location, subjective interpretation of the quality metric, subjective interpretation of the relationship between quality and travel distance and procedure type (all variables we will gather as part of the experiment). An actual shopping action could be executed by the consumer and this actual transaction data will be used to estimate consumer preferences, validate the choice model estimated using the hypothetical profiles-based discrete choice experiment and evaluate incentive compatibility properties.
Experimental Design Details
Not available
Randomization Method
Randomization done by Qualtrics' Randomizer element to assign respondents to either a control block of questions or an experimental block of questions
Randomization Unit
Individual
Was the treatment clustered?
No
Experiment Characteristics
Sample size: planned number of clusters
Approx. 300-600 patients shopping for one of the 3 medical procedures between December 2020 to February 2021
Sample size: planned number of observations
Approx. 300-600 patients shopping for one of the 3 medical procedures between December 2020 to February 2021
Sample size (or number of clusters) by treatment arms
50% of 300-600 patients shopping for one of the 3 medical procedures between December 2020 to February 2021 will be in the treatment arm and the other 50% in the control arm
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
IRB Approval Date
IRB Approval Number