Returns to Physician Human Capital

Last registered on October 24, 2016

Pre-Trial

Trial Information

General Information

Title
Returns to Physician Human Capital
RCT ID
AEARCTR-0001614
Initial registration date
October 24, 2016

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
October 24, 2016, 1:11 AM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Locations

Primary Investigator

Affiliation
MIT

Other Primary Investigator(s)

PI Affiliation
VA Palo Alto and Stanford
PI Affiliation
University of Wisconsin-Madison

Additional Trial Information

Status
Completed
Start date
1993-01-01
End date
2006-12-31
Secondary IDs
Abstract
Physicians play a major role in determining the cost and quality of healthcare, yet estimates of these effects can be confounded by patient sorting. This paper considers a natural experiment where nearly 30,000 patients were randomly assigned to clinical teams from one of two academic institutions. One institution is among the top medical schools in the U.S., while the other institution is ranked lower in the distribution. Patients treated by the two programs have similar observable characteristics and have access to a single set of facilities and ancillary staff. Those treated by physicians from the higher ranked institution have 10-25% less expensive stays than patients assigned to the lower ranked institution. Health outcomes are not related to the physician team assignment. Cost differences are most pronounced for serious conditions, and they largely stem from diagnostic-testing rates: the lower ranked program tends to order more tests and takes longer to order them.

Registration Citation

Citation
Doyle, Joseph, Steven M. Ewer and Todd H. Wagner. 2016. "Returns to Physician Human Capital." AEA RCT Registry. October 24. https://doi.org/10.1257/rct.1614
Former Citation
Doyle, Joseph, Steven M. Ewer and Todd H. Wagner. 2016. "Returns to Physician Human Capital." AEA RCT Registry. October 24. https://www.socialscienceregistry.org/trials/1614/history/11419
Experimental Details

Interventions

Intervention(s)
Patients in a large, urban Veterans Affairs (VA) hospital were randomly assigned to one of two teams of clinicians from two academic institutions:

1) Program A: higher ranked team of clinicians
2) Program B: lower ranked team of clinicians

Higher vs. lower rank was determined by statistics from US News and World Report, American Board of Internal Medicine, American Board of Surgery, and AMA Masterfile.
Intervention Start Date
1993-01-01
Intervention End Date
2006-12-31

Primary Outcomes

Primary Outcomes (end points)
readmission to hospital, mortality, length of stay, accounting cost, and estimated expenditures
Primary Outcomes (explanation)
1) Readmission to hospital: 30 days and one year readmission to hospital
2) Mortality: 30 day, 1 year, and 5 year patient mortality

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
This paper considers a unique natural experiment in a large, urban Department of Veterans Affairs (VA) hospital, where nearly 30,000 patients (and over 70,000 admissions) were randomly assigned to teams comprised of clinicians from one of two academic institutions. One team of clinicians (Program A) is ranked higher, relative to the other team of clinicians (Program B). The teams have access to the same facilities, the same nursing staff, and the same specialists for consultations. Comparing patient outcomes across these two groups allows us to estimate effects of physicians on costs and health outcomes, i.e. returns to physician human capital.
Experimental Design Details
Randomization Method
Patients' social security numbers: odd SSN patients were assigned to Program A, and even SSN patients were assigned to Program B.
Randomization Unit
30,000 patients
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
No clusters.
Sample size: planned number of observations
30,000 patients
Sample size (or number of clusters) by treatment arms
35,932 inpatient stays Program A, 36,434 inpatient stays Program B
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

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
Yes
Intervention Completion Date
December 31, 2006, 12:00 +00:00
Data Collection Complete
Yes
Data Collection Completion Date
December 31, 2006, 12:00 +00:00
Final Sample Size: Number of Clusters (Unit of Randomization)
No cluster.
Was attrition correlated with treatment status?
No
Final Sample Size: Total Number of Observations
30,000 patients
Final Sample Size (or Number of Clusters) by Treatment Arms
35,932 inpatient stays Program A, 36,434 inpatient stays Program B
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
No
Reports, Papers & Other Materials

Relevant Paper(s)

Abstract
Physicians play a major role in determining the cost and quality of healthcare, yet estimates of these effects can be confounded by patient sorting. This paper considers a natural experiment where nearly 30,000 patients were randomly assigned to clinical teams from one of two academic institutions. One institution is among the top medical schools in the U.S., while the other institution is ranked lower in the distribution. Patients treated by the two programs have similar observable characteristics and have access to a single set of facilities and ancillary staff. Those treated by physicians from the higher ranked institution have 10-25% less expensive stays than patients assigned to the lower ranked institution. Health outcomes are not related to the physician team assignment. Cost differences are most pronounced for serious conditions, and they largely stem from diagnostic-testing rates: the lower ranked program tends to order more tests and takes longer to order them.
Citation
Doyle, Jr., Joseph J., Steven M. Ewer, and Todd H. Wagner. 2010. “Returns to physician human capital: Evidence from patients randomized to physician teams.” Journal of Health Economics 29: 866–882.

Reports & Other Materials