Economies of scale in institutional review boards.
BACKGROUND
Research with human subjects is essential for most clinical and social science research. As such, the ethical treatment of subjects, including the role of Institutional Review Boards (IRBs), is of paramount concern. The prevailing system of IRBs in the United States reflects an integrated approach in which research organizations have their own local IRB. Recent regulatory changes and a few high-profile problems have prompted proposals for greater investments in IRBs.


OBJECTIVE
We conducted regression analyses, looking at how IRB size was associated with IRB costs (economies of scale).


METHODS
We studied data from a cross-sectional survey.


METHODS
We studied IRBs at Veterans Affairs (VA) and VA-affiliated medical centers (n = 109); 81 (73%) IRB administrators completed the survey. Fourteen of the administrators had missing data and were excluded from final analysis, leaving a sample of 67.


METHODS
The primary dependent variable was IRB costs in 2001, which we estimated from the survey. Independent variables included IRB size measured as the number of actions (ie, number of initial reviews, amendments, continuing/annual reviews, and harms/adverse event reports) reviewed by the IRB in the last year.


RESULTS
The results indicate that very large economies of scale exist, especially for IRBs that handle fewer than 150 actions per year.


CONCLUSIONS
A discussion of the costs of benefits of having 3000 to 5000 local IRBs in the United States is warranted because other organizational arrangements could be economically and socially advantageous.
Wagner
Todd H
TH
VA Health Economics Resource Center, Stanford University, Stanford, California 94025, USA. twagner@stanford.edu
Cruz
Anne Marie E
AM
Chadwick
Gary L
GL
D002985:Clinical Protocols; D003430:Cross-Sectional Studies; D003625:Data Collection; D028744:Ethics Committees, Research / Q000191:economics* / Q000592:standards; D004991:Ethics, Institutional; D005378:Financial Support; D017721:Hospital Costs / Q000706:statistics & numerical data; D006787:Hospitals, Veterans / Q000191:economics* / Q000941:ethics*; D006805:Human Experimentation / Q000941:ethics*; D006801:Humans; D007449:Investments / Q000191:economics / Q000706:statistics & numerical data*; D012044:Regression Analysis; D014481:United States; D014493:United States Department of Veterans Affairs; D016526:Workload / Q000191:economics