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Is expert peer review obsolete? A model suggests that post-publication reader review may exceed the accuracy of traditional peer review

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Abstract

Background

The peer review process is the gold standard by which academic manuscripts are vetted for publication. However, some investigators have raised concerns regarding its unopposed supremacy, including lack of expediency, susceptibility to editorial bias and statistical limitation due to the small number of reviewers used. Post-publication review—in which the article is assessed by the general readership of the journal instead of a small group of appointed reviewers—could potentially supplement or replace the peer-review process. In this study, we created a computer model to compare the traditional peer-review process to that of post-publication reader review.

Methods

We created a mathematical model of the manuscript review process. A hypothetical manuscript was randomly assigned a “true value” representing its intrinsic quality. We modeled a group of three expert peer reviewers and compared it to modeled groups of 10, 20, 50, or 100 reader-reviewers. Reader-reviewers were assumed to be less skillful at reviewing and were thus modeled to be only ¼ as accurate as expert reviewers. Percentage of correct assessments was calculated for each group.

Results

400,000 hypothetical manuscripts were modeled. The accuracy of the reader-reviewer group was inferior to the expert reviewer group in the 10-reviewer trial (93.24% correct vs. 97.67%, p < 0.0001) and the 20-reviewer trial (95.50% correct, p < 0.0001). However, the reader-reviewer group surpassed the expert reviewer group in accuracy when 50 or 100 reader-reviewers were used (97.92 and 99.20% respectively, p < 0.0001).

Conclusions

In a mathematical model of the peer review process, the accuracy of public reader-reviewers can surpass that of a small group of expert reviewers if the group of public reviewers is of sufficient size. Further study will be required to determine whether the mathematical assumptions of this model are valid in actual use.

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Notes

  1. To achieve a random number in a normal distribution with a standard deviation of n, we used the following Excel formula: NORMSINV(RAND()) * n.

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Acknowledgments

Special Thanks are extended to Dr. David Urbach, MD, MSc, FACS, FRCSC from the Departments of Surgery and Health Policy in the University of Toronto for his assistance with details of the experimental model.

Disclosure

Dr. Herron holds stock options in Hourglass Technology.

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Authors and Affiliations

  1. Mount Sinai School of Medicine, 1 Gustave L. Levy Place, #1259, New York, NY, 10029, USA

    Daniel M. Herron

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  1. Daniel M. Herron
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Correspondence to Daniel M. Herron.

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Herron, D.M. Is expert peer review obsolete? A model suggests that post-publication reader review may exceed the accuracy of traditional peer review. Surg Endosc 26, 2275–2280 (2012). https://doi.org/10.1007/s00464-012-2171-1

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  • DOI: https://doi.org/10.1007/s00464-012-2171-1

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