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Redefining the Practice of Peer Review Through Intelligent Automation Part 1: Creation of a Standardized Methodology
1Department of Radiology, Veterans Affairs Maryland Healthcare System, 10 North Greene Street, Baltimore, MD, 21201, USA. breiner1@comcast.net.
Journal of Digital Imaging
|July 27, 2017
Summary
Conventional peer review is flawed by biases and lacks objectivity. A proposed new model uses blinding, independent reporting, and automated analysis to improve medical malpractice determination and create a standardized database for education and decision support.
Area of Science:
- Medical research methodology
- Healthcare quality improvement
- Legal medicine
Background:
- Conventional peer review is susceptible to biases, hindering accurate standard of care analysis crucial for medical malpractice cases.
- Current peer review processes suffer from a lack of standardization, objectivity, and automation, limiting their effectiveness.
Purpose of the Study:
- To propose an alternative peer review model designed to overcome the limitations of conventional practices.
- To enhance the objectivity and standardization of peer review for medical malpractice determination.
Main Methods:
- The proposed model incorporates complete blinding of peer reviewers.
- It mandates independent reporting from all parties involved.
- Automated data mining techniques are utilized for neutral analysis and data reconciliation.
Main Results:
- Implementation of this model can lead to a standardized and referenceable peer review database.
- Objective analysis of reports and resolution of differences are facilitated.
- Potential for improved accuracy in standard of care assessments.
Conclusions:
- This novel peer review model offers a more objective and standardized approach to evaluating medical practices.
- It has the potential to significantly improve the determination of medical malpractice.
- The resulting database can support customized education, technological advancements, and real-time decision support systems.
