Technical and administrative review of a lab analysis by a second qualified scientist, also known as peer review, takes a significant amount of time and reduces the peer-review scientist's ability to perform other tasks. Peer review of all (100 percent) of lab reports has become the standard in many forensic laboratories. The goal of these reviews is to eliminate Type 1 and Type 2 errors. A Type 1 error occurs when the data or conclusion incorrectly associates two samples or incorrectly identifies a substance. Type 2 errors occur when the analysis fails to associate samples or identify a substance. The current study examined cases completed at the Georgia Bureau of Investigation (GBI) Division of Forensic Sciences in the forensic disciplines of Chemistry (drug identification reports), Toxicology, Firearms, and Latent Prints. The study's design and methods are first described in this report, including data analysis. This is followed by a statement of study findings and their implications for criminal justice policy and practice in the United States. Based on the study findings, the GBI laboratory continues to review all drug identification reports with 25 or more pages in the technical record and 10 percent of reports with less than 25 pages in the technical record. All reports completed by analysts in supervised casework are reviewed, and all reports not previously reviewed are reviewed prior to court testimony. This protocol will be continually monitored, and the auto-release of cases will be halted or adjusted as needed in order to ensure the highest quality of work product. 4 tables
Evaluation of Peer Review and Verification Processes and Evaluation of an Enhanced Screening Technique for Toxicological Specimens with High Resolution Accurate Mass Spectrometer
NCJ Number
254412
Date Published
December 2018
Length
17 pages
Annotation
This is the Final Summary Overview of the findings and methodology of a study that tested the hypothesis that conducing 100-percent technical and administrative review is the most effective approach to minimizing Type 1 and Type 2 errors in forensic lab analysis.
Abstract
Date Published: December 1, 2018