Related Experiment Video
Updated: May 1, 2026

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
Published on: May 15, 2020
A prospective tool for risk assessment of sendout testing
Bonnie Cole1, Jane A Dickerson2, Mark L Graber3
1Department of Laboratories, Seattle Children's Hospital, Seattle, WA, United States; Department of Pathology, University of Washington, Seattle, WA, United States.
Objective:
Errors associated with laboratory testing can cause significant patient harm. Sendout testing refers to tests sent by a primary lab to a reference lab when testing is unavailable at the primary lab. Sendout testing is particularly high risk for patient harm, due to many factors including increased hand-offs, manual processes, and complexity associated with rare, low-volume tests. No published prospective tools exist for sendout risk assessment.
Methods:
A novel prospective tool was developed to assess risk of diagnostic errors involving laboratory sendout testing. This tool was successfully piloted at nine sites.
Results:
Marked diversity was noted among survey respondents, particularly in the sections on quality metrics and utilization management. Of note, most sites had committees who managed rules for test ordering, but few places reported enforcing these rules. Only one site claimed to routinely measure the frequency clinicians failed to retrieve test results. An evaluation of the tool indicated that it was both useful and easy to use.
Conclusions:
This tool could be used by other laboratories to identify the areas of highest risk to patients, which in turn may guide them in focusing their quality improvement efforts and resources.
Related Concept Videos
Significance Testing: Overview
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
Testing a Claim about Population Proportion
There are two methods of testing a claim about a population proportion: (1) Using the sample proportion from the data where a binomial distribution is approximated to the normal distribution and (2) Using the binomial probabilities calculated from the data.
The first method uses normal distribution as an approximation to the binomial distribution. The requirements are as follows: sample size is large...
Receiver Operating Characteristic Plot
Quantifying and Rejecting Outliers: The Grubbs Test
Sensitivity, Specificity, and Predicted Value
Sensitivity is the...

