A-192 Cause and Departmental Origin of Errors—An Investigation of Questionable Patient Test Results

Abstract Introduction Reliable patient test results are crucial for quality patient care, involving pre-, post- and analytical phases. Questionable Patient test Results (QPRs), either not matching patient clinical presentation or apparent outliers for the patient population, are often encountered. We aimed to investigate the source and nature of possible errors that cause QPRs. Methods 960 QPRs were identified during July-December 2022 at our institution. We examined the nature of the QPRs, the corresponding patient clinical records, the procedures involved in pre-, post- and analytical phases, and quality control systems. Results The QPRs were found to be originated from 31 departments and medical specialty units. Of those, 5 departments/units had >50 QPRs (accounting for 64% of total QPRs) and are listed in the table provided. The table also lists the information on 7 types of errors identified by our analysis. Of all errors, 78% occurred at pre-analytical phase, with the majority of errors occurring during sample collection. Discussion The most common types of errors were either diluted or contaminated samples accounting for 38% and 34%, respectively. Such errors often occur during sample drawing from an existing I.V. access port if not adequately flushed after saline solution infusion (causing sample dilution) or dextrose solution (causing glucose contamination). Many errors were due to samples drawn in the wrong collection tube type. Sample integrity issues included hemolysis, lack of sufficient sample volume, or clotting. For those QPRs that we did not find apparent errors, they were either due to random errors or the results fit the patient’s true medical condition. Conclusions Our findings highlight the importance of pre-analytical quality control measures and the need for regular staff education/training. This study pinpointed the errors that require targeted education materials, as well as the hospital units that would benefit most from this focus on error prevention.