A Comparison of Four 3-Axis-Accelerometers for Monitoring Hospital Pneumatic Tube Systems.

BACKGROUND: Validation of hospital pneumatic tube systems (PTS) is recommended to predict and prevent errors caused by sample hemolysis. 3-Axis accelerometer dataloggers have been successfully implemented as tools for PTS validation, but the most suitable device for such validation has not been investigated. The aim of this study was to evaluate the performance of four commercially available 3-axis accelerometers for PTS validation. METHODS: PCE-VD3 (PCE), CEM DT-178A (CEM), Extech VB300 (EXT), and MSR 145 (MSR) dataloggers were placed into a single PTS carrier and repeatedly transported through one of three PTS routes. The number and magnitude of accelerations within each PTS route was collected by each device. Deming regression analysis was used to compare device performance. RESULTS: The MSR datalogger captured the greatest number of g-forces >3 g, 5 g, 10 g, and 15 g, and the greatest magnitude of g-force (26.7 g) relative to the other devices (CEM: 23.0 g, EXT: 23.3 g, PCE: 23.7 g). As a result of increased sampling frequency, the MSR recorded the lowest AUC and the greatest number of g-forces exceeding 3 g relative to the other devices. Subjectively, the data were difficult to extract from 4 tested devices. CONCLUSIONS: Commercially available dataloggers differ in their ability to detect the number and magnitude of g-forces within PTSs. We recommend that one device be used to perform all PTS evaluations, with baseline evaluations for tolerable AUC, number, and magnitude of g-forces established internally. Lack of harmonization, cumbersome data processing, and time-consuming data analysis are substantial barriers to universal implementation of dataloggers for PTS validation and monitoring.

Parameters for Validating a Hospital Pneumatic Tube System.

BACKGROUND: Pneumatic tube systems (PTSs) provide rapid transport of patient blood samples, but physical stress of PTS transport can damage blood cells and alter test results. Despite this knowledge, there is limited information on how to validate a hospital PTS. METHODS: We compared 2 accelerometers and evaluated multiple PTS routes. Variabilities in PTS forces over the same routes were assessed. Response curves that demonstrate the relationship between the number and magnitude of accelerations on plasma lactate dehydrogenase (LD), hemolysis index, and potassium in PTS-transported blood from volunteers were generated. Extrapolations from these relationships were used to predict PTS routes that may be prone to false laboratory results. Historical data and prospective patient studies were compared with predicted effects. RESULTS: The maximum recorded g-force was 10g for the smartphone and 22g for the data logger. There was considerable day-to-day variation in the magnitude of accelerations (CV, 4%-39%) within a single route. The linear relationship between LD and accelerations within the PTS revealed 2 PTS routes predicted to increase LD by ≥20%. The predicted increase in LD was similar to that observed in patient results when using that PTS route. CONCLUSIONS: Hospital PTSs can be validated by documenting the relationship between the concentrations of analytes in plasma, such as LD, with PTS forces recorded by 3-axis accelerometers. Implementation of this method for PTS validation is relatively inexpensive, simple, and robust.