The Value of Radio Frequency Identification in Quality Management of the Blood Transfusion Chain in an Academic Hospital Setting
Bibliographic record
Abstract
BACKGROUND: A complex process like the blood transfusion chain could benefit from modern technologies such as radio frequency identification (RFID). RFID could, for example, play an important role in generating logistic and temperature data of blood products, which are important in assessing the quality of the logistic process of blood transfusions and the product itself. OBJECTIVE: This study aimed to evaluate whether location, time stamp, and temperature data generated in real time by an active RFID system containing temperature sensors attached to red blood cell (RBC) products can be used to assess the compliance of the management of RBCs to 4 intrahospital European and Dutch guidelines prescribing logistic and temperature constraints in an academic hospital setting. METHODS: An RFID infrastructure supported the tracking and tracing of 243 tagged RBCs in a clinical setting inside the hospital at the blood transfusion laboratory, the operating room complex, and the intensive care unit within the Academic Medical Center, a large academic hospital in Amsterdam, the Netherlands. The compliance of the management of 182 out of the 243 tagged RBCs could be assessed on their adherence to the following guidelines on intrahospital storage, transport, and distribution: (1) RBCs must be preserved within an environment with a temperature between 2°C and 6°C; (2) RBCs have to be transfused within 1 hour after they have left a validated cooling system; (3) RBCs that have reached a temperature above 10°C must not be restored or must be transfused within 24 hours or else be destroyed; (4) unused RBCs are to be returned to the BTL within 24 hours after they left the transfusion laboratory. RESULTS: In total, 4 blood products (4/182 compliant; 2.2%) complied to all applicable guidelines. Moreover, 15 blood products (15/182 not compliant to 1 out of several guidelines; 8.2%) were not compliant to one of the guidelines of either 2 or 3 relevant guidelines. Finally, 148 blood products (148/182 not compliant to 2 guidelines; 81.3%) were not compliant to 2 out of the 3 relevant guidelines. CONCLUSIONS: The results point out the possibilities of using RFID technology to assess the quality of the blood transfusion chain itself inside a hospital setting in reference to intrahospital guidelines concerning the storage, transport, and distribution conditions of RBCs. This study shows the potentials of RFID in identifying potential bottlenecks in hospital organizations' processes by use of objective data, which are to be tackled in process redesign efforts. The effect of these efforts can subsequently be evaluated by the use of RFID again. As such, RFID can play a significant role in optimization of the quality of the blood transfusion chain.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".