BACKGROUND: Half of the reported serious adverse events from transfusion are a consequence of medical error. A no-fault medical-event reporting system for transfusion medicine (MERS-TM) was developed to capture and analyze both near-miss and actual transfusion-related errors. STUDY DESIGN AND METHODS: A prospective audit of transfusion-related errors was performed to determine the ability of MERS-TM to identify the frequency and patterns of errors. RESULTS: Events and near-miss events (total, 819) were recorded for a period of 19 months (median, 51/month). No serious adverse patient outcome occurred, despite these events, with the transfusion of 17,465 units of RBCs. Sixty-one events (7.4%) were potentially life-threatening or could have led to permanent injury (severity Level 1). Of most concern were 3 samples collected from the wrong patient, 13 mislabeled samples, and 22 requests for blood for the wrong patient. Near-miss events were five times more frequent than actual transfusion errors, and 68 percent of errors were detected before blood was issued. Sixty-one percent of events originated from patient areas, 35 percent from the blood bank, and 4 percent from the blood supplier or other hospitals. Repeat collection was required for 1 of every 94 samples, and 1 in 346 requests for blood components was incorrect. Education of nurses and alterations to blood bank forms were not by themselves effective in reducing severe errors. An artifactual 50-percent reduction in the number of errors reported was noted during a 6-month period when two chief members of the event-reporting team were on temporary leave. CONCLUSION: The MERS-TM allowed the recognition and analysis of errors, determination of patterns of errors, and monitoring for changes in frequency after corrective action was implemented. Although no permanent injury resulted from the 819 events, innovative mechanisms must be designed to prevent these errors, instead of relying on faulty informal checks to capture errors after they occur.
BACKGROUND: Half of the reported serious adverse events from transfusion are a consequence of medical error. A no-fault medical-event reporting system for transfusion medicine (MERS-TM) was developed to capture and analyze both near-miss and actual transfusion-related errors. STUDY DESIGN AND METHODS: A prospective audit of transfusion-related errors was performed to determine the ability of MERS-TM to identify the frequency and patterns of errors. RESULTS: Events and near-miss events (total, 819) were recorded for a period of 19 months (median, 51/month). No serious adverse patient outcome occurred, despite these events, with the transfusion of 17,465 units of RBCs. Sixty-one events (7.4%) were potentially life-threatening or could have led to permanent injury (severity Level 1). Of most concern were 3 samples collected from the wrong patient, 13 mislabeled samples, and 22 requests for blood for the wrong patient. Near-miss events were five times more frequent than actual transfusion errors, and 68 percent of errors were detected before blood was issued. Sixty-one percent of events originated from patient areas, 35 percent from the blood bank, and 4 percent from the blood supplier or other hospitals. Repeat collection was required for 1 of every 94 samples, and 1 in 346 requests for blood components was incorrect. Education of nurses and alterations to blood bank forms were not by themselves effective in reducing severe errors. An artifactual 50-percent reduction in the number of errors reported was noted during a 6-month period when two chief members of the event-reporting team were on temporary leave. CONCLUSION: The MERS-TM allowed the recognition and analysis of errors, determination of patterns of errors, and monitoring for changes in frequency after corrective action was implemented. Although no permanent injury resulted from the 819 events, innovative mechanisms must be designed to prevent these errors, instead of relying on faulty informal checks to capture errors after they occur.
Authors: Michael P Ast; David J Mayman; Mathias P Bostrom; Alejandro Gonzalez Della Valle; Steven B Haas Journal: Clin Orthop Relat Res Date: 2019-01 Impact factor: 4.176
Authors: Jonathan D Burlison; Robert B McDaniel; Donald K Baker; Murad Hasan; Jennifer J Robertson; Scott C Howard; James M Hoffman Journal: Appl Clin Inform Date: 2018-01-31 Impact factor: 2.342
Authors: Aziz A Boxwala; Meghan Dierks; Maura Keenan; Susan Jackson; Robert Hanscom; David W Bates; Luke Sato Journal: J Am Med Inform Assoc Date: 2004-08-06 Impact factor: 4.497