title: The Medical Event Reporting System for Transfusion Medicine: will it help get the right blood to the right patient?
abstract: The Medical Event Reporting System for Transfusion Medicine (MERS-TM) collects, classifies, and analyzes events that potentially could compromise the safety of transfused blood to facilitate system improvement. This system is designed to collect data on near misses as well as actual events. Near-miss events are a valuable source of data because they occur more frequently than, but share many characteristics and causes of, actual events. Further, although most current reporting efforts describe only what has occurred with little attention to what caused the event, MERS-TM includes a standardized method of causal analysis. The standardization provided by MERS allows users to compare their experience with that of other organizations, which speeds learning across the entire transfusion medicine community. Important features of the MERS-TM system are that it is able to capture threats, hazards, near misses, injuries, and deaths; characterizes failures and recoveries systematically; identifies and provides causal codes for the entire range of system defects including technical, organizational, cultural, and human factors; raises staff awareness about error management; is easily integrated with existing quality assurance programs; has a consistent and straightforward classification method; enables compliance with mandatory Food and Drug Administration reporting and accreditation requirements; has features to deal with a high volume of reports; supplies Web-based training, data entry, and analysis; and provides comparative benchmarks from comparable institutions.
authors.affiliation: New York Presbyterian Hospital and Columbia University, Harkness Pavilion 4-418, 622 West 168th Street, New York, NY 10032, USA.
authors.forename: Harold S
authors.initials: HS
authors.lastname: Kaplan
authors.forename: Jeannie L
authors.initials: JL
authors.lastname: Callum
authors.forename: Barbara
authors.initials: B
authors.lastname: Rabin Fastman
authors.forename: Lisa L
authors.initials: LL
authors.lastname: Merkley
mesh_terms: D001803:Blood Transfusion; D015984:Causality; D003625:Data Collection; D003628:Database Management Systems; D006801:Humans; D019300:Medical Errors / Q000517:prevention & control* / Q000639:trends; D018570:Risk Assessment; D012308:Risk Management / Q000145:classification / Q000379:methods / Q000592:standards*