Radio-Frequency Identification Specimen Tracking to Improve Quality in Anatomic Pathology.
Context.-- Preanalytic errors, including specimen labeling errors and specimen loss, occur frequently during specimen collection, transit, and accessioning. Radio-frequency identification tags can decrease specimen identification and tracking errors through continuous and automated tracking of speci...
| Publicado en: | Archives of Pathology & Laboratory Medicine Vol. 144; no. 2; pp. 189 - 196 |
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| Autores principales: | , , , , , , , , , , , |
| Formato: | pictorial research tables/charts Journal Article |
| Publicado: |
College of American Pathologists
Feb2020
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=141449116&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 141449116 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 00039985 1FS jtl: Archives of Pathology & Laboratory Medicine issn: 00039985 maglogo: N pubinfo: dt: Feb2020 vid: 144 iid: 2 pid: 2550 pub: College of American Pathologists place: Northfield, Illinois artinfo: ui: 141449116 141449116 141449116 10.5858/arpa.2019-0011-OA 141449116 ppf: 189 ppct: 7 formats: fmt: @attributes: type: P tig: atl: Radio-Frequency Identification Specimen Tracking to Improve Quality in Anatomic Pathology. aug: au: Norgan, Andrew P. Simon, Kurt E. Feehan, Barbara A. Saari, Lynn L. Doppler, Joseph M. Welder, G. Scott Sedarski, John A. Yoch, Christopher T. Comfere, Nneka I. Martin, John A. Bartholmai, Brian J. Reichard, R. Ross affil: Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota sug: subj: Pathology, Clinical Specimen Handling Radio Frequency Identification Clinical Laboratory Information Systems Quality Improvement Diagnostic Errors Prevention and Control Human Point-of-Care Testing Electronic Health Records Systems Integration Electronic Order Entry ab: Context.-- Preanalytic errors, including specimen labeling errors and specimen loss, occur frequently during specimen collection, transit, and accessioning. Radio-frequency identification tags can decrease specimen identification and tracking errors through continuous and automated tracking of specimens. Objective.-- To implement a specimen tracking infrastructure to reduce preanalytic errors (specimen mislabeling or loss) between specimen collection and laboratory accessioning. Specific goals were to decrease preanalytic errors by at least 70% and to simultaneously decrease employee effort dedicated to resolving preanalytic errors or investigating lost specimens. Design.-- A radio-frequency identification specimen-tracking system was developed. Major features included integral radio-frequency identification labels (radio-frequency identification tags and traditional bar codes in a single printed label) printed by point-of-care printers in collection suites; dispersed radio-frequency identification readers at major transit points; and systems integration of the electronic health record, laboratory information system, and radio-frequency identification tracking system to allow for computerized physician order entry driven label generation, specimen transit time tracking, interval-based alarms, and automated accessioning. Results.-- In the 6-month postimplementation period, 6 mislabeling events occurred in collection areas using the radio-frequency identification system, compared with 24 events in the 6-month preimplementation period (75% decrease; P = .001). In addition, the system led to the timely recovery of 3 lost specimens. Labeling expenses were decreased substantially in the transition from high-frequency to ultrahigh frequency radio-frequency identification tags. Conclusions.-- Radio-frequency identification specimen tracking prevented several potential specimen-loss events, decreased specimen recovery time, and decreased specimen labeling errors. Increases in labeling/tracking expenses for the system were more than offset by time savings and loss avoidance through error mitigation. pubtype: Academic Journal doctype: pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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