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A 1.5 Hour Procedure for Identification of Enterococcus Species Directly from Blood Cultures
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Patient identification errors: the detective in the laboratory.

Maria Salinas1, Maite López-Garrigós, Rosa Lillo

  • 1Clinical Laboratory Department, Hospital Universitario de San Juan, San Juan de Alicante, Spain; Biochemistry and Molecular Pathology Department, Universidad Miguel Hernandez, Elche, Spain.

Clinical Biochemistry
|August 21, 2013
PubMed
Summary

Patient identification errors in Laboratory Information Systems (LIS) persist despite electronic ordering. Error rates varied significantly between primary care centers (PCC), indicating a continued reliance on personnel for accuracy.

Keywords:
GPHISLISLaboratory managementPCCPatient identification errorPatient safetySOPepmerrors per milliongeneral practitionerhospital information systemlaboratory information systempatients from several originsprimary care centers

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Area of Science:

  • Medical Laboratory Science
  • Patient Safety
  • Health Informatics

Background:

  • Patient identification errors are a critical concern for healthcare safety.
  • Clinical laboratories significantly impact patient care decisions (70%).
  • This study investigated demographic data errors within a Laboratory Information System (LIS).

Purpose of the Study:

  • To quantify Laboratory Information System (LIS) demographic data errors over one year.
  • To identify factors contributing to these errors.
  • To assess the impact of electronic ordering on error rates.

Main Methods:

  • Analysis of demographic data errors in LIS over a 12-month period.
  • Comparison of error rates between manual registration and electronic ordering.
  • Evaluation of data from inpatients and outpatients, including primary care centers (PCC).

Main Results:

  • Electronic ordering led to fewer demographic data errors compared to manual registration.
  • Significant variability in error rates was observed among different primary care centers (PCC) even with electronic ordering.
  • Errors were still detected despite the implementation of electronic ordering systems.

Conclusions:

  • Errors in LIS demographic data are influenced by patient origin and the method of test request.
  • Electronic ordering reduces but does not eliminate demographic data errors.
  • Personnel and their interaction with technology play a crucial role in error reduction, as evidenced by inter-PCC variability.