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1.
Biopreserv Biobank ; 15(1): 31-36, 2017 Feb.
Article in English | MEDLINE | ID: mdl-27860489

ABSTRACT

This article discusses the evolution of the University of Pittsburgh (UPitt) Health Sciences Tissue Bank (HSTB) operation and how it has successfully positioned itself, manages to sustain its value, and remains viable in today's research landscape. We describe the various components of our biobanking operation, which are valued by our researchers, thus leading to sustainability for our biorepository. Operating within the infrastructure of a large academic university, we have access to the most cutting-edge database resources for collecting, tracking, and annotating thousands of specimens. We are constantly improving upon our ability to provide real-time longitudinal follow-up data for our collections, thus providing researchers with valuable, highly annotated research specimens. We believe the combination of all that is described within this article helps to create a biobank that will remain sustainable well into the future.


Subject(s)
Biological Specimen Banks/standards , Cooperative Behavior , Data Mining , Humans , Registries
2.
J Pathol Inform ; 2: 42, 2011.
Article in English | MEDLINE | ID: mdl-21969923

ABSTRACT

BACKGROUND: Quality assurance (QA) programs in cytopathology laboratories in the USA currently primarily involve the review of Pap tests per clinical laboratory improvement amendments of 1988 federal regulations. A pre-signout quality assurance tool (PQAT) at our institution allows the laboratory information system (LIS) to also automatically and randomly select an adjustable percentage of non-gynecological cytopathology cases for review before release of the final report. The aim of this study was to review our experience and the effectiveness of this novel PQAT tool in cytology. MATERIALS AND METHODS: Software modifications in the existing LIS application (CoPathPlus, Cerner) allow for the random QA of 8% of cases prior to signout. Selected cases are assigned to a second QA cytopathologist for review and all agreement and disagreements tracked. Detected errors are rectified before the case is signed out. Data from cases selected for PQAT over an 18-month period were collected and analyzed. RESULTS: The total number of non-gynecological cases selected for QA review was 1339 (7.45%) out of 17,967 cases signed out during this time period. Most (1304) cases (97.4%) had an agreement in diagnosis. In 2.6% of cases, there were disagreements, including 34 minor and only 1 major disagreement. Average turnaround time of cases selected for review was not significantly altered. CONCLUSION: The PQAT provides a prospective QA mechanism in non-gynecological cytopathology to prevent diagnostic errors from occurring. This LIS-driven tool allows for peer review and corrective action to be taken prior to reporting without delaying turnaround time, thereby improving patient safety.

3.
Am J Surg Pathol ; 34(9): 1319-23, 2010 Sep.
Article in English | MEDLINE | ID: mdl-20697250

ABSTRACT

We recently implemented a novel pre-sign-out quality assurance tool in our subspecialty-based surgical pathology practice at the University of Pittsburgh Medical Center. It randomly selects an adjustable percentage of cases for review by a second pathologist at the time the originating pathologist's electronic signature is entered and requires that the review be completed within 24 hours, before release of the final report. The tool replaced a retrospective audit system and it has been in successful use since January 2009. We report our initial experience for the first 14 months of its service. During this time, the disagreement numbers and levels were similar to those identified using the retrospective system, case turnaround time was not significantly affected, and the number of case amendments generated decreased. The tool is a useful quality assurance instrument and its prospective nature allows for the potential prevention of some serious errors.


Subject(s)
Clinical Laboratory Information Systems , Pathology, Surgical/standards , Peer Review/methods , Quality Assurance, Health Care , Hospitals, University/standards , Humans , Medical Errors/prevention & control , Workflow
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