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Related Concept Videos

Bone Marrow Sampling and Transplants01:22

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Bone marrow transplant is a potential cure for several diseases, including cancer and specific genetic disorders. Notably, this procedure is applicable for patients suffering from aplastic anemia, certain types of leukemia, severe combined immunodeficiency disease (SCID), Hodgkin's disease, non-Hodgkin's lymphoma, multiple myeloma, thalassemia, sickle-cell disease, and certain cancers.
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Integration of Wet and Dry Bench Processes Optimizes Targeted Next-generation Sequencing of Low-quality and Low-quantity Tumor Biopsies
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Optimizing personalized bone marrow testing using an evidence-based, interdisciplinary team approach.

Adam C Seegmiller1, Annette S Kim, Claudio A Mosse

  • 1Depts of Pathology, Microbiology, and Immunology, Vanderbilt University School of Medicine, Room C-3321A, 1161 21st Ave S, Nashville, TN 37232-2561; mary.zutter@vanderbilt.edu.

American Journal of Clinical Pathology
|October 15, 2013
PubMed
Summary
This summary is machine-generated.

Implementing a diagnostic management team reduced unnecessary hematologic malignancy testing, improving efficiency and lowering costs. This approach optimizes complex diagnostic testing for better patient care.

Keywords:
GeneticsHematopathologyInformaticsMolecular diagnostics

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Area of Science:

  • Hematology
  • Oncology
  • Clinical Pathology

Background:

  • Overuse of diagnostic testing in hematologic malignancies increases costs and complicates patient care.
  • Lack of standardized guidelines contributes to suboptimal testing practices.

Purpose of the Study:

  • To implement a diagnostic management team (DMT) to develop and deploy evidence-based guidelines for diagnostic testing in hematologic malignancies.
  • To reduce testing overuse, improve diagnostic quality, and decrease associated costs.

Main Methods:

  • A multidisciplinary DMT developed standard ordering protocols (SOPs) for cytogenetic and molecular testing.
  • SOPs were applied to bone marrow biopsy specimens in adult patients.
  • Testing data from 780 pre-implementation specimens were compared with 1,806 post-implementation specimens.

Main Results:

  • Significant reduction in discordant and omitted tests post-SOP implementation.
  • Increased fraction of positive test results observed.
  • Estimated cost of testing decreased, with clinicians reporting acceptance and time savings.

Conclusions:

  • The diagnostic management team model effectively optimizes complex and personalized diagnostic testing.
  • Implementation of SOPs leads to improved efficiency, reduced costs, and enhanced diagnostic accuracy.