• Arch. Pathol. Lab. Med. · Dec 2013

    Inpatient preanalytic process improvements.

    • Elizabeth A Wagar, Ron Phipps, Robert Del Guidice, Lavinia P Middleton, John Bingham, Cheryl Prejean, Martha Johnson-Hamilton, Pheba Philip, Ngoc Han Le, and Waheed Muses.
    • From the Departments of Laboratory Medicine (Dr Wagar, Messrs Del Guidice and Muses, and Ms Prejean), Pathology and Laboratory Medicine Quality Improvement (Mr Phipps and Ms Han Le and Ms Johnson-Hamilton), Pathology (Dr Middleton), Performance Improvement (Mr Bingham), and Quality Measurement and Engineering (Ms Philip), University of Texas MD Anderson Cancer Center, Houston. Mr Muses is now with the National Guard Health Affairs, Imam Abdulrahman Bin Feisal Hospital, Dammam, Kingdom of Saudi Arabia.
    • Arch. Pathol. Lab. Med. 2013 Dec 1; 137 (12): 1753-60.

    ContextPhlebotomy services are a common target for preanalytic improvements. Many new, quality engineering tools have recently been applied in clinical laboratories. However, data on relatively few projects have been published. This example describes a complete application of current, quality engineering tools to improve preanalytic phlebotomy services.ObjectivesTo decrease the response time in the preanalytic inpatient laboratory by 25%, to reduce the number of incident reports related to preanalytic phlebotomy, and to make systematic process changes that satisfied the stakeholders.DesignThe Department of Laboratory Medicine, General Services Section, at the University of Texas MD Anderson Cancer Center (Houston) is responsible for inpatient phlebotomy in a 24-hour operation, which serves 689 inpatient beds. The study director was project director of the Division of Pathology and Laboratory Medicine's Quality Improvement Section and was assisted by 2 quality technologists and an industrial engineer from MD Anderson Office of Performance Improvement.ResultsAfter implementing each solution, using well-recognized, quality tools and metrics, the response time for blood collection decreased by 23%, which was close to meeting the original responsiveness goal of 25%. The response time between collection and arrival in the laboratory decreased by 8%. Applicable laboratory-related incident reports were reduced by 43%.ConclusionsComprehensive application of quality tools, such as statistical control charts, Pareto diagrams, value-stream maps, process failure modes and effects analyses, fishbone diagrams, solution prioritization matrices, and customer satisfaction surveys can significantly improve preset goals for inpatient phlebotomy.

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