This certificate program is completed online, at your own pace, within ADLM’s learning platform. It must be completed within one year of the purchase date.
PROGRAM DESCRIPTION
This program focuses on the principles and applications of good statistical quality control (QC) practices. Its aim is to explain how QC works, explain what errors interpretive rules are designed to detect, and suggest appropriate investigations for QC failures. Minimal mathematical or statistical theories are presented, as the emphasis is on practical and implementable practices and an explanation of why these practices are suggested.
Quality control topics not expressly covered in this certificate program include: an Individual Quality Control Plan (IQCP), control processes that may be "built in" to a measurement system, preparing in-house QC material, using patient results as a QC parameter, or assessing if a measurement procedure is fit for its intended use in clinical care.
TARGET AUDIENCE
Lab Supervisors, Lab Directors (and/or assistant directors), Lab Managers (supervisory and/or non-supervisory), Medical Technologists, In-Training Individuals
LEARNING OBJECTIVES
- Explain the basic terminology used in QC, discuss how the medical requirements of test results are established, describe measurement procedure performance, and explain the statistical quality control process.
- Discuss considerations to select QC materials, explain the process to establish control values, list five sources of variability when establishing control values, and describe the steps necessary to evaluate a new reagent lot.
- List four possible outcomes of a QC measurement, describe common QC rules, explain a power function graph and how it can identify appropriate QC rules, and describe the cumulative sum procedure which can be used to identify analytical trends.
- Explain how to implement QC strategy design principles, explain QC strategy considerations, explain QC scheduling risk and the risk of unacceptable patient results, and describe how to implement effective QC scheduling practices.
- Investigate QC failures, establishes a process for responding to QC failures, and identify patient results that need to be corrected after a QC failure.
- Describe the parameters that should be included in the daily, weekly, and monthly review of QC data, explain the management of QC for multiple analyzers, and explain how to utilize ongoing assessment of a QC program to optimize error detection.
- Explain the value of external assessment, explain the limitations of proficiency testing, describe how to appropriately measure and report results from EQA/PT, and explain how to correctly interpret results from an EQA/PT program.
COURSES & FACULTY
The program is composed of seven courses, listed below. Each course can be completed online in approximately 1-2 hours and contains a lecture, readings, resources, and a quiz.
- Overview and Basic Concepts of Quality Control
Greg Miller, PhD, DABCC, Virginia Commonwealth University, Richmond, VA
- Establishing QC Parameters for a Test Procedure
M. Laura Parnas, PhD, DABCC, FADLM, Sutter Health, Livermore, CA
- Using QC to Assess Performance of a Test Procedure
David G. Grenache, PhD, DABCC, FADLM University of Utah and ARUP Laboratories, Salt Lake City, UT
- Frequency to Measure QC Samples
Curtis Parvin, PhD, Bio-Rad Laboratories, El Paso, TX
- Responding to Out of Control Situations
Nikola Baumann, PhD, DABCC, Mayo Clinic, Rochester, MN
- Reviewing QC Data
David G. Grenache, PhD, DABCC, FADLM & Nikola Baumann, PhD, DABCC
- External Quality Assessment/Proficiency Testing
Greg Miller, PhD, DABCC
DISCLOSURES
The Association for Diagnostics & Laboratory Medicine (formerly AACC) is dedicated to ensuring balance, independence, objectivity, and scientific rigor in all educational activities. All participating planning committee members and faculty are required to disclose to the program audience any financial relationships related to the subject matter of this program. Disclosure information is reviewed in advance in order to manage and resolve any possible conflicts of interest. The intent of this disclosure is to provide participants with information on which they can make their own judgments.
The following planners and faculty reported relevant financial relationship(s) and have indicated that those relationships would not impact the content of the activity:
- Greg Miller, PhD, DABCC
Salary/Consultant Fee: Abbott Laboratories
- Curtis Parvin, PhD
Honoraria: Bio-Rad Laboratories
The following planners and faculty reported no relevant financial relationships:
- M. Laura Parnas, PhD, DABCC, FADLM
- David G. Grenache, PhD, DABCC, FADLM
- Nikola Baumann, PhD, DABCC
CONTENT VALIDITY
All recommendations involving clinical medicine are based on evidence accepted within the profession of medicine as adequate justification for their indications and contraindications in the care of patients; AND/OR all scientific research referred to or reported in support or justification of a patient care recommendation conforms to generally accepted standards of experimental design, data collection, and analysis.
ACCREDITATION STATEMENT
This activity is approved for 10.0 ACCENT® continuing education credits. Activity ID #4156. This activity was planned in accordance with ACCENT Standards and Policies.
SUCCESFUL COMPLETION STATMENT
Verification of Participation certificates are provided to registered participants based on completion of the activity, in its entirety, and the activity evaluation. The evaluation link will be emailed to the participants after all work within ADLM’s learning platform is complete. For questions regarding continuing education, please email [email protected].
METHODS OF SUPPORT
This educational activity is sponsored by Bio Rad.
Program Launch Year: 2014