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Rutgers SHP Requirements for Graduation and Course Descriptions

Department of Clinical Laboratory Sciences/Medical Laboratory Sciences

Clinical Laboratory Science

CLSC5213 - Clinical Laboratory Data Analysis

Course Description

This course provides a foundation for participation in planning, application, and evaluation of a program of laboratory medicine quality management and improvement. Assignments will apply theoretical concepts to clinical laboratory data analysis situation.

Credits/Modes of Instruction

Credits: 3

Participants should anticipate spending approximately 135 hours on the course, or an average of at least 9 hours per week for 15 weeks. This includes online and off-line activities. Various active teaching/learning strategies and techniques will be utilized via Internet delivery of the course. Modes of instruction and course format may include posted lectures, questions for online discussion, critical thinking activities, directed study, and Internet-enhanced reading assignments.

Prerequisites

Baccalaureate degree with previous course work in statistics and work experience in a clinical laboratory required.

Course Goals and Outcomes:

Goals

Provide students with a stable foundation with which to identify and implement a well- informed quality control program.

Outcomes

Upon completion of the course, the student will be able to:
Explain the difference between parametric and non-parametric statistical tests.
Describe measures of central tendency.
Describe a normal distribution.
List assumptions of the major statistical tests.
Explain power analysis and why it is used.
List the five components of power analysis.
Differentiate between the tests that explore relationships.
Differentiate between the tests that explore differences between groups.
Define the control rules commonly used in the multirole QC procedure.
Analyze and evaluate QC data.
Interpret Multirule QC results across and within materials and across and within analytical runs.
Predict the type of analytical error expected on the basis of control rule violations.
Describe the common need for error assessment in the evaluation of both analytical performance and diagnostic performance.
Differentiate and perform calculations with the measures of diagnostic accuracy.
Apply measures of diagnostic accuracy in the interpretation of test performance and post-test probability of diseases.
Describe the relevance of diagnostic accuracy to evaluate the role of a test in the clinical context.
Describe the concept of calculated "error" as related to method evaluation.
Define random, systematic error and total error.
Explain the difference between constant and proportional systematic error.
Explain the purpose/protocol, usefulness and limitations of linear regression, correlation coefficient, F test.
From laboratory data, calculate and interpret findings of linear regression (m, b, Sy/x), correlation coefficient, F-test, random error, systematic error, and total error statistics.
Describe what is meant by clinical significance, and how statistical findings relate to it.
Explain the principle/purpose of recovery, interference, and linearity studies.
Describe the utility and limitations of the t-test and chi square calculations in relation to evaluating laboratory data, list the type of hypotheses being tested, and given a data set, calculate the observed t and/or chi square.
Demonstrate appropriate decisions regarding the observed vs critical t or chi square values relating to hypotheses.
Relate t and or chi square results to select problems or data sets.
Compare and contrast statistical vs clinical significance.
Describe how proficiency testing is regulated.
Access CLIA online and locate the subparts defining the proficiency testing requirements.
Demonstrate an understanding of how tests are categorized under CLIA and how those impacts regulations.
Define the proficiency testing program standards and requirements by test specialty.
Compare the criteria of acceptable performance for regulated analytes - concentration, percent, and SD.
Demonstrate an understanding of the criteria for being an approved proficiency testing provider.
List currently approved proficiency testing providers.
Identify tools that accrediting agencies use to assess proficiency testing program compliance.
List the steps in the total testing process required upon a proficiency testing shipment receipt.
Analyze proficiency testing evaluation reports.
Describe the utility of participant data summary report when reviewing proficiency testing results.
Conduct proficiency testing investigations using “Proficiency Testing Investigation and Corrective Action Form” as a guide.
Analyze sample before-and-after quality improvement data using statistical software and the statistical process control chart approach.
Through a guided final project, develop a description of your laboratory-wide quality assessment plan, identify and describe quality plan goals, definitions, standards, and regulatory/accrediting organizations; quality plan components and processes that support achievement of quality goals; data sources for monitoring quality; key standards, guidelines, and strategies relevant to quality plan implementation; quality indicators/metrics (list, define, and prioritize, and indicate performance targets), and how they are implemented for process and outcomes assessment; how assessment findings are used to support achievement of quality goals.
Through a guided final project, develop a description of an original proposal for a quality improvement study; Identify and describe a well-defined quality issue capable of measurable improvement in the context of 1) the laboratory's quality plan, 2) an analytic framework, 3) a quality improvement framework, and 4) a quality improvement study design.
Identify and describe a quality improvement intervention and study, including performance indicator(s) (generally, these will be represented by the intermediate outcomes in your analytic framework) and performance target(s).