PDC 107

Evaluating Data Quality for Exposure Assessment

e-Handout

e-Handout

Publication

PUBLICATION

intermediate | Credits: 8 CM Credit Hours / 0.8 CEU / 0.5 CMP
Saturday, May 21 | 8:00 AM – 5:00 PM
Limit: 60

Topics:

Big Data: Data Management & Interpretation, Exposure Assessment Strategies, Occupational and Environmental Epidemiology, Risk Assessment and Management

Description

Exposure assessments are important as a source of information in support of health risk assessments, epidemiological studies, litigation, and REACH-related exposure scenario evaluations. The instructors will describe work by AIHA, ACGIH, the European Union and others who provide leadership in the area of evaluating human health exposure data quality. A step-by-step approach for evaluating quality of exposure data will be provided including statistical tools. Checklists and an annotated bibliography of data quality references will be provided. An overview and case studies to illustrate the issues associated with presenting exposure data and statistical analyses in a legal setting will be covered. Perspectives and rationale will be provided to help participants understand how they can incorporate the hallmarks of data quality into their IH practice in a way that makes good economic sense in today’s business environment.

Prerequisites

Exposure Assessment Strategies and Statistics PDC or equivalent. Familiarity with AIHA Exposure Assessment Strategies Committee’s IHSTAT software (available free on the Exposure Assessment Strategies Committee webpage).

Learning Aids

Participants must bring a laptop OR tablet/iPad.

Value Added

Learn to evaluate the quality of exposure assessment data using the checklist provided in AIHA’s A Strategy for Assessing and Managing Occupational Exposures, 4th edition (pdf version).  Apply the hallmarks of data quality to improve future exposure assessment strategies. Discussions, group activities, and Q&A sessions to share skills for improving data quality.

Outcomes

Upon completion, participants will be able to:

  • Identify the four basic hallmarks of data quality.
  • Understand the application of defining data quality for a prospective assessment or the complexities of a retrospective data quality assessment.
  • Conduct a data quality evaluation of exposure-monitoring data.
  • Select and apply statistical tools to assist with data quality evaluation of exposure monitoring data.

Outline

  • Overview and perspectives
  • Current guidance on data quality
  • Data quality and exposure assessment
  • Prospective exposure assessment
  • Exposure reconstruction
  • Data mining
  • Data quality in the courtroom
  • Case studies
  • Questions and discussion
  • Group activity
  • Issues with “Big Data”
  • Review of learning outcomes
  • Supplemental materials

Transfer of Knowledge

Instructors will evaluate participants understanding of the materials presented based on:

  • Practice exercises
  • Workshops
  • Group activities

Course Survey: https://www.surveymonkey.com/r/16PDC107

Sponsoring Committee

Exposure Assessment Strategies

Instructors