OPERATION AND METHOD FOR PREDICTION AND MANAGEMENT OF THE VALIDITY OF SUBJECT REPORTED DATA

• US 20080052259A1
• Filed: 08/24/2007
• Published: 02/28/2008
• Est. Priority Date: 04/02/2001
• Status: Active Grant

• Current Assignee: eResearchTechnology, Inc. (Explorer Holdings, Inc.)
• Original Assignee: Invivodata Incorporated (Explorer Holdings, Inc.)
• Inventors: Engfer, Douglas, Shiffman, Saul, Paty, Jean
• Granted Patent: US 7,873,589 B2
• Time in Patent Office: Days
• US Class Current: 706/47
• CPC Class Codes: G06F 16/24575 using context
• CPC Class Codes: G06F 16/2465 Query processing support for facilitating data mining operations in structured databases
• CPC Class Codes: G06N 5/02 Knowledge representation; Symbolic representation
• CPC Class Codes: G06N 5/025 Extracting rules from data

Abstract

A system for developing and implementing empirically derived algorithms to generate decision rules to predict invalidity of subject reported data and fraud with research protocols in surveys allows for the identification of complex patterns of variables that detect or predict subject invalidity of subject reported data and fraud with the research protocol in the survey. The present invention may also be used to monitor invalidity of subject reported data within a research protocol to determine preferred actions to be performed. Optionally, the invention may provide a spectrum of invalidity, from minor invalidity needing only corrective feedback, to significant invalidity requiring subject removal from the survey. The algorithms and decision rules can also be domain-specific, such as detecting invalidity or fraud among subjects in a workplace satisfaction survey, or demographically specific, such as taking into account gender or age. The algorithms and decision rules may be optimized for the specific sample of subjects being studied.

Claims