University of Texas Health Science Center at Houston
Fraud in Genetic Testing: Swindling the System
Abstract
dc:description.abstract<p>Healthcare fraud comprises a sizable portion of the United States healthcare expenditure and inflicts strain on payors, patients, and the healthcare system overall. The genetic testing industry is rapidly growing which provides a multitude of fraud opportunities. There is limited research exploring genetic testing fraud, although federal organizations have highlighted it as an issue. In this study, a retrospective review of federal websites, news articles, and a legal database identified 42 cases of fraud involving outpatient genetic testing published between February 2019 and December 2023. These cases were analyzed for themes via inductive conventional content analysis. Themes of fraudulent activity included submission of fraudulent claims, kickback or bribe payments, minimal or no contact with patients for which testing was ordered, inappropriate billing and documentation practices, and further actions to conceal fraud. High rates of medically unnecessary testing highlight the value of genetics experts such as genetic counselors in ordering or reviewing claims for genetic testing. Repercussions imposed on defendants included monetary penalty, imprisonment, business restrictions, and seizure of property. Examining fraudulent activity in genetic testing can help providers identify and report fraud, and provide awareness of fraud, waste, abuse and optimal healthcare allocation in the genetic testing industry.</p>
Degree
thesis:*- Name thesis:degree_name
- Masters of Science (MS)
- Level thesis:degree_level
- Thesis (MS)
- Year dc:date.available
- 2024
Author and committee
dc:creator, dc:contributor.*- Authors dc:creator
-
- Notestine, Rachel
- Singletary, Claire N.
- <p>0009-0001-5785-7983</p>
- Contributors dc:contributor
-
- Claire N. Singletary, MS, CGC
- Quinn Stein, MS, CGC
- Meagan Choates, MS, CGC
Subjects
dc:subject × 10Identifiers
dc:identifier.*- Repository record dc:identifier
- https://digitalcommons.library.tmc.edu/utgsbs_dissertations/1352
- OAI identifier oai:identifier
- oai:digitalcommons.library.tmc.edu:utgsbs_dissertations-2410