EMPLOYEE - MILITARY - Federal Exclusion Data
What the EMPLOYEE - MILITARY Exclusion Data Reveals
EMPLOYEE - MILITARY ranks #76 out of 137 provider-type categories by federal-exclusion volume, with 6 exclusions recorded in the HHS OIG LEIE, roughly 0.0% of all currently-tracked exclusions. That places EMPLOYEE - MILITARY below the average per-category share of 0.7%, in the lower-volume half of the provider-type landscape.
The most common reason for an EMPLOYEE - MILITARY exclusion is Conviction: Healthcare Fraud (6 cases, 100% of the category). CA, IL, AL account for the largest share of EMPLOYEE - MILITARY exclusions on record.
Common Questions
What is the most common reason for an EMPLOYEE - MILITARY exclusion?
Is EMPLOYEE - MILITARY's exclusion volume above or below average?
Recent Federal Exclusions - EMPLOYEE - MILITARY
| Name | State | Reason | Date |
|---|---|---|---|
| Kyle Adams | TX | Conviction: Healthcare Fraud | 2025-12-18 |
| Daniel Castro | IL | Conviction: Healthcare Fraud | 2025-12-18 |
| Jeremy Syto | CA | Conviction: Healthcare Fraud | 2025-12-18 |
| Bradley White | CA | Conviction: Healthcare Fraud | 2025-12-18 |
| Christopher Toups | AL | Conviction: Healthcare Fraud | 2024-05-20 |
| Romeatrius Moss | IL | Conviction: Healthcare Fraud | 2020-12-20 |
Source: HHS OIG LEIE HHS OIG LEIE
Source: HHS OIG List of Excluded Individuals/Entities (LEIE) HHS OIG List of Excluded Individuals/Entities (LEIE) Federal exclusion data from the HHS Office of Inspector General (LEIE). Provider-type categories are as recorded in the LEIE dataset. This information is for educational purposes only and does not constitute medical or legal advice
Read our methodology - how this data is sourced, computed, and verified.
Every figure on PlainDiscipline is rendered directly from public regulatory source data, no number is typed in by an editor. This page draws directly on public regulatory source data, no figure is typed in by an editor. See our editorial standards & corrections policy, the methodology behind these numbers, or report a data error.