Medicaid Provider SpendingClaims paid 2018–2024 · HHS public file
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Physician

University of South Alabama

University of South Alabama was paid $35K by Medicaid between Feb 2018 and Mar 2019, across 1 billing code. Its largest line is 99232, hospital visit by a doctor, follow-up day — 100% of everything it billed.

33Billing provider infoUNIVERSITY OF SOUTH ALABAMA
MOBILE, AL 36617
33aNPI1962862656assigned 02/24/2016
28Total paid$35K
24GClaims572
24DCodes billed1
24AFirst – last monthFeb 2018 – Mar 2019
Compared with peers

Next to other Infectious Disease Physician providers in Alabama

Rank by total paid#7 of 14
Median peer was paid$27K
This provider vs. median1.3×

Peers share this provider's primary NPPES type and state. Size alone says nothing about billing quality: a big agency or a hospital system is expected to sit far above the median.

Auditor's notes

Automated statistical signals. Not evidence of fraud — how these are computed.

Entity ProliferationAuthorized official IKNER, HARVEY controls 13+ related entities in our dataset. Read more
Box 24A · Dates of service

Paid by month

$0$2.0K$4.0K$6.0K2018201920202021202220232024
Paid that monthNov–Dec 2024: claims still arriving when the file was cut, so these months run low for every provider
By year, as a table
YearClaimsPaid
2018485$27K
201987$7K
Box 24 · Service lines

What it billed for

CodeServiceShareClaimsBene. recordsPaid
99232 Hospital visit by a doctor, follow-up daySubsequent hospital care, per day, moderate complexity 100% 572 235 $35K

Claims and beneficiary counts add up across code × month rows, so one patient seen every month counts many times. Rows with fewer than 12 claims are suppressed by HHS, so small lines can be missing.

From NPPES

Who's on the registration

Authorized officialIKNER, HARVEY (ASSO ADMIN OF AMBULATORY CLINICS)
Parent organizationUNIVERSITY OF SOUTH ALABAMA
Same official

Other billing entities under IKNER, HARVEY

Full network →

Matched on the authorized-official name exactly as entered in NPPES. A common name can match unrelated people.