Dataset Viewer
Auto-converted to Parquet Duplicate
BILLING_PROVIDER_NPI_NUM
string
SERVICING_PROVIDER_NPI_NUM
string
HCPCS_CODE
string
CLAIM_FROM_MONTH
string
TOTAL_UNIQUE_BENEFICIARIES
int64
TOTAL_CLAIMS
int64
TOTAL_PAID
float64
1376609297
1376609297
T1019
2024-07
39,765
1,205,701
118,887,675.31
1376609297
1376609297
T1019
2024-08
39,677
1,152,534
115,561,066.11
1376609297
1376609297
T1019
2024-05
39,678
1,157,235
112,823,255.3
1376609297
1376609297
T1019
2024-06
39,834
1,164,582
111,449,173.13
1376609297
1376609297
T1019
2024-09
39,527
1,099,808
111,199,832.57
1376609297
1376609297
T1019
2023-12
35,011
1,126,059
108,654,424.08
1376609297
1376609297
T1019
2024-10
38,705
1,049,751
107,690,814.77
1376609297
1376609297
T1019
2023-05
39,160
1,202,398
107,504,894.55
1376609297
1376609297
T1019
2023-03
38,858
1,218,388
107,350,444.62
1376609297
1376609297
T1019
2024-01
35,029
1,127,389
107,097,709.23
1376609297
1376609297
T1019
2024-03
38,160
1,087,063
104,727,513.47
1376609297
1376609297
T1019
2023-10
34,860
1,064,642
103,630,659.12
1376609297
1376609297
T1019
2022-05
38,456
1,180,315
103,075,855
1376609297
1376609297
T1019
2023-04
38,987
1,148,650
102,695,845.07
1376609297
1376609297
T1019
2022-08
38,230
1,177,425
102,535,435.35
1376609297
1376609297
T1019
2024-04
35,952
1,039,887
102,524,798.67
1376609297
1376609297
T1019
2022-07
38,344
1,201,576
102,046,918.74
1376609297
1376609297
T1019
2023-07
35,171
1,116,597
101,493,876.67
1376609297
1376609297
T1019
2023-08
35,191
1,093,176
101,253,721.85
1376609297
1376609297
T1019
2022-01
37,841
1,056,979
101,079,555
1376609297
1376609297
T1019
2023-09
35,096
1,050,555
100,054,621.4
1376609297
1376609297
T1019
2022-06
38,438
1,144,931
99,853,690
1376609297
1376609297
T1019
2023-01
36,552
1,133,460
99,041,713.07
1376609297
1376609297
T1019
2022-04
38,219
1,134,813
98,812,845
1376609297
1376609297
T1019
2022-03
38,098
1,013,674
98,713,611.08
1376609297
1376609297
T1019
2022-10
37,981
1,120,009
98,339,631.52
1376609297
1376609297
T1019
2023-11
34,495
1,020,888
98,269,821.56
1376609297
1376609297
T1019
2024-02
38,017
1,022,012
97,899,274.65
1376609297
1376609297
T1019
2022-09
38,238
1,107,628
96,631,527.72
1376609297
1376609297
T1019
2023-06
38,599
1,046,043
94,937,006.53
1376609297
1376609297
T1019
2022-11
34,438
1,071,071
93,439,759.64
1376609297
1376609297
T1019
2023-02
38,497
1,054,313
92,928,567.51
1376609297
1376609297
T1019
2022-12
34,293
1,036,060
91,520,744.99
1376609297
1376609297
T1019
2022-02
37,787
928,488
90,176,965
1376609297
1376609297
T1019
2024-11
31,676
787,315
84,814,419.88
1922467554
1922467554
T1019
2024-07
28,053
546,207
82,917,536.32
1922467554
1922467554
T1019
2024-05
26,940
532,679
80,004,885.61
1922467554
1922467554
T1019
2024-04
26,665
511,360
77,215,261.03
1922467554
1922467554
T1019
2024-06
27,527
500,538
75,926,938.59
1922467554
1922467554
T1019
2024-01
25,255
502,099
75,363,400.77
1922467554
1922467554
T1019
2024-03
26,149
499,197
75,238,132.72
1922467554
1922467554
T1019
2024-11
29,317
504,374
71,010,282.91
1922467554
1922467554
T1019
2024-02
25,618
473,076
70,935,310.69
1922467554
1922467554
T1019
2024-10
28,894
502,214
70,308,663.84
1922467554
1922467554
T1019
2023-10
24,276
473,832
69,646,988.13
1922467554
1922467554
T1019
2023-12
24,923
474,531
69,575,418.86
1922467554
1922467554
T1019
2023-11
24,671
473,860
69,338,817.96
1922467554
1922467554
T1019
2023-08
23,303
454,631
66,164,474.42
1922467554
1922467554
T1019
2023-09
23,676
442,659
64,469,103.67
1922467554
1922467554
T1019
2023-05
21,944
442,643
63,921,904.82
1922467554
1922467554
T1019
2023-07
22,842
435,741
63,398,304.57
1376609297
1376609297
T1019
2021-12
36,985
710,618
61,969,545
1922467554
1922467554
T1019
2023-06
22,526
427,428
61,866,353.91
1922467554
1922467554
T1019
2023-03
20,994
416,735
60,215,547.19
1922467554
1922467554
T1019
2023-04
21,435
396,370
57,191,893.29
1922467554
1922467554
T1019
2023-01
20,162
394,511
57,035,988.52
1417262056
1417262056
T1019
2024-09
34,818
597,907
55,056,558.57
1922467554
1922467554
T1019
2022-12
19,717
385,714
54,956,784.5
1417262056
1417262056
T1019
2024-08
34,690
599,234
54,781,914.5
1417262056
1417262056
T1019
2024-07
34,337
644,264
54,761,232.8
1417262056
1417262056
T1019
2024-10
34,486
590,591
53,809,750.65
1417262056
1417262056
T1019
2024-05
33,732
595,379
53,401,322.33
1922467554
1922467554
T1019
2022-11
19,299
372,499
53,324,574.8
1417262056
1417262056
T1019
2024-06
34,074
581,629
53,250,080.13
1417262056
1417262056
T1019
2024-01
33,875
603,803
52,946,668.11
1922467554
1922467554
T1019
2023-02
20,465
362,504
52,487,083
1417262056
1417262056
T1019
2023-11
33,363
597,700
52,417,283.45
1417262056
1417262056
T1019
2023-10
33,142
607,495
52,416,359.25
1417262056
1417262056
T1019
2024-04
33,504
597,705
52,277,254.98
1417262056
1417262056
T1019
2024-02
33,819
580,015
52,132,534.47
1417262056
1417262056
T1019
2024-03
33,071
601,225
51,473,263.69
1922467554
1922467554
T1019
2024-09
21,308
370,898
51,425,984.24
1922467554
1922467554
T1019
2022-10
18,828
353,523
50,622,691.57
1417262056
1417262056
T1019
2023-09
32,630
581,215
50,235,951.33
1376609297
1376609297
T1019
2021-07
18,533
580,324
49,654,522.21
1376609297
1376609297
T1019
2021-08
18,575
559,574
49,237,837.4
1417262056
1417262056
T1019
2023-08
31,728
575,778
49,046,808.31
1417262056
1417262056
T1019
2023-07
31,597
571,180
48,767,700.55
1417262056
1417262056
T1019
2023-12
33,331
547,426
48,729,988.28
1417262056
1417262056
T1019
2023-06
31,559
586,553
48,554,673.73
1417262056
1417262056
T1019
2023-03
30,828
578,980
48,047,103.65
1417262056
1417262056
T1019
2023-05
30,756
577,903
48,028,831.56
1417262056
1417262056
T1019
2023-04
31,068
568,351
46,853,006.04
1417262056
1417262056
T1019
2023-02
30,257
557,742
46,628,399.56
1922467554
1922467554
T1019
2022-08
17,959
355,577
46,252,616.5
1417262056
1417262056
T1019
2022-12
29,808
558,276
46,125,624.97
1922467554
1922467554
T1019
2022-09
18,500
352,828
45,989,971.99
1376609297
1376609297
T1019
2021-10
19,001
502,129
45,984,100
1922467554
1922467554
T1019
2024-08
18,101
330,406
45,703,229.53
1376609297
1376609297
T1019
2021-11
19,403
506,103
45,523,887.49
1417262056
1417262056
T1019
2022-11
29,457
549,751
45,374,745.42
1417262056
1417262056
T1019
2023-01
29,982
571,769
45,310,028.42
1417262056
1417262056
T1019
2022-10
29,135
555,342
45,082,618.49
1376609297
1376609297
T1019
2021-09
18,732
495,367
44,298,937.8
1922467554
1922467554
T1019
2022-06
17,916
351,934
44,083,025.79
1922467554
1922467554
T1019
2022-07
18,097
348,109
43,970,867.85
1376609297
1376609297
T1019
2020-07
18,210
515,973
43,798,993.07
1417262056
1417262056
T1019
2022-08
28,481
553,632
43,723,874.8
1417262056
1417262056
T1019
2022-09
28,862
543,161
43,667,639.44
1922467554
1922467554
T1019
2022-05
17,481
354,591
43,550,197.55
End of preview. Expand in Data Studio

Medicaid Provider Spending

This dataset contains provider-level Medicaid spending data aggregated from outpatient and professional claims with valid HCPCS codes, covering January 2018 through December 2024. It provides insights into how Medicaid dollars are distributed across providers and procedures nationwide.

Provider details (name, address, taxonomy) are sourced from the NPPES NPI Registry (February 2026 dissemination).

Data Description

Attribute Value
Time Period January 2018 - December 2024
Granularity Provider (NPI) x HCPCS Code x Month
Geographic Scope National (all states and territories)
Coverage Fee-for-service, managed care, and CHIP

This dataset aggregates individual claims to the provider-procedure-month level, providing counts of beneficiaries served, claims submitted, and total amounts paid by Medicaid.

Splits

Split Rows Description
spending 227,083,361 Claim-level spending by billing/servicing NPI, HCPCS code, and month
billing_providers 617,503 Distinct billing provider NPIs with name, address, taxonomy
servicing_providers 1,627,362 Distinct servicing provider NPIs with name, address, taxonomy
hcpcs_codes 7,549 HCPCS Level II code descriptions (A-V prefix codes)

Schema

spending

Column Type Description
BILLING_PROVIDER_NPI_NUM string NPI of the billing provider
SERVICING_PROVIDER_NPI_NUM string NPI of the servicing provider
HCPCS_CODE string Healthcare Common Procedure Coding System code
CLAIM_FROM_MONTH string Claim month (YYYY-MM)
TOTAL_UNIQUE_BENEFICIARIES int64 Number of unique Medicaid beneficiaries
TOTAL_CLAIMS int64 Total number of claims
TOTAL_PAID float64 Total amount paid ($)

billing_providers / servicing_providers

Column Type Description
npi string National Provider Identifier
entity_type int64 1 = Individual, 2 = Organization
org_name string Organization name (entity_type = 2)
last_name string Provider last name (entity_type = 1)
first_name string Provider first name (entity_type = 1)
middle_name string Provider middle name
credential string Provider credential (MD, DO, etc.)
address_line1 string Practice location address
city string Practice location city
state string Practice location state
zip string Practice location ZIP code
phone string Practice location phone
sex string Provider sex (individuals only)
taxonomy_code string Primary healthcare provider taxonomy code
enumeration_date date Date the NPI was assigned

hcpcs_codes

Column Type Description
hcpcs_code string HCPCS Level II code
description string Short description of the procedure/service

Note: This split contains HCPCS Level II codes only (alpha-prefixed: A-V). CPT codes (5-digit numeric) used in the spending data are not included as they are separately licensed by the AMA.

Joining

Join provider details onto spending data by NPI:

SELECT
  s.*,
  b.org_name AS billing_org,
  b.city AS billing_city,
  b.state AS billing_state
FROM spending s
LEFT JOIN billing_providers b ON s.BILLING_PROVIDER_NPI_NUM = b.npi;

Loading the Data

from datasets import load_dataset

ds = load_dataset("cfahlgren1/medicaid-provider-spending")

spending = ds["spending"]
billing = ds["billing_providers"]
servicing = ds["servicing_providers"]

Use Cases

  • Provider spending analysis: Identify top Medicaid providers by total spending or volume
  • Procedure utilization trends: Track how utilization of specific procedures changes over time
  • Geographic comparisons: Compare provider spending patterns across states
  • Outlier detection: Identify unusual billing patterns for further investigation
  • Policy research: Analyze the impact of policy changes on Medicaid spending

About T-MSIS

The Transformed Medicaid Statistical Information System (T-MSIS) is CMS's comprehensive data system for collecting Medicaid and CHIP data from all 50 states, the District of Columbia, and US territories. T-MSIS data is submitted monthly by states to CMS and includes information on beneficiary enrollment and eligibility, fee-for-service claims, managed care encounter data, and provider information.

Cell Suppression Methodology

To protect beneficiary privacy, this dataset applies cell suppression:

  • Threshold: Rows with fewer than 12 total claims are dropped entirely
  • Purpose: Prevents re-identification of individuals who received uncommon procedures or visited low-volume providers

This means the dataset represents the majority of Medicaid spending but excludes low-volume provider-procedure combinations.

Data Accuracy

This data is derived from T-MSIS submissions and is only as accurate as the data submitted by each state. State Medicaid agencies should be considered the authoritative source for all provider and claims data. T-MSIS has known data quality issues that vary by state and data element. For detailed information on data quality concerns, refer to CMS's DQ Atlas.

Sources

Downloads last month
286