483 Analytics & Benchmarking

Industry benchmarking and cross-dataset analytics for 483 compliance intelligence. Compare facility performance against peer groups and get aggregate statistics across all 483 datasets.

Tier Access

Required Tier: Pro+ (Pro, Enterprise)

Rate limits apply per tier — see Rate Limits for details.

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GET /v1/483/analytics/benchmarks

List industry benchmarks with optional filtering by grouping dimension and group value. Benchmarks aggregate risk scores, OAI rates, and citation frequencies across peer groups.

Request

GET https://api.ctwise.ai/v1/483/analytics/benchmarks?grouping=product_type&limit=10
X-Api-Key: YOUR_API_KEY

Query Parameters

Parameter	Type	Required	Description
grouping	string	No	Filter by grouping dimension: product_type, state, program_area, country
group_value	string	No	Filter by specific group value (e.g., Drugs, NJ, CDER)
limit	integer	No	Results per page (default: 20, max: 100)
offset	integer	No	Pagination offset (default: 0)

Available Groupings

Grouping	Description	Example Values
product_type	FDA product classification	Drugs, Devices, Biologics
state	US state (2-letter code)	NJ, CA, TX, PA
program_area	FDA program area	Drugs, Devices, Biologics
country	Country of facility	United States, India, China

Response

{
  "results": [
    {
      "grouping": "product_type",
      "group_value": "Drugs",
      "metrics": {
        "avg_oai_rate": 0.15,
        "median_oai_rate": 0.12,
        "avg_risk_score": 35.5,
        "median_risk_score": 32.0,
        "avg_citations_per_inspection": 2.1,
        "total_facilities": 500,
        "percentile_25": 20.0,
        "percentile_75": 48.0,
        "percentile_90": 62.0
      },
      "peer_group_size": 500,
      "insufficient_data": false,
      "last_updated": "2026-02-21T12:00:00+00:00"
    },
    {
      "grouping": "product_type",
      "group_value": "Devices",
      "metrics": {
        "avg_oai_rate": 0.10,
        "median_oai_rate": 0.08,
        "avg_risk_score": 28.0,
        "median_risk_score": 25.0,
        "avg_citations_per_inspection": 1.5,
        "total_facilities": 300,
        "percentile_25": 15.0,
        "percentile_75": 40.0,
        "percentile_90": 55.0
      },
      "peer_group_size": 300,
      "insufficient_data": false,
      "last_updated": "2026-02-21T12:00:00+00:00"
    }
  ],
  "total": 2,
  "offset": 0,
  "limit": 20,
  "filters_applied": {
    "grouping": "product_type",
    "group_value": null
  },
  "data_source": "483-intelligence/serving/benchmarks.jsonl",
  "query_metadata": {
    "execution_time_ms": 65
  }
}

Response Fields

Field	Type	Description
results	array	List of benchmark records
results[].grouping	string	Grouping dimension (product_type, state, etc.)
results[].group_value	string	Specific group (e.g., "Drugs", "NJ")
results[].metrics	object	Aggregate metrics for this peer group
results[].metrics.avg_oai_rate	number	Average OAI rate across peer group
results[].metrics.median_oai_rate	number	Median OAI rate (robust to outliers)
results[].metrics.avg_risk_score	number	Average composite risk score [0-100]
results[].metrics.median_risk_score	number	Median risk score
results[].metrics.avg_citations_per_inspection	number	Average citations per inspection
results[].metrics.total_facilities	integer	Number of facilities in peer group
results[].metrics.percentile_25	number	25th percentile risk score
results[].metrics.percentile_75	number	75th percentile risk score
results[].metrics.percentile_90	number	90th percentile risk score
results[].peer_group_size	integer	Number of facilities in peer group
results[].insufficient_data	boolean	true if <10 facilities (interpret with caution)
results[].last_updated	string	When benchmarks were last computed
total	integer	Total matching records
offset	integer	Current pagination offset
limit	integer	Current page size

Insufficient Data Flag

Groups with fewer than 10 facilities are flagged with insufficient_data: true. These benchmarks have limited statistical reliability and should be interpreted with caution.

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GET /v1/483/analytics/summary

Cross-dataset analytics summary combining citations, facilities, CFR references, and risk scores.

Request

GET https://api.ctwise.ai/v1/483/analytics/summary
X-Api-Key: YOUR_API_KEY

Response

{
  "total_citations": 25522,
  "total_facilities": 8145,
  "total_cfr_references": 1410,
  "risk_distribution": {
    "low": 4200,
    "medium": 2800,
    "high": 900,
    "critical": 245
  },
  "top_cited_cfr": [
    {
      "act_cfr_number": "21 CFR 211.22",
      "short_description": "Responsibilities of quality control unit",
      "occurrence_count": 1245
    }
  ],
  "fiscal_year_breakdown": {
    "2020": 3200,
    "2021": 2800,
    "2022": 4100,
    "2023": 5200,
    "2024": 5800
  },
  "data_freshness": {
    "citations": "25522 records",
    "facilities": "8145 records",
    "risk_scores": "8145 records",
    "cfr_references": "1410 records"
  },
  "query_metadata": {
    "execution_time_ms": 310
  }
}

Summary Response Fields

Field	Type	Description
total_citations	integer	Total 483 citation records
total_facilities	integer	Total unique facilities
total_cfr_references	integer	Total unique CFR sections cited
risk_distribution	object	Facility count by risk level
top_cited_cfr	array	Most frequently cited CFR sections
fiscal_year_breakdown	object	Citation counts by fiscal year
data_freshness	object	Record counts per dataset

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Examples

Get Benchmarks by Product Type

curl -X GET "https://api.ctwise.ai/v1/483/analytics/benchmarks?grouping=product_type" \
  -H "X-Api-Key: YOUR_API_KEY"

Get Benchmarks for a Specific State

curl -X GET "https://api.ctwise.ai/v1/483/analytics/benchmarks?grouping=state&group_value=NJ" \
  -H "X-Api-Key: YOUR_API_KEY"

Python Example - Benchmark Analysis

import requests

API_KEY = "your_api_key"
BASE_URL = "https://api.ctwise.ai/v1"

# Get benchmarks by product type
response = requests.get(
    f"{BASE_URL}/483/analytics/benchmarks",
    headers={"X-Api-Key": API_KEY},
    params={"grouping": "product_type"}
)

data = response.json()
print(f"Benchmarks: {data['total']} peer groups\n")

for benchmark in data["results"]:
    metrics = benchmark["metrics"]
    flag = " (insufficient data)" if benchmark["insufficient_data"] else ""
    print(f"{benchmark['group_value']}{flag}")
    print(f"  Avg Risk Score: {metrics['avg_risk_score']:.1f}")
    print(f"  OAI Rate: {metrics['avg_oai_rate']:.1%}")
    print(f"  Facilities: {metrics['total_facilities']}")
    print(f"  Risk P25/P75/P90: {metrics['percentile_25']:.0f} / {metrics['percentile_75']:.0f} / {metrics['percentile_90']:.0f}")
    print()

Python Example - Compare Facility Against Peers

import requests

API_KEY = "your_api_key"
BASE_URL = "https://api.ctwise.ai/v1"

# Get your facility's risk score
fei = "3005012345"
risk_response = requests.get(
    f"{BASE_URL}/483/risk-scores/{fei}",
    headers={"X-Api-Key": API_KEY}
)
risk = risk_response.json()

# Get benchmark for Drugs product type
bench_response = requests.get(
    f"{BASE_URL}/483/analytics/benchmarks",
    headers={"X-Api-Key": API_KEY},
    params={"grouping": "product_type", "group_value": "Drugs"}
)
bench = bench_response.json()["results"][0]
metrics = bench["metrics"]

# Compare
my_score = risk["risk_score"]
print(f"Your Facility: {my_score:.1f}/100 ({risk['risk_level']})")
print(f"Drugs Peer Group: avg={metrics['avg_risk_score']:.1f}, median={metrics['median_risk_score']:.1f}")
print(f"Peer Group Size: {metrics['total_facilities']} facilities")

if my_score < metrics["percentile_25"]:
    print("Result: Below 25th percentile - Strong compliance record")
elif my_score < metrics["percentile_75"]:
    print("Result: Within interquartile range - Typical performance")
elif my_score < metrics["percentile_90"]:
    print("Result: Above 75th percentile - Elevated risk")
else:
    print("Result: Above 90th percentile - High priority for improvement")

JavaScript Example - Analytics Summary

const API_KEY = 'your_api_key';
const BASE_URL = 'https://api.ctwise.ai/v1';

// Get analytics summary
const response = await fetch(`${BASE_URL}/483/analytics/summary`, {
  headers: { 'X-Api-Key': API_KEY }
});
const summary = await response.json();

console.log(`Total Citations: ${summary.total_citations}`);
console.log(`Total Facilities: ${summary.total_facilities}`);
console.log(`\nRisk Distribution:`);
Object.entries(summary.risk_distribution).forEach(([level, count]) => {
  console.log(`  ${level}: ${count}`);
});

console.log(`\nCitations by Fiscal Year:`);
Object.entries(summary.fiscal_year_breakdown).forEach(([year, count]) => {
  console.log(`  ${year}: ${count}`);
});

Error Responses

Invalid Parameters

{
  "error": "Invalid grouping. Allowed values: product_type, state, program_area, country",
  "status_code": 400
}

Status: 400 Bad Request

Method Not Allowed

{
  "error": "Method not allowed",
  "status_code": 405
}

Status: 405 Method Not Allowed

Performance

Metric	Target
Benchmarks response time	< 2 seconds
Analytics summary response time	< 3 seconds
Data freshness	Updated with each pipeline run
Timeout	30 seconds

Use Cases

Industry Benchmarking:

• Assess facility performance vs industry peers
• Identify high-risk product types or operations
• Set realistic compliance improvement targets
• Support executive reporting and KPIs

Cross-Dataset Analytics:

• Get a high-level overview of all 483 intelligence data
• Track citation trends by fiscal year
• Understand risk distribution across all facilities
• Monitor data freshness and coverage

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Planned: POST /v1/483/observations/regulatory-mapping

Coming Soon

Regulatory mapping is a planned capability that will map FDA 483 observations to CTWise regulatory rules with remediation guidance. Share your feedback →

This endpoint will accept observation text and return:

• CFR identification and categorization
• Mapped CTWise regulatory rules with similarity scores
• Remediation guidance with prioritized actions
• Industry best practices and regulatory references

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Related Endpoints

• POST /v1/483/observations/search - Search observations
• GET /v1/483/risk-scores - Facility risk scores
• GET /v1/483/cfr-references - CFR references
• GET /v1/483/facilities - Facility profiles