Healthcare SQL Generator - Query Medical Databases with AI

Healthcare data is complex, sensitive, and critical. AI2sql Healthcare SQL Generator helps medical data analysts, healthcare IT professionals, and clinical researchers generate SQL queries tailored for healthcare databases - with an understanding of medical data models, terminology, and compliance requirements.

Healthcare Data Challenges

Medical databases have unique characteristics:

• Complex schemas - EHR systems have hundreds of interconnected tables

• Temporal data - Patient history, admissions, medications tracked over time

• Coded values - ICD-10, CPT, SNOMED, LOINC codes

• Privacy requirements - HIPAA, patient data protection

• Data quality issues - Missing values, inconsistent formats

Healthcare Query Types

Patient Demographics

Input: "Find all patients over 65 with diabetes diagnosis"

SELECT p.patient_id, p.first_name, p.last_name, p.date_of_birth,
  TIMESTAMPDIFF(YEAR, p.date_of_birth, CURDATE()) as age
 FROM patients p
 INNER JOIN diagnoses d ON p.patient_id = d.patient_id
 WHERE TIMESTAMPDIFF(YEAR, p.date_of_birth, CURDATE()) > 65
  AND d.icd10_code LIKE 'E11%'
 GROUP BY p.patient_id;

Medication Analysis

Input: "List patients on blood pressure medications with recent readings above 140/90"

SELECT DISTINCT p.patient_id, p.first_name, p.last_name,
  v.systolic_bp, v.diastolic_bp, v.reading_date
 FROM patients p
 INNER JOIN prescriptions rx ON p.patient_id = rx.patient_id
 INNER JOIN medications m ON rx.medication_id = m.medication_id
 INNER JOIN vitals v ON p.patient_id = v.patient_id
 WHERE m.drug_class = 'antihypertensive'
  AND rx.status = 'active'
  AND (v.systolic_bp > 140 OR v.diastolic_bp > 90)
  AND v.reading_date >= DATE_SUB(CURDATE(), INTERVAL 30 DAY)
 ORDER BY v.reading_date DESC;

Lab Results Tracking

Input: "Show HbA1c trends for diabetic patients over the last year"

SELECT 
  p.patient_id,
  p.first_name,
  p.last_name,
  lr.result_date,
  lr.result_value as hba1c_value,
  CASE 
  WHEN lr.result_value < 5.7 THEN 'Normal'
  WHEN lr.result_value BETWEEN 5.7 AND 6.4 THEN 'Prediabetic'
  ELSE 'Diabetic Range'
  END as classification
 FROM patients p
 INNER JOIN lab_results lr ON p.patient_id = lr.patient_id
 INNER JOIN diagnoses d ON p.patient_id = d.patient_id
 WHERE lr.test_code = '4548-4'
  AND d.icd10_code LIKE 'E11%'
  AND lr.result_date >= DATE_SUB(CURDATE(), INTERVAL 1 YEAR)
 ORDER BY p.patient_id, lr.result_date;

Hospital Utilization

Input: "Calculate 30-day readmission rates by department"

WITH readmission_data AS (
  SELECT 
  a1.admission_id,
  a1.department,
  a1.discharge_date,
  CASE WHEN a2.admission_id IS NOT NULL THEN 1 ELSE 0 END as readmitted
  FROM admissions a1
  LEFT JOIN admissions a2 ON a1.patient_id = a2.patient_id
  AND a2.admission_date BETWEEN a1.discharge_date 
  AND DATE_ADD(a1.discharge_date, INTERVAL 30 DAY)
  AND a2.admission_id != a1.admission_id
  WHERE a1.discharge_date >= DATE_SUB(CURDATE(), INTERVAL 6 MONTH)
 )
 SELECT 
  department,
  COUNT(*) as total_discharges,
  SUM(readmitted) as readmissions,
  ROUND(100.0 * SUM(readmitted) / COUNT(*), 2) as readmission_rate_pct
 FROM readmission_data
 GROUP BY department
 ORDER BY readmission_rate_pct DESC;

Medical Coding Support

Generate queries using standard medical codes:

• ICD-10 - Diagnosis codes

• CPT - Procedure codes

• LOINC - Lab test codes

• RxNorm - Medication codes

• SNOMED CT - Clinical terminology

Healthcare Database Schemas

Our generator understands common healthcare data models:

• HL7 FHIR - Modern healthcare interoperability standard

• OMOP CDM - Observational Medical Outcomes Partnership Common Data Model

• i2b2 - Informatics for Integrating Biology and the Bedside

• Epic/Cerner schemas - Major EHR system structures

Use Cases in Healthcare

Clinical Research

Identify patient cohorts, track outcomes, analyze treatment effectiveness.

Population Health

Analyze disease prevalence, risk stratification, care gap identification.

Quality Reporting

Generate data for HEDIS, MIPS, and other quality programs.

Revenue Cycle

Claims analysis, coding accuracy, denial management.

Generate Healthcare Queries Now

Describe your healthcare data needs in plain English, and let AI2sql generate queries optimized for medical databases. Save time while ensuring accurate, efficient queries for your clinical data.