India-Specific Oncology¶
Implementation Note: All FHIR bundle generation and validation uses HAPI FHIR with ABDM India profiles.
IN-ONC-001: ABHA/ABDM Oncology Bundle Compliance¶
Purpose: Ensure oncology events (pathology, radiology, regimens, labs) are converted into ABDM-compliant FHIR bundles with ABHA ID linkage for interoperability across Indian hospital systems.
| Property | Value |
|---|---|
| Actor | ABDM Integration Service |
| Trigger | Oncology event generated |
| Priority | P0 |
Main Success Scenario:
1. Capture oncology event data
2. Retrieve patient's ABHA ID
3. Use HAPI FHIR to map data to ABDM-compliant FHIR bundle (e.g., Cancer Registry Profile)
4. Validate bundle against ABDM profiles using HAPI Validator
5. Link bundle to ABHA ID
6. Submit to ABDM network/repository
Acceptance Criteria: 1. [ ] Generates valid FHIR bundles using HAPI FHIR 2. [ ] Successful ABHA linkage 3. [ ] Compliance with ABDM oncology standards
IN-ONC-002: NCRP/ICMR Cancer Registry Auto-Reporting¶
Purpose: Automatically map diagnosis, morphology, stage, and treatment data into NCRP/ICMR reporting schemas, generate registry-ready files, and validate completeness before submission.
| Property | Value |
|---|---|
| Actor | Registry Reporting Service |
| Trigger | Confirmed cancer diagnosis or treatment completion |
| Priority | P1 |
Main Success Scenario:
1. Extract diagnosis, morphology, stage, and treatment data
2. Map to NCRP/ICMR specific codes and format
3. Validate data completeness against registry schema
4. Generate submission file (XML/CSV)
5. Submit/Queue for submission to NCRP/ICMR
Acceptance Criteria: 1. [ ] Maps correctly to NCRP/ICMR schema 2. [ ] Validates mandatory fields 3. [ ] Generates valid submission files
IN-ONC-003: India-Specific Drug Formulary and Generic Mapping¶
Purpose: Match recommended regimens to India-available formulations, link to CDSCO-approved generics, and flag cost-effective biosimilar options frequently used in Indian oncology practice.
| Property | Value |
|---|---|
| Actor | Formulary Service |
| Trigger | Treatment regimen selected/prescribed |
| Priority | P1 |
Main Success Scenario:
1. Identify prescribed regimen/drug
2. Query India-specific formulary database
3. Match to available brands and CDSCO-approved generics
4. Flag cost-effective biosimilar options
5. Present options to clinician
Acceptance Criteria: 1. [ ] Accurate mapping to Indian brands/generics 2. [ ] Identifies CDSCO-approved drugs 3. [ ] Suggests valid biosimilars
IN-ONC-004: Regional Language and Hinglish Clinical NLP¶
Purpose: Interpret mixed-language radiology and pathology reports (English + Hindi/Telugu/Tamil, etc.), normalizing variable phrasing into structured oncology concepts with high accuracy.
| Property | Value |
|---|---|
| Actor | Multilingual NLP Service |
| Trigger | Clinical report ingestion (mixed language) |
| Priority | P1 |
Main Success Scenario:
1. Detect language mix (e.g., English + Hindi)
2. Normalize variable phrasing to standard English oncology concepts
3. Extract structured data (diagnosis, stage, findings)
4. Store structured data
Acceptance Criteria: 1. [ ] Handles mixed-language (Hinglish, etc.) accurately 2. [ ] Normalizes to standard medical terminology 3. [ ] High accuracy for target regional languages
IN-ONC-005: NABH-Compliant Documentation and Audit Checks¶
Purpose: Validate that all oncology notes, treatments, and deviations follow NABH documentation standards, flag missing mandatory fields, and generate audit-compliant logs.
| Property | Value |
|---|---|
| Actor | Compliance Validator |
| Trigger | Documentation entry or periodic audit |
| Priority | P1 |
Main Success Scenario:
1. Analyze oncology notes and treatment records
2. Check against NABH mandatory field requirements
3. Flag missing fields or deviations
4. Generate audit-compliant logs
Acceptance Criteria: 1. [ ] Checks against current NABH oncology standards 2. [ ] Flags non-compliant documentation 3. [ ] Generates audit logs
IN-ONC-006: TPA Health Insurance Pre-Auth and Discharge Mapping¶
Purpose: Extract diagnosis, stage, procedures, and drug plans to auto-fill TPA pre-authorization and claims formats, ensuring compliance with IRDAI rules and insurer-specific templates.
| Property | Value |
|---|---|
| Actor | Claims Processing Service |
| Trigger | Pre-auth request or discharge summary generation |
| Priority | P1 |
Main Success Scenario:
1. Extract diagnosis, stage, procedures, and drug plans
2. Map to specific TPA/Insurer pre-auth/claim templates
3. Auto-fill forms ensuring IRDAI compliance
4. Generate ready-to-submit claim documents
Acceptance Criteria: 1. [ ] Accurate extraction of claim data 2. [ ] Maps to major TPA formats 3. [ ] Complies with IRDAI rules