Lithuanian Cervical Cancer Implementation Guide, published by Lithuanian Medical Library. This guide is not an authorized publication; it is the continuous build for version 0.0.1 built by the FHIR (HL7® FHIR® Standard) CI Build. This version is based on the current content of https://github.com/HL7LT/ig-lt-cervical/ and changes regularly. See the Directory of published versions

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Official URL: https://hl7.lt/fhir/cervical/ImplementationGuide/lt.hl7.fhir.cervical				Version: 0.0.1	Highlight text changes?
					Computable Name: LTCervical

Lithuanian Cervical Cancer Prevention and Early Diagnosis Implementation Guide

Introduction and Purpose

This Implementation Guide specifies how to consistently represent and exchange structured clinical data related to the Lithuanian Cervical Cancer Prevention Programme using the HL7® FHIR® standard.

The guide supports the national programme for early detection and prevention of cervical cancer, with a primary focus on human papillomavirus (HPV) testing, cytological examination (Pap test), colposcopy, and histopathological diagnosis, together with structured capture of clinically relevant patient information and diagnostic results.

Its purpose is to enable:

• consistent and high-quality data capture across healthcare providers and laboratories,
• semantic interoperability between primary care, gynaecology, laboratory, pathology, and national screening systems,
• structured reporting for programme coordination, quality assurance, monitoring, and secondary use,
• and reliable tracking of patients across screening, diagnostic follow-up, and treatment pathways.

The guide is developed as part of the national ADP project, which aims to support coordinated, data-driven management of preventive and early diagnostic programmes in Lithuania.

Scope

This guide focuses on the cervical cancer prevention and early diagnosis workflow, covering screening, diagnostic testing, and pathological confirmation processes.

It covers the following clinical domains:

• HPV testing, including high-risk HPV detection and genotype information,
• cytological screening (Pap test) and structured classification of epithelial cell abnormalities,
• colposcopic examination and associated diagnostic procedures,
• histopathological examination of cervical tissue samples, including biopsy analysis and tumour classification,
• patient clinical context, including relevant medical history and risk factors,
• and longitudinal diagnostic pathways, allowing tracking of screening results and follow-up procedures over time.

The guide models cervical cancer prevention as a screening-driven diagnostic pathway, where HPV testing and cytology act as primary detection methods and where further diagnostic procedures (colposcopy and histopathology) are triggered by abnormal screening results.

Key Modelling Principles

The modelling approach is based on the following core principles:

1. Separation of screening, diagnostic procedures, and pathology results
   Screening tests, follow-up diagnostic procedures, and final pathological findings are represented as distinct but connected parts of the clinical workflow.

2. Structured representation of laboratory and cytological results
   HPV testing and cytological findings are captured in a structured format that supports standardized classification and comparison across healthcare institutions.

3. Integration of multiple diagnostic modalities
   The data model supports the full diagnostic pathway, including HPV testing, cytology, colposcopy, biopsy procedures, and histopathological examination.

4. Explicit modelling of diagnostic conclusions
   Observations represent clinical findings, while diagnostic interpretations and pathology conclusions represent the confirmed clinical assessment and disease classification.

5. Support for longitudinal patient pathways
   Cervical cancer prevention programmes rely on repeated screening and follow-up examinations. The data model supports tracking patient screening history, follow-up tests, and diagnostic outcomes over time.

6. Terminology-based interoperability
   The guide relies on internationally recognised terminologies and classifiers, especially SNOMED CT, and where relevant also LOINC, ICD-10-AM, and ICD-O, to ensure semantic consistency and interoperability between systems.

Content of the Guide

This guide provides:

• FHIR profiles and extensions for representing cervical cancer screening and diagnostic workflows,
• structured modelling of HPV testing and cytological examinations,
• support for colposcopy procedures and findings,
• structured representation of histopathological examination results and tumour classification,
• terminology bindings using SNOMED CT, LOINC, ICD-10-AM, and ICD-O,
• structured example instances illustrating realistic programme scenarios,
• mappings from the national cervical cancer prevention dataset to interoperable FHIR artefacts,
• and identification of gaps and future development needs.

At the current stage, the guide focuses on the core data structures required to support the cervical cancer prevention programme, including laboratory testing, cytology reporting, and histopathological diagnosis. Further refinement, terminology expansion, and workflow alignment will be performed in subsequent iterations.

Why Use This Guide?

By adopting this guide, implementers and healthcare institutions can:

1. Interoperability: Ensure consistent and comparable cervical cancer screening and diagnostic data across healthcare systems and institutions.
2. Data Quality: Improve the consistency, completeness, and reusability of screening and diagnostic data.
3. Clinical Utility: Support structured reporting, diagnostic decision-making, and coordinated follow-up care.
4. Programme Monitoring: Enable population-level analysis of screening participation, test outcomes, and diagnostic pathways.
5. Longitudinal Care: Support tracking of patients across repeated screening cycles and diagnostic procedures.

Navigate the sections below to access the profiles, terminology bindings, and detailed examples needed to implement the standard.

Contributors

Name	Role	Organization
Audra Stepanauskaite	Primary Author	LMB
Albert Kuslevic	Primary Author	LMB
Igor Bossenko	Primary Author	HELEX Solutions
Kati Laidus	Co-Author	HELEX Solutions
Martynas Bieliauskas	Co-Author	LMB