HL7®, FHIR® and the flame Design mark are the registered trademarks of Health Level Seven International and are used with per mission.

Redmond, June 10 – 12 | @HL7 @FirelyTeam | #fhirdevdays | www.devdays.com/us

FHIR and Genomics

Gil Alterovitz (Harvard Medical School) James Jones (Boston Children’s Hospital)

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FHIR Genomics Learning Objectives

• FHIR Genomics Motivation & Significance

• FHIR Genomics Tools

• Genomics Reporting IG structure

• Genomics Reporting IG profiles

• Genomics Report Examples

• Tutorial Review & Close

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FHIR Genomics Motivation & Significance

• Precision Medicine Initiative

• Modernize Genomic Lab Reports

• Enable Point of Care Apps for Precision Medicine

• Facilitate Downstream Research/Reanalysis

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Precision Medicine Initiative

• Emerging approach for disease treatment and prevention considering individual variability in genes, environment, and

lifestyle.

4

Modernize Genomic Lab Reports

Currently: PDFs! (sometimes faxed)

• Often printed/signed/scanned

• Not machine readable!

• Not standardized between labs or tests

• Can require expert knowledge to read

Solution: structured data!

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Enable Point of Care Apps for Precision Medicine

Genomics Lab

EMR

FHIR Genomics

Data

FHIR Service

Request

Order

Panel or

Sequencing 1

2 Return

Data Results

3 Send Data to Clinicogenomic App

SMART on FHIR Clinical + Genomics Data

4 Connect to external

services and APIs

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Enable Point of Care Apps for Precision Medicine

• Securely links patient-specific data from EHRs via FHIR and multiple laboratory/reference knowledge bases for information and

treatment options.

• For a patient-specific gene mutation, show information for most common mutations in similar cancer populations

Warner & Alterovitz, JAMIA 2016

Warner, Alterovitz, et al, JCO Precision Oncology 2018

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Facilitate Downstream Research/Reanalysis

GACS = Genomics Archiving and Communication System

• System akin to PACS, for housing

Genomics data

• Enables extra-EHR storage of genomic

data in other/GA4GH standards, to be

served on demand to SMART apps

and/or CDS Hooks cards using FHIR

• Highlighted in May 2019 HL7 Newsletter following Connectathon 20

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Facilitate Downstream Research/Reanalysis

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FHIR Genomics Tools

• Clinical Genomics Work Group

• https://confluence.hl7.org/display/CGW/WorkGroup+Home

• https://chat.fhir.org/#narrow/stream/genomics

• clingenomics@lists.hl7.org

• HL7 Domain Analysis Model: Clinical Genomics (2018)

• Implementation Guide - Genomics Reporting (draft)

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Implementation Guide - Genomics Reporting (draft)

Where to find it?

• Google “FHIR Genomics Reporting”

• Fhir.org/guides/registry

• Linked through hl7.org/fhir/genomics

• (R4 and above)

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Implementation Guide - Genomics Reporting (draft)

Covers all aspects of human genetic reporting, including:

• Representation of known variants (mainly using terminologies) as well as fully describing de novo variations

• Relevance of identified variations from the perspective of disease pathology, pharmacogenomics, transplant suitability (e.g. HLA typing), etc.

• Full and partial DNA sequencing, including whole genome and exome studies

• Focuses on data structures for encoding genomic test results

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Implementation Guide - Genomics Reporting (draft) • International in scope, leverages industry standard terminologies which are freely available to all countries.

• Maximizes the use of clinical resources Observation and DiagnosticReport and minimizes FHIR extension. This eases implementation and also reduces the chance of data being lost by systems that might not have been designed to specifically accommodate genetic-related information.

• Avoids pre-coordinating the type of variant, medication or other information into Observation.code. This aids leveraging genomic information terminologies and avoids duplication of information into coding systems such as LOINC.

• Allows for variability in the amount of discrete information captured. Systems are encouraged to populate what discrete elements they can and allows for the possibility of systems populating additional elements as their technical capability and/or time and other resources allow.

• Uses separate observations for each independently useful assertion, to maximize discoverability and query-ability of the data.

• Where possible the guide aligns with HL7's v2 Genetic Variation Model Implementation Guide and v2 Cytogenetic Model Implementation Guide to maximize consistency for those FHIR systems converting from or otherwise interoperating with v2 systems.

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Implementation Guide - Genomics Reporting (draft)

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Genomics Report

• Category = genetics, code = 81247-9

• Extension: related-artifact

• Media attachments

• Sub-Report references

• Results (category = Laboratory)

• Regions Studied (53041-0)

• Findings (variants, named genotypes, etc)

• Implications (medication efficacy, pathogenicity, etc)

• Overall Interpretation (51968-6)

• (arbitrarily grouped for representation)

http://build.fhir.org/ig/HL7/genomics-reporting/general.html

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Profiles Legend

Observation

Other Resources

Diagnostic Report

Common

Properties

http://build.fhir.org/ig/HL7/genomics-reporting/index.html

Genomics Reporting IG

Grouper(s)

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Genomics Report Result References

Reference Options for different meaning:

• Observation.hasMember

• Observation.derivedFrom

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Other Resources

• Request for Genetics Test (ServiceRequest)

• Specimen

• Patient

• Organization/ Practitioner

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Supporting Information

• Family Member History

• Risk Assessment

• Document Reference

• Other (Clinical) Observations

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Findings

• Structural Genetic Finding (81291-7)

• Sequence Phase Relation (82120-7)

Computable:

• Variant (69548-6)

• Haplotype (84414-2)

• Genotype (84413-4)

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Genetic Finding (Abstract) Profile

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• Prefer codings to text

• Multiple codings OK*

CodeableConcepts, coding(s), and text

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Variant Assessment (69548-6)

• Genomic Location components

• Variant Location components

• Variant Change components

• Reference sequence

• Amino Acid Change components

• Allelic State components

• Can point to other variants to describe a ’complex’ change

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Implication Observations

• Level of Evidence

• Related Artifacts

• Secondary Findings

• Inherited Pathogenicity (53037-8)

• Associated Phenotype(s)

• Mode of Inheritance

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PGx Implications

• Mandatory Medication Assessed component (51963-7)

• Medication Efficacy (51961-1)

• Medication Metabolism (53040-2)

• High Risk Allele (83009-1)

• Medication Usage (Task/ MedicationStatement)

• Recommended Action

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Somatic Implications

• Mandatory Associated-Cancer component

• Somatic Diagnostic Implication

• (How) Do the findings indicate the cancer?

• Somatic Prognostic Implication

• (How) Do they imply positive or negative outcome for medication or therapies?

• Somatic Predictive Implication

• (How) Is the medication likely to affect the tumor based on the findings

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Profiles Legend

Observation

Other Resources

Diagnostic Report

Common

Properties

http://build.fhir.org/ig/HL7/genomics-reporting/index.html

Genomics Reporting IG

Grouper(s)

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Domain Analysis Model: Clinical Genomics (CGDAM)

• Identifies stakeholders, use cases, and workflows

• Ongoing iterative feedback

• Standard and platform agnostic

• Human Readable

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CGDAM Cancer Profiling

• Analysis of Somatic (acquired) mutations

• Determine individual mutations present

• Variants/variations from a reference

• Tumor vs normal analysis

• Genetic analysis for more accurate prognostics

• Diagnose specific cancer subtypes and treatment options

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Cancer Profiling Stakeholders and Data Generated

• Healthcare Provider and Pathologist

• Physician/Oncologist orders sequence testing, Clinician/Surgeon gathers specimen of tumor cells, optionally also gathers blood/cheek swab for germline DNA. Pathologist analyzes tumor specimen for proper diagnosis.

• Molecular Diagnostic Laboratory

• Receives Specimen(s) and order for test, containing indication, cancer type, and other clinical and pathological data. Sequences and processes specimens in bioinformatics pipeline, creating data for alignment, variations found, and QA.

• Molecular Pathologist

• Transcodes data for entry in EMR, generates narrative/interpretive structured report. Optionally shares report with Pathologist before sending to Clinician for patient review, care plan creation, and results are made available in patient portal.

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Domain Analysis Model: Clinical Genomics (CGDAM)

• Identifies stakeholders, use cases, and workflows

• Ongoing iterative feedback

• Standard and platform agnostic

• Human Readable

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Example Oncology Report

Transaction Bundle

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Example Oncology Report

Transaction Bundle

• Patient, Practitioner, Specimen,

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Example Oncology Report

Transaction Bundle

• Patient, Practitioner, Specimen,

• Observation (TMB)

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Example Oncology Report

Transaction Bundle:

• Patient, Practitioner, Specimen,

• Observation (TMB)

• Observation (MSI)

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Example Oncology Report

Transaction Bundle:

• Patient, Practitioner, Specimen,

• Observation (TMB)

• Observation (MSI)

• Observation (Variant on JAK2)

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Example Oncology Report

Transaction Bundle:

• Patient, Practitioner, Specimen,

• Observation (TMB)

• Observation (MSI)

• Observation (Variant on JAK2)

• Observation (Variant on KDR)

• Observation (Variant on ERBB4)

• Observation (Therapy Match

Result)

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Example Oncology Report

Transaction Bundle:

• Patient, Practitioner, Specimen,

• Observation (TMB)

• Observation (MSI)

• Observation (Variant on JAK2)

• Observation (Variant on KDR)

• Observation (Variant on ERBB4)

• Observation (Therapy Match Result1)

• Observation (Therapy Match Result2)

• Observation (Therapy Match Result2)

• DiagnosticReport referencing each

Observation

> 1000 lines of XML but (could be worse) but

everything can successfully be queried!

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Tutorial Review & Close

• FHIR Genomics Motivation &

Significance

• FHIR Genomics Tools

• CG Work Group

• Domain Analysis Model

• Genomics Reporting IG

• Genomics Report Examples

• Come to Meet & Code!

• Ask questions in the Zulip!

• Join the webcalls!

HL7®, FHIR® and the flame Design mark are the registered trademarks of Health Level Seven International and are used with per mission.

Redmond, June 10 – 12 | @HL7 @FirelyTeam | #fhirdevdays | www.devdays.com/us

Thanks!

Gil Alterovitz (Harvard Medical School) James Jones (Boston Children’s Hospital)