Enhancing interoperation: an i2b2 ETL schema for Epic EHRs James R. Campbell MD James McClay MD Departments of Internal Medicine & Emergency Medicine University of Nebraska Medical Center

Outline Organizing i2b2 for interoperation I2b2 Extract, Transfer and Load architecture for Epic EHRs Data warehouse extracts vs CCDA vs FHIR interface for transportability of code

Operational Expectations of i2b2 load Query / aggregate data across collaborators with little or no mapping (Move towards US standard data model) Store facts so that query by value is supported: Numeric, Code lists, structured text Narrative reflects content of many EHRs but is not interoperable and should be structured when extracted

ONC Top Level Model for Semantic Interoperability Information model: Social and medical history: Problem list/encounter diagnoses: Lab results Radiology and other test results: Physical findings: Medication orders: Laboratory Orders: Immunizations: Procedures: Documents: Demographics: LOINC, HL7/OMB code set Social and medical history: SNOMED CT Problem list/encounter diagnoses: SNOMED CT / ICD-10-CM Lab results (observables): Lab LOINC Physical findings: LOINC, SNOMED CT observables Medication orders: RxNORM, SNOMED CT Laboratory Orders: LOINC Immunizations: CVX, MVX Procedures: CPT, HCPCS Documents: LOINC (Clinical) Observables Findings and Situations Findings, Events and Situations (Laboratory) Observables (Clinical) Observables (Laboratory) Observables

ONC Terminology Model for Semantic Interoperability Demographics: LOINC, HL7/OMB code set Social and medical history: SNOMED CT Problem list/encounter diagnoses: SNOMED CT / ICD-10-CM Lab results (observables): Lab LOINC Physical findings: LOINC, SNOMED CT observables Medication orders: RxNORM, SNOMED CT Laboratory Orders: LOINC Immunizations: CVX, MVX Procedures: CPT, HCPCS Documents: LOINC (Clinical) Observables Findings and Situations Findings, Events and Situations (Laboratory) Observables (Clinical) Observables (Laboratory) Observables

I2b2 Star schema: One fact per record (= One question + answer) i2b2 Observation fact Encounter Patient Observation Fact Instance_num Concept_CD Modifier_CD Provider Start_date End_date VALTYPE_CD UNITS_CD TVAL_CHAR NVAL_NUM OBSERVATION_BLOB

Desiderata for interoperability of OBSERVATION_FACTs (OFs) When possible for observables, CONCEPT_CD should align with interoperability reference standards When coded ontologies are the answer, use…MODIFIER_CD for imposing information model context Complex data records (allergy list, medication orders) should be organized into set of facts that are organized by content with MODIFIER_CD linked by INSTANCE_NUM Precoordinate results into CONCEPT_CD only if valueset is small and there is no reference observable code Choice of TVAL_CHAR, NVAL_NUM or BLOB for results should reflect datatypes; use published valuesets always for interoperability

What is the patient hemoglobin? “13.2 mg/dl” i2b2 Observation fact Encounter Patient Modifier_CD Concept_CD LOINC:2951-2 Observation Fact Provider 11/1/2016 7:30AM End_date 13.2 Mg/dl

Epic Laboratory in i2b2 LRRCLARITY_COMPONENT Laboratory results LABS_TRANSFORM.sql LRRCLARITY_COMPONENT 1534435|“Hemoglobin”|”HGB”|LOINC:718-7| Maps ORD ORDER_RESULTS Record Data

What is the patient problem? “Breast cancer” i2b2 Observation fact Encounter Patient Concept_CD SNOMEDCT:254837009 (Malignant tumor of breast) Observation Fact Modifier_CD DX|PROB\ACTIVE Provider Start_date End_date

I2b2 Metadata I2b2 client employs reference ontologies such as ONC terminologies in the user interface: displays the hierarchical structure of the terminology which may be useful for concept navigation supports queries of sets of concepts (hierarchical sub-trees) supported by boolean logic

“Severe allergic rx to aspirin with anaphylaxis” i2b2 Observation fact Encounter Patient Concept_CD SNOMEDCT:39579001 (Anaphylaxis) Observation Fact Instance:10030 Modifier_CD DX|ALGRX Provider Start_date End_date

Nebraska Medicine i2b2 Data Architecture I2b2 Information Class Standard Metadata Ontology ADT history Epic Facility Cancer registry ICD-O Clinical measurements Social history LOINC; SNOMED CT Demographics Diagnoses (Encounter dx; Problems; Past Med History) (ICD-9-CM); ICD-10-CM; SNOMED CT Encounters Epic Facility; Encounter classes Laboratory results LOINC Medications (Orders and Rx; Dispense records) RXNORM; NDC Procedures (Professional services; Hospital procedures; Procedure history ) CPT; (ICD-9-CM); ICD-10-PCS; HCPCS;

Loading an i2b2 warehouse from Epic with ONC terminology Install and maintain terminology maps in Epic and i2b2 Refresh research Clarity (Epic includes mapping data) Run ETLs and load (identified) staging tables Obfuscate dates, anonymize patients and encounters and populate (identified and de-identified) OBSERVATION_FACT tables Install and maintain i2b2 standards metadata & metadataxml for browsing and query Extract CDMV3 tables (SAS) from OBSERVATION_FACT

I2b2 Load Documentation on the Epic UserWeb https://datahandbook. epic UNMC i2b2 ETL Procedures 20160803.docx Identified (idwk) dataset procedures: Heronloader data extracts and table builds(ETLs) Blueheronmetadata metadata build De-identified (deid) dataset procedures: Heronloader extracts and table builds Blueheronmetadata CDMV3 extracts from deid Python scripts: Fact counter code

FHIR datatypes supported by Epic *Adverse reaction *Allergy/Intolerance *Conditions Devices Document Reference *Family History Goals Immunizations Lab results *Medications *Prescription *Patient *Practitioner Procedures *Substance *Social history; smoking status *Vital signs *2015 release

Questions? Comments?