SNOMED CT, LOINC, and RxNorm, fuelled by the Meaningful Use legislation, are poised to become the cornerstone of U.S. health information interchange. SNOMED CT is one of the most comprehensive, multilingual medical terminologies in the world. LOINC is a universal standard for identifying laboratory observations. RxNorm is a standardized nomenclature for generic and branded drugs. All three are integrated within the Unified Medical Language System (UMLS) maintained by the U.S. National Library of Medicine.
While physicians rarely have to deal with clinical terminologies directly, these are indispensable for data querying, validation and reconciliation. The Clinical Informatics team at the Medical College of Wisconsin has developed ClinMiner (https://clinminer.hmgc.mcw.edu), a clinical research portal for clinical and diagnostic information on patients in genetics clinics and clinical sequencing programs, as well as other clinical research projects. ClinMiner is a larger system that incorporates data entry forms, patient reports, advanced querying, export and data visualization. Data for the system consists of many clinical and referral documents the patients have accumulated throughout their clinic and diagnostic histories, and are standardized through the three Meaningful Use ontologies: SNOMED CT, RxNorm and LOINC; integrated into a single UMLS perspective that allows for seamless and dynamic translation between the annotating sources, as well as provides a consolidated view of the underlying patient data.
This approach is unique in integrating all three terminologies into a single workflow of a clinical application, and in fact is not limited to Meaningful Use, as any terminology integrated within the UMLS can be used to annotate, visualize, and query data. This is of particular significance for reintegrating legacy clinical information, for example, billing data annotated with ICD-9 codes in the process of transitioning to ICD-10. Most importantly, as large resources such as SNOMED CT and the UMLS often remain underused due to their sheer size and complexity, ClinMiner demonstrates that the additional effort is well worth it.
4. It pays to get started early (259,000 providers so far)
http://www.cms.gov/Regulations-and-Guidance/Legislation/EHRIncentivePrograms/Downloads/Beginners_Guide.pdf
5. 2015 will be the defining year in the CMS EHR Incentive Programs
https://www.cms.gov/Regulations-and-Guidance/Legislation/EHRIncentivePrograms/downloads/EHRIncentProgtimeline508V1.pdf
Penalties!
7. Each stage will have its own set of requirements
Final rule, September 4, 2012
8. Information exchange is at the heart of Meaningful Use
Core Measures:
12. Provide patients with an electronic copy of their health information, upon request
13. Provide clinical summaries for patients for each office visit
14. Capability to exchange key clinical information
Menu Measure:
8. The EP (…) should provide summary care record for each transition of care or referral
https://www.cms.gov/Regulations-and-Guidance/Legislation/EHRIncentivePrograms/Downloads/EHR_Medicaid_Guide_Remediated_2012.pdf
Stage 2
9. “unstructured document” is explicitly prohibited in transition of care
Electronic Access
Clinical Summaries
Information exchange in MU Stage 2
Patients
Referring provider
Receiving provider
Receiving provider
10. Structured Summary of Care
Problem list
•ICD–9–CM
•SNOMED CT 2009
•SNOMED CT 2012
Medications
•Any source vocabulary that is included in RxNorm
•RxNorm
Encounter diagnoses
•ICD-10-CM
Laboratory tests
•LOINC 2.24
•LOINC 2.27
Procedures
•ICD-9-CM
•HCPCS + CPT-4
•CDT
•ICD–10–PCS
11. The era of non-MU ontologies is over
Expertise in working with medical and pharmacy coding schemes (ICD9/ICD10, HCPCS, CPT4, hospital revenue codes, LOINC, SNOMED and NDC)
Knowledge of clinical terminology and coding standards such as ICD-9, ICD-10, CPT, LOINC, and SNOMED.
This individual will be well-versed in Meaningful Use and standard vocabularies (e.g. RxNorm, SNOMED, etc.)
Experience with healthcare modeling efforts and terminologies such as HL7 v3, SNOMED, LOINC, FDB, CPT
12. If only there was something to pull all these terminologies together!
13. UMLS – an idea ahead of its time
Donald A.B. Lindberg, M.D.
C. Tilley and J. Willis, The Unified Medical Language System, What is it and how to use it?
16. The sheer scale makes manual integration impractical
Gene tests
HLA tests
Evaluation and management
Skin tests
Patient information
HPA tests
Everything else
Here Be Dragons
17. Ontology-based database, query and reporting system
MU Terminologies
•SNOMED CT
•RxNorm
•LOINC
•+
Data types
•Patient and family information
•Demographic information
•Laboratory and genetic test results
•Clinical measurements
•Phenotypes and diseases
•Imaging phenotypes
•Procedures
18. Data Warehouse
EHR Reports
Clinical Documents
Multiple Data Sources
Data Integration in
ClinMiner
Standardized with Meaningful Use Ontologies
Study -> ETL -> Report
27. Clinical
Avatars
ClinMiner entity
MU source
mapping
UMLS
mapping
Term label
GENDER F Phenotype None C0015780 Female
GENDER M Phenotype None C0024554 Male gender
RACE
African American
Asian
Native American
Other
Pacific Islander
Unknown
White
Phenotype OMB standard C0085756
C1515945
C0078988
C0043157
C0086409
C1513907
C1532697
African American
American Indian or Alaska Native
Asians
Caucasians
Hispanic or Latino
Native Hawaiian or Other Pacific Islander
Unknown racial group
HEIGHT ClnicalResult LNC:3137-7 C0365282 Body height Measured
WEIGHT ClnicalResult LNC:3141-9 C0365286 Body weight Measured
BSA ClnicalResult LNC:3139-3 C0365285 body surface area measured
INR ClnicalResult LNC:34714-6 C1369580 INR in Blood by Coagulation assay value
SMOKER Y Phenotype SCT:77176002 C0337664 Smoker
SMOKER N NormalPhenotype SCT:8392000 C0337672 Non-smoker
DVT Y Phenotype SCT:128053003 C0149871 Deep venous thrombosis
DVT N NormalPhenotype SCT:413076004 C1446197 No past history of venous thrombosis
AMI Y Phenotype SCT:57054005 C0155626 Acute myocardial infarction
AMI N NormalPhenotype SCT:301121007 C0577811 Myocardial perfusion normal
CYP2C9 GeneticResult LNC:46724-1 C1830800 cyp2c9 gene mutations found [identifier] in blood or
tissue by molecular genetics method nominal
CYP2C92 GeneticResult LNC:56164-7 C2734139 cyp2c9 gene allele 2 [identifier] in blood by
molecular genetics method nominal
CYP2C93 GeneticResult LNC:56165-4 C2734141 cyp2c9 gene allele 3 [identifier] in blood by
molecular genetics method nominal
VKORC1 GeneticResult LNC:50722-8 C1978717 vkorc1 gene mutations found [identifier] in blood or
tissue by molecular genetics method nominal
VKORC1A GeneticResult LNC:50722-8 C1978717 vkorc1 gene mutations found [identifier] in blood or
tissue by molecular genetics method nominal
VKORC1G GeneticResult LNC:50722-8 C1978717 vkorc1 gene mutations found [identifier] in blood or
tissue by molecular genetics method nominal
WARFARIN Medication RxNorm:11289 C0043031 Warfarin
Demo and
evaluation:
100 000
clinical avatars
x
90 days
x
genotype-guided
warfarin
dosing
43. Acknowledgments
Marek Tutaj
Stacy Zacher
Clinical Avatars
Vincent A. Fusaro PhD
Peter J. Tonellato PhD
Laboratory for Personalized Medicine Harvard Medical School