Table 1.

Data Sources for EHR relevant to drive Clinical Decision Support

Type of Information	Standardization	Opportunities	Challenges
Laboratory	LOINC, HGVS, HL7 FHIR value sets	Clinical laboratory tests have a mature standardization capabilities via LOINC LOINC and HL7 genomics groups have started developing standards for genetic tests - that enable standardized discrete coding of some genetic test information	Not all clinical lab tests are encoded with LOINC (still in process in many institutions) Discussions on including genetic text in EHR in a structured way have only recently commenced Significant volumes of tests are performed at external laboratories with processes and results that lack standardization. Laboratory orders are frequently matched in the computer to component results. Genetic test results are not systematically incorporated into EMR in a searchable way. For example they are non-discretely stored in the EMR as a scanned PDF document or image at the UCSD Medical Center
Medication	RxNorm, NDC	Clinical drug names have been standardized using these codes Dictionaries provide the opportunity to include manufacturer, dosing, and route information	Categorization is not clean as medications may have multiple indications both on and off label that skew groupings Combination drugs may not neatly fit into clinical groupings Deriving relevance related to effect over time, dosing intensity, or adherence are problematic
Diagnosis	ICD 9, ICD 10, SNOMED-CT	Most institutions adopt ICD system to support both active problem lists and encounter diagnoses Diagnosis names are interrelated; meaning that terms encoded with other one terminology such as SNOMED-CT, can be converted to ICD through cross-mapping established between the two systems	Coding is frequently completed by a clinician with time constraints that may not search through the extensive terms for the true best fit (undercoding, miscoding) ICD9 and 10 contain level of detail that may deviate from clinical relevance ICD9 is historic and ICD10 current (codes expire and newly develop) Not all codes are billable (irrelevant) Some diagnoses are not encoded (missing) SNOMED concepts are frequently not parsed into terms that support clinically specific workflows IMO updates can impact term groupings and insert clinically mismatched concepts
Radiology	RadLex, SNOMED-CT DICOM	Standards to capture the key findings and metadata about the radiologic studies exist	Radiology test related metadata may not be formatted in a structured way using a standard like DICOM Radiology reports are in an unstructured narrative text format. Processing the text to tease out the key findings and mapping them to the standardized codes requires additional efforts/resources that involves Natural Language Processing (NLP)
Pathology	SNOMED-CT HL7 (anatomic pathology)	Standards to capture the key findings and metadata about the pathology test exist NAACCR is interested in adopting standard for cancer pathology reporting	Pathology reports are in a unstructured narrative text format or PDF. Processing the text to tease out the key findings and mapping them to the standardized codes requires additional efforts/resources (NLP) Pathology frequently utilizes standardized nomenclature but does not record data in structured format
Clinical Evidence & Outcomes	OMOP CDM and all terminology systems listed above	EHR data stored in a clinical data warehouse serves a powerful knowledge resource OMOP CDM is recognized as a de facto standard and adopted by many institutions	There are types of data that are not sufficiently represented by the OMOP CDM such as patient reported outcomes OMOP has not been universally adopted across organizations
Procedures	Terms to represent clinical procedures	Standardized terms that define common clinical procedures and their associated charges	Process for approving new procedural codes is onerous as a result the library may incompletely represent activity detail Many procedural codes are fairly generic and do not incorporate the level of details that impact outcomes