by Angela Guess
Brian Wells recently wrote in Healthcare IT News, “There are many promising initiatives underway that seek to combine rich clinical data from electronic health record systems running in provider sites across the county into large patient cohorts and then combine that data with genetic sequences created from samples provided by each patient in the cohort. The sponsors of these initiatives span industry, private foundations and the federal government. While the ambitious goals are commendable and the potential for discovery is worthy of the effort, there are data quality and semantic interoperability requirements that must be met prior to the combining of the clinical data.”
Wells goes on, “Without these standards, consolidation and harmonization of rich clinical data will yield only a portion of the expected value. Identifying genetic determinants of disease from this large population, for instance, requires a clinical data set based on standards such that large subpopulations can be compared using common clinical vocabularies. The standards to be addressed fall into two categories: 1) Existing, popularly used or incentivized coding systems and 2) value lists that need to be defined. Category 1 includes coding systems such as: ICD-10 diagnosis codes (and historically ICD-9), CPT and ICD-10 procedure codes, LOINC codes for lab orders and results and RxNorm codes for drugs.”
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