The Importance Of Standardized Healthcare Terminology

By Cheryl Mason, Health Language

In our previous blog, we discussed the importance of leveraging administrative data for better quality assessment. As the wrap-up to this standards blog series, I want to look back at Crossing the Quality Chasm as a foundational work for improving the quality of healthcare delivery. This paper called not only for better quality but also for a reduction in the cost of that care--this at a time when the population is aging, technology is evolving, and research is rapidly expanding evidenced-based medicine. At least eight of the 13 recommendations made by the authors of Crossing the Quality Chasm directly involve the collection, aggregation, and actionable use of healthcare data. The remaining five are supporting those objectives through the development of committees that address quality care and reimbursement models, and in training the workforce to meet the increasing needs of an industry that is becoming more and more reliant on data and analytics.

We introduced the major standard terminologies needed to help collect data in a structured way so that we can measure quality, meet meaningful use requirements, and provide accurate information at the point of care. We also touched on value-based care models and how standards such as SNOMED, LOINC, and RxNorm can help your organization aggregate and analyze the data that is found in disparate systems across your enterprise to meet the needs of better reporting and quality measures. We talked about billing and coding standards (ICD-9, ICD-10, and CPT), SNOMED for documenting problem lists in the EHR, LOINC to code laboratory data, RxNorm for pharmaceutical information, and the importance of administrative data like race and ethnicity.