In our latest data quality blog series, we introduced the importance of interoperability and how healthcare organizations can achieve a framework of data normalization by mapping disparate data to industry standards. The first blog in the series explored the value of terminology mapping for lab data.
In this second installment, we review the complexities of normalizing medication data that comes from disparate sources and why mapping these variations to a common standard language is critical for driving accurate clinical decisions support and quality patient care. Mapping healthcare data to a common standard, such as RxNorm, can also help improve data accuracy for care and disease management initiatives, optimize quality measures reporting, and achieve reliable analytics.
The importance of data normalization in healthcare
In the age of electronic patient records, pharmacy IT systems, and other supporting technologies, medication terminology standards are critical for advancing interoperability to optimize patient care and support high-level analytics initiatives. Accurate and complete data aggregation provides value for research, population health, and medication best practices for care and disease management.
The multitude of medication standards used within the industry—both standard and proprietary—creates challenges in reconciling all available data in a meaningful way. Most hospitals use at least ten disparate IT systems, most of which contain some level of drug information and rely on different terminologies. Multiple access points make the consolidation and normalization of data a significant obstacle.
Additionally, some medication standards are updated daily, requiring time-intensive ongoing maintenance. Accurate and complete data aggregation doesn’t happen by accident. For example, your EHR probably uses Medi-Span for prescribing medications and RxNorm for recording a medication list or allergies. Your dispensing system is probably based on National Drug Codes (NDCs). All of this information is required to accurately tell your patient's story and needs to be harmonized to avoid duplicative information that feeds into your downstream high-value initiatives, like a chronic care management program.