| | Jan/Feb 20188UTLOOK Healthcare Tech IN MY OPINIONUnstructured Data in HealthcareNearly 80 percent of clinical information in electronic health records (EHRs) is "unstructured" and in a format that health information technology systems cannot use. As a result, unstructured information is either ignored or when feasible, converted into a precise "structured" format to make it accessible and available for analysis. When structured, however, the information is relatively limited, preventing physicians from capturing the nuances of care.Today, unstructured data is still largely untapped. Most healthcare organizations use manual processes to extract needed information from unstructured data in the EHR, primarily for purposes such as registries, quality reporting, chronic disease management, documentation review, and for some research applications. At a time when healthcare organizations face increasing economic pressure, this manual extraction effort is both time-consuming and resource intensive. Increased reporting requirements associated with MIPS/MACRA and the shift to value-based care have multiplied the time spent manually extracting information from unstructured data, resulting in a growing administrative burden for frontline caregivers.What if we could tap the full depth and breadth of clinical information residing in the EHR to provide meaningful context and nuanced clinical details of the patient's condition? What if this data was available for a broad range of applications, from clinical patient management and more efficient health resource utilization within a community to large-scale population health initiatives? What if we could automatically and in real-time access the clinical information hidden in unstructured data to advance clinical trials, quickly complete prior authorizations, enable better care coordination/management, automate registries, quality reporting and chart audits, speed claims adjudication/review, and enhance clinical decision support? The promise of NLPFinding answers to these questions is more essential than ever as we attempt to measure value and improve patient outcomes in the shift to precision medicine and value-based care. One possible answer is natural language processing (NLP), a technology that converts unstructured data into structured codes, making the data accessible and actionable. NLP works with the most valuable form of clinical communication: the clinical narrative. By processing unstructured text directly with computer applications, NLP leverages the wealth of available patient information in the EHR to improve communication between caregivers, reduce the cost of working with clinical documentation, and automate repetitive data capture and reporting requirements. Until recently, its use has been limited to specific niche use cases or academic research with little application at enterprise scale. In our work with more than 3,000 client sites, however, we can attest to the promise of NLP as the technology is already demonstrating its potential in freeing physicians to focus on patient care rather than requiring them to change their existing, proven processes to accommodate technology.3MTM currently supports client sites with an NLP platform that processes more than 2.5 million clinical documents daily Hon S. PakBy Hon S. Pak, MD MBA, Chief Medical Officer, 3M HIS
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