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  The Health Record Review
by Dee Lang, RHIT


Turning Clinical Data into Actionable Information is Key to Navigating Impending Healthcare Challenges

Posted on Fri, Jun 10, 2011 - 08:14 am

Guest commentary

We are in the midst of one of the most challenging and exciting times in the history of healthcare. At every turn there are words and phrases striking fear and tribulation among healthcare providers: healthcare reform, meaningful use, RAC, ICD-10, accountable care, CDI, pay for performance, compliance…the list goes on and on. And while the pros and cons of all of these issues are being hotly debated, one thing is for certain: Change is coming, and in order to survive and thrive, healthcare providers will need to find new ways of gaining productivity, improving efficiencies, reducing costs and finding new sources of revenue. But how?
 

The key to navigating what’s on the horizon, in whatever form it winds up taking, is the ability to transform clinical data into meaningful, actionable information. Gone are the days when we can draw from disparate, disconnected data silos and expect to succeed. Rather, we must take the data we have, powerfully capture it and organize it into understandable, actionable information that support interpretation of clinical findings.

There are two integral components that provide the power to transform data into actionable information, and both must work together to accomplish the task. The first of these components is computer-assisted coding. The transition to ICD-10 alone will involve going from 17,000 to 155,000 codes, and an anticipated 25-50 percent decrease in productivity for most coders. Most experts agree that without computer-assisted coding, the task will be virtually impossible. To achieve the added benefits of more clinically relevant data for research, the coding workforce of 2013 and beyond will need to be supported with powerful technology to improve the quality of their coding in addition to the efficiency of their workflow. But not just any computer-assisted coding solution will suffice. While the coding function is at the heart of a computer-assisted coding solution, the kind of solution that is needed to meet the challenges that lie ahead will go beyond coding and unify and optimize the entire workflow process, from clinical care through the traditional revenue cycle.
 
And that brings me to the second equally important part of this equation: Natural Language Comprehension (NLC), not to be confused with Natural Language Processing (NLP). The difference between the two technologies lies in the letter “C” (Comprehension) versus the letter “P” (Processing). Variations of NLP are able to process textual data and find semantic meaning that can be provided as suggestions back to the coder. In many cases, NLP solutions are not able to strike the right balance between semantic recall and precision, and the end-result is too much or too little feedback. NLC establishes the clinical relevance of the patient story by breaking down data to its SNOMED concepts combined with other attributes that collectively drive a contextual representation back to the coder in the form of ICD-9 and ICD-10 diagnostic and procedure codes.
 
NLC can read both structured and unstructured data, apply contextual rules to impart a structure to the data and organize it into more understandable and actionable information that supports the capture and interpretation of clinical findings. The episode-specific patient narrative can be analyzed and interpreted by a powerful rules–based engine. It can be easily searched, mined and analyzed for clinical facts and encoded for a variety of clinical purposes ranging from coding and reimbursement to clinical research outcomes management, as well as quality management data that is so richly embedded in the unstructured clinical documentation. Furthermore, providing a set of queries that support the ability to look at text and coding data in a new way will open up the ability for facilities to move toward meaningful use even though currently they may be without large quantities of structured data in their electronic medical record. 
 
NLC-enabled computer-assisted coding provides a distinct advantage to healthcare providers and has already been shown to significantly improve coding workflow and production. The combination of computer-assisted coding engines with NLC-driven intelligent workflow solutions provides a single, comprehensive platform to optimize coding processes and unify the entire clinical documentation workflow process. This is the single best solution for providers as they face the imminent challenges on the horizon for the healthcare industry.
 
Dee Lang, RHIT, is vice president of product management and strategy at Precyse Advanced Technologies. You can contact Dee at dlang@precysesolutions.com.