Clinicians aren’t coders – or at least they aren’t trained to be. But that doesn’t mean they don’t function as coders in practice. In fact, clinicians typically play the primary role in establishing diagnosis codes, even when they’re backed up by professional coders (in the inpatient setting), and particularly when they don’t (in the ambulatory setting).
How well do clinicians function as “lay coders”? As an internist myself, I’d probably give us a “B” (or, in the era before grade inflation, a “gentleman’s C”). That is, good enough but far from the standard of excellence we apply to medical care. Superbills have been helpful in many settings, as has the occasional hectoring from billing specialists. But the result too often has been codes that are too imprecise for accurate billing or risk adjustment, or even codes that are inaccurate (at a rate of approximately 20% based on an NCBI review).
This will only get worse with ICD-10-CM, should implementation escape another year of delay (and all indications right now are that it will). So how can we assist clinicians in more accurate coding? While a brief introduction to ICD-10-CM is important for doctors, doctors shouldn’t waste precious clinical time combing through coding manuals. Instead, doctors need smart systems that guide them, as quickly and intuitively as possible, from the language commonly used in clinical practice to the formal encoding standards necessary for information systems and billing.
An interface terminology such as Health Language’s Provider Friendly Terminology is the backbone of such smart systems. Embedded in EHRs and billing systems, Provider-Friendly Terminology recognizes the hundreds of thousands of synonyms, colloquialisms, and abbreviations clinicians use in practice, and links them smoothly and unobtrusively to codes such as ICD-9-CM, ICD-10-CM, and SNOMED CT. Moreover, Provider Friendly Terminology can provide guideposts to distinctions that matter in practice, from those which are necessary to avoid rejected claims (Which side was the broken arm? Which trimester did pregnancy-induced hypertension develop?) to those that matter for risk adjustment and analytics (was this type 2 diabetes alone, or can key complications be identified?).
No clinician went into medicine for the sake of coding. But hopefully all clinicians can understand the critical role they play in coding, as the persons who know the patient best. Making it easier for clinicians to get coding right, before the memory of the patient and the encounter quickly fade, will pay off in better information capture, better knowledge, better revenue capture, and better decisions.
What other benefits do you see by mapping clinical terms to standards?