This blog post is part of our ongoing series discussing the True Clinical Picture. Before we go any further, let’s quickly reflect on what we mean by True Clinical Picture.
TRUE CLINICAL PICTURE: A complete and comprehensive record that serves as the source of truth by accurately reflecting the care provided. The True Clinical Picture allows healthcare organizations to make meaningful use of health information and achieve positive outcomes for both patients and the organization.
We began the series discussing the importance of the foundation of the True Clinical Picture –
complete and thorough clinical documentation that fully describes the patient encounter. Let’s now turn our attention to the ever-important role of coding in the formulation of the True Clinical Picture. After all, even the best clinical documentation can be laid to waste if not skillfully processed as part of this step. It’s the combination of optimized clinical documentation and optimized coding that allows for the True Clinical Picture to be realized.
In normal circumstances, coding optimization contemplates both accuracy and productivity. For this discussion, let’s set productivity aside, and focus simply on what we can do to enhance coding completeness and accuracy with the True Clinical Picture as the intended outcome.
A Look Back
Those of us who code or who are familiar with coding are aware of the constant evolution of coding. Coding changed in a big way in 2015 with the implementation of ICD-10, but coding – and the use of coded data – are constantly evolving. Speaking from personal experience, coding for completeness wasn’t top of mind twenty years ago. My marching orders were to code and code fast. For all I knew, or should I say, all that I was taught, the life cycle of the code ended with the facility’s payment. If need be, coding errors could be corrected by rebilling, restoring order to the coding universe. Certainly, naiveté and poor training factored into my schema, but at the end of the day, the truth is there was less collateral damage back then than there is now.
On the road to the True Clinical Picture, super-selective coding practices are shelved in favor of comprehensive coding practices.
Now let’s fast forward a bit. The convenience of coded data has proven difficult to resist for those that are interested in measuring quality, adjusting for risk, studying population health, etc. To put it plainly, codes carry more weight these days because their influence extends well beyond encounter-level reimbursement. What can we do to mitigate risk associated with inaccurate or incomplete coding?
Coders need to look no further than the auditing and measurement processes that follow their work to know that accuracy and thoroughness are important. However, most coders do not fully understand why.
Take a step back and inform the coders of the internal and external influence of their codes:
- Physician scorecards
- Healthcare quality rankings
- Population health
- Clinical process improvement initiatives
- Denials prevention
There’s a good chance they recently scrolled past a healthcare-related article that was influenced by coded data so the spheres of influence listed above should resonate with your coding audience. Reinforce that codes matter. Provide specific examples of where codes matter. Do this and you’ll elevate their coding awareness and by extension, improve coding performance.
Assume that All Codes Matter
Well, perhaps that’s a bit of an overstatement, all the initiatives in the world couldn’t find a use for 68,000 ICD-10-CM codes. Let’s walk that back and say that most codes matter.
Take for example a secondary diagnosis code that influences MS-DRG determination. Or a diagnosis code that influences the severity of illness determination for a particular APR-DRG. Or a diagnosis code for a chronic condition that doesn’t factor into DRG determination whatsoever but influences risk adjustment. Trying to remember what codes matter and where they matter is a nearly impossible task.
A more reasonable approach might be to scrap the “if-thens” and treat all codes equally and to take all lapses in documentation seriously. Policies, procedures, and productivity expectations will need to be reevaluated to align with this new plan of attack. Admittedly, assuming that all codes matter is an aggressive approach to thoroughness, but given what’s at risk, a worthwhile approach to thoroughness.
Strive for the True Clinical Picture
By using the quest for the True Clinical Picture as your guiding principle, you will leave no stone unturned. All diagnoses that are suggested by, but not fully established in clinical documentation, should be probed through queries or CDI interaction. Assume that all diagnoses are likely to matter somewhere, if not now then probably sometime soon. On the road to the True Clinical Picture, super-selective coding practices are shelved in favor of comprehensive coding practices. Codes describing chronic conditions, personal history, and family history are treated with the same importance as codes that influence DRG assignment.
By incorporating these practices, the patient’s visit is fully characterized through codes and full reimbursement potential will be realized. Just as importantly, you have the benefit of knowing that your documentation and coding is thorough and complete, that this same information provides optimal insulation from denial efforts and that your coded data serves as the basis of accurate downstream calculations, whatever those may be.
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