- Managing both HCC v24 and v28 creates complexity in clinical documentation and reimbursement workflows
- Standard code sets have limitations, but clinical terminology helps capture the full patient story
- Missing clinical details can impact outcomes at both the individual and population health levels
In the healthcare industry – from hospitals to health tech companies to insurance agencies – specificity is everything. On the provider side especially, precise documentation is crucial for accurately capturing patient interactions, maintaining clinical intent, and of course, getting paid appropriately.
But all too often, granular details within medical records, documented during patient encounters, get lost or muddied as they traverse the dynamic healthcare ecosystem. This lack of specificity can ignite a domino effect throughout an organization and its partners, not only compromising critical data but patient care, billing and reimbursement, and other downstream processes.
To begin tackling this challenge, healthcare organizations must understand how granularity gets lost in the first place. Keep reading to learn how to safeguard specificity and ultimately, your bottom line.
Only have time for an excerpt? Continue reading to learn how a lack of specificity affects both individual patients and wider communities.
Losing specificity impacts both the patient and population levels
On the surface, it’s fairly easy to see how losing specificity at the point of care can impact a patient’s overall health. Typing in diabetes when a patient really has diabetes mellitus due to underlying condition, with stage 4 chronic kidney disease, with long-term current use of insulin isn’t incorrect per se, but it’s clearly not as helpful as it could be for the next clinician involved in the patient’s care. At the population level, lack of granularity also has major implications. In this situation, the data doesn’t hold the level of detail that many health tech solutions need in order to properly process data and provide meaningful insights. Without the details of this patient’s diabetes – and the relevant details of every patient’s diabetes – it’s also impossible to create accurate value sets in order to generate population health data that can improve patient health and well-being.
Impact on the bottom line
In an outcomes-based care world, accurate population health metrics have financial ripple effects throughout the healthcare system – from hospitals to health tech organizations. Whether a lack of specificity causes Hierarchical Condition Category (HCC) claims to be denied, or contributes to a pool of vague, generalized data that doesn’t provide meaningful insights after large-scale analysis, many organizations feel the financial pain long after the patient encounter is documented.
