October 13 2016 | 0 Comments | 137 reads Average Rating: 3
The Other Edge of the Coding Accuracy Sword
It’s hard to fit the complexities of a neonate in intensive care into a box. Especially the seven boxes that are available through the legacy diagnosis related group (DRG) classification system developed for Medicare.
The DRGs developed primarily for the elderly simply don’t offer the granularity needed to describe the complex conditions treated and care offered to the most premature babies, who can vary materially in their acuity and risk. The same was true in other areas, particularly for demographics different than Medicare, particularly the poor, who rely on Medicaid for their care. Medical professionals pointed out for years that, because each individual MS-DRG cover such a broad spectrum of patients and care, they don’t really draw distinctions among certain populations, including newborns, with varying levels of risk. They noted that one unintended result is that they received reimbursement that did not align well with the true cost of the care they provided.
Enter All Patient Refined (APR)-DRGs. Instead of just seven “boxes” for newborns, APR-DRGs offer 28. As such, they make it possible for provider organizations to reflect the details of their patients’ needs and risks much more accurately. The good news is they offer plenty of opportunity to get it right – making it possible to code for additional complexity and more accurate reimbursement. On the other edge of the sword, in a cash strapped world of hospitals with declining bed days and nursing shortages that increase staffing costs, they offer plenty of opportunity to get it wrong – paying for a higher level of care than actually rendered.
In this world, health plans need to deploy advanced analytics to ensure that provider organizations are not making the following mistakes:
#1: Failing to reflect lower levels of care as the episode progresses
It is not uncommon for neonatal patients to receive a high level of care initially and make vast improvements as they grow to more natural size and weight. In such circumstances, the baby is typically “stepped” down to less intense care, and possibly even moved to a different unit within the facility. At times, however, providers can neglect to account for this improvement and continue to code as though the higher level of care is still being rendered.
#2: Coding incorrectly based on included conditions
There are times a baby has a certain condition that includes various other things by its very nature. A baby might be small for his gestational age – which the facility correctly reflects in the claim. However, the provider organization may also code for malnutrition. However, small babies by definition have some malnutrition. Unless the infant is malnourished beyond what is typical for the baby’s small size, that code is inaccurate, which is problematic as it can increase the acuity level for the claim.
#3: Confusing testing with treating
Sometimes, a provider might be concerned that a baby could have a certain condition - such as SEPSIS. They appropriately evaluate the patient for the condition through various tests. This is completely normal and appropriate. The problem arises when they code for the condition – even if the tests ruled the condition out. They should only code for the condition if the tests confirm that it is present.
These are some of the inaccuracies that health plans can uncover with analytics. Can you identify any others?