As the healthcare industry changes, there needs to be a shift from a growth perspective to an efficiency perspective. Most hospitals had their highest case mix index (CMI) during COVID, but most also had negative margins. What COVID confirmed is that CMI is not a great measure, because a hospital can have a very high CMI and still be losing money. It is far better to track clinical revenue departmental performance based on how it impacts the hospital operating margin.
But how is that done? It requires better coordination and collaboration among the clinical revenue cycle departments, with metrics that measure the true performance of each of these departments. The hospital operating margin is a measure of how much a hospital spends on expenses, compared to the revenue it receives. Therefore, clinical revenue cycle departments should be protecting earned revenue. Most hospital payment systems are prospective, meaning that the hospital provides patient care in good faith that it will be paid fairly for the services performed. Unfortunately, the hospital can successfully treat the patient and still receive a denial. The problem is that payment is not really based on the quality of care – even though there are quality measures that can marginally impact payment, it is really based on . . . say it with me . . . documentation and/or coding. Even performance on quality measures is impacted by documentation and, sometimes, coding.
How does this connect with the concept of denials management? Well, as hospital margins continued to struggle to meet pre-COVID values, many hospitals realized they need to focus on preventing revenue leakage. In other words, if you can’t grow your way out of a problem with higher revenue, then you need to reduce expenditures and prevent losses, which often occurs with greater efficiency and higher effectiveness. Unfortunately, many hospitals decide to address this financial puzzle through denial avoidance, setting a goal to reduce the volume of denials. The problem with denial avoidance is that it too often results in higher revenue losses as the hospital proactively concedes earned revenue. Yes, the volume of denials is surging to its highest levels and is expected to continue to increase as more payors implement artificial intelligence (AI) tools to scrub claims data, but avoiding denials is unlikely to result in higher net revenue reimbursement.
When I meet with a CFO, one of the first questions I ask is what their tolerance for denials is. Would you rather be aggressive, knowing that it may increase the denial rate but should also reduce overall revenue leakage, or would you rather be conservative, where there is a greater likelihood of revenue leakage through underbilling? Ideally, a hospital should find the balance between being too conservative and too aggressive. Denials are not such a terrible thing that they should be avoided at all costs, even if that was possible. Everyone makes errors, both hospitals and payors, so some denials are valid, but there are also reports that anywhere between 46 to 75 percent of denials are eventually overturned on appeal. It is costly to appeal denials, which is why hospitals need to build denial management strategies within each clinical revenue cycle department by measuring how these departments impact the hospital’s operating margins.
Let’s bring this back down to the clinical revenue cycle departments, which begins with utilization review (UR). The UR staff are the gatekeepers to the hospital. Their work determines who gets billed as inpatients and outpatients. Most clinical documentation integrity (CDI) departments primarily focus on inpatients, so UR efforts determine the CDI workload. Higher inpatient rates usually lead to lower CMI, because it increases the volume of cases that fall into lower-weighted MS-DRGs. One of the reasons CMI was so high during COVID is that services were suspended for elective surgeries, and patients with lower acuity self-selected to avoid hospital care. When only high-acuity patients are admitted, CMI rises. The higher the volume of inpatients, the lower the CMI, as lower-acuity patients mix with the higher-acuity patients, lowering the overall average.
CDI staff often get frustrated in hospitals with compliantly aggressive UR departments, because healthier inpatients usually have lower acuity, making it difficult for CDI staff to find diagnoses classified as complications or comorbidities (CCs) or major CCs (MCCs) to move the DRG. But a higher inpatient-to-observation status ratio supports a healthier operating margin. As the CMI decreases due to UR efforts, it may appear that CDI is less successful, but the reality is that net revenue is still usually higher for an inpatient admission compared to the average payment for observation services, which is billed using outpatient methodologies. The difference is usually at least a couple of thousand dollars, if not more, depending on how many tests were performed in the emergency department and if the payor has a bundle methodology for outpatient services.
How do you minimize revenue leakage from medical necessity denials? Data, data, data. There needs to be more analytics that track payors by inpatient ratios, medical necessity denial rates, peer-to-peer overturn rates, and appeal rates. But most importantly, hospitals should not incentivize low denial rates and high overturn rates. This approach does not support a healthy clinical revenue cycle, because staff will become more conservative when validating inpatient status and choosing when to challenge a payor’s decision. A low denial rate and/or high overturn rate is likely to result in greater revenue leakage. Remember, the hospital is trying to be paid for the resources it has already used to treat the patient. It is much better to have an overturn rate of 50 percent where 90 percent of denials that can be appealed are appealed, than to have a 90-percent overturn rate when only appealing 40 percent of claims. Let’s add numbers to this concept: if $1 million is being denied and $900,000 could be appealed, with an overturn rate of 50 percent, the hospital would recoup $450,000. When only appealing claims with the most potential to be overturned e.g., 40 percent, to reach a high overturn rate goal, the maximum return is $400,000. When an overturn rate of 90 percent is factored into the equation, only $360,000 is recouped. That’s a loss of $90,000 more, even though the hospital has a higher overturn rate.
You never know what may be overturned unless you try, and the benefit of doing so often outweighs the cost, either in staffing or outsourcing. Most hospitals have no idea how conservatively their clinical revenue staff are practicing, because they don’t have good metrics – or the ability to longitudinally follow a claim across all business processes.
The primary function of each clinical revenue cycle department must be measured to identify opportunities for efficiency and effective processes and procedures. Denials management is not the responsibility of a single department; it must be incorporated into all clinical revenue cycle departments. Next week, I’ll continue this thought process with the CDI departmental activities.
How CDI Can Prevent Revenue Leakage
Unfortunately, clinical documentation integrity (CDI ) strategies are not keeping up with the changing landscape of the healthcare industry. More often than not, the focus of CDI remains finding diagnoses classified as CCs and MCCs or increasing the severity of illness (SOI) and risk of mortality (ROM) scores for DRG payers.
Yes, some CDI departments also try to accurately capture risk-adjustment measures, but my point is that too many hospital administrators continue to remain focused on case mix index (CMI) when, as I have discussed, the focus needs to be on hospital margins. Because it is becoming more difficult to grow CMI due to a variety of reasons, the focus should shift from growing revenue to reducing revenue leakage.
Consequently, hospital leadership should be measuring how CDI activities contribute to organizational revenue goals beyond CMI. Some hospitals have made this shift but may be relying upon “back-end” processes which are less efficient than building the workflows into concurrent CDI review process.
Let’s start with the role of CDI professionals in preventing medical necessity denials. Yes, CDI reviews can prevent medical necessity reviews by validating the principal diagnosis. The Uniform Hospital Discharge Data Set (UHDDS) defines the principal diagnosis as “that condition established after study to be chiefly responsible for occasioning the admission of the patient to the hospital for care.” There are two types of claims that are most vulnerable to medical necessity denials, those where a patient began their hospitalization with outpatient services and short-stay admissions, those with a length of stay of less than 3 days.
Establishing the principal diagnosis for patient whose admission was preceded by outpatient hospital services like surgery or observation is tricky even though there are two ICD-10-CM Guidelines for Coding and Reporting that address these areas:
- Admission Following Medical Observation
- Admission Following Post-Operative Observation
The problem is that the Medicare criteria for medical necessity is time-based, not diagnosis based. Once a patient has crossed two midnights and continues to need hospital services, they are likely appropriate for an inpatient admission.
This Medicare rule can lead to patients being admitted for signs and symptoms rather than definitive diagnoses. It is imperative that the CDI professional monitors the record for a definitive diagnosis that explains the admitting symptoms to avoid the reporting of a symptom related MS-DRG, which lead to medical necessity denials. Utilization Review (UR) staff often use commercial screening tools like InterQual or MCG for determine if a Medicare patient meets medical necessity for inpatient status. Although this is not necessary because Medicare medical necessity is based on the Two-Midnight Rule, it could be helpful to the CDI professional to know what criteria set was used to justify the admission to make sure it aligns with the principal diagnosis.
Determining the most accurate principal diagnosis following an outpatient procedure can also be challenging because the reason for the surgery may or may not be the reason for the ensuing inpatient admission. This is when the following principal diagnosis coding guidelines may apply:
- Original Treatment Plan Not Carried Out
- Complications of Surgery or Other Medical Care
- Admission from Outpatient Surgery
But the documentation needs to reflect if the reason for admission occurred prior to surgery, during surgery, or post-operatively. The CDI may need to query to clarify if there is a relationship between the procedure and the admission. The coding guidelines state:
- If the reason for the inpatient admission is a complication, assign the complication as the principal diagnosis.
- If no complication, or other condition, is documented as the reason for the inpatient admission, assign the reason for the outpatient surgery as the principal diagnosis.
- If the reason for the inpatient admission is another condition unrelated to the surgery, assign the unrelated condition as the principal diagnosis.
Identifying the reason for admission was much easier before electronic health records because the provider would document it as part of the admission order; however, with the electronic health record, an admission order has less supporting documentation because it prompts an action. Consequently, this documentation is often missing.
There is also a common CDI and coding habit that can contribute to medical necessity denials. CDI and coding professionals often focus on the relative weight associated with the DRG, because hospital leadership measures their success using CMI. This is not to suggest that CDI and coders are doing anything inappropriate, they are invoking the principal diagnosis guidelines of “Two or more diagnoses that equally meet the definition for principal diagnosis,” so they can “choose” which is the principal diagnosis. The issue is when criteria used to establish medical necessity is not reflected in the principal diagnosis, medical necessity denials can occur.
The most effective CDI departments have pre-bill processes to identify short-stay admissions that are at risk of medical necessity denials. This is particularly important when the discharges occur over the weekend because many CDI priority tools will bypass these cases. The focus for CDI on low acuity, short-stay patients should be validating the principal diagnosis and risk-adjustment, if that is within the scope of CDI because these claims are least likely to have diagnoses classified as a CC or MCC. All too often I see hospitals billing short-stay inpatient cases with symptoms as the principal diagnosis rather than querying for a definitive diagnosis that was identified after study. Maybe it is because CDI reviews the record too soon or maybe it is because they don’t perform reviews after discharge, but this can be a source of revenue leakage.
Unfortunately, instead of making changes in the concurrent CDI review process, most hospitals are adding backend processes like creating work queues for claims with a high risk of denial. Why not review denied claims to see if they were reviewed by CDI staff and if so, it a query opportunity was missed. Having a better understanding of why a denial occurred can allow the organization to refine CDI workflows and provide additional education if needed.
In my opinion, rather than measuring CMI, why not measure the difference between expected payments and actual payments. This allows the hospital to track revenue leakage associated with UR and CDI functions based on the type of denial that led to a lower payment than expected. The goal should be to identify missed opportunities that lead to revenue leakage so any gaps can be addressed by updating CDI concurrent workflows.
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Originally Published On: ICD10 Monitor
Photo courtesy of: ICD10 Monitor
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