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A CDI strategy that does not compromise CMI over Quality Metrics

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Early on, the focus and goal of CDI was to optimize the Case Mix Index by appropriately capturing CCs and MCCs through more accurate and specific clinical documentation. Improving the documentation of conditions classified as CCs and MCCs via chart review, inevitably resulted in a positive impact on CMI since these higher severity patients were now reported at a higher RW value. The metric that was and is still used today to assess performance on this severity documentation component of the CMI is capture rates (a percentage of the total number of a specific DRG reported either with a CC or with an MCC).


Fast-forward to today, the healthcare industry has gone through many regulatory and compliance evolutionary changes, perhaps the most impactful being the value-based purchasing model. This push to deliver high quality care cost effectively, is an indicator of the delivery of high value care to a patient population. With that in mind, monitoring a host of quality metrics, ranging from mortality measures to PSIs are priority areas of focus for many acute care organizations. These metrics are frequently driven by risk adjustment models influenced by the complexity and risk of a specific patient population by factoring in the reporting of comorbidities that have coefficient values relative to the measure being monitored. For example, being able to optimize a population’s Expected Mortality rate is best accomplished by reporting comorbidities that have been shown to have a correlation with a higher risk of mortality for certain patient types. This is in fact, the overall purpose of the CDI initiative, which can be described as “To compliantly optimize the severity reporting (data) of a specific and unique patient population by ensuring the appropriate reporting of clinical conditions.”

This evolution from an initial focus on reimbursement to a more expanded scope that strives to optimize reporting on the full breadth and depth of patient severity, makes complete sense in a value-based healthcare environment, but often results in a dilemma: what should we focus and measure performance on? CCs and MCCs, or risk factors that frequently do not have any CC/MCC value and may very well not impact reimbursement at least in the short term?

We often hear CDI leaders say, “we don’t monitor CMI and just focus on quality!”. One can understand a potential reason for them adopting that stance since at the highest level, monitoring the impact of our efforts on CMI could very easily be interpreted as being “driven by the dollars”. It is far nobler to claim that we focus on quality by optimizing SOI and ROM scores and other frequently occurring conditions that impact quality metrics (e.g., post-op respiratory failure as a PSI) and not reimbursement. That said, we believe that programs should monitor performance on all organizational metrics that could be impacted via accurate severity documentation, which translates to focusing on both CMI and Quality, as opposed to CMI vs. Quality.

That claim could still be met with challenges if your organization is relying on traditional metrics and methodologies to monitor severity documentation performance and quantify the impact on CMI respectively. For example, CC/MCC capture rates are frequently monitored to assess performance on the severity reporting component of specific DRGs. Here are a couple of challenges you will run into if that is your “go-to” metric as it pertains to assessing performance under the MS-DRG billing system:

- Capture rates are binary, meaning you either record that the DRG was reported with or without it, and there are literally thousands of conditions that could help you check off the “with CC” or “with MCC box.”

- Capture rates also assume that all CCs and MCCs are of equal value (more specifically RW value), which is not the case. Calculate the RW value of an MCC in one DRG group and then do the same for a different DRG group. You will get different RW values, even though that MCC is being driven by the same clinical condition.

If we stick to our purpose, our role in optimizing severity reporting data will be driven by accurate reporting of clinical conditions and their corresponding ICD-10 diagnosis codes. Based on that, these clinical conditions can be viewed as not germane to CMI or Quality alone, but rather their relevance and impact on each initiative is a byproduct of improving performance on accurate clinical condition reporting.

ClinIntell's Approach

These truths are incorporated in ClinIntell’s approach to severity reporting analytics and insights and make this approach real and quantifiable. ClinIntell’s analytics provide the acute care industry with the prevalence of specific clinical conditions in the unique inpatient population, we can identify if there is a “gap” in reporting relative to the prevalence. Taking additional factors into consideration, like applicable coefficient values for risk adjustment, ClinIntell can quantify how much the improved reporting on that specific condition will impact each severity reporting initiative (CMI and Quality).

This empowers Acute Care Organizations in the following ways:

- An 80/20 approach to clinical condition improvement efforts can be utilized which is especially beneficial to providers

- The impact of severity reporting efforts can be quantified and monitored as it pertains to CMI as well as risk adjustment in quality initiatives

- A target list of conditions can be selected based on their value to each initiative corresponding to organizational goals and priorities, without having to choose one over the other.

ClinIntell’s patient population severity reporting platform is the only platform that assesses performance and quantifies improvements in a way that truly speaks to our purpose – “To compliantly optimize the severity reporting (data) of a specific and unique patient population by ensuring the appropriate reporting of clinical conditions”.


Redefining Severity Reporting

ClinIntell is the only CDI data analytics firm in the industry that is able to assess documentation quality at the health system, hospital, specialty and provider levels over time. ClinIntell’s clinical condition analytics assists its clients in identifying gaps in the documentation of high severity diagnoses specific to their patient mix, ensuring the breadth and depth of severity reporting beyond Stage 1. Accountability and an ownership mentality is promoted by the ability to share peer-to-peer documentation performance comparisons and physician-specific areas of improvement.

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