Revenue Cycle

Is Case Mix Index Still a Relevant Key Performance Indicator?

The origins of the clinical documentation integrity (CDI) profession can be traced back to the implementation of the Centers for Medicare and Medicaid Service’s (CMS) Diagnostic-Related Grouper (DRG) system back in 1983. It was during this time that Medicare reimbursement transitioned to the Inpatient Prospective Payment System (IPPS) in response to a Congressional mandate to control medical costs associated with caring for the elderly and disabled, creating a relationship between claims data and reimbursement.

The basis of payment under IPPS is the DRG, which is determined by the assignment and sequencing of diagnosis and inpatient procedure codes. Prior to implementation of the DRG system, Medicare made interim payments to hospitals throughout the year and reconciled those payments with the hospital’s “allowable costs” as detailed on a cost report filed each fascial year.  Implementation of the DRG system resulted in a per-case reimbursement mechanism where Medicare paid a flat rate for each inpatient hospital claim in hopes of promoting efficiency and, thereby, keeping healthcare costs down.1 It also resulted in a new metric, case mix index (CMI), defined by CMS as, “the average diagnosis-related group (DRG) relative weight for that hospital.”

DRGs are a classification scheme comprised of classes of clinically similar patients, who medically would be expected to consistently use a similar amount of hospital resources. It was designed to cover “most routine operating costs attributed to patient care, including routine nursing services, room and board, and diagnostic and ancillary services.”2 The bundling of routine labor and nonlabor services needed to treat “similar” patients allowed CMS to create an “average” payment rate.3 The DRG system also allowed for the possibility that some patients, in some disease groups, may require more than “average” services, which could be demonstrated by the presence of a secondary diagnosis classified by CMS as a complication/comorbidity (CC). In other words, it was possible to “move” some DRGs to reflect higher patient acuity that resulted in hospital resource consumption to achieve “maximum” reimbursement.

DRG payments are based on a formula that considers the relative weight associated with each billed DRG and an organization’s individual operating rate. CMS assigns a unique weight to each DRG that is consistent across all short-term acute care hospitals paid under the IPPS with annual adjustments each fiscal year (October 1 through September 30) based on prior year(s) claims data. The weight reflects the average level of resources for an average Medicare patient in each DRG, relative to the average level of resources for all Medicare patients.4 The weights are intended to account for cost variations between different types of treatments, so more costly conditions are assigned higher DRG weights.5 Because CMI reflects the averages of these weights within an organization, hospital finance departments often use CMI to project their budgets.

Although there are several factors that can impact CMI, it has become the primary tool used by healthcare organizations to “measure” the success of their CDI department. The development of the DRG payment system is what ultimately lead to the creation of the CDI profession. Prior to 1983, healthcare data was mainly used for research so hospitals did not have an incentive to ensure their data was as complete and accurate as possible.6

Early research on DRGs found “miscoded and mis-ordered diagnoses” in clinical data contributed to DRG classification errors, which could affect hospital payments but according to an Advisory Research Report, “many problems of data quality will be largely eliminated if the information is used in a context in which accuracy is of greater importance.7”

As the coding profession focused on improving the accuracy of code assignment and diagnosis sequencing, the relationship between ambiguous, missing, incomplete, or inconsistent documentation and coding accuracy became more apparent. Not only did better documentation translate into higher quality coding but the ability to demonstrate greater patient acuity through the capture of CCs also led to increased reimbursement. Organizations that focused on identifying documentation opportunities that allowed them to capture a CC were, therefore, able to increase their CMI and the CDI profession was born.

The US Department of Health and Human Services (HHS) expected an increase in CMIs due to the incentive for more accurate coding, but they severely underestimated the expected increase over the first five years. Studies found the cumulative increase in payments due to case-mix change during that period increased over 20 percent compared to an expected rate of less than eight percent.8 The issue discovered by early DRG analysis, which some could argue remains today, is the inability to determine the proportion of CMI increase due “only to increased patient resource requirements” compared to increases based on better documentation and coding practices.9  This is an important concept to consider when applying CMI to current Medicare populations, how much can CMI continue to grow due to CDI efforts.

The result of early CDI efforts became apparent by the mid-2000s when nearly 80 percent of patients had a CC, thereby, DRG reducing the power of the DRG system to discriminate hospital resource use.10 Consequently, effective FY 2008, CMS updated the DRG payment mechanism to the Medicare Severity (MS)-DRG. Among the changes that occurred with the migration to MS-DRGs was revision of the CC list to reflect significant acute disease, acute exacerbations of significant chronic disease, advanced or end stage chronic disease, and chronic disease associated with extensive disability.11

The revision of the CC list resulted in an estimated decrease in Medicare patients with CCs from 80 percent to 40 percent.12 MS-DRGs also introduced a new subset of ICD-9-CM diagnosis codes that were classified as major complications or comorbidities (MCCs) based on relative resource use. The first version of MS-DRGs resulted in approximately 12 percent of all diagnosis codes classified as a MCC and 24 percent as a CC. As expected, fewer diagnoses classified as a CC or MCC dramatically impacted CMI at most healthcare facilities causing them to fall as a new baseline was established.  CDI specialists were viewed by many health systems as the best solution to rebuild organization’s CMI to reflect patient acuity. Implementation of MS-DRGs, therefore, accelerated the adoption of CDI programs.

Initially, the need for CDI professionals was thought to be temporary as the expectation was coding departments would eventually be able to acclimate to MS-DRGs as effectively as they did DRGs, eliminating the need for additional, dedicated CDI staff. This expectation has not come to fruition as the IPPS system has continued to grow in complexity with both the adoption of ICD-10-CM and the shift to a value-based reimbursement mechanisms and many CDI programs have become full-fledged CDI departments. Perhaps the most obvious impact of ICD-10-CM was on the proportion of codes classified as CCs or MCCs. For FY 2021 approximately 21 percent of codes are classified as CCs and approximately 5 percent are classified as MCCs.13 The impact of migration to ICD-10-CM is still being felt as MS-DRGs are still being reconfigured to reflect its associated coding trends on the Medicare population

The change to MS-DRGs reset an organization’s CMI to a new baseline allowing organizations to once again grow their CMI as they adapted to the MS-DRG reimbursement system and continue to adjust to ICD-10-CM. However, the idea that CMI can continue to increase year over year as a result of improved documentation and coding accuracy is likely misguided. Eventually, the acuity of the patient population will be reflected in the CMI. That does not mean organizations should eliminate their CDI departments, it just means that CMI is likely to be a less relevant indicator of a successful CDI department.

What many organizations are failing to acknowledge is changing admission patterns are likely having a bigger impact on CMI than documentation and coding practices. As more services move to the outpatient setting, CMI increases because less acute patients are lowering the inpatient CMI. A prime example of this phenomenon occurred during the spring of 2020 as only the most acute patients were admitted due to COVID-19. For many organizations, CMI grew as during this period as elective surgeries were suspended and many admissions were limited to only the most acute patients.

Perhaps what is even more concerning is the idea that CMI is the best indicator of the financial health of a hospital and CDI success. At one time, an increasing CMI did reflect incremental revenue opportunities, but those days may be over.  First, the prevalence and maturity of CDI along with collaboration with coding has likely removed the error factor that was cited by early Advisory Board research as most patient populations are likely accurately depicted within the CMI.7 Secondly, as the acuity of the overall Medicare population has increased, CMS has responded by modifying the IPPS through introduction of value-based reimbursement mechanisms and annual updates to the CC and MCC lists.

As a result, it is increasingly more difficult to sustain an increasing CMI so organizational leadership should focus on maintaining their CMI and monitoring their profit margins. Put another way, it is unrealistic to think CMIs can continue to increase when the MS-DRG system is at risk of being “maxed out” if not nationally, at most hospitals with mature, high performing CDI departments.

The value of CMI is anticipating what the reimbursement rate will be based on patient case mix. However, CMI is not tied to hospital charges nor the expense associated with caring for each individual patient. It is an average of all Medicare patients within the MS-DRG. It is a tool for predicting reimbursement based on what is becoming an increasingly faulty assumption: that a higher CMI with its associated higher Medicare payments translates into profitability.

The reality is, if the resources used to treat patients is greater than the “maximum” Medicare payment, an organization can have a high CMI but a low hospital margin.

A 2019 Advisory Board Report stated, “Hospital and health system margin pressures are intensifying as expenses continue to outgrow revenue . . . The gap between cost growth and revenue growth increased between 2016 and 2017, and operating margins dipped to a 10-year low point.”14   

The American Hospital Association (AHA) puts it more clearly stating “a positive operating margin is essential for long-term survival. Few organizations can maintain themselves for an extended period when total expenses are greater than total revenues.”15Even though CMI has been increasing, margins have been steadily declining. Although CDI is a powerful revenue system tool, it is unlikely that any organization can grow their way out of their financial difficulties by increasing a CMI that is likely already maximized. Again, look no further than the impact of COVID-19 with higher CMIs that resulted in a “downturn in volume of patients and revenue, while expenses remained high,” according to the American Hospital Association.16 A report commissioned by the AHA finds median margins are forecast to drop to –3 percent in the second quarter of 2020 and without further government support could drop even further to -7% in the second half of 2020, according to some estimates.17

Rather than trying to increase the CMI, shouldn’t efforts be on controlling costs so that they don’t exceed the expected reimbursement rate?

Think of it like your family budget. If you know you only have some much money to spend at the grocery store wouldn’t you purchase more budget friendly items to stay within your budget? I’m not advocating making decisions that impact the delivery of care. I am advocating for taking a look at what is considered “routine” care and examining whether or not it is medically necessary. This is exactly what CMS expects. Perhaps the next frontier of CDI is helping organizations better understand their “family budget” with a focus on medical necessity to better align revenue and cost as more MS-DRGs are reaching a reimbursement ceiling.

Notes
  1. US Department of Health and Human Services Office of Inspector General. “Medicare Hospital Prospective Payment System: How DRG Rates are Calculated and Updated.” August 2001. https://oig.hhs.gov/oei/reports/oei-09-00-00200.pdf
  2. Ibid
  3. Ibid
  4. Ibid
  5. Ibid
  6. Pettengill, Julian, and Vertrees, James. “Reliability and Validity in Hospital Case Mix Index.” Healthcare Finance Review. 1982 Dec; 4(2): 101–128. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4191289/
  7. Advisory Board (2019). “Re-igniting the Growth Engine, Part 1: Reducing Avoidable Revenue Erosion.” Health Care Advisory Board Research Report.
  8. Steinwald, Bruce, and Dummit, Laura A. “Hospital Case-Mix Change: Sicker Patients or DRG Creep?” Health Affairs. https://doi.org/10.1377/hlthaff.8.2.35
  9. Ibid.
  10. Centers for Medicare and Medicaid Services. “Design and development of Diagnosis Related Group.” https://www.cms.gov/icd10m/version37-fullcode-cms/fullcode_cms/Design_and_development_of_the_Diagnosis_Related_Group_(DRGs).pdf
  11. Ibid.
  12. Ibid.
  13. FY 2021 IPPS Final Rule. https://www.cms.gov/medicare/acute-inpatient-pps/fy-2021-ipps-final-rule-home-page
  14. Advisory Board (2019). “Re-igniting the Growth Engine, Part 1: Reducing Avoidable Revenue Erosion.” Health Care Advisory Board Research Report.
  15. American Hospital Association (July 2020). “The Effect of COVID-19 on Hospital Financial Health.” https://www.aha.org/guidesreports/2020-07-20-effect-covid-19-hospital-financial-health).
  16. Ibid.
  17. Kaufman, Hall & Associates. “The Effect of COVID-19 on Hospital Financial Health.” July 2020. https://www.aha.org/system/files/media/file/2020/07/KH-COVID-Hospital-Financial-Health_FINAL.pdf

 

Cheryl Ericson (cericson@iodinesoftware.com) is a member of the CDI Practice Council.

Tags: clinical documentation integrity , case mix index