• No results found

HFMA s Revenue Cycle Forum


Academic year: 2021

Share "HFMA s Revenue Cycle Forum"


Loading.... (view fulltext now)

Full text


A peer-to-peer online discussion community REPRINT July/August 2013


Revenue Cycle



Case mix index (CMI) is a constant concern for healthcare financial leaders because of its impact on the revenue stream. A measure of the relative complexity and severity of patients treated in a hospi-tal, CMI serves as the basis for payment methodologies administered by the Cen-ters for Medicare and Medicaid Services (CMS) as well as other third-party payers. A number of factors can affect a hospital’s CMI, including volume changes in certain diagnosis-related groups (DRGs) and doc-umentation/coding improvements (see the exhibit at right). The need to account for CMI fluctuations and particularly declines in CMI has become increasingly important as healthcare organizations encounter new cost pressures and ever-changing regulations. Through proper measurement and analysis, providers can identify ways to improve a declining CMI.

Calculating CMI in Various Ways

Before the why of a declining CMI can be addressed, healthcare organizations should first examine the how—that is, how CMI is being measured. CMI measurement

can be accomplished in a variety of ways. Many facilities measure overall CMI, which often includes all payers regardless of whether they pay by DRGs; others measure Medicare separately from all other payers. These two measures tell only part of the story, however. For a comprehensive understanding of your facility’s CMI, you should analyze it based on five separate categories:

Understanding a Declining CMI:

A Step-by-Step Analysis

By Garri Garrison

The first step in revitalizing a declining CMI is determining the root

cause that is driving its downswing.


Overall CMI. To calculate, add the relative weights of all DRGs and divide by the total inpatient population, excluding psychiatric and rehabilitation patients.

Medical CMI. To calculate, add the relative weights of all medical DRGs and divide by the total medical inpatient population, excluding psychiatric and rehabilitation patients. Surgical CMI. To calculate, add the relative weights of all surgical DRGs and divide by the total surgical inpatient population, excluding psychiatric and rehabilitation patients.

Adjusted CMI. Remove all high-weighted DRGs that are not typically influ enced by

coding and/or clinical documentation improvements from the inpatient population (excluding psychiatric and rehabilitation patients). This step typically means removing tracheotomies and transplants (MS-DRGs 1-17 and 652). Remove this volume from the overall population before repeating the calculation for total CMI outlined above. Medical/surgical mix and volume-adjusted CMI. This calculation can help you determine the percentage by which CMI has declined over two equal periods (e.g., Q1 of 2012 to Q1 of 2013) and the decrease or increase in reim-bursement for the designated time period. First, calculate medical/surgical mix and compare volumes from two equal time peri-ods. Next, adjust the CMI to equalize these

two components by freezing one period and adjusting the mix distribution and vol-ume of the other period to match the frozen period. For example, in the exhibit on page 4, the volumes in period 2 were adjusted to equal the medical/surgical mix in period 1. Once adjusted, it became apparent that the largest impact was a decline in medical CMI, as well as medical reimbursement.

Finding the Root of CMI Challenges

Armed with these five measures, healthcare finance leaders can begin to investigate a declining CMI. Follow these steps to get to the root of the problem. Many of these steps involve benchmarking current perfor-mance against your organization’s past performance or against industry peers.

By comparing CMI by service lines between two periods, one hospital found it had a declining CMI in surgery, vascular, renal, medicine, cardiology, and other areas.

Source: 3M Health Information Systems. Used with permission.

Period 1 Period 2

Service Description Cases Percent of Total Case Average CMI Percent of Total Case Average CMI % Change Average Contribution

Line Total Cases Weight Case Weight Rank Contribution Cases Total Cases Weight Case Weight Rank Contribution Case Wt (Hi to Low) Difference

Comparison of CMI by Service Line

VNT Vent TRA Trach NEU Neurology NEO Neonatology OPT Ophthalmology PSY Psych REH Rehab TRN Transplant UNG Ungroupable ORT Orthopedics WMH Women’s Health SUR Surgery VAS Vascular PUL Pulmonary REN Renal MED Medicine CAR Cardiology PSD Behavioral NUS Neurosurgery CTS CT Surgery 18 0.84% 56.0767 3.1154 9 0.0262 4 0.19% 51.8448 12.9612 11 0.0242 111 5.18% 125.7056 1.1325 7 0.0586 0 0.00% 0.0000 0.0000 17 0.0000 0 0.00% 0.0000 0.0000 16 0.0000 0 0.00% 0.0000 0.0000 15 0.0000 0 0.00% 0.0000 0.0000 18 0.0000 0 0.00% 0.0000 0.0000 19 0.0000 0 0.00% 0.0000 0.0000 20 0.0000 476 22.20% 981.0055 2.0609 1 0.4576 10 0.47% 9.7444 0.9744 13 0.0045 103 4.80% 271.5223 2.6361 5 0.1266 21 0.98% 57.2032 2.7240 8 0.0267 285 13.29% 333.8736 1.1715 4 0.1557 115 5.36% 159.6637 1.3884 6 0.0745 670 31.25% 763.3035 1.1393 2 0.3560 285 13.29% 356.0117 1.2492 3 0.1661 5 0.23% 5.6721 1.1344 14 0.0026 35 1.63% 54.3844 1.5538 10 0.0254 6 0.28% 20.0740 3.3457 12 0.0094


Compare the current CMI to an earlier CMI. Use like periods of time, such as the most current 12 months compared to the previous 12 months.

One hospital that completed this compari-son found that it had lost significant vol-ume in orthopedic surgery procedures over the 12-month period. Hospital leaders had assumed this volume was moving to ambu-latory surgery. However, after a closer look, they found that the volume loss was in hip replacements, which are not performed as outpatient procedures. Discussions with orthopedic surgeons revealed that they had been referring these hip replacements to a competing facility with improved operat-ing room equipment.

Another facility found that it had a large influx of one- and two-day length of stay (LOS) patients over the past 12 months. After investigating the increase, leaders determined that physicians had stopped using observation as an option because of confusion around a new order set. Calculate the overall CMI, medical CMI, and surgical CMI. Determining the medical CMI and the surgical CMI will identify underlying problems masked in the overall CMI.

For example, many facilities are comfort-able with their overall CMI. However, when they review medical CMI separately, they often find it to be in the 1.0 range, which is

on the low end of the relative weights for medical cases (medical weights on average range from 1.0 to 1.15). When they perform a root cause analysis, they may find many symptom DRGs, or DRGs without complications and comorbidities (CCs). This could indicate the need for a more specific principal diagnosis or CCs that should have been captured. Low medical CMIs may be heavily influenced by incor-rectly documented and/or sequenced principal diagnoses. An example is docu-menting hypertension as a principal diag-nosis when another more specific condi-tion meets medical necessity for the acute hospital stay.

Period 1 Period 2

Service Description Cases Percent of Total Case Average CMI Percent of Total Case Average CMI % Change Average Contribution

Line Total Cases Weight Case Weight Rank Contribution Cases Total Cases Weight Case Weight Rank Contribution Case Wt (Hi to Low) Difference

Comparison of CMI by Service Line

10 0.42% 35.6526 3.5653 10 0.0151 5 0.21% 69.9687 13.9937 8 0.0296 135 5.72% 154.0743 1.1413 6 0.0653 0 0.00% 0.0000 0.0000 15 0.0000 0 0.00% 0.0000 0.0000 17 0.0000 0 0.00% 0.0000 0.0000 16 0.0000 0 0.00% 0.0000 0.0000 18 0.0000 0 0.00% 0.0000 0.0000 19 0.0000 0 0.00% 0.0000 0.0000 20 0.0000 559 23.69% 1151.7902 2.0604 1 0.4880 14 0.59% 13.5508 0.9679 12 0.0057 116 4.92% 303.4754 2.6162 5 0.1286 26 1.10% 69.3238 2.6663 9 0.0294 312 13.22% 349.8274 1.1212 4 0.1482 87 3.69% 114.4905 1.3160 7 0.0485 748 31.69% 786.7449 1.0518 2 0.3334 317 13.43% 364.9175 1.1512 3 0.1546 5 0.21% 4.6230 0.9246 13 0.0020 25 1.06% 31.4864 1.2595 11 0.0133 1 0.04% 2.0567 2.0567 14 0.0009 14.4% -0.0110 8.0% 0.0055 0.8% 0.0067 0.0% 0.0000 0.0% 0.0000 0.0% 0.0000 0.0% 0.0000 0.0% 0.0000 0.0% 0.0000 0.0% 0.0305 -0.7% 0.0012 -0.8% 0.0019 -2.1% 0.0027 -4.3% -0.0075 -5.2% -0.0260 -7.7% -0.0227 -7.8% -0.0114 -18.5% -0.0007 -18.9% -0.0120 -38.5% -0.0085


Remove all tracheotomies/transplants (MS-DRGS 1-17 and 652) and calculate the adjusted CMI. By removing tracheotomies and transplants, providers eliminate those DRGs that documentation is not likely to influence. Providers that increase the number of tracheotomies and transplants performed over a period of time will see a significant rise in CMI because these types of procedures are very high-weighted DRGs. A high CMI makes it easier for pro-viders to miss underlying coding or docu-mentation issues that need to be


Analyze time periods and case mix. You can compare the volume of all inpatient cases in two comparable time periods, as well as the percentage of cases that are medical versus surgical, by calculating the medical/

surgical mix and volume-adjusted CMI. Be sure to note losses and gains that may indicate the need for further investigation: > Look at volume loss or medical/surgical

mix change to determine if you are losing market share to competitors.

> Review the case types to see if they are moving to a different level of service (inpatient to ambulatory surgery or to observation).

> Review the CMI by service line to identify focus areas and break it down further by DRGs to see if CC capture rates or key DRG pairs are in the optimal DRG assignments.

Calculate the percentage of one- to two-day LOSs in both periods. An increase in short-stay cases may be causing a decline in CMI. Consider benchmarking your LOS against

other hospitals to uncover any major differences. MEDPAR data from CMS shows the following performance from hospitals across the United States: > One- and two-day LOS volume

com-bined: 30.16 percent

> One-day LOS volume: 14.07 percent > Two-day LOS volume: 16.09 percent Calculate CMI by each service line or by major diagnostic category. Perform this calculation for comparable time periods, such as six-month periods in different years, to determine if CMI has increased or decreased. This will help narrow down the root cause(s) of a declining overall CMI to a particular set of DRGs or case types. Fur-ther investigation may indicate less com-plex cases than anticipated or possible

Period 1 Period 2 Vol % Period 1 Period 2

DRG Description Volume Volume Change Ratio Ratio Performance %Change 177 Respiratory Infections &

Inflammations W MCC 24 36 50.00% 52.17% 45.00% 51.28% -13.75%

193 Simple Pneumonia &

Pleurisy W MCC 22 44 100.00%

Comparison of Key DRG Pairs

In this scenario, a physician was not correlating the sputum culture organism to the pneumonia type. Therefore, the case was coded to an unspecified pneumonia, which is in DRG 193.

Source: 3M Health Information Systems. Used with permission.

Change in Reimbursement with Adjusted Period 2 Volume for Period 1 (%)

Period 2 Med/Surg Mix Adj Period 2 Cases

Contrib to Change in

Description CMI Change Change in CMI Overall CMI Actual Adjusted Blended Rate Reimbursement Medical 1.1565 23.95% 20.0476 0.6724 7,961 7,473 $6,755.76 2$2,403,124 Surgical 3.0144 20.85% 20.0258 1.2618 4,892 5,380 $6,755.76 2$ 937,727 Overall 1.9341 21.95% 20.0385 1.9341

Total 12,853 12,853 Total 2$3,340,850

Adjusting Case Mix Distribution and Volume Between Two Periods

The actual cases in period 2 for medical, surgical, and overall were 12,853. These volumes were adjusted to equal the medical/surgical mix in period 1. The adjustment revealed that the largest impact was a decline in medical CMI, as well as medical reimbursement.


Republished from HFMA’s Revenue Cycle Forum.

Copyright 2013 by the Healthcare Financial Management Association. Three Westbrook Corporate Center, Suite 600, Westchester, IL 60154.

documentation/coding deficiencies or inaccuracies, such as lower capture rates of CCs.

For example, one hospital found it had a declining CMI in several service lines, including surgery, vascular, pulmonary, renal, medicine, and cardiology (see the exhibit on pages 2 and 3). On further investigation, the hospital found that it was not capturing CCs on these cases at the same rate it had in the previous time period. The facility solved the problem by implementing a clinical documenta-tion improvement program, which lev-eraged staff to assist physicians in iden-tifying diagnoses that were being treated but not documented in the medical record.

Calculate the overall CC capture rate and then by individual DRG level. Compare the CC capture rate between two periods to

determine focus areas. Providers with access to industry benchmarks for CC capture rates should use these as points of comparison in addition to their organi-zations’ past performance. A CC capture rate may be measured against a previous year, but it still may be significantly behind industry performance if a provider com-pares it to others outside its facility. Compare the volume of distribution in key DRG pairs. For example, calculate the vol-ume of complex versus simple pneumo-nia, COPD versus respiratory failure, and gastroenteritis versus dehydration (see the bottom exhibit on page 4). Review the distribution of cases in the higher-weight-ed DRGs comparhigher-weight-ed to peers or industry benchmarks.

Audit cases. Evaluate specific patient records to review the quality of coding, compliance with coding regulations, the quality of

physician documentation, and inpatient admission criteria for short LOS cases.

Identifying Next Steps

Demystifying CMI changes is all about tracking the root cause. While sometimes out of a hospital’s control, declining CMI is often the result of poor documentation capture and can be quickly improved through focused physician education and regular documentation audits.

Garri Garrison, RN, is director, emerging business, 3M Health Information Systems (glgarrison@mmm. com).


Related documents

stability; the quality of network, server, and storage infrastructure; and the ability across a network, the strength, quality, and diversity of network technologies and

Spatial Data (.zip): This is a digital file of the land cover (aerial) imagery data used in this project. All geospatial data must be in UTM NAD 83. In most cases this is a CIR

Most research-related injury cases allege negligence, an action that requires plain- tiffs to prove not only that the research team breached a duty to them, but also that the

Standards like LOM (Learning Object Metadata), SCORM (Sharable Content Object Reference Model) or Learning Design have not yet agreed on how metadata should or must be implemented

It is worth mentioning that 5-octadecenoic Acid (AGI) compared with other SFA was found in high concentrations in each and every one of the salamis analyzed and its

By clicking on the red figure you will be able to allocate users of webCRM to record time, expenses and mileage..

Blame and guilt are poison to desire loestrin 24 patient savings card expires generic loestrin 24 side effects. online pharmacy loestrin 24 fe loestrin fe cost with insurance