Denise M. Nash, MD, CCS, CIM
Vice President of Compliance and Education, MiraMed Global Services Inc., Jackson, MI
Angela Hickman, MS, CPC, CPCO, CEDC, CPMA, AHIMA ICD-10-CM/PCS Trainer and Ambassador
Vice President RA-HCC Strategy and Business, MiraMed Global Services Inc., Jackson, MI
The Centers for Medicare and Medicaid Services’ (CMS) Hierarchical Condition Category (HCC) risk adjustment model is used to calculate risk scores, which will adjust capitated payments made for aged and disabled beneficiaries enrolled in Medicare Advantage (MA) and other plans.
The CMS-HCC model design uses two risk segments with separate coefficients to reflect the cost patterns of beneficiaries. The community model represents those who have lived in the community less than 90 days, as opposed to a more permanent residence in an institution. Beneficiaries residing in an institution for 90 days or more fall into the long-term care category, which incurs an additional risk adjustment. By design, both models predict healthcare costs for beneficiaries.
The CMS-HCC risk adjustment model looks at prospective data to predetermine the cost for the next year. CMS pays a per-member/per-month fee to the payer based on the prospective year’s risk scores. Providers must identify all chronic conditions and/or severe diagnoses their patients have in a given year to substantiate a “base year” health profile for each patient that predicts costs in the following year.
For Medicare accounts, expected differences in resource needs of patients or health plan enrollees are risk adjusted so the payments made to healthcare facilities, such as hospitals, skilled nursing and home health agencies, reflect the proper premiums it pays to health plans.
The risk adjustment program is designed to ensure that premiums are adequate for patients or plan enrollees who require more resources than the average Medicare beneficiary does. The program is set up to protect beneficiary access as well as the financial condition of the provider or plan. At the same time, risk adjustment modeling lowers payments or premiums for beneficiaries who expect to use fewer resources.
HCC Auditing Options
The search for more efficient and effective care of chronic conditions is gaining attention. Developing risk models can contribute to this effort by efficiently identifying enrollees within defined populations who are likely to generate high costs and who could benefit from integrated care.
CMS has the needed resources to continue refining the forecasting models of high-cost users of healthcare. Few providers have the resources and are proficient enough in risk adjustment modeling to mitigate all of the compliance risks they face. This creates a problem for providers because significant dollars are at risk for their enterprises. In order to reduce risks, providers either hire expert HCC auditors as an internal resource or look to outside firms that are experts at executing risk adjustment and HCC auditing. Many companies are capable of providing this service; however, the best practice approach is to work with a company that can guide providers to keep up with CMS’s requirements for compliance while monitoring healthcare outcomes.
Understanding the Requirements of HCCs
In 2010, the Patient Protection and Affordable Care Act (ACA) included legislation that leveraged the model known as CMS-HCC. HCCs have been the basis for reimbursement for Medicare Advantage plans (Medicare Part C) since 2004. HCCs model prospective data to determine predicted costs for enrolled members during the next year of coverage. Such estimates come from demographic information, such as age and major medical conditions, documented from patient encounters in the previous 12 months. Its current use is to adjust Medicare capitation payments to Medicare Advantage health plans based on the anticipated risk of enrollees calculated from relevant ICD-9-CM (DOS on or before September 30, 2015) or ICD- 10-CM codes (DOS on or after October 1, 2015).
Because of the proven success of HCCs in predicting resource usage by Medicare Advantage enrollees, the model now determines, in part, reimbursement for Accountable Care Organizations (ACOs) and the Hospital Value-Based Purchasing (HVBP) program. Few providers traditionally have assumed the risk for outpatient documentation and coding. Under ACOs and HVBPs, more providers are assuming risk when they record health status for their patients. That means good things for providers that accurately capture their patients’ health status benefits. Providers who fail to capture relevant conditions receive lower reimbursement payments.
Prospective risk models applied to retrospective data have a number of potential applications for health plan managers and other decision makers concerned with identifying high-cost cases. A straightforward application is to use a risk model as a primary or complementary needs assessment tool. Large organizations can produce their own model coefficients and predicted expense scores, whereas smaller providers can just score their own memberships with factors based on larger, more generalized populations. Plans can use these individual-level cost predictions for case management patients who are most likely to exceed a predetermined cost threshold, whether set in dollars or percentiles. The cost limit will be set according to budgetary constraints and organizational objectives.
There is value in the identification of more clearly established chronic disease cohorts, such as enrollees with asthma. The disease classification system underlying a risk model can help stratify enrollees with asthma by the level of expected cost and comorbidity to develop appropriate disease management. For example, an enrollee with asthma, congestive heart failure and/or emphysema will cost more and utilize additional resources compared to an asthma patient without complications. Risk models could be especially important in the disease context because, at least for some conditions, case management proves to be effective. Similarly, risk models used to identify high-cost members of demographic groups, such as children (and their families), are invaluable. Targeted conditions would be those that are particularly expensive within those groups.
Depending on organizational interests and data availability, two- to three-year time gaps between risk-factor assessment and realized expense begs exploration. Shorter, six-month time gaps can also be examined, especially among subgroups with well-defined modifiable risk factors such as tobacco and alcohol use or sedentary lifestyle. This will be facilitated by more frequent, i.e., monthly, updates to diagnostic data that enhance the predictive performance of risk models by identifying patients closer to when the risk is realized. In addition, risk models can be used to create individual-level clinical profiles that might take the form of an overall expected cost (or, alternatively, a normalized risk score) and a list of the various disease classes or categories into which the patient falls. These clinical profiles can guide case managers in choosing the appropriate treatment.
A critical part of the risk adjustment program is data validation. CMS provides guidance for Risk Adjustment Data Validation (RADV) on the CMS.gov website and more information is located in the March 31, 2016 HHS-Operated Risk Adjustment Methodology Meeting Discussion Paper.
The following may help to determine a record’s suitability for RADV and provide some key criteria that should be considered when building a medical record checklist.
When Submitting a Record For RADV, Consider the Following:
- Is the record for the correct enrollee?
- Is the record from the correct calendar year for the payment year being audited? (For example, for audits of 2011 payments, validating records should be from calendar year 2010)
- Is the date of service present for the face-to-face visit? Is the record legible? Is the record from a valid provider type (hospital inpatient, hospital outpatient/physician)?
- Are credentials valid and/or is a valid physician specialty documented on the record?
- Does the record contain a signature from an acceptable type of physician specialist?
- If the outpatient/physician record does not contain a valid credential and/or signature, is there a completed CMS-generated attestation for this date of service?
- Is there a diagnosis on the record? Does the diagnosis support an HCC? Does the diagnosis support the requested HCC?
- If the condition warrants an inpatient hospitalization, the HCC may be supported by an inpatient record. Examples of such conditions may include septicemia, cerebral hemorrhage, cardiorespiratory failure and shock. For these conditions, an inpatient record, a stand-alone inpatient consultation record or a stand-alone discharge summary may be appropriate for submission.
- When possible, obtain a record from the specialist treating the condition, e.g., an oncologist for a cancer diagnosis. These records may be more likely to sufficiently document the condition.
- Pay particular attention to cancer diagnoses. A notation indicating “history of cancer,” without an indication of current cancer treatment, may not be sufficient documentation for validation. For example, if, in an attempt to validate HCC 10 (breast, prostate, colorectal and other cancers and tumors), a MA contract submits a record that indicates a patient has a history of cancer that was last treated outside the data collection year, the HCC may be not be validated.
- When reviewing medical records, pay special attention to the problem list on the electronic medical record. In certain systems, a diagnosis never drops off the list, even if the patient is no longer suffering from the condition. Conversely, the problem list may not document the HCC your MA contract submitted for payment.
- Any problem list in submitted documentation should be included and not just referenced.
- Records provided to validate HCCs that encompass additional manifestations or complications related to the disease (e.g., HCC 15, Diabetes with Renal Manifestations or Diabetes with Peripheral Circulatory Manifestations) should include language from an acceptable physician specialist that establishes a causal link between the disease and the complication. An acceptable record that clearly defines the complication or manifestation and expressly relates it to the disease may validate the HCC. A record that does not identify and link this relationship may not validate the HCC.
- If a physician or outpatient record is missing a provider’s signature and/or credentials, consider using the CMS-generated attestation that was provided with your data. CMS will only consider CMS-generated attestations for RADV.
- Minimum requirements for inpatient records state that these must contain an admission and discharge date. In addition:
- Inpatient records must include the signed discharge summary.
- Stand-alone consultations must contain the consultation date.
- Stand-alone discharge summaries submitted as physician provider type must contain the discharge date.
Getting Ready for 2017 and Beyond
The ultimate purpose of the CMS-HCC payment model is to promote fair payments to Medicare providers and Medicaid Managed Care Organizations by rewarding efficiency and encouraging the delivery of outstanding care for the chronically ill. The model has evolved over the past 20 years from detailed research, with careful attention to clinical credibility, realworld incentives and feasibility tradeoffs.
Continuous feedback between government technical staff and policymakers at CMS has shaped the CMS-HCC model. CMS has an ongoing commitment to evaluate the effect on organizations and the beneficiaries they serve. Their continued assessment of the model will identify the practicality and effects of matching healthcare resources to patients’ needs.
To that end, CMS has been working on areas for improvement by recently requesting comments and suggestions with the 2017 Payment Notice (81 Federal Register 12204).
After receiving feedback from the public and in response to the comments received, CMS is continuing its evaluation of potential data sources and determining if the risk adjustment methodology adequately captures the risk associated with:
- Partial year enrollment;
- Prescription drug utilization as a predictor in the model;
- Undercompensates for new or fast-growing plans;
- Pooling of high-cost enrollees;
- Proper evaluation of concurrent and prospective risk adjustment models;
- Model based on outdated data; and
- Improvements by including prescription drug utilization data as a predictor.
CMS’s continued priorities include making improvements in the risk assessment methodology to ensure that all of the provisions incorporated are accurately recalibrated for 2018 and 2019.
The information contained in this document provides general guidelines and information for the CMS Risk Adjustment Model and is in no way offering legal advice.