Improving Health-Based Payment for Medicaid Beneficiaries: CDPS - Chronic Illness and Disability Payment System

Health Care Financing Review, Spring, 2000 by Richard Kronick, Todd Gilmer, Tony Dreyfus, Lora Lee

In theory, if the gathering and reporting of diagnoses were perfect, it would be advantageous to include high-frequency, low-cost diagnoses because their presence would increase accuracy and fairness by bringing more money to the plans that serve people with greater needs. In practice, however, plans' ability and eagerness to make and report diagnoses might vary. As we argued previously, the more high-frequency, low-cost diagnoses are included, the more apparent variation in need is likely to result from differences in reporting, not actual differences in need.

An important consideration in deciding whether to include diagnoses for payment purposes is whether there is reason to expect uneven distribution of enrollees with a certain diagnosis across plans. For many of the extremely low-cost diagnoses, such as bladder infections, minor upper respiratory conditions, or ear infections, there is little reason to expect that people with these conditions will be distributed unevenly among plans. On the other hand, some other low-cost conditions, such as hypertension, migraines, or asthma, have somewhat higher cost effects and might be distributed unevenly among plans, and plans that have stronger specialist networks or are located in poorer neighborhoods might attract a disproportionate share. In addition, encouraging plans to diagnose these conditions has a value in itself because attention to them can be highly beneficial for individual health. The inclusion of hypertension is particularly important for this reason and also because 13 percent of disabled adults are coded with hypertension but not more serious cardiovascular disease.

As a result of all these considerations, we decided to eliminate many of the lower cost conditions from our recommended payment model. We recommend the use of 56 diagnostic subcategories for payment purposes and an additional 15 subcategories of high-frequency diagnoses with very small cost effects only for profiling purposes.

Counting Diagnoses with the CDPS Subcategories

The organization of diagnostic categories and the rules for counting diagnoses are somewhat different in CDPS than they were in the original DPS. The most obvious change is an increase in the number of diagnostic subcategories, from 43 in DPS to 56 in CDPS, which results partly from the more comprehensive and larger set of diagnoses included in CDPS. Some of the new subcategories result from increasing distinctions among diagnoses that were in DPS, while other new subcategories are in new major areas. New major areas include infectious disease, pregnancy, and infants. Two new subcategories resulted from creating separate subcategories for Type 1 and Type 2 diabetes. And several other major categories gained a subcategory to reflect finer distinctions among cost levels.

A less obvious but equally significant change is in the rules used for counting diagnoses within major categories. In the original DPS, 10 of the 18 major categories were designated as "hierarchic" categories in which only the single most severe diagnosis within the major category was counted, while 8 were designated as "fully counted" categories in which multiple diagnoses could be counted. Our use of fully counted categories had been intended to capture the additional needs that arise from distinct diseases, but in revisiting this issue, we placed a higher value on limiting incentives for proliferative coding and on consistency across major categories. We also found relatively little predictive benefit in counting multiple diagnoses within major categories. As a result, every one of the major categories in CDPS is counted hierarchically. This change in the counting rules simplifies the model, strengthens its resistance to additional coding, and produces only small decreases in the accuracy of simulated payments.