Medicaid managed care: how to target efforts to reduce costs

BMC Health Serv Res. 2014 Nov 14;14:461. doi: 10.1186/1472-6963-14-461.


Background: To be successful, cost control efforts must target Medicaid Managed Care (MMC) beneficiaries likely to incur high costs. The critical question is how to identify potential high cost beneficiaries with simple, reproducible, transparent, auditable criteria. Our objective in this analysis was to evaluate whether the total burden of comorbidity, assessed by the Charlson comorbidity index, could identify MMC beneficiaries who incurred high health care costs.

Methods: The MetroPlus MMC claims database was use to analyze six months of claims data from 07/07-12/07; the analysis focused on the total amount paid. Age, gender, Charlson comorbidity score, serious mental illness and pregnancy were analyzed as predictors of total costs.

Results: We evaluated the cost profile of 4,614 beneficiaries enrolled at MetroPlus, an MMC plan. As hypothesized, the comorbidity index was a key correlate of total costs (p < .01). Yearly costs were more related to the total burden of comorbidity than any specific comorbid disease. For adults, in addition to comorbidity (p < .01) both serious mental illness (p < .01) and pregnancy (p < .01) were also related to total costs, while age, drug addiction and gender were not. The model with age, gender, comorbidity, serious mental illness, pregnancy and addiction explained 20% of the variance in total costs. In children, comorbidity (p < .01), serious mental illness (p < .01), addiction (p < .03) and pregnancy (p < .01) were associated with log cost; the model with those variables explained 6% of the variance in costs.

Conclusions: Comorbidity can be used to identify MMC beneficiaries most likely to have high costs.

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Comorbidity
  • Cost Control
  • Female
  • Humans
  • Insurance Claim Review
  • Male
  • Managed Care Programs / economics*
  • Medicaid / economics*
  • Middle Aged
  • New York City
  • Pregnancy
  • Risk Factors
  • United States