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Care Management Challenges and Barriers for High-Cost Medicaid Beneficiaries

A recent GAO report explored the efforts to identify, predict, or manage high-expenditure beneficiaries. Five percent of high-cost Medicaid beneficiaries account for nearly half of the expenditures for all beneficiaries.

Examining beneficiaries who were enrolled only in Medicaid, the GAO found the most expensive 5 percent of beneficiaries were much more likely to have certain conditions—such as asthma, diabetes, and behavioral health conditions—than all other beneficiaries enrolled only in Medicaid. The GAO when examining 2009 data, found that about 65 percent of the total expenditures for high-expenditure beneficiaries enrolled only in Medicaid were for hospital services and long-term services and supports, with the remaining 35 percent of expenditures for drugs, payments to managed care organizations and premium assistance, and non-hospital acute care.

Care Management Strategies

Care management programs can be used as efforts to manage the cost and quality of health care services delivered to high-expenditure Medicaid populations, with the aim of improving outcomes and achieving cost savings. Care management programs seek to assist consumers manage physical and mental health conditions more effectively, for example, by assessing patient needs and coordinating care across different providers.

The GAO found seven selected states to explore strategies for managing high-expenditure beneficiaries. To manage costs and ensure quality of care for high-expenditure beneficiaries, the seven selected states used care management and other strategies.

How Did State Predict High-Expenditure Beneficiaries?

Through interviews with officials all seven selected states, five MCOs, and the ACO took at least one approach to identify or predict high-expenditure beneficiaries, and some took more than one approach. State officials said they used these approaches to identify or predict high-expenditure beneficiaries among different segments of their Medicaid populations, such as beneficiaries in fee-for-service delivery systems or those with certain chronic conditions.

The approaches were as follows:

  1. Using high-risk scores. Officials from most state agencies, MCOs, and the ACO said they used risk scores to identify or predict high-expenditure beneficiaries. Officials from four of the seven selected states, four MCOs, and the ACO said they used software or hired vendors who computed beneficiaries’ risk scores based on Medicaid service utilization data.

Washington state officials said that in addition to Medicaid service utilization data, they used utilization data from Medicare Parts A, B, and D to compute risk scores for their dual-eligible population. In contrast, officials from an MCO in Nevada said they considered risk scores alongside other contextual information, such as the recent diagnosis of a chronic condition, to predict whether the beneficiary would likely generate high expenditures in the future and should be assigned care management services. Officials from three states, an MCO in South Carolina, and the ACO interviewed said their software or vendors identified or predicted high-expenditure beneficiaries by using the risk scores they computed to stratify beneficiaries into risk tiers, such as low, medium, and high risk.

  1. Utilization. Officials from South Carolina’s state Medicaid agency and two MCOs from Pennsylvania and Washington said they identified high-expenditure beneficiaries by examining service utilization data to identify statistical outliers or trends.

Officials from the two MCOs said they looked for statistical outliers for various types of service utilization, such as emergency department visits, inpatient stays, and pharmacy use. Officials from South Carolina said they built internal software tools to help them easily examine service utilization for various subsets of beneficiaries and services. These officials said they looked for beneficiaries whose utilization appeared to be significantly higher or lower compared with other beneficiaries with similar characteristics, such as among children with Type 1 diabetes or among children in foster care.

The officials also said that after they identified those outliers, they examined the reasons for those beneficiaries’ utilization patterns to better understand why those beneficiaries were outliers and to take corrective action if appropriate. The officials explained that they did not simply focus on a discrete list of beneficiaries with the highest overall expenditures, because many of those beneficiaries have medical needs that are inherently expensive and cannot be meaningfully improved through intervention.

  1. Diagnosis. Officials from three of the seven state Medicaid agencies and four MCOs said they identified high-expenditure beneficiaries based on diagnoses or other group categorization. Officials commonly said they used chronic conditions, such as end-stage renal disease, the human immunodeficiency virus or acquired immune deficiency syndrome, chronic obstructive pulmonary disease, diabetes, or Hepatitis C. Pennsylvania officials said their list was developed based on clinical experience. Officials from South Carolina said their list of diagnoses was based on a review of conditions associated with high expenditures.
  1. Service Utilization and Claims Expenditures. Officials from two state Medicaid agencies—Indiana and Nevada—and all five MCOs said they identified high-expenditure beneficiaries as beneficiaries who exceed certain service utilization or claims expenditure thresholds.

Indiana officials said they used service utilization thresholds, such as visiting the emergency room six or more times in the past 6 months. Nevada officials said one of their programs identified high-expenditure beneficiaries as those whose treatment costs exceeded $100,000 over a 12-month period. Officials from the five MCOs offered varying thresholds, such as claims exceeding $100,000 over a 6-month period; claims exceeding $40,000 during a state fiscal year; or stays in a neonatal intensive care unit exceeding 15 days.

  1. Clinical Judgment. Officials from two state Medicaid agencies—Nevada and Pennsylvania— four MCOs, and the ACO said they relied on clinical judgment to decide whether a beneficiary was likely to be high expenditure. Officials from one MCO in Washington said the MCO conducted health assessments of new members to obtain a baseline understanding of their clinical states, which were then used to stratify beneficiaries and identify appropriate staff to address their needs.

Similarly, officials from Pennsylvania and three MCOs said clinical reviews of beneficiaries’ needs or histories were triggered by providers, caregivers, or self-referrals for care management or other services. Officials from the ACO said that while risk scores made initial predictions about beneficiaries’ risk for generating high expenditures, those predictions could be overridden by clinical judgment.

What are the Five Barriers to Care Management?

The report site five barriers to care management. Officials from the selected states, MCOs, and the ACO identified barriers to implementing care management for some high-expenditure Medicaid beneficiaries, including the inability to contact beneficiaries, the lack of social supports—that are part of what is referred  to as “social determinants of health”—and shortages of providers or care management staff in rural areas.

At the same time, states and MCOs can face challenges to addressing social determinants of health, such as lack of data on social determinants of health and a lack of understanding about the effect of social determinants of health on health care utilization, which if available could help bolster program investments in those areas.

Although CMS has programs such as the Health Home State Plan Option, the Financial Alignment Initiative, the Medicaid Innovation Accelerator Program, a State Data Resource Center, and the Medicare-Medicaid Data Integration Initiative, additional resources will be needed to reduce the expenditures of high-expenditure beneficiaries.


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