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Designing Healthcare Systems That Work for People With Chronic Illnesses & Disabilities

Payment & Risk Adjustment

Presenters:

Richard Kronick, Ph.D., Associate Professor and Chief, Division of Health Care Sciences, University of California, San Diego School of Medicine, La Jolla, CA.

Katharine K. Willrich, M.S., Director of Program Development, Division of Medical Assistance, Commonwealth of Massachusetts, Boston, MA.


States often adjust capitation rates for geographic and demographic variables (including aid category). These adjustments have limited capabilities to accurately predict service utilization of people with complex health needs.

Four states (Colorado, Maryland, Oregon, and Utah) are now using health-based risk adjustment, with other States (New Jersey, Minnesota, Michigan, and Delaware) far into the planning phase.

Health-based payment systems should meet four criteria:

  • Provision of accurate payments, with incentives for serving those with the greatest needs.
  • Ease of implementation.
  • Resistance to gaming.
  • Ongoing incentives for efficiency.

Dr. Kronick stressed that the usefulness of the system depends on how well it meets the four criteria, not simply its predictive value. For any system, the key ingredient is data that are equally good across Managed Care Organizations (MCOs) within the State.

Four diagnostic classification systems currently exist:

  • Ambulatory Clinical Groups (ACGs, developed by Johns Hopkins University).
  • Diagnostic Cost Groups (DCGs, developed by Boston University).
  • National Association of Children's Hospitals and Related Institutions (developed by 3M).
  • Chronic Illness and Disability Payment System (CDPS, developed by Dr. Kronick and others).

The Chronic Illness and Disability Payment System (CDPS, formerly DPS)—on publicly available software—was developed for people with disabilities enrolled in either Supplemental Security Income (SSI) or Aid to Families with Dependent Children or Temporary Assistance for Needy Families. Diagnoses are categorized by ICD-9 codes. To allow for variation within diagnoses, severity subcategories range from very high to very low cost. The system can account for comorbidities. It has not been applied to people dually eligible for Medicaid and Medicare.

Under CDPS, weights are calculated for each grouping, then an average case-mix value is determined for the MCO based on its enrolled population.

Colorado makes these calculations twice per year, and Oregon and Utah once per year. Maryland uses rate cells, which it calculates in real time. Colorado and Oregon use encounter data; Maryland uses fee-for-service data prior to enrollment.

Several States have or are planning to merge Medicaid and Medicare data to better understand the utilization and expenditure patterns of dually eligible beneficiaries. Massachusetts' initiative for integrated services for dually eligible persons is the Senior Care Options program (being developed with Health Care Financing Administration [HCFA]).

No Medicaid waivers are required for this voluntary program; Medicare 222 payment waivers and Medicare+Choice variances will be granted by HCFA to jointly selected Senior Care Organizations (SCOs). SCOs will be accountable for providing all covered services and improving quality of care.

Linked Medicaid and Medicare data (both eligibility and claims data) is used by the policymakers implementing the Senior Care Options program for multiple purposes, including:

  • To profile the dually eligible population (county distribution by age, gender, diagnoses, institutional status, and frailty, using a proxy based on service use and home and community-based services (HCBS) waiver enrollment).
  • To examine Medicare and Medicaid spending for this population.
  • To design capitation methodologies that promote the development of SCOs, eliminate cost-shifting between Medicare and Medicaid, and control the rate of growth.
  • To establish benchmarks for quality measures (e.g., rates of preventable hospitalizations).
  • To assess SCO provider network needs and capacity.

Ms. Willrich presented several reasons for States to link data; such linked data:

  • Provide a more accurate and complete picture of the population.
  • Help in developing better risk adjusters.
  • Allow for flexibility to create different analysis files for different uses.

However, linking data is very costly, requiring ongoing internal and external resources in finances and personnel.

References

Health Care Financing Administration. Report to Congress: proposed method of incorporating health status risk adjusters into Medicare+Choice payments. Baltimore (MD): Office of Strategic Planning, Research and Evaluation Group, Division of Payment Research; 1999 Mar.

Newhouse JP, Beeuwkees M, Chapman JD. Risk adjustment and Medicare. New York (NY): The Commonwealth Fund; 1997 Apr. Available at: http://www.cmwf.org/programs/medfutur/riskex.asp

Kronick R, Gilnmer T, Dreyfus T, et al. The chronic illness and disability payment system: health-based payment for SSI and TANF Medicaid Beneficiaries. San Diego (CA): Department of Family and Community Medicine, University of California, San Diego; 1999 Jul.

American Public Health Services Association. Capitation rate development guide for States implementing Medicaid Managed Care programs. Washington (DC): American Public Health Services Association; 1999 May.

Merlis M. (Institute for Health Policy Solutions, Washington, DC) Linked Medicare and Medicaid data on dually eligible beneficiaries: progress and challenges. Portland (ME): Muskie School of Public Service, University of Southern Maine; 1999 Sep.

Profile of dually eligible seniors in Massachusetts 1995: a MassHealth senior care options technical assistance report. Washington (DC): The Massachusetts Division of Medical Assistance and JEN Associates, Inc.; 1999 Mar.


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