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.
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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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