Browsing by keyword "Eligibility Determination"
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Nursing home residence confounds gender differences in Medicare utilization an example of Simpson's paradoxBACKGROUND: Gender differences in health care utilization in older Americans may be confounded by nursing home residence. Medicare data contain several files that can be used to create a measure of nursing home residence, but prior work has not addressed which best account for potential confounding. Simpson's paradox occurs when aggregated data support a different conclusion from what the disaggregated data show. We describe such a paradox that appeared when we sharpened our definition of "nursing home residence" while examining gender differences in Medicare utilization at the end of life. METHODS: To understand gender-specific health care utilization at the end of life, we conducted a retrospective analysis of a national random sample of Medicare beneficiaries aged 66 or older who died in 2001 with Parts A and B data for 18 months before death. We sought to associate each of total hospital days and costs during the final 6 months of life with numbers of primary care physician visits in the 12 preceding months. In addition to demographics, comorbidities, and geography, "nursing home residence" was a potential confounder, which we imputed in two ways: 1) from skilled nursing facility bills in the Part A Medicare Provider Analysis and Review (MedPAR) file; and 2) from Berenson-Eggers-Type-of-Service codes indicating widely spaced doctor visits in nursing homes obtained from Medicare's carrier file. CONCLUSION: Gender differences in Medicare utilization are strongly confounded by nursing home resident status, which can be imputed well from Medicare's carrier file, but not MedPAR. Inc. All rights reserved.
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Overview of publicly funded managed behavioral health care.Using MEDLINE and other Internet sources, the authors perform a systematic review of published literature. A total of 109 articles and reports are identified and reviewed that address the development, implementation, outcomes, and trends related to Managed behavioral health care (MBHC). MBHC remains a work in progress. States have implemented their MBHC programs in a number of ways, making interstate comparisons challenging. While managed behavioral health care can lower costs and increase access, ongoing concerns about MBHC include potential incentives to under-treat those with more severe conditions due to the nature of risk-based contracting, the tendency to focus on acute care, difficulties assuring quality and outcomes consistently across regions, and a potential cost-shift to other public agencies or systems. Success factors for MBHC programs appear to include stakeholder involvement in program and policy development, effective contract development and management, and rate adequacy.
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Using diagnoses to describe populations and predict costsThe Diagnostic Cost Group Hierarchical Condition Category (DCG/HCC) payment models summarize the health care problems and predict the future health care costs of populations. These models use the diagnoses generated during patient encounters with the medical delivery system to infer which medical problems are present. Patient demographics and diagnostic profiles are, in turn, used to predict costs. We describe the logic, structure, coefficients and performance of DCG/HCC models, as developed and validated on three important data bases (privately insured, Medicaid, and Medicare) with more than 1 million people each.
