Risk adjustment for dually eligible beneficiaries using long-term care.

Part of a special section on dually eligible Medicare and Medicaid beneficiaries. A study was conducted to examine use of the principal inpatient diagnostic cost groups (PIPDCG) and hierarchical coexisting conditions (HCC) risk-adjustment methodologies for a population of dually eligible beneficiar...

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Publicado en:Health Care Financing Review Vol. 20; no. 2; pp. 71 - 91
Autores principales: McCall, Nelda, Korb, Jodi
Formato: Artículo
Publicado: HCFA ORDS Publications Winter 1998
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Risk adjustment for dually eligible beneficiaries using long-term care.
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          McCall, Nelda
          Korb, Jodi
      su:
        Medicaid
        Medicare
        Long-term care of people with disabilities
        Medical care
        Risk assessment
        Long-term care of older people
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        subj:
          Medicaid
          Medicare
          Long-term care of people with disabilities
          Medical care
          Risk assessment
          Long-term care of older people
      keyword: Risk adjustment (Medical care)
      ab: Part of a special section on dually eligible Medicare and Medicaid beneficiaries. A study was conducted to examine use of the principal inpatient diagnostic cost groups (PIPDCG) and hierarchical coexisting conditions (HCC) risk-adjustment methodologies for a population of dually eligible beneficiaries receiving chronic long-term care. It was argued that measures of individual predictive accuracy for this population compared with the total Medicare population were similar for the PIPDCG models but somewhat smaller for the HCC models. In addition, it was contended that incorporating measures of functional status raised the R2 values by only a small amount for Medicare expenditures but by a somewhat larger amount for total expenditures. Finally, it was noted that the addition of other variables further enhanced the predictive power.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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