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    Results: 1 to 20 of 99

    1.

    Performance of comorbidity, risk adjustment, and functional status measures in expenditure prediction for patients with diabetes.

    Maciejewski ML, Liu CF, Fihn SD.

    Diabetes Care. 2009 Jan;32(1):75-80. Epub 2008 Oct 22.PMID: 18945927 [PubMed - in process]Related articlesFree article

    2.

    The performance of administrative and self-reported measures for risk adjustment of Veterans Affairs expenditures.

    Maciejewski ML, Liu CF, Derleth A, McDonell M, Anderson S, Fihn SD.

    Health Serv Res. 2005 Jun;40(3):887-904.PMID: 15960696 [PubMed - indexed for MEDLINE]Related articlesFree article

    3.

    Use of diagnosis-based risk adjustment models to predict individual health care expenditure under the National Health Insurance system in Taiwan.

    Chang RE, Lai CL.

    J Formos Med Assoc. 2005 Dec;104(12):883-90.PMID: 16607444 [PubMed - indexed for MEDLINE]Related articles

    4.

    Predicting healthcare costs in a population of veterans affairs beneficiaries using diagnosis-based risk adjustment and self-reported health status.

    Pietz K, Ashton CM, McDonell M, Wray NP.

    Med Care. 2004 Oct;42(10):1027-35.PMID: 15377936 [PubMed - indexed for MEDLINE]Related articles

    5.

    Taking health status into account when setting capitation rates: a comparison of risk-adjustment methods.

    Fowles JB, Weiner JP, Knutson D, Fowler E, Tucker AM, Ireland M.

    JAMA. 1996 Oct 23-30;276(16):1316-21.PMID: 8861990 [PubMed - indexed for MEDLINE]Related articles

    6.

    Assessing and using comorbidity measures in elderly veterans with lower extremity amputations.

    Kurichi JE, Stineman MG, Kwong PL, Bates BE, Reker DM.

    Gerontology. 2007;53(5):255-9. Epub 2007 Apr 13.PMID: 17435390 [PubMed - indexed for MEDLINE]Related articles

    7.

    Applying diabetes-related Prevention Quality Indicators to a national cohort of veterans with diabetes.

    Helmer DA, Tseng CL, Brimacombe M, Rajan M, Stiptzarov N, Pogach L.

    Diabetes Care. 2003 Nov;26(11):3017-23.PMID: 14578233 [PubMed - indexed for MEDLINE]Related articlesFree article

    8.

    Health care expenditure prediction with a single item, self-rated health measure.

    DeSalvo KB, Jones TM, Peabody J, McDonald J, Fihn S, Fan V, He J, Muntner P.

    Med Care. 2009 Apr;47(4):440-7.PMID: 19238099 [PubMed - indexed for MEDLINE]Related articles

    9.

    Does the addition of functional status indicators to case-mix adjustment indices improve prediction of hospitalization, institutionalization, and death in the elderly?

    Mayo NE, Nadeau L, Levesque L, Miller S, Poissant L, Tamblyn R.

    Med Care. 2005 Dec;43(12):1194-202.PMID: 16299430 [PubMed - indexed for MEDLINE]Related articles

    10.

    Evaluating diagnosis-based risk-adjustment methods in a population with spinal cord dysfunction.

    Warner G, Hoenig H, Montez M, Wang F, Rosen A.

    Arch Phys Med Rehabil. 2004 Feb;85(2):218-26.PMID: 14966705 [PubMed - indexed for MEDLINE]Related articles

    11.

    Can pharmacy data improve prediction of hospital outcomes? Comparisons with a diagnosis-based comorbidity measure.

    Parker JP, McCombs JS, Graddy EA.

    Med Care. 2003 Mar;41(3):407-19.PMID: 12618644 [PubMed - indexed for MEDLINE]Related articles

    12.

    Characteristics of older adults who meet the annual prescription drug expenditure threshold for medicare medication therapy management programs.

    Daniel GW, Malone DC.

    J Manag Care Pharm. 2007 Mar;13(2):142-54.PMID: 17330975 [PubMed - indexed for MEDLINE]Related articlesFree article

    13.

    Risk adjustment for high utilizers of public mental health care.

    Kapur K, Young AS, Murata D.

    J Ment Health Policy Econ. 2000 Sep 1;3(3):129-137.PMID: 11967448 [PubMed - as supplied by publisher]Related articles

    14.

    In search of the perfect comorbidity measure for use with administrative claims data: does it exist?

    Baldwin LM, Klabunde CN, Green P, Barlow W, Wright G.

    Med Care. 2006 Aug;44(8):745-53.PMID: 16862036 [PubMed - indexed for MEDLINE]Related articles

    15.

    Risk-adjusted capitation based on the Diagnostic Cost Group Model: an empirical evaluation with health survey information.

    Lamers LM.

    Health Serv Res. 1999 Feb;33(6):1727-44.PMID: 10029506 [PubMed - indexed for MEDLINE]Related articlesFree article

    16.

    Higher costs and therapeutic factors associated with adherence to NCQA HEDIS antidepressant medication management measures: analysis of administrative claims.

    Robinson RL, Long SR, Chang S, Able S, Baser O, Obenchain RL, Swindle RW.

    J Manag Care Pharm. 2006 Jan-Feb;12(1):43-54.PMID: 16420107 [PubMed - indexed for MEDLINE]Related articlesFree article

    17.

    The responsiveness of disease-specific and generic health measures to changes in the severity of asthma among adults.

    Ware JE Jr, Kemp JP, Buchner DA, Singer AE, Nolop KB, Goss TF.

    Qual Life Res. 1998 Apr;7(3):235-44.PMID: 9584554 [PubMed - indexed for MEDLINE]Related articles

    18.

    Does diagnostic information contribute to predicting functional decline in long-term care?

    Rosen A, Wu J, Chang BH, Berlowitz D, Ash A, Moskowitz M.

    Med Care. 2000 Jun;38(6):647-59.PMID: 10843312 [PubMed - indexed for MEDLINE]Related articles

    19.

    Using risk-adjustment models to identify high-cost risks.

    Meenan RT, Goodman MJ, Fishman PA, Hornbrook MC, O'Keeffe-Rosetti MC, Bachman DJ.

    Med Care. 2003 Nov;41(11):1301-12.PMID: 14583693 [PubMed - indexed for MEDLINE]Related articles

    20.

    Comparison of the predictive validity of diagnosis-based risk adjusters for clinical outcomes.

    Petersen LA, Pietz K, Woodard LD, Byrne M.

    Med Care. 2005 Jan;43(1):61-7.PMID: 15626935 [PubMed - indexed for MEDLINE]Related articles

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