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    Using the case mix of pressure ulcer healing to evaluate nursing home performance

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    Authors
    Kapoor, Alok
    Kader, Boris
    Cabral, Howard
    Ash, Arlene S.
    Berlowitz, Dan R.
    UMass Chan Affiliations
    Department of Quantitative Health Sciences
    Document Type
    Journal Article
    Publication Date
    2008-06-28
    Keywords
    Age Factors
    Female
    Humans
    Male
    Middle Aged
    Nursing Homes
    Paralysis
    Pressure Ulcer
    *Quality Indicators, Health Care
    Severity of Illness Index
    Sex Factors
    Terminally Ill
    *Wound Healing
    Biostatistics
    Epidemiology
    Health Services Research
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    Link to Full Text
    http://dx.doi.org/10.1177/1062860608316109
    Abstract
    Pressure ulcer healing is an important quality measure for nursing homes, but the factors that predict healing have not been well studied. Using the Minimum Data Set, the authors identified candidate variables for a logistic regression, risk-adjustment model to predict ulcer healing. The authors then assessed model discrimination and calibration. Finally, the authors compared unadjusted with risk-adjusted performance for the individual facilities within a nursing home chain. Significant predictors of healing included mobility in bed, presence of a stage 2 ulcer (compared with a stage 4 ulcer), absence of paraplegia and quadriplegia, and absence of end-stage illness. The model C statistic was 0.67, and the calibration was acceptable. Judgments about nursing performance varied in 2 cases depending upon whether unadjusted or risk-adjusted performance was used. The model that the authors developed contains credible predictors of healing. Pressure ulcer healing may be one of many indicators used to evaluate nursing home quality.
    Source
    Am J Med Qual. 2008 Sep-Oct;23(5):342-9. Epub 2008 Jun 25. Link to article on publisher's site
    DOI
    10.1177/1062860608316109
    Permanent Link to this Item
    http://hdl.handle.net/20.500.14038/47611
    PubMed ID
    18583308
    Related Resources
    Link to Article in PubMed
    ae974a485f413a2113503eed53cd6c53
    10.1177/1062860608316109
    Scopus Count
    Collections
    Population and Quantitative Health Sciences Publications

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