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Morbidity during hospitalization: can we predict it?

M E Charlson, F L Sax, C R MacKenzie

    Journal of Chronic Diseases
    |January 1, 1987
    PubMed
    Summary
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    Physician assessment of patient stability accurately predicts hospitalization morbidity. Stable patients had a low risk of complications, while unstable patients faced significantly higher risks, highlighting the importance of this clinical judgment.

    Area of Science:

    • Internal Medicine
    • Clinical Prediction
    • Patient Safety

    Background:

    • Physicians utilize patient stability assessments to anticipate potential deterioration during hospitalization.
    • Accurate prediction of patient morbidity risk is crucial for effective medical management.

    Purpose of the Study:

    • To evaluate the accuracy of physicians' prospective assessment of patient stability in predicting morbidity.
    • To determine the predictive value of stability judgments for adverse events during hospitalization.

    Main Methods:

    • Prospective assessment of stability in 603 hospitalized medical patients.
    • Analysis of morbidity rates based on physician-assigned stability categories (stable, somewhat unstable, most unstable).
    • Multivariable analysis controlling for demographic and clinical variables.

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    Main Results:

    • Morbidity occurred in 12% of stable, 39% of somewhat unstable, and 61% of most unstable patients.
    • Physician estimates of patient stability were the most significant predictor of morbidity (p < 0.001).
    • Judgments of 'stable' had 87% negative predictive accuracy; 'unstable' had 46% positive predictive accuracy.

    Conclusions:

    • Physician judgment of patient stability is a highly significant predictor of hospitalization morbidity.
    • The concept of stability effectively identifies patients at higher risk for complications and deterioration.
    • Clinical assessment of stability should be integrated into risk stratification protocols for hospitalized patients.