Validating an index dream dating now

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Assessment studies of conservation efforts have shown that best management practices were not always implemented in the most vulnerable areas where they are most needed.While complex computer simulation models can be used to identify these areas, resources needed for using such models are beyond reach for most water resources managers.To apply the index in administrative hospital discharge data, Deyo et al. (13) assessed the index's performance in ICD-10 international hospital discharge abstract databases.With advances in chronic disease management and improvements in treatments and technology, patients now survive longer than they did in 1984 when the original Charlson weights were developed.Canada has a government-financed universal health insurance system.

Among many potential comorbidity variables assessed, 17 were found to be associated with 1-year mortality. assigned a weighted score to each comorbid condition based on the relative risk of 1-year mortality.

After validating the index in breast cancer patients, Charlson et al.

reported that the score as an indicator of disease burden had a strong ability to predict mortality (1). (11) independently developed coding algorithms using the , Tenth Revision (ICD-10), coding algorithms to define the Charlson index, and Sundararajan et al.

For each diagnosis code, a 1-digit “diagnosis type” code is assigned to specify the timing of diagnosis (the principal diagnosis is the diagnosis primarily responsible for resource use).

Conditions that arise or are diagnosed after hospital admission are labeled postadmission comorbidities or complications.

For each patient, we retrieved all records 1 year prior to the date of the index hospitalization to identify comorbidities.

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