Key result
Predictive indices applied to administrative data identified 26 high-risk admitting diagnoses, among which 25% of patients experienced in-hospital medical complications.
Why the study?
Does the application of predictive indices using administrative data predict medical complications and adverse financial outcomes in hospitalized adult patients?
Population
321,558 adult patients discharged from a hospital network
Design
Cohort
Follow-up
In-hospital
Authors
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May support admission risk stratification via administrative data; leaves open need for prospective validation before guiding care.
Observational (n=321,558)
Yes
Does the application of predictive indices using administrative data predict medical complications and adverse financial outcomes in hospitalized adult patients?
Administrative data available at admission can effectively identify a small subset of patients at high risk for in-hospital medical complications and adverse financial outcomes.
Zarling et al. (1999) conducted an observational in In-hospital complications (n=321,558). Predictive indices using hospital administrative data was evaluated on Medical complications during hospitalization. Predictive indices applied to administrative data identified 26 high-risk admitting diagnoses, among which 25% of patients experienced in-hospital medical complications.
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