Objective
To determine the incidence and types of preventable adverse events in elderly patients.
Design
Review of random sample of medical records in two stage process by nurses and physicians to detect adverse events. Two study investigators then judged preventability.
Setting
Hospitals in US states of Utah and Colorado, excluding psychiatric and Veterans Administration hospitals.
Subjects
15
000 hospitalised patients discharged in 1992.
000 hospitalised patients discharged in 1992.Main outcome measures
Incidence of preventable adverse events (number of preventable events per 100 discharges) in elderly patients (
65 years old) and non-elderly patients (16-64 years).
65 years old) and non-elderly patients (16-64 years).Results
When results were extrapolated to represent all discharges in 1992 in both states, non-elderly patients had 8901 adverse events (incidence 2.80% (SE 0.18%)) compared with 7419 (5.29% (0.37%)) among elderly patients (P=0.001). Non-elderly patients had 5038 preventable adverse events (incidence 1.58% (0.14%)) compared with 4134 (2.95% (0.28%)) in elderly patients (P=0.001). Elderly patients had a higher incidence of preventable events related to medical procedures (such as thoracentesis, cardiac catheterisation) (0.69% (0.14%) v 0.13% (0.04%)), preventable adverse drug events (0.63% (0.14%) v 0.17% (0.05%)), and preventable falls (0.10% (0.06%) v 0.01% (0.02%)). In multivariate analyses, adjusted for comorbid illnesses and case mix, age was not an independent predictor of preventable adverse events.
Conclusions
Preventable adverse events were more common among elderly patients, probably because of the clinical complexity of their care rather than age based discrimination. Preventable adverse drug events, events related to medical procedures, and falls were especially common in elderly patients and should be targets for efforts to prevent errors.



Contributors: EJT supervised data collection, conducted data analysis and interpretation, and wrote the paper. TAB was principal investigator, supervised data collection and analysis, interpreted data, and assisted in writing the paper. Mr Tim Zeena performed statistical programming. EJT is guarantor for the study.
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