Impact of data source and time reference of functional status on hospital mortality prediction

The study objective was to compare physical function documented in the medical records with interview data, and also to evaluate hospital mortality predictions using pre-admission and on-admission functional status derived from these two data sources.

A prospective cohort study of 1402 subjects aged 65 years and older to the general medicine department of an acute care hospital was conducted. Patient-reported pre-admission and on-admission functional status for impairment in any of the five activities of daily living (ADLs) items (feeding, dressing, grooming, toileting and bathing), transferring and walking, were compared with those extracted from the medical records. For the purpose of mortality prediction, pre-admission and on-admission impairment in transferring from the two data sources were included in separate multivariable logistic regression models. We used a variable selection method that combines bootstrap resampling with stepwise backward elimination.

For all ADL categories, the agreement between the data sources was good for pre-admission functional status (k: 0.53–0.75) but poor for on-admission status (k: 0.18–0.31). On-admission impairment was higher in the medical records than at interview for all basic ADLs. Using interview data as the gold standard, although sensitivity for pre- and on-admission ADLs was high (59–93%), specificity for on-admission status was poor (30–37%). The pre-admission models using interview data predicted mortality better than the model using medical records (c-statistic: 0.83 versus 0.82). Similar results were found for models incorporating on-admission functional status (c-statistic: 0.84 versus 0.81). However, the differences between the four models were not statistically significant.

Medical records can be a good source for pre-admission functional status but on-admission functional impairment was over-reported in the medical records. The discriminatory power of the hospital mortality prediction model was significantly improved with the incorporation of functional status information but it was not significantly affected by their time reference or source of data.