Thirty to sixty per cent of older patients experience functional decline after hospitalisation, associated with an increase in dependence, readmission, nursing home placement and mortality. First step in prevention is the identification of patients at risk. The objective of this study is to develop and validate a prediction model to assess the risk of functional decline in older hospitalised patients.
Aims and objectives: To examine the predictive properties of the brief Dutch National Safety Management Program for the screening of frail hospitalised older patients (VMS) and to compare these with the more extensive Maastricht Frailty Screening Tool for Hospitalised Patients (MFST-HP). Background: Screening of older patients during admission may help to detect frailty and underlying geriatric conditions. The VMS screening assesses patients on four domains (i.e. functional decline, delirium risk, fall risk and nutrition). The 15-item MFST-HP assesses patients on three domains of frailty (physical, social and psychological). Design: Retrospective cohort study. Methods: Data of 2,573 hospitalised patients (70+) admitted in 2013 were included, and relative risks, sensitivity and specificity and area under the receiver operating characteristic (AUC) curve of the two tools were calculated for discharge destination, readmissions and mortality. The data were derived from the patients nursing files. A STARD checklist was completed. Results: Different proportions of frail patients were identified by means of both tools: 1,369 (53.2%) based on the VMS and 414 (16.1%) based on the MFST-HP. The specificity was low for the VMS, and the sensitivity was low for the MFST-HP. The overall AUC for the VMS varied from 0.50 to 0.76 and from 0.49 to 0.69 for the MFST-HP. Conclusion: The predictive properties of the VMS and the more extended MFST-HP on the screening of frailty among older hospitalised patients are poor to moderate and not very promising. Relevance to clinical practice: The VMS labels a high proportion of older patients as potentially frail, while the MFST-HP labels over 80% as nonfrail. An extended tool did not increase the predictive ability of the VMS. However, information derived from the individual items of the screening tools may help nurses in daily practice to intervene on potential geriatric risks such as delirium risk or fall risk.
After being hospitalised, 30–60% of older patients experience a decline in functioning, resulting in a decreased quality of life and autonomy. The objective of this study was to establish a screening instrument for identifying older hospitalised patients at risk for functional decline by comparing the predictive values of three screening instruments: identification of seniors at risk, care complexity prediction instrument and hospital admission risk profile.
