Measuring frailty in population-based healthcare databases: multi-dimensional prognostic indices for the improvement of geriatric care


Submitted: 20 October 2015
Accepted: 20 January 2016
Published: 14 April 2016
Abstract Views: 1830
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Authors

  • Janet Sultana Department of Clinical and Experimental Medicine, G. Martino Hospital, University of Messina, Messina, Italy.
  • Giorgio Basile Department of Clinical and Experimental Medicine, G. Martino Hospital, University of Messina, Messina, Italy.
  • Gianluca Trifiro' Department of Biomedical and Dental Sciences and Morphofunctional Imaging, G. Martino Hospital, University of Messina, Messina, Italy.
The prognostic evaluation of geriatric patients is critical in helping clinicians to weigh the risks versus the benefits of available therapeutic options. Frailty contributes significantly to the risk of mortality in older patients and is already known to have implications on the outcome of treatment in a clinical context. The multi-dimensional prognostic index (MPI) is a prognostic tool based on a comprehensive geriatric assessment and includes detailed information on patient cognition, functionality, disease and drug burden. The value of the MPI in predicting mortality has already been shown in hospital and community settings but never in a population- based healthcare database setting. One of the aims of the ongoing EU-funded MPI_Age project is to improve our understanding of how geriatric frailty data can be identified in healthcare databases and whether this can be used to predict serious adverse events associated with pharmacotherapy. Our findings suggest that data on functionality in elderly patients is poorly registered in The Health Improvement Network (THIN), a UK nationwide general practice database, and only few of the functionality domains could be used in a population-based analysis. The most commonly registered functionality information was related to mobility, dressing, accommodation and cognition. Our results suggest that some of these functionality domains are predictive of short- and long-term mortality in community-dwelling patients. This may have implications in observational research where frailty is an unmeasured confounder.

Supporting Agencies

European Commission

Sultana, J., Basile, G., & Trifiro’, G. (2016). Measuring frailty in population-based healthcare databases: multi-dimensional prognostic indices for the improvement of geriatric care. Geriatric Care, 2(1). https://doi.org/10.4081/gc.2016.5596

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