Introduction: Functional decline is commonly assessed by questionnaire-based surveys; however, administrative data can provide an alternative to evaluate functional decline. The aim of this study was to find out whether administrative data can be used to predict functional decline by conducting a systematic review of the literature.

Methods: The methodology of the systematic review was based on PRISMA guidelines and PICOS process. The included studies were analyzed to identify different methods based on administrative to predict functional decline.

Results: Three predictive models were developed from outcome measures based on administrative data. Firstly, model based on hospital readmissions was used to predict functional decline. Both model and survey results were compared to predict restricted activity days over 4 years’ duration. Hospital readmission based model had a predictive accuracy (AUC 0.69) like self-reported surveys (AUC 0.71 p 0.14). Secondly, procedural claims-based codes were used to construct a model that identified hospital procedures and services associated with functional decline. The model was compared to self-reported information on activities of daily living. It showed sensitivity of 0.79 and specificity of 0.92. Thirdly, post-operative imaging and reoperation codes were reviewed as predictive indicators, but were found to have no significant association with functional decline.

Conclusion: Models based on hospital readmissions have the potential to be used widely because it has significant correlation with functional health and is a commonly recorded outcome measure in hospital administrative data. Its predictive accuracy is like self-reported functional health.