Validating a model using statistics
Objectives This study aimed to examine the prevalence of frailty coding within the Dr Foster Global Comparators (GC) international database.
We then aimed to develop and validate a risk prediction model, based on frailty syndromes, for key outcomes using the GC data set.
The score’s predictive capacity was higher in the elective group compared with non-elective, and may reflect improved performance in lower acuity states.
Conclusions Frailty syndromes can be coded in international secondary care administrative data sets.
To develop and test Dr Foster Global Frailty Score, Global Comparators data were extracted from 34 hospitals in nine countries: Australia, Belgium, Denmark, Finland, Italy, Netherlands, Norway, UK and USA.
Hospital Episode Statistics (HES) is an English national administrative data set, housed within the safe haven of NHS Digital, and contains administrative data from English hospital trusts, which are cleaned and securely stored.
In older persons, risk prediction models often use chronological age,20 comorbidity21 and functional dependence22 as patient-specific factors for risk prediction.
Differences in the health and function of individuals as they grow older is not readily explained by chronological age.5 Frailty is common and increasingly prevalent with advancing age and often defined as a decrease in physiological reserve over a life course.
The Global Comparators programme at Dr Foster was an international hospital collaborative which ran from 2011 to 2017, focused on pooling and benchmarking data, knowledge-sharing networks and health services research to better understand variations in outcomes and disseminate international best practice.
The hospitals within the collaboration contributed administrative data to be pooled within the Global Comparators data set, using established data cleaning processes.36 This provided a rich patient-level data set containing demographics, diagnostic codes, procedure codes and outcomes, collected primarily for administrative purposes, such as operational needs and costing.
A weighting was then created for each syndrome group and summated to create the Dr Foster Global Frailty Score.
Performance of the score for predictive capacity was compared with an established prognostic comorbidity model (Elixhauser) and tested on another administrative database Hospital Episode Statistics (2011-2015), for external validation.