Development and validation of a modified Cambridge Multimorbidity Score for use with internationally recognized electronic health record clinical terms (SNOMED CT)

AbstractBackground: People with multiple health conditions are more likely to have poorer health outcomes and greater care and service needs; a reliable measure of multimorbidity would inform management strategies and resource allocation. This study aims to develop and validate a modified version of the Cambridge Multimorbidity Score in an extended age range, using clinical terms which are routinely used in electronic health records across the world (SNOMED CT).Methods and Findings<jats:p/>We curated new variables describing 37 health conditions and modelled the associations between these and 1-year mortality risk using the Cox proportional hazard model in a development dataset (n=300,000). We then developed two simplified models – a 20-condition model as per the original Cambridge Multimorbidity Score, and a variable reduction model using backward elimination with Akaike information criterion as the stopping criterion. The results were compared and validated for 1-year mortality in a synchronous validation dataset (n=150,000), and for 1-year and 5-year mortality in an asynchronous validation dataset (n=150,000).<jats:p/>Our final variable reduction model retained 21 conditions, and the conditions mostly overlapped with those in the 20-condition model. The model performed similarly to the 37- and 20-condition models, showing high discrimination and good calibration following recalibration.Conclusions<jats:p/>This modified version of the Cambridge Multimorbidity Score allows reliable estimation using clinical terms which can be applied internationally across multiple healthcare settings.