Predicting Carer Health Effects for Use in Economic Evaluation
2017
Illnesses and interventions can affect the health status of family carers in addition to patients. However economic evaluation studies rarely incorporate data on health status of carers. In order to investigate whether changes in carer health status could be ‘predicted’ from the health data of those they provide care to, as a means of incorporating carer outcomes in economic evaluation, the authors used regression models to analyse changes in carers’ health status. They derive predictive algorithms based on variables relating to the patient through a case study of the family impact of meningitis, with 497 carer-patient dyads surveyed at two points.
The authors found that while it was feasible to estimate models to predict changes in carers’ health status, the predictions generated in an external testing sample were poorly correlated with the observed changes in individual carers’ health status. When aggregated, predictions provided some indication of the observed health changes for groups of carers, but a ‘one-size-fits-all’ predictive model of carer outcomes does not appear possible and further research aimed to identify predictors of carer’s health status from (readily available) patient data is recommended.
Predicting Carer Health Effects for Use in Economic Evaluation
Source:
Al-Janabi H, Manca A, Coast J. Predicting Carer Health Effects for Use in Economic Evaluation. PLOS One 2017; 12 (9): e0184886. https://doi.org/10.1371/journal.pone.0184886