Proxy ratings of patient quality of life Factors related to patient–proxy agreement
Louise von Essén
Abstract
Open-access reader
Louise von Essén
Abstract
Open-access reader
It is generally agreed that patients are the best raters of their quality of life (QL). Where it is not possible to obtain information from the patient the use of proxies can be an alternative. The proxy can be a significant other or a healthcare provider. The use of a proxy offers a solution to non-response. The accuracy of proxy reports is most typically determined by examining the extent to which patient and proxy ratings agree. A literature overview shows that agreement depends on several factors. Methodological limitations may have an impact on agreement. Agreement also varies according to the QL domains under study; the highest agreement is usually found for concrete domains. In addition, patient and proxy characteristics are related to agreement. When designing QL studies the threat of selection bias due to exclusion of patients has to be balanced against the threat of information bias due to proxy ratings.
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It is generally agreed that patients are the best raters of their quality of life (QL). Where it is not possible to obtain information from the patient the use of proxies can be an alternative. The proxy can be a significant other or a healthcare provider. The use of a proxy offers a solution to non-response. The accuracy of proxy reports is most typically determined by examining the extent to which patient and proxy ratings agree. A literature overview shows that agreement depends on several factors. Methodological limitations may have an impact on agreement. Agreement also varies according to the QL domains under study; the highest agreement is usually found for concrete domains. In addition, patient and proxy characteristics are related to agreement. When designing QL studies the threat of selection bias due to exclusion of patients has to be balanced against the threat of information bias due to proxy ratings.
Key concepts: Proxy (statistics), Medicine, Selection bias, Agreement, Actuarial science, Econometrics, Statistics, Pathology