Plain Language Summary

This research is crucial because it seeks to improve how health-related quality of life is assessed for individuals with dementia. Dementia impacts the ability of people to self-report their health status due to cognitive impairments, making it often necessary to use reports from caregivers, known as proxies. A commonly reported issue is the discrepancies between self-reports and proxy reports, with each source offering valuable insights into a person’s health-related quality of life.

The study highlights the importance of combining both self-reports and proxy reports to get a more complete picture of the individual's health status. Proxies included family members in the ACTIFCARE study and professional caregivers in the EPIC study. By integrating these reports, the study aims to predict combined utility values when both are available and apply mapping techniques to estimate them when only one type of report is collected, allowing a more accurate reflection of subtle changes in health status. This approach can greatly enhance economic evaluations of dementia interventions, which are crucial for healthcare decision making. This study builds on previous findings that certain health dimensions, like "pain/discomfort" and "anxiety/depression" are more accurately reported by patients themselves, while proxies are better at assessing "self-care" and "usual activities." Results of this study show that, for some dimensions, proxy report can reliably be used to predict self-report in people with dementia, especially for mild-to-moderate dementia.

For healthcare decision makers, this research suggests that using combined utility values can lead to more sensitive assessments of health-related quality of life, improving the evaluation of dementia treatments and policies. For patients and caregivers, it underlines the importance of considering multiple perspectives to get a comprehensive understanding of the patient's health-related quality of life. For researchers, it opens the door to further studies that can refine these models and explore their application in severe dementia cases, where the current data is limited.

Despite the promising results, challenges remain, particularly in severe dementia stages due to the lack of available data. The approach needs further validation and refinement to ensure its applicability across all stages of dementia and different living settings. Nonetheless, the study offers a promising method for improving health-related quality of life assessments and influencing healthcare policies and economic evaluations in dementia care.

^{Note: This content was created with assistance from artificial intelligence (AI) and has been reviewed and edited by ISPOR staff. For more information or for inquiries on ISPOR’s AI policy, click here or contact us at info@ispor.org.}