Health-Related Quality-of-Life Measures
Semi-technical discussions about the science behind health-related quality-of-life measures such as those we offer at MyHealthOutcomes.
Clinical studies involving HRQOL endpoints have remained a niche pursuit over the past several decades owing to a variety of conceptual and methodological challenges. Enhanced interest in such studies is now driven by several powerful factors, including patient consumerism, product marketing, health economics, regulatory evolution and recent study results that have revealed how predictive HRQOL measures can be. New information technologies are available that can support cost-effective deployment of HRQOL studies longitudinally over large populations. Leading outcomes research organizations are creating new collaborative associations to increase the speed and efficiency of HRQOL clinical research.
Quantitative strategies for assaying patients’ ‘quality-of-life’ evolved as part of the medical outcomes and quality assessment initiatives that began three decades ago. Subsequent work has
produced a well-defined set of measurement tools for collecting healthrelated quality-of-life (HRQOL) data, although the basic concepts of health that these tools measure remain perplexingly
overlapped and amorphous. Rigorous development steps during the creation and validation of these HRQOL ‘instruments’ distinguish them from ad hoc survey questionnaires. Methodological issues do
nevertheless remain about how to deploy these data collection tools within the study design of clinical trials.
A preponderant body of clinical research has demonstrated the validity, reliability and responsiveness of health-related quality-of-life (HRQOL) data endpoints. HRQOL information is able to accurately characterize patient status and, as a consequence, it is now beginning to be applied to a variety of important non-research clinical activities, such as patient monitoring, risk prediction and quality assessment. For there to be routine, widespread use of HRQOL measures in clinical applications, advances will be required in information technology infrastructure and biostatistical strategies to enable the interpretation of the large-scale data sets that continually accrue. Also crucial to this will be studies demonstrating that clinical decisions guided by HRQOL data can yield sufficiently improved medical and financial outcomes to justify the cost and effort of HRQOL systems. As real-time health status tracking over entire patient populations becomes routine, each patient encounter will be guided by—and in turn will help shape—dynamically derived definitions of clinical guidelines. This fusion of clinical research and practice will finally enable the healthcare industry to monitor, define and improve the quality of its services with the accuracy that other industries have achieved for years.
The Seattle Angina Questionnaire, Kansas City Cardiomyopathy Questionnaire, and Peripheral Artery Questionnaire have been in widespread use in clinical trials, longitudinal clinical registries, and routine clinical practice for over a decade. Their development, validation, and use have been thoroughly documented in peer-reviewed scientific literature. We present here a brief synopsis of the work backing these instruments.