Methodological Issues Surrounding the Use of Baseline Health-Related Quality of Life Data to Inform Trial-Based Economic Evaluations of Interventions Within Emergency and Critical Care Settings: A Systematic Literature Review.

backgroundTrial-based cost-utility analyses require health-related quality of life data that generate utility values in order to express health outcomes in terms of quality-adjusted life years (QALYs). Assessments of baseline health-related quality of life are problematic where trial participants are incapacitated or critically ill at the time of randomisation. This review aims to identify and critique methods for handling non-availability of baseline health-related quality of life data in trial-based cost-utility analyses within emergency and critical illness settings.

methodsA systematic literature review was conducted, following PRISMA guidelines, to identify trial-based cost-utility analyses of interventions within emergency and critical care settings. Databases searched included the National Institute for Health Research (NIHR) Journals Library (1991-July 2016), Cochrane Library (all years); National Health Service (NHS) Economic Evaluation Database (all years) and Ovid MEDLINE/Embase (without time restriction). Strategies employed to handle non-availability of baseline health-related quality of life data in final QALY estimations were identified and critiqued.

resultsA total of 4224 published reports were screened, 19 of which met the study inclusion criteria (mean trial size 1670): 14 (74 %) from the UK, four (21%) from other European countries and one (5%) from India. Twelve studies (63%) were based in emergency departments and seven (37%) in intensive care units. Only one study was able to elicit patient-reported health-related quality of life at baseline. To overcome the lack of baseline data when estimating QALYs, eight studies (42%) assigned a fixed utility weight corresponding to either death, an unconscious health state or a country-specific norm to patients at baseline, four (21%) ignored baseline utilities, three (16%) applied values from another study, one (5%) generated utility values via retrospective recall and one (5%) elicited utilities from experts. A preliminary exploration of these methods shows that incremental QALY estimation is unlikely to be biased if balanced trial allocation is achieved and subsequent collection of health-related quality of life data occurs at the earliest possible opportunity following commencement of treatment, followed by an adequate number of follow-up assessments.

conclusionTrial-based cost-utility analyses within emergency and critical illness settings have applied different methods for QALY estimation, employing disparate assumptions about the health-related quality of life of patients at baseline. Where baseline measurement is not practical, measurement at the earliest opportunity following commencement of treatment should minimise bias in QALY estimation.