Purpose This study describes the reporting of the preference-based health-related quality-of-life (HRQOL) instrument, the EQ-5D, and proposes strategies to improve reporting and reduce research waste. The EQ-5D is a validated instrument widely used for health economic evaluation and is useful for informing health policy. Methods As part of a systematic review of papers reporting EQ-5D utility weights in patients with coronary artery disease, we noted the reasons data from some papers could not be reused in a meta-analysis, including whether health utility weights and sufficient statistical details were reported. Research waste was quantified using: (1) the percentage of papers and sample size excluded, and (2) researcher time and cost reviewing poorly reported papers. Results Our search strategy found 5942 papers. At title and abstract screening 93% were excluded. Of the 379 full text papers screened, 130 papers reported using EQ-5D. Only 46% (60/130) of those studies reported utility weights and/or statistical properties enabling meta-analysis. Only 67% of included papers had reported EQ-5D in the title or abstract. A total sample size of 133,298 was excluded because of poor reporting. The cost of researcher time wasted estimated to be between $3816 and $13,279 for our review. Conclusions Poor reporting of EQ-5D data creates research waste where potentially useful data are excluded from meta-analyses and economic evaluations. Poor reporting of HRQOL instruments also creates waste due to additional time spent reviewing papers for systematic reviews that are subsequently excluded. Recommendations Studies using the EQ-5D should report utility weights with appropriate summary statistics to enable reuse in meta-analysis and more robust evidence for health policy. We recommend authors report the HRQOL instrument in the title or abstract in line with current reporting guidelines (CONSORT-PRO and SPIRIT-PRO Extensions) to make it easier for other researchers to find. Validated instruments should also be listed in the Medical Subject Headings (MeSH) to improve cataloguing and retrieval of previous research.