Collection and use of EQ-5D for follow-up, decision-making, and quality improvement in health care - the case of the Swedish National Quality Registries

Background: The Swedish National Quality Registries (NQRs) contain individual-level health care data for specific patient populations, or patients receiving specific interventions. Approximately 90% of the 105 Swedish NQRs include any patient-reported outcome measure, with EQ-5D being the most common. As there has been no general overview of EQ-5D data within the NQRs, this study fills a knowledge gap by reporting how the data are collected, presented, and used at different levels of the Swedish health care system. Methods: All 46 NQRs with a license for the use of EQ-5D were included. Information was retrieved from the registries’ annual reports or from websites, using a template that was subsequently sent to each registry for completion and confirmation. If considered necessary, the contact was followed-up with an interview, either inperson or over the telephone. The uses of EQ-5D were categorised as denoting usage for follow-up, decisionmaking, or quality improvement in Swedish health care. Results: In total, 41 of the 46 licensed registries reported collection of EQ-5D data. EQ-5D is most commonly collected within registries related to the musculoskeletal system, but it has a wide application also in other disease areas. Thirty-six registries provide EQ-5D results to patients, clinicians, or other decision-makers. Twenty-two of the registries reported that EQ-5D data are being used for follow-up, decision-making or quality improvement. The registries most commonly reported use of data for assessing interventions, and in quality indicators to follow-up the quality of care at a national level. Conclusion: Collection and use of EQ-5D data vary across the Swedish NQRs, which may partly be accounted for by the different purposes of the registries. The provided examples of use illustrate how EQ-5D data can inform decisions at different levels of the health care system. However, there is potential for improving the use of EQ-5D data

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