A new version of the EQ-5D, the EQ-5D-5L, has been developed to improve sensitivity and standardize language across dimensions. This study aimed to produce a value set for the EQ-5D-5L to support decision-making. A 20-parameter hybrid model combined time trade-off (TTO) and discrete choice experiment (DCE) data to generate values for 3,125 health states. Valuation data from 996 respondents were used, with face validity demonstrated by lower values for more severe health states. Pain/discomfort and anxiety/depression received the greatest weight. Compared to the existing EQ-5D-3L value set, the EQ-5D-5L has fewer "worse than dead" states and a higher minimum value. Values range from -0.285 to 0.950. Results have important implications for users of the EQ-5D-5L both in England and internationally. Quality-adjusted life year gains from interventions may be smaller using this value set and may have been previously overestimated. The study followed an international protocol, with randomly selected members of the English general public completing TTO and DCE tasks. The EQ-5D-5L includes five dimensions with five levels each, describing 3,125 unique health states. The design allows for a direct link between measurement and valuation, with each health state summarized by a single value. Values are based on the general public's views, reflecting their importance in health decisions. The EQ-5D-5L is being incorporated into routine data collection in clinical settings and population health surveys. The study's results provide a value set for the EQ-5D-5L that can be used to support decision-making in the English NHS. The value set has international impact as NICE decisions influence global health technology assessment. The study is relevant to clinicians and health care professionals using PRO data in decision-making. It demonstrates the relative importance of different health problems in England and how they should be reflected in priority setting. The study used a hybrid model combining TTO and DCE data to generate values for 3,125 health states. The 20-parameter model was selected as it applied no assumptions about parameters. The model included three latent groups and provided a value set with a minimum value of -0.285 and 5.1% of health states valued as worse than dead. The value set reflects the relative weight placed on different health problems by the sample. Pain/discomfort and anxiety/depression received the greatest weight. The value set has important implications for health care decision-making, as it provides a more accurate reflection of health-related quality of life. The study highlights the importance of considering the heterogeneity of participants' views in health utilities and the nature of preference data that are bounded. The results demonstrate the value of using a hybrid model to combine TA new version of the EQ-5D, the EQ-5D-5L, has been developed to improve sensitivity and standardize language across dimensions. This study aimed to produce a value set for the EQ-5D-5L to support decision-making. A 20-parameter hybrid model combined time trade-off (TTO) and discrete choice experiment (DCE) data to generate values for 3,125 health states. Valuation data from 996 respondents were used, with face validity demonstrated by lower values for more severe health states. Pain/discomfort and anxiety/depression received the greatest weight. Compared to the existing EQ-5D-3L value set, the EQ-5D-5L has fewer "worse than dead" states and a higher minimum value. Values range from -0.285 to 0.950. Results have important implications for users of the EQ-5D-5L both in England and internationally. Quality-adjusted life year gains from interventions may be smaller using this value set and may have been previously overestimated. The study followed an international protocol, with randomly selected members of the English general public completing TTO and DCE tasks. The EQ-5D-5L includes five dimensions with five levels each, describing 3,125 unique health states. The design allows for a direct link between measurement and valuation, with each health state summarized by a single value. Values are based on the general public's views, reflecting their importance in health decisions. The EQ-5D-5L is being incorporated into routine data collection in clinical settings and population health surveys. The study's results provide a value set for the EQ-5D-5L that can be used to support decision-making in the English NHS. The value set has international impact as NICE decisions influence global health technology assessment. The study is relevant to clinicians and health care professionals using PRO data in decision-making. It demonstrates the relative importance of different health problems in England and how they should be reflected in priority setting. The study used a hybrid model combining TTO and DCE data to generate values for 3,125 health states. The 20-parameter model was selected as it applied no assumptions about parameters. The model included three latent groups and provided a value set with a minimum value of -0.285 and 5.1% of health states valued as worse than dead. The value set reflects the relative weight placed on different health problems by the sample. Pain/discomfort and anxiety/depression received the greatest weight. The value set has important implications for health care decision-making, as it provides a more accurate reflection of health-related quality of life. The study highlights the importance of considering the heterogeneity of participants' views in health utilities and the nature of preference data that are bounded. The results demonstrate the value of using a hybrid model to combine T