Using stated-preferences methods to develop a summary metric to determine successful treatment of children with a surgical condition: a study protocol
IntroductionWide variation in the management of key paediatric surgical conditions in the UK has likely resulted in outcomes for some children being worse than they could be. Consequently, it is important to reduce unwarranted variation. However, major barriers to this are the inability to detect di...
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Veröffentlicht in: | BMJ open 2022-06, Vol.12 (6), p.e062833-e062833 |
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Sprache: | eng |
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Zusammenfassung: | IntroductionWide variation in the management of key paediatric surgical conditions in the UK has likely resulted in outcomes for some children being worse than they could be. Consequently, it is important to reduce unwarranted variation. However, major barriers to this are the inability to detect differences between observed and expected hospital outcomes based on the casemix of the children they have treated, and the inability to detect variation in significant outcomes between hospitals. A stated-preference study has been designed to estimate the value key stakeholders place on different elements of the outcomes for a child with a surgical condition. This study proposes to develop a summary metric to determine what represents successful treatment of children with surgical conditions.Methods and analysisPreferences from parents, individuals treated for surgical conditions as infants/children, healthcare professionals and members of the public will be elicited using paired comparisons and kaizen tasks. A descriptive framework consisting of seven attributes representing types of operations, infections treated in hospital, quality of life and survival was identified. An experimental design has been completed using a D-efficient design with overlap in three attributes and excluding implausible combinations. All participants will be presented with an additional choice task including a palliative scenario that will be used as an anchor. The survey will be administered online. Primary analysis will estimate a mixed multinomial logit model. A traffic light system to determine what combination of attributes and levels represent successful treatment will be created.Ethics and disseminationEthics approval to conduct this study has been obtained from the Medical Sciences Inter-Divisional Research Ethics Committee (IDREC) at the University of Oxford (R59631/RE001-05). We will disseminate all of our results in peer-review publications and scientific presentations. Findings will be additionally disseminated through relevant charities and support groups and professional organisations. |
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ISSN: | 2044-6055 2044-6055 |
DOI: | 10.1136/bmjopen-2022-062833 |