Qual Life Res (2017) 26:2497–2505 DOI 10.1007/s11136-017-1599-0 Use of large-scale HRQoL datasets to generate individualised predictions and inform patients about the likely beneﬁt of surgery 1 1 Nils Gutacker Andrew Street Accepted: 20 May 2017 / Published online: 31 May 2017 The Author(s) 2017. This article is an open access publication Abstract Introduction Purpose The English NHS has mandated the routine collec- tion of health-related quality of life (HRQoL) data before and ‘‘But will this treatment help me?’’ This simple question after surgery, giving prospective patient information about the reﬂects one of the most commonly voiced concerns in likely beneﬁt of surgery. Yet, the information is difﬁcult to many consultations with a doctor. Patients facing surgery access and interpret because it is not presented in a lay- have always wanted to know about the risks they face and friendly format and does not reﬂect patients’ individual cir- whether treatment will be effective. Nowadays patients cumstances. We set out a methodology to generate person- increasingly want to be actively engaged in the (co-)man- alised information to help patients make informed decisions. agement of their medical condition, including the choice of Methods We used anonymised, pre- and postoperative treatment. To be
Quality of Life Research – Springer Journals
Published: May 31, 2017
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