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Diabet Med ; 41(5): e15259, 2024 May.
Article in English | MEDLINE | ID: mdl-38017616

ABSTRACT

OBJECTIVE: Standardised person-reported outcomes (PRO) data can contextualise clinical outcomes enabling precision diabetes monitoring and care. Comprehensive outcome sets can guide this process, but their implementation in routine diabetes care has remained challenging and unsuccessful at international level. We aimed to address this by developing a person-centred outcome set for Type 1 and Type 2 diabetes, using a methodology with prospects for increased implementability and sustainability in international health settings. METHODS: We used a three-round questionnaire-based Delphi study to reach consensus on the outcome set. We invited key stakeholders from 19 countries via purposive snowball sampling, namely people with diabetes (N = 94), healthcare professionals (N = 65), industry (N = 22) and health authorities (N = 3), to vote on the relevance and measurement frequency of 64 previously identified clinical and person-reported outcomes. Subsequent consensus meetings concluded the study. RESULTS: The list of preliminary outcomes was shortlisted via the consensus process to 46 outcomes (27 clinical outcomes and 19 PROs). Two main collection times were recommended: (1) linked to a medical visit (e.g. diabetes-specific well-being, symptoms and psychological health) and (2) annually (e.g. clinical data, general well-being and diabetes self management-related outcomes). CONCLUSIONS: PROs are often considered in a non-standardised way in routine diabetes care. We propose a person-centred outcome set for diabetes, specifically considering psychosocial and behavioural aspects, which was agreed by four international key stakeholder groups. It guides standardised collection of meaningful outcomes at scale, supporting individual and population level healthcare decision making. It will be implemented and tested in Europe as part of the H2O project.


Subject(s)
Diabetes Mellitus, Type 2 , Humans , Diabetes Mellitus, Type 2/therapy , Delphi Technique , Consensus , Research Design , Mental Health
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