Decision aids (DAs) are evidence-based tools that support shared decision-making (SDM) implementation in practice; this study aimed to identify existing osteoporosis DAs and assess their quality and efficacy; and to gain feedback from a patient advisory group on findings and implications for further research. We searched multiple bibliographic databases to identify research studies from 2000 to 2019 and undertook an environmental scan (search conducted February 2019, repeated in March 2020). A pair of reviewers, working independently selected studies for inclusion, extracted data, evaluated each trial’s risk of bias, and conducted DA quality assessment using the International Patient Decision Aid Standards (IPDAS). Public contributors (patients and caregivers with experience of osteoporosis and fragility fractures) participated in discussion groups to review a sample of DAs, express preferences for a new DA, and discuss plans for development of a new DA. We identified 6 studies, with high or unclear risk of bias. Across included studies, use of an osteoporosis DA was reported to result in reduced decisional conflict compared with baseline, increased SDM, and increased accuracy of patients’ perceived fracture risk compared with controls. Eleven DAs were identified, of which none met the full set of IPDAS criteria for certification for minimization of bias. Public contributors expressed preferences for encounter DAs that are individualized to patients’ own needs and risk. Using a systematic review and environmental scan, we identified 11 decision aids to inform patient decisions about osteoporosis treatment and 6 studies evaluating their effectiveness. Use of decision aids increased accuracy of risk perception and shared decision-making but the decision aids themselves fail to comprehensively meet international quality standards and patient needs, underpinning the need for new DA development.
- Decisions aids
- Shared decision-making
- Systematic review
ASJC Scopus subject areas
- Endocrinology, Diabetes and Metabolism