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Uncertainty in serious illness: A national interdisciplinary consensus exercise to identify clinical research
Simon N Etkind1,2, Stephen Barclay1, Anna Spathis1,2
1Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.
Background:
Serious illness is characterised by uncertainty, particularly in older age groups. Uncertainty may be experienced by patients, family carers, and health professionals about a broad variety of issues. There are many evidence gaps regarding the experience and management of uncertainty.
Aim:
We aimed to identify priority research areas concerning uncertainty in serious illness, to ensure that future research better meets the needs of those affected by uncertainty and reduce research inefficiencies.
Methods:
Rapid prioritisation workshop comprising five focus groups to identify research areas, followed by a ranking exercise to prioritise them. Participants were healthcare professionals caring for those with serious illnesses including geriatrics, palliative care, intensive care; researchers; patient/carer representatives, and policymakers. Descriptive analysis of ranking data and qualitative framework analysis of focus group transcripts was undertaken.
Results:
Thirty-four participants took part; 67% female, mean age 47 (range 33-67). The highest priority was communication of uncertainty, ranked first by 15 participants (overall ranking score 1.59/3). Subsequent priorities were: 2) How to cope with uncertainty; 3) healthcare professional education/training; 4) Optimising clinical approaches to uncertainty; and 5) exploring in-depth experiences of uncertainty. Research questions regarding optimal management of uncertainty were given higher priority than questions about experiences of uncertainty and its impact.
Conclusions:
These co-produced, clinically-focused research priorities map out key evidence gaps concerning uncertainty in serious illness. Managing uncertainty is the most pressing issue, and researchers should prioritise how to optimally manage uncertainty in order to reduce distress, unlock decision paralysis and improve illness and care experience.
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