Managing clinical uncertainty in older people towards the end of life: a systematic review of person-centred tools

Abstract

Abstract Background Older people with multi-morbidities commonly experience an uncertain illness trajectory. Clinical uncertainty is challenging to manage, with risk of poor outcomes. Person-centred care is essential to align care and treatment with patient priorities and wishes. Use of evidence-based tools may support person-centred management of clinical uncertainty. We aimed to develop a logic model of person-centred evidence-based tools to manage clinical uncertainty in older people. Methods A systematic mixed-methods review with a results-based convergent synthesis design: a process-based iterative logic model was used, starting with a conceptual framework of clinical uncertainty in older people towards the end of life. This underpinned the methods. Medline, PsycINFO, CINAHL and ASSIA were searched from 2000 to December 2019, using a combination of terms: “uncertainty” AND “palliative care” AND “assessment” OR “care planning”. Studies were included if they developed or evaluated a person-centred tool to manage clinical uncertainty in people aged ≥65 years approaching the end of life and quality appraised using QualSyst. Quantitative and qualitative data were narratively synthesised and thematically analysed respectively and integrated into the logic model. Results Of the 17,095 articles identified, 44 were included, involving 63 tools. There was strong evidence that tools used in clinical care could improve identification of patient priorities and needs (n = 14 studies); that tools support partnership working between patients and practitioners (n = 8) and that tools support integrated care within and across teams and with patients and families (n = 14), improving patient outcomes such as quality of death and dying and satisfaction with care. Communication of clinical uncertainty to patients and families had the least evidence and is challenging to do well. Conclusion The identified logic model moves current knowledge from conceptualising clinical uncertainty to applying evidence-based tools to optimise person-centred management and improve patient outcomes. Key causal pathways are identification of individual priorities and needs, individual care and treatment and integrated care. Communication of clinical uncertainty to patients is challenging and requires training and skill and the use of tools to support practice.