Strengths and limitations
This study involved 283 palliative care professionals completing a prognostic decision‐making task. The study followed a rigorous RCT study design, and analyses were conducted blinded, adding robustness to the findings. The experimental design allowed us to control for several variables involved in prognostic decision‐making, which meant we were able to isolate and quantify the degree to which clinicians' integration of advice were influenced by the source of the advice. It would have been difficult to achieve the same quantitative outcome, had the study relied on observations or interviews involving participants' strategies or attitudes towards integrating prognostic advice from colleagues or algorithms.There were some limitations with the experimental design. By necessity, the experimental set‐up was rather artificial and therefore lacked some ecological validity. Study vignettes were based on information from palliative care patients, collected as part of the PiPS2 study. This meant that some clinical information such as rate of decline was not available, which may have been useful in prognostic decision‐making. Also, most clinicians would usually expect to review a patient face‐to‐face before providing a prognostic estimate. Nonetheless, there are occasions when prognostic decisions might be made without face‐to‐face review (e.g. deciding on admission priorities to a hospice on the basis of information provided in referral forms).This study focused on patients' two‐week survival rather than survival to other time points. This was because the PiPS‐B algorithms and database which were used to create the vignettes are only able to calculate survival probabilities at either 14 or 56 days. Of these two time points, we were most interested in 14 days survival as we considered this to be the more clinically useful time point (identifying for instance those patients who may or may not be suitable for hospice admission or fast‐track arrangements for discharge home for terminal care). Future studies could explore the influence of other time frames, and whether these have an impact on clinicians' integration of advice.Another limitation of the study set‐up was the formulation of patients' survival in percentage probability estimates. Clinicians might not formulate prognoses using precise probability estimates, instead other formulations might be used to manage and mitigate prognostic uncertainty.Study participants were primarily doctors and nurses, while ‘other’ types of HCPs only represented 10% of the overall sample. This raises issues related to comparing the other types of HCPs to other professions. Since the hospices circulated the invitation email to their clinicians, we do not know how many clinicians were approached in total and if any selection bias was present. Future studies should aim at recruiting more other types of HCPs, creating a more balanced cohort of professional backgrounds.The magnitude of difference between the WOA in those receiving advice perceived to come from an algorithm as opposed to from another clinician was −0.12 (95% ‐0.18, −0.07). Although statistically significant, the clinical importance of this difference is not immediately apparent. There is no agreed minimally important clinical difference in WOA, and further research would be needed to fully understand the effect (if any) that these differences would have on real‐world clinical judgements or management plans.