AUTHOR=Göcking Beatrix , Gloeckler Sophie , Ferrario Andrea , Brandi Giovanna , Glässel Andrea , Biller-Andorno Nikola TITLE=A case for preference-sensitive decision timelines to aid shared decision-making in intensive care: need and possible application JOURNAL=Frontiers in Digital Health VOLUME=5 YEAR=2023 URL=https://www.frontiersin.org/journals/digital-health/articles/10.3389/fdgth.2023.1274717 DOI=10.3389/fdgth.2023.1274717 ISSN=2673-253X ABSTRACT=

In the intensive care unit, it can be challenging to determine which interventions align with the patients' preferences since patients are often incapacitated and other sources, such as advance directives and surrogate input, are integral. Managing treatment decisions in this context requires a process of shared decision-making and a keen awareness of the preference-sensitive instances over the course of treatment. The present paper examines the need for the development of preference-sensitive decision timelines, and, taking aneurysmal subarachnoid hemorrhage as a use case, proposes a model of one such timeline to illustrate their potential form and value. First, the paper draws on an overview of relevant literature to demonstrate the need for better guidance to (a) aid clinicians in determining when to elicit patient preference, (b) support the drafting of advance directives, and (c) prepare surrogates for their role representing the will of an incapacitated patient in clinical decision-making. This first section emphasizes that highlighting when patient (or surrogate) input is necessary can contribute valuably to shared decision-making, especially in the context of intensive care, and can support advance care planning. As an illustration, the paper offers a model preference-sensitive decision timeline—whose generation was informed by existing guidelines and a series of interviews with patients, surrogates, and neuro-intensive care clinicians—for a use case of aneurysmal subarachnoid hemorrhage. In the last section, the paper offers reflections on how such timelines could be integrated into digital tools to aid shared decision-making.