Evidence map›Paper›PMID 37881363›Full record

ArticleFrontiers in digital health2023

A case for preference-sensitive decision timelines to aid shared decision-making in intensive care: need and possible application.

Beatrix Göcking, Sophie Gloeckler, Andrea Ferrario, Giovanna Brandi, Andrea Glässel, Nikola Biller-Andorno

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Article in Frontiers in digital health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Beatrix GöckingInstitute of Biomedical Ethics and History of Medicine, University of Zurich, Zurich, Switzerland.
Sophie GloecklerInstitute of Biomedical Ethics and History of Medicine, University of Zurich, Zurich, Switzerland.
Andrea FerrarioDepartment of Management, Technology, and Economics, Swiss Federal Institute of Technology in Zurich, Zurich, Switzerland.
Giovanna BrandiInstitute of Intensive Care Medicine, University Hospital Zurich, Zurich, Switzerland.
Andrea GlässelInstitute of Biomedical Ethics and History of Medicine, University of Zurich, Zurich, Switzerland.
Nikola Biller-AndornoInstitute of Biomedical Ethics and History of Medicine, University of Zurich, Zurich, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

advance care planningcritical caredecision aidsshared decision-makingsubarachnoid hemorrhagesurrogate decision-makers

Identifiers

PMID37881363
PMCPMC10595152

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.