ReviewAmerican journal of respiratory and critical care medicine2014
A universal decision support system. Addressing the decision-making needs of patients, families, and clinicians in the setting of critical illness.
Review in American journal of respiratory and critical care medicine, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 2 of them syntheses that pooled 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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
19 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Efficacy of decision aid delivery modes in prostate cancer screening: umbrella review and network meta-analysis.BJU international · 2025Pooled it
- Use of digital patient decision-support tools for atrial fibrillation treatments: a systematic review and meta-analysis.BMJ evidence-based medicine · 2025Pooled it
- Perceptions and Attitudes Toward Life-Sustaining Treatment Communication: A Comparison Between Physicians and Surrogates.Healthcare (Basel, Switzerland) · 2025Article
- Comparative Effectiveness of Decision Aids for Cancer-Screening Decision Making: An Overview of Reviews.Journal of general internal medicine · 2024Review
- Family Satisfaction of Polytrauma Patients in Intensive Care Unit at a Tertiary Care Center.Cureus · 2024Article
- The Role of Recipient Characteristics in Health Video Communication Outcomes: Scoping Review.Journal of medical Internet research · 2021Article
- Development and validation of a novel informational booklet for pediatric long-term ventilation decision support.Pediatric pulmonology · 2021Article
- Modelling clinical experience data as an evidence for patient-oriented decision support.BMC medical informatics and decision making · 2020Article
- Developing the family support tool: An interactive, web-based tool to help families navigate the complexities of surrogate decision making in ICUs.Journal of critical care · 2020Article
- Patients Decision Aid System Based on FHIR Profiles.Journal of medical systems · 2018Article
- Surrogate Decision Makers' Perspectives on Family Members' Prognosis after Intracerebral Hemorrhage.Journal of palliative medicine · 2018Article
- Family members' satisfaction with care and decision-making in intensive care units and post-stay follow-up needs-a cross-sectional survey study.Nursing open · 2018Article
- Recognizing difficult trade-offs: values and treatment preferences for end-of-life care in a multi-site survey of adult patients in family practices.BMC medical informatics and decision making · 2017Article
- The unmet need of information access for family members of ICU patients.Intensive care medicine · 2017Article
- Balancing digital information-sharing and patient privacy when engaging families in the intensive care unit.Journal of the American Medical Informatics Association : JAMIA · 2016Article
- Personalization and Patient Involvement in Decision Support Systems: Current Trends.Yearbook of medical informatics · 2015Review
- Development and usability testing of a Web-based decision aid for families of patients receiving prolonged mechanical ventilation.Annals of intensive care · 2015Article
- Feasibility and acceptability of a web-based advance care plan for dementia.Geriatric nursing (New York, N.Y.)Article
- Should We Use the IMPACT-Model for the Outcome Prognostication of TBI Patients? A Qualitative Study Assessing Physicians' Perceptions.MDM policy & practiceArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
In the setting of a complex critical illness, preference-sensitive decision making-choosing between two or more reasonable treatment options-can be difficult for patients, families, and clinicians alike. A common challenge to making high-quality decisions in this setting is a lack of critical information access and sharing among participants. Decision aids-brochures, web applications, and videos-are a major focus of current research because mounting evidence suggests they can improve decision-making quality and enhance collaborative shared decision making. However, many decision aids have important limitations, including a relatively narrow capacity for personalization, an inability to gather and generate clinical data, a focus on only a single disease or treatment, and high developmental costs. To address these issues and to help guide future research, we propose a model of "universal" electronic decision support that can be easily adapted by clinicians and patients/families for whatever decision is at hand. In this scalable web-based platform, a general shared decision-making core structure would accommodate simple, interchangeable disease and treatment information modules. The format and content of the system could be adapted to decisional participants' unique characteristics, abilities, and needs. Universal decision support can better standardize a decisional approach and also allow a unique degree of personalization within a framework of shared decision making. We also discuss potential criticisms of this approach as well as strategies that can overcome them in a critical illness setting.
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Registered trials
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.