MétaCan
Menu
Back to cohort
Record W4412869601 · doi:10.2196/72552

SPAN@DEM (SingHealth Patient Advocacy Network @ Department of Emergency Medicine)—A Pioneer in Emergency Department-Specific Patient Advocacy: Development Study

2025· article· en· W4412869601 on OpenAlexvenueno aff
Marilyn Ng, Zhenghong Liu, Mohan Pillay, Sook Mei Chang, Bingqian Tan

Bibliographic record

VenueJournal of Participatory Medicine · 2025
Typearticle
Languageen
FieldMedicine
TopicEmergency and Acute Care Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPreprintEmergency departmentAeronauticsSpan (engineering)EngineeringMedical emergencyMedicineComputer scienceNursingWorld Wide WebCivil engineering

Abstract

fetched live from OpenAlex

Background: Launched in January 2022, the SingHealth Patient Advocacy Network at the Department of Emergency Medicine (SPAN@DEM) represents the first emergency department-specific advocacy group in Singapore. This initiative marks a significant advancement in local patient advocacy efforts because it employs a shared collaborative model to address the needs and concerns of patients within the unique context of the emergency department environment. SPAN@DEM emerged in recognition of the limitations of existing cluster-level advocacy groups, which are inadequate to address specific challenges inherent to the fast-paced, high-pressure nature of the emergency department. Objective: In this article, we describe the establishment of SPAN@DEM, discuss the challenges and considerations encountered, and reflect on lessons gleaned through this journey. Methods: A start-up committee, comprising two emergency physicians and four patient advocates, was convened to delineate the processes required to form a new patient advocacy group. Key features of SPAN@DEM include co-leadership by an emergency physician and a patient advocate, and diverse membership composition with equal representation from health care professionals and patient advocates. SPAN@DEM convenes quarterly with informal luncheons during meetings to foster open communication between advocates and health care staff. Membership is voluntary and motivated solely by altruism, and all members are required to participate in mandatory advocacy training to empower them to provide more actionable insights. Results: Since its inception, SPAN@DEM has implemented several initiatives such as PIKACHU (Project to Improve next-of-Kin Advice, Communications and Helpful Updates)-a suite of quality improvement measures that resulted in improved patient and next-of-kin satisfaction rates and reduced formal communication-related complaints-and Digital FAQ-an online web-based resource designed to clarify emergency department processes for patients. SPAN@DEM advocates have also contributed to the planning, design, and transition to the new Emergency Medicine Building. More importantly, SPAN@DEM has fostered a cultural shift towards patient-centered care, with the department now routinely engaging patient advocates in decisions affecting patient and next-of-kin experience. Conclusions: SPAN@DEM exemplifies the value of specialized emergency department-specific advocacy groups in advancing patient-centered emergency care. This model may serve as an exemplar for other health care institutions seeking to enhance patient advocacy efforts.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.099
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.070
GPT teacher head0.374
Teacher spread0.304 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Participatory MedicineSame topicEmergency and Acute Care StudiesFrench-language works237,207