ReviewCureus2025
Optimizing Specialist Consultation to Reduce Hospital Length of Stay.
Review in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Using Sydney Triage to Admission Risk Tool With Artificial Intelligence (START-AI) to Predict Inpatient Admitting Specialty for Emergency Department Patients: Single Centre Deep Learning Analysis.Emergency medicine Australasia : EMA · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Hospital length of stay (LOS) remains one of the most telling indicators of hospital performance, directly affecting patient safety, cost, bed availability, and overall care quality. Yet, while specialist consultation is a cornerstone of inpatient medicine, its role in influencing LOS is often misunderstood or misused. This review explores a more strategic approach: one that values not just when a consultant is called but how they are engaged. Early consultation, particularly in time-sensitive conditions such as chest pain or terminal illness, has been shown to accelerate diagnostics and streamline care transitions when tied to a clear clinical goal. However, equally important is early communication, reaching out to consultants at the beginning of their involvement and again at the start of the anticipated discharge day to clarify expectations, identify potential barriers, and confirm whether inpatient tasks can be safely shifted to outpatient follow-up. In contrast, reactive or unnecessary consultations frequently delay discharge through redundant testing, fragmented plans, or surprise recommendations late in the hospital course. Reducing LOS is not simply about avoiding delays, it is about building a collaborative culture in which consultants and primary teams share responsibility for discharge readiness, communicate proactively, and distinguish between what must be done in the hospital versus what can safely wait. Smarter consultation means earlier action, clearer alignment, and a hospital ecosystem where efficiency and safety go hand in hand.
Indexed as
Identifiers
What OpenQuestion holds
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.