Evidence map›Paper›PMID 40428880›Full record

ReviewMedicina (Kaunas, Lithuania)2025

Strategies to Reduce Hospital Length of Stay: Evidence and Challenges.

Rahim Hirani, Dhruba Podder, Olivia Stala, Ryan Mohebpour, Raj K Tiwari, Mill Etienne

Abstract readReview
In one paragraph

Review in Medicina (Kaunas, Lithuania), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing 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

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.

3 · Its place in the literature

Who cites it

29 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.

Rahim HiraniSchool of Medicine, New York Medical College, Valhalla, NY 10595, USA.ORCID 0000-0002-9304-9916
Dhruba PodderSchool of Medicine, New York Medical College, Valhalla, NY 10595, USA.
Olivia StalaSchool of Medicine, New York Medical College, Valhalla, NY 10595, USA.
Ryan MohebpourSchool of Medicine, New York Medical College, Valhalla, NY 10595, USA.
Raj K TiwariSchool of Medicine, New York Medical College, Valhalla, NY 10595, USA.
Mill EtienneSchool of Medicine, New York Medical College, Valhalla, NY 10595, USA.ORCID 0000-0002-8086-3986

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hospital length of stay (HLOS) is a critical healthcare metric influencing patient outcomes, resource utilization, and healthcare costs. While reducing HLOS can improve hospital efficiency and patient throughput, it also poses risks such as premature discharge, increased readmission rates, and potential compromise of patient safety. This literature review synthesizes current evidence on the determinants of HLOS, including patient-specific factors such as demographics, comorbidities, and socioeconomic status, as well as hospital-related factors like admission route, resource allocation, and institutional policies. We also examine the relationship between HLOS and key clinical outcomes, including mortality, readmission rates, and healthcare-associated infections. Additionally, we evaluate predictive modeling approaches, including artificial intelligence and machine learning, for forecasting HLOS and guiding early intervention strategies. While interventions such as enhanced recovery after surgery (ERAS) protocols, multidisciplinary care teams, and structured discharge planning have demonstrated efficacy in reducing HLOS, their success varies based on healthcare setting, patient complexity, and resource availability. Predictive analytics, incorporating clinical and non-clinical variables, offer promising avenues for improving hospital efficiency, yet may carry risks related to data quality and model bias. Given the impact of HLOS on clinical and economic outcomes, targeted interventions and predictive models should be applied cautiously, with future research focusing on refining personalized discharge strategies and addressing disparities across diverse patient populations.

Indexed as

Length of StayHumansPatient DischargePatient Readmissionhealthcare efficiencyhospital length of staynosocomial infectionspatient outcomespredictive modeling

Identifiers

PMID40428880
PMCPMC12112870

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.