Evidence map›Paper›PMID 39712829›Full record

ReviewCureus2024

Enhancing Emergency Room Mental Health Crisis Response: A Systematic Review of Integrated Models.

Chiko Katiki, V Jaswitha S Ponnapalli, Kesha J Desai, Sadia Mansoor, Anushka Jindal, Nana Yaw Afriyie Badu

Abstract readReview
In one paragraph

Review in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Review
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.

Chiko KatikiEmergency Department, American International Medical School, Alpharetta, USA.
V Jaswitha S PonnapalliPsychiatry, California Institute of Behavioral Neurosciences and Psychology, Fairfield, USA.
Kesha J DesaiMedicine, Medical College Baroda, Vadodara, IND.
Sadia MansoorInternal Medicine, Dow University of Health Sciences, Karachi, PAK.
Anushka JindalSurgery, University Hospital Sussex, Worthing, GBR.
Nana Yaw Afriyie BaduSurgery, University of Ghana, Accra, GHA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The integration of psychiatric treatment into emergency services is critical to improving the management of severe mental health emergencies. Emergency departments (EDs) are frequently the initial point of contact for patients with mental emergencies, but they are not always prepared to offer adequate care. This systematic review aims to analyze the effectiveness of collaborative care models (CCMs), psychiatric consultation-liaison (C-L) teams, and telepsychiatry in enhancing psychiatric treatment in emergencies. We searched numerous databases, including PubMed, PsycINFO, EMBASE, and the Cochrane Library, for papers published between 2013 and 2023. A total of 18 studies matched our inclusion criteria, and the results show that integrated care models shorten hospital stays, enhance patient outcomes, and expand access to psychiatric treatments, particularly in remote locations. The limitations of this review include the heterogeneity of study designs and the underrepresentation of low-income countries. Future research should focus on developing standardized protocols for psychiatric integration into emergency services. This review bridges a critical gap in the literature by offering a comprehensive evaluation of various psychiatric care models in EDs and addressing existing barriers to implementation.

Indexed as

collaborative care modelsconsultation-liaison teamsemergency roompsychiatric caretelepsychiatry consultation

Identifiers

PMID39712829
PMCPMC11661900

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.