Evidence map›Paper›PMID 27957466›Full record

ArticleIranian journal of public health2016

Bed Capacity Planning Using Stochastic Simulation Approach in Cardiac-surgery Department of Teaching Hospitals, Tehran, Iran.

Amin Torabipour, Hojjat Zeraati, Mohammad Arab, Arash Rashidian, Ali Akbari Sari, Mahmuod Reza Sarzaiem

Open access · greenAbstract read
In one paragraph

Article in Iranian journal of public health, 2016. 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
1.5field-weighted citation impact, top 16% of its field
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, 9 citations in OpenAlex.

  1. Merging of two level-1 trauma centers in Amsterdam: premerger demand in integrated acute trauma care.European journal of trauma and emergency surgery : official publication of the European Trauma Society · 2024
    Observational
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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 at 3 institutions in 1 country.

Amin TorabipourDept. of Health Services Management, School of Health, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran; Dept. of Health Economics & Management, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Hojjat ZeraatiDept. of Epidemiology & Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Mohammad ArabDept. of Health Economics & Management, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Arash RashidianDept. of Health Economics & Management, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Ali Akbari SariDept. of Health Economics & Management, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Mahmuod Reza SarzaiemDept. of Cardiac Surgery, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.
Iran University of Medical Sciences · IRTehran University of Medical Sciences · IRAhvaz Jundishapur University of Medical Sciences · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo determine the hospital required beds using stochastic simulation approach in cardiac surgery departments.

methodsThis study was performed from Mar 2011 to Jul 2012 in three phases: First, collection data from 649 patients in cardiac surgery departments of two large teaching hospitals (in Tehran, Iran). Second, statistical analysis and formulate a multivariate linier regression model to determine factors that affect patient's length of stay. Third, develop a stochastic simulation system (from admission to discharge) based on key parameters to estimate required bed capacity.

resultsCurrent cardiac surgery department with 33 beds can only admit patients in 90.7% of days. (4535 d) and will be required to over the 33 beds only in 9.3% of days (efficient cut off point). According to simulation method, studied cardiac surgery department will requires 41-52 beds for admission of all patients in the 12 next years. Finally, one-day reduction of length of stay lead to decrease need for two hospital beds annually.

conclusionVariation of length of stay and its affecting factors can affect required beds. Statistic and stochastic simulation model are applied and useful methods to estimate and manage hospital beds based on key hospital parameters.

Indexed as

Cardiac surgery departmentHospital bedsHospital stayStochastic simulation

Identifiers

PMID27957466
PMCPMC5149475
OpenAlexW2526085363

What OpenQuestion holds

Textmetadata
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.