Evidence map›Paper›PMID 34868613›Full record

ArticleDigital health

More from less: Study on increasing throughput of COVID-19 screening and testing facility at an apex tertiary care hospital in New Delhi using discrete-event simulation software.

Naveen R Gowda, Amitesh Khare, H Vikas, Angel R Singh, D K Sharma, Ramya Poulose, Dhayal C John

Open access · goldAbstract read
In one paragraph

Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.4field-weighted citation impact, top 18% 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

3 citing papers in PubMed, 7 citations in OpenAlex.

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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

7 authors at 1 institution in 1 country.

Naveen R GowdaDepartment of Hospital Administration, All India Institute of Medical Sciences (AIIMS), India.ORCID https://orcid.org/0000-0002-5331-1107
Amitesh KhareDepartment of Hospital Administration, All India Institute of Medical Sciences (AIIMS), India.
H VikasDepartment of Hospital Administration, All India Institute of Medical Sciences (AIIMS), India.ORCID https://orcid.org/0000-0002-4789-3729
Angel R SinghDepartment of Hospital Administration, All India Institute of Medical Sciences (AIIMS), India.
D K SharmaAll India Institute of Medical Sciences (AIIMS), India.
Ramya PouloseAll India Institute of Medical Sciences (AIIMS), India.
Dhayal C JohnAll India Institute of Medical Sciences (AIIMS), India.
All India Institute of Medical Sciences · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOne of the challenges has been coping with an increasing need for COVID-19 testing. A COVID-19 screening and testing facility was created. There was a need for increasing throughput of the facility within the existing space and limited resources. Discrete event simulation was used to address this challenge. METHODOLOGY: A cross-sectional interventional study was done from September 2020 to October 2020. Detailed process mapping with all micro-processes was done. Patient arrival patterns and time taken at each step were measured by two independent observers at random intervals over two weeks. The existing system was simulated and a bottleneck was identified. Two possible alternatives to the problem were simulated and evaluated.

resultsScenario 1 showed a maximum throughput of 316. The average milestone times of all the processes after the step of "Preparation of sampling kits" jumped 62%; from 82 to 133 min. Staff state times also showed that staff at this step was stretched and medical lab technicians were underutilized. Scenario 2 simulated the alternative with lesser time spent on sampling kit preparation with a 22.4% increase in throughput, but could have led to impaired quality check. Scenario 3 simulated with increased manpower at the stage of bottleneck with 26.5% increase in throughput and was implemented on-ground.

conclusionDiscrete event simulation helped to identify the bottleneck, simulate possible alternative solutions without disturbing the ongoing work, and finally choose the most suitable intervention to increase throughput, without the need for additional space allocation. It therefore helped to optimally utilize resources and get "more from less."

Indexed as

COVID-19 testingDiscrete event simulationhealth care reengineeringhealth care simulationresource optimization

Identifiers

PMID34868613
PMCPMC8642042
OpenAlexW3203534422

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.