Evidence map›Paper›PMID 36192104›Full record

ArticleBMJ open2022

Contact tracing using real-time location system (RTLS): a simulation exercise in a tertiary hospital in Singapore.

Guan Yee Ng, Biauw Chi Ong

Abstract read
In one paragraph

Article in BMJ open, 2022. 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. Article
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

2 authors.

Guan Yee NgDuke-NUS Medical School, Singapore davegyng@gmail.com.ORCID 0000-0003-0391-6025
Biauw Chi OngMedical Board, Sengkang General Hospital, Singapore.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveWe aim to assess the effectiveness of contact tracing using real-time location system (RTLS) compared with the conventional (electronic medical records (EMRs)) method via an emerging infectious disease (EID) outbreak simulation exercise. The aims of the study are: (1) to compare the time taken to perform contact tracing and list of contacts identified for RTLS versus EMR; (2) to compare manpower and manpower-hours required to perform contact tracing for RTLS versus EMR; and (3) to extrapolate the cost incurred by RTLS versus EMR.

designProspective case study.

settingSengkang General Hospital, a 1000-bedded public tertiary hospital in Singapore.

participants1000 out of 4000 staff wore staff tags in this study.

interventionsA simulation exercise to determine and compare the list of contacts, time taken, manpower and manpower-hours required between RTLS and conventional methods of contact tracing. Cost of both methods were compared. PRIMARY AND SECONDARY OUTCOME MEASURES: List of contacts, time taken, manpower required, manpower-hours required and cost incurred.

resultsRTLS identified almost three times the number of contacts compared with conventional methods, while achieving that with a 96.2% reduction in time taken, 97.6% reduction in manpower required and 97.5% reduction in manpower-hours required. However, RTLS incurred significant equipment cost and might take many contact tracing episodes before providing economic benefit.

conclusionAlthough costly, RTLS is effective in contact tracing. RLTS might not be ready at present time to replace conventional methods, but with further refinement, RTLS has the potential to be the gold standard in contact tracing methods of the future, particularly in the current pandemic.

Indexed as

Contact TracingPandemicsComputer SystemsHumansSingaporeTertiary Care CentersCOVID-19EPIDEMIOLOGYHEALTH ECONOMICSHealth informaticsHealth policyInfection control

Identifiers

PMID36192104
PMCPMC9535253

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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.