Evidence map›Paper›PMID 38743464›Full record

ArticleJournal of medical Internet research2024

The Effects of Displaying the Time Targets of the Manchester Triage System to Emergency Department Personnel: Prospective Crossover Study.

Jonas Bienzeisler, Guido Becker, Bernadett Erdmann, Alexander Kombeiz, Raphael W Majeed, Rainer Röhrig, Felix Greiner, Ronny Otto, Fabian Otto-Sobotka, AKTIN Research Group

Abstract read
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Article in Journal of medical Internet research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Observational
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

10 authors.

Jonas BienzeislerInstitute of Medical Informatics, Medical Faculty, RWTH Aachen University, Aachen, Germany.ORCID 0000-0003-3633-147X
Guido BeckerDedalus HealthCare, Bonn, Germany.ORCID 0009-0005-1305-3587
Bernadett ErdmannKlinikum Wolfsburg, Wolfsburg, Germany.ORCID 0009-0005-9530-6911
Alexander KombeizInstitute of Medical Informatics, Medical Faculty, RWTH Aachen University, Aachen, Germany.ORCID 0000-0001-9745-8576
Raphael W MajeedInstitute of Medical Informatics, Medical Faculty, RWTH Aachen University, Aachen, Germany.ORCID 0000-0002-8260-8815
Rainer RöhrigInstitute of Medical Informatics, Medical Faculty, RWTH Aachen University, Aachen, Germany.ORCID 0000-0002-0032-5118
Felix GreinerInstitute for Occupational and Maritime Medicine (ZfAM), University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany.ORCID 0000-0003-1171-9355
Ronny OttoDepartment of Trauma Surgery, Otto von Guericke University, Magdeburg, Germany.ORCID 0000-0002-5914-1129
Fabian Otto-SobotkaDivision of Epidemiology and Biometry, Faculty of Medicine and Health Sciences, Carl von Ossietzky University Oldenburg, Oldenburg, Germany.ORCID 0000-0002-9874-1311
AKTIN Research Groupsee Acknowledgements, .

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe use of triage systems such as the Manchester Triage System (MTS) is a standard procedure to determine the sequence of treatment in emergency departments (EDs). When using the MTS, time targets for treatment are determined. These are commonly displayed in the ED information system (EDIS) to ED staff. Using measurements as targets has been associated with a decline in meeting those targets.

objectiveThis study investigated the impact of displaying time targets for treatment to physicians on processing times in the ED.

methodsWe analyzed the effects of displaying time targets to ED staff on waiting times in a prospective crossover study, during the introduction of a new EDIS in a large regional hospital in Germany. The old information system version used a module that showed the time target determined by the MTS, while the new system version used a priority list instead. Evaluation was based on 35,167 routinely collected electronic health records from the preintervention period and 10,655 records from the postintervention period. Electronic health records were extracted from the EDIS, and data were analyzed using descriptive statistics and generalized additive models. We evaluated the effects of the intervention on waiting times and the odds of achieving timely treatment according to the time targets set by the MTS.

resultsThe average ED length of stay and waiting times increased when the EDIS that did not display time targets was used (average time from admission to treatment: preintervention phase=median 15, IQR 6-39 min; postintervention phase=median 11, IQR 5-23 min). However, severe cases with high acuity (as indicated by the triage score) benefited from lower waiting times (0.15 times as high as in the preintervention period for MTS1, only 0.49 as high for MTS2). Furthermore, these patients were less likely to receive delayed treatment, and we observed reduced odds of late treatment when crowding occurred.

conclusionsOur results suggest that it is beneficial to use a priority list instead of displaying time targets to ED personnel. These time targets may lead to false incentives. Our work highlights that working better is not the same as working faster.

Indexed as

Cross-Over StudiesEmergency Service, HospitalTriageAdultAgedFemaleGermanyHumansMaleMiddle AgedProspective StudiesTime FactorsAKTIN, process managementcrowdingEHRelectronic health recordemergency departmentemergency medicinehealth caretreatmenttriage system

Identifiers

PMID38743464
PMCPMC11134237

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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.