Evidence map›Paper›PMID 39014362›Full record

ArticleBMC health services research2024

Impact of decentralized management on sickness absence in hospitals: a two-wave cohort study of frontline managers in Danish hospital wards.

Thim Prætorius, Thomas Clausen, Ann Dyreborg Larsen, Jonas Kirchheiner Rasmussen, Lykke Margot Ricard, Peter Hasle

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Article in BMC health services research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Thim PrætoriusSteno Diabetes Center Aarhus, Aarhus University Hospital, Aarhus, Denmark. thipra@rm.dk.
Thomas ClausenNational Research Center for the Working Environment, Copenhagen, Denmark.
Ann Dyreborg LarsenNational Research Center for the Working Environment, Copenhagen, Denmark.
Jonas Kirchheiner RasmussenNational Research Center for the Working Environment, Copenhagen, Denmark.
Lykke Margot RicardDepartment of Technology and Innovation, University of Southern Denmark, Odense, Denmark.
Peter HasleDepartment of Technology and Innovation, University of Southern Denmark, Odense, Denmark.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis study explores the impact of decentralized management on the sickness absence among healthcare professionals. Sickness absence is a reliable indicator of employees' wellbeing and it is linked to management quality. However, the influence of decentralized management on sickness absence has not been adequately studied.

methodsThe research design combined a two-wave, web-survey of frontline managers in two Danish university hospitals with administrative data on sickness absence at the ward-level. The first and second wave included data from 163165 and 137 frontline managers linked to 121 wards and 108 wards. Data was analysed using an ordinal logistic regression model.

resultsWards where frontline managers had the highest level of decentralised decision authority compared to none showed lower odds of ward-level sickness absence (OR

conclusionHigher levels of decentralized management in wards were positively associated with lower risks of sickness absence in hospital wards. The study supports future research on how to empower decision autonomy at the frontline level of management.

Indexed as

Sick LeaveAbsenteeismAdultCohort StudiesDenmarkFemaleHospitals, UniversityHumansMaleMiddle AgedPoliticsSurveys and QuestionnairesCross-functional decision authorityDecentralised decision authorityDecision makingFrontline managersHospitalsSickness absence

Identifiers

PMID39014362
PMCPMC11250969

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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.