Evidence map›Paper›PMID 40921645›Full record

ArticleBMJ open2025

Public perceptions of digitalisation and patient safety: a cross-sectional survey in Germany.

Olga Anastasia Amberger, Dorothea Lemke, Hardy Müller, Dagmar Lüttel, David Schwappach, Max Geraedts, Beate S Müller

Abstract read
In one paragraph

Article in BMJ open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

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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

7 authors.

Olga Anastasia AmbergerInstitute of General Practice, Goethe University Frankfurt, Frankfurt on the Main, Germany sawicki@allgemeinmedizin.uni-frankfurt.de.ORCID http://orcid.org/0000-0002-2207-6036
Dorothea LemkeInstitute of General Practice, Goethe University Frankfurt, Frankfurt on the Main, Germany.
Hardy MüllerGerman Society for Patient Safety, Reutlingen, Germany.
Dagmar LüttelGerman Society for Patient Safety, Reutlingen, Germany.
David SchwappachInstitute of Social and Preventive Medicine, Universität Bern, Bern, Switzerland.ORCID http://orcid.org/0000-0001-8668-3065
Max GeraedtsUniversity of Marburg, Marburg, Germany.
Beate S MüllerInstitute of General Practice, University of Cologne, Cologne, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo explore perceptions of digitalisation and patient safety from the view of the German general public and related sociodemographic factors.

designCross-sectional survey.

settingA nationwide survey was undertaken in 2024, using data from the Techniker Krankenkasse (TK) Monitor of Patient Safety. The TK Monitor of Patient Safety is an annual survey of the population on the state of patient safety in medical care.

participants1000 German adults (18 years and older). PRIMARY AND SECONDARY OUTCOME MEASURES: Ordinal logistic regression analyses were performed to investigate the associations among sociodemographic factors (age, gender, education and household income) and perceptions on digitalisation and patient safety.

resultsThe majority of respondents expected benefits from digital applications in healthcare. Over half of the respondents (58%) believed that artificial intelligence (AI) can help reduce complications and errors, while 49% of the respondents believed that the use of AI poses serious new risks for the healthcare sector. The results showed that sociodemographic variables are important factors influencing patient safety perceptions of digitalisation and AI. Female, older, less educated and/or lower-income individuals were less likely to perceive benefits from digital care applications and AI.

conclusionsIn our study, the German public appears to view digital technologies and AI as tools both for improving patient safety and as potential risk factors. Our findings also highlight the importance of analysing sociodemographic factors to identify specific disparities in how different groups are affected by digitalisation. Such analysis is essential for developing targeted strategies that mitigate current patient safety risks, ensuring that digital health solutions are equitable and safe across all demographic groups.

Indexed as

Artificial IntelligenceDigital TechnologyPatient SafetyPublic OpinionAdolescentAdultAgedCross-Sectional StudiesFemaleGermanyHumansMaleMiddle AgedSurveys and QuestionnairesYoung AdultArtificial IntelligenceCross-Sectional StudiesHealth & safetyPublic health

Identifiers

PMID40921645
PMCPMC12421183

What OpenQuestion holds

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LicenceCC BY-NC
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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.