Evidence map›Paper›PMID 41053639›Full record

ArticleBMC geriatrics2025

Emergency department visits due to severe falls: comparing patient self- reports and general practitioner records: A cross-sectional study.

Greta Fellhölter, Tim Stuckenschneider, Laura Himmelmann, Tania Zieschang

Abstract readComparative Study
In one paragraph

Article in BMC geriatrics, 2025. 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. Review
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

4 authors.

Greta FellhölterDepartment for Health Services Research, Geriatric Medicine, School of Medicine and Health Services, Carl von Ossietzky University, Ammerländer Heerstraße 114-118, Lower Saxony, 26129, Oldenburg, Germany.
Tim StuckenschneiderDepartment for Health Services Research, Geriatric Medicine, School of Medicine and Health Services, Carl von Ossietzky University, Ammerländer Heerstraße 114-118, Lower Saxony, 26129, Oldenburg, Germany. tim.stuckenschneider@uni-oldenburg.de.
Laura HimmelmannDepartment for Health Services Research, Geriatric Medicine, School of Medicine and Health Services, Carl von Ossietzky University, Ammerländer Heerstraße 114-118, Lower Saxony, 26129, Oldenburg, Germany.
Tania ZieschangDepartment for Health Services Research, Geriatric Medicine, School of Medicine and Health Services, Carl von Ossietzky University, Ammerländer Heerstraße 114-118, Lower Saxony, 26129, Oldenburg, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOlder individuals who experience a severe fall are at high risk for long-term consequences and require structured follow-up care including risk assessments and secondary prevention (e.g. exercise). Accurate knowledge of pre-existing diagnoses is essential for tailoring interventions. However, identifying these diagnoses in emergency department (ED) is challenging due to time constraints, high workload, potential recall bias after a traumatic event, and limited electronic data exchange across healthcare settings in Germany. This study analyses the concordance between self-reported diagnoses of adults aged > 60 years presenting to the ED after a fall without hospitalisation and diagnostic information provided by their general practitioners (GPs).

methodsData from the SeFallED study conducted in Germany were analysed. To analyse concordance, 28 major diagnostic groups (e.g. heart diseases, cancer, lung diseases) were established. Cohen's Kappa assessed the agreement between self-reported and GP-reported diagnoses. Logistic regression identified associations between population characteristics (e.g., cognition, concerns about falling, age) and discordance between self-reported and GP-reported diagnoses.

resultsA total of 216 participants (mean age 75.2), with an average of five diagnoses per person, were included. Agreement was almost perfect (K = 0.81-1.0) for Parkinson's disease, substantial (K = 0.61-0.80) for diabetes mellitus and cancer, and moderate (K = 0.41-0.60) for heart and lung diseases. Other conditions showed fair, poor, or no agreement. Age, sex, BMI, cognition, concerns about falling, education, and living arrangements were associated with discordance. Only higher concerns about falling were linked to non-agreement for overall diagnoses.

conclusionOverall, there was poor agreement between self-reported and GP-reported diagnoses. Special attention should be given to older adults and individuals with high concerns about falling, as these factors predicted discordance. Participants were more likely to report diseases with more noticeable symptoms and frequent monitoring such as Parkinson's disease or diabetes mellitus. To optimise follow-up care, improving the accuracy of diagnostic information is essential, which may be facilitated by harmonizing patient information across electronic systems (e.g., electronic health cards). Improved communication between GPs and patients regarding existing illnesses is also crucial to enhance the accuracy of patient self-reports.

trial registrationDRKS (Deutsches Register für klinische Studien, DRKS00025949, prospectively registered on 4th November, 2021).

Indexed as

Accidental FallsEmergency Service, HospitalGeneral PractitionersSelf ReportAgedAged, 80 and overCross-Sectional StudiesEmergency Room VisitsFemaleGermanyHumansMaleMiddle AgedEmergency departmentFalls preventionMorbidityOlder peopleSelf-report

Identifiers

PMID41053639
PMCPMC12502360

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LicenceCC BY
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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.