Evidence map›Paper›PMID 35999511›Full record

Observational studyBMC primary care2022

Patient satisfaction with computer-assisted structured initial assessment facilitating patient streaming to emergency departments and primary care practices: results from a cross-sectional observational study accompanying the DEMAND intervention in Germany.

Ingmar Schäfer, Agata Menzel, Tobias Herrmann, Jan Hendrik Oltrogge, Dagmar Lühmann, Martin Scherer

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in BMC primary care, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.3field-weighted citation impact, top 21% of its field
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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Observational
  2. Observational
  3. 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

6 authors at 2 institutions in 1 country.

Ingmar SchäferDepartment of Primary Medical Care, University Medical Center Hamburg-Eppendorf, Martinistr. 52, 20246, Hamburg, Germany. in.schaefer@uke.de.
Agata MenzelDepartment of Primary Medical Care, University Medical Center Hamburg-Eppendorf, Martinistr. 52, 20246, Hamburg, Germany.
Tobias HerrmannaQua Institut für angewandte Qualitätsförderung und Forschung im Gesundheitswesen GmbH, Göttingen, Germany.
Jan Hendrik OltroggeDepartment of Primary Medical Care, University Medical Center Hamburg-Eppendorf, Martinistr. 52, 20246, Hamburg, Germany.
Dagmar LühmannDepartment of Primary Medical Care, University Medical Center Hamburg-Eppendorf, Martinistr. 52, 20246, Hamburg, Germany.
Martin SchererDepartment of Primary Medical Care, University Medical Center Hamburg-Eppendorf, Martinistr. 52, 20246, Hamburg, Germany.
Universität Hamburg · DEUniversity Medical Center Hamburg-Eppendorf · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPatient numbers in emergency departments are on the rise. The DEMAND intervention aims to improve the efficacy of emergency services by computer-assisted structured initial assessment assigning patients to emergency departments or primary care practices. The aims of our study were to evaluate patient satisfaction with this intervention and to analyse if reduced patient satisfaction is predicted by sociodemographic data, health status or health literacy.

methodsWe conducted a cross-sectional patient survey in emergency departments and co-located primary care practices. Each intervention site was planned to participate for two observation periods, each with a duration of one full week. Study participants were recruited by the local staff. The patients filled out a written questionnaire during their waiting time. Patient satisfaction was assessed by agreement to four statements on a four point Likert scale. Predictors of patient satisfaction were identified by multilevel, multivariable logistic regression models adjusted for random effects at the intervention site level.

resultsThe sample included 677 patients from 10 intervention sites. The patients had a mean age of 38.9 years and 59.0% were women. Between 67.5% and 55.0% were fully satisfied with aspects of the intervention. The most criticised aspect was that the staff showed too little interest in the patients' personal situation. Full satisfaction ("clearly yes" to all items) was reported by 44.2%. Reduced patient satisfaction (at least one item rated as "rather yes", "rather no", "clearly no") was predicted by lower age (odds ratio 0.79 for ten years difference, 95% confidence interval 0.67/0.95, p = 0.009), presenting with infections (3.08,1.18/8.05,p = 0.022) or injuries (3.46,1.01/11.82,p = 0.048), a higher natural logarithm of the symptom duration (1.23,1.07/1.30,p = 0.003) and a lower health literacy (0.71 for four points difference, 0.53/0.94,p = 0.019).

conclusionsThe patients were for the most part satisfied with the intervention. Assessment procedures should be evaluated a) regarding if all relevant patient-related aspects are included; and whether patient information can be improved b) for patients with strong opinions about cause, consequences and treatment options for their health problem; and c) for patients who have problems in the handling of information relevant to health and healthcare.

trial registrationGerman Clinical Trials Register ( https://www.drks.de/drks_web/setLocale_EN.do ) no. DRKS00017014.

Indexed as

Emergency Service, HospitalPatient SatisfactionAdultChildComputersCross-Sectional StudiesFemaleGermanyHumansMalePrimary Health CareEmergency careEmergency department crowdingPatient streaming

Identifiers

PMID35999511
PMCPMC9397153
OpenAlexW4292756570

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.