Evidence map›Paper›PMID 37106447›Full record

ArticleBMC primary care2023

Evaluating an app for digital medical history taking in urgent care practices: study protocol of the cluster-randomized interventional trial 'DASI'.

Eva Maria Noack, Dagmar Zajontz, Tim Friede, Kai Antweiler, Eva Hummers, Tobias Schmidt, Lea Roddewig, Dominik Schröder, Frank Müller

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC primary care, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.0field-weighted citation impact, top 23% 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

5 citing papers in PubMed, 4 citations in OpenAlex.

  1. Trial
  2. Review
  3. Article
  4. Article
  5. 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

9 authors at 3 institutions in 1 country.

Eva Maria NoackDepartment of General Practice, University Medical Center Göttingen, Humboldtallee 38, 37073, Göttingen, Germany. evamaria.noack@med.uni-goettingen.de.
Dagmar ZajontzDepartment of General Practice, University Medical Center Göttingen, Humboldtallee 38, 37073, Göttingen, Germany.
Tim FriedeDepartment of Medical Statistics, University Medical Center Göttingen, Humboldtallee 32, 37073, Göttingen, Germany.
Kai AntweilerDepartment of Medical Statistics, University Medical Center Göttingen, Humboldtallee 32, 37073, Göttingen, Germany.
Eva HummersDepartment of General Practice, University Medical Center Göttingen, Humboldtallee 38, 37073, Göttingen, Germany.
Tobias SchmidtDepartment of General Practice, University Medical Center Göttingen, Humboldtallee 38, 37073, Göttingen, Germany.
Lea RoddewigDepartment of General Practice, University Medical Center Göttingen, Humboldtallee 38, 37073, Göttingen, Germany.
Dominik SchröderDepartment of General Practice, University Medical Center Göttingen, Humboldtallee 38, 37073, Göttingen, Germany.
Frank MüllerDepartment of General Practice, University Medical Center Göttingen, Humboldtallee 38, 37073, Göttingen, Germany.
Universitätsmedizin Göttingen · DEMSH Medical School Hamburg – University of Applied Sciences and Medical University · DEUniversity of Göttingen · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn out-of-hours urgent care practices in Germany, physicians of different specialties care for a large number of patients, most of all unknown to them, resulting in a high workload and challenging diagnostic decision-making. As there is no common patient file, physicians have no information about patients' previous conditions or received treatments. In this setting, a digital tool for medical history taking could improve the quality of medical care. This study aims to implement and evaluate a software application (app) that takes a structured symptom-oriented medical history from patients in urgent care settings.

methodsWe conduct a time-cluster-randomized trial in two out-of-hours urgent care practices in Germany for 12 consecutive months. Each week during the study defines a cluster. We will compare participants with (intervention group) and without app use (control group) prior to consultation and provision of the self-reported information for the physician. We expect the app to improve diagnostic accuracy (primary outcome), reduce physicians' perceived diagnostic uncertainty, and increase patients' satisfaction and the satisfaction with communication of both physician and patient (secondary outcomes). DISCUSSION: While similar tools have only been subject to small-scale pilot studies surveying feasibility and usability, the present study uses a rigorous study design to measure outcomes that are directly associated with the quality of delivered care.

trial registrationThe study was registered at the German Clinical Trials Register (No. DRKS00026659 registered Nov 03 2021. World Health Organization Trial Registration Data Set, https://trialsearch.who.int/Trial2.aspx? TrialID = DRKS00026659.

Indexed as

Mobile ApplicationsAmbulatory CareCommunicationGermanyHumansMedical History TakingApplication softwareCluster randomized trialDiagnostic uncertaintyDigital medical history takingDigitizationGeneral practicemHealthOut-of-hours practiceUrgent care

Identifiers

PMID37106447
PMCPMC10133907
OpenAlexW4367182793

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.