Evidence map›Paper›PMID 32938448›Full record

ArticleBMC medical informatics and decision making2020

Interviews with experts in rare diseases for the development of clinical decision support system software - a qualitative study.

Jannik Schaaf, Hans-Ulrich Prokosch, Martin Boeker, Johanna Schaefer, Jessica Vasseur, Holger Storf, Martin Sedlmayr

Open access · goldAbstract read
In one paragraph

Article in BMC medical informatics and decision making, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
2.3field-weighted citation impact, top 11% 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

8 citing papers in PubMed, 27 citations in OpenAlex.

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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 at 3 institutions in 1 country.

Jannik SchaafMedical Informatics Group (MIG), University Hospital Frankfurt, Frankfurt, Germany. jannik.schaaf@kgu.de.ORCID 0000-0002-0058-155X
Hans-Ulrich ProkoschChair of Medical Informatics, Department of Medical Informatics, Biometrics and Epidemiology, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany.
Martin BoekerInstitute of Medical Biometry and Statistics, Medical Faculty and Medical Centre - University of Freiburg, Freiburg, Germany.
Johanna SchaeferMedical Informatics Group (MIG), University Hospital Frankfurt, Frankfurt, Germany.
Jessica VasseurMedical Informatics Group (MIG), University Hospital Frankfurt, Frankfurt, Germany.
Holger StorfMedical Informatics Group (MIG), University Hospital Frankfurt, Frankfurt, Germany.
Martin SedlmayrInstitute for Medical Informatics and Biometry, Carl Gustav Carus Faculty of Medicine Technical University of Dresden, Dresden, Germany.
Goethe University Frankfurt · DEFriedrich-Alexander-Universität Erlangen-Nürnberg · DEUniversity of Freiburg · DE

Funding

Bundesministerium für Bildung und Forschung 01ZZ1801ABundesministerium für Bildung und Forschung 01ZZ1801BBundesministerium für Bildung und Forschung 01ZZ1801CBundesministerium für Bildung und Forschung 01ZZ1801L
6 · The paper itself

Abstract

backgroundPatients with rare diseases (RDs) are often diagnosed too late or not at all. Clinical decision support systems (CDSSs) could support the diagnosis in RDs. The MIRACUM (Medical Informatics in Research and Medicine) consortium, which is one of four funded consortia in the German Medical Informatics Initiative, will develop a CDSS for RDs based on distributed clinical data from ten university hospitals. This qualitative study aims to investigate (1) the relevant organizational conditions for the operation of a CDSS for RDs when diagnose patients (e.g. the diagnosis workflow), (2) which data is necessary for decision support, and (3) the appropriate user group for such a CDSS.

methodsInterviews were carried out with RDs experts. Participants were recruited from staff physicians at the Rare Disease Centers (RDCs) at the MIRACUM locations, which offer diagnosis and treatment of RDs. An interview guide was developed with a category-guided deductive approach. The interviews were recorded on an audio device and then transcribed into written form. We continued data collection until all interviews were completed. Afterwards, data analysis was performed using Mayring's qualitative content analysis approach.

resultsA total of seven experts were included in the study. The results show that medical center guides and physicians from RDC B-centers (with a focus on different RDs) are involved in the diagnostic process. Furthermore, interdisciplinary case discussions between physicians are conducted. The experts explained that RDs exist which cannot be fully differentiated, but rather described only by their overall symptoms or findings: diagnosis is dependent on the disease or disease group. At the end of the diagnostic process, most centers prepare a summary of the patient case. Furthermore, the experts considered both physicians and experts from the B-centers to be potential users of a CDSS. The experts also have different experiences with CDSS for RDs.

conclusionsThis qualitative study is a first step towards establishing the requirements for the development of a CDSS for RDs. Further research is necessary to create solutions by also including the experts on RDs.

Indexed as

Decision Support Systems, ClinicalRare DiseasesChildFemaleHumansMalePhysiciansQualitative ResearchSoftwareClinical decision support systemsComputer-assisted diagnosisInterviewQualitative researchRare diseases

Identifiers

PMID32938448
PMCPMC7493382
OpenAlexW3087696663

What OpenQuestion holds

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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.