Evidence map›Paper›PMID 37525175›Full record

ArticleBMC medical informatics and decision making2023

Requirements analysis for an AI-based clinical decision support system for general practitioners: a user-centered design process.

Dania Schütze, Svea Holtz, Michaela C Neff, Susanne M Köhler, Jannik Schaaf, Lena S Frischen, Brita Sedlmayr, Beate S Müller

Abstract read
In one paragraph

Article in BMC medical informatics and decision making, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 3 pooled it
–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

15 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
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  6. Enhancing diagnostic precision for rare diseases using case-based reasoning.Journal of the American Medical Informatics Association : JAMIA · 2026
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  10. AI and Primary Care: Scoping Review.Journal of medical Internet research · 2025
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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

8 authors.

Dania SchützeGoethe University Frankfurt, Institute of General Practice, Theodor-Stern-Kai 7, 60590, Frankfurt, Germany. schuetze@allgemeinmedizin.uni-frankfurt.de.ORCID 0000-0003-4788-2082
Svea HoltzGoethe University Frankfurt, Institute of General Practice, Theodor-Stern-Kai 7, 60590, Frankfurt, Germany.ORCID 0000-0002-4477-701X
Michaela C NeffGoethe University Frankfurt, University Hospital, Institute of Medical Informatics, Frankfurt, Germany.ORCID 0000-0003-4286-7959
Susanne M KöhlerGoethe University Frankfurt, Institute of General Practice, Theodor-Stern-Kai 7, 60590, Frankfurt, Germany.ORCID 0000-0002-4255-1770
Jannik SchaafGoethe University Frankfurt, University Hospital, Institute of Medical Informatics, Frankfurt, Germany.ORCID 0000-0002-0058-155X
Lena S FrischenExecutive Department for Medical IT-Systems and Digitalization, University Hospital Frankfurt, Goethe University, Frankfurt, Germany.
Brita SedlmayrTechnische Universität Dresden, Institute for Medical Informatics and Biometry, Carl Gustav Carus Faculty of Medicine, Dresden, Germany.ORCID 0000-0001-6159-7822
Beate S MüllerGoethe University Frankfurt, Institute of General Practice, Theodor-Stern-Kai 7, 60590, Frankfurt, Germany.ORCID 0000-0002-6745-1047

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAs the first point of contact for patients with health issues, general practitioners (GPs) are frequently confronted with patients presenting with non-specific symptoms of unclear origin. This can result in delayed, prolonged or false diagnoses. To accelerate and improve the diagnosis of diseases, clinical decision support systems would appear to be an appropriate tool. The objective of the project 'Smart physician portal for patients with unclear disease' (SATURN) is to employ a user-centered design process based on the requirements analysis presented in this paper to develop an artificial Intelligence (AI)-based diagnosis support system that specifically addresses the needs of German GPs.

methodsRequirements analysis for a GP-specific diagnosis support system was conducted in an iterative process with five GPs. First, interviews were conducted to analyze current workflows and the use of digital applications in cases of diagnostic uncertainty (as-is situation). Second, we focused on collecting and prioritizing tasks to be performed by an ideal smart physician portal (to-be situation) in a workshop. We then developed a task model with corresponding user requirements.

resultsNumerous GP-specific user requirements were identified concerning the tasks and subtasks: performing data entry (open system, enter patient data), reviewing results (receiving and evaluating results), discussing results (with patients and colleagues), scheduling further diagnostic procedures, referring to specialists (select, contact, make appointments), and case closure. Suggested features particularly concerned the process of screening and assessing results: e.g., the system should focus more on atypical patterns of common diseases than on rare diseases only, display probabilities of differential diagnoses, ensure sources and results are transparent, and mark diagnoses that have already been ruled out. Moreover, establishing a means of using the platform to communicate with colleagues and transferring patient data directly from electronic patient records to the system was strongly recommended.

conclusionsEssential user requirements to be considered in the development and design of a diagnosis system for primary care could be derived from the analysis. They form the basis for mockup-development and system engineering.

Indexed as

Decision Support Systems, ClinicalGeneral PractitionersArtificial IntelligenceElectronic Health RecordsHumansUser-Centered DesignClinical decision support systemsComputer-assisted diagnosisPrimary careQualitative researchRequirements analysisUser-centered design

Identifiers

PMID37525175
PMCPMC10391889

What OpenQuestion holds

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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.