Evidence map›Paper›PMID 36360517›Full record

ArticleHealthcare (Basel, Switzerland)2022

Accelerating the Front End of Medicine: Three Digital Use Cases and HCI Implications.

Matthias Klumpp, André Hanelt, Maike Greve, Lutz M Kolbe, Schahin Tofangchi, Florian Böhrnsen, Jens Jakob, Sylvia Kaczmarek, Ingo Börsting, Christopher Ehmke and 2 more

Abstract read
In one paragraph

Article in Healthcare (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 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

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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

12 authors.

Matthias KlumppFraunhofer IML Dortmund, 44227 Dortmund, Germany.ORCID 0000-0002-7543-2751
André HaneltFaculty of Economics and Management, University of Kassel, 34125 Kassel, Germany.
Maike GreveDepartment of Business Administration, University of Göttingen, 37073 Göttingen, Germany.
Lutz M KolbeDepartment of Business Administration, University of Göttingen, 37073 Göttingen, Germany.
Schahin TofangchiDAK Hamburg, 20097 Hamburg, Germany.
Florian BöhrnsenUniversity Medical Center Göttingen, 37075 Göttingen, Germany.
Jens JakobUniversity Medical Center Göttingen, 37075 Göttingen, Germany.
Sylvia KaczmarekFraunhofer IML Dortmund, 44227 Dortmund, Germany.
Ingo BörstingFaculty of Business Administration and Economics, University of Duisburg-Essen, 45127 Essen, Germany.ORCID 0000-0003-3659-9636
Christopher EhmkeFaculty of Business Administration and Economics, University of Duisburg-Essen, 45127 Essen, Germany.ORCID 0000-0002-8323-5889
Helena DüsingUniversity Medical Center of Münster, 48149 Münster, Germany.
Christian JuhraUniversity Medical Center of Münster, 48149 Münster, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Digital applications in health care are a concurrent research and management question, where implementation experiences are a core field of information systems research. It also contributes to fighting pandemic crises like COVID-19 because contactless information flow and speed of diagnostics are improved. This paper presents three digital application case studies from emergency medicine, administration management, and cancer diagnosis with AI support from the University Medical Centers of Münster and Göttingen in Germany. All cases highlight the potential of digitalization to increase speed and efficiency within the front end of medicine as the crucial phase before patient treatment starts. General challenges for health care project implementations and human-computer interaction (HCI) concepts in health care are derived and discussed, including the importance of specific processes together with user analysis and adaption. A derived concept for HCI includes the criteria speed, accuracy, modularity, and individuality to achieve sustainable improvements within the front end of medicine.

Indexed as

Artificial intelligencecancer diagnosisdigital health careemergency medicinefront endhuman-centered computinginpatient data management

Identifiers

PMID36360517
PMCPMC9690901

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.