Evidence map›Paper›PMID 37140980›Full record

ArticleJMIR human factors2023

Removing Dust From the German Health Care System by Introducing Health Apps Into Standard Care: Semistructured Interview Study.

Alexandra Heidel, Christian Hagist, Stefan Spinler, Michael Schoeneberger

Abstract read
In one paragraph

Article in JMIR human factors, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–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

4 citing papers in PubMed.

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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

4 authors.

Alexandra HeidelWHU - Otto Beisheim School of Management, Vallendar, Germany.ORCID https://orcid.org/0000-0002-7374-7725
Christian HagistWHU - Otto Beisheim School of Management, Vallendar, Germany.ORCID https://orcid.org/0000-0002-6322-3178
Stefan SpinlerWHU - Otto Beisheim School of Management, Vallendar, Germany.ORCID https://orcid.org/0000-0003-2669-4728
Michael SchoenebergerWHU - Otto Beisheim School of Management, Vallendar, Germany.ORCID https://orcid.org/0000-0001-6678-423X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn 2019, Germany launched the Digital Healthcare Act. The reform enables physicians to prescribe health apps as treatments to their statutory-insured patients.

objectiveWe aimed to determine the extent to which the integration of health apps into standard care could be considered beneficial and which aspects of the regulation could still be improved.

methodsWe conducted a semistructured interview study with 23 stakeholders in Germany and analyzed them thematically. We used descriptive coding for the first-order codes and pattern coding for the second-order codes.

resultsWe created 79 first-order codes and 9 second-order codes following the interview study. Most stakeholders argued that the option of prescribing health apps could improve treatment quality.

conclusionsThe inclusion of health apps into German standard care could improve the quality of treatment by expanding treatment portfolios. The educational elements of the apps might additionally lead to more patient emancipation through a better understanding of personal conditions. Location and time flexibility are the biggest advantages of the new technologies, but they also raise the most significant concerns for stakeholders because app use requires personal initiative and self-motivation. Overall, stakeholders agree that the Digital Healthcare Act has the potential to remove dust from the German health care system.

Indexed as

Digitale Versorgung GesetzDigital Healthcare ActDVGGerman statutory health care systemhealth appsinterview studymHealthmobile health

Identifiers

PMID37140980
PMCPMC10196889

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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.