Evidence map›Paper›PMID 40750660›Full record

ArticleNPJ digital medicine2025

Healthcare effects and evidence robustness of reimbursable digital health applications in Germany: a systematic review.

Khira Sippli, Stefanie Deckert, Jochen Schmitt, Madlen Scheibe

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in NPJ digital medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Article
  4. Review
  5. Review
  6. Article
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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.

Khira Sippli *Center for Evidence-Based Healthcare, Faculty of Medicine and University Hospital Carl Gustav Carus, TUD Dresden University of Technology, Dresden, Germany. khira.sippli@ukdd.de.
Stefanie Deckert *Center for Evidence-Based Healthcare, Faculty of Medicine and University Hospital Carl Gustav Carus, TUD Dresden University of Technology, Dresden, Germany.
Jochen SchmittCenter for Evidence-Based Healthcare, Faculty of Medicine and University Hospital Carl Gustav Carus, TUD Dresden University of Technology, Dresden, Germany.
Madlen ScheibeCenter for Evidence-Based Healthcare, Faculty of Medicine and University Hospital Carl Gustav Carus, TUD Dresden University of Technology, Dresden, Germany.

Funding

Innovation Fund of the German Joint Federal Committee (G-BA) 01VSF22027
6 · The paper itself

Abstract

In Germany, statutory health insurance reimburses digital health applications (DiGAs) approved by the Federal Institute for Drugs and Medical Devices (BfArM). Permanent approval requires evidence of positive healthcare effects, either medical benefits or patient-relevant improvements in structures and processes (pSVV). This systematic review analyzed all 23 DiGA approval studies available as of March 15, 2024. The studies, conducted between 2012 and 2022, included 56 to 1245 participants and intervention durations from 1.5 to 12 months. Drop-out rates varied (mean 21.7% in intervention, 11.8% in control group). Most studies (13/23) focused on primary outcomes related to mental health conditions; one addressed pSVV. All reported significant medium to large effects, but risk of bias was high, particularly in outcome measurement (21/23) and due to missing data (15/23). These findings raise concerns about the robustness of the evidence supporting DiGA efficacy. The review recommends revising the DiGA approval process to enhance study quality. The systematic review was registered prospectively with PROSPERO https://www.crd.york.ac.uk/prospero/ (CRD42023460497).

Identifiers

PMID40750660
PMCPMC12317029

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.