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Record W4414321469 · doi:10.1186/s12913-025-13455-5

Feasibility, utility, usability and acceptance of a multimodal telemonitoring for COVID-19 patients in general practitioners practices in Germany: a mixed methods study with patients

2025· article· en· W4414321469 on OpenAlexaff
Zoe S. Oftring, Kim Deutsch, Svea Holtz, Susanne Maria Köhler, Peter Jan Chabiera, Nurlan Dauletbaev, Lukas Niekrenz, Beate S. Müller, Sebastian Kühn

Bibliographic record

VenueBMC Health Services Research · 2025
Typearticle
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsMcGill University Health Centre
FundersBundesministerium für Bildung und ForschungPhilipps-Universität Marburg
KeywordsHealth informaticsUsabilityQuality of Life ResearchInformed consentNursing researchGermanPublic healthHealth administrationClinical trial

Abstract

fetched live from OpenAlex

BACKGROUND: During the COVID-19 pandemic, infected outpatients were at risk of declining at home without themselves and their general practitioner (GP) noticing, above all due to silent hypoxemia. To support patients in quarantine, telemonitoring solutions were developed for primary care in several countries. However, evidence on patient perceptions of COVID-19 telemonitoring in primary care settings remains limited. This prospective study evaluates COVID-19 outpatients' experiences with and perception of the usability, utility and acceptance of an app-based telemonitoring in Germany, identifying key conditions for its successful implementation. METHODS: To support home-isolated COVID-19 patients remotely, eight GP practices in Germany implemented a multimodal telemonitoring system. Telemonitoring consisted of an app with connected sensors to remotely measure vital signs and symptoms, with data transmitted to a GP telemedicine platform. Between January to December 2021, 34 COVID-19 outpatients participated in telemonitoring. Telemonitoring duration was 28 days for acute infection or up to 12 weeks for prolonged/post-acute symptoms. Afterwards, patients participated in a mixed-methods evaluation about their experiences consisting of semi-structured telephone interviews and an in-house questionnaire. Interviews were analyzed using qualitative content analysis, questionnaires were analyzed descriptively. RESULTS: =19-74, comorbidities present = 13/34). Patients generally viewed telemonitoring as feasible and beneficial, with high acceptance rates and a perception of the system as valuable and reassuring support during illness. Participants, even those with limited prior experience in recording health data, successfully managed the monitoring process. Key insights included patient expectations regarding GP data access, underscoring the importance of integrating patient perspectives into the design process of future telemonitoring solutions. Connectivity issues with sensors occasionally disrupted data collection. Generally, the results emphasize the importance of comprehensive onboarding and support structures to optimize telemonitoring effectiveness. CONCLUSIONS: This study demonstrates that app-based telemonitoring in primary care is a feasible, well-accepted intervention for COVID-19 outpatients, with patients perceiving it as valuable, supportive and reassuring. Findings emphasize the critical role of patient-centered design and strong support structures for successful telemonitoring integration into primary care. Lastly, these findings underscore the value of telemonitoring in pandemic preparedness, ensuring timely detection of patient deterioration and strengthening primary care resilience. TRIAL REGISTRATION: The study was registered with the German Clinical Trials Register (DRKS00024604). The study was approved by the Ethics Committee of Goethe University Frankfurt (No. 20-1023, 18.01.2021), and written informed consent was obtained from all participants.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.168
GPT teacher head0.593
Teacher spread0.425 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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