Currently accepted at: Journal of Medical Internet Research
Date Submitted: Mar 6, 2026
Date Accepted: Oct 3, 2026
This paper has been accepted and is currently in production.
It will appear shortly on 10.2196/94803
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Paving the way for an efficient and sustainable integration: implementation strategies for digital nursing technologies in home care – a scoping review
ABSTRACT
Background:
The benefits of digital nursing technologies (DNTs) in home care are well documented. These technologies enable care recipients to live in their homes, independently, by reducing acute events and, consequently, preventing negative outcomes, such as (re-)hospitalization and higher care needs. Numerous DNTs have been developed and were implemented in home care nursing through scientific investigations. Thereby, researchers focused primarily on the DNTs itself, and less on explicit implementation issues. They have applied implicit implementation strategies to promote the adoption of these DNTs. However, a comprehensive and practical overview of potential implementation strategies is still required to support home care nursing in implementing DNTs efficiently and sustainably. Therefore, it remains unclear which implementation strategies are actually used.
Objective:
We aimed to identify and map implementation strategies for DNTs in home care and provide starting points for further research in this field. Additionally, we intend to derive practical recommendations for decision-makers and implementation practitioners working in this implementation context to support a more efficient implementation of DNT.
Methods:
We conducted a scoping review with a systematic literature search in MEDLINE via PubMed, CINAHL via EBSCO, and Scopus. Guided by the PCC (Population, Concept, Context) - framework, we included primary studies and study protocols that addressed the implementation of a DNT in home care and were published between 2015 and 2025. We excluded studies from other healthcare settings, technologies not related to nursing, concept papers, and reviews. Data charting was conducted in MAXQDA 24 using deductive content analysis. We applied the 73 implementation strategies from the Expert Recommendations for Implementing Change (ERIC) framework to define our deductive category system.
Results:
Eighteen papers of fifteen studies were included in this review. Most of them are primary studies, and study protocols, published in 2022, until 2024. We identified 48 implementation strategies out of the 73 strategies listed in the ERIC framework. These strategies were highly heterogeneous, which corresponds to the diversity of the included DNTs that varied in function, purpose, and stage of development. However, our findings show most frequently identified implementation strategies: conduct meetings to inform care managers, nurses, care recipients and their relatives about the DNT; involve these key stakeholders by capturing their demands regarding the adoption of a DNT; achieve a fit between the technology and demands; and foster the collaboration between all involved stakeholders for ambition and problem-solving.
Conclusions:
These frequently identified multi-faceted implementation strategies have not yet been evaluated for effectiveness in a trial, which represent an important starting point for future research, conducted in close collaboration with home care practice. Building on generated insights, subsequent research could meaningfully contribute to transforming home care nursing by promoting a more efficient, sustainable, and evidence informed implementation of DNT. Clinical Trial: OSF Registries (International): doi: 10.17605/OSF.IO/DSRH8
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Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.