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Record W4409365566 · doi:10.2196/73024

Nurse-Delivered Telehealth in Home-Based Palliative Care: Integrative Systematic Review

2025· review· en· W4409365566 on OpenAlexaff
Cong Ma, Ying Zheng, Wanchen Zhao, Ge Yan, Yaoxin Zeng, Xiao-Hong Ning, Zhimeng Jia

Bibliographic record

VenueJournal of Medical Internet Research · 2025
Typereview
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsUniversity of TorontoMount Sinai Hospital
Fundersnot available
KeywordsPreprintTelehealthNursingPalliative careTelemedicineMedicineMEDLINEHealth carePsychologyWorld Wide WebComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: Telehealth technologies can enhance patients' and their families' access to high-quality resources in home-based palliative care. Nurses are deeply involved in delivering telehealth in home-based palliative care. However, no previous integrative systematic reviews have synthesized evidence on nurses' roles, facilitators, and barriers to implementing nurse-delivered telehealth in home-based palliative care. OBJECTIVE: This integrative systematic review aimed to provide a comprehensive understanding of the roles of nurses and the multilevel facilitators and barriers to implementing nurse-delivered telehealth in home-based palliative care, which could inform future policy development, research, and clinical practice. METHODS: This integrative systematic review was conducted using Joanna Briggs Institute methodological guidance. We followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines. We systematically searched articles published from January 1, 2014, to May 2024 in PubMed, Embase, Web of Science, CINAHL, and Cochrane Library. We included English-language; peer-reviewed; original; and qualitative, quantitative, and mixed methods studies that centered on nurse-delivered telehealth in home-based palliative care. We used the Mixed Methods Appraisal Tool to assess the quality of the included articles. Furthermore, 3 authors independently assessed eligibility, extracted data, and assessed the quality of articles. The entities to extract were identified by research questions of interest regardless of the type of study. We applied a convergent synthesis approach to integrate quantitative and qualitative data. Guided by the updated Consolidated Framework for Implementation Research (CFIR) 2.0, we synthesized the facilitators and barriers to implementing nurse-delivered telehealth in home-based palliative care. RESULTS: This integrative systematic review identified 4819 unique articles, including 34 papers encompassing 29 unique primary research studies. Innovations were mainly delivered by nurses (n=8) and nurse-involved multiprofessional teams (n=18). The roles of nurses in telehealth home-based palliative care involve palliative care nurses, community nurses, nurse coordinators, nurse coaches or nurse navigators, and nurse case managers. Guided by CFIR 2.0, facilitators and barriers to implementing nurse-delivered, telehealth, home-based palliative care were identified to 6 implementation levels and 20 constructs. The key facilitators included the COVID-19 pandemic, cost avoidance to the health care system, engagement of patients and their family caregivers, and so on. The barriers included a lack of reimbursement and payment mechanisms, technical problems, insufficiently trained health care providers, and so on. CONCLUSIONS: This integrative systematic review synthesizes evidence on nurses' evolving roles in telehealth home-based palliative care and identifies multilevel facilitators and barriers to nurse-delivered, home-based palliative care implementation. With the empowerment of telehealth technologies, nurses could establish a stronger professional identity and develop leadership in home-based palliative care. Nurses should leverage influence to promote nursing practice, clinical management, and policy support in the implementation of telehealth home-based palliative care. TRIAL REGISTRATION: PROSPERO CRD42024541038; https://www.crd.york.ac.uk/PROSPERO/view/CRD42024541038.

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)0.028
metaresearch head score (Gemma)0.113
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.028
Threshold uncertainty score0.147

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0280.113
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0100.008
Bibliometrics0.0160.016
Science and technology studies0.0010.001
Scholarly communication0.0040.004
Open science0.0030.003
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.134
GPT teacher head0.546
Teacher spread0.413 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations10
Published2025
Admission routes1
Has abstractyes

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