Evidence map›Paper›PMID 42764818›Full record

ArticleF1000Research2025

Combining Implementation and Data Sciences to Accelerate Evidence Integration into Healthcare - ImpleMATE.

Jeffery Chan, Janna Hastings, Gabriella Tiernan, Jeannie Paterson, Nigel Lovell, Luc Betbeder-Matibet, Patrick Kin Man Tung, Sarah Pink, Debora Lanzeni, Thomasina Donovan and 11 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in F1000Research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

21 authors.

Jeffery ChanImplementation to Impact (i2i), School of Population Health, Faculty of Medicine and Health, University of New South Wales, Sydney, New South Wales, Australia.ORCID https://orcid.org/0000-0002-7521-9504
Janna HastingsInstitute for Implementation, Science in Health Care, University of Zurich, Zurich, Switzerland.
Gabriella TiernanImplementation to Impact (i2i), School of Population Health, Faculty of Medicine and Health, University of New South Wales, Sydney, New South Wales, Australia.
Jeannie PatersonCentre for AI and Digital Ethics, The University of Melbourne, Melbourne, Victoria, Australia.
Nigel LovellGraduate School of Biomedical Engineering, Faculty of Engineering, University of New South Wales, Sydney, New South Wales, Australia.
Luc Betbeder-MatibetResearch Technology Services, University of New South Wales, Sydney, New South Wales, Australia.
Patrick Kin Man TungResearch Technology Services, University of New South Wales, Sydney, New South Wales, Australia.
Sarah PinkEmerging Technologies Lab, Monash University, Melbourne, Victoria, Australia.
Debora LanzeniDepartment of Design, Monash University, Melbourne, Victoria, Australia.
Thomasina DonovanAustralian Centre for Health Services Innovation and Centre for Healthcare Transformation, School of Public Health and Social Work, Faculty of Health, Queensland University of Technology, Brisbane, Queensland, Australia.ORCID https://orcid.org/0000-0002-0127-0091
Andrew MilatAgency for Clinical Innovation, Sydney, New South Wales, Australia.
Louisa JormCentre for Big Data Research in Health, University of New South Wales, Sydney, New South Wales, Australia.
Carolyn MazariegoImplementation to Impact (i2i), School of Population Health, Faculty of Medicine and Health, University of New South Wales, Sydney, New South Wales, Australia.
Chi ZhangImplementation to Impact (i2i), School of Population Health, Faculty of Medicine and Health, University of New South Wales, Sydney, New South Wales, Australia.
Guillaume FontaineCentre for Implementation Research, Ottawa Hospital Research Institute, Ottawa, Canada.ORCID https://orcid.org/0000-0002-7806-814X
Stephanie BestAustralian Genomics, Melbourne, Victoria, Australia.
Georgina KennedyFaculty of Medicine and Health, University of New South Wales, Sydney, New South Wales, Australia.
Susan MichieCentre for Behaviour Change, University College London, London, UK.
Frank LinFaculty of Medicine and Health, University of New South Wales, Sydney, New South Wales, Australia.
ImpleMATE Network
Natalie TaylorImplementation to Impact (i2i), School of Population Health, Faculty of Medicine and Health, University of New South Wales, Sydney, New South Wales, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The translation of research evidence into routine healthcare practice is often slow and inconsistent, even timely implementation can significantly improve patient outcomes. While implementation science offers strategies to close this gap, current approaches are frequently manual, fragmented, and poorly integrated within healthcare systems. To address these challenges, we propose ImpleMATE - an AI-assisted implementation science platform designed to streamline implementation efforts. Grounded in the Learning Health System (LHS) model, ImpleMATE aims to establish a continuous, data-driven cycle of learning and improvement in implementation practice. Methods: ImpleMATE will be developed through a co-design and co-production approach rooted in human-centred design principles. Development will proceed through four key activities: (1) establishing a data processing pipeline and building an implementation-focused ontology; (2) creating and validating an AI system to extract implementation knowledge, structure the ontology, and support implementation solution delivery; (3) designing an interactive web application to deliver AI-assisted decision support and streamline implementation processes; and (4) developing an evaluation framework to assess platform's effectiveness and plan for national integration. These activities align with three core components of the LHS model: converting data into knowledge, translating knowledge into practice, and feeding implementation process and outcome data back into the system for continuous learning. The platform will be underpinned by strong ethical and governance frameworks to ensure data privacy, transparency, and responsible AI use. Discussion: ImpleMATE aims to transform the adoption of evidence-based innovations in healthcare by embedding trustworthy AI into the core of implementation practice. Through the integration of structured ontologies, real-time AI reasoning, and an interactive user interface, the platform will provide tailored solutions to support implementation efforts. Designed as a dynamic learning system, ImpleMATE will evolve with user input and real-world data, offering a scalable, ethically grounded solution to accelerate and enhance implementation across healthcare settings.

Indexed as

Artificial IntelligenceData ScienceDelivery of Health CareImplementation ScienceLearning Health SystemHumansArtificial intelligencedata sciencehealthcareimplementation sciencelarge language modelnatural language processing

Identifiers

PMID42764818
PMCPMC13589178

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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 Socratic graph.