Evidence map›Paper›PMID 39354649›Full record

ArticleImplementation science communications2024

Use of implementation mapping to develop a multifaceted implementation strategy for an electronic prospective surveillance model for cancer rehabilitation.

Christian J Lopez, Sarah E Neil-Sztramko, Mounir Tanyoas, Kristin L Campbell, Jackie L Bender, Gillian Strudwick, David M Langelier, Tony Reiman, Jonathan Greenland, Jennifer M Jones and 1 more

Abstract read
In one paragraph

Article in Implementation science communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. An introduction to implementation science in rehabilitation medicine.PM & R : the journal of injury, function, and rehabilitation · 2025
    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

11 authors.

Christian J LopezDepartment of Supportive Care, Princess Margaret Cancer Centre, Toronto, Ontario, Canada. Christian.lopez@uhn.ca.
Sarah E Neil-SztramkoFaculty of Health Sciences, McMaster University, Hamilton, Ontario, Canada.
Mounir TanyoasDepartment of Supportive Care, Princess Margaret Cancer Centre, Toronto, Ontario, Canada.
Kristin L CampbellDepartment of Physical Therapy, University of British Columbia, Vancouver, British Columbia, Canada.
Jackie L BenderDepartment of Supportive Care, Princess Margaret Cancer Centre, Toronto, Ontario, Canada.
Gillian StrudwickInstitute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada.
David M LangelierInstitute of Medical Science, University of Toronto, Toronto, Ontario, Canada.
Tony ReimanDepartment of Oncology, Saint John Regional Hospital, Saint John, New Brunswick, Canada.
Jonathan GreenlandFaculty of Medicine, Memorial University of Newfoundland, St John's, Newfoundland, Canada.
Jennifer M JonesDepartment of Supportive Care, Princess Margaret Cancer Centre, Toronto, Ontario, Canada.
Canadian Cancer Rehabilitation Team

Funding

Canadian Cancer Society 706699CIHR 02022-000
6 · The paper itself

Abstract

backgroundElectronic Prospective Surveillance Models (ePSMs) remotely monitor the rehabilitation needs of people with cancer via patient-reported outcomes at pre-defined time points during cancer care and deliver support, including links to self-management education and community programs, and recommendations for further clinical screening and rehabilitation referrals. Previous guidance on implementing ePSMs lacks sufficient detail on approaches to select implementation strategies for these systems. The purpose of this article is to describe how we developed an implementation plan for REACH, an ePSM system designed for breast, colorectal, lymphoma, and head and neck cancers.

methodsImplementation Mapping guided the process of developing the implementation plan. We integrated findings from a scoping review and qualitative study our team conducted to identify determinants to implementation, implementation actors and actions, and relevant outcomes. Determinants were categorized using the Consolidated Framework for Implementation Research (CFIR), and the implementation outcomes taxonomy guided the identification of outcomes. Next, determinants were mapped to the Expert Recommendations for Implementing Change (ERIC) taxonomy of strategies using the CFIR-ERIC Matching Tool. The list of strategies produced was refined through discussion amongst our team and feedback from knowledge users considering each strategy's feasibility and importance rating via the Go-Zone plot, feasibility and applicability to the clinical contexts, and use among other ePSMs reported in our scoping review.

resultsOf the 39 CFIR constructs, 22 were identified as relevant determinants. Clinic managers, information technology teams, and healthcare providers with key roles in patient education were identified as important actors. The CFIR-ERIC Matching Tool resulted in 50 strategies with Level 1 endorsement and 13 strategies with Level 2 endorsement. The final list of strategies included 1) purposefully re-examine the implementation, 2) tailor strategies, 3) change record systems, 4) conduct educational meetings, 5) distribute educational materials, 6) intervene with patients to enhance uptake and adherence, 7) centralize technical assistance, and 8) use advisory boards and workgroups.

conclusionWe present a generalizable method that incorporates steps from Implementation Mapping, engages various knowledge users, and leverages implementation science frameworks to facilitate the development of an implementation strategy. An evaluation of implementation success using the implementation outcomes framework is underway.

Indexed as

Cancer survivorshipConsolidated framework for implementation researchExpert recommendations for implementing changeImplementation mappingImplementation scienceImplementation strategiesKnowledge to action frameworkPatient-reported outcomesProspective surveillance modelRehabilitation

Identifiers

PMID39354649
PMCPMC11446052

What OpenQuestion holds

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LicenceCC BY
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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.