Evidence map›Paper›PMID 38750652›Full record

ArticleHealth services research2024

A structured approach to modifying an implementation package while scaling up a complex evidence-based practice.

Kristina M Cordasco, Sonya E Gabrielian, Jenny Barnard, Taylor Harris, Erin P Finley

Abstract read
In one paragraph

Article in Health services research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

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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

5 authors.

Kristina M CordascoVA Center for the Study of Healthcare Innovation, Implementation and Policy, VA Greater Los Angeles Healthcare System, Los Angeles, California, USA.ORCID 0000-0002-5866-1763
Sonya E GabrielianVA Center for the Study of Healthcare Innovation, Implementation and Policy, VA Greater Los Angeles Healthcare System, Los Angeles, California, USA.ORCID 0000-0002-1790-4271
Jenny BarnardVA Center for the Study of Healthcare Innovation, Implementation and Policy, VA Greater Los Angeles Healthcare System, Los Angeles, California, USA.
Taylor HarrisVA Center for the Study of Healthcare Innovation, Implementation and Policy, VA Greater Los Angeles Healthcare System, Los Angeles, California, USA.ORCID 0000-0003-3471-029X
Erin P FinleyVA Center for the Study of Healthcare Innovation, Implementation and Policy, VA Greater Los Angeles Healthcare System, Los Angeles, California, USA.ORCID 0000-0003-4497-7721

Funding

Quality Enhancement Research Initiative PII 21-285
6 · The paper itself

Abstract

objectiveTo describe a structured, iterative, data-driven approach for modifying implementation strategies for a complex evidence-based practice during a nationwide scale-up initiative. DATA SOURCES AND STUDY

settingWe scaled-up implementation of Critical Time Intervention (CTI)-an evidence-based case management model-across 32 diverse community-based Veterans Affairs (VA) "Grant and Per Diem" case management (GPD-CM) agencies that serve homeless-experienced Veterans transitioning to independent living. Primary data were collected using qualitative methods. STUDY

designWe embarked on a scale-up initiative while conducting a pragmatic randomized evaluation using a roll-out design, comparing two versions of a CTI implementation package tailored to VA's GPD-CM program. We iteratively assessed contextual factors and implementation outcomes (e.g., acceptability); findings informed package modifications that were characterized using the Framework for Reporting Adaptations and Modifications to Evidence-based Implementation Strategies. DATA COLLECTION

methodsWe conducted semi-structured interviews with Veterans, GPD-CM staff, and liaising VA clinicians; periodic reflections with liaising VA clinicians and implementation team members; and drew upon detailed meeting notes. We used rapid qualitative methods and content analysis to integrate data and characterize modifications. PRINCIPAL

findingsAfter each scale-up wave-in response to variations in agency-level characteristics- we made iterative modifications to the implementation package to increase CTI adoption and fidelity across the diverse contexts of our scale-up sites. Modifications included adding, deleting, integrating, and altering the package; core package components were preserved.

conclusionsImplementation packages for complex evidence-based practices undergoing scale-up in diverse contexts may benefit from iterative modifications to optimize practice adoption with fidelity. We offer a structured, pragmatic approach for iteratively identifying data-driven, midstream implementation package adjustments, for use in both VA and non-VA scale-up initiatives. Our project demonstrates the importance of assessing for and making modifications in a scale-up initiative, as well as the trade-offs of projects having simultaneous formative and summative evaluation aims.

Indexed as

Evidence-Based PracticeUnited States Department of Veterans AffairsCase ManagementHumansIll-Housed PersonsInterviews as TopicQualitative ResearchUnited StatesVeteransVeterans Health Servicesevidence‐based practicehealth services administrationhomelessnessimplementation scienceveterans

Identifiers

PMID38750652
PMCPMC11540582

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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.