Evidence map›Paper›PMID 34627399›Full record

ArticleImplementation science communications2021

Rapid-cycle systems modeling to support evidence-informed decision-making during system-wide implementation.

R Christopher Sheldrick, Gracelyn Cruden, Ana J Schaefer, Thomas I Mackie

Open access · goldAbstract read
In one paragraph

Article in Implementation science communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
3.8field-weighted citation impact, top 7% of its field
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

10 citing papers in PubMed, 16 citations in OpenAlex.

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  10. Future Directions in Lay Health Worker Involvement in Children's Mental Health Services in the U.S.Journal of clinical child and adolescent psychology : the official journal for the Society of Clinical Child and Adolescent Psychology, American Psychological Association, Division 53
    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

4 authors at 3 institutions in 1 country.

R Christopher SheldrickDepartment of Health Law, Policy and Management, School of Public Health, Boston University, One Silber Way, Boston, MA, USA. rshldrck@bu.edu.ORCID http://orcid.org/0000-0003-0534-856X
Gracelyn CrudenOregon Social Learning Center, 10 Shelton McMurphey Blvd, Eugene, OR, USA.
Ana J SchaeferSUNY Downstate Health Sciences University, 450 Clarkson Ave, Brooklyn, NY, USA.
Thomas I MackieSUNY Downstate Health Sciences University, 450 Clarkson Ave, Brooklyn, NY, USA.
SUNY Downstate Health Sciences University · USBoston University · USOregon Social Learning Center · US

Funding

William T. Grant Foundation 183659
6 · The paper itself

Abstract

backgroundTo "model and simulate change" is an accepted strategy to support implementation at scale. Much like a power analysis can inform decisions about study design, simulation models offer an analytic strategy to synthesize evidence that informs decisions regarding implementation of evidence-based interventions. However, simulation modeling is under-utilized in implementation science. To realize the potential of simulation modeling as an implementation strategy, additional methods are required to assist stakeholders to use models to examine underlying assumptions, consider alternative strategies, and anticipate downstream consequences of implementation. To this end, we propose Rapid-cycle Systems Modeling (RCSM)-a form of group modeling designed to promote engagement with evidence to support implementation. To demonstrate its utility, we provide an illustrative case study with mid-level administrators developing system-wide interventions that aim to identify and treat trauma among children entering foster care.

methodsRCSM is an iterative method that includes three steps per cycle: (1) identify and prioritize stakeholder questions, (2) develop or refine a simulation model, and (3) engage in dialogue regarding model relevance, insights, and utility for implementation. For the case study, 31 key informants were engaged in step 1, a prior simulation model was adapted for step 2, and six member-checking group interviews (n = 16) were conducted for step 3.

resultsStep 1 engaged qualitative methods to identify and prioritize stakeholder questions, specifically identifying a set of inter-related decisions to promote implementing trauma-informed screening. In step 2, the research team created a presentation to communicate key findings from the simulation model that addressed decisions about programmatic reach, optimal screening thresholds to balance demand for treatment with supply, capacity to start-up and sustain screening, and availability of downstream capacity to provide treatment for those with indicated need. In step 3, member-checking group interviews with stakeholders documented the relevance of the model results to implementation decisions, insight regarding opportunities to improve system performance, and potential to inform conversations regarding anticipated implications of implementation choices.

conclusionsBy embedding simulation modeling in a process of stakeholder engagement, RCSM offers guidance to realize the potential of modeling not only as an analytic strategy, but also as an implementation strategy.

Indexed as

Computer simulationEpistemologyEvidence-based practiceImplementation sciencePsychological traumaScreening

Identifiers

PMID34627399
PMCPMC8502394
OpenAlexW3207386723

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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 OpenQuestion graph.