Evidence map›Paper›PMID 36050742›Full record

ArticleImplementation science : IS2022

Data-driven approach to implementation mapping for the selection of implementation strategies: a case example for risk-aligned bladder cancer surveillance.

Florian R Schroeck, A Aziz Ould Ismail, David A Haggstrom, Steven L Sanchez, DeRon R Walker, Lisa Zubkoff

Abstract read
In one paragraph

Article in Implementation science : IS, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
–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

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  11. Using Quality Improvement and Implementation Science to Identify Strategies That Foster Electronic Patient-Reported Outcome Submissions.Journal for healthcare quality : official publication of the National Association for Healthcare Quality
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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

6 authors.

Florian R SchroeckWhite River Junction VA Medical Center, White River Junction, VT, USA. florian.r.schroeck@dartmouth.edu.ORCID 0000-0002-1860-2611
A Aziz Ould IsmailWhite River Junction VA Medical Center, White River Junction, VT, USA.
David A HaggstromVA HSR&D Center for Health Information and Communication, Richard L. Roudebush Veterans Affairs Medical Center, Indianapolis, IN, USA.
Steven L SanchezVA HSR&D Center for Health Information and Communication, Richard L. Roudebush Veterans Affairs Medical Center, Indianapolis, IN, USA.
DeRon R WalkerVA HSR&D Center for Health Information and Communication, Richard L. Roudebush Veterans Affairs Medical Center, Indianapolis, IN, USA.
Lisa ZubkoffBirmingham/Atlanta VA Geriatric Research Education and Clinical Center (GRECC), Department of Veterans Affairs, Birmingham, AL, USA.

Funding

Implementing Risk-aligned Bladder Cancer SurveillanceI01HX002780 · VA · WHITE RIVER JUNCTION VA MEDICAL CENTER · PI SCHROECK, FLORIAN R · 2020 to 2023
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HSRD VA I01 HX002780
6 · The paper itself

Abstract

backgroundImplementation Mapping is an organized method to select implementation strategies. However, there are 73 Expert Recommendations for Implementing Change (ERIC) strategies. Thus, it is difficult for implementation scientists to map all potential strategies to the determinants of their chosen implementation science framework. Prior work using Implementation Mapping employed advisory panels to select implementation strategies. This article presents a data-driven approach to implementation mapping, in which we systematically evaluated all 73 ERIC strategies using the Tailored Implementation for Chronic Diseases (TICD) framework. We illustrate our approach using implementation of risk-aligned bladder cancer surveillance as a case example.

methodsWe developed objectives based on previously collected qualitative data organized by TICD determinants, i.e., what needs to be changed to achieve more risk-aligned surveillance. Next, we evaluated all 73 ERIC strategies, excluding those that were not applicable to our clinical setting. The remaining strategies were mapped to the objectives using data visualization techniques to make sense of the large matrices. Finally, we selected strategies with high impact, based on (1) broad scope, defined as a strategy addressing more than the median number of objectives, (2) requiring low or moderate time commitment from clinical teams, and (3) evidence of effectiveness from the literature.

resultsWe identified 63 unique objectives. Of the 73 ERIC strategies, 45 were excluded because they were not applicable to our clinical setting (e.g., not feasible within the confines of the setting, not appropriate for the context). Thus, 28 ERIC strategies were mapped to the 63 objectives. Strategies addressed 0 to 26 objectives (median 10.5). Of the 28 ERIC strategies, 10 required low and 8 moderate time commitments from clinical teams. We selected 9 strategies based on high impact, each with a clearly documented rationale for selection.

conclusionsWe enhanced Implementation Mapping via a data-driven approach to the selection of implementation strategies. Our approach provides a practical method for other implementation scientists to use when selecting implementation strategies and has the advantage of favoring data-driven strategy selection over expert opinion.

Indexed as

Urinary Bladder NeoplasmsChronic DiseaseHumansImplementation Science

Identifiers

PMID36050742
PMCPMC9438061

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.