Evidence map›Paper›PMID 37720844›Full record

ArticleFrontiers in health services2023

Toward a more comprehensive understanding of organizational influences on implementation: the organization theory for implementation science framework.

Sarah A Birken, Cheyenne R Wagi, Alexandra G Peluso, Michelle C Kegler, Jure Baloh, Prajakta Adsul, Maria E Fernandez, Manal Masud, Terry T-K Huang, Matthew Lee and 7 more

Abstract read
In one paragraph

Article in Frontiers in health services, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Observational
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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

17 authors.

Sarah A BirkenDepartment of Implementation Science, Wake Forest University School of Medicine, Winston-Salem, NC, United States.
Cheyenne R WagiDepartment of Implementation Science, Wake Forest University School of Medicine, Winston-Salem, NC, United States.
Alexandra G PelusoDepartment of Implementation Science, Wake Forest University School of Medicine, Winston-Salem, NC, United States.
Michelle C KeglerEmory Prevention Research Center, Rollins School of Public Health, Emory University, Atlanta, GA, United States.
Jure BalohCollege of Public Health, Department of Health Policy and Management, University of Arkansas for Medical Sciences, Little Rock, AR, United States.
Prajakta AdsulDepartment of Internal Medicine, University of New Mexico, Albuquerque, NM, United States.
Maria E FernandezCenter for Health Promotion and Prevention Research, University of Texas Health Science Center at Houston School of Public Health, Houston, TX, United States.
Manal MasudDepartment of Health Systems and Population Health, School of Public Health, University of Washington, Seattle, WA, United States.
Terry T-K HuangCenter for Systems and Community Design and NYU-CUNY Prevention Research Center, Graduate School of Public Health and Health Policy, City University of New York, New York, NY, United States.
Matthew LeeDepartment of Population Health, New York University Grossman School of Medicine, New York, NY, United States.
Mary WangenUNC Center for Health Promotion and Disease Prevention, University of North Carolina Chapel Hill, Chapel Hill, NC, United States.
Per NilsenDepartment of Health, Medicine and Caring Sciences, Division of Society and Health, Linköping University, Linköping, Sweden.
Miriam BenderSue & Bill Gross School of Nursing, University of California Irvine, Irvine, CA, United States.
Mimi Choy-BrownCollege of Education and Human Development, School of Social Work, University of Minnesota, St. Paul, MN, United States.
Grace RyanDepartment of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, MA, United States.
Aliza RandazzoDepartment of Implementation Science, Wake Forest University School of Medicine, Winston-Salem, NC, United States.
Linda K KoDepartment of Health Systems and Population Health, School of Public Health, University of Washington, Seattle, WA, United States.

Funding

Mentored Education for Dissemination and Implementation Science (MEDIS) ProgramR25DK123008 · NIDDK · WASHINGTON UNIVERSITY · PI BROWNSON, ROSS C, HAIRE-JOSHU, DEBRA · 2020 to 2024
$1.1M
NCCDPHP CDC HHS U48 DP006400NIDDK NIH HHS R25 DK123008
6 · The paper itself

Abstract

Introduction: Implementation is influenced by factors beyond individual clinical settings. Nevertheless, implementation research often focuses on factors related to individual providers and practices, potentially due to limitations of available frameworks. Extant frameworks do not adequately capture the myriad organizational influences on implementation. Organization theories capture diverse organizational influences but remain underused in implementation science. To advance their use among implementation scientists, we distilled 70 constructs from nine organization theories identified in our previous work into theoretical domains in the Organization Theory for Implementation Science (OTIS) framework. Methods: The process of distilling organization theory constructs into domains involved concept mapping and iterative consensus-building. First, we recruited organization and implementation scientists to participate in an online concept mapping exercise in which they sorted organization theory constructs into domains representing similar theoretical concepts. Multidimensional scaling and hierarchical cluster analyses were used to produce visual representations (clusters) of the relationships among constructs in concept maps. Second, to interpret concept maps, we engaged members of the Cancer Prevention and Control Research Network (CPCRN) OTIS workgroup in consensus-building discussions. Results: Twenty-four experts participated in concept mapping. Based on resulting construct groupings' coherence, OTIS workgroup members selected the 10-cluster solution (from options of 7-13 clusters) and then reorganized clusters in consensus-building discussions to increase coherence. This process yielded six final OTIS domains: organizational characteristics (e.g., size; age); governance and operations (e.g., organizational and social subsystems); tasks and processes (e.g., technology cycles; excess capacity); knowledge and learning (e.g., tacit knowledge; sense making); characteristics of a population of organizations (e.g., isomorphism; selection pressure); and interorganizational relationships (e.g., dominance; interdependence). Discussion: Organizational influences on implementation are poorly understood, in part due to the limitations of extant frameworks. To improve understanding of organizational influences on implementation, we distilled 70 constructs from nine organization theories into six domains. Applications of the OTIS framework will enhance understanding of organizational influences on implementation, promote theory-driven strategies for organizational change, improve understanding of mechanisms underlying relationships between OTIS constructs and implementation, and allow for framework refinement. Next steps include testing the OTIS framework in implementation research and adapting it for use among policymakers and practitioners.

Indexed as

concept mappingconsensus-buildingdeterminant frameworkimplementationorganization theory

Identifiers

PMID37720844
PMCPMC10501605

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.