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Smith NR, Levy DE, Falbe J, Purtle J, Chriqui JF. Design considerations for developing measures of policy implementation in quantitative evaluations of public health policy. FRONTIERS IN HEALTH SERVICES 2024; 4:1322702. [PMID: 39076770 PMCID: PMC11285065 DOI: 10.3389/frhs.2024.1322702] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Accepted: 06/20/2024] [Indexed: 07/31/2024]
Abstract
Typical quantitative evaluations of public policies treat policies as a binary condition, without further attention to how policies are implemented. However, policy implementation plays an important role in how the policy impacts behavioral and health outcomes. The field of policy-focused implementation science is beginning to consider how policy implementation may be conceptualized in quantitative analyses (e.g., as a mediator or moderator), but less work has considered how to measure policy implementation for inclusion in quantitative work. To help address this gap, we discuss four design considerations for researchers interested in developing or identifying measures of policy implementation using three independent NIH-funded research projects studying e-cigarette, food, and mental health policies. Mini case studies of these considerations were developed via group discussions; we used the implementation research logic model to structure our discussions. Design considerations include (1) clearly specifying the implementation logic of the policy under study, (2) developing an interdisciplinary team consisting of policy practitioners and researchers with expertise in quantitative methods, public policy and law, implementation science, and subject matter knowledge, (3) using mixed methods to identify, measure, and analyze relevant policy implementation determinants and processes, and (4) building flexibility into project timelines to manage delays and challenges due to the real-world nature of policy. By applying these considerations in their own work, researchers can better identify or develop measures of policy implementation that fit their needs. The experiences of the three projects highlighted in this paper reinforce the need for high-quality and transferrable measures of policy implementation, an area where collaboration between implementation scientists and policy experts could be particularly fruitful. These measurement practices provide a foundation for the field to build on as attention to incorporating measures of policy implementation into quantitative evaluations grows and will help ensure that researchers are developing a more complete understanding of how policies impact health outcomes.
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Affiliation(s)
- Natalie Riva Smith
- Department of Social and Behavioral Sciences, Harvard TH Chan School of Public Health, Boston, MA, United States
| | - Douglas E. Levy
- Mongan Institute Health Policy Research Center, Massachusetts General Hospital, Boston, MA, United States
- Harvard Medical School, Boston, MA, United States
| | - Jennifer Falbe
- Human Development and Family Studies Program, Department of Human Ecology, University of California, Davis, CA, United States
| | - Jonathan Purtle
- Department of Public Health Policy & Management, Global Center for Implementation Science, New York University School of Global Public Health, New York, NY, United States
| | - Jamie F. Chriqui
- Institute for Health Research and Policy, University of Illinois Chicago, Chicago, IL, United States
- Department of Health Policy and Administration, School of Public Health, University of Illinois Chicago, Chicago, IL, United States
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Dodson EA, Parks RG, Jacob RR, An R, Eyler AA, Lee N, Morshed AB, Politi MC, Tabak RG, Yan Y, Brownson RC. Effectively communicating with local policymakers: a randomized trial of policy brief dissemination to address obesity. Front Public Health 2024; 12:1246897. [PMID: 38525334 PMCID: PMC10957535 DOI: 10.3389/fpubh.2024.1246897] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2023] [Accepted: 02/05/2024] [Indexed: 03/26/2024] Open
Abstract
Introduction Evidence-based policies are a powerful tool for impacting health and addressing obesity. Effectively communicating evidence to policymakers is critical to ensure evidence is incorporated into policies. While all public health is local, limited knowledge exists regarding effective approaches for improving local policymakers' uptake of evidence-based policies. Methods Local policymakers were randomized to view one of four versions of a policy brief (usual care, narrative, risk-framing, and narrative/risk-framing combination). They then answered a brief survey including questions about their impressions of the brief, their likelihood of using it, and how they determine legislative priorities. Results Responses from 331 participants indicated that a majority rated local data (92%), constituent needs/opinions (92%), and cost-effectiveness data (89%) as important or very important in determining what issues they work on. The majority of respondents agreed or strongly agreed that briefs were understandable (87%), believable (77%), and held their attention (74%) with no brief version rated significantly higher than the others. Across the four types of briefs, 42% indicated they were likely to use the brief. Logistic regression models showed that those indicating that local data were important in determining what they work on were over seven times more likely to use the policy brief than those indicating that local data were less important in determining what they work on (aOR = 7.39, 95% CI = 1.86,52.57). Discussion Among local policymakers in this study there was no dominant format or type of policy brief; all brief types were rated similarly highly. This highlights the importance of carefully crafting clear, succinct, credible, and understandable policy briefs, using different formats depending on communication objectives. Participants indicated a strong preference for receiving materials incorporating local data. To ensure maximum effect, every effort should be made to include data relevant to a policymaker's local area in policy communications.
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Affiliation(s)
- Elizabeth A. Dodson
- Prevention Research Center, Brown School at Washington University in St. Louis, St. Louis, MO, United States
| | - Renee G. Parks
- Prevention Research Center, Brown School at Washington University in St. Louis, St. Louis, MO, United States
| | - Rebekah R. Jacob
- Prevention Research Center, Brown School at Washington University in St. Louis, St. Louis, MO, United States
| | - Ruopeng An
- Brown School, Washington University in St. Louis, St. Louis, MO, United States
| | - Amy A. Eyler
- Prevention Research Center, Brown School at Washington University in St. Louis, St. Louis, MO, United States
| | | | - Alexandra B. Morshed
- Prevention Research Center, Brown School at Washington University in St. Louis, St. Louis, MO, United States
- Rollins School of Public Health, Emory University, Atlanta, GA, United States
| | - Mary C. Politi
- Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, St. Louis, MO, United States
| | - Rachel G. Tabak
- Prevention Research Center, Brown School at Washington University in St. Louis, St. Louis, MO, United States
| | - Yan Yan
- Division of Public Health Sciences, Department of Surgery, Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, United States
| | - Ross C. Brownson
- Prevention Research Center, Brown School at Washington University in St. Louis, St. Louis, MO, United States
- Department of Surgery, Division of Public Health Sciences, and Alvin J. Siteman Cancer Center, Washington University School of Medicine, St. Louis, MO, United States
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Rogers CD, Amemiya C, Arur S, Babonis L, Barresi M, Bartlett M, Behringer R, Benham-Pyle B, Bergmann D, Blackman B, Brown CT, Browne B, Camacho J, Chabu CY, Chow I, Cleaver O, Cool J, Dennis MY, Dickinson AJ, Di Talia S, Frank M, Gillmor S, Haag ES, Hariharan I, Harland R, Husbands A, Jerome-Majewska L, Koenig K, Labonne C, Layden M, Lowe C, Mani M, Martik M, McKown K, Moens C, Mosimann C, Onyenedum J, Reed R, Rivera A, Rokhsar D, Royer L, Rutaganira F, Shahan R, Sinha N, Swalla B, Van Norman JM, Wagner DE, Wikramanayake A, Zebell S, Brady SM. Pluripotency of a founding field: rebranding developmental biology. Development 2024; 151:dev202342. [PMID: 38345109 PMCID: PMC10986740 DOI: 10.1242/dev.202342] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/15/2024]
Abstract
The field of developmental biology has declined in prominence in recent decades, with off-shoots from the field becoming more fashionable and highly funded. This has created inequity in discovery and opportunity, partly due to the perception that the field is antiquated or not cutting edge. A 'think tank' of scientists from multiple developmental biology-related disciplines came together to define specific challenges in the field that may have inhibited innovation, and to provide tangible solutions to some of the issues facing developmental biology. The community suggestions include a call to the community to help 'rebrand' the field, alongside proposals for additional funding apparatuses, frameworks for interdisciplinary innovative collaborations, pedagogical access, improved science communication, increased diversity and inclusion, and equity of resources to provide maximal impact to the community.
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Affiliation(s)
- Crystal D. Rogers
- Anatomy, Physiology, and Cell Biology, School of Veterinary Medicine, University of California Davis, Davis, CA 95616, USA
| | - Chris Amemiya
- University of California, Merced, Department of Molecular and Cell Biology and Quantitative and Systems Biology Program, 5200 N. Lake Road, SE1 262, Merced, CA 95343, USA
| | - Swathi Arur
- The University of Texas, MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Leslie Babonis
- Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, NY 14853, USA
| | | | - Madelaine Bartlett
- Biology Department, University of Massachusetts Amherst, Amherst, MA 01003, USA
| | - Richard Behringer
- The University of Texas, MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Blair Benham-Pyle
- Stem Cell and Regenerative Medicine Center, Baylor College of Medicine, Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX 77030, USA
| | - Dominique Bergmann
- Department of Biology and HHMI, Stanford University, Stanford, CA 94305, USA
| | - Ben Blackman
- University of California, Berkeley, Berkeley CA 94720, USA
| | - C. Titus Brown
- Population Health & Reproduction, School of Veterinary Medicine, University of California Davis, Davis, CA 95616, USA
| | - Bill Browne
- Department of Biology, University of Miami, Coral Gables, FL 33146, USA
| | - Jasmin Camacho
- Stowers Institute for Medical Research, Kansas City, MO 64110, USA
| | | | - Ida Chow
- Society for Developmental Biology, Rockville, MD 20852, USA
| | - Ondine Cleaver
- Department of Molecular Biology, Center for Regenerative Science and Medicine, UT Southwestern Medical School, Dallas, TX 75390, USA
| | - Jonah Cool
- Chan Zuckerberg Initiative, Redwood City, CA 94063, USA
| | - Megan Y. Dennis
- Genome Center, MIND Institute, and Department of Biochemistry & Molecular Medicine, University of California, Davis, CA 95616, USA
| | - Alexandra Jazz Dickinson
- Department of Cell and Developmental Biology, School of Biological Science, University of California San Diego, La Jolla, CA 92093, USA
| | - Stefano Di Talia
- Department of Cell Biology, Duke University Medical Center, Durham, NC 27710, USA
| | - Margaret Frank
- School of Integrative Plant Science, Cornell University, Ithaca, NY 14853, USA
| | - Stewart Gillmor
- Unidad de Genómica Avanzada, CINVESTAV-IPN, Irapuato, Guanajuato 36824, Mexico
| | - Eric S. Haag
- Department of Biology, University of Maryland, College Park, MD 20742, USA
| | - Iswar Hariharan
- University of California Berkeley, Department of Molecular and Cell Biology, Berkeley, CA 94720, USA
| | - Richard Harland
- University of California Berkeley, Department of Molecular and Cell Biology, Berkeley, CA 94720, USA
| | - Aman Husbands
- Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Loydie Jerome-Majewska
- Department of Pediatrics, Human Genetics, Anatomy and Cell Biology, McGill University and Research Institute of the McGill University Health Centre at Glen Site, Montreal, QC H4A 3J1, Canada
| | | | - Carole Labonne
- Department of Molecular Biosciences, Northwestern University, Evanston, IL 60208, USA
| | - Michael Layden
- Department of Biological Sciences, Lehigh University, Bethlehem, PA 18015, USA
| | - Chris Lowe
- Hopkins Marine Station, Department of Biology, Stanford University, 120 Oceanview Blvd., Pacific Grove, CA 93950, USA
| | - Madhav Mani
- Department of Molecular Biosciences, Northwestern University, Evanston, IL 60208, USA
| | - Megan Martik
- University of California Berkeley, Department of Molecular and Cell Biology, Berkeley, CA 94720, USA
| | - Katelyn McKown
- Department of Biology and Stanford Introductory Studies, Stanford University, Stanford, CA 94305, USA
| | - Cecilia Moens
- Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
| | - Christian Mosimann
- Children's Hospital Colorado, Department of Pediatrics, Section of Developmental Biology, University of Colorado School of Medicine, Anschutz Medical Campus, 12801 E. 17th Avenue, RC1 South, 12114, Aurora, CO 80045, USA
| | - Joyce Onyenedum
- School of Integrative Plant Sciences and L. H. Bailey Hortorium, Cornell University, Ithaca, NY 14853, USA
| | - Robert Reed
- Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, NY 14853, USA
| | - Ajna Rivera
- University of the Pacific, Stockton, CA 95211, USA
| | - Dan Rokhsar
- University of California Berkeley, Department of Molecular and Cell Biology, Berkeley, CA 94720, USA
| | - Loic Royer
- Chan Zuckerberg Biohub, San Francisco, CA 94158, USA
| | - Flora Rutaganira
- Departments of Biochemistry and Developmental Biology, Stanford University, Stanford, CA 94305, USA
| | - Rachel Shahan
- Department of Biology, Duke University, Durham, NC 27708, USA
- Howard Hughes Medical Institute, Duke University, Durham, NC 27708, USA
| | - Neelima Sinha
- Department of Plant Biology, University of California, Davis, CA 95616, USA
| | - Billie Swalla
- Biology Department and Friday Harbor Labs, University of Washington, Seattle, WA 98195, USA
| | - Jaimie M. Van Norman
- Department of Botany and Plant Sciences, University of California, Riverside, Riverside, CA 92521, USA
| | - Daniel E. Wagner
- Department of Obstetrics, Gynecology and Reproductive Science, University of California, San Francisco, CA 94143, USA
| | | | - Sophia Zebell
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Siobhán M. Brady
- Department of Plant Biology and Genome Center, University of California, Davis, CA 95616, USA
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Smith NR, Hassmiller Lich K, Ng SW, Hall MG, Trogdon JG, Frerichs L. Implementation costs of sugary drink policies in the United States. J Public Health Policy 2023; 44:566-587. [PMID: 37714964 PMCID: PMC10841536 DOI: 10.1057/s41271-023-00435-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/11/2023] [Indexed: 09/17/2023]
Abstract
To support implementation of important public health policies, policymakers need information about implementation costs over time and across stakeholder groups. We assessed implementation costs of two federal sugar-sweetened beverage (SSB) policies of current policy interest and with evidence to support their effects: excise taxes and health warning labels. Our analysis encompassed the entire policy life cycle using the Exploration, Preparation, Implementation, and Sustainment framework. We identified implementation actions using key informant interviews and developed quantitative estimates of implementation costs using published literature and government documents. Results show that implementation costs vary over time and among stakeholders. Explicitly integrating implementation science theory and using mixed methods improved the comprehensiveness of our results. Although this work is specific to federal SSB policies, the process can inform how we understand the costs of many public health policies, providing crucial information for public health policy making.
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Affiliation(s)
- Natalie Riva Smith
- Department of Social and Behavioral Sciences, Harvard TH Chan School of Public Health, 677 Huntington Ave, Boston, MA, 02115, USA.
| | - Kristen Hassmiller Lich
- Department of Health Policy and Management, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Shu Wen Ng
- Department of Nutrition, Gillings School of Global Public Health, Carolina Population Center, University of North Carolina, Chapel Hill, NC, USA
- Carolina Population Center, University of North Carolina, Chapel Hill, NC, USA
| | - Marissa G Hall
- Carolina Population Center, University of North Carolina, Chapel Hill, NC, USA
- Department of Health Behavior, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC, USA
| | - Justin G Trogdon
- Department of Health Policy and Management, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Leah Frerichs
- Department of Health Policy and Management, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
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Pellowski JA, Price DM, Desir A, Golub S, Operario D, Purtle J. Using audience segmentation to identify implementation strategies to improve PrEP uptake among at-risk cisgender women: a mixed-methods study protocol. Implement Sci Commun 2023; 4:140. [PMID: 37978402 PMCID: PMC10656952 DOI: 10.1186/s43058-023-00518-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Accepted: 10/28/2023] [Indexed: 11/19/2023] Open
Abstract
BACKGROUND In the USA, 19% of new HIV infections occur among cisgender women (cis women); however, only 10% of eligible cis women have been prescribed pre-exposure prophylaxis (PrEP) for the prevention of HIV infection (an evidence-based intervention). A fundamental challenge for expanding HIV prevention to cis women is ensuring implementation strategies are tailored to the various healthcare settings in which cis women seek care and the heterogeneous providers nested within these settings. This project's specific aims are to (1) explore clinician-level characteristics and organizational climate factors that are related to variability in adoption of PrEP service delivery as an evidence-based intervention for cis women; (2) identify latent audience segments of women's health providers as the related to PrEP acceptability, adoption, and maintenance and analyze demographic correlates of these segments; and (3) identify audience segment-specific implementation strategies to facilitate the adoption of PrEP as an evidence-based intervention among at-risk cis women. METHODS Using the i-PARIHS framework, this mixed-methods study examines three domains for guiding audience segmentation to facilitate PrEP implementation for cis women: innovation (degree of fit with existing practices, usability), recipient beliefs and knowledge and context factors (organizational culture, readiness for change), needs to determine appropriate facilitation methods. To achieve aim 1, qualitative interviews will be conducted with PrEP-eligible cis women, women's health providers, and other key stakeholders. Aim 2 will consist of a quantitative survey among 340 women's health providers. Latent class analysis will be used to facilitate audience segmentation. To achieve aim 3, a panel of 5-8 providers for each audience segment will meet and engage in iterative discussions guided by Fernandez's implementation mapping to identify (1) implementation outcomes and performance objectives, determinants, and change objectives and (2) determine and refine of implementation strategies for each audience segment. DISCUSSION This exploratory mixed methods study will provide an empirical foundation to inform the development implementations strategies aimed at increasing PrEP delivery to cis women among heterogenous groups of providers.
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Affiliation(s)
- Jennifer A Pellowski
- Department of Behavioral and Social Sciences, Brown University School of Public Health, International Health Institute, 121 South Main Street, Providence, RI, 02903, USA.
| | - Devon M Price
- Department of Psychology, Hunter College & Graduate Center of the City University of New York, 695 Park Avenue, New York, NY, 10065, USA
| | - Arielle Desir
- Department of Behavioral and Social Sciences, Brown University School of Public Health, 121 South Main Street, Providence, RI, 02903, USA
| | - Sarit Golub
- Department of Psychology, Hunter College & Graduate Center of the City University of New York, 695 Park Avenue, New York, NY, 10065, USA
| | - Don Operario
- Department of Behavioral, Social, and Health Education Sciences, Emory University Rollins School of Public Health, 1518 Clifton Road, Atlanta, GA, 30322, USA
| | - Jonathan Purtle
- Department of Public Health Policy & Management, Global Center for Implementation Science, New York University School of Global Public Health, 708 Broadway, New York, NY, 10003, USA
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Purtle J, Moucheraud C, Yang LH, Shelley D. Four very basic ways to think about policy in implementation science. Implement Sci Commun 2023; 4:111. [PMID: 37700360 PMCID: PMC10496363 DOI: 10.1186/s43058-023-00497-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Accepted: 09/04/2023] [Indexed: 09/14/2023] Open
Abstract
BACKGROUND Policy is receiving increasing attention in the field of implementation science. However, there remains a lack of clear, concise guidance about how policy can be conceptualized in implementation science research. Building on Curran's article "Implementation science made too simple"-which defines "the thing" as the intervention, practice, or innovation in need of implementation support-we offer a typology of four very basic ways to conceptualize policy in implementation science research. We provide examples of studies that have conceptualized policy in these different ways and connect aspects of the typology to established frameworks in the field. The typology simplifies and refines related typologies in the field. Four very basic ways to think about policy in implementation science research. 1) Policy as something to adopt: an evidence-supported policy proposal is conceptualized as "the thing" and the goal of research is to understand how policymaking processes can be modified to increase adoption, and thus reach, of the evidence-supported policy. Policy-focused dissemination research is well-suited to achieve this goal. 2) Policy as something to implement: a policy, evidence-supported or not, is conceptualized as "the thing" and the goal of research is to generate knowledge about how policy rollout (or policy de-implementation) can be optimized to maximize benefits for population health and health equity. Policy-focused implementation research is well-suited to achieve this goal. 3) Policy as context to understand: an evidence-supported intervention is "the thing" and policies are conceptualized as a fixed determinant of implementation outcomes. The goal of research is to understand the mechanisms through which policies affect implementation of the evidence-supported intervention. 4) Policy as strategy to use: an evidence-supported intervention is "the thing" and policy is conceptualized as a strategy to affect implementation outcomes. The goal of research is to understand, and ideally test, how policy strategies affect implementation outcomes related to the evidence-supported intervention. CONCLUSION Policy can be conceptualized in multiple, non-mutually exclusive ways in implementation science. Clear conceptualizations of these distinctions are important to advancing the field of policy-focused implementation science and promoting the integration of policy into the field more broadly.
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Affiliation(s)
- Jonathan Purtle
- Department of Public Health Policy & Management, Global Center for Implementation Science, New York University School of Global Public Health, 708 Broadway, New York, NY, 10003, USA.
| | - Corrina Moucheraud
- Department of Public Health Policy & Management, Global Center for Implementation Science, New York University School of Global Public Health, 708 Broadway, New York, NY, 10003, USA
| | - Lawrence H Yang
- Department of Social and Behavioral Sciences, Global Center for Implementation Science, New York University School of Global Public Health, Global Mental Health and Stigma Program, 708 Broadway, New York, NY, 10003, USA
| | - Donna Shelley
- Department of Public Health Policy & Management, Global Center for Implementation Science, New York University School of Global Public Health, 708 Broadway, New York, NY, 10003, USA
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Crable EL, Grogan CM, Purtle J, Roesch SC, Aarons GA. Tailoring dissemination strategies to increase evidence-informed policymaking for opioid use disorder treatment: study protocol. Implement Sci Commun 2023; 4:16. [PMID: 36797794 PMCID: PMC9936679 DOI: 10.1186/s43058-023-00396-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2022] [Accepted: 01/30/2023] [Indexed: 02/18/2023] Open
Abstract
BACKGROUND Policy is a powerful tool for systematically altering healthcare access and quality, but the research to policy gap impedes translating evidence-based practices into public policy and limits widespread improvements in service and population health outcomes. The US opioid epidemic disproportionately impacts Medicaid members who rely on publicly funded benefits to access evidence-based treatment including medications for opioid use disorder (MOUD). A myriad of misaligned policies and evidence-use behaviors by policymakers across federal agencies, state Medicaid agencies, and managed care organizations limit coverage of and access to MOUD for Medicaid members. Dissemination strategies that improve policymakers' use of current evidence are critical to improving MOUD benefits and reducing health disparities. However, no research describes key determinants of Medicaid policymakers' evidence use behaviors or preferences, and few studies have examined data-driven approaches to developing dissemination strategies to enhance evidence-informed policymaking. This study aims to identify determinants and intermediaries that influence policymakers' evidence use behaviors, then develop and test data-driven tailored dissemination strategies that promote MOUD coverage in benefit arrays. METHODS Guided by the Exploration, Preparation, Implementation, and Sustainment (EPIS) framework, we will conduct a national survey of state Medicaid agency and managed care organization policymakers to identify determinants and intermediaries that influence how they seek, receive, and use research in their decision-making processes. We will use latent class methods to empirically identify subgroups of agencies with distinct evidence use behaviors. A 10-step dissemination strategy development and specification process will be used to tailor strategies to significant predictors identified for each latent class. Tailored dissemination strategies will be deployed to each class of policymakers and assessed for their acceptability, appropriateness, and feasibility for delivering evidence about MOUD benefit design. DISCUSSION This study will illuminate key determinants and intermediaries that influence policymakers' evidence use behaviors when designing benefits for MOUD. This study will produce a critically needed set of data-driven, tailored policy dissemination strategies. Study results will inform a subsequent multi-site trial measuring the effectiveness of tailored dissemination strategies on MOUD benefit design and implementation. Lessons from dissemination strategy development will inform future research about policymakers' evidence use preferences and offer a replicable process for tailoring dissemination strategies.
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Affiliation(s)
- Erika L Crable
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA. .,Child and Adolescent Services Research Center, San Diego, CA, USA. .,University of California, San Diego Altman Clinical and Translational Research Institute Dissemination and Implementation Science Center, La Jolla, CA, USA.
| | - Colleen M Grogan
- Crown Family School of Social Work, Policy, and Practice, The University of Chicago, Chicago, IL, USA
| | - Jonathan Purtle
- Department of Public Health Policy and Management, New York University School of Global Public Health, New York City, NY, USA.,Global Center for Implementation Science, New York University School of Global Public Health, New York City, NY, USA
| | - Scott C Roesch
- Child and Adolescent Services Research Center, San Diego, CA, USA.,Department of Psychology, San Diego State University, San Diego, CA, USA
| | - Gregory A Aarons
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA.,Child and Adolescent Services Research Center, San Diego, CA, USA.,University of California, San Diego Altman Clinical and Translational Research Institute Dissemination and Implementation Science Center, La Jolla, CA, USA
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Kwon N, Stewart RE, Wang X, Marzalik JS, Bufka LF, Halfond RW, Purtle J. Where do psychologists turn to inform clinical decisions? Audience segmentation to guide dissemination strategies. IMPLEMENTATION RESEARCH AND PRACTICE 2023; 4:26334895231185376. [PMID: 37790187 PMCID: PMC10331216 DOI: 10.1177/26334895231185376] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/05/2023] Open
Abstract
Background Audience segmentation is an analysis technique that can identify meaningful subgroups within a population to inform the tailoring of dissemination strategies. We have conducted an empirical clustering audience segmentation study of licensed psychologists using survey data about the sources of knowledge they report most often consulting to guide their clinical decision-making. We identify meaningful subgroups within the population and inform the tailoring of dissemination strategies for evidence-based practice (EBP) materials. Method Data come from a 2018-2019 web-based survey of licensed psychologists who were members of the American Psychological Association (APA; N = 518, response rate = 29.8%). Ten dichotomous variables assessed sources that psychologists regularly consult to inform clinical decision-making (e.g., colleagues, academic literature, and practice guidelines). We used latent class analysis to identify segments of psychologists who turn to similar sources and named each segment based on the segment's most salient characteristics. Results Four audience segments were identified: the No-guidelines (45% of psychologists), Research-driven (16%), Thirsty-for-knowledge (9%), and No-reviews (30%). The four segments differed not only in their preferred sources of knowledge, but also in the types of evidence-based posttraumatic stress disorder (PTSD) treatments they provide, their awareness and usage intention of the APA PTSD clinical practice guideline, and attitudes toward clinical practice guidelines. Conclusion The results demonstrate that licensed psychologists are heterogeneous in terms of their knowledge-seeking behaviors and preferences for knowledge sources. The distinctive characteristics of these segments could guide the tailoring of dissemination materials and strategies to subsequently enhance the implementation of EBP among psychologists.
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Affiliation(s)
- Nayoung Kwon
- Department of Social and Behavioral Sciences, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Rebecca E. Stewart
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Xi Wang
- PolicyLab, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Jacob S. Marzalik
- Office of Practice Transformation and Quality, Practice Directorate, American Psychological Association, Washington, DC, USA
| | - Lynn F. Bufka
- Office of Practice Transformation and Quality, Practice Directorate, American Psychological Association, Washington, DC, USA
| | - Raquel W. Halfond
- Office of Practice Transformation and Quality, Practice Directorate, American Psychological Association, Washington, DC, USA
| | - Jonathan Purtle
- Department of Public Health Policy and Management, New York University School of Global Public Health, New York, NY, USA
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Proctor E, Ramsey AT, Saldana L, Maddox TM, Chambers DA, Brownson RC. FAST: A Framework to Assess Speed of Translation of Health Innovations to Practice and Policy. GLOBAL IMPLEMENTATION RESEARCH AND APPLICATIONS 2022; 2:107-119. [PMID: 35669171 PMCID: PMC9161655 DOI: 10.1007/s43477-022-00045-4] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Accepted: 05/14/2022] [Indexed: 04/14/2023]
Abstract
The 17-year time span between discovery and application of evidence in practice has become a unifying challenge for implementation science and translational science more broadly. Further, global pandemics and social crises demand timely implementation of rapidly accruing evidence to reduce morbidity and mortality. Yet speed remains an understudied metric in implementation science. Prevailing evaluations of implementation lack a temporal aspect, and current approaches have not yielded rapid implementation. In this paper, we address speed as an important conceptual and methodological gap in implementation science. We aim to untangle the complexities of studying implementation speed, offer a framework to assess speed of translation (FAST), and provide guidance to measure speed in evaluating implementation. To facilitate specification and reporting on metrics of speed, we encourage consideration of stakeholder perspectives (e.g., comparison of varying priorities), referents (e.g., speed in attaining outcomes, transitioning between implementation phases), and observation windows (e.g., time from intervention development to first patient treated) in its measurement. The FAST framework identifies factors that may influence speed of implementation and potential effects of implementation speed. We propose a research agenda to advance understanding of the pace of implementation, including identifying accelerators and inhibitors to speed.
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Affiliation(s)
- Enola Proctor
- Brown School, Washington University in St. Louis, St. Louis, MO 63130 USA
| | - Alex T. Ramsey
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110 USA
| | - Lisa Saldana
- Oregon Social Learning Center, Eugene, OR 97401 USA
| | - Thomas M. Maddox
- Healthcare Innovation Lab, BJC HealthCare/Washington University School of Medicine, St. Louis, MO 63110 USA
- Division of Cardiology, Washington University School of Medicine, St. Louis, MO 63110 USA
| | - David A. Chambers
- Division of Cancer Control and Population Sciences, National Cancer Institute, NIH, Bethesda, MD 20892 USA
| | - Ross C. Brownson
- Prevention Research Center, Brown School, Washington University in St. Louis, St. Louis, MO 63130 USA
- Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, St. Louis, MO 63110 USA
- Alvin J. Siteman Cancer Center, Washington University School of Medicine, St. Louis, MO 63110 USA
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