Application of the FRAME-IS to a multifaceted implementation strategy.
Adaptation
Federally qualified health center
Implementation strategy
Practice facilitation
Journal
BMC health services research
ISSN: 1472-6963
Titre abrégé: BMC Health Serv Res
Pays: England
ID NLM: 101088677
Informations de publication
Date de publication:
01 Jun 2024
01 Jun 2024
Historique:
received:
05
02
2024
accepted:
22
05
2024
medline:
1
6
2024
pubmed:
1
6
2024
entrez:
31
5
2024
Statut:
epublish
Résumé
Research demonstrates the importance of documenting adaptations to implementation strategies that support integration of evidence-based interventions into practice. While studies have utilized the FRAME-IS [Framework for Reporting Adaptations and Modifications for Implementation Strategies] to collect structured adaptation data, they are limited by a focus on discrete implementation strategies (e.g., training), which do not reflect the complexity of multifaceted strategies like practice facilitation. In this paper, we apply the FRAME-IS to our trial evaluating the effectiveness of PF on implementation fidelity of an evidence-based technology-facilitated team care model for improved hypertension control within a federally qualified health center (FQHC). Three data sources are used to document adaptations: (1) implementation committee meeting minutes, (2) narrative reports completed by practice facilitators, and (3) structured notes captured on root cause analysis and Plan-Do-Study-Act worksheets. Text was extracted from the data sources according to the FRAME-IS modules and inputted into a master matrix for content analysis by two authors; a third author conducted member checking and code validation. We modified the FRAME-IS to include part 2 of module 2 (what is modified) to add greater detail of the modified strategy, and a numbering system to track adaptations across the modules. This resulted in identification of 27 adaptations, of which 88.9% focused on supporting practices in identifying eligible patients and referring them to the intervention. About half (52.9%) of the adaptations were made to modify the context of the PF strategy to include a group-based format, add community health workers to the strategy, and to shift the implementation target to nurses. The adaptations were often widespread (83.9%), affecting all practices within the FQHC. While most adaptations were reactive (84.6%), they resulted from a systematic process of reviewing data captured by multiple sources. All adaptations included the FQHC in the decision-making process. With modifications, we demonstrate the ability to document our adaptation data across the FRAME-IS modules, attesting to its applicability and value for a range of implementation strategies. Based on our experiences, we recommend refinement of tracking systems to support more nimble and practical documentation of iterative, ongoing, and multifaceted adaptations. Clinicaltrials.gov NCT03713515, Registration date: October 19, 2018.
Sections du résumé
BACKGROUND
BACKGROUND
Research demonstrates the importance of documenting adaptations to implementation strategies that support integration of evidence-based interventions into practice. While studies have utilized the FRAME-IS [Framework for Reporting Adaptations and Modifications for Implementation Strategies] to collect structured adaptation data, they are limited by a focus on discrete implementation strategies (e.g., training), which do not reflect the complexity of multifaceted strategies like practice facilitation. In this paper, we apply the FRAME-IS to our trial evaluating the effectiveness of PF on implementation fidelity of an evidence-based technology-facilitated team care model for improved hypertension control within a federally qualified health center (FQHC).
METHODS
METHODS
Three data sources are used to document adaptations: (1) implementation committee meeting minutes, (2) narrative reports completed by practice facilitators, and (3) structured notes captured on root cause analysis and Plan-Do-Study-Act worksheets. Text was extracted from the data sources according to the FRAME-IS modules and inputted into a master matrix for content analysis by two authors; a third author conducted member checking and code validation.
RESULTS
RESULTS
We modified the FRAME-IS to include part 2 of module 2 (what is modified) to add greater detail of the modified strategy, and a numbering system to track adaptations across the modules. This resulted in identification of 27 adaptations, of which 88.9% focused on supporting practices in identifying eligible patients and referring them to the intervention. About half (52.9%) of the adaptations were made to modify the context of the PF strategy to include a group-based format, add community health workers to the strategy, and to shift the implementation target to nurses. The adaptations were often widespread (83.9%), affecting all practices within the FQHC. While most adaptations were reactive (84.6%), they resulted from a systematic process of reviewing data captured by multiple sources. All adaptations included the FQHC in the decision-making process.
CONCLUSION
CONCLUSIONS
With modifications, we demonstrate the ability to document our adaptation data across the FRAME-IS modules, attesting to its applicability and value for a range of implementation strategies. Based on our experiences, we recommend refinement of tracking systems to support more nimble and practical documentation of iterative, ongoing, and multifaceted adaptations.
TRIAL REGISTRATION
BACKGROUND
Clinicaltrials.gov NCT03713515, Registration date: October 19, 2018.
Identifiants
pubmed: 38822342
doi: 10.1186/s12913-024-11139-0
pii: 10.1186/s12913-024-11139-0
doi:
Banques de données
ClinicalTrials.gov
['NCT03713515']
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
695Informations de copyright
© 2024. The Author(s).
Références
Chambers DA. Advancing adaptation of evidence-based interventions through implementation science: progress and opportunities. Front Health Serv. 2023;3:1204138.
doi: 10.3389/frhs.2023.1204138
pubmed: 37342795
pmcid: 10277471
Stirman SW, Gamarra J, Bartlett B, Calloway A, Gutner C. Empirical examinations of modifications and adaptations to evidence-based psychotherapies: methodologies, impact, and future directions. Clin Psychol (New York). 2017;24(4):396–420.
pubmed: 29593372
Stirman SW, Miller CJ, Toder K, Calloway A. Development of a framework and coding system for modifications and adaptations of evidence-based interventions. Implement Sci. 2013;8(1):65.
doi: 10.1186/1748-5908-8-65
pubmed: 23758995
pmcid: 3686699
Escoffery C, Lebow-Skelley E, Haardoerfer R, Boing E, Udelson H, Wood R, et al. A systematic review of adaptations of evidence-based public health interventions globally. Implement Sci. 2018;13(1):125.
doi: 10.1186/s13012-018-0815-9
pubmed: 30257683
pmcid: 6158804
Aarons GA, Green AE, Palinkas LA, Self-Brown S, Whitaker DJ, Lutzker JR, et al. Dynamic adaptation process to implement an evidence-based child maltreatment intervention. Implement Sci. 2012;7(1):32.
doi: 10.1186/1748-5908-7-32
pubmed: 22512914
pmcid: 3436717
Miller CJ, Barnett ML, Baumann AA, Gutner CA, Wiltsey-Stirman S. The FRAME-IS: a framework for documenting modifications to implementation strategies in healthcare. Implement Sci. 2021;16(1):36.
doi: 10.1186/s13012-021-01105-3
pubmed: 33827716
pmcid: 8024675
Kirk MA, Moore JE, WiltseyStirman S, Birken SA. Towards a comprehensive model for understanding adaptations’ impact: the model for adaptation design and impact (MADI). Implement Sci. 2020;15(1):56.
doi: 10.1186/s13012-020-01021-y
pubmed: 32690104
pmcid: 7370455
Smith JD, Merle JL, Webster KA, Cahue S, Penedo FJ, Garcia SF. Tracking dynamic changes in implementation strategies over time within a hybrid type 2 trial of an electronic patient-reported oncology symptom and needs monitoring program. Front Health Serv. 2022;2:983217.
doi: 10.3389/frhs.2022.983217
pubmed: 36925901
pmcid: 10012686
Haley AD, Powell BJ, Walsh-Bailey C, Krancari M, Gruß I, Shea CM, et al. Strengthening methods for tracking adaptations and modifications to implementation strategies. BMC Med Res Methodol. 2021;21(1):133.
doi: 10.1186/s12874-021-01326-6
pubmed: 34174834
pmcid: 8235850
Lyles CR, Handley MA, Ackerman SL, Schillinger D, Williams P, Westbrook M, et al. Innovative Implementation studies conducted in US safety net health care settings: a systematic review. Am J Med Qual. 2019;34(3):293–306.
doi: 10.1177/1062860618798469
pubmed: 30198304
Institute of Medicine Committee on the Changing Market MC, the Future Viability of Safety Net P. In: Ein Lewin M, Altman S, editors. Americas's Health Care Safety Net: Intact but Endangered. Washington (DC): National Academies Press (US) Copyright 2000 by the National Academy of Sciences: 2000. All rights reserved.
Lewin ME, Baxter RJ. America’s health care safety net: revisiting the 2000 IOM report. Health Aff (Millwood). 2007;26(5):1490–4.
doi: 10.1377/hlthaff.26.5.1490
pubmed: 17848461
Mangale DI, Onyango A, Mugo C, Mburu C, Chhun N, Wamalwa D, et al. Characterizing provider-led adaptations to mobile phone delivery of the Adolescent Transition Package (ATP) in Kenya using the Framework for Reporting Adaptations and Modifications to Evidence-based Implementation Strategies (FRAME-IS): a mixed methods approach. Implement Sci Commun. 2023;4(1):95.
doi: 10.1186/s43058-023-00446-y
pubmed: 37580836
pmcid: 10424422
Yakovchenko V, Rogal SS, Goodrich DE, Lamorte C, Neely B, Merante M, et al. Getting to implementation: adaptation of an implementation playbook. Front Public Health. 2022;10:980958.
doi: 10.3389/fpubh.2022.980958
pubmed: 36684876
Martinez K, Lane E, Hernandez V, Lugo E, Muñoz FA, Sahms T, et al. Optimizing ATTAIN implementation in a federally qualified health center guided by the FRAME-IS. Am Psychol. 2023;78(2):82–92.
doi: 10.1037/amp0001077
pubmed: 37011161
pmcid: 10071441
Zehner ME, Kirsch JA, Adsit RT, Gorrilla A, Hayden K, Skora A, et al. Electronic health record closed-loop referral (“eReferral”) to a state tobacco quitline: a retrospective case study of primary care implementation challenges and adaptations. Implement Sci Commun. 2022;3(1):107.
doi: 10.1186/s43058-022-00357-4
pubmed: 36209149
pmcid: 9548147
Schoenthaler A, De La Calle F, Soto A, Barrett D, Cruz J, Payano L, et al. Bridging the evidence-to-practice gap: a stepped-wedge cluster randomized controlled trial evaluating practice facilitation as a strategy to accelerate translation of a multi-level adherence intervention into safety net practices. Implement Sci Commun. 2021;2(1):21.
doi: 10.1186/s43058-021-00111-2
pubmed: 33597041
pmcid: 7888171
Damschroder LJ, Reardon CM, OpraWiderquist MA, Lowery J. Conceptualizing outcomes for use with the Consolidated Framework for Implementation Research (CFIR): the CFIR outcomes addendum. Implement Sci. 2022;17(1):7.
doi: 10.1186/s13012-021-01181-5
pubmed: 35065675
pmcid: 8783408
Proctor E, Silmere H, Raghavan R, Hovmand P, Aarons G, Bunger A, et al. Outcomes for implementation research: conceptual distinctions, measurement challenges, and research agenda. Adm Policy Ment Health. 2011;38(2):65–76.
doi: 10.1007/s10488-010-0319-7
pubmed: 20957426
Smith AP, Overton K, Rakotz M, Wozniak G, Sanchez E. Target: BP: a national initiative to improve blood pressure control. Hypertension. 2023;80(12):2523–32.
doi: 10.1161/HYPERTENSIONAHA.123.20389
pubmed: 37855141
Gold HT, Siman N, Cuthel AM, Nguyen AM, Pham-Singer H, Berry CA, et al. A practice facilitation-guided intervention in primary care settings to reduce cardiovascular disease risk: a cost analysis. Implement Sci Commun. 2021;2(1):15.
doi: 10.1186/s43058-021-00116-x
pubmed: 33549152
pmcid: 7868016
Shelley DR, Ogedegbe G, Anane S, Wu WY, Goldfeld K, Gold HT, et al. Testing the use of practice facilitation in a cluster randomized stepped-wedge design trial to improve adherence to cardiovascular disease prevention guidelines: HealthyHearts NYC. Implement Sci. 2016;11(1):88.
doi: 10.1186/s13012-016-0450-2
pubmed: 27377404
pmcid: 4932668
Powell BJ, Waltz TJ, Chinman MJ, Damschroder LJ, Smith JL, Matthieu MM, et al. A refined compilation of implementation strategies: results from the Expert Recommendations for Implementing Change (ERIC) project. Implement Sci. 2015;10(1):21.
doi: 10.1186/s13012-015-0209-1
pubmed: 25889199
pmcid: 4328074
McCreight M, Rohs C, Lee M, Sjoberg H, Ayele R, Battaglia C, et al. Using a longitudinal multi-method approach to document, assess, and understand adaptations in the veterans health administration advanced care coordination program. Front Health Serv. 2022;2:970409.
doi: 10.3389/frhs.2022.970409
pubmed: 36925896
pmcid: 10012685
Sjoberg H, Kenney RR, Morgan B, Connelly B, Jones CD, Ali HN, et al. Adaptations to relational facilitation for two national care coordination programs during COVID-19. Front Health Serv. 2022;2:952272.
doi: 10.3389/frhs.2022.952272
pubmed: 36925807
pmcid: 10012763
McCarthy MS, Ujano-De Motta LL, Nunnery MA, Gilmartin H, Kelley L, Wills A, et al. Understanding adaptations in the Veteran Health Administration’s Transitions Nurse Program: refining methodology and pragmatic implications for scale-up. Implement Sci. 2021;16(1):71.
doi: 10.1186/s13012-021-01126-y
pubmed: 34256763
pmcid: 8276503
Blanchard CM, Livet M. Ensuring intervention success: assessing fit as an overlooked step of the implementation process. Pharm Pract (Granada). 2020;18(4):2235.
doi: 10.18549/PharmPract.2020.4.2235
pubmed: 33343775
Khanbhai M, Anyadi P, Symons J, Flott K, Darzi A, Mayer E. Applying natural language processing and machine learning techniques to patient experience feedback: a systematic review. BMJ Health & Care Informatics. 2021;28(1):e100262.
doi: 10.1136/bmjhci-2020-100262
Chambers DA, Norton WE. The adaptome: advancing the science of intervention adaptation. Am J Prev Med. 2016;51(4 Suppl 2):S124–31.
doi: 10.1016/j.amepre.2016.05.011
pubmed: 27371105
pmcid: 5030159