Analysis of FRAME data (A-FRAME): An analytic approach to assess the impact of adaptations on health services interventions and evaluations

IF 2.6 Q2 HEALTH POLICY & SERVICES
Heather Z. Mui, Cati G. Brown-Johnson, Erika A. Saliba-Gustafsson, Anna Sophia Lessios, Mae Verano, Rachel Siden, Laura M. Holdsworth
{"title":"Analysis of FRAME data (A-FRAME): An analytic approach to assess the impact of adaptations on health services interventions and evaluations","authors":"Heather Z. Mui,&nbsp;Cati G. Brown-Johnson,&nbsp;Erika A. Saliba-Gustafsson,&nbsp;Anna Sophia Lessios,&nbsp;Mae Verano,&nbsp;Rachel Siden,&nbsp;Laura M. Holdsworth","doi":"10.1002/lrh2.10364","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Introduction</h3>\n \n <p>Tracking adaptations during implementation can help assess and interpret outcomes. The framework for reporting adaptations and modifications-expanded (FRAME) provides a structured approach to characterize adaptations. We applied the FRAME across multiple health services projects, and developed an analytic approach to assess the impact of adaptations.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>Mixed methods analysis of research diaries from seven quality improvement (QI) and research projects during the early stages of the COVID-19 pandemic. Using the FRAME as a codebook, discrete adaptations were described and categorized. We then conducted a three-step analysis plan: (1) calculated the frequency of adaptations by FRAME categories across projects; (2) qualitatively assessed the impact of adaptations on project goals; and (3) qualitatively assessed relationships between adaptations within projects to thematically consolidate adaptations to generate more explanatory value on how adaptations influenced intervention progress and outcomes.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>Between March and July 2020, 42 adaptations were identified across seven health services projects. The majority of adaptations related to training or evaluation (52.4%) with the goal of maintaining the feasibility (66.7%) of executing projects during the pandemic. Five FRAME constructs offered the most explanatory benefit to assess the impact of adaptations on program and evaluation goals, providing the basis for creating an analytic approach dubbed the “A-FRAME,” analysis of FRAME data. Using the A-FRAME, the 42 adaptations were consolidated into 17 succinct adaptations. Two QI projects discontinued altogether. Intervention adaptations related to staffing, training, or delivery, while evaluation adaptations included design, recruitment, and data collection adjustments.</p>\n </section>\n \n <section>\n \n <h3> Conclusions</h3>\n \n <p>By sifting qualitative data about adaptations into the A-FRAME, implementers and researchers can succinctly describe how adaptations affect interventions and their evaluations. The simple and concise presentation of information using the A-FRAME matrix can help implementers and evaluators account for the influence of adaptations on program outcomes.</p>\n </section>\n </div>","PeriodicalId":43916,"journal":{"name":"Learning Health Systems","volume":"8 1","pages":""},"PeriodicalIF":2.6000,"publicationDate":"2023-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/lrh2.10364","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Learning Health Systems","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/lrh2.10364","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"HEALTH POLICY & SERVICES","Score":null,"Total":0}
引用次数: 0

Abstract

Introduction

Tracking adaptations during implementation can help assess and interpret outcomes. The framework for reporting adaptations and modifications-expanded (FRAME) provides a structured approach to characterize adaptations. We applied the FRAME across multiple health services projects, and developed an analytic approach to assess the impact of adaptations.

Methods

Mixed methods analysis of research diaries from seven quality improvement (QI) and research projects during the early stages of the COVID-19 pandemic. Using the FRAME as a codebook, discrete adaptations were described and categorized. We then conducted a three-step analysis plan: (1) calculated the frequency of adaptations by FRAME categories across projects; (2) qualitatively assessed the impact of adaptations on project goals; and (3) qualitatively assessed relationships between adaptations within projects to thematically consolidate adaptations to generate more explanatory value on how adaptations influenced intervention progress and outcomes.

Results

Between March and July 2020, 42 adaptations were identified across seven health services projects. The majority of adaptations related to training or evaluation (52.4%) with the goal of maintaining the feasibility (66.7%) of executing projects during the pandemic. Five FRAME constructs offered the most explanatory benefit to assess the impact of adaptations on program and evaluation goals, providing the basis for creating an analytic approach dubbed the “A-FRAME,” analysis of FRAME data. Using the A-FRAME, the 42 adaptations were consolidated into 17 succinct adaptations. Two QI projects discontinued altogether. Intervention adaptations related to staffing, training, or delivery, while evaluation adaptations included design, recruitment, and data collection adjustments.

Conclusions

By sifting qualitative data about adaptations into the A-FRAME, implementers and researchers can succinctly describe how adaptations affect interventions and their evaluations. The simple and concise presentation of information using the A-FRAME matrix can help implementers and evaluators account for the influence of adaptations on program outcomes.

Abstract Image

FRAME数据分析(A‐FRAME):一种评估调整对卫生服务干预和评价影响的分析方法
导言 跟踪实施过程中的适应情况有助于评估和解释成果。报告适应性调整和修改的扩展框架(FRAME)为描述适应性调整提供了一种结构化方法。我们在多个医疗服务项目中应用了 FRAME,并开发了一种分析方法来评估调整的影响。 方法 对 COVID-19 大流行初期的七个质量改进 (QI) 和研究项目的研究日记进行混合方法分析。使用 FRAME 作为编码手册,对离散的适应性进行描述和分类。然后,我们进行了三步分析计划:(1) 按 FRAME 类别计算各项目中调整的频率;(2) 定性评估调整对项目目标的影响;(3) 定性评估项目内调整之间的关系,以便对调整进行专题整合,从而对调整如何影响干预进展和结果产生更多解释价值。 结果 在 2020 年 3 月至 7 月期间,七个医疗服务项目共确定了 42 项适应性调整。大多数调整与培训或评估有关(52.4%),目的是在大流行期间保持执行项目的可行性(66.7%)。FRAME 中的五个构造对评估适应性调整对项目和评估目标的影响最有解释力,为创建一种被称为 "A-FRAME "的 FRAME 数据分析方法奠定了基础。利用 A-FRAME 分析方法,42 项调整被整合为 17 项简洁的调整。两个 QI 项目完全终止。干预调整涉及人员配备、培训或交付,而评估调整包括设计、招聘和数据收集调整。 结论 通过在 A-FRAME 中筛选有关调整的定性数据,实施者和研究者可以简明扼要地描述调整是如何影响干预及其评估的。使用 A-FRAME 矩阵简单扼要地展示信息,可以帮助实施者和评估者说明调整对计划结果的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Learning Health Systems
Learning Health Systems HEALTH POLICY & SERVICES-
CiteScore
5.60
自引率
22.60%
发文量
55
审稿时长
20 weeks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信