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      Rapid versus traditional qualitative analysis using the Consolidated Framework for Implementation Research (CFIR)

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          Abstract

          Background

          Qualitative approaches, alone or in mixed methods, are prominent within implementation science. However, traditional qualitative approaches are resource intensive, which has led to the development of rapid qualitative approaches. Published rapid approaches are often inductive in nature and rely on transcripts of interviews. We describe a deductive rapid analysis approach using the Consolidated Framework for Implementation Research (CFIR) that uses notes and audio recordings. This paper compares our rapid versus traditional deductive CFIR approach.

          Methods

          Semi-structured interviews were conducted for two cohorts of the Veterans Health Administration (VHA) Diffusion of Excellence (DoE). The CFIR guided data collection and analysis. In cohort A, we used our traditional CFIR-based deductive analysis approach (directed content analysis), where two analysts completed independent in-depth manual coding of interview transcripts using qualitative software. In cohort B, we used our new rapid CFIR-based deductive analysis approach (directed content analysis), where the primary analyst wrote detailed notes during interviews and immediately “coded” notes into a MS Excel CFIR construct by facility matrix; a secondary analyst then listened to audio recordings and edited the matrix. We tracked time for our traditional and rapid deductive CFIR approaches using a spreadsheet and captured transcription costs from invoices. We retrospectively compared our approaches in terms of effectiveness and rigor.

          Results

          Cohorts A and B were similar in terms of the amount of data collected. However, our rapid deductive CFIR approach required 409.5 analyst hours compared to 683 h during the traditional deductive CFIR approach. The rapid deductive approach eliminated $7250 in transcription costs. The facility-level analysis phase provided the greatest savings: 14 h/facility for the traditional analysis versus 3.92 h/facility for the rapid analysis. Data interpretation required the same number of hours for both approaches.

          Conclusion

          Our rapid deductive CFIR approach was less time intensive and eliminated transcription costs, yet effective in meeting evaluation objectives and establishing rigor. Researchers should consider the following when employing our approach: (1) team expertise in the CFIR and qualitative methods, (2) level of detail needed to meet project aims, (3) mode of data to analyze, and (4) advantages and disadvantages of using the CFIR.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s13012-021-01111-5.

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          Most cited references35

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          Using thematic analysis in psychology

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            Three approaches to qualitative content analysis.

            Content analysis is a widely used qualitative research technique. Rather than being a single method, current applications of content analysis show three distinct approaches: conventional, directed, or summative. All three approaches are used to interpret meaning from the content of text data and, hence, adhere to the naturalistic paradigm. The major differences among the approaches are coding schemes, origins of codes, and threats to trustworthiness. In conventional content analysis, coding categories are derived directly from the text data. With a directed approach, analysis starts with a theory or relevant research findings as guidance for initial codes. A summative content analysis involves counting and comparisons, usually of keywords or content, followed by the interpretation of the underlying context. The authors delineate analytic procedures specific to each approach and techniques addressing trustworthiness with hypothetical examples drawn from the area of end-of-life care.
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              Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science

              Background Many interventions found to be effective in health services research studies fail to translate into meaningful patient care outcomes across multiple contexts. Health services researchers recognize the need to evaluate not only summative outcomes but also formative outcomes to assess the extent to which implementation is effective in a specific setting, prolongs sustainability, and promotes dissemination into other settings. Many implementation theories have been published to help promote effective implementation. However, they overlap considerably in the constructs included in individual theories, and a comparison of theories reveals that each is missing important constructs included in other theories. In addition, terminology and definitions are not consistent across theories. We describe the Consolidated Framework For Implementation Research (CFIR) that offers an overarching typology to promote implementation theory development and verification about what works where and why across multiple contexts. Methods We used a snowball sampling approach to identify published theories that were evaluated to identify constructs based on strength of conceptual or empirical support for influence on implementation, consistency in definitions, alignment with our own findings, and potential for measurement. We combined constructs across published theories that had different labels but were redundant or overlapping in definition, and we parsed apart constructs that conflated underlying concepts. Results The CFIR is composed of five major domains: intervention characteristics, outer setting, inner setting, characteristics of the individuals involved, and the process of implementation. Eight constructs were identified related to the intervention (e.g., evidence strength and quality), four constructs were identified related to outer setting (e.g., patient needs and resources), 12 constructs were identified related to inner setting (e.g., culture, leadership engagement), five constructs were identified related to individual characteristics, and eight constructs were identified related to process (e.g., plan, evaluate, and reflect). We present explicit definitions for each construct. Conclusion The CFIR provides a pragmatic structure for approaching complex, interacting, multi-level, and transient states of constructs in the real world by embracing, consolidating, and unifying key constructs from published implementation theories. It can be used to guide formative evaluations and build the implementation knowledge base across multiple studies and settings.
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                Author and article information

                Contributors
                Andrea.Nevedal@va.gov
                Journal
                Implement Sci
                Implement Sci
                Implementation Science : IS
                BioMed Central (London )
                1748-5908
                2 July 2021
                2 July 2021
                2021
                : 16
                : 67
                Affiliations
                [1 ]GRID grid.280747.e, ISNI 0000 0004 0419 2556, Center for Innovation to Implementation (Ci2i), , VA Palo Alto Health Care System (152-MPD), ; 795 Willow Road, Building 324, Menlo Park, CA 94025 USA
                [2 ]GRID grid.497654.d, ISNI 0000 0000 8603 8958, Veterans Affairs (VA) Center for Clinical Management Research, , Ann Arbor Healthcare System, ; 2215 Fuller Rd. (152), Ann Arbor, MI 48105 USA
                [3 ]Center of Innovation to Accelerate Discovery and Practice Transformation (ADAPT), Durham VA Health Care System, Durham, USA
                [4 ]GRID grid.26009.3d, ISNI 0000 0004 1936 7961, Department of Population Health Science, , Duke University, ; Durham, USA
                [5 ]GRID grid.26009.3d, ISNI 0000 0004 1936 7961, Division of General Internal Medicine, , Duke University, ; Durham, USA
                [6 ]GRID grid.26009.3d, ISNI 0000 0004 1936 7961, Department of Family Medicine and Community Health, , Duke University, ; Durham, USA
                [7 ]Center for Healthcare Organization & Implementation Research, Bedford & Boston VA Medical Centers, Boston, USA
                [8 ]GRID grid.168645.8, ISNI 0000 0001 0742 0364, Department of Population and Quantitative Health Sciences, , University of Massachusetts Medical School, ; Worcester, USA
                [9 ]GRID grid.168645.8, ISNI 0000 0001 0742 0364, Division of General Internal Medicine, , University of Massachusetts Medical School, ; Worcester, USA
                Author information
                http://orcid.org/0000-0003-3859-8493
                Article
                1111
                10.1186/s13012-021-01111-5
                8252308
                34215286
                4664a58b-3ba0-41e3-8f97-2ca3a3fed1ad
                © The Author(s) 2021

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 26 December 2020
                : 5 April 2021
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100007181, Quality Enhancement Research Initiative;
                Award ID: PEC-17-002
                Award ID: PEC-17-002
                Categories
                Methodology
                Custom metadata
                © The Author(s) 2021

                Medicine
                consolidated framework for implementation research (cfir),qualitative methods,rapid analysis,implementation science,veterans

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