Suchergebnisse

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.

Background: One goal of health systems seeking to evolve into learning health systems is to accelerate the implementation and sustainment of evidence-based practices (EBPs). As part of this evolution, the Veterans Health Administration (VHA) developed the Innovation Ecosystem, which includes the Diffusion of Excellence (DoE), a program that identifies and diffuses Gold Status Practices (GSPs) across facilities. The DoE hosts an annual "Shark Tank" competition in which leaders bid on the opportunity to implement a GSP with 6 months of implementation support. Over 750 diverse practices were submitted in cohorts 2 and 3 of Shark Tank; 23 were designated GSPs and were implemented in 31 VA networks or facilities. As part of a national evaluation of the DoE, we identified factors contributing to GSP implementation and sustainment. Methods: Our sequential mixed methods evaluation of cohorts 2 and 3 of Shark Tank included semi-structured interviews with at least one representative from 30/31 implementing teams (N = 78/105 people invited) and survey responses from 29/31 teams (N = 39/47 invited). Interviews focused on factors influencing implementation and future sustainment. Surveys focused on sustainment 1.5-2 years after implementation. The Consolidated Framework for Implementation Research (CFIR) informed data collection and directed content analysis. Ordinal scales were developed inductively to rank implementation and sustainment outcomes. Results: Over 50% of teams (17/30) successfully implemented their GSP within the 6-month implementation period. Despite extensive implementation support, significant barriers related to centralized decision-making, staffing, and resources led to partial (n = 6) or no (n = 7) implementation for the remaining teams. While 12/17 initially successful implementation teams reported sustained use of their GSP, over half of the initially unsuccessful teams (n = 7/13) also reported sustained GSP use 1.5 years after the initial implementation period. When asked at 6 months, 18/27 teams with complete data accurately anticipated their future sustainability based on reported sustainment an average of 1.5 years later. Conclusions: Most teams implemented within 6 months and/or sustained their GSP 1.5 years later. High levels of implementation and sustainment across diverse practices and teams suggest that VHA's DoE is a successful large-scale model of diffusion. Team predictions about sustainability after the first 6 months of implementation provide a promising early assessment and point of intervention to increase sustainability.

BACKGROUND: Collaboration between researchers, implementers and policymakers improves uptake of health systems research. In 2018, researchers and VHA Innovators Network (iNET) leadership used an embedded research model to conduct an evaluation of iNET. We describe our evaluation design, early results, and lessons learned. METHODS: This mixed-methods evaluation incorporated primary data collection via electronic survey, descriptive analysis using existing VA datasets (examining associations between facility characteristics and iNET participation), and qualitative interviews to support real-time program implementation and to probe perceived impacts, benefits and challenges of participation. RESULTS: We developed reporting tools and collected data regarding site participation, providing iNET leadership rapid access to needed information on projects (e.g., target populations reached, milestones achieved, and barriers encountered). Secondary data analyses indicated iNET membership was greater among larger, more complex VA facilities. Of the 37 iNET member sites, over half (n = 22) did not have any of the six major types of VA research centers; thus iNET is supporting VA sites not traditionally served by research innovation pathways. Qualitative findings highlighted enhanced engagement and perceived value of social and informational networks. CONCLUSIONS: Working alongside our iNET partners, we supported and influenced iNET's development through our embedded evaluation's preliminary findings. We also provided training and guidance aimed at building capacity among iNET participants. IMPLICATIONS: Embedded research can yield successful collaborative efforts between researchers and partners. An embedded research team can help programs pivot to ensure effective use of limited resources. Such models inform program development and expansion, supporting strategic planning and demonstrating value.