Article

Implementing the MOVE! Weight-Management Program in the Veterans Health Administration, 2007-2010: A Qualitative Study

Department of Health Policy and Management, CB 7411, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-7411, USA.
Preventing chronic disease (Impact Factor: 2.12). 01/2012; 9(1):E16. DOI: 10.5888/pcd9.110127
Source: PubMed

ABSTRACT

One-third of US veterans receiving care at Veterans Health Administration (VHA) medical facilities are obese and, therefore, at higher risk for developing multiple chronic diseases. To address this problem, the VHA designed and nationally disseminated an evidence-based weight-management program (MOVE!). The objective of this study was to examine the organizational factors that aided or inhibited the implementation of MOVE! in 10 VHA medical facilities.
Using a multiple, holistic case study design, we conducted 68 interviews with medical center program coordinators, physicians formally appointed as program champions, managers directly responsible for overseeing the program, clinicians from the program's multidisciplinary team, and primary care physicians identified by program coordinators as local opinion leaders. Qualitative data analysis involved coding, memorandum writing, and construction of data displays.
Organizational readiness for change and having an innovation champion were most consistently the 2 factors associated with MOVE! implementation. Other organizational factors, such as management support and resource availability, were barriers to implementation or exerted mixed effects on implementation. Barriers did not prevent facilities from implementing MOVE! However, they were obstacles that had to be overcome, worked around, or accepted as limits on the program's scope or scale.
Policy-directed implementation of clinical weight-management programs in health care facilities is challenging, especially when no new resources are available. Instituting powerful, mutually reinforcing organizational policies and practices may be necessary for consistent, high-quality implementation.

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Available from: Lindsey Haynes-Maslow, Mar 13, 2014
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    • "It provides both primary and specialty care within both inpatient and outpatient settings. To combat the challenges of obesity in this population, the VHA requires that Veterans seen within primary care are screened for obesity [6] and that overweight and obese patients are offered intensive treatment through the MOVE! program [8], which is available at all VHA medical centers [9]. Rates of screening and referral to MOVE! and/or offering other treatment options are 94 % due to the use of clinical reminders in the electronic health record [10]. "
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    ABSTRACT: Background: Obesity affects 37 % of patients at Veterans Health Administration (VHA) medical centers. The VHA offers an intensive weight management program (MOVE!) but less than 10 % of eligible patients ever attend. However, VHA patients see their primary care provider about 3.6 times per year, supporting the development of primary care-based weight management interventions. To address gaps in the literature regarding Veterans' experiences with weight management and determine whether and how to develop a primary care-based weight management intervention to both improve obesity counseling and increase attendance to MOVE!, we conducted a qualitative study to assess: 1) Veterans' personal experiences with healthy weight-related behavior change (including barriers and facilitators to behavior change and experiences with primary care providers, staff, and the MOVE! program), and 2) potential new approaches to improve weight management within primary care at the VHA including goal setting and technology. Methods: Overweight/obese VHA patients (aged 18-75, BMI greater than 30 or greater than 25 with at least 1 co-morbidity) were recruited for focus group sessions stratified by gender, MOVE! referral, and attendance. Each session was facilitated by a trained moderator, audio-recorded, and professionally transcribed. Using an iterative coding approach, two coders separately reviewed and coded transcripts, and met frequently to negotiate codes and synthesize emerging themes. Results: Of 161 eligible patients, 54 attended one of 6 focus groups (2 female, 4 male, 9-11 participants per session): 63 % were male, 46 % identified as African-American, 32 % White/Caucasian, 74 % were college-educated or higher, and 61 % reported having attended MOVE!. We identified two major themes: Impact of Military Service and Promotion and Sustainability of Healthy Behaviors. After service in a highly structured military environment, Veterans had difficulty maintaining weight on their own. They perceived physical activity as having more impact than diet, but chronic pain was a barrier. We identified individual/interpersonal-, community/environment-, and healthcare system-related factors affecting healthy behaviors. We also received input about Veteran's preferences and experiences with technology and setting health goals. Conclusions: Unique factors influence weight management in Veterans. Findings will inform development of a technology-assisted weight management intervention with tailored counseling and goal-setting within primary care at the VHA.
    Full-text · Article · Feb 2016
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    • "This survey was based on concepts from Weiner’s Organizational Readiness to Change Theory [9]. The survey has been pilot tested and modified for use in other settings [19-21]. We selected relevant items from Dr. Weiner’s survey item data bank [9]. "
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    ABSTRACT: Hypertension is prevalent and often sub-optimally controlled; however, interventions to improve blood pressure control have had limited success.Objectives: Through implementation of an evidence-based nurse-delivered self-management phone intervention to facilitate hypertension management within large complex health systems, we sought to answer the following questions: What is the level of organizational readiness to implement the intervention? What are the specific facilitators, barriers, and contextual factors that may affect organizational readiness to change?Study design: Each intervention site from three separate Veterans Integrated Service Networks (VISNs), which represent 21 geographic regions across the US, agreed to enroll 500 participants over a year with at least 0.5 full time equivalent employees of nursing time. Our mixed methods approach used a priori semi-structured interviews conducted with stakeholders (n = 27) including nurses, physicians, administrators, and information technology (IT) professionals between 2010 and 2011. Researchers iteratively identified facilitators and barriers of organizational readiness to change (ORC) and implementation. Additionally, an ORC survey was conducted with the stakeholders who were (n = 102) preparing for program implementation. Key ORC facilitators included stakeholder buy-in and improving hypertension. Positive organizational characteristics likely to impact ORC included: other similar programs that support buy-in, adequate staff, and alignment with the existing site environment; improved patient outcomes; is positive for the professional nurse role, and is evidence-based; understanding of the intervention; IT infrastructure and support, and utilization of existing equipment and space.The primary ORC barrier was unclear long-term commitment of nursing. Negative organizational characteristics likely to impact ORC included: added workload, competition with existing programs, implementation length, and limited available nurse staff time; buy-in is temporary until evidence shows improved outcomes; contacting patients and the logistics of integration into existing workflow is a challenge; and inadequate staffing is problematic. Findings were complementary across quantitative and qualitative analyses. The model of organizational change identified key facilitators and barriers of organizational readiness to change and successful implementation. This study allows us to understand the needs and challenges of intervention implementation. Furthermore, examination of organizational facilitators and barriers to implementation of evidence-based interventions may inform dissemination in other chronic diseases.
    Full-text · Article · Sep 2013 · Implementation Science
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    • "The majority of constructs that distinguished between high and low implementation facilities were related to the inner setting. Klein et al. [27] and others [15,28] highlight the important and influential roles and interrelationships of leadership engagement, available resources, and relative priority. Leadership engagement can lead to provision of sufficient available resources in terms of space and dedicated time, and strong communication about the program, which in turn can lead to sufficiently strong perceptions that an intervention has high relative priority in the midst of other initiatives. "
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    ABSTRACT: Background In the United States, as in many other parts of the world, the prevalence of overweight/obesity is at epidemic proportions in the adult population and even higher among Veterans. To address the high prevalence of overweight/obesity among Veterans, the MOVE!® weight management program was disseminated nationally to Veteran Affairs (VA) medical centers. The objective of this paper is two-fold: to describe factors that explain the wide variation in implementation of MOVE!; and to illustrate, step-by-step, how to apply a theory-based framework using qualitative data. Methods Five VA facilities were selected to maximize variation in implementation effectiveness and geographic location. Twenty-four key stakeholders were interviewed about their experiences in implementing MOVE!. The Consolidated Framework for Implementation Research (CFIR) was used to guide collection and analysis of qualitative data. Constructs that most strongly influence implementation effectiveness were identified through a cross-case comparison of ratings. Results Of the 31 CFIR constructs assessed, ten constructs strongly distinguished between facilities with low versus high program implementation effectiveness. The majority (six) were related to the inner setting: networks and communications; tension for change; relative priority; goals and feedback; learning climate; and leadership engagement. One construct each, from intervention characteristics (relative advantage) and outer setting (patient needs and resources), plus two from process (executing and reflecting) also strongly distinguished between high and low implementation. Two additional constructs weakly distinguished, 16 were mixed, three constructs had insufficient data to assess, and one was not applicable. Detailed descriptions of how each distinguishing construct manifested in study facilities and a table of recommendations is provided. Conclusions This paper presents an approach for using the CFIR to code and rate qualitative data in a way that will facilitate comparisons across studies. An online Wiki resource (http://www.wiki.cfirwiki.net) is available, in addition to the information presented here, that contains much of the published information about the CFIR and its constructs and sub-constructs. We hope that the described approach and open access to the CFIR will generate wide use and encourage dialogue and continued refinement of both the framework and approaches for applying it.
    Full-text · Article · May 2013 · Implementation Science
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