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Lattimer TA, Tenzek KE, Ophir Y. Shouts from the Void: A Mixed-Method Analysis Surrounding the Online Chronic Illness Community, NEISVoid. HEALTH COMMUNICATION 2024; 39:1966-1977. [PMID: 37691142 DOI: 10.1080/10410236.2023.2250939] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/12/2023]
Abstract
Chronic illness affects millions worldwide, rendering the life of those affected complex to manage. Extant research points to the need for effective and supportive care for the successful treatment, yet health care encounters for this population are often filled with negative experiences, ranging from discontinuity of care to disenfranchisement from providers. One such group dedicated to sharing struggles is the NEISVoid (No End In Sight) community on Twitter. Through the use of the hashtag, #NEISVoid, they come together to share what experiences living with chronic illness look like, in vulnerable and potentially unfiltered ways. The present study analyzes the discourse surrounding the hashtag #NEISVoid in tweets published from January 1 2020, until September 1 2022 (N = 450,914 tweets) using the mixed-method analysis of topic model network (ANTMN) approach. We identify and discuss four broad discursive themes: community experiences, symptom management, efficacy solutions, and biomedical health. We analyze this discourse through the chronic care model (CCM) and in light of research on hashtag activism. We discuss practical and theoretical implications for health communicators.
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Affiliation(s)
| | | | - Yotam Ophir
- Department of Communication, University at Buffalo
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Landes SJ, Matarazzo BB, Pitcock JA, Drummond KL, Smith BN, Kirchner JE, Clark KA, Gerard GR, Jankovsky MC, Brenner LA, Reger MA, Eagan AE, Raciborski R, Painter J, Townsend JC, Jegley SM, Singh RS, Trafton JA, McCarthy JF, Katz IR. Impact of Implementation Facilitation on the REACH VET Clinical Program for Veterans at Risk for Suicide. Psychiatr Serv 2024; 75:726-732. [PMID: 38444365 DOI: 10.1176/appi.ps.20230277] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/07/2024]
Abstract
OBJECTIVE In 2017, the Veterans Health Administration (VHA) implemented a national suicide prevention program, called Recovery Engagement and Coordination for Health-Veterans Enhanced Treatment (REACH VET), that uses a predictive algorithm to identify, attempt to reach, assess, and care for patients at the highest risk for suicide. The authors aimed to evaluate whether facilitation enhanced implementation of REACH VET at VHA facilities not meeting target completion rates. METHODS In this hybrid effectiveness-implementation type 2 program evaluation, a quasi-experimental pre-post design was used to assess changes in implementation outcome measures evaluated 6 months before and 6 months after onset of facilitation of REACH VET implementation at 23 VHA facilities. Measures included percentages of patients with documented coordinator and provider acknowledgment of receipt, care evaluation, and outreach attempt. Generalized estimating equations were used to compare differences in REACH VET outcome measures before and after facilitation. Qualitative interviews were conducted with personnel and were explored via template analysis. RESULTS Time had a significant effect in all outcomes models (p<0.001). An effect of facilitation was significant only for the outcome of attempted outreach. Patients identified by REACH VET had significantly higher odds of having a documented outreach attempt after facilitation of REACH VET implementation, compared with before facilitation. Site personnel felt supported and reported that the external facilitators were helpful and responsive. CONCLUSIONS Facilitation of REACH VET implementation was associated with an improvement in outreach attempts to veterans identified as being at increased risk for suicide. Outreach is critical for engaging veterans in care.
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Affiliation(s)
- Sara J Landes
- Central Arkansas Veterans Healthcare System, Little Rock (Landes, Pitcock, Drummond, Smith, Kirchner, Raciborski, Painter, Townsend, Jegley, Singh); Department of Psychiatry, University of Arkansas for Medical Sciences, Little Rock (Landes, Drummond, Kirchner, Painter, Singh); Rocky Mountain Mental Illness Research, Education, and Clinical Center, U.S. Department of Veterans Affairs (VA), Aurora, Colorado (Matarazzo, Clark, Gerard, Jankovsky, Brenner); Departments of Psychiatry and Physical Medicine and Rehabilitation, University of Colorado School of Medicine, Aurora (Matarazzo, Brenner); Veterans Integrated Service Network 19 Clinical Resource Hub, Salt Lake City (Clark); VA Puget Sound Health Care System, Seattle (Reger); VA Office of Mental Health and Suicide Prevention, Washington, D.C. (Eagan, Trafton, McCarthy, Katz)
| | - Bridget B Matarazzo
- Central Arkansas Veterans Healthcare System, Little Rock (Landes, Pitcock, Drummond, Smith, Kirchner, Raciborski, Painter, Townsend, Jegley, Singh); Department of Psychiatry, University of Arkansas for Medical Sciences, Little Rock (Landes, Drummond, Kirchner, Painter, Singh); Rocky Mountain Mental Illness Research, Education, and Clinical Center, U.S. Department of Veterans Affairs (VA), Aurora, Colorado (Matarazzo, Clark, Gerard, Jankovsky, Brenner); Departments of Psychiatry and Physical Medicine and Rehabilitation, University of Colorado School of Medicine, Aurora (Matarazzo, Brenner); Veterans Integrated Service Network 19 Clinical Resource Hub, Salt Lake City (Clark); VA Puget Sound Health Care System, Seattle (Reger); VA Office of Mental Health and Suicide Prevention, Washington, D.C. (Eagan, Trafton, McCarthy, Katz)
| | - Jeffery A Pitcock
- Central Arkansas Veterans Healthcare System, Little Rock (Landes, Pitcock, Drummond, Smith, Kirchner, Raciborski, Painter, Townsend, Jegley, Singh); Department of Psychiatry, University of Arkansas for Medical Sciences, Little Rock (Landes, Drummond, Kirchner, Painter, Singh); Rocky Mountain Mental Illness Research, Education, and Clinical Center, U.S. Department of Veterans Affairs (VA), Aurora, Colorado (Matarazzo, Clark, Gerard, Jankovsky, Brenner); Departments of Psychiatry and Physical Medicine and Rehabilitation, University of Colorado School of Medicine, Aurora (Matarazzo, Brenner); Veterans Integrated Service Network 19 Clinical Resource Hub, Salt Lake City (Clark); VA Puget Sound Health Care System, Seattle (Reger); VA Office of Mental Health and Suicide Prevention, Washington, D.C. (Eagan, Trafton, McCarthy, Katz)
| | - Karen L Drummond
- Central Arkansas Veterans Healthcare System, Little Rock (Landes, Pitcock, Drummond, Smith, Kirchner, Raciborski, Painter, Townsend, Jegley, Singh); Department of Psychiatry, University of Arkansas for Medical Sciences, Little Rock (Landes, Drummond, Kirchner, Painter, Singh); Rocky Mountain Mental Illness Research, Education, and Clinical Center, U.S. Department of Veterans Affairs (VA), Aurora, Colorado (Matarazzo, Clark, Gerard, Jankovsky, Brenner); Departments of Psychiatry and Physical Medicine and Rehabilitation, University of Colorado School of Medicine, Aurora (Matarazzo, Brenner); Veterans Integrated Service Network 19 Clinical Resource Hub, Salt Lake City (Clark); VA Puget Sound Health Care System, Seattle (Reger); VA Office of Mental Health and Suicide Prevention, Washington, D.C. (Eagan, Trafton, McCarthy, Katz)
| | - Brandy N Smith
- Central Arkansas Veterans Healthcare System, Little Rock (Landes, Pitcock, Drummond, Smith, Kirchner, Raciborski, Painter, Townsend, Jegley, Singh); Department of Psychiatry, University of Arkansas for Medical Sciences, Little Rock (Landes, Drummond, Kirchner, Painter, Singh); Rocky Mountain Mental Illness Research, Education, and Clinical Center, U.S. Department of Veterans Affairs (VA), Aurora, Colorado (Matarazzo, Clark, Gerard, Jankovsky, Brenner); Departments of Psychiatry and Physical Medicine and Rehabilitation, University of Colorado School of Medicine, Aurora (Matarazzo, Brenner); Veterans Integrated Service Network 19 Clinical Resource Hub, Salt Lake City (Clark); VA Puget Sound Health Care System, Seattle (Reger); VA Office of Mental Health and Suicide Prevention, Washington, D.C. (Eagan, Trafton, McCarthy, Katz)
| | - JoAnn E Kirchner
- Central Arkansas Veterans Healthcare System, Little Rock (Landes, Pitcock, Drummond, Smith, Kirchner, Raciborski, Painter, Townsend, Jegley, Singh); Department of Psychiatry, University of Arkansas for Medical Sciences, Little Rock (Landes, Drummond, Kirchner, Painter, Singh); Rocky Mountain Mental Illness Research, Education, and Clinical Center, U.S. Department of Veterans Affairs (VA), Aurora, Colorado (Matarazzo, Clark, Gerard, Jankovsky, Brenner); Departments of Psychiatry and Physical Medicine and Rehabilitation, University of Colorado School of Medicine, Aurora (Matarazzo, Brenner); Veterans Integrated Service Network 19 Clinical Resource Hub, Salt Lake City (Clark); VA Puget Sound Health Care System, Seattle (Reger); VA Office of Mental Health and Suicide Prevention, Washington, D.C. (Eagan, Trafton, McCarthy, Katz)
| | - Kaily A Clark
- Central Arkansas Veterans Healthcare System, Little Rock (Landes, Pitcock, Drummond, Smith, Kirchner, Raciborski, Painter, Townsend, Jegley, Singh); Department of Psychiatry, University of Arkansas for Medical Sciences, Little Rock (Landes, Drummond, Kirchner, Painter, Singh); Rocky Mountain Mental Illness Research, Education, and Clinical Center, U.S. Department of Veterans Affairs (VA), Aurora, Colorado (Matarazzo, Clark, Gerard, Jankovsky, Brenner); Departments of Psychiatry and Physical Medicine and Rehabilitation, University of Colorado School of Medicine, Aurora (Matarazzo, Brenner); Veterans Integrated Service Network 19 Clinical Resource Hub, Salt Lake City (Clark); VA Puget Sound Health Care System, Seattle (Reger); VA Office of Mental Health and Suicide Prevention, Washington, D.C. (Eagan, Trafton, McCarthy, Katz)
| | - Georgia R Gerard
- Central Arkansas Veterans Healthcare System, Little Rock (Landes, Pitcock, Drummond, Smith, Kirchner, Raciborski, Painter, Townsend, Jegley, Singh); Department of Psychiatry, University of Arkansas for Medical Sciences, Little Rock (Landes, Drummond, Kirchner, Painter, Singh); Rocky Mountain Mental Illness Research, Education, and Clinical Center, U.S. Department of Veterans Affairs (VA), Aurora, Colorado (Matarazzo, Clark, Gerard, Jankovsky, Brenner); Departments of Psychiatry and Physical Medicine and Rehabilitation, University of Colorado School of Medicine, Aurora (Matarazzo, Brenner); Veterans Integrated Service Network 19 Clinical Resource Hub, Salt Lake City (Clark); VA Puget Sound Health Care System, Seattle (Reger); VA Office of Mental Health and Suicide Prevention, Washington, D.C. (Eagan, Trafton, McCarthy, Katz)
| | - Molly C Jankovsky
- Central Arkansas Veterans Healthcare System, Little Rock (Landes, Pitcock, Drummond, Smith, Kirchner, Raciborski, Painter, Townsend, Jegley, Singh); Department of Psychiatry, University of Arkansas for Medical Sciences, Little Rock (Landes, Drummond, Kirchner, Painter, Singh); Rocky Mountain Mental Illness Research, Education, and Clinical Center, U.S. Department of Veterans Affairs (VA), Aurora, Colorado (Matarazzo, Clark, Gerard, Jankovsky, Brenner); Departments of Psychiatry and Physical Medicine and Rehabilitation, University of Colorado School of Medicine, Aurora (Matarazzo, Brenner); Veterans Integrated Service Network 19 Clinical Resource Hub, Salt Lake City (Clark); VA Puget Sound Health Care System, Seattle (Reger); VA Office of Mental Health and Suicide Prevention, Washington, D.C. (Eagan, Trafton, McCarthy, Katz)
| | - Lisa A Brenner
- Central Arkansas Veterans Healthcare System, Little Rock (Landes, Pitcock, Drummond, Smith, Kirchner, Raciborski, Painter, Townsend, Jegley, Singh); Department of Psychiatry, University of Arkansas for Medical Sciences, Little Rock (Landes, Drummond, Kirchner, Painter, Singh); Rocky Mountain Mental Illness Research, Education, and Clinical Center, U.S. Department of Veterans Affairs (VA), Aurora, Colorado (Matarazzo, Clark, Gerard, Jankovsky, Brenner); Departments of Psychiatry and Physical Medicine and Rehabilitation, University of Colorado School of Medicine, Aurora (Matarazzo, Brenner); Veterans Integrated Service Network 19 Clinical Resource Hub, Salt Lake City (Clark); VA Puget Sound Health Care System, Seattle (Reger); VA Office of Mental Health and Suicide Prevention, Washington, D.C. (Eagan, Trafton, McCarthy, Katz)
| | - Mark A Reger
- Central Arkansas Veterans Healthcare System, Little Rock (Landes, Pitcock, Drummond, Smith, Kirchner, Raciborski, Painter, Townsend, Jegley, Singh); Department of Psychiatry, University of Arkansas for Medical Sciences, Little Rock (Landes, Drummond, Kirchner, Painter, Singh); Rocky Mountain Mental Illness Research, Education, and Clinical Center, U.S. Department of Veterans Affairs (VA), Aurora, Colorado (Matarazzo, Clark, Gerard, Jankovsky, Brenner); Departments of Psychiatry and Physical Medicine and Rehabilitation, University of Colorado School of Medicine, Aurora (Matarazzo, Brenner); Veterans Integrated Service Network 19 Clinical Resource Hub, Salt Lake City (Clark); VA Puget Sound Health Care System, Seattle (Reger); VA Office of Mental Health and Suicide Prevention, Washington, D.C. (Eagan, Trafton, McCarthy, Katz)
| | - Aaron E Eagan
- Central Arkansas Veterans Healthcare System, Little Rock (Landes, Pitcock, Drummond, Smith, Kirchner, Raciborski, Painter, Townsend, Jegley, Singh); Department of Psychiatry, University of Arkansas for Medical Sciences, Little Rock (Landes, Drummond, Kirchner, Painter, Singh); Rocky Mountain Mental Illness Research, Education, and Clinical Center, U.S. Department of Veterans Affairs (VA), Aurora, Colorado (Matarazzo, Clark, Gerard, Jankovsky, Brenner); Departments of Psychiatry and Physical Medicine and Rehabilitation, University of Colorado School of Medicine, Aurora (Matarazzo, Brenner); Veterans Integrated Service Network 19 Clinical Resource Hub, Salt Lake City (Clark); VA Puget Sound Health Care System, Seattle (Reger); VA Office of Mental Health and Suicide Prevention, Washington, D.C. (Eagan, Trafton, McCarthy, Katz)
| | - Rebecca Raciborski
- Central Arkansas Veterans Healthcare System, Little Rock (Landes, Pitcock, Drummond, Smith, Kirchner, Raciborski, Painter, Townsend, Jegley, Singh); Department of Psychiatry, University of Arkansas for Medical Sciences, Little Rock (Landes, Drummond, Kirchner, Painter, Singh); Rocky Mountain Mental Illness Research, Education, and Clinical Center, U.S. Department of Veterans Affairs (VA), Aurora, Colorado (Matarazzo, Clark, Gerard, Jankovsky, Brenner); Departments of Psychiatry and Physical Medicine and Rehabilitation, University of Colorado School of Medicine, Aurora (Matarazzo, Brenner); Veterans Integrated Service Network 19 Clinical Resource Hub, Salt Lake City (Clark); VA Puget Sound Health Care System, Seattle (Reger); VA Office of Mental Health and Suicide Prevention, Washington, D.C. (Eagan, Trafton, McCarthy, Katz)
| | - Jacob Painter
- Central Arkansas Veterans Healthcare System, Little Rock (Landes, Pitcock, Drummond, Smith, Kirchner, Raciborski, Painter, Townsend, Jegley, Singh); Department of Psychiatry, University of Arkansas for Medical Sciences, Little Rock (Landes, Drummond, Kirchner, Painter, Singh); Rocky Mountain Mental Illness Research, Education, and Clinical Center, U.S. Department of Veterans Affairs (VA), Aurora, Colorado (Matarazzo, Clark, Gerard, Jankovsky, Brenner); Departments of Psychiatry and Physical Medicine and Rehabilitation, University of Colorado School of Medicine, Aurora (Matarazzo, Brenner); Veterans Integrated Service Network 19 Clinical Resource Hub, Salt Lake City (Clark); VA Puget Sound Health Care System, Seattle (Reger); VA Office of Mental Health and Suicide Prevention, Washington, D.C. (Eagan, Trafton, McCarthy, Katz)
| | - James C Townsend
- Central Arkansas Veterans Healthcare System, Little Rock (Landes, Pitcock, Drummond, Smith, Kirchner, Raciborski, Painter, Townsend, Jegley, Singh); Department of Psychiatry, University of Arkansas for Medical Sciences, Little Rock (Landes, Drummond, Kirchner, Painter, Singh); Rocky Mountain Mental Illness Research, Education, and Clinical Center, U.S. Department of Veterans Affairs (VA), Aurora, Colorado (Matarazzo, Clark, Gerard, Jankovsky, Brenner); Departments of Psychiatry and Physical Medicine and Rehabilitation, University of Colorado School of Medicine, Aurora (Matarazzo, Brenner); Veterans Integrated Service Network 19 Clinical Resource Hub, Salt Lake City (Clark); VA Puget Sound Health Care System, Seattle (Reger); VA Office of Mental Health and Suicide Prevention, Washington, D.C. (Eagan, Trafton, McCarthy, Katz)
| | - Susan M Jegley
- Central Arkansas Veterans Healthcare System, Little Rock (Landes, Pitcock, Drummond, Smith, Kirchner, Raciborski, Painter, Townsend, Jegley, Singh); Department of Psychiatry, University of Arkansas for Medical Sciences, Little Rock (Landes, Drummond, Kirchner, Painter, Singh); Rocky Mountain Mental Illness Research, Education, and Clinical Center, U.S. Department of Veterans Affairs (VA), Aurora, Colorado (Matarazzo, Clark, Gerard, Jankovsky, Brenner); Departments of Psychiatry and Physical Medicine and Rehabilitation, University of Colorado School of Medicine, Aurora (Matarazzo, Brenner); Veterans Integrated Service Network 19 Clinical Resource Hub, Salt Lake City (Clark); VA Puget Sound Health Care System, Seattle (Reger); VA Office of Mental Health and Suicide Prevention, Washington, D.C. (Eagan, Trafton, McCarthy, Katz)
| | - Rajinder Sonia Singh
- Central Arkansas Veterans Healthcare System, Little Rock (Landes, Pitcock, Drummond, Smith, Kirchner, Raciborski, Painter, Townsend, Jegley, Singh); Department of Psychiatry, University of Arkansas for Medical Sciences, Little Rock (Landes, Drummond, Kirchner, Painter, Singh); Rocky Mountain Mental Illness Research, Education, and Clinical Center, U.S. Department of Veterans Affairs (VA), Aurora, Colorado (Matarazzo, Clark, Gerard, Jankovsky, Brenner); Departments of Psychiatry and Physical Medicine and Rehabilitation, University of Colorado School of Medicine, Aurora (Matarazzo, Brenner); Veterans Integrated Service Network 19 Clinical Resource Hub, Salt Lake City (Clark); VA Puget Sound Health Care System, Seattle (Reger); VA Office of Mental Health and Suicide Prevention, Washington, D.C. (Eagan, Trafton, McCarthy, Katz)
| | - Jodie A Trafton
- Central Arkansas Veterans Healthcare System, Little Rock (Landes, Pitcock, Drummond, Smith, Kirchner, Raciborski, Painter, Townsend, Jegley, Singh); Department of Psychiatry, University of Arkansas for Medical Sciences, Little Rock (Landes, Drummond, Kirchner, Painter, Singh); Rocky Mountain Mental Illness Research, Education, and Clinical Center, U.S. Department of Veterans Affairs (VA), Aurora, Colorado (Matarazzo, Clark, Gerard, Jankovsky, Brenner); Departments of Psychiatry and Physical Medicine and Rehabilitation, University of Colorado School of Medicine, Aurora (Matarazzo, Brenner); Veterans Integrated Service Network 19 Clinical Resource Hub, Salt Lake City (Clark); VA Puget Sound Health Care System, Seattle (Reger); VA Office of Mental Health and Suicide Prevention, Washington, D.C. (Eagan, Trafton, McCarthy, Katz)
| | - John F McCarthy
- Central Arkansas Veterans Healthcare System, Little Rock (Landes, Pitcock, Drummond, Smith, Kirchner, Raciborski, Painter, Townsend, Jegley, Singh); Department of Psychiatry, University of Arkansas for Medical Sciences, Little Rock (Landes, Drummond, Kirchner, Painter, Singh); Rocky Mountain Mental Illness Research, Education, and Clinical Center, U.S. Department of Veterans Affairs (VA), Aurora, Colorado (Matarazzo, Clark, Gerard, Jankovsky, Brenner); Departments of Psychiatry and Physical Medicine and Rehabilitation, University of Colorado School of Medicine, Aurora (Matarazzo, Brenner); Veterans Integrated Service Network 19 Clinical Resource Hub, Salt Lake City (Clark); VA Puget Sound Health Care System, Seattle (Reger); VA Office of Mental Health and Suicide Prevention, Washington, D.C. (Eagan, Trafton, McCarthy, Katz)
| | - Ira R Katz
- Central Arkansas Veterans Healthcare System, Little Rock (Landes, Pitcock, Drummond, Smith, Kirchner, Raciborski, Painter, Townsend, Jegley, Singh); Department of Psychiatry, University of Arkansas for Medical Sciences, Little Rock (Landes, Drummond, Kirchner, Painter, Singh); Rocky Mountain Mental Illness Research, Education, and Clinical Center, U.S. Department of Veterans Affairs (VA), Aurora, Colorado (Matarazzo, Clark, Gerard, Jankovsky, Brenner); Departments of Psychiatry and Physical Medicine and Rehabilitation, University of Colorado School of Medicine, Aurora (Matarazzo, Brenner); Veterans Integrated Service Network 19 Clinical Resource Hub, Salt Lake City (Clark); VA Puget Sound Health Care System, Seattle (Reger); VA Office of Mental Health and Suicide Prevention, Washington, D.C. (Eagan, Trafton, McCarthy, Katz)
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Resnik J, Miller CJ, Roth CE, Burns K, Bovin MJ. A Systematic Review of the Department of Veterans Affairs Mental Health-Care Access Interventions for Veterans With PTSD. Mil Med 2024; 189:1303-1311. [PMID: 37837200 DOI: 10.1093/milmed/usad376] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Revised: 08/23/2023] [Accepted: 09/18/2023] [Indexed: 10/15/2023] Open
Abstract
INTRODUCTION Access to mental health care has been a priority area for the U.S. Department of Veterans Affairs (DVA) for decades. Access for veterans with PTSD is essential because untreated PTSD is associated with numerous adverse outcomes. Although interventions have been developed to improve access to DVA mental health care, the impact of these interventions on access for veterans with untreated PTSD has not been examined comprehensively, limiting guidance on appropriate implementation. MATERIALS AND METHODS We conducted a systematic review of PubMed and PTSDpubs between May 2019 and January 2022 to identify DVA access interventions for veterans with PTSD not engaged in DVA mental health care. We identified 17 interventions and 29 manuscripts reporting quantitative access outcomes. We categorized interventions into four major categories: Primary care mental health integration, other national initiatives, telemental health, and direct outreach. We evaluated five outcome domains: Binary attendance, number of sessions attended, wait time, number of patients seen, and care initiation. We assessed the risk of bias using the Cochrane Collaboration criteria. RESULTS Across articles, binary attendance generally improved, whereas the impact on the number of sessions attended was equivocal. Overall, the number of patients seen increased compared to control participants and retrospective data. The few articles that examined care initiation had mixed results. Only one article examined the impact on wait time. CONCLUSIONS Access interventions for veterans with PTSD demonstrated varied success across interventions and outcomes. The national initiatives-particularly primary care mental health integration -were successful across several outcomes; telemental health demonstrated promise in improving access; and the success of direct outreach varied across interventions. Confidence in these findings is tempered by potential bias among studies. Limited literature on how these interventions impact relevant preattendance barriers, along with incomplete data on how many perform nationally, suggests that additional work is needed to ensure that these interventions increase access for veterans with PTSD nationwide.
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Affiliation(s)
- Jack Resnik
- VA Boston Healthcare System, Center for Healthcare Organization and Implementation Research (CHOIR), Boston, MA 02130, USA
| | - Christopher J Miller
- VA Boston Healthcare System, Center for Healthcare Organization and Implementation Research (CHOIR), Boston, MA 02130, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA 02115, USA
| | - Clara E Roth
- VA Boston Healthcare System, National Center for PTSD (116B-2), Boston, MA 02130, USA
- Boston VA Research Institute (BVARI), Boston, MA 02130, USA
| | - Katharine Burns
- VA Boston Healthcare System, National Center for PTSD (116B-2), Boston, MA 02130, USA
- Emmanuel College, Boston, MA 02115, USA
| | - Michelle J Bovin
- VA Boston Healthcare System, National Center for PTSD (116B-2), Boston, MA 02130, USA
- Department of Psychiatry, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA
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Ritchie MJ, Smith JL, Kim B, Woodward EN, Kirchner JE. Building a sharable literature collection to advance the science and practice of implementation facilitation. FRONTIERS IN HEALTH SERVICES 2024; 4:1304694. [PMID: 38784706 PMCID: PMC11111980 DOI: 10.3389/frhs.2024.1304694] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Accepted: 04/30/2024] [Indexed: 05/25/2024]
Abstract
Background Implementation science seeks to produce generalizable knowledge on strategies that promote the adoption and sustained use of evidence-based innovations. Literature reviews on specific implementation strategies can help us understand how they are conceptualized and applied, synthesize findings, and identify knowledge gaps. Although rigorous literature reviews can advance scientific knowledge and facilitate theory development, they are time-consuming and costly to produce. Improving the efficiency of literature review processes and reducing redundancy of effort is especially important for this rapidly developing field. We sought to amass relevant literature on one increasingly used evidence-based strategy, implementation facilitation (IF), as a publicly available resource. Methods We conducted a rigorous systematic search of PubMed, CINAHL, and Web of Science citation databases for peer-reviewed, English-language articles with "facilitation" and a combination of other terms published from January 1996 to December 2021. We searched bibliographies of articles published from 1996 to 2015 and identified articles during the full text review that reported on the same study. Two authors screened 3,168 abstracts. After establishing inter-rater reliability, they individually conducted full-text review of 786 relevant articles. A multidisciplinary team of investigators provided recommendations for preparing and disseminating the literature collection. Findings The literature collection is comprised of 510 articles. It includes 277 empirical studies of IF and 77 other articles, including conceptual/theoretical articles, literature reviews, debate papers and descriptions of large-scale clinical initiatives. Over half of the articles were published between 2017 and 2021. The collection is publicly available as an Excel file and as an xml file that can be imported into reference management software. Conclusion We created a publicly accessible collection of literature about the application of IF to implement evidence-based innovations in healthcare. The comprehensiveness of this collection has the potential to maximize efficiency and minimize redundancy in scientific inquiry about this strategy. Scientists and practitioners can use the collection to more rapidly identify developments in the application of IF and to investigate a wide range of compelling questions on its use within and across different healthcare disciplines/settings, countries, and payer systems. We offer several examples of how this collection has already been used.
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Affiliation(s)
- Mona J. Ritchie
- VA Behavioral Health Quality Enhancement Research Initiative (QUERI), Central Arkansas Veterans Healthcare System, North Little Rock, AR, United States
- Department of Psychiatry, University of Arkansas for Medical Sciences, Little Rock, AR, United States
| | - Jeffrey L. Smith
- VA Behavioral Health Quality Enhancement Research Initiative (QUERI), Central Arkansas Veterans Healthcare System, North Little Rock, AR, United States
- Department of Psychiatry, University of Arkansas for Medical Sciences, Little Rock, AR, United States
| | - Bo Kim
- Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System, Boston, MA, United States
- Department of Psychiatry, Harvard Medical School, Boston, MA, United States
| | - Eva N. Woodward
- Department of Psychiatry, University of Arkansas for Medical Sciences, Little Rock, AR, United States
- VA Center for Mental Healthcare & Outcomes Research, Central Arkansas Veterans Healthcare System, North Little Rock, AR, United States
| | - JoAnn E. Kirchner
- VA Behavioral Health Quality Enhancement Research Initiative (QUERI), Central Arkansas Veterans Healthcare System, North Little Rock, AR, United States
- Department of Psychiatry, University of Arkansas for Medical Sciences, Little Rock, AR, United States
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Reilly S, Hobson-Merrett C, Gibbons B, Jones B, Richards D, Plappert H, Gibson J, Green M, Gask L, Huxley PJ, Druss BG, Planner CL. Collaborative care approaches for people with severe mental illness. Cochrane Database Syst Rev 2024; 5:CD009531. [PMID: 38712709 PMCID: PMC11075124 DOI: 10.1002/14651858.cd009531.pub3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
BACKGROUND Collaborative care for severe mental illness (SMI) is a community-based intervention that promotes interdisciplinary working across primary and secondary care. Collaborative care interventions aim to improve the physical and/or mental health care of individuals with SMI. This is an update of a 2013 Cochrane review, based on new searches of the literature, which includes an additional seven studies. OBJECTIVES To assess the effectiveness of collaborative care approaches in comparison with standard care (or other non-collaborative care interventions) for people with diagnoses of SMI who are living in the community. SEARCH METHODS We searched the Cochrane Schizophrenia Study-Based Register of Trials (10 February 2021). We searched the Cochrane Common Mental Disorders (CCMD) controlled trials register (all available years to 6 June 2016). Subsequent searches on Ovid MEDLINE, Embase and PsycINFO together with the Cochrane Central Register of Controlled Trials (with an overlap) were run on 17 December 2021. SELECTION CRITERIA Randomised controlled trials (RCTs) where interventions described as 'collaborative care' were compared with 'standard care' for adults (18+ years) living in the community with a diagnosis of SMI. SMI was defined as schizophrenia, other types of schizophrenia-like psychosis or bipolar affective disorder. The primary outcomes of interest were: quality of life, mental state and psychiatric admissions at 12 months follow-up. DATA COLLECTION AND ANALYSIS Pairs of authors independently extracted data. We assessed the quality and certainty of the evidence using RoB 2 (for the primary outcomes) and GRADE. We compared treatment effects between collaborative care and standard care. We divided outcomes into short-term (up to six months), medium-term (seven to 12 months) and long-term (over 12 months). For dichotomous data we calculated the risk ratio (RR) and for continuous data we calculated the standardised mean difference (SMD), with 95% confidence intervals (CIs). We used random-effects meta-analyses due to substantial levels of heterogeneity across trials. We created a summary of findings table using GRADEpro. MAIN RESULTS Eight RCTs (1165 participants) are included in this review. Two met the criteria for type A collaborative care (intervention comprised of the four core components). The remaining six met the criteria for type B (described as collaborative care by the trialists, but not comprised of the four core components). The composition and purpose of the interventions varied across studies. For most outcomes there was low- or very low-certainty evidence. We found three studies that assessed the quality of life of participants at 12 months. Quality of life was measured using the SF-12 and the WHOQOL-BREF and the mean endpoint mental health component scores were reported at 12 months. Very low-certainty evidence did not show a difference in quality of life (mental health domain) between collaborative care and standard care in the medium term (at 12 months) (SMD 0.03, 95% CI -0.26 to 0.32; 3 RCTs, 227 participants). Very low-certainty evidence did not show a difference in quality of life (physical health domain) between collaborative care and standard care in the medium term (at 12 months) (SMD 0.08, 95% CI -0.18 to 0.33; 3 RCTs, 237 participants). Furthermore, in the medium term (at 12 months) low-certainty evidence did not show a difference between collaborative care and standard care in mental state (binary) (RR 0.99, 95% CI 0.77 to 1.28; 1 RCT, 253 participants) or in the risk of being admitted to a psychiatric hospital at 12 months (RR 5.15, 95% CI 0.67 to 39.57; 1 RCT, 253 participants). One study indicated an improvement in disability (proxy for social functioning) at 12 months in the collaborative care arm compared to usual care (RR 1.38, 95% CI 0.97 to 1.95; 1 RCT, 253 participants); we deemed this low-certainty evidence. Personal recovery and satisfaction/experience of care outcomes were not reported in any of the included studies. The data from one study indicated that the collaborative care treatment was more expensive than standard care (mean difference (MD) international dollars (Int$) 493.00, 95% CI 345.41 to 640.59) in the short term. Another study found the collaborative care intervention to be slightly less expensive at three years. AUTHORS' CONCLUSIONS This review does not provide evidence to indicate that collaborative care is more effective than standard care in the medium term (at 12 months) in relation to our primary outcomes (quality of life, mental state and psychiatric admissions). The evidence would be improved by better reporting, higher-quality RCTs and the assessment of underlying mechanisms of collaborative care. We advise caution in utilising the information in this review to assess the effectiveness of collaborative care.
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Affiliation(s)
- Siobhan Reilly
- Centre for Applied Dementia Studies, Faculty of Health Studies, University of Bradford, Bradford, UK
- Wolfson Centre for Applied Health Research, Bradford, UK
- Division of Health Research, Lancaster University, Lancaster, UK
| | - Charley Hobson-Merrett
- Primary Care Plymouth, University of Plymouth, Plymouth, UK
- National Institute for Health Research Applied Research Collaboration South West Peninsula, Plymouth, UK
| | | | - Ben Jones
- College of Medicine and Health, University of Exeter, Exeter, UK
| | - Debra Richards
- Primary Care Plymouth, University of Plymouth, Plymouth, UK
| | - Humera Plappert
- Primary Care Clinical Sciences, University of Birmingham, Birmingham, UK
| | | | - Maria Green
- Pennine Health Care NHS Foundation Trust, Bury, UK
| | - Linda Gask
- Health Sciences Research Group, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK
| | - Peter J Huxley
- Centre for Mental Health and Society, School of Health Sciences, Bangor University, Bangor, UK
| | - Benjamin G Druss
- Department of Health Policy and Management, Emory University, Atlanta, USA
| | - Claire L Planner
- Centre for Primary Care and Health Services Research, University of Manchester, Manchester, UK
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Griauzde DH, Turner CD, Othman A, Oshman L, Gabison J, Arizaca-Dileo PK, Walford E, Henderson J, Beckius D, Lee JM, Carter EW, Dallas C, Herrera-Theut K, Richardson CR, Kullgren JT, Piatt G, Heisler M, Kraftson A. A Primary Care-Based Weight Navigation Program. JAMA Netw Open 2024; 7:e2412192. [PMID: 38771575 PMCID: PMC11109771 DOI: 10.1001/jamanetworkopen.2024.12192] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Accepted: 03/18/2024] [Indexed: 05/22/2024] Open
Abstract
Importance Evidence-based weight management treatments (WMTs) are underused; strategies are needed to increase WMT use and patients' weight loss. Objective To evaluate the association of a primary care-based weight navigation program (WNP) with WMT use and weight loss. Design, Setting, and Participants This cohort study comprised a retrospective evaluation of a quality improvement program conducted from October 1, 2020, to September 30, 2021. Data analysis was performed from August 2, 2022, to March 7, 2024. Adults with obesity and 1 or more weight-related condition from intervention and control sites in a large academic health system in the Midwestern US were propensity matched on sociodemographic and clinical factors. Exposure WNP, in which American Board of Obesity Medicine-certified primary care physicians offered weight-focused visits and guided patients' selection of preference-sensitive WMTs. Main Outcomes and Measures Primary outcomes were feasibility measures, including rates of referral to and engagement in the WNP. Secondary outcomes were mean weight loss, percentage of patients achieving 5% or more and 10% or more weight loss, referral to WMTs, and number of antiobesity medication prescriptions at 12 months. Results Of 264 patients, 181 (68.6%) were female and mean (SD) age was 49.5 (13.0) years; there were no significant differences in demographic characteristics between WNP patients (n = 132) and matched controls (n = 132). Of 1159 WNP-eligible patients, 219 (18.9%) were referred to the WNP and 132 (11.4%) completed a visit. In a difference-in-differences analysis, WNP patients lost 4.9 kg more than matched controls (95% CI, 2.11-7.76; P < .001), had 4.4% greater weight loss (95% CI, 2.2%-6.4%; P < .001), and were more likely to achieve 5% or more weight loss (odds ratio [OR], 2.90; 95% CI, 1.54-5.58); average marginal effects, 21.2%; 95% CI, 8.8%-33.6%) and 10% or more weight loss (OR, 7.19; 95% CI, 2.55-25.9; average marginal effects, 17.4%; 95% CI, 8.7%-26.2%). Patients in the WNP group were referred at higher rates to WMTs, including bariatric surgery (18.9% vs 9.1%; P = .02), a low-calorie meal replacement program (16.7% vs 3.8%; P < .001), and a Mediterranean-style diet and activity program (10.6% vs 1.5%; P = .002). There were no between-group differences in antiobesity medication prescribing. Conclusions and Relevance The findings of this cohort study suggest that WNP is feasible and associated with greater WMT use and weight loss than matched controls. The WNP warrants evaluation in a large-scale trial.
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Affiliation(s)
- Dina H. Griauzde
- Department of Internal Medicine, University of Michigan Medical School, Ann Arbor
- VA Ann Arbor Healthcare System, Ann Arbor, Michigan
- University of Michigan Institute for Healthcare Policy and Innovation, Ann Arbor
| | - Cassie D. Turner
- Department of Internal Medicine, University of Michigan Medical School, Ann Arbor
- VA Ann Arbor Healthcare System, Ann Arbor, Michigan
- Department of Learning Health Sciences, University of Michigan Medical School, Ann Arbor
| | - Amal Othman
- Department of Family Medicine, University of Michigan Medical School, Ann Arbor
| | - Lauren Oshman
- University of Michigan Institute for Healthcare Policy and Innovation, Ann Arbor
- Department of Family Medicine, University of Michigan Medical School, Ann Arbor
| | - Jonathan Gabison
- Department of Family Medicine, University of Michigan Medical School, Ann Arbor
| | | | - Eric Walford
- Department of Internal Medicine, University of Michigan Medical School, Ann Arbor
| | - James Henderson
- Department of Internal Medicine, University of Michigan Medical School, Ann Arbor
- University of Michigan Institute for Healthcare Policy and Innovation, Ann Arbor
| | - Deena Beckius
- University of Michigan Elizabeth Weiser Caswell Diabetes Institute, Ann Arbor
| | - Joyce M. Lee
- VA Ann Arbor Healthcare System, Ann Arbor, Michigan
- Department of Pediatrics, University of Michigan Medical School, Ann Arbor
| | - Eli W. Carter
- Department of Internal Medicine, University of Michigan Medical School, Ann Arbor
| | - Chris Dallas
- Department of Internal Medicine, University of Michigan Medical School, Ann Arbor
- University of Michigan Elizabeth Weiser Caswell Diabetes Institute, Ann Arbor
| | - Kathyrn Herrera-Theut
- Department of Internal Medicine, University of Michigan Medical School, Ann Arbor
- Department of Pediatrics, University of Michigan Medical School, Ann Arbor
| | - Caroline R. Richardson
- Department of Family Medicine, The Warren Alpert Medical School of Brown University and Care New England, Providence, Rhode Island
| | - Jeffrey T. Kullgren
- Department of Internal Medicine, University of Michigan Medical School, Ann Arbor
- VA Ann Arbor Healthcare System, Ann Arbor, Michigan
- University of Michigan Institute for Healthcare Policy and Innovation, Ann Arbor
- Department of Health Management and Policy, University of Michigan School of Public Health, Ann Arbor
| | - Gretchen Piatt
- Department of Learning Health Sciences, University of Michigan Medical School, Ann Arbor
- Department of Health Behavior and Health Education, University of Michigan School of Public Health, Ann Arbor
| | - Michele Heisler
- Department of Internal Medicine, University of Michigan Medical School, Ann Arbor
- VA Ann Arbor Healthcare System, Ann Arbor, Michigan
- University of Michigan Institute for Healthcare Policy and Innovation, Ann Arbor
| | - Andrew Kraftson
- Department of Internal Medicine, University of Michigan Medical School, Ann Arbor
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Nash P, Clark V, McConnell E, Mills W, Morgan R, Pimentel C, Ritchey K, Levy C, Snow AL, Hartmann C. Improving safety and preventing falls using an evidence-based, front-line staff huddling practice: protocol for a pragmatic trial to increase quality of care in State Veterans Homes. BMJ Open 2024; 14:e084011. [PMID: 38413157 PMCID: PMC10900326 DOI: 10.1136/bmjopen-2024-084011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/05/2024] [Accepted: 01/22/2024] [Indexed: 02/29/2024] Open
Abstract
INTRODUCTION Falls in nursing homes are a major cause for decreases in residents' quality of life and overall health. This study aims to reduce resident falls by implementing the LOCK Falls Programme, an evidence-based quality improvement intervention. The LOCK Falls Programme involves the entire front-line care team in (1) focusing on evidence of positive change, (2) collecting data through systematic observation and (3) facilitating communication and coordination of care through the practice of front-line staff huddles. METHODS AND ANALYSIS The study protocol describes a mixed-methods, 4-year hybrid (type 2) effectiveness-implementation study in State Veterans Homes in the USA. The study uses a pragmatic stepped-wedge randomised trial design and employs relational coordination theory and the Reach, Effectiveness, Adoption, Implementation and Maintenance framework to guide implementation and evaluation. A total of eight State Veterans Homes will participate and data will be collected over an 18-month period. Administrative data inclusive of all clinical assessments and Minimum Data Set assessments for Veterans with a State Veterans Home admission or stay during the study period will be collected (8480 residents total). The primary outcome is a resident having any fall. The primary analysis will be a partial intention-to-treat analysis using the rate of participants experiencing any fall. A staff survey (n=1200) and qualitative interviews with residents (n=80) and staff (n=400) will also be conducted. This research seeks to systematically address known barriers to nursing home quality improvement efforts associated with reducing falls. ETHICS AND DISSEMINATION This study is approved by the Central Institutional Review Board (#167059-11). All participants will be recruited voluntarily and will sign informed consent as required. Collection, assessment and managing of solicited and spontaneously reported adverse events, including required protocol alterations, will be communicated and approved directly with the Central Institutional Review Board, the data safety monitoring board and the Office of Research and Development. Study results will be disseminated through peer-reviewed publications and conference presentations at the Academy Health Annual Research Meeting, the Gerontological Society of America Annual Scientific Meeting and the American Geriatrics Society Annual Meeting. Key stakeholders will also help disseminate lessons learnt. TRIAL REGISTRATION NUMBER NCT05906095.
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Affiliation(s)
- Princess Nash
- Research and Development, Tuscaloosa VA Medical Center, Tuscaloosa, Alabama, USA
| | - Valerie Clark
- Center for Healthcare Organization and Implementation Research, VA Bedford Healthcare System, Bedford, Massachusetts, USA
| | - Eleanor McConnell
- Geriatric Research Education and Clinical Center, Durham VA Health Care System, Durham, North Carolina, USA
- School of Nursing, Duke University, Durham, North Carolina, USA
| | - Whitney Mills
- Center for Innovation in Long-Term Services and Supports, Providence VA Medical Center, Providence, Rhode Island, USA
- Department of Health Services Policy and Practice, Brown University, Providence, Rhode Island, USA
| | - Robert Morgan
- Center for Healthcare Organization and Implementation Research, VA Bedford Healthcare System, Bedford, Massachusetts, USA
- School of Public Health, The University of Texas Health Science Center, Houston, Texas, USA
| | - Camilla Pimentel
- New England Geriatric Research Education and Clinical Center, VA Bedford Healthcare System, Bedford, Massachusetts, USA
- Department of Public Health, Zuckerberg College of Health Sciences, University of Massachusetts Lowell, Lowell, Massachusetts, USA
| | - Katherine Ritchey
- US Department of Veterans Affairs, VA Puget Sound Healthcare System, Seattle, Washington, USA
- Department of Medicine, University of Washington, Seattle, Washington, USA
| | - Cari Levy
- Rocky Mountain Regional VA Medical Center, Aurora, Colorado, USA
- Division of Geriatric Medicine, University of Colorado School of Medicine, Aurora, Colorado, USA
| | - A Lynn Snow
- Research and Development, Tuscaloosa VA Medical Center, Tuscaloosa, Alabama, USA
- Department of Psychology, The University of Alabama, Tuscaloosa, Alabama, USA
| | - Christine Hartmann
- Center for Healthcare Organization and Implementation Research, VA Bedford Healthcare System, Bedford, Massachusetts, USA
- Department of Public Health, Zuckerberg College of Health Sciences, University of Massachusetts Lowell, Lowell, Massachusetts, USA
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8
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Kim B, Sullivan JL, Brown ME, Connolly SL, Spitzer EG, Bailey HM, Sippel LM, Weaver K, Miller CJ. Sustaining the collaborative chronic care model in outpatient mental health: a matrixed multiple case study. Implement Sci 2024; 19:16. [PMID: 38373979 PMCID: PMC10875770 DOI: 10.1186/s13012-024-01342-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Accepted: 01/21/2024] [Indexed: 02/21/2024] Open
Abstract
BACKGROUND Sustaining evidence-based practices (EBPs) is crucial to ensuring care quality and addressing health disparities. Approaches to identifying factors related to sustainability are critically needed. One such approach is Matrixed Multiple Case Study (MMCS), which identifies factors and their combinations that influence implementation. We applied MMCS to identify factors related to the sustainability of the evidence-based Collaborative Chronic Care Model (CCM) at nine Department of Veterans Affairs (VA) outpatient mental health clinics, 3-4 years after implementation support had concluded. METHODS We conducted a directed content analysis of 30 provider interviews, using 6 CCM elements and 4 Integrated Promoting Action on Research Implementation in Health Services (i-PARIHS) domains as codes. Based on CCM code summaries, we designated each site as high/medium/low sustainability. We used i-PARIHS code summaries to identify relevant factors for each site, the extent of their presence, and the type of influence they had on sustainability (enabling/neutral/hindering/unclear). We organized these data into a sortable matrix and assessed sustainability-related cross-site trends. RESULTS CCM sustainability status was distributed among the sites, with three sites each being high, medium, and low. Twenty-five factors were identified from the i-PARIHS code summaries, of which 3 exhibited strong trends by sustainability status (relevant i-PARIHS domain in square brackets): "Collaborativeness/Teamwork [Recipients]," "Staff/Leadership turnover [Recipients]," and "Having a consistent/strong internal facilitator [Facilitation]" during and after active implementation. At most high-sustainability sites only, (i) "Having a knowledgeable/helpful external facilitator [Facilitation]" was variably present and enabled sustainability when present, while (ii) "Clarity about what CCM comprises [Innovation]," "Interdisciplinary coordination [Recipients]," and "Adequate clinic space for CCM team members [Context]" were somewhat or less present with mixed influences on sustainability. CONCLUSIONS MMCS revealed that CCM sustainability in VA outpatient mental health clinics may be related most strongly to provider collaboration, knowledge retention during staff/leadership transitions, and availability of skilled internal facilitators. These findings have informed a subsequent CCM implementation trial that prospectively examines whether enhancing the above-mentioned factors within implementation facilitation improves sustainability. MMCS is a systematic approach to multi-site examination that can be used to investigate sustainability-related factors applicable to other EBPs and across multiple contexts.
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Affiliation(s)
- Bo Kim
- Center for Healthcare Organization and Implementation Research (CHOIR), VA Boston Healthcare System, 150 South Huntington Avenue, Boston, MA, 02130, USA.
- Harvard Medical School, 25 Shattuck Street, Boston, MA, 02115, USA.
| | - Jennifer L Sullivan
- Center of Innovation in Long Term Services and Supports (LTSS COIN), VA Providence Healthcare System, 385 Niagara Street, Providence, RI, 02907, USA
- Brown University School of Public Health, 121 South Main Street, Providence, RI, 02903, USA
| | - Madisen E Brown
- Center for Healthcare Organization and Implementation Research (CHOIR), VA Boston Healthcare System, 150 South Huntington Avenue, Boston, MA, 02130, USA
| | - Samantha L Connolly
- Center for Healthcare Organization and Implementation Research (CHOIR), VA Boston Healthcare System, 150 South Huntington Avenue, Boston, MA, 02130, USA
- Harvard Medical School, 25 Shattuck Street, Boston, MA, 02115, USA
| | - Elizabeth G Spitzer
- Center for Healthcare Organization and Implementation Research (CHOIR), VA Boston Healthcare System, 150 South Huntington Avenue, Boston, MA, 02130, USA
- VA Rocky Mountain Mental Illness Research, Education and Clinical Center (MIRECC), 1700 N Wheeling Street, Aurora, CO, 80045, USA
| | - Hannah M Bailey
- Center for Healthcare Organization and Implementation Research (CHOIR), VA Boston Healthcare System, 150 South Huntington Avenue, Boston, MA, 02130, USA
| | - Lauren M Sippel
- VA Northeast Program Evaluation Center, 950 Campbell Avenue, West Haven, CT, 06516, USA
- Geisel School of Medicine at Dartmouth, 1 Rope Ferry Road, Hanover, NH, 03755, USA
| | - Kendra Weaver
- VA Office of Mental Health and Suicide Prevention, 810 Vermont Avenue NW, Washington, DC, 20420, USA
| | - Christopher J Miller
- Center for Healthcare Organization and Implementation Research (CHOIR), VA Boston Healthcare System, 150 South Huntington Avenue, Boston, MA, 02130, USA
- Harvard Medical School, 25 Shattuck Street, Boston, MA, 02115, USA
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9
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Miller CJ, Sullivan JL, Connolly SL, Richardson EJ, Stolzmann KL, Brown M, Bailey HM, Weaver K, Sippel L, Kim B. Adaptation for sustainability in an implementation trial of team-based collaborative care. IMPLEMENTATION RESEARCH AND PRACTICE 2024; 5:26334895231226197. [PMID: 38322803 PMCID: PMC10807389 DOI: 10.1177/26334895231226197] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2024] Open
Abstract
Background Sustaining healthcare interventions once they have been implemented is a pivotal public health endeavor. Achieving sustainability requires context-sensitive adaptations to evidence-based practices (EBPs) or the implementation strategies used to ensure their adoption. For replicability of adaptations beyond the specific setting in question, the underlying logic needs to be clearly described, and adaptations themselves need to be plainly documented. The goal of this project was to describe the process by which implementation facilitation was adapted to improve the uptake of clinical care practices that are consistent with the collaborative chronic care model (CCM). Method Quantitative and qualitative data from a prior implementation trial found that CCM-consistent care practices were not fully sustained within outpatient general mental health teams that had received 1 year of implementation facilitation to support uptake. We undertook a multistep consensus process to identify adaptations to implementation facilitation based on these results, with the goal of enhancing the sustainability of CCM-based care in a subsequent trial. The logic for these adaptations, and the resulting adaptations themselves, were documented using two adaptation-oriented implementation frameworks (the iterative decision-making for evaluation of adaptations [IDEA] and the framework for reporting adaptations and modifications to evidence-based implementation strategies [FRAME-IS], respectively). Results Three adaptations emerged from this process and were documented using the FRAME-IS: (a) increasing the scope of implementation facilitation within the medical center, (b) having the internal facilitator take a greater role in the implementation process, and (c) shortening the implementation timeframe from 12 to 8 months, while increasing the intensity of facilitation support during that time. Conclusions EBP sustainability may require careful adaptation of EBPs or the implementation strategies used to get them into routine practice. Recently developed frameworks such as the IDEA and FRAME-IS may be used to guide decision-making and document resulting adaptations themselves. An ongoing funded study is investigating the utility of the resulting adaptations for improving healthcare.
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Affiliation(s)
- Christopher J. Miller
- Center for Healthcare Organization and Implementation Research (CHOIR), VA Boston Healthcare System, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Jennifer L. Sullivan
- Center of Innovation in Long Term Services and Supports (LTSS COIN), VA Providence Healthcare System Capt. Jonathan H. Harwood Jr. Center for Research, Providence, RI, USA
- Department of Health Services, Policy and Practice, School of Public Health, Brown University, Providence, RI, USA
| | - Samantha L. Connolly
- Center for Healthcare Organization and Implementation Research (CHOIR), VA Boston Healthcare System, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Eric J. Richardson
- Center for Healthcare Organization and Implementation Research (CHOIR), VA Boston Healthcare System, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Kelly L. Stolzmann
- Center for Healthcare Organization and Implementation Research (CHOIR), VA Boston Healthcare System, Boston, MA, USA
| | - Madisen Brown
- Center for Healthcare Organization and Implementation Research (CHOIR), VA Boston Healthcare System, Boston, MA, USA
| | - Hannah M. Bailey
- Center for Healthcare Organization and Implementation Research (CHOIR), VA Boston Healthcare System, Boston, MA, USA
| | - Kendra Weaver
- U.S. Department of Veterans Affairs Office of Mental Health and Suicide Prevention, Washington, DC, USA
| | - Lauren Sippel
- U.S. Department of Veterans Affairs Office of Mental Health and Suicide Prevention, Washington, DC, USA
- Department of Veterans Affairs Northeast Program Evaluation Center, West Haven, Connecticut, USA
- Department of Psychiatry, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire, USA
| | - Bo Kim
- Center for Healthcare Organization and Implementation Research (CHOIR), VA Boston Healthcare System, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
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Curran G, Mosley C, Gamble A, Painter J, Ounpraseuth S, Brewer NT, Teeter B, Smith M, Halladay J, Hughes T, Shepherd JG, Hastings T, Simpson K, Carpenter D. Addressing COVID-19 vaccine hesitancy in rural community pharmacies: a protocol for a stepped wedge randomized clinical trial. Implement Sci 2023; 18:72. [PMID: 38110979 PMCID: PMC10726603 DOI: 10.1186/s13012-023-01327-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Accepted: 11/27/2023] [Indexed: 12/20/2023] Open
Abstract
BACKGROUND Uptake of COVID-19 vaccines remains problematically low in the USA, especially in rural areas. COVID-19 vaccine hesitancy is associated with lower uptake, which translates to higher susceptibility to SARS-CoV-2 variants in communities where vaccination coverage is low. Because community pharmacists are among the most accessible and trusted health professionals in rural areas, this randomized clinical trial will examine implementation strategies to support rural pharmacists in delivering an adapted evidence-based intervention to reduce COVID-19 vaccine hesitancy. METHODS We will use an incomplete stepped wedge trial design in which we will randomize 30 rural pharmacies (unit of analysis) to determine the effectiveness and incremental cost-effectiveness of a standard implementation approach (consisting of online training that describes the vaccine hesitancy intervention, live webinar, and resource website) compared to adding on a virtual facilitation approach (provided by a trained facilitator in support of the delivery of the vaccine hesitancy counseling intervention by pharmacists). The intervention (ASORT) has been adapted from an evidence-based vaccine communication intervention for HPV vaccines through a partnership with rural pharmacies in a practice-based research network in seven southern US states. ASORT teaches pharmacists how to identify persons eligible for COVID-19 vaccination (including a booster), solicit and address vaccine concerns in a non-confrontational way, recommend the vaccine, and repeat the steps later if needed. The primary trial outcome is fidelity to the ASORT intervention, which will be determined through ratings of recordings of pharmacists delivering the intervention. The secondary outcome is the effectiveness of the intervention, determined by rates of patients who agree to be vaccinated after receiving the intervention. Other secondary outcomes include feasibility, acceptability, adoption, reach, and cost. Cost-effectiveness and budget impact analyses will be conducted to maximize the potential for future dissemination and sustainability. Mixed methods will provide triangulation, expansion, and explanation of quantitative findings. DISCUSSION This trial contributes to a growing evidence base on vaccine hesitancy interventions and virtual-only facilitation of evidenced-based practices in community health settings. The trial will provide the first estimate of the relative value of different implementation strategies in pharmacy settings. TRIAL REGISTRATION NCT05926544 (clinicaltrials.gov); 07/03/2023.
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Affiliation(s)
- Geoffrey Curran
- Center for Implementation Research, Department of Pharmacy Practice, University of Arkansas for Medical Sciences, Little Rock, AR, USA.
| | - Cynthia Mosley
- Center for Implementation Research, Department of Pharmacy Practice, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - Abigail Gamble
- Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC, USA
| | - Jacob Painter
- Pharmaceutical Evaluation and Policy, Department of Pharmacy Practice, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - Songthip Ounpraseuth
- Department of Biostatistics, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - Noel T Brewer
- Department of Health Behavior, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC, USA
| | - Ben Teeter
- Center for Implementation Research, Department of Pharmacy Practice, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - Megan Smith
- Center for Implementation Research, Department of Pharmacy Practice, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - Jacquie Halladay
- Department of Family Medicine, University of North Carolina, Chapel Hill, Chapel Hill, NC, USA
- The Cecil G. Sheps Center for Health Services Research, University of North Carolina, Chapel Hill, NC, USA
| | - Tamera Hughes
- Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC, USA
| | - J Greene Shepherd
- Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC, USA
| | - Tessa Hastings
- Department of Clinical Pharmacy and Outcomes Sciences, College of Pharmacy, University of South Carolina, Columbia, SC, USA
| | - Kit Simpson
- Department of Health Care Leadership and Management, College of Health Professions, Medical University of South Carolina, Charleston, SC, USA
- Department of Public Health Science, College of Medicine, Medical University of South Carolina, Charleston, SC, USA
| | - Delesha Carpenter
- Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC, USA
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Ruderman MA, Byers AL, Bauer MS, Stolzmann K, Miller CJ, Connolly SL, Kim B. One-Year All-Cause Mortality and Delivery of the Collaborative Chronic Care Model in General Mental Health Clinics. Psychiatr Serv 2023; 74:1077-1080. [PMID: 37016822 PMCID: PMC10543562 DOI: 10.1176/appi.ps.20220428] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/06/2023]
Abstract
OBJECTIVE This study aimed to determine whether the evidence-based collaborative chronic care model (CCM) is associated with reduced all-cause mortality among adult patients treated in general mental health clinics. METHODS Data came from a stepped-wedge, cluster-randomized CCM implementation trial across nine U.S. Department of Veterans Affairs medical centers. Survival analysis was used to estimate the relative effect of the treatment (N=5,570) compared with a control group (N=46,443) over 1 year. RESULTS After adjustment for site-level and individual-level acute care utilization factors, analyses indicated that patients treated with the CCM experienced a reduction in all-cause mortality relative to patients in the control cohort (hazard ratio=0.76, 95% CI=0.60-0.95). CONCLUSIONS This study is the first in which CCM has been shown to reduce all-cause mortality for patients treated in general mental health clinics. Care delivery models should be considered part of efforts to reduce the life expectancy gap between individuals with psychiatric conditions and those without such conditions.
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Affiliation(s)
- Michael A Ruderman
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, and San Francisco U.S. Department of Veterans Affairs (VA) Health Care, San Francisco (Ruderman, Byers); Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System, Boston (Bauer, Stolzmann, Miller, Connolly, Kim); Department of Psychiatry, Harvard Medical School, Boston (Bauer, Miller, Connolly, Kim)
| | - Amy L Byers
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, and San Francisco U.S. Department of Veterans Affairs (VA) Health Care, San Francisco (Ruderman, Byers); Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System, Boston (Bauer, Stolzmann, Miller, Connolly, Kim); Department of Psychiatry, Harvard Medical School, Boston (Bauer, Miller, Connolly, Kim)
| | - Mark S Bauer
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, and San Francisco U.S. Department of Veterans Affairs (VA) Health Care, San Francisco (Ruderman, Byers); Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System, Boston (Bauer, Stolzmann, Miller, Connolly, Kim); Department of Psychiatry, Harvard Medical School, Boston (Bauer, Miller, Connolly, Kim)
| | - Kelly Stolzmann
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, and San Francisco U.S. Department of Veterans Affairs (VA) Health Care, San Francisco (Ruderman, Byers); Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System, Boston (Bauer, Stolzmann, Miller, Connolly, Kim); Department of Psychiatry, Harvard Medical School, Boston (Bauer, Miller, Connolly, Kim)
| | - Christopher J Miller
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, and San Francisco U.S. Department of Veterans Affairs (VA) Health Care, San Francisco (Ruderman, Byers); Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System, Boston (Bauer, Stolzmann, Miller, Connolly, Kim); Department of Psychiatry, Harvard Medical School, Boston (Bauer, Miller, Connolly, Kim)
| | - Samantha L Connolly
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, and San Francisco U.S. Department of Veterans Affairs (VA) Health Care, San Francisco (Ruderman, Byers); Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System, Boston (Bauer, Stolzmann, Miller, Connolly, Kim); Department of Psychiatry, Harvard Medical School, Boston (Bauer, Miller, Connolly, Kim)
| | - Bo Kim
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, and San Francisco U.S. Department of Veterans Affairs (VA) Health Care, San Francisco (Ruderman, Byers); Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System, Boston (Bauer, Stolzmann, Miller, Connolly, Kim); Department of Psychiatry, Harvard Medical School, Boston (Bauer, Miller, Connolly, Kim)
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Kirchner HL, Rocha D, Linner RK, Wilimitis D, Walsh CG, Ripperger M, Lee H, Liu Z, Davis L, Hu Y, Chabris CF, Smoller JW. Association Between Psychiatric Polygenic Scores, Healthcare Utilization and Comorbidity Burden. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.09.29.23296345. [PMID: 37808705 PMCID: PMC10557834 DOI: 10.1101/2023.09.29.23296345] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/10/2023]
Abstract
Purpose To estimate the association of psychiatric polygenic scores with healthcare utilization and comorbidity burden. Methods Observational cohort study (N = 118,882) of adolescent and adult biobank participants with linked electronic health records (EHRs) from three diverse study sites; (Massachusetts General Brigham, Vanderbilt University Medical Center, Geisinger). Polygenic scores (PGS) were derived from the largest available GWAS of major depressive depression, bipolar disorder, and schizophrenia at the time of analysis. Negative binomial regression models were used to estimate the association between each psychiatric PGS and healthcare utilization and comorbidity burden. Healthcare utilization was measured as frequency of emergency department (ED), inpatient (IP), and outpatient (OP) visits. Comorbidity burden was defined by the Elixhauser Comorbidity Index and the Charlson Comorbidity Index. Results Participants had a median follow-up duration of 12 years in the EHR. Individuals in the top decile of polygenic score for major depressive disorder had significantly more ED visits (RR=1.22, 95% CI; 1.17, 1.29) compared to those the lowest decile. Increases were also observed with IP and comorbidity burden. Among those diagnosed with depression and in the highest decile of the PGS, there was an increase in all utilization types (ED: RR=1.56, 95% CI 1.41, 1.72; OP: RR=1.16, 95% CI 1.08, 1.24; IP: RR=1.23, 95% CI 1.12, 1.36) post-diagnosis. No clinically significant results were observed with bipolar and schizophrenia polygenic scores. Conclusions Polygenic score for depression is modestly associated with increased healthcare resource utilization and comorbidity burden, in the absence of diagnosis. Following a diagnosis of depression, the PGS was associated with further increases in healthcare utilization. These findings suggest that depression genetic risk is associated with utilization and burden of chronic disease in real-world settings.
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Affiliation(s)
| | - Daniel Rocha
- Phenomic Analytics and Clinical Data Core, Geisinger, Danville PA
| | - Richard K Linner
- Department of Bioethics and Decision Sciences, Geisinger, Danville PA
| | - Drew Wilimitis
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Vanderbilt University School of Medicine, Nashville, TN
| | - Colin G Walsh
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Vanderbilt University School of Medicine, Nashville, TN
- Department of Medicine, Vanderbilt University Medicine Center, Nashville, TN
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN
| | - Michael Ripperger
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Vanderbilt University School of Medicine, Nashville, TN
| | - Hyunjoon Lee
- Center for Precision Psychiatry, Department of Psychiatry, Massachusetts General Hospital, Boston, MA
| | - Zhaowen Liu
- Center for Precision Psychiatry, Department of Psychiatry, Massachusetts General Hospital, Boston, MA
| | - Lea Davis
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
| | - Yirui Hu
- Department of Population Health Sciences, Geisinger, Danville PA
| | | | - Jordan W Smoller
- Center for Precision Psychiatry, Department of Psychiatry, Massachusetts General Hospital, Boston, MA
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
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Hynes DM, Govier DJ, Niederhausen M, Tuepker A, Laliberte AZ, McCready H, Hickok A, Rowneki M, Waller D, Cordasco KM, Singer SJ, McDonald KM, Slatore CG, Thomas KC, Maciejewski M, Battaglia C, Perla L. Understanding care coordination for Veterans with complex care needs: protocol of a multiple-methods study to build evidence for an effectiveness and implementation study. FRONTIERS IN HEALTH SERVICES 2023; 3:1211577. [PMID: 37654810 PMCID: PMC10465329 DOI: 10.3389/frhs.2023.1211577] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Accepted: 08/01/2023] [Indexed: 09/02/2023]
Abstract
Background For patients with complex health and social needs, care coordination is crucial for improving their access to care, clinical outcomes, care experiences, and controlling their healthcare costs. However, evidence is inconsistent regarding the core elements of care coordination interventions, and lack of standardized processes for assessing patients' needs has made it challenging for providers to optimize care coordination based on patient needs and preferences. Further, ensuring providers have reliable and timely means of communicating about care plans, patients' full spectrum of needs, and transitions in care is important for overcoming potential care fragmentation. In the Veterans Health Administration (VA), several initiatives are underway to implement care coordination processes and services. In this paper, we describe our study underway in the VA aimed at building evidence for designing and implementing care coordination practices that enhance care integration and improve health and care outcomes for Veterans with complex care needs. Methods In a prospective observational multiple methods study, for Aim 1 we will use existing data to identify Veterans with complex care needs who have and have not received care coordination services. We will examine the relationship between receipt of care coordination services and their health outcomes. In Aim 2, we will adapt the Patient Perceptions of Integrated Veteran Care questionnaire to survey a sample of Veterans about their experiences regarding coordination, integration, and the extent to which their care needs are being met. For Aim 3, we will interview providers and care teams about their perceptions of the innovation attributes of current care coordination needs assessment tools and processes, including their improvement over other approaches (relative advantage), fit with current practices (compatibility and innovation fit), complexity, and ability to visualize how the steps proceed to impact the right care at the right time (observability). The provider interviews will inform design and deployment of a widescale provider survey. Discussion Taken together, our study will inform development of an enhanced care coordination intervention that seeks to improve care and outcomes for Veterans with complex care needs.
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Affiliation(s)
- Denise M. Hynes
- Center to Improve Veteran Involvement in Care (CIVIC), VA Portland Health Care System, Portland, OR, United States
- School of Nursing, Oregon Health & Science University, Portland, OR, United States
- College of Public Health and Human Sciences, Oregon State University, Corvallis, OR, United States
| | - Diana J. Govier
- Center to Improve Veteran Involvement in Care (CIVIC), VA Portland Health Care System, Portland, OR, United States
- School of Public Health, Oregon Health & Science University & Portland State University, Portland, OR, United States
| | - Meike Niederhausen
- Center to Improve Veteran Involvement in Care (CIVIC), VA Portland Health Care System, Portland, OR, United States
- School of Public Health, Oregon Health & Science University & Portland State University, Portland, OR, United States
| | - Anaïs Tuepker
- Center to Improve Veteran Involvement in Care (CIVIC), VA Portland Health Care System, Portland, OR, United States
- Department of Family Medicine, Oregon Health & Science University, Portland, OR, United States
| | - Avery Z. Laliberte
- Center to Improve Veteran Involvement in Care (CIVIC), VA Portland Health Care System, Portland, OR, United States
| | - Holly McCready
- Center to Improve Veteran Involvement in Care (CIVIC), VA Portland Health Care System, Portland, OR, United States
| | - Alex Hickok
- Center to Improve Veteran Involvement in Care (CIVIC), VA Portland Health Care System, Portland, OR, United States
| | - Mazhgan Rowneki
- Center to Improve Veteran Involvement in Care (CIVIC), VA Portland Health Care System, Portland, OR, United States
| | - Dylan Waller
- Center to Improve Veteran Involvement in Care (CIVIC), VA Portland Health Care System, Portland, OR, United States
| | - Kristina M. Cordasco
- Center for the Study of Healthcare Innovation, Implementation & Policy (CSHIIP), VA Greater Los Angeles Healthcare System, Los Angeles, CA, United States
- Department of Medicine, David Geffen School of Medicine at the University of California, Los Angeles, CA, United States
| | - Sara J. Singer
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, United States
| | - Kathryn M. McDonald
- Center for Diagnostic Excellence, Armstrong Institute for Patient Safety and Quality, Johns Hopkins School of Nursing, Baltimore, MD, United States
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, MD, United States
| | - Christopher G. Slatore
- Center to Improve Veteran Involvement in Care (CIVIC), VA Portland Health Care System, Portland, OR, United States
- Division of Pulmonary & Critical Care Medicine, Department of Medicine, Oregon Health & Science University, Portland, OR, United States
- Section of Pulmonary & Critical Care Medicine, VA Portland Health Care System, Portland, OR, United States
| | - Kathleen C. Thomas
- Division of Pharmaceutical Outcomes and Policy, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Matthew Maciejewski
- Center of Innovation to Accelerate Discovery and Practice Transformation (ADAPT), Durham Veterans Affairs Health Care System, Durham, NC, United States
- Department of Population Health Sciences & Division of General Internal Medicine, Department of Medicine, Duke University, Durham, NC, United States
| | - Catherine Battaglia
- Department of Veterans Affairs, Eastern Colorado Health Care System, Denver, CO, United States
- Department of Health Systems, Management & Policy, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
| | - Lisa Perla
- Rehabilitation Services, Veterans Affairs Central Office, Washington, DC, United States
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Tenzek KE, Lattimer TA, Heneveld K, Lapan E, Neurohr M, Gillis S. Mediated depictions of mental health, chronic care and literacy: a narrative analysis of Randall's mental health journey in the television series, This is Us. Front Psychiatry 2023; 14:1204973. [PMID: 37398586 PMCID: PMC10312097 DOI: 10.3389/fpsyt.2023.1204973] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Accepted: 05/17/2023] [Indexed: 07/04/2023] Open
Abstract
Introduction Mental health and delivery of care is a global issue, that was only magnified by COVID-19. Over the past 3 years, people's time spent watching television increased, while the way that mental health care was delivered changed. Audiences can gain insight into mental health issues through positive or negative mediated depictions on television. We argue that mental health is a chronic condition and the importance of literacy through different domains is critical for how the characters in media content and audience viewers make sense of mental health. Method The current study uses qualitative narrative analysis to examine the narrative probability and fidelity at the intersection of mental health depictions, the chronic care model, and different types of literacy in the award-winning series, This is Us. Results Findings reveal that Randall's experiences with mental health (N = 38 episodes) depict moments of narrative coherence and fidelity to varying degrees. We see Randall's experiences align most with the self-management support and community elements of the CCM, but the overall depiction is unbalanced. Randall's literacy level is high, but if inspected on a deeper level, analysis points to differing levels of health and mental health literacy, thus enabling and constraining positive and realistic portrayals of mental health. Discussion Implications for mental health as a chronic issue and care delivery through CCM are discussed along with the importance of different types of literacy for audience members who may be struggling with a mental health disorder or trying to navigate the health care system. We offer recommendations for using Randall's narrative as a teaching tool, integrating CCM into clinical visits to help guide delivery of care and understand literacy levels, and finally future work should continue this line of work from an Entertainment-Education perspective.
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Kilbourne AM, Geng E, Eshun-Wilson I, Sweeney S, Shelley D, Cohen DJ, Kirchner JE, Fernandez ME, Parchman ML. How does facilitation in healthcare work? Using mechanism mapping to illuminate the black box of a meta-implementation strategy. Implement Sci Commun 2023; 4:53. [PMID: 37194084 DOI: 10.1186/s43058-023-00435-1] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Accepted: 05/06/2023] [Indexed: 05/18/2023] Open
Abstract
BACKGROUND Healthcare facilitation, an implementation strategy designed to improve the uptake of effective clinical innovations in routine practice, has produced promising yet mixed results in randomized implementation trials and has not been fully researched across different contexts. OBJECTIVE Using mechanism mapping, which applies directed acyclic graphs that decompose an effect of interest into hypothesized causal steps and mechanisms, we propose a more concrete description of how healthcare facilitation works to inform its further study as a meta-implementation strategy. METHODS Using a modified Delphi consensus process, co-authors developed the mechanistic map based on a three-step process. First, they developed an initial logic model by collectively reviewing the literature and identifying the most relevant studies of healthcare facilitation components and mechanisms to date. Second, they applied the logic model to write vignettes describing how facilitation worked (or did not) based on recent empirical trials that were selected via consensus for inclusion and diversity in contextual settings (US, international sites). Finally, the mechanistic map was created based on the collective findings from the vignettes. FINDINGS Theory-based healthcare facilitation components informing the mechanistic map included staff engagement, role clarification, coalition-building through peer experiences and identifying champions, capacity-building through problem solving barriers, and organizational ownership of the implementation process. Across the vignettes, engagement of leaders and practitioners led to increased socialization of the facilitator's role in the organization. This in turn led to clarifying of roles and responsibilities among practitioners and identifying peer experiences led to increased coherence and sense-making of the value of adopting effective innovations. Increased trust develops across leadership and practitioners through expanded capacity in adoption of the effective innovation by identifying opportunities that mitigated barriers to practice change. Finally, these mechanisms led to eventual normalization and ownership of the effective innovation and healthcare facilitation process. IMPACT Mapping methodology provides a novel perspective of mechanisms of healthcare facilitation, notably how sensemaking, trust, and normalization contribute to quality improvement. This method may also enable more efficient and impactful hypothesis-testing and application of complex implementation strategies, with high relevance for lower-resourced settings, to inform effective innovation uptake.
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Affiliation(s)
- Amy M Kilbourne
- Health Services Research & Development, VA Office of Research and Development, US Department of Veterans Affairs and University of Michigan, 810 Vermont Ave, NW, Washington, D.C., 20420, USA.
| | - Elvin Geng
- Washington University at St. Louis, St. Louis, MO, USA
| | | | | | - Donna Shelley
- New York University School of Global Public Health, New York, New York, USA
| | | | - JoAnn E Kirchner
- Central Arkansas VA Healthcare System and University of Arkansas for Medical Sciences, North Little Rock, AR, USA
| | - Maria E Fernandez
- University of Texas Health Science Center at Houston, School of Public Health, Houston, TX, USA
| | - Michael L Parchman
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
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Kim B, Sullivan JL, Drummond KL, Connolly SL, Miller CJ, Weaver K, Bauer MS. Interdisciplinary behavioral health provider perceptions of implementing the Collaborative Chronic Care Model: an i-PARIHS-guided qualitative study. Implement Sci Commun 2023; 4:35. [PMID: 36998010 DOI: 10.1186/s43058-023-00407-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Accepted: 03/04/2023] [Indexed: 04/01/2023] Open
Abstract
BACKGROUND The evidence-based Collaborative Chronic Care Model (CCM), developed to help structure care for chronic health conditions, comprises six elements: work role redesign, patient self-management support, provider decision support, clinical information systems, linkages to community resources, and organizational/leadership support. As the CCM is increasingly implemented in real-world settings, there is heightened interest in understanding specific influences upon implementation. Therefore, guided by the Integrated Promoting Action on Research Implementation in Health Services (i-PARIHS) framework, we (i) identified innovation-, recipient-, context-, and facilitation-related influences on CCM implementation and (ii) assessed the influences' relationship to each CCM element's implementation. METHODS Using semi-structured interviews, we examined interdisciplinary behavioral health providers' experiences at nine VA medical centers that implemented the CCM. We used i-PARIHS constructs as a priori codes for directed content analysis, then analyzed the data for cross-coding by CCM element and i-PARIHS construct. RESULTS Participants (31 providers) perceived the CCM innovation as enabling comprehensive care but challenging to coordinate with existing structures/procedures. As recipients, participants recounted not always having the authority to design CCM-consistent care processes. They perceived local leadership support to be indispensable to implementation success and difficult to garner when CCM implementation distracted from other organizational priorities. They found implementation facilitation helpful for keeping implementation on track. We identified key themes at the intersection of i-PARIHS constructs and core CCM elements, including (i) the CCM being an innovation that offers a formal structure to stepping down care intensity for patients to encourage their self-management, (ii) recipients accessing their multidisciplinary colleagues' expertise for provider decision support, (iii) relationships with external services in the community (e.g., homelessness programs) being a helpful context for providing comprehensive care, and (iv) facilitators helping to redesign specific interdisciplinary team member roles. CONCLUSIONS Future CCM implementation would benefit from (i) facilitating strategic development of supportive maintenance plans for patients' self-management, (ii) collocating multidisciplinary staff (on-site or virtually) to enhance provider decision support, (iii) keeping information on available community resources up to date, and (iv) making clearer the explicit CCM-consistent care processes that work roles can be designed around. This work can inform concrete tailoring of implementation efforts to focus on the more challenging CCM elements, which is crucial to better account for multiple influences that vary across diverse care settings in which the CCM is being implemented.
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Affiliation(s)
- Bo Kim
- VA Boston Healthcare System, 150 South Huntington Avenue, Boston, MA, 02130, USA.
- Harvard Medical School, 25 Shattuck Street, Boston, MA, 02115, USA.
| | - Jennifer L Sullivan
- VA Providence Healthcare System, 385 Niagara Street, Providence, RI, 02907, USA
- Brown University School of Public Health, 121 South Main Street, Providence, RI, 02903, USA
| | - Karen L Drummond
- Central Arkansas Veterans Healthcare System, 4300 West 7th Street, Little Rock, AR, 72205, USA
- University of Arkansas for Medical Sciences, 4301 West Markham Street, Little Rock, AR, 72205, USA
| | - Samantha L Connolly
- VA Boston Healthcare System, 150 South Huntington Avenue, Boston, MA, 02130, USA
- Harvard Medical School, 25 Shattuck Street, Boston, MA, 02115, USA
| | - Christopher J Miller
- VA Boston Healthcare System, 150 South Huntington Avenue, Boston, MA, 02130, USA
- Harvard Medical School, 25 Shattuck Street, Boston, MA, 02115, USA
| | - Kendra Weaver
- VA Office of Mental Health and Suicide Prevention, 810 Vermont Avenue NW, Washington, DC, 20420, USA
| | - Mark S Bauer
- Harvard Medical School, 25 Shattuck Street, Boston, MA, 02115, USA
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Spitzer EG, Kaitz J, Fix GM, Harvey KLL, Stadnick NA, Sullivan JL, Williamson AK, Miller CJ. Developing Relational Coordination: A Qualitative Study of Outpatient Mental Health Teams. ADMINISTRATION AND POLICY IN MENTAL HEALTH AND MENTAL HEALTH SERVICES RESEARCH 2023:10.1007/s10488-023-01261-2. [PMID: 36892721 PMCID: PMC9996570 DOI: 10.1007/s10488-023-01261-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/21/2023] [Indexed: 03/10/2023]
Abstract
Previous studies have shown Relational Coordination improves team functioning in healthcare settings. The aim of this study was to examine the relational factors needed to support team functioning in outpatient mental health care teams with low staffing ratios. We interviewed interdisciplinary mental health teams that had achieved high team functioning despite low staffing ratios in U.S. Department of Veterans Affairs medical centers. We conducted qualitative interviews with 21 interdisciplinary team members across three teams within two medical centers. We used directed content analysis to code the transcripts with a priori codes based on the Relational Coordination dimensions, while also being attentive to emergent themes. We found that all seven dimensions of Relational Coordination were relevant to improved team functioning: frequent communication, timely communication, accurate communication, problem-solving communication, shared goals, shared knowledge, and mutual respect. Participants also described these dimensions as reciprocal processes that influenced each other. In conclusion, relational Coordination dimensions can play pivotal roles in improving team functioning both individually and in combination. Communication dimensions were a catalyst for developing relationship dimensions; once relationships were developed, there was a mutually reinforcing cycle between communication and relationship dimensions. Our results suggest that establishing high-functioning mental health care teams, even in low-staffed settings, requires encouraging frequent communication within teams. Moreover, attention should be given to ensuring appropriate representation of disciplines among leadership and defining roles of team members when teams are formed.
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Affiliation(s)
- Elizabeth G Spitzer
- VA Boston Healthcare System Center for Healthcare Organization and Implementation Research, Boston, Massachusetts and Department of Psychiatry, Harvard Medical School, Boston, Massachusetts, United States.
| | - Jenesse Kaitz
- VA Bedford Center for Healthcare Organization and Implementation Research, Bedford, Massachusetts, United States
| | - Gemmae M Fix
- VA Bedford Healthcare System Center for Healthcare Organization and Implementation Research and Boston University School of Public Health Boston, Bedford, Massachusetts, United States
| | - Kimberly L L Harvey
- VA Boston Healthcare System Center for Healthcare Organization and Implementation Research, Boston, Massachusetts and Department of Psychiatry, Harvard Medical School, Boston, Massachusetts, United States
| | - Nicole A Stadnick
- Department of Psychiatry, University of California, San Diego; UC San Diego, Altman Clinical and Translational Research, Institute, Dissemination and Implementation Science Center, La Jolla, California; and Child and Adolescent Services Research Center, San Diego, California, United States
| | - Jennifer L Sullivan
- A Medical Center, Center of Innovation in Long Term Services and Supports and Brown University School of Public Health, Providence, Providence, Rhode Island, United States
| | | | - Christopher J Miller
- VA Boston Healthcare System Center for Healthcare Organization and Implementation Research and Department of Psychiatry, Harvard Medical School, Bedford, Massachusetts, United States
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Colla CH, Lewis VA, Chang CH, Crawford M, Peck KA, Meara E. Changes in spending and quality after ACO contract participation for dually eligible beneficiaries with mental illness. HEALTHCARE (AMSTERDAM, NETHERLANDS) 2023; 11:100664. [PMID: 36543011 PMCID: PMC9898178 DOI: 10.1016/j.hjdsi.2022.100664] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Revised: 07/15/2022] [Accepted: 11/22/2022] [Indexed: 12/24/2022]
Abstract
BACKGROUND Fragmented care and misaligned payment across Medicare and Medicaid lower care quality for dually eligible beneficiaries with mental illness. Accountable care organizations aim to improve the quality and value of care. METHODS Using Medicare fee-for-service Part A and B claims data from 2009 to 2017 and a difference-in-differences design, we compared the spending and utilization of dually eligible beneficiaries with mental illness that were and were not attributed to Medicare ACO providers before and after ACO contract entry. RESULTS Dually eligible beneficiaries with mental illness (N = 5,157,533, 70% depression, 22% bipolar, 27% schizophrenia and other psychotic disorders) had average annual Medicare spending of $17,899. ACO contract participation was generally not associated with spending or utilization changes. However, ACO contract participation was associated with higher rates of follow-up visits after mental health hospitalization: 1.17 and 1.30 percentage points within 7 and 30 days of discharge, respectively (p < 0.001). ACO-attributed beneficiaries with schizophrenia, bipolar, or other psychotic disorders received more ambulatory visits (393.9 per 1000 person-years, p = 0.002), while ACO-attributed beneficiaries with depression experienced fewer emergency department visits (-29.5 per 1000 person-years, p = 0.003) after ACO participation. CONCLUSIONS Dually eligible beneficiaries served by Medicare ACOs did not have lower spending, hospitalizations, or readmissions compared with other beneficiaries. However, ACO participation was associated with timely follow-up after mental health hospitalization, as well as more ambulatory care and fewer ED visits for certain diagnostic groups. IMPLICATIONS ACOs that include dually eligible beneficiaries with mental illness should tailor their designs to address the distinct needs of this population.
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Affiliation(s)
- Carrie H Colla
- The Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth, Level 5, WTRB, 1 Medical Center Drive, Lebanon, NH, 03756, USA; Congressional Budget Office, Ford House Office Building, Fourth Floor, Second and D Streets, SW, Washington, DC, 20515-6925, USA.
| | - Valerie A Lewis
- Department of Health Policy and Management, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 170 Rosenau Hall, CB #7400, 135 Dauer Driver, Chapel Hill, NC, 27599, USA
| | - Chiang-Hua Chang
- Institute for Healthcare Policy and Innovation, University of Michigan, 2800 Plymouth Road North Campus Research Complex (NCRC), Building 16, Ann Arbor, MI, 48109, USA
| | - Maia Crawford
- The Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth, Level 5, WTRB, 1 Medical Center Drive, Lebanon, NH, 03756, USA
| | - Kristen A Peck
- Dartmouth Health, 1 Medical Center Dr, Lebanon, NH, 03756, USA
| | - Ellen Meara
- Department of Health Policy and Management, Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Boston, MA, 02115, USA
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Miller CJ, Kim B, Connolly SL, Spitzer EG, Brown M, Bailey HM, Weaver K, Sullivan JL. Sustainability of the Collaborative Chronic Care Model in Outpatient Mental Health Teams Three Years Post-Implementation: A Qualitative Analysis. ADMINISTRATION AND POLICY IN MENTAL HEALTH AND MENTAL HEALTH SERVICES RESEARCH 2023; 50:151-159. [PMID: 36329294 PMCID: PMC9633036 DOI: 10.1007/s10488-022-01231-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/12/2022] [Indexed: 11/06/2022]
Abstract
Our goal was to investigate the sustainability of care practices that are consistent with the collaborative chronic care model (CCM) in nine outpatient mental health teams located within US Department of Veterans Affairs (VA) medical centers, three to four years after the completion of CCM implementation. We conducted qualitative interviews (N = 30) with outpatient mental health staff from each of the nine teams. We based our directed content analysis on the six elements of the CCM. We found variable sustainability of CCM-based care processes across sites. Some care processes, such as delivery of evidence-based psychotherapies (EBPs) and use of measurement-based care (MBC) to guide clinic decision-making, were robustly maintained or even expanded within participating teams. In contrast, other care processes-which had in some cases been developed with considerable effort-had not been sustained. For example, care manager roles were diminished in scope or eliminated completely in response to workload pressures, frontline care needs, or the COVID-19 pandemic. Similarly, processes for engaging Veterans more fully in decision-making had generally been scaled back. Leadership support in the form of adequate team staffing and time to conduct team meetings were seen as crucial for sustaining CCM-consistent care. Given the potential impact of leadership turnover on sustainability in mental health, future efforts to implement CCM-based mental health care should strive to involve multiple leaders in implementation and sustainment efforts, lest one key departure undo years of implementation work. Our results also suggest that implementing CCM processes may best be conceptualized as a partnership across multiple levels of medical center leadership.
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Affiliation(s)
- Christopher J. Miller
- Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System, 150 S. Huntington Ave (152M), Boston, MA USA ,Department of Psychiatry, Harvard Medical School, 25 Shattuck St., Boston, MA USA
| | - Bo Kim
- Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System, 150 S. Huntington Ave (152M), Boston, MA USA ,Department of Psychiatry, Harvard Medical School, 25 Shattuck St., Boston, MA USA
| | - Samantha L. Connolly
- Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System, 150 S. Huntington Ave (152M), Boston, MA USA ,Department of Psychiatry, Harvard Medical School, 25 Shattuck St., Boston, MA USA
| | - Elizabeth G. Spitzer
- Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System, 150 S. Huntington Ave (152M), Boston, MA USA ,Department of Psychiatry, Harvard Medical School, 25 Shattuck St., Boston, MA USA
| | - Madisen Brown
- Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System, 150 S. Huntington Ave (152M), Boston, MA USA
| | - Hannah M. Bailey
- Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System, 150 S. Huntington Ave (152M), Boston, MA USA
| | - Kendra Weaver
- Department of Veterans Affairs Office of Mental Health & Suicide Prevention, 810 Vermont Ave NW, Washington, DC USA
| | - Jennifer L. Sullivan
- Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System, 150 S. Huntington Ave (152M), Boston, MA USA ,Department of Health Law, Policy and Management, Boston University School of Public Health, 715 Albany St, Talbot Building, Boston, MA USA
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Abstract
There has been an increasing emphasis on placing patients at the center of clinical care and health care research and, in particular, assessing outcomes and experiences from the patient's perspective. One of the most widely used patient-reported outcome instruments is the Veterans RAND 12-item Health Survey (VR-12). This article reviews the VR-12 development and its applications over the last 2 decades, including research and potential uses in clinical care.
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Wallis M, Craswell A, Marsden E, Taylor A. Establishing the Geriatric Emergency Department Intervention in Queensland emergency departments: a qualitative implementation study using the i-PARIHS model. BMC Health Serv Res 2022; 22:692. [PMID: 35606808 PMCID: PMC9128293 DOI: 10.1186/s12913-022-08081-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Accepted: 05/13/2022] [Indexed: 12/04/2022] Open
Abstract
BACKGROUND Frail older adults require specific, targeted care and expedited shared decision making in the emergency department (ED) to prevent poor outcomes and minimise time spent in this chaotic environment. The Geriatric Emergency Department Intervention (GEDI) model was developed to help limit these undesirable consequences. This qualitative study aimed to explore the ways in which two hospital implementation sites implemented the structures and processes of the GEDI model and to examine the ways in which the i-PARIHS (innovation-Promoting Action on Research Implementation in Health Services) framework influenced the implementation. METHODS Using the i-PARIHS approach to implementation, the GEDI model was disseminated into two hospitals using a detailed implementation toolkit, external and internal facilitators and a structured program of support. Following implementation, interviews were conducted with a range of staff involved in the implementation at both sites to explore the implementation process used. Transcribed interviews were analysed for themes and sub-themes. RESULTS There were 31 interviews with clinicians involved in the implementation, conducted across two hospitals, including interviews with the two external facilitators. Major themes identified included: (i) elements of the GEDI model adopted or (ii) adapted by implementation sites and (iii) factors that affected the implementation of the GEDI model. Both sites adopted the model of care and there was general support for the GEDI approach to the management of frail older people in the ED. Both sites adapted the structure of the GEDI team and the expertise of the team members to suit their needs and resources. Elements such as service focus, funding, staff development and service evaluation were initially adopted but adaptation occurred over time. Resourcing and cost shifting issues at the implementation sites and at the site providing the external facilitators negatively impacted the facilitation process. CONCLUSIONS The i-PARIHS framework provided a pragmatic approach to the implementation of the evidenced-based GEDI model. Passionate, driven clinicians ensured that successful implementation occurred despite unanticipated changes in context at both the implementation and host facilitator sites as well as the absence of sustained facilitation support.
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Affiliation(s)
- Marianne Wallis
- Faculty of Health, Southern Cross University, Southern Cross Drive, Bilinga, Queensland Australia
- Sunshine Coast Health Institute, Birtinya, Queensland Australia
| | - Alison Craswell
- School of Nursing, Midwifery and Paramedicine, University of Sunshine Coast, Sippy Downs, Queensland Australia
| | - Elizabeth Marsden
- Sunshine Coast Health Institute, Birtinya, Queensland Australia
- School of Nursing, Midwifery and Paramedicine, University of Sunshine Coast, Sippy Downs, Queensland Australia
| | - Andrea Taylor
- Sunshine Coast Health Institute, Birtinya, Queensland Australia
- School of Nursing, Midwifery and Paramedicine, University of Sunshine Coast, Sippy Downs, Queensland Australia
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22
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Kim B, Miller CJ, Ritchie MJ, Smith JL, Kirchner JE, Stolzmann K, Connolly SL, Drummond KL, Bauer MS. Time–motion analysis of external facilitation for implementing the Collaborative Chronic Care Model in general mental health clinics: Use of an interval-based data collection approach. IMPLEMENTATION RESEARCH AND PRACTICE 2022; 3:26334895221086275. [PMID: 37091094 PMCID: PMC9924237 DOI: 10.1177/26334895221086275] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Background: Facilitation is an effective strategy to implement evidence-based practices, often involving external facilitators (EFs) bringing content expertise to implementation sites. Estimating time spent on multifaceted EF activities is complex. Furthermore, collecting continuous time–motion data for facilitation tasks is challenging. However, organizations need this information to allocate implementation resources to sites. Thus, our objectives were to conduct a time–motion analysis of external facilitation, and compare continuous versus noncontinuous approaches to collecting time–motion data. Methods: We analyzed EF time–motion data from six VA mental health clinics implementing the evidence-based Collaborative Chronic Care Model (CCM). We documented EF activities during pre-implementation (4–6 weeks) and implementation (12 months) phases. We collected continuous data during the pre-implementation phase, followed by data collection over a 2-week period (henceforth, “a two-week interval”) at each of three time points (beginning/middle/end) during the implementation phase. As a validity check, we assessed how closely interval data represented continuous data collected throughout implementation for two of the sites. Results: EFs spent 21.8 ± 4.5 h/site during pre-implementation off-site, then 27.5 ± 4.6 h/site site-visiting to initiate implementation. Based on the 2-week interval data, EFs spent 2.5 ± 0.8, 1.4 ± 0.6, and 1.2 ± 0.6 h/week toward the implementation’s beginning, middle, and end, respectively. Prevalent activities were preparation/planning, process monitoring, program adaptation, problem identification, and problem-solving. Across all activities, 73.6% of EF time involved email, phone, or video communication. For the two continuous data sites, computed weekly time averages toward the implementation’s beginning, middle, and end differed from the interval data’s averages by 1.0, 0.1, and 0.2 h, respectively. Activities inconsistently captured in the interval data included irregular assessment, stakeholder engagement, and network development. Conclusions: Time–motion analysis of CCM implementation showed initial higher-intensity EF involvement that tapered. The 2-week interval data collection approach, if accounting for its potential underestimation of irregular activities, may be promising/efficient for implementation studies collecting time–motion data.
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Affiliation(s)
- Bo Kim
- Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Christopher J. Miller
- Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Mona J. Ritchie
- VA Behavioral Health Quality Enhancement Research Initiative (QUERI), Central Arkansas Veterans Healthcare System, North Little Rock, AR, USA
- Department of Psychiatry, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - Jeffrey L. Smith
- VA Behavioral Health Quality Enhancement Research Initiative (QUERI), Central Arkansas Veterans Healthcare System, North Little Rock, AR, USA
- Department of Psychiatry, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - JoAnn E. Kirchner
- VA Behavioral Health Quality Enhancement Research Initiative (QUERI), Central Arkansas Veterans Healthcare System, North Little Rock, AR, USA
- Department of Psychiatry, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - Kelly Stolzmann
- Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System, Boston, MA, USA
| | - Samantha L. Connolly
- Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Karen L. Drummond
- VA Behavioral Health Quality Enhancement Research Initiative (QUERI), Central Arkansas Veterans Healthcare System, North Little Rock, AR, USA
- Department of Psychiatry, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - Mark S. Bauer
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
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Stolzmann K, Lew RA, Miller CJ, Kim B, Wu H, Bauer MS. Does balancing site characteristics result in balanced population characteristics in a cluster-randomized controlled trial? HEALTH SERVICES AND OUTCOMES RESEARCH METHODOLOGY 2022. [DOI: 10.1007/s10742-022-00271-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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Das S, Wang J, Chen SY, Chen CE. Telemental Health Collaborative Care Medication Management: Implementation and Outcomes. Telemed J E Health 2021; 28:1035-1043. [PMID: 34939839 PMCID: PMC9293679 DOI: 10.1089/tmj.2021.0401] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Introduction: Access to quality mental health medication management (MM) in the United States is limited, even among those with employment-based health insurance. This implementation, feasibility, and outcome study sought to design and evaluate an evidence-based telemental health MM service using a collaborative care model (CoCM). Materials and Methods: CoCM MM was available to adult employees/dependents through their employer benefits, in addition to therapy. Outcomes included Patient Health Questionnaire-9 (PHQ-9) and the Generalized Anxiety Disorder-7 (GAD-7) collected at baseline and throughout participation. This analysis was not deemed to be human subjects research by the Western Institutional Review Board. Results: Over 17 months, 212 people enrolled and completed >2 assessments; the enrollees were 58.96% female with average age of 32.00 years (standard deviation [SD] = 7.38). In people with moderate to severe depression or anxiety, PHQ-9 and GAD-7 scores reduced by an average of 7.27 (SD = 4.80) and 6.71 (SD = 5.18) points after at least 12 ± 4 weeks in the program. At 24 ± 4 weeks, the PHQ-9 and GAD-7 reductions were on average 7.17 (SD = 5.00) and 6.03 (SD = 5.37), respectively. Approximately 65.88% of participants with either baseline depression or anxiety had a response on either the PHQ-9 or GAD-7 at 12 ± 4 weeks and 44.71% of participants experienced remission; at 24 ± 4 weeks, 56.41% had response and 41.03% experienced remission. Conclusions: An evidence-based CoCM telemedicine service within an employee behavioral health benefit is feasible and effective in reducing anxiety and depression symptoms when using measurement-based care. Widespread implementation of a benefit like this could expand access to evidence-based mental health MM.
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Affiliation(s)
- Smita Das
- Lyra Health, Burlingame, California, USA
| | - Jane Wang
- Internal Medicine Residency Program, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
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Paciocco S, Kothari A, Licskai CJ, Ferrone M, Sibbald SL. Evaluating the implementation of a chronic obstructive pulmonary disease management program using the Consolidated Framework for Implementation Research: a case study. BMC Health Serv Res 2021; 21:717. [PMID: 34289847 PMCID: PMC8293496 DOI: 10.1186/s12913-021-06636-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Accepted: 06/14/2021] [Indexed: 01/14/2023] Open
Abstract
BACKGROUND Chronic obstructive pulmonary disease (COPD) is a prevalent chronic disease that requires comprehensive approaches to manage; it accounts for a significant portion of Canada's annual healthcare spending. Interprofessional teams are effective at providing chronic disease management that meets the needs of patients. As part of an ongoing initiative, a COPD management program, the Best Care COPD program was implemented in a primary care setting. The objectives of this research were to determine site-specific factors facilitating or impeding the implementation of a COPD program in a new setting, while evaluating the implementation strategy used. METHODS A qualitative case study was conducted using interviews, focus groups, document analysis, and site visits. Data were deductively analyzed using the Consolidated Framework for Implementation Research (CFIR) to assess the impact of each of its constructs on Best Care COPD program implementation at this site. RESULTS Eleven CFIR constructs were determined to meaningfully affect implementation. Five were identified as the most influential in the implementation process. Cosmopolitanism (partnerships with other organizations), networks and communication (amongst program providers), engaging (key individuals to participate in program implementation), design quality and packaging (of the program), and reflecting and evaluating (throughout the implementation process). A peer-to-peer implementation strategy included training of registered respiratory therapists (RRT) as certified respiratory educators and the establishment of a communication network among RRTs to discuss experiences, collectively solve problems, and connect with the program lead. CONCLUSIONS This study provides a practical example of the various factors that facilitated the implementation of the Best Care COPD program. It also demonstrates the potential of using a peer-to-peer implementation strategy. Focusing on these factors will be useful for informing the continued spread and success of the Best Care COPD program and future implementation of other chronic care programs.
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Affiliation(s)
- Stefan Paciocco
- Health and Rehabilitation Sciences, Western University, London, Canada
| | - Anita Kothari
- School of Health Studies, Faculty of Health Sciences, Western University, London, Canada
| | - Christopher J Licskai
- Department of Family Medicine, Schulich School of Medicine and Dentistry, Western University, London, Canada
| | | | - Shannon L Sibbald
- School of Health Studies, Faculty of Health Sciences, Department of Family Medicine, Schulich School of Medicine and Dentistry, The Schulich Interfaculty Program in Public Health, Schulich School of Medicine and Dentistry, Western University, London, Canada.
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Promoting high-functioning mental health treatment teams in the context of low staffing ratios. Health Care Manage Rev 2021; 47:12-20. [PMID: 34038917 DOI: 10.1097/hmr.0000000000000312] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
BACKGROUND Many previous studies of health care teamwork have taken place in clinical teams with high staffing ratios (i.e., high ratios of staff to patients). PURPOSE The aim of this study was to identify clinicians' viewpoints of foundational resources necessary to support good team functioning in the context of low staffing ratios. METHODOLOGY We used administrative data, validated with local mental health chiefs, to identify mental health teams that had achieved high team functioning despite low staffing ratios in U.S. Department of Veterans Affairs medical centers. Guided by a recently developed model of team effectiveness, the Team Effectiveness Pyramid, we conducted qualitative interviews with 21 team members across three teams within two medical centers. Interview questions focused on the resources needed to support good team functioning despite low staffing ratios. We used directed content analysis to analyze results. RESULTS We found there were several domains of relevant resources: material, staffing, temporal, organizational, and psychological. These represent an expansion of the domains originally included in the Team Effectiveness Pyramid. CONCLUSIONS Within the five domains, we identified key tensions to be addressed when forming teams, including the balances between providing care for new versus established patients, emphasizing shared caseloads within the team versus matching patients to clinicians based on individual expertise, and establishing reporting structures by clinical discipline versus team membership. PRACTICE IMPLICATIONS Establishing high-functioning health care teams in the context of low staffing ratios requires attention to key resource domains and fundamental trade-offs in how teams are structured.
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27
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Domlyn AM. Implementation stages in practice: A review of behavioral health innovation within hospitals. Health Serv Manage Res 2021; 35:92-109. [PMID: 34039075 DOI: 10.1177/09514848211010271] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Behavioral health influences patient health outcomes and healthcare utilization rates. Hospitals are promising settings for appropriate identification, treatment, and referral of behavioral health issues and may affect hospital admission rates and healthcare costs. Implementation frameworks are designed to aid successful adoption and scaling of health innovations. One type - process models - present staged frameworks for rolling out an innovation into routine practice. Process models are appealing for their pragmatism but are criticized for oversimplifying the complexity of implementation. This review investigates the empirical evidence for process models' utility in hospitals, chosen for their uniquely complex structures, by determining whether their use impacts implementation outcomes. Using systematic search and selection criteria across six databases, ten peer-reviewed studies were identified. Each applied a process model for implementing behavioral health innovations within hospital systems. Studies were coded by type of stage framework and reported implementation outcomes. Studies reported mostly favorable or mixed outcomes. No one framework prevailed in use nor evidence. Due to the paucity of published literature and reported data, there is limited evidence that process model application propels implementation outcomes in hospital settings. Furthering the science requires creating and utilizing systematic guidelines to employ process models, measure and report implementation stage transition, and measure and report implementation outcomes. Management and practitioners can include such data collection in standard process evaluations of hospital implementation and scale-up activities, or adopt complexity-informed approaches that lack the simplicity of process models but may be more realistic for complex settings.
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Affiliation(s)
- Ariel M Domlyn
- Department of Psychology 2629University of South Carolina, Columbia, SC, USA
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28
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Bauer MS, Stolzmann K, Miller CJ, Kim B, Connolly SL, Lew R. Implementing the Collaborative Chronic Care Model in Mental Health Clinics: Achieving and Sustaining Clinical Effects. Psychiatr Serv 2021; 72:586-589. [PMID: 33730885 DOI: 10.1176/appi.ps.202000117] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
OBJECTIVE Collaborative chronic care models (CCMs) were established with implementation support in nine mental health clinics. This study sought to determine whether their clinical impact was maintained after implementation support ceased. METHODS Posttrial data were analyzed from a randomized stepped-wedge CCM implementation trial in general mental health clinics in nine Department of Veterans Affairs medical centers. Sites received 1 year of implementation support, which was associated with reduced mental health hospitalization rates compared with non-CCM clinics in the same medical centers. Hospitalization rates for the year after implementation support were analyzed by using repeated measures logistic regression comparing the same clinics. RESULTS Hospitalization rates for the postsupport year did not differ from comparison clinics either in the population that initially showed the difference or the population active in the clinics at the end of the year of implementation support. CONCLUSIONS Clinical effects of the CCM may wane after cessation of active implementation support.
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Affiliation(s)
- Mark S Bauer
- Center for Healthcare Organization and Implementation Research, and the Behavior Health Quality Enhancement Research Initiative, U.S. Department of Veterans Affairs (VA), Boston (all authors); Department of Psychiatry, Harvard Medical School, Boston (Bauer, Miller, Kim, Connolly); Department of Biostatistics, Boston University School of Medicine, Boston (Lew)
| | - Kelly Stolzmann
- Center for Healthcare Organization and Implementation Research, and the Behavior Health Quality Enhancement Research Initiative, U.S. Department of Veterans Affairs (VA), Boston (all authors); Department of Psychiatry, Harvard Medical School, Boston (Bauer, Miller, Kim, Connolly); Department of Biostatistics, Boston University School of Medicine, Boston (Lew)
| | - Christopher J Miller
- Center for Healthcare Organization and Implementation Research, and the Behavior Health Quality Enhancement Research Initiative, U.S. Department of Veterans Affairs (VA), Boston (all authors); Department of Psychiatry, Harvard Medical School, Boston (Bauer, Miller, Kim, Connolly); Department of Biostatistics, Boston University School of Medicine, Boston (Lew)
| | - Bo Kim
- Center for Healthcare Organization and Implementation Research, and the Behavior Health Quality Enhancement Research Initiative, U.S. Department of Veterans Affairs (VA), Boston (all authors); Department of Psychiatry, Harvard Medical School, Boston (Bauer, Miller, Kim, Connolly); Department of Biostatistics, Boston University School of Medicine, Boston (Lew)
| | - Samantha L Connolly
- Center for Healthcare Organization and Implementation Research, and the Behavior Health Quality Enhancement Research Initiative, U.S. Department of Veterans Affairs (VA), Boston (all authors); Department of Psychiatry, Harvard Medical School, Boston (Bauer, Miller, Kim, Connolly); Department of Biostatistics, Boston University School of Medicine, Boston (Lew)
| | - Robert Lew
- Center for Healthcare Organization and Implementation Research, and the Behavior Health Quality Enhancement Research Initiative, U.S. Department of Veterans Affairs (VA), Boston (all authors); Department of Psychiatry, Harvard Medical School, Boston (Bauer, Miller, Kim, Connolly); Department of Biostatistics, Boston University School of Medicine, Boston (Lew)
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29
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Fleury MJ, Grenier G, Gentil L, Roberge P. Deployment of the consultation-liaison model in adult and child-adolescent psychiatry and its impact on improving mental health treatment. BMC FAMILY PRACTICE 2021; 22:82. [PMID: 33926390 PMCID: PMC8086343 DOI: 10.1186/s12875-021-01437-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 12/11/2020] [Accepted: 04/06/2021] [Indexed: 11/21/2022]
Abstract
Background Little information exists on the perceptions of psychiatrists regarding the implementation and various impacts of the consultation-liaison model. This model has been used in Quebec (Canada) through the function of specialist respondent-psychiatrists (SRP) since 2009. This study assessed the main activities, barriers or facilitators, and impact of SRP in adult and child-adolescent psychiatry on the capacity of service providers in primary care and youth centers to treat patients with mental health disorders (MHD). Methods Data included 126 self-administered questionnaires from SRP and semi-structured interviews from 48 SRP managers. Mixed methods were used, with qualitative findings from managers complementing the SRP survey. Comparative analyses of SRP responses in adult versus child-adolescent psychiatry were also conducted. Results Psychiatrists dedicated a median 24.12 h/month to the SRP function, mainly involving case discussions with primary care teams or youth centers. They were confident about the level of support they provided and satisfied with their influence in clinical decision-making, but less satisfied with the support provided by their organizations. SRP evaluated their impacts on clinical practice as moderate, particularly among general practitioners (GP). SRP working in child-adolescent psychiatry were more comfortable, motivated, and positive about their overall performance and impact than in adult psychiatry. Organizational barriers (e.g. team instability) were most prevalent, followed by system-level factors (e.g. network size and complexity, lack of resources, model inflexibility) and individual factors (e.g. GP reluctance to treat patients with MHD). Organizational facilitators included support from family medicine group directors, collaboration with university family medicine groups and coordination by liaison nurses; at the system level, pre-existing relationships and working in the same institution; while individual-level facilitators included SRP personality and strong organizational support. Conclusion Quebec SRP were implemented sparingly in family medicine groups and youth centers, while SRP viewed their overall impact as moderate. Results were more positive in child-adolescent psychiatry than in adult psychiatry. Increased support for the SRP function, adapting the model to GP in need of more direct support, and resolving key system issues may improve SRP effectiveness in terms of team stability, coordination among providers, access to MH services and readiness to implement innovations. Supplementary Information The online version contains supplementary material available at 10.1186/s12875-021-01437-5.
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Affiliation(s)
- M-J Fleury
- Department of Psychiatry, McGill University, Montreal, QC, Canada. .,Douglas Mental Health University Institute Research Center, Montréal, QC, Canada.
| | - G Grenier
- Douglas Mental Health University Institute Research Center, Montréal, QC, Canada
| | - L Gentil
- Douglas Mental Health University Institute Research Center, Montréal, QC, Canada
| | - P Roberge
- Department of Family Medicine and Emergency Medicine, University of Sherbrooke, Sherbrooke, QC, Canada
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Ruderman MA, Kim B, Stolzmann K, Connolly S, Miller CJ, Bauer MS. Time course and heterogeneity of treatment effect of the collaborative chronic care model on psychiatric hospitalization rates: A survival analysis using routinely collected electronic medical records. PLoS One 2021; 16:e0249007. [PMID: 33765038 PMCID: PMC7993804 DOI: 10.1371/journal.pone.0249007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2020] [Accepted: 03/09/2021] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND Health systems are undergoing widespread adoption of the collaborative chronic care model (CCM). Care structured around the CCM may reduce costly psychiatric hospitalizations. Little is known, however, about the time course or heterogeneity of treatment effects (HTE) for CCM on psychiatric hospitalization. RATIONALE Assessment of CCM implementation support on psychiatric hospitalization might be more efficient if the timing were informed by an expected time course. Further, understanding HTE could help determine who should be referred for intervention. OBJECTIVES (i) Estimate the trajectory of CCM effect on psychiatric hospitalization rates. (ii) Explore HTE for CCM across demographic and clinical characteristics. METHODS Data from a stepped wedge CCM implementation trial were reanalyzed using 5 570 patients in CCM treatment and 46 443 patients receiving usual care. Time-to-event data was constructed from routine medical records. Effect trajectory of CCM on psychiatric hospitalization was simulated from an extended Cox model over one year of implementation support. Covariate risk contributions were estimated from subset stratified Cox models without using simulation. Ratios of hazard ratios (RHR) allowed comparison by trial arm for HTE analysis, also without simulation. No standard Cox proportional hazards models were used for either estimating the time-course or heterogeneity of treatment effect. RESULTS The effect of CCM implementation support increased most rapidly immediately after implementation start and grew more gradually throughout the rest of the study. On the final study day, psychiatric hospitalization rates in the treatment arm were 17% to 49% times lower than controls, with adjustment for all model covariates (HR 0.66; 95% CI 0.51-0.83). Our analysis of HTE favored usual care for those with a history of prior psychiatric hospitalization (RHR 4.92; 95% CI 3.15-7.7) but favored CCM for those with depression (RHR 0.61; 95% CI: 0.41-0.91). Having a single medical diagnosis, compared to having none, favored CCM (RHR 0.52; 95% CI 0.31-0.86). CONCLUSION Reduction of psychiatric hospitalization is evident immediately after start of CCM implementation support, but assessments may be better timed once the effect size begins to stabilize, which may be as early as six months. HTE findings for CCM can guide future research on utility of CCM in specific populations.
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Affiliation(s)
- Michael A. Ruderman
- Center for Healthcare Organization & Implementation Research, VA Boston Healthcare System, Jamaica Plain, Boston, Massachusetts, United States of America
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Bo Kim
- Center for Healthcare Organization & Implementation Research, VA Boston Healthcare System, Jamaica Plain, Boston, Massachusetts, United States of America
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Kelly Stolzmann
- Center for Healthcare Organization & Implementation Research, VA Boston Healthcare System, Jamaica Plain, Boston, Massachusetts, United States of America
| | - Samantha Connolly
- Center for Healthcare Organization & Implementation Research, VA Boston Healthcare System, Jamaica Plain, Boston, Massachusetts, United States of America
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Christopher J. Miller
- Center for Healthcare Organization & Implementation Research, VA Boston Healthcare System, Jamaica Plain, Boston, Massachusetts, United States of America
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Mark S. Bauer
- Center for Healthcare Organization & Implementation Research, VA Boston Healthcare System, Jamaica Plain, Boston, Massachusetts, United States of America
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts, United States of America
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Sullivan JL, Kim B, Miller CJ, Elwy AR, Drummond KL, Connolly SL, Riendeau RP, Bauer MS. Collaborative chronic care model implementation within outpatient behavioral health care teams: qualitative results from a multisite trial using implementation facilitation. Implement Sci Commun 2021; 2:33. [PMID: 33762023 PMCID: PMC7992349 DOI: 10.1186/s43058-021-00133-w] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Accepted: 03/08/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND This paper reports on a qualitative evaluation of a hybrid type II stepped-wedge, cluster randomized trial using implementation facilitation to implement team-based care in the form of the collaborative chronic care model (CCM) in interdisciplinary outpatient mental health teams. The objective of this analysis is to compare the alignment of sites' clinical processes with the CCM elements at baseline (time 1) and after 12 months of implementation facilitation (time 2) from the perspective of providers. METHODS We conducted semi-structured interviews to assess the extent to which six CCM elements were in place: work role redesign, patient self-management support, provider decision support, clinical information systems, linkages to community resources, and organizational/leadership support. Interviews were transcribed and a priori CCM elements were coded using a directed content analysis approach at times 1 and 2. We sought consensus on, and compared, the extent to which each CCM element was in place at times 1 and 2. RESULTS We conducted 27 and 31 telephone interviews at times 1 and 2, respectively, with outpatient mental health providers at nine participating sites. At time 1 and time 2, three CCM elements were most frequently present across the sites: work role redesign, patient self-management support, and provider decision support. The CCM elements with increased implementation from time 1 to time 2 were work role redesign, patient self-management support, and clinical information systems. For two CCM elements, linkages to community resources and organizational/leadership support, some sites had increased implementation at time 2 compared to time 1, while others had reductions. For the provider decision support element, we saw little change in the extent of its implementation. CONCLUSIONS Sites increased the extent of implementation on several CCM elements. The most progress was made in the CCM elements where sites had CCM-aligned processes in place at time 1. Teams made progress on elements they could more easily control, such as work role redesign. Our results suggest that maximizing the benefits of CCM-based outpatient mental health care may require targeting resources and training toward specific CCM elements-especially in the use of clinical information systems and linking with community resources. TRIAL REGISTRATION Clinical Trials NCT02543840 .
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Affiliation(s)
- Jennifer L Sullivan
- Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System, 150 S. Huntington Ave (152M), Boston, MA, USA.
- Department of Health Law, Policy and Management, Boston University School of Public Health, 715 Albany St, Talbot Building, Boston, MA, USA.
| | - Bo Kim
- Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System, 150 S. Huntington Ave (152M), Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Christopher J Miller
- Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System, 150 S. Huntington Ave (152M), Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - A Rani Elwy
- Center for Healthcare Organization and Implementation Research, VA Bedford Healthcare System, 200 Springs Road (152), Bedford, MA, USA
- Department of Psychiatry and Human Behavior, Warren Alpert Medical School, Brown University, Providence, RI, USA
| | - Karen L Drummond
- Center for Mental Healthcare and Outcomes Research, Central Arkansas Veterans Healthcare System, North Little Rock, AR, USA
- Department of Psychiatry, University of Arkansas for Medical Sciences College of Medicine, Little Rock, AR, USA
| | - Samantha L Connolly
- Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System, 150 S. Huntington Ave (152M), Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Rachel P Riendeau
- Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System, 150 S. Huntington Ave (152M), Boston, MA, USA
| | - Mark S Bauer
- Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System, 150 S. Huntington Ave (152M), Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
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Rates and predictors of brief intervention for women veterans returning from recent wars: Examining gaps in service delivery for unhealthy alcohol use. J Subst Abuse Treat 2021; 123:108257. [PMID: 33612192 DOI: 10.1016/j.jsat.2020.108257] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2020] [Revised: 11/01/2020] [Accepted: 12/11/2020] [Indexed: 11/20/2022]
Abstract
BACKGROUND Approximately one in four women veterans accessing the Department of Veterans Affairs (VA) engage in unhealthy alcohol use. There is substantial evidence for gender-sensitive screening (AUDIT-C = 3) and brief intervention (BI) to reduce risks associated with unhealthy alcohol use in women veterans; however, VA policies and incentives remain gender-neutral (AUDIT-C = 5). Women veterans who screen positive at lower-risk-level alcohol use (AUDIT-C = 3 or 4) may screen out and therefore not receive BI. This study aimed to examine gaps in implementation of BI practice for women veterans through identifying rates of BI at different alcohol risk levels (AUDIT-C = 3-4; =5-7; =8-12), and the role of alcohol risk level and other factors in predicting receipt of BI. METHODS From administrative data (2010-2016), we drew a sample of women veterans returning from recent wars who accessed outpatient and/or inpatient care. Of 869 women veterans, 284 screened positive for unhealthy alcohol use at or above a gender-sensitive cut-point (AUDIT-C ≥ 3). We used chart review methods to abstract variables from the medical record and then employed logistic regression comparing women veterans who received BI at varying alcohol risk levels to those who did not. RESULTS While almost 60% of the alcohol positive-risk sample received BI, among the subset of women veterans who screened positive for lower-risk alcohol use (57%; AUDIT-C = 3 or 4) only 34% received BI. Nurses in primary care programs were less likely to deliver BI than other types of clinicians (e.g., physicians, psychologists, social workers) in mental health programs; further, nurses in women's health programs were less likely to deliver BI than other types of clinicians in mixed-gender programs; Those women veterans with more medical problems were no more likely to receive BI than those with fewer medical problems. CONCLUSIONS Given that women veterans are a rapidly growing veteran population and a VA priority, underuse of BI for women veterans screening positive at a lower-risk level and those with more medical comorbidities requires attention, as do potential gaps in service delivery of BI in primary care and women's health programs. Women veterans health and well-being may be improved by tailoring screening for a younger cohort of women veterans at high-risk for, or with co-occurring disorders and then training providers in best practices for BI implementation.
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Zivin K, Kononowech J, Boden M, Abraham K, Harrod M, Sripada RK, Kales HC, Garcia HA, Pfeiffer P. Predictors and Consequences of Veterans Affairs Mental Health Provider Burnout: Protocol for a Mixed Methods Study. JMIR Res Protoc 2020; 9:e18345. [PMID: 33346737 PMCID: PMC7781796 DOI: 10.2196/18345] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2020] [Revised: 08/27/2020] [Accepted: 09/01/2020] [Indexed: 01/16/2023] Open
Abstract
Background In the Veterans Health Administration (VHA), mental health providers (MHPs) report the second highest level of burnout after primary care physicians. Burnout is defined as increased emotional exhaustion and depersonalization and decreased sense of personal accomplishment at work. Objective This study aims to characterize variation in MHP burnout by VHA facility over time, identifying workplace characteristics and practices of high-performing facilities. Methods Using both qualitative and quantitative methods, we will evaluate factors that influence MHP burnout and their effects on patient outcomes. We will compile annual survey data on workplace conditions and annual staffing as well as productivity data to assess same and subsequent year provider and patient outcomes reflecting provider and patient experiences. We will conduct interviews with mental health leadership at the facility level and with frontline MHPs sampled based on our quantitative findings. We will present our findings to an expert panel of operational partners, Veterans Affairs clinicians, administrators, policy leaders, and experts in burnout. We will reengage with facilities that participated in the earlier qualitative interviews and will hold focus groups that share results based on our quantitative and qualitative work combined with input from our expert panel. We will broadly disseminate these findings to support the development of actionable policies and approaches to addressing MHP burnout. Results This study will assist in developing and testing interventions to improve MHP burnout and employee engagement. Our work will contribute to improvements within VHA and will generate insights for health care delivery, informing efforts to address burnout. Conclusions This is the first comprehensive, longitudinal, national, mixed methods study that incorporates different types of MHPs. It will engage MHP leadership and frontline providers in understanding facilitators and barriers to effectively address burnout. International Registered Report Identifier (IRRID) PRR1-10.2196/18345
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Affiliation(s)
- Kara Zivin
- Center for Clinical Management Research, Department of Veterans Affairs, Ann Arbor, MI, United States.,Department of Psychiatry, University of Michigan Medical School, Ann Arbor, MI, United States
| | - Jennifer Kononowech
- Center for Clinical Management Research, Department of Veterans Affairs, Ann Arbor, MI, United States
| | - Matthew Boden
- Program Evaluation and Resource Center and VA Office of Mental Health Operations, VA Palo Alto Health Care System, Palo Alto, CA, United States
| | - Kristen Abraham
- Center for Clinical Management Research, Department of Veterans Affairs, Ann Arbor, MI, United States.,Department of Psychology, University of Detroit Mercy, Detroit, MI, United States
| | - Molly Harrod
- Center for Clinical Management Research, Department of Veterans Affairs, Ann Arbor, MI, United States
| | - Rebecca K Sripada
- Center for Clinical Management Research, Department of Veterans Affairs, Ann Arbor, MI, United States.,Department of Psychiatry, University of Michigan Medical School, Ann Arbor, MI, United States
| | - Helen C Kales
- Department of Psychiatry and Behavioral Sciences, UC Davis Health, Sacramento, CA, United States
| | - Hector A Garcia
- VA Texas Valley Coastal Bend Health Care System, Harlingen, TX, United States.,Department of Psychiatry, University of Texas Health Science Center, San Antonio, TX, United States
| | - Paul Pfeiffer
- Center for Clinical Management Research, Department of Veterans Affairs, Ann Arbor, MI, United States.,Department of Psychiatry, University of Michigan Medical School, Ann Arbor, MI, United States
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Smith SN, Liebrecht CM, Bauer MS, Kilbourne AM. Comparative effectiveness of external vs blended facilitation on collaborative care model implementation in slow-implementer community practices. Health Serv Res 2020; 55:954-965. [PMID: 33125166 DOI: 10.1111/1475-6773.13583] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023] Open
Abstract
OBJECTIVE To evaluate the comparative effectiveness of external facilitation (EF) vs external + internal facilitation (EF/IF), on uptake of a collaborative chronic care model (CCM) in community practices that were slower to implement under low-level implementation support. STUDY SETTING Primary data were collected from 43 community practices in Michigan and Colorado at baseline and for 12 months following randomization. STUDY DESIGN Sites that failed to meet a pre-established implementation benchmark after six months of low-level implementation support were randomized to add either EF or EF/IF support for up to 12 months. Key outcomes were change in number of patients receiving the CCM and number of patients receiving a clinically significant dose of the CCM. Moderators' analyses further examined whether comparative effectiveness was dependent on prerandomization adoption, number of providers trained or practice size. Facilitation log data were used for exploratory follow-up analyses. DATA COLLECTION Sites reported monthly on number of patients that had received the CCM. Facilitation logs were completed by study EF and site IFs and shared with the study team. PRINCIPAL FINDINGS N = 21 sites were randomized to EF and 22 to EF/IF. Overall, EF/IF practices saw more uptake than EF sites after 12 months (ΔEF/IF-EF = 4.4 patients, 95% CI = 1.87-6.87). Moderators' analyses, however, revealed that it was only sites with no prerandomization uptake of the CCM (nonadopter sites) that saw significantly more benefit from EF/IF (ΔEF/IF-EF = 9.2 patients, 95% CI: 5.72, 12.63). For sites with prerandomization uptake (adopter sites), EF/IF offered no additional benefit (ΔEF/IF-EF = -0.9; 95% CI: -4.40, 2.60). Number of providers trained and practice size were not significant moderators. CONCLUSIONS Although stepping up to the more intensive EF/IF did outperform EF overall, its benefit was limited to sites that failed to deliver any CCM under the low-level strategy. Once one or more providers were delivering the CCM, additional on-site personnel did not appear to add value to the implementation effort.
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Affiliation(s)
- Shawna N Smith
- Department of Health Management and Policy, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA.,Department of Psychiatry, University of Michigan Medical School, Ann Arbor, Michigan, USA
| | - Celeste M Liebrecht
- Department of Psychiatry, University of Michigan Medical School, Ann Arbor, Michigan, USA
| | - Mark S Bauer
- Center for Healthcare Organization & Implementation Research, VA Boston Healthcare System, Boston, Massachusetts, USA
| | - Amy M Kilbourne
- Department of Learning Health Sciences, University of Michigan Medical School, Ann Arbor, Michigan, USA.,Quality Enhancement Research Initiative, U.S. Department of Veterans Affairs, Washington, District of Columbia, USA
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Miller CJ, Griffith KN, Stolzmann K, Kim B, Connolly SL, Bauer MS. An Economic Analysis of the Implementation of Team-based Collaborative Care in Outpatient General Mental Health Clinics. Med Care 2020; 58:874-880. [PMID: 32732780 PMCID: PMC8177737 DOI: 10.1097/mlr.0000000000001372] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
BACKGROUND Collaborative Chronic Care Models represent an evidence-based way to structure care for chronic conditions, including mental health conditions. Few studies, however, have examined the cost implications of collaborative care for mental health. OBJECTIVE We aimed to conduct an economic analysis of implementing collaborative care in 9 outpatient general mental health clinics. RESEARCH DESIGN Analyses were derived from a stepped wedge hybrid implementation-effectiveness trial. We conducted cost-minimization analyses from the health system perspective, incorporating implementation costs, outpatient costs, and inpatient costs for the year before collaborative care implementation and the implementation year. We used a difference-in-differences approach and conducted 1-way sensitivity analyses to determine the robustness of results to variations ±15% in model parameters, along with probabilistic sensitivity analysis using Monte Carlo simulation. SUBJECTS Our treatment group included 5507 patients who were initially engaged in care within 9 outpatient general mental health teams that underwent collaborative care implementation. We compared costs for this group to 45,981 control patients who received mental health treatment as usual at the same medical centers. RESULTS Collaborative care implementation cost about $40 per patient and was associated with a significant decrease in inpatient costs and a nonsignificant increase in outpatient mental health costs. This implementation was associated with $78 in cost savings per patient. Monte Carlo simulation suggested that implementation was cost saving in 78% of iterations. CONCLUSIONS Collaborative care implementation for mental health teams was associated with significant reductions in mental health hospitalizations, leading to substantial cost savings of about $1.70 for every dollar spent for implementation.
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Affiliation(s)
- Christopher J. Miller
- Center for Healthcare Organization and Implementation Research (CHOIR), VA Boston Healthcare System
- Department of Psychiatry, Harvard Medical School
| | - Kevin N. Griffith
- Partnered Evidence-Based Policy Resource Center (PEPReC), VA Boston Healthcare System
- Department of Health Law, Policy, & Management, Boston University School of Public Health, Boston, MA
| | - Kelly Stolzmann
- Center for Healthcare Organization and Implementation Research (CHOIR), VA Boston Healthcare System
| | - Bo Kim
- Center for Healthcare Organization and Implementation Research (CHOIR), VA Boston Healthcare System
- Department of Psychiatry, Harvard Medical School
| | - Samantha L. Connolly
- Center for Healthcare Organization and Implementation Research (CHOIR), VA Boston Healthcare System
- Department of Psychiatry, Harvard Medical School
| | - Mark S. Bauer
- Center for Healthcare Organization and Implementation Research (CHOIR), VA Boston Healthcare System
- Department of Psychiatry, Harvard Medical School
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Hunter SC, Kim B, Mudge A, Hall L, Young A, McRae P, Kitson AL. Experiences of using the i-PARIHS framework: a co-designed case study of four multi-site implementation projects. BMC Health Serv Res 2020; 20:573. [PMID: 32576197 PMCID: PMC7310499 DOI: 10.1186/s12913-020-05354-8] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2020] [Accepted: 05/24/2020] [Indexed: 11/21/2022] Open
Abstract
BACKGROUND The integrated-Promoting Action on Research Implementation in Health Services (i-PARIHS) framework is an implementation framework that has been developed and refined over the last 20 years. Its underlying philosophy is that implementing research into healthcare practice is complex, unpredictable and non-linear which therefore requires a flexible and responsive approach to implementation. Facilitation is recognized as the central ingredient of this approach, and i-PARIHS now provides a Facilitation Guide with associated tools. This multiple case study of four implementation projects explored how the i-PARIHS framework has been practically operationalized by diverse implementation project teams. METHODS A co-design approach was used to elicit the experiences of four implementation project teams who used the i-PARIHS framework to guide their implementation approach. We conducted the established co-design steps of (i) setting up for success, (ii) gathering the experience, and (iii) understanding the experience. In particular we explored teams' approaches to setting up their projects; why and how they used the i-PARIHS framework and what they learnt from the experience. RESULTS We found both commonalities and differences in the use of i-PARIHS across the four implementation projects: (i) all the projects used the Facilitation Checklist that accompanies i-PARIHS as a starting point, (ii) the projects differed in how facilitation was carried out, (iii) existing tools were adapted for distinct phases: pre-implementation, during implementation, and post-implementation stages; and (iv) project-specific tools were often developed for monitoring implementation activities and fidelity. CONCLUSIONS We have provided a detailed overview of how current users of i-PARIHS are operationalising the framework, which existing tools they are using or adapting to use, and where they have needed to develop new tools to best utilise the framework. Importantly, this study highlights the value of existing tools from the published i-PARIHS Facilitation Guide and provides a starting point to further refine and add to these tools within a future Mobilising Implementation of i-PARIHS (or "Mi-PARIHS") suite of resources. Specifically, Mi-PARIHS might include more explicit guidance and/or tools for developing a structured implementation plan and monitoring fidelity to the implementation plan, including recording how strategies are tailored to an evolving context.
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Affiliation(s)
- S C Hunter
- College of Nursing and Health Sciences, Flinders University, Sturt Road, Bedford Park, Adelaide, SA, 5042, Australia.
- Caring Futures Institute, Flinders University, Adelaide, SA, Australia.
| | - B Kim
- Centre for Healthcare Organization and Implementation Research, U.S. Department of Veterans Affairs, Boston, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - A Mudge
- Internal Medicine Research Unit, Royal Brisbane and Women's Hospital, Brisbane, QLD, Australia
- School of Clinical Medicine, University of Queensland, Brisbane, QLD, Australia
| | - L Hall
- School of Public Health and Social Work, Faculty of Health, Queensland University of Technology, Brisbane, QLD, Australia
| | - A Young
- Nutrition and Dietetics, Royal Brisbane and Women's Hospital, QLD, Brisbane, Australia
- School of Exercise and Nutrition Sciences, Faculty of Health, Queensland University of Technology, Brisbane, QLD, Australia
| | - P McRae
- Internal Medicine Research Unit, Royal Brisbane and Women's Hospital, Brisbane, QLD, Australia
| | - A L Kitson
- College of Nursing and Health Sciences, Flinders University, Sturt Road, Bedford Park, Adelaide, SA, 5042, Australia
- Caring Futures Institute, Flinders University, Adelaide, SA, Australia
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Hunter SC, Kim B, Kitson AL. Interactive workshop to develop implementation framework (i-PARIHS) resources to support practice facilitation. Implement Sci Commun 2020; 1:56. [PMID: 32885212 PMCID: PMC7427849 DOI: 10.1186/s43058-020-00046-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2019] [Accepted: 06/05/2020] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND Practice facilitation is a method used to address the complexity associated with implementation of innovations into primary care. To provide support, we propose that the i-PARIHS (Integrated Promoting Action on Research Implementation in Health Services) framework could support practice facilitators. The i-PARIHS framework positions facilitation as a core element for successful implementation. Therefore, the aim of this study was to provide support to practice facilitators whilst simultaneously gaining feedback on what facilitators in practice need in regard to support with operationalising the i-PARIHS framework in practice. METHODS This study involved the delivery of a 1-h workshop on the i-PARIHS framework at the 2018 International Conference on Practice Facilitation. The authors provided an overview of the i-PARIHS framework, how it can be used to support the facilitation of innovations into practice, and finally, attendees worked through facilitation scenarios and applied an i-PARIHS resource. At the end of the workshop, attendees were invited to participant in the research component, by completing a post-workshop survey on the workshop content and the i-PARIHS resource. RESULTS Participants were highly engaged and enthusiastic about the workshop. Participants reported that an introduction to implementation frameworks was valuable and the example of how the i-PARIHS framework had been used in a previous project was helpful. Overall, this study identifies how framework informed facilitation helped participants feel more equipped to conduct systematic facilitation and that the development of i-PARIHS resources would be helpful in their everyday work. CONCLUSIONS This study demonstrates that the existence of implementation frameworks is not sufficient to provide support to those who facilitate in the real world. The current study introduced practice facilitators to the i-PARIHS framework, and the findings demonstrate the need to develop and refine existing i-PARIHS resources to support facilitation. Specifically, the next steps stemming from this study will be to (i) continue to utilize workshops for sharing and refining tools, (ii) allocate development efforts to tools that assist with planning, (iii) focus on tool provision mechanisms that keep user-friendliness in mind, and (iv) translate the i-PARIHS facilitation checklist from academic language into more practical and user-friendly language.
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Affiliation(s)
- Sarah C. Hunter
- College of Nursing and Health Sciences, Flinders University, Sturt Road, Bedford Park, Adelaide, South Australia 5042 Australia
- Caring Futures Institute, Flinders University, Sturt Road, Bedford Park, Adelaide, South Australia 5042 Australia
| | - Bo Kim
- Center for Healthcare Organization and Implementation Research, US Veterans Health Administration, 150 South Huntington Avenue, Boston, MA 02130 USA
- Department of Psychiatry, Harvard Medical School, 25 Shattuck Street, Boston, MA 02115 USA
| | - Alison L. Kitson
- College of Nursing and Health Sciences, Flinders University, Sturt Road, Bedford Park, Adelaide, South Australia 5042 Australia
- Caring Futures Institute, Flinders University, Sturt Road, Bedford Park, Adelaide, South Australia 5042 Australia
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The Collaborative Chronic Care Model for Mental Health Conditions: From Evidence Synthesis to Policy Impact to Scale-up and Spread. Med Care 2020; 57 Suppl 10 Suppl 3:S221-S227. [PMID: 31517791 PMCID: PMC6749976 DOI: 10.1097/mlr.0000000000001145] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
BACKGROUND Extensive evidence indicates that Collaborative Chronic Care Models (CCMs) improve outcome in chronic medical conditions and depression treated in primary care. Beginning with an evidence synthesis which indicated that CCMs are also effective for multiple mental health conditions, we describe a multistage process that translated this knowledge into evidence-based health system change in the US Department of Veterans Affairs (VA). EVIDENCE SYNTHESIS In 2010, recognizing that there had been numerous CCM trials for a wide variety of mental health conditions, we conducted an evidence synthesis compiling randomized controlled trials of CCMs for any mental health condition. The systematic review demonstrated CCM effectiveness across mental health conditions and treatment venues. Cumulative meta-analysis and meta-regression further informed our approach to subsequent CCM implementation. POLICY IMPACT In 2015, based on the evidence synthesis, VA Office of Mental Health and Suicide Prevention (OMHSP) adopted the CCM as the model for their outpatient mental health teams. RANDOMIZED IMPLEMENTATION TRIAL In 2015-2018 we partnered with OMHSP to conduct a 9-site stepped wedge implementation trial, guided by insights from the evidence synthesis. SCALE-UP AND SPREAD In 2017 OMHSP launched an effort to scale-up and spread the CCM to additional VA medical centers. Seventeen facilitators were trained and 28 facilities engaged in facilitation. DISCUSSION Evidence synthesis provided leverage for evidence-based policy change. This formed the foundation for a health care leadership/researcher partnership, which conducted an implementation trial and subsequent scale-up and spread effort to enhance adoption of the CCM, as informed by the evidence synthesis.
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Miller CJ, Wiltsey-Stirman S, Baumann AA. Iterative Decision-making for Evaluation of Adaptations (IDEA): A decision tree for balancing adaptation, fidelity, and intervention impact. JOURNAL OF COMMUNITY PSYCHOLOGY 2020; 48:1163-1177. [PMID: 31970812 PMCID: PMC7261620 DOI: 10.1002/jcop.22279] [Citation(s) in RCA: 53] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/30/2019] [Revised: 10/23/2019] [Accepted: 10/26/2019] [Indexed: 05/17/2023]
Abstract
BACKGROUND Evidence-based practices (EBPs) are frequently adapted to maximize outcomes while maintaining fidelity to core EBP elements. Many step-by-step frameworks for adapting EBPs have been developed, but these models may not account for common complexities in the adaptation process. In this paper, we introduce the Iterative Decision-making for Evaluation of Adaptations (IDEA), a tool to guide adaptations that addresses these issues. FRAMEWORK DESIGN AND USE Adapting EBPs requires attending to key contingencies incorporated into the IDEA, including: the need for adaptations; fidelity to core EBP elements; the timeframe in which to make adaptations; the potential to collect pilot data; key clinical and implementation outcomes; and stakeholder viewpoints. We use two examples to illustrate application of the IDEA. CONCLUSIONS The IDEA is a practical tool to guide EBP adaptation that incorporates important decision points and the dynamism of ongoing adaptation. Its use may help implementation scientists, clinicians, and administrators maximize EBP impact.
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Affiliation(s)
- Christopher J Miller
- Department of Psychiatry, VA Boston Healthcare System, Center for Healthcare Organization and Implementation Research (CHOIR), Harvard Medical School, Boston, Massachusetts
| | - Shannon Wiltsey-Stirman
- Department of Psychiatry and Behavioral Sciences, VA Palo Alto Healthcare System, National Center for PTSD Dissemination and Training Division, Stanford University, Stanford, California
| | - Ana A Baumann
- Brown School, Washington University in St. Louis, St. Louis, Missouri
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Moore T, Groppi J, Ourth H, Morreale A, Torrise V. Increasing access to care using clinical pharmacy specialist providers in outpatient mental health: Successful practice integration within the Department of Veterans Affairs. J Am Pharm Assoc (2003) 2020; 60:S107-S112. [PMID: 32280020 DOI: 10.1016/j.japh.2020.03.011] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2019] [Revised: 03/02/2020] [Accepted: 03/06/2020] [Indexed: 11/25/2022]
Abstract
BACKGROUND To highlight the role and impact of the mental health (MH) clinical pharmacist provider in outpatient MH through successful practice integration into team-based care. OBJECTIVE The MH clinical pharmacy specialist (CPS) provider serves in many key roles to improve patient-centered care and medication outcomes by supporting the needs of the MH team, patients, and caregivers in areas of comprehensive medication management. MH CPS providers are integrated as MH providers in general and specialty MH clinics, behavioral health clinics embedded in primary care, residential rehabilitation facilities, specialty MH programs, and in inpatient MH units to improve access, quality, and safety. PRACTICE DESCRIPTION There is a shortage of psychiatrists across the United States, which affects the ability to provide MH care to patients. PRACTICE INNOVATION There is a need to transform the MH team to include clinicians focused on providing services to the growing population with MH conditions; hence, the expertise of the MH CPS is an asset to increase access to comprehensive medication management services. EVALUATION The MH CPS provider serves patients with a variety of MH conditions, managing medication-related adverse events, performing ongoing and acute medication monitoring, and collaborating with other health care providers for management of new diagnoses. RESULTS The MH CPS provider improves access to care, clinical outcomes, and safety when deployed as direct patient care providers on Veterans Affairs (VA) interprofessional care teams. VA MH clinical pharmacy practice continues to demonstrate what the MH CPS provider, practicing at the top of their license, can achieve as a core member in MH team-based care. CONCLUSION These foundational concepts can be applied to further expand MH clinical pharmacy practice into non-VA settings through the use collaborative practice agreements and integration into interprofessional care teams, providing access to patients in need of MH care.
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Connolly SL, Sullivan JL, Ritchie MJ, Kim B, Miller CJ, Bauer MS. External facilitators' perceptions of internal facilitation skills during implementation of collaborative care for mental health teams: a qualitative analysis informed by the i-PARIHS framework. BMC Health Serv Res 2020; 20:165. [PMID: 32131824 PMCID: PMC7057643 DOI: 10.1186/s12913-020-5011-3] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2019] [Accepted: 02/20/2020] [Indexed: 11/16/2022] Open
Abstract
Background Facilitation is a key strategy that may contribute to successful implementation of healthcare innovations. In blended facilitation, external facilitators (EFs) guide and support internal facilitators (IFs) in directing implementation processes. Developers of the i-PARIHS framework propose that successful facilitation requires project management, team/process, and influencing/negotiating skills. It is unclear what IF skills are most important in real-world settings, which could inform recruitment and training efforts. As prior qualitative studies of IF skills have only interviewed IFs, the perspectives of their EF partners are needed. Furthermore, little is known regarding the distribution of implementation tasks between IFs and EFs, which could impact sustainability once external support is removed. In the context of an implementation trial, we therefore: 1) evaluated IFs’ use of i-PARIHS facilitation skills, from EFs’ perspectives; 2) identified attributes of IFs not encompassed within the i-PARIHS skills; and 3) investigated the relative contributions of IFs and EFs during facilitation. Methods Analyses were conducted within a hybrid type II trial utilizing blended facilitation to implement the collaborative chronic care model within mental health teams of nine VA medical centers. Each site committed one team and an IF to weekly process design meetings and additional implementation activities over 12 months. Three EFs worked with three sites each. Following study completion, the EFs completed semi-structured qualitative interviews reflecting on the facilitation process, informed by the i-PARIHS facilitation skill areas. Interviews were analyzed via directed content analysis. Results EFs emphasized the importance of IFs having strong project management, team/process, and influencing/negotiating skills. Prior experience in these areas and a mental health background were also benefits. Personal characteristics (e.g., flexible, assertive) were described as critical, particularly when faced with conflict. EFs discussed the importance of clear delineation of EF/IF roles, and the need to shift facilitation responsibilities to IFs. Conclusions Key IF skills, according to EFs, are aligned with i-PARIHS recommendations, but IFs’ personal characteristics were also emphasized as important factors. Findings highlight traits to consider when selecting IFs and potential training areas (e.g., conflict management). EFs and IFs must determine an appropriate distribution of facilitation tasks to ensure long-term sustainability of practices. Trial registration Clinicaltrials.gov, September 7, 2015, #NCT02543840.
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Affiliation(s)
- Samantha L Connolly
- Center for Healthcare Organization & Implementation Research, VA Boston Healthcare System, 150 S. Huntington Ave., Building 9, Room 208C, Boston, MA, 02130, USA. .,Department of Psychiatry, Harvard Medical School, Boston, MA, USA.
| | - Jennifer L Sullivan
- Center for Healthcare Organization & Implementation Research, VA Boston Healthcare System, 150 S. Huntington Ave., Building 9, Room 208C, Boston, MA, 02130, USA.,Department of Health Law, Policy and Management, Boston University School of Public Health, Boston, MA, USA
| | - Mona J Ritchie
- VA Quality Enhancement Research Initiative (QUERI) Program for Team-Based Behavioral Health, Central Arkansas Veterans Healthcare System, North Little Rock, AR, USA.,Department of Psychiatry, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - Bo Kim
- Center for Healthcare Organization & Implementation Research, VA Boston Healthcare System, 150 S. Huntington Ave., Building 9, Room 208C, Boston, MA, 02130, USA.,Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Christopher J Miller
- Center for Healthcare Organization & Implementation Research, VA Boston Healthcare System, 150 S. Huntington Ave., Building 9, Room 208C, Boston, MA, 02130, USA.,Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Mark S Bauer
- Center for Healthcare Organization & Implementation Research, VA Boston Healthcare System, 150 S. Huntington Ave., Building 9, Room 208C, Boston, MA, 02130, USA.,Department of Psychiatry, Harvard Medical School, Boston, MA, USA
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Kim B, Sullivan JL, Ritchie MJ, Connolly SL, Drummond KL, Miller CJ, Greenan MA, Bauer MS. Comparing variations in implementation processes and influences across multiple sites: What works, for whom, and how? Psychiatry Res 2020; 283:112520. [PMID: 31627960 DOI: 10.1016/j.psychres.2019.112520] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/02/2019] [Revised: 08/01/2019] [Accepted: 08/16/2019] [Indexed: 10/26/2022]
Abstract
Traditional analyses and interpretation of controlled trials rely on measures of central tendency (e.g., mean findings for treatment versus control) to detect treatment effects. These trial designs therefore emphasize homogeneity of results, with variations within the experimental or control groups treated as error to be controlled for or ignored. For implementation trials, however, heterogeneity of results is an expected result to be explored rather than an imperfection to be minimized. Thus, many implementation trials seek to understand not only "Does it work?" but also "What works, for whom, and how?" Hence, mixed quantitative-qualitative methods that can capitalize on heterogeneity are needed to (i) comprehensively identify factors that influence the implementation process and (ii) understand their impact on implementation outcomes. This paper outlines the matrixed multiple case study approach, which allows for understanding how these processes and influences similarly or differently interact with outcomes across multiple implementation sites. We provide an example of this approach using data from a multi-site trial that tested the implementation of the evidence-based Collaborative Chronic Care Model at nine US Department of Veterans Affairs medical centers.
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Affiliation(s)
- Bo Kim
- Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System, Boston, MA, USA; Department of Psychiatry, Harvard Medical School, Boston, MA, USA.
| | - Jennifer L Sullivan
- Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System, Boston, MA, USA; Department of Health Law, Policy and Management, Boston University School of Public Health, Boston, MA, USA
| | - Mona J Ritchie
- Central Arkansas Veterans Healthcare System, North Little Rock, AR, USA; Department of Psychiatry, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - Samantha L Connolly
- Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System, Boston, MA, USA; Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Karen L Drummond
- Central Arkansas Veterans Healthcare System, North Little Rock, AR, USA; Department of Psychiatry, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - Christopher J Miller
- Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System, Boston, MA, USA; Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - M Alexis Greenan
- Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System, Boston, MA, USA
| | - Mark S Bauer
- Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System, Boston, MA, USA; Department of Psychiatry, Harvard Medical School, Boston, MA, USA
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Miller CJ, Smith SN, Pugatch M. Experimental and quasi-experimental designs in implementation research. Psychiatry Res 2020; 283:112452. [PMID: 31255320 PMCID: PMC6923620 DOI: 10.1016/j.psychres.2019.06.027] [Citation(s) in RCA: 70] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/28/2019] [Revised: 06/18/2019] [Accepted: 06/19/2019] [Indexed: 01/22/2023]
Abstract
Implementation science is focused on maximizing the adoption, appropriate use, and sustainability of effective clinical practices in real world clinical settings. Many implementation science questions can be feasibly answered by fully experimental designs, typically in the form of randomized controlled trials (RCTs). Implementation-focused RCTs, however, usually differ from traditional efficacy- or effectiveness-oriented RCTs on key parameters. Other implementation science questions are more suited to quasi-experimental designs, which are intended to estimate the effect of an intervention in the absence of randomization. These designs include pre-post designs with a non-equivalent control group, interrupted time series (ITS), and stepped wedges, the last of which require all participants to receive the intervention, but in a staggered fashion. In this article we review the use of experimental designs in implementation science, including recent methodological advances for implementation studies. We also review the use of quasi-experimental designs in implementation science, and discuss the strengths and weaknesses of these approaches. This article is therefore meant to be a practical guide for researchers who are interested in selecting the most appropriate study design to answer relevant implementation science questions, and thereby increase the rate at which effective clinical practices are adopted, spread, and sustained.
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Affiliation(s)
- Christopher J. Miller
- VA Boston Healthcare System, Center for Healthcare Organization and Implementation Research (CHOIR), United States Department of Veterans Affairs, Boston, MA, USA,Department of Psychiatry, Harvard Medical School, Boston, MA, USA,Corresponding Author: ; (p) 857-364-5688 (fax) 857-364-6140
| | - Shawna N. Smith
- Department of Psychiatry, University of Michigan Medical School, Ann Arbor, MI, USA,Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Marianne Pugatch
- VA Boston Healthcare System, Center for Healthcare Organization and Implementation Research (CHOIR), United States Department of Veterans Affairs, Boston, MA, USA
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Kim B, Bolton RE, Hyde J, Fincke BG, Drainoni ML, Petrakis BA, Simmons MM, McInnes DK. Coordinating across correctional, community, and VA systems: applying the Collaborative Chronic Care Model to post-incarceration healthcare and reentry support for veterans with mental health and substance use disorders. HEALTH & JUSTICE 2019; 7:18. [PMID: 31832790 PMCID: PMC6909453 DOI: 10.1186/s40352-019-0099-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/01/2019] [Accepted: 11/20/2019] [Indexed: 05/05/2023]
Abstract
BACKGROUND Between 12,000 and 16,000 veterans leave incarceration annually. As is known to be the case for justice-involved populations in general, mental health disorders (MHDs) and substance use disorders (SUDs) are highly prevalent among incarcerated veterans, and individuals with MHDs and SUDs reentering the community are at increased risk of deteriorating health and recidivism. We sought to identify opportunities to better coordinate care/services across correctional, community, and VA systems for reentry veterans with MHDs and SUDs. METHODS We interviewed 16 veterans post-incarceration and 22 stakeholders from reentry-involved federal/state/community organizations. We performed a grounded thematic analysis, and recognizing consistencies between the emergent themes and the evidence-based Collaborative Chronic Care Model (CCM), we mapped findings to the CCM's elements - work role redesign (WRR), patient self-management support (PSS), provider decision support (PDS), clinical information systems (CIS), linkages to community resources (LCR), and organizational/leadership support (OLS). RESULTS Emergent themes included (i) WRR - coordination challenges among organizations involved in veterans' reentry; (ii) PSS - veterans' fear of reentering society; (iii) PDS - uneven knowledge by reentry support providers regarding available services when deciding which services to connect a reentry veteran to and whether he/she is ready and/or willing to receive services; (iv) CIS - lapses in MHD/SUD medications between release and a first scheduled health care appointment, as well as challenges in transfer of medical records; (v) LCR - inconsistent awareness of existing services and resources available across a disparate reentry system; and (vi) OLS - reentry plans designed to address only immediate transitional needs upon release, which do not always prioritize MHD/SUD needs. CONCLUSIONS Applying the CCM to coordinating cross-system health care and reentry support may contribute to reductions in mental health crises and overdoses in the precarious first weeks of the reentry period.
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Affiliation(s)
- Bo Kim
- VA Center for Healthcare Organization and Implementation Research, Bedford/Boston, MA USA
- Harvard Medical School, Boston, MA USA
| | - Rendelle E. Bolton
- VA Center for Healthcare Organization and Implementation Research, Bedford/Boston, MA USA
- Brandeis University The Heller School for Social Policy and Management, Waltham, MA USA
| | - Justeen Hyde
- VA Center for Healthcare Organization and Implementation Research, Bedford/Boston, MA USA
- Boston University School of Medicine, Boston, MA USA
| | - B. Graeme Fincke
- VA Center for Healthcare Organization and Implementation Research, Bedford/Boston, MA USA
- Boston University School of Public Health, Boston, MA USA
| | - Mari-Lynn Drainoni
- VA Center for Healthcare Organization and Implementation Research, Bedford/Boston, MA USA
- Boston University School of Medicine, Boston, MA USA
- Boston University School of Public Health, Boston, MA USA
| | - Beth Ann Petrakis
- VA Center for Healthcare Organization and Implementation Research, Bedford/Boston, MA USA
| | | | - D. Keith McInnes
- VA Center for Healthcare Organization and Implementation Research, Bedford/Boston, MA USA
- Boston University School of Public Health, Boston, MA USA
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Kilbourne AM, Braganza MZ, Bowersox NW, Goodrich DE, Miake-Lye I, Floyd N, Garrido MM, Frakt AB, Bever CT, Vega R, Ramoni R. Research Lifecycle to Increase the Substantial Real-world Impact of Research: Accelerating Innovations to Application. Med Care 2019; 57 Suppl 10 Suppl 3:S206-S212. [PMID: 31517789 PMCID: PMC6750195 DOI: 10.1097/mlr.0000000000001146] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
BACKGROUND US health care systems face a growing demand to incorporate innovations that improve patient outcomes at a lower cost. Funding agencies increasingly must demonstrate the impact of research investments on public health. The Learning Health System promotes continuous institutional innovation, yet specific processes to develop innovations for further research and implementation into real-world health care settings to maximize health impacts have not been specified. OBJECTIVE We describe the Research Lifecycle and how it leverages institutional priorities to support the translation of research discoveries to clinical application, serving as a broader operational approach to enhance the Learning Health System. METHODS Developed by the US Department of Veterans Affairs Office of Research and Development Research-to-Real-World Workgroup, the Research Lifecycle incorporates frameworks from product development, translational science, and implementation science methods. The Lifecycle is based on Workgroup recommendations to overcome barriers to more direct translation of innovations to clinical application and support practice implementation and sustainability. RESULTS The Research Lifecycle posits 5 phases which support a seamless pathway from discovery to implementation: prioritization (leadership priority alignment), discovery (innovation development), validation (clinical, operational feasibility), scale-up and spread (implementation strategies, performance monitoring), and sustainability (business case, workforce training). An example of how the Research Lifecycle has been applied within a health system is provided. CONCLUSIONS The Research Lifecycle aligns research and health system investments to maximize real-world practice impact via a feasible pathway, where priority-driven innovations are adapted for effective clinical use and supported through implementation strategies, leading to continuous improvement in real-world health care.
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Affiliation(s)
- Amy M. Kilbourne
- Veterans Health Administration, US Department of Veterans Affairs, Washington, DC
- Department of Psychiatry, University of Michigan Medical School
| | - Melissa Z. Braganza
- Veterans Health Administration, US Department of Veterans Affairs, Washington, DC
| | - Nicholas W. Bowersox
- Department of Psychiatry, University of Michigan Medical School
- Center for Evaluation and Implementation Resources, VA Ann Arbor Center for Clinical Management Research, Ann Arbor, MI
| | - David E. Goodrich
- Center for Evaluation and Implementation Resources, VA Ann Arbor Center for Clinical Management Research, Ann Arbor, MI
| | - Isomi Miake-Lye
- Center for the Study of Healthcare Innovation, Implementation & Policy, VA Greater Los Angles Healthcare System, Los Angeles, CA
| | - Nicole Floyd
- Evidence Synthesis Program Coordinating Center, Portland VA Health Care System, Portland, OR
| | - Melissa M. Garrido
- Partnered Evidence-based Policy Resource Center, Boston VA Healthcare System
- Department of Health Law, Policy and Management, Boston University School of Public Health, Boston, MA
| | - Austin B. Frakt
- Partnered Evidence-based Policy Resource Center, Boston VA Healthcare System
- Department of Health Law, Policy and Management, Boston University School of Public Health, Boston, MA
| | - Christopher T. Bever
- Veterans Health Administration, US Department of Veterans Affairs, Washington, DC
| | - Ryan Vega
- Veterans Health Administration, US Department of Veterans Affairs, Washington, DC
| | - Rachel Ramoni
- Veterans Health Administration, US Department of Veterans Affairs, Washington, DC
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Lew RA, Miller CJ, Kim B, Wu H, Stolzmann K, Bauer MS. A method to reduce imbalance for site-level randomized stepped wedge implementation trial designs. Implement Sci 2019; 14:46. [PMID: 31053157 PMCID: PMC6500026 DOI: 10.1186/s13012-019-0893-3] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2018] [Accepted: 04/12/2019] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Controlled implementation trials often randomize the intervention at the site level, enrolling relatively few sites (e.g., 6-20) compared to trials that randomize by subject. Trials with few sites carry a substantial risk of an imbalance between intervened (cases) and non-intervened (control) sites in important site characteristics, thereby threatening the internal validity of the primary comparison. A stepped wedge design (SWD) staggers the intervention at sites over a sequence of times or time waves until all sites eventually receive the intervention. We propose a new randomization method, sequential balance, to control time trend in site allocation by minimizing sequential imbalance across multiple characteristics. We illustrate the new method by applying it to a SWD implementation trial. METHODS The trial investigated the impact of blended internal-external facilitation on the establishment of evidence-based teams in general mental health clinics in nine US Department of Veterans Affairs medical centers. Prior to randomization to start time, an expert panel of implementation researchers and health system program leaders identified by consensus a series of eight facility-level characteristics judged relevant to the success of implementation. We characterized each of the nine sites according to these consensus features. Using a weighted sum of these characteristics, we calculated imbalance scores for each of 1680 possible site assignments to identify the most sequentially balanced assignment schemes. RESULTS From 1680 possible site assignments, we identified 34 assignments with minimal imbalance scores, and then randomly selected one assignment by which to randomize start time. Initially, the mean imbalance score was 3.10, but restricted to the 34 assignments, it declined to 0.99. CONCLUSIONS Sequential balancing of site characteristics across groups of sites in the time waves of a SWD strengthens the internal validity of study conclusions by minimizing potential confounding. TRIAL REGISTRATION Registered at ClinicalTrials.gov as clinical trials # NCT02543840 ; entered 9/4/2015.
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Affiliation(s)
- Robert A. Lew
- VA Boston Healthcare System, Center for Healthcare Organization and Implementation Research, 150 South Huntington Avenue, Jamaica Plain, Boston, MA 02130 USA
- The Massachusetts Veterans Epidemiology Research and Information Center, 150 South Huntington Avenue, Jamaica Plain, Boston, MA 02130 USA
| | - Christopher J. Miller
- VA Boston Healthcare System, Center for Healthcare Organization and Implementation Research, 150 South Huntington Avenue, Jamaica Plain, Boston, MA 02130 USA
- The Massachusetts Veterans Epidemiology Research and Information Center, 150 South Huntington Avenue, Jamaica Plain, Boston, MA 02130 USA
| | - Bo Kim
- VA Boston Healthcare System, Center for Healthcare Organization and Implementation Research, 150 South Huntington Avenue, Jamaica Plain, Boston, MA 02130 USA
- The Massachusetts Veterans Epidemiology Research and Information Center, 150 South Huntington Avenue, Jamaica Plain, Boston, MA 02130 USA
| | - Hongsheng Wu
- Department of Computer Science & Networking, Wentworth Institute of Technology, Boston, USA
| | - Kelly Stolzmann
- VA Boston Healthcare System, Center for Healthcare Organization and Implementation Research, 150 South Huntington Avenue, Jamaica Plain, Boston, MA 02130 USA
| | - Mark S. Bauer
- VA Boston Healthcare System, Center for Healthcare Organization and Implementation Research, 150 South Huntington Avenue, Jamaica Plain, Boston, MA 02130 USA
- Department of Psychiatry, Harvard Medical School, Boston, MA USA
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