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Duan Y, Wang J, Lanham HJ, Berta W, Chamberlain SA, Hoben M, Choroschun K, Iaconi A, Song Y, Perez JS, Shrestha S, Beeber A, Anderson RA, Hayduk L, Cummings GG, Norton PG, Estabrooks CA. How context links to best practice use in long-term care homes: a mixed methods study. Implement Sci Commun 2024; 5:63. [PMID: 38849909 PMCID: PMC11157780 DOI: 10.1186/s43058-024-00600-0] [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] [Received: 10/23/2023] [Accepted: 05/28/2024] [Indexed: 06/09/2024] Open
Abstract
BACKGROUND Context (work environment) plays a crucial role in implementing evidence-based best practices within health care settings. Context is multi-faceted and its complex relationship with best practice use by care aides in long-term care (LTC) homes are understudied. This study used an innovative approach to investigate how context elements interrelate and influence best practice use by LTC care aides. METHODS In this secondary analysis study, we combined coincidence analysis (a configurational comparative method) and qualitative analysis to examine data collected through the Translating Research in Elder Care (TREC) program. Coincidence analysis of clinical microsystem (care unit)-level data aggregated from a survey of 1,506 care aides across 36 Canadian LTC homes identified configurations (paths) of context elements linked consistently to care aides' best practices use, measured with a scale of conceptual research use (CRU). Qualitative analysis of ethnographic case study data from 3 LTC homes (co-occurring with the survey) further informed interpretation of the configurations. RESULTS Three paths led to very high CRU at the care unit level: very high leadership; frequent use of educational materials; or a combination of very high social capital (teamwork) and frequent communication between care aides and clinical educators or specialists. Conversely, 2 paths led to very low CRU, consisting of 3 context elements related to unfavorable conditions in relationships, resources, and formal learning opportunities. Our qualitative analysis provided insights into how specific context elements served as facilitators or barriers for best practices. This qualitative exploration was especially helpful in understanding 2 of the paths, illustrating the pivotal role of leadership and the function of teamwork in mitigating the negative impact of time constraints. CONCLUSIONS Our study deepens understanding of the complex interrelationships between context elements and their impact on the implementation of best practices in LTC homes. The findings underscore that there is no singular, universal bundle of context-related elements that enhance or hinder best practice use in LTC homes.
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Affiliation(s)
- Yinfei Duan
- Faculty of Nursing, College of Health Sciences, University of Alberta, Edmonton, AB, Canada.
| | - Jing Wang
- Nursing Department, College of Health and Human Services, University of New Hampshire, Durham, NH, USA
| | - Holly J Lanham
- Joe R. & Teresa Lozano Long School of Medicine, University of Texas Health, San Antonio, TX, USA
| | - Whitney Berta
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
| | | | - Matthias Hoben
- Faculty of Nursing, College of Health Sciences, University of Alberta, Edmonton, AB, Canada
- School of Health Policy and Management, Faculty of Health, York University, Toronto, ON, Canada
| | | | - Alba Iaconi
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
| | - Yuting Song
- Faculty of Nursing, College of Health Sciences, University of Alberta, Edmonton, AB, Canada
- School of Nursing, Qingdao University, Qingdao, Shandong, China
| | - Janelle Santos Perez
- School of Nursing, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Shovana Shrestha
- Faculty of Nursing, College of Health Sciences, University of Alberta, Edmonton, AB, Canada
| | - Anna Beeber
- School of Nursing, Johns Hopkins University, Baltimore, MD, USA
| | - Ruth A Anderson
- School of Nursing, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Leslie Hayduk
- Sociology Department, Faculty of Arts, University of Alberta, Edmonton, AB, Canada
| | - Greta G Cummings
- Faculty of Nursing, College of Health Sciences, University of Alberta, Edmonton, AB, Canada
| | - Peter G Norton
- Department of Family Medicine, University of Calgary, Calgary, AB, Canada
| | - Carole A Estabrooks
- Faculty of Nursing, College of Health Sciences, University of Alberta, Edmonton, AB, Canada
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Essien UR, Kim N, Hausmann LRM, Washington DL, Mor MK, Litam TMA, Boyer TL, Gellad WF, Fine MJ. Veterans Affairs Medical Center Racial and Ethnic Composition and Initiation of Anticoagulation for Atrial Fibrillation. JAMA Netw Open 2024; 7:e2418114. [PMID: 38913375 PMCID: PMC11197447 DOI: 10.1001/jamanetworkopen.2024.18114] [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: 11/30/2023] [Accepted: 04/22/2024] [Indexed: 06/25/2024] Open
Abstract
Importance Racial and ethnic disparities exist in anticoagulation therapy for atrial fibrillation (AF). Whether medical center racial and ethnic composition is associated with these disparities is unclear. Objective To determine whether medical center racial and ethnic composition is associated with overall anticoagulation and disparities in anticoagulation for AF. Design, Setting, and Participants Retrospective cohort study of Black, White, and Hispanic patients with incident AF from 2018 to 2021 at 140 Veterans Health Administration medical centers (VAMCs). Data were analyzed from March to November 2023. Exposure VAMC racial and ethnic composition, defined as the proportion of patients from minoritized racial and ethnic groups treated at a VAMC, categorized into quartiles. VAMCs in quartile 1 (Q1) had the lowest percentage of patients from minoritized groups (ie, the reference group). Main Outcomes and Measures The odds of initiating any anticoagulant, direct-acting oral anticoagulant (DOAC), or warfarin therapy within 90 days of an index AF diagnosis, adjusting for sociodemographics, medical comorbidities, and facility factors. Results The cohort comprised 89 791 patients with a mean (SD) age of 73.0 (10.1) years; 87 647 (97.6%) were male, 9063 (10.1%) were Black, 3355 (3.7%) were Hispanic, and 77 373 (86.2%) were White. Overall, 64 770 individuals (72.1%) initiated any anticoagulant, 60 362 (67.2%) initiated DOAC therapy, and 4408 (4.9%) initiated warfarin. Compared with White patients, Black and Hispanic patients had lower rates of any anticoagulant and DOAC therapy initiation but higher rates of warfarin initiation across all quartiles of VAMC racial and ethnic composition. Any anticoagulant therapy initiation was lower in Q4 than Q1 (69.8% vs 74.9%; adjusted odds ratio [aOR], 0.80; 95% CI, 0.69-0.92; P < .001). DOAC and warfarin initiation were also lower in Q4 than in Q1 (DOAC, 69.4% vs 65.3%; aOR, 0.85; 95% CI, 0.74-0.97; P < .001; warfarin, 5.4% vs 4.5%; aOR, 0.82; 95% CI, 0.67-1.00; P < .001). In adjusted models, patients in Q4 were significantly less likely to initiate any anticoagulant therapy than those in Q1 (aOR, 0.88; 95% CI, 0.78-0.99). Patients in Q3 (aOR, 0.75; 95% CI, 0.60-0.93) and Q4 (aOR, 0.69; 95% CI, 0.55-0.87) were significantly less likely to initiate warfarin therapy than those in Q1. There was no significant difference in the adjusted odds of initiating DOAC therapy across racial and ethnic composition quartiles. Although significant Black-White and Hispanic-White differences in initiation of any anticoagulant, DOAC, and warfarin therapy were observed, interactions between patient race and ethnicity and VAMC racial composition were not significant. Conclusions and Relevance In a national cohort of VA patients with AF, initiation of any anticoagulant and warfarin, but not DOAC therapy, was lower in VAMCs serving more minoritized patients.
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Affiliation(s)
- Utibe R. Essien
- Veterans Affairs Health Systems Research Center for the Study of Healthcare Innovation, Implementation and Policy, Greater Los Angeles Veterans Affairs Healthcare System, California
- Division of General Internal Medicine and Health Services Research, David Geffen School of Medicine at the University of California, Los Angeles
| | - Nadejda Kim
- Center for Health Equity Research and Promotion, Veterans Affairs Pittsburgh Healthcare System, Pennsylvania
| | - Leslie R. M. Hausmann
- Center for Health Equity Research and Promotion, Veterans Affairs Pittsburgh Healthcare System, Pennsylvania
- Division of General Internal Medicine, University of Pittsburgh School of Medicine, Pennsylvania
| | - Donna L. Washington
- Division of General Internal Medicine and Health Services Research, David Geffen School of Medicine at the University of California, Los Angeles
| | - Maria K. Mor
- Center for Health Equity Research and Promotion, Veterans Affairs Pittsburgh Healthcare System, Pennsylvania
- Department of Biostatistics, University of Pittsburgh Graduate School of Public Health, Pennsylvania
| | - Terrence M. A. Litam
- Center for Health Equity Research and Promotion, Veterans Affairs Pittsburgh Healthcare System, Pennsylvania
| | - Taylor L. Boyer
- Center for Health Equity Research and Promotion, Veterans Affairs Pittsburgh Healthcare System, Pennsylvania
| | - Walid F. Gellad
- Center for Health Equity Research and Promotion, Veterans Affairs Pittsburgh Healthcare System, Pennsylvania
- Division of General Internal Medicine, University of Pittsburgh School of Medicine, Pennsylvania
| | - Michael J. Fine
- Center for Health Equity Research and Promotion, Veterans Affairs Pittsburgh Healthcare System, Pennsylvania
- Division of General Internal Medicine, University of Pittsburgh School of Medicine, Pennsylvania
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Hung A, Pura JA, Stechuchak KM, Dennis PA, Maciejewski ML, Smith VA, Blalock DV, Hoerster K, Raffa SD, Wong E. Association between a national behavioral weight management program and real-world weight change. Obes Res Clin Pract 2024; 18:201-208. [PMID: 38851989 DOI: 10.1016/j.orcp.2024.05.003] [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] [Received: 10/11/2023] [Revised: 03/29/2024] [Accepted: 05/29/2024] [Indexed: 06/10/2024]
Abstract
OBJECTIVE In a national cohort of Veterans, weight change was compared between participants in a US Department of Veterans Affairs (VA) behavioral weight management program (MOVE!) and matched non-participants, and between high-intensity and low-intensity participants. METHODS Retrospective cohort study of Veterans with 1 + MOVE! visits in 2008-2017 were matched to MOVE! non-participants via sequential stratification. Percent weight change up to two years after MOVE! initiation of participants and non-participants was modeled using generalized additive mixed models, and 1-year weight change of high-intensity or low-intensity participants was also compared. RESULTS MOVE! participants (n = 499,696) and non-participant controls (n = 1,336,172) were well-matched, with an average age of 56 years and average BMI of 35. MOVE! participants lost 1.4 % at 12 months and 1.2 % at 24 months, which was 0.89 % points (95 % CI: 0.83-0.96) more at 12 months than non-participants and 0.55 % points (95 % CI: 0.41-0.68) more at 24 months. 9.1 % of MOVE! participants had high-intensity use in one year, and they had 2.38 % point (95 % CI: 2.25-2.52) greater weight loss than low-intensity participation at 12 months (2.8 % vs 0.4 %). CONCLUSIONS Participation in VA's system-wide behavioral weight management program (MOVE!) was associated with modest weight loss, suggesting that program modifications are needed to increase Veteran engagement and program effectiveness. Future research should further explore how variations in program delivery and the use of newer anti-obesity medications may impact the program's effectiveness.
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Affiliation(s)
- Anna Hung
- Center of Innovation to Accelerate Discovery and Practice Transformation, Durham VA Medical Center, Durham, NC, USA; Department of Population Health Sciences, Duke University School of Medicine, Durham, NC, USA; Duke-Margolis Center for Health Policy, Durham, NC, USA.
| | - John A Pura
- Center of Innovation to Accelerate Discovery and Practice Transformation, Durham VA Medical Center, Durham, NC, USA; Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA
| | - Karen M Stechuchak
- Center of Innovation to Accelerate Discovery and Practice Transformation, Durham VA Medical Center, Durham, NC, USA
| | - Paul A Dennis
- Center of Innovation to Accelerate Discovery and Practice Transformation, Durham VA Medical Center, Durham, NC, USA; Department of Population Health Sciences, Duke University School of Medicine, Durham, NC, USA
| | - Matthew L Maciejewski
- Center of Innovation to Accelerate Discovery and Practice Transformation, Durham VA Medical Center, Durham, NC, USA; Department of Population Health Sciences, Duke University School of Medicine, Durham, NC, USA; Duke-Margolis Center for Health Policy, Durham, NC, USA; Division of General Internal Medicine, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Valerie A Smith
- Center of Innovation to Accelerate Discovery and Practice Transformation, Durham VA Medical Center, Durham, NC, USA; Department of Population Health Sciences, Duke University School of Medicine, Durham, NC, USA; Division of General Internal Medicine, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Dan V Blalock
- Center of Innovation to Accelerate Discovery and Practice Transformation, Durham VA Medical Center, Durham, NC, USA; Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA
| | - Katherine Hoerster
- Health Services Research & Development Center of Innovation for Veteran-Centered and Value-Driven Care, Veterans Affairs Puget Sound Health Care System, Seattle, WA, USA; Department of Health Services, University of Washington, Seattle, WA, USA; School of Medicine, Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, USA
| | - Susan D Raffa
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA; National Center for Health Promotion and Disease Prevention, Veterans Health Administration, Durham, NC, USA
| | - Edwin Wong
- Health Services Research & Development Center of Innovation for Veteran-Centered and Value-Driven Care, Veterans Affairs Puget Sound Health Care System, Seattle, WA, USA; Department of Health Services, University of Washington, Seattle, WA, USA
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Wang R, Rouleau G, Booth GL, Brazeau AS, El-Dassouki N, Taylor M, Cafazzo JA, Greenberg M, Nakhla M, Shulman R, Desveaux L. Understanding Whether and How a Digital Health Intervention Improves Transition Care for Emerging Adults Living With Type 1 Diabetes: Protocol for a Mixed Methods Realist Evaluation. JMIR Res Protoc 2023; 12:e46115. [PMID: 37703070 PMCID: PMC10534286 DOI: 10.2196/46115] [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: 01/31/2023] [Revised: 06/27/2023] [Accepted: 07/24/2023] [Indexed: 09/14/2023] Open
Abstract
BACKGROUND Emerging adults living with type 1 diabetes (T1D) face a series of challenges with self-management and decreased health system engagement, leading to an increased risk of acute complications and hospital admissions. Effective and scalable strategies are needed to support this population to transfer seamlessly from pediatric to adult care with sufficient self-management capability. While digital health interventions for T1D self-management are a promising strategy, it remains unclear which elements work, how, and for which groups of individuals. OBJECTIVE This study aims to evaluate the design and implementation of a multicomponent SMS text message-based digital health intervention to support emerging adults living with T1D in real-world settings. The objectives are to identify the intervention components and associated mechanisms that support user engagement and T1D health care transition experiences and determine the individual characteristics that influence the implementation process. METHODS We used a realist evaluation embedded alongside a randomized controlled trial, which uses a sequential mixed methods design to analyze data from multiple sources, including intervention usage data, patient-reported outcomes, and realist interviews. In step 1, we conducted a document analysis to develop a program theory that outlines the hypothesized relationships among "individual-level contextual factors, intervention components and features, mechanisms, and outcomes," with special attention paid to user engagement. Among them, intervention components and features depict 10 core characteristics such as transition support information, problem-solving information, and real-time interactivity. The proximal outcomes of interest include user engagement, self-efficacy, and negative emotions, whereas the distal outcomes of interest include transition readiness, self-blood glucose monitoring behaviors, and blood glucose. In step 2, we plan to conduct semistructured realist interviews with the randomized controlled trial's intervention-arm participants to test the hypothesized "context-intervention-mechanism-outcome" configurations. In step 3, we plan to triangulate all sources of data using a coincidence analysis to identify the necessary combinations of factors that determine whether and how the desired outcomes are achieved and use these insights to consolidate the program theory. RESULTS For step 1 analysis, we have developed the initial program theory and the corresponding data collection plan. For step 2 analysis, participant enrollment for the randomized controlled trial started in January 2023. Participant enrollment for this realist evaluation was anticipated to start in July 2023 and continue until we reached thematic saturation or achieved informational power. CONCLUSIONS Beyond contributing to knowledge on the multiple pathways that lead to successful engagement with a digital health intervention as well as target outcomes in T1D care transitions, embedding the realist evaluation alongside the trial may inform real-time intervention refinement to improve user engagement and transition experiences. The knowledge gained from this study may inform the design, implementation, and evaluation of future digital health interventions that aim to improve transition experiences. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) PRR1-10.2196/46115.
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Affiliation(s)
- Ruoxi Wang
- Institute for Better Health, Trillium Health Partners, Mississauga, ON, Canada
| | - Geneviève Rouleau
- Institute for Health System Solutions and Virtual Care, Women's College Hospital, Toronto, ON, Canada
- Département des Sciences Infirmières, Université du Québec en Outaouais, St-Jérôme, QC, Canada
- Faculté des sciences infirmières, l'Université de Montréal, Montreal, QC, Canada
| | - Gillian Lynn Booth
- MAP Centre for Urban Health Solutions, Unity Health Toronto, Toronto, ON, Canada
- Department of Medicine, University of Toronto, Toronto, ON, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
| | | | - Noor El-Dassouki
- Centre for Digital Therapeutics, Toronto General Hospital, University Health Network, Toronto, ON, Canada
| | - Madison Taylor
- Centre for Digital Therapeutics, Toronto General Hospital, University Health Network, Toronto, ON, Canada
| | - Joseph A Cafazzo
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
- Centre for Digital Therapeutics, Toronto General Hospital, University Health Network, Toronto, ON, Canada
- Institute of Biomedical Engineering, University of Toronto, Toronto, ON, Canada
- Department of Computer Science, University of Toronto, Toronto, ON, Canada
| | - Marley Greenberg
- Department of Philosophy, Joint Centre for Bioethics, University of Toronto, Toronto, ON, Canada
- Diabetes Action Canada, Toronto, ON, Canada
| | - Meranda Nakhla
- Division of Endocrinology, Montreal Children's Hospital, McGill University, Montréal, QC, Canada
- Research Institute of the McGill University Health Centre, Montréal, QC, Canada
| | - Rayzel Shulman
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
- Child Health Evaluative Sciences, SickKids Research Institute, Toronto, ON, Canada
- Division of Endocrinology, The Hospital for Sick Children, Toronto, ON, Canada
- Department of Pediatrics, University of Toronto, Toronto, ON, Canada
| | - Laura Desveaux
- Institute for Better Health, Trillium Health Partners, Mississauga, ON, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
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Knott CL, Miech EJ, Woodard N, Huq M. The role of organizational capacity in intervention efficacy in a church-based cancer education program: A configurational analysis. GLOBAL IMPLEMENTATION RESEARCH AND APPLICATIONS 2023; 3:284-294. [PMID: 38107832 PMCID: PMC10723821 DOI: 10.1007/s43477-023-00089-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Accepted: 05/29/2023] [Indexed: 12/19/2023]
Abstract
It is well-established in the field of implementation science that the context in which an intervention is delivered can play a crucial role in how well it is implemented. However, less is known about how organizational context or capacity relates to efficacy outcomes, particularly with health promotion interventions delivered outside of healthcare settings. The present study examined whether organizational capacity indicators were linked to key efficacy outcomes in an evidence-based cancer control intervention delivered in 13 African American churches in Maryland. Outcomes included increases in colorectal cancer knowledge and self-report colonoscopy screening behavior from baseline to follow-up. We used Coincidence Analysis to identify features of organizational capacity that uniquely distinguished churches with varying levels of cancer knowledge and screening. Indicators of organizational capacity (e.g., congregation size, prior health promotion experience) were from an existing measure of church organizational capacity for health promotion. A single solution pathway accounted for greater increases in colorectal cancer knowledge over 12 months, a combination of two conditions: conducting 3 or more health promotion activities in the prior 2 years together with not receiving any technical assistance from outside partners in the prior 2 years. A single condition accounted for greater increases in colonoscopy screening over 24 months: churches that had conducted health promotion activities in 1-4 different topical areas in the prior 2 years. Findings highlight aspects of organizational capacity (e.g., prior experience in health promotion) that may facilitate intervention efficacy and can help practitioners identify organizational settings most promising for intervention impact.
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Affiliation(s)
- Cheryl L. Knott
- University of Maryland School of Public Health, Department of Behavioral and Community Health, 1234 School of Public Health Building, College Park, MD, 20742, USA
| | - Edward J. Miech
- Center for Health Services Research, Regenstrief Institute, Indianapolis, IN, USA
| | - Nathaniel Woodard
- University of Maryland School of Public Health, Department of Behavioral and Community Health, 1234 School of Public Health Building, College Park, MD, 20742, USA
| | - Maisha Huq
- University of Maryland School of Public Health, Department of Behavioral and Community Health, 1234 School of Public Health Building, College Park, MD, 20742, USA
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Damush TM, Wilkinson JR, Martin H, Miech EJ, Tang Q, Taylor S, Daggy JK, Bastin G, Islam R, Myers LJ, Penney LS, Narechania A, Schreiber SS, Williams LS. The VA National TeleNeurology Program implementation: a mixed-methods evaluation guided by RE-AIM framework. FRONTIERS IN HEALTH SERVICES 2023; 3:1210197. [PMID: 37693238 PMCID: PMC10484508 DOI: 10.3389/frhs.2023.1210197] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Accepted: 08/01/2023] [Indexed: 09/12/2023]
Abstract
Introduction The Veteran Affairs (VA) Office of Rural Health (ORH) funded the Veterans Health Administration (VHA) National TeleNeurology Program (NTNP) as an Enterprise-Wide Initiative (EWI). NTNP is an innovative healthcare delivery model designed to fill the patient access gap for outpatient neurological care especially for Veterans residing in rural communities. The specific aim was to apply the RE-AIM framework in a pragmatic evaluation of NTNP services. Materials and methods We conducted a prospective implementation evaluation. Guided by the pragmatic application of the RE-AIM framework, we conceptualized a mixed-methods evaluation for key metrics: (1) reach into the Veteran patient population assessed as total NTNP new patient consult volume and total NTNP clinical encounters (new and return); (2) effectiveness through configurational analysis of conditions leading to high Veteran satisfaction and referring providers perceived effectiveness; (3) adoption and implementation by VA sites through site staff and NTNP interviews; (4) implementation success through perceived management, implementation barriers, facilitators, and adaptations and through rapid qualitative analysis of multiple stakeholders' assessments; and (5) maintenance of NTNP through monitoring quarterly TeleNeurology consultation volume. Results NTNP was successfully implemented in 13 VA Medical Centers over 2 years. The total NTNP new patient consult volume in fiscal year 2021 (FY21) was 836 (58% rurally residing); this increased to 1,706 in fiscal year 2022 (FY22) (55% rurally residing). Total (new and follow-up) NTNP clinical encounters were 1,306 in FY21 and 3,730 in FY22. Overall, the sites reported positive experiences with program implementation and perceived that the program was serving Veterans with little access to neurological care. Veterans also reported high satisfaction with the NTNP program. We identified the patient level of perceived excellent teleneurologist-patient communications, reduced need to drive to get care, and that NTNP provided care that the Veteran otherwise could not access as key factors related to high Veteran satisfaction. Conclusions The VA NTNP demonstrated substantial reach, adoption, effectiveness, implementation success, and maintenance over the first 2 years of the program. The NTNP was highly acceptable to both the clinical providers making the referrals and the Veterans receiving the referred video care. The pragmatic application of the RE-AIM framework to guide implementation evaluations is appropriate, comprehensive, and recommended for future applications.
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Affiliation(s)
- Teresa M. Damush
- Richard L. Roudebush VAMC HSR&D EXTEND QUERI, Indianapolis, IN, United States
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, United States
- Regenstrief Institute, Inc., Indianapolis, IN, United States
| | - Jayne R. Wilkinson
- Corporal Michael J Crescenz VAMC, Philadelphia, PA, United States
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Holly Martin
- Regenstrief Institute, Inc., Indianapolis, IN, United States
| | - Edward J. Miech
- Richard L. Roudebush VAMC HSR&D EXTEND QUERI, Indianapolis, IN, United States
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, United States
- Regenstrief Institute, Inc., Indianapolis, IN, United States
| | - Qing Tang
- Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, IN, United States
| | - Stanley Taylor
- Richard L. Roudebush VAMC HSR&D EXTEND QUERI, Indianapolis, IN, United States
| | - Joanne K. Daggy
- Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, IN, United States
| | - Grace Bastin
- Richard L. Roudebush VAMC HSR&D EXTEND QUERI, Indianapolis, IN, United States
| | - Robin Islam
- Corporal Michael J Crescenz VAMC, Philadelphia, PA, United States
| | - Laura J. Myers
- Richard L. Roudebush VAMC HSR&D EXTEND QUERI, Indianapolis, IN, United States
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, United States
- Regenstrief Institute, Inc., Indianapolis, IN, United States
| | - Lauren S. Penney
- South Texas Veterans Health Care System, San Antonio, TX, United States
| | - Aditi Narechania
- Jesse Brown VAMC, Chicago, IL, United States
- University of Illinois Chicago, Chicago, IL, United States
- Northwestern University, Chicago, IL, United States
| | - Steve S. Schreiber
- Department of Neurology, University of California, Irvine, Irvine, CA, United States
| | - Linda S. Williams
- Richard L. Roudebush VAMC HSR&D EXTEND QUERI, Indianapolis, IN, United States
- Regenstrief Institute, Inc., Indianapolis, IN, United States
- Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, United States
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Dodge JR, Youles B, Caldararo J, Sears ED, Caverly TJ, Michael Ho P, Shimada SL, Kaboli P, Albright K, Robinson SA, McNeal DM, Damschroder L, Saini SD, Adams MA. Engaging Operational Partners Is Critical for Successful Implementation of Research Products: a Coincidence Analysis of Access-Related Projects in the Veterans Affairs Healthcare System. J Gen Intern Med 2023; 38:923-930. [PMID: 37340262 PMCID: PMC10356702 DOI: 10.1007/s11606-023-08115-5] [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: 06/17/2022] [Accepted: 02/24/2023] [Indexed: 06/22/2023]
Abstract
BACKGROUND/OBJECTIVE The Veterans Health Administration (VHA) has prioritized timely access to care and has invested substantially in research aimed at optimizing veteran access. However, implementing research into practice remains challenging. Here, we assessed the implementation status of recent VHA access-related research projects and explored factors associated with successful implementation. DESIGN We conducted a portfolio review of recent VHA-funded or supported projects (1/2015-7/2020) focused on healthcare access ("Access Portfolio"). We then identified projects with implementable research deliverables by excluding those that (1) were non-research/operational projects; (2) were only recently completed (i.e., completed on or after 1/1/2020, meaning that they were unlikely to have had time to be implemented); and (3) did not propose an implementable deliverable. An electronic survey assessed each project's implementation status and elicited barriers/facilitators to implementing deliverables. Results were analyzed using novel Coincidence Analysis (CNA) methods. PARTICIPANTS/KEY RESULTS Among 286 Access Portfolio projects, 36 projects led by 32 investigators across 20 VHA facilities were included. Twenty-nine respondents completed the survey for 32 projects (response rate = 88.9%). Twenty-eight percent of projects reported fully implementing project deliverables, 34% reported partially implementing deliverables, and 37% reported not implementing any deliverables (i.e., resulting tool/intervention not implemented into practice). Of 14 possible barriers/facilitators assessed in the survey, two were identified through CNA as "difference-makers" to partial or full implementation of project deliverables: (1) engagement with national VHA operational leadership; (2) support and commitment from local site operational leadership. CONCLUSIONS These findings empirically highlight the importance of operational leadership engagement for successful implementation of research deliverables. Efforts to strengthen communication and engagement between the research community and VHA local/national operational leaders should be expanded to ensure VHA's investment in research leads to meaningful improvements in veterans' care. The Veterans Health Administration (VHA) has prioritized timely access to care and has invested substantially in research aimed at optimizing veteran access. However, implementing research findings into clinical practice remains challenging, both within and outside VHA. Here, we assessed the implementation status of recent VHA access-related research projects and explored factors associated with successful implementation. Only two factors were identified as "difference-makers" to adoption of project findings into practice: (1) engagement with national VHA leadership or (2) support and commitment from local site leadership. These findings highlight the importance of leadership engagement for successful implementation of research findings. Efforts to strengthen communication and engagement between the research community and VHA local/national leaders should be expanded to ensure VHA's investment in research leads to meaningful improvements in veterans' care.
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Affiliation(s)
- Jessica R Dodge
- Center for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, MI, USA
| | - Bradley Youles
- Center for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, MI, USA
| | - Jennifer Caldararo
- Center for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, MI, USA
| | - Erika D Sears
- Center for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, MI, USA
- University of Michigan Medical School, Ann Arbor, MI, USA
- Institute for Healthcare Policy and Innovation, Ann Arbor, MI, USA
| | - Tanner J Caverly
- Center for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, MI, USA
- University of Michigan Medical School, Ann Arbor, MI, USA
- Institute for Healthcare Policy and Innovation, Ann Arbor, MI, USA
| | - P Michael Ho
- Denver-Seattle Center of Innovation for Veteran-Centered and Value-Driven Care, Rocky Mountain Regional VA Medical Center, Aurora, CO, USA
| | - Stephanie L Shimada
- VA Center for Healthcare Organization and Implementation Research, VA Bedford Healthcare System, Bedford, MA, USA
| | - Peter Kaboli
- Iowa City VA Center for Access and Delivery Research and Evaluation (CADRE), Iowa VA Healthcare System, Iowa City, IA, USA
| | - Karen Albright
- Iowa City VA Center for Access and Delivery Research and Evaluation (CADRE), Iowa VA Healthcare System, Iowa City, IA, USA
- Division of General Internal Medicine, University of Colorado School of Medicine, Aurora, CO, USA
| | - Stephanie A Robinson
- VA Center for Healthcare Organization and Implementation Research, VA Bedford Healthcare System, Bedford, MA, USA
- The Pulmonary Center, Boston University School of Medicine, Boston, MA, USA
| | - Demetria M McNeal
- Iowa City VA Center for Access and Delivery Research and Evaluation (CADRE), Iowa VA Healthcare System, Iowa City, IA, USA
- Division of General Internal Medicine, University of Colorado School of Medicine, Aurora, CO, USA
| | - Laura Damschroder
- Center for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, MI, USA
| | - Sameer D Saini
- Center for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, MI, USA
- University of Michigan Medical School, Ann Arbor, MI, USA
- Institute for Healthcare Policy and Innovation, Ann Arbor, MI, USA
- Department of Internal Medicine, Division of Gastroenterology, University of Michigan, Ann Arbor, MI, USA
| | - Megan A Adams
- Center for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, MI, USA.
- University of Michigan Medical School, Ann Arbor, MI, USA.
- Institute for Healthcare Policy and Innovation, Ann Arbor, MI, USA.
- Department of Internal Medicine, Division of Gastroenterology, University of Michigan, Ann Arbor, MI, USA.
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8
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Van Houtven CH, Drake C, Malo TL, Decosimo K, Tucker M, Sullivan C, D'Adolf J, Hughes JM, Christensen L, Grubber JM, Coffman CJ, Sperber NR, Wang V, Allen KD, Hastings SN, Shea CM, Zullig LL. Ready, set, go! The role of organizational readiness to predict adoption of a family caregiver training program using the Rogers' diffusion of innovation theory. Implement Sci Commun 2023; 4:69. [PMID: 37337208 DOI: 10.1186/s43058-023-00447-x] [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] [Received: 12/28/2022] [Accepted: 05/30/2023] [Indexed: 06/21/2023] Open
Abstract
BACKGROUND Caregivers FIRST is an evidence-based program addressing gaps in caregivers' skills. In 2020, the Veterans Health Administration Caregiver Support Program (CSP) nationally endorsed Caregivers FIRST, offering credit in leadership performance plans to encourage all VA medical centers (VAMCs) to implement locally. This study examines the association of organizational readiness with VAMC adoption of Caregivers FIRST. METHODS In a cohort observational study, we surveyed CSP managers about their facilities' readiness to implement using the Organizational Readiness for Implementing Change (ORIC) instrument and compared change commitment and change efficacy domains among VAMCs "adopters" defined as delivering Caregivers FIRST within 1 year of the national announcement to those that did not ("non-adopters"). Within "adopters," we categorized time to adoption based on Rogers' diffusion of innovation theory including "innovators," "early adopters," "early majority," "late adopters," and "laggards." Organizational readiness and site characteristics (facility complexity, staffing levels, volume of applications for caregiver assistance services) were compared between "adopters," "non-adopters," and between time to adoption subcategories. Separate logistic regression models were used to assess whether ORIC and site characteristics were associated with early adoption among "adopters." RESULTS Fifty-one of 63 (81%) VAMCs with CSP manager survey respondents adopted Caregivers FIRST during the first year. ORIC change commitment and efficacy were similar for "adopters" and "non-adopters." However, sites that adopted earlier (innovators and early adopters) had higher ORIC change commitment and efficacy scores than the rest of the "adopters." Logistic regression results indicated that higher ORIC change commitment (odds ratio [OR] = 2.57; 95% confidence interval [CI], 1.11-5.95) and ORIC change efficacy (OR = 2.60; 95% CI, 1.12-6.03) scores were associated with increased odds that a VAMC was an early adopter (categorized as an "innovator," "early adopter", or "early majority"). Site-level characteristics were not associated with Caregivers FIRST early adoption. CONCLUSIONS To our knowledge, this study is the first to prospectively assess organizational readiness and the timing of subsequent program adoption. Early adoption was associated with higher ORIC change commitment and change efficacy and not site-level characteristics. These findings yield insights into the role of organizational readiness to accelerate program adoption. TRIAL REGISTRATION ClinicalTrials.gov, NCT03474380. Registered on March 22, 2018.
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Affiliation(s)
- Courtney H Van Houtven
- Center of Innovation to Accelerate Discovery and Practice Transformation, Durham VA Health Care System (152), 508 Fulton Street, Durham, NC, 27705, USA
- Department of Population Health Sciences, Duke University, Durham, NC, USA
- Duke-Margolis Center for Health Policy, Duke University, Durham, NC, USA
| | - Connor Drake
- Center of Innovation to Accelerate Discovery and Practice Transformation, Durham VA Health Care System (152), 508 Fulton Street, Durham, NC, 27705, USA
- Department of Population Health Sciences, Duke University, Durham, NC, USA
| | - Teri L Malo
- Center of Innovation to Accelerate Discovery and Practice Transformation, Durham VA Health Care System (152), 508 Fulton Street, Durham, NC, 27705, USA
| | - Kasey Decosimo
- Center of Innovation to Accelerate Discovery and Practice Transformation, Durham VA Health Care System (152), 508 Fulton Street, Durham, NC, 27705, USA.
| | - Matthew Tucker
- Center of Innovation to Accelerate Discovery and Practice Transformation, Durham VA Health Care System (152), 508 Fulton Street, Durham, NC, 27705, USA
| | - Caitlin Sullivan
- Center of Innovation to Accelerate Discovery and Practice Transformation, Durham VA Health Care System (152), 508 Fulton Street, Durham, NC, 27705, USA
| | - Josh D'Adolf
- Center of Innovation to Accelerate Discovery and Practice Transformation, Durham VA Health Care System (152), 508 Fulton Street, Durham, NC, 27705, USA
| | - Jaime M Hughes
- Center of Innovation to Accelerate Discovery and Practice Transformation, Durham VA Health Care System (152), 508 Fulton Street, Durham, NC, 27705, USA
- Department of Implementation Science, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Section on Gerontology and Geriatric Medicine, Division of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Leah Christensen
- Veteran's Health Administration Central Office, Washington, DC, USA
| | - Janet M Grubber
- Center of Innovation to Accelerate Discovery and Practice Transformation, Durham VA Health Care System (152), 508 Fulton Street, Durham, NC, 27705, USA
- Cooperative Studies Program Coordinating Center, Veterans Affairs Boston Healthcare System, Boston, MA, USA
| | - Cynthia J Coffman
- Center of Innovation to Accelerate Discovery and Practice Transformation, Durham VA Health Care System (152), 508 Fulton Street, Durham, NC, 27705, USA
- Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, NC, USA
| | - Nina R Sperber
- Center of Innovation to Accelerate Discovery and Practice Transformation, Durham VA Health Care System (152), 508 Fulton Street, Durham, NC, 27705, USA
- Department of Population Health Sciences, Duke University, Durham, NC, USA
| | - Virginia Wang
- Center of Innovation to Accelerate Discovery and Practice Transformation, Durham VA Health Care System (152), 508 Fulton Street, Durham, NC, 27705, USA
- Department of Population Health Sciences, Duke University, Durham, NC, USA
- Duke-Margolis Center for Health Policy, Duke University, Durham, NC, USA
| | - Kelli D Allen
- Center of Innovation to Accelerate Discovery and Practice Transformation, Durham VA Health Care System (152), 508 Fulton Street, Durham, NC, 27705, USA
- Department of Medicine & Thurston Arthritis Research Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - S Nicole Hastings
- Center of Innovation to Accelerate Discovery and Practice Transformation, Durham VA Health Care System (152), 508 Fulton Street, Durham, NC, 27705, USA
- Department of Population Health Sciences, Duke University, Durham, NC, USA
- Center for the Study of Aging and Human Development, Duke University School of Medicine, Durham, NC, USA
- Geriatric Research, Education, and Clinical Center, Durham VA Health Care System, Durham, NC, USA
- Division of Geriatrics, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Christopher M Shea
- Department of Health Policy and Management, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Leah L Zullig
- Center of Innovation to Accelerate Discovery and Practice Transformation, Durham VA Health Care System (152), 508 Fulton Street, Durham, NC, 27705, USA
- Department of Population Health Sciences, Duke University, Durham, NC, USA
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Rattray NA, Miech EJ, True G, Natividad D, Laws B, Frankel RM, Kukla M. Modeling Contingency in Veteran Community Reintegration: A Mixed Methods Approach. JOURNAL OF MIXED METHODS RESEARCH 2023; 17:70-92. [PMID: 36523449 PMCID: PMC9742921 DOI: 10.1177/15586898211059616] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
Researchers need approaches for analyzing complex phenomena when assessing contingency relationships where specific conditions explain an outcome only when combined with other conditions. Using a mixed methods design, we paired configurational methods and qualitative thematic analysis to model contingency in veteran community reintegration outcomes, identifying combinations of conditions that led to success or lack of success in community reintegration among US military veterans. This pairing allowed for modeling contingency at a detailed level beyond the capabilities of either approach alone. Our analysis revealed multiple contingent relationships at work in explaining reintegration, including social support, purpose, cultural adjustment, and military separation experiences. This study contributes to the field of mixed methods by pairing a mathematical cross-case method with a qualitative method to model contingency.
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Affiliation(s)
- Nicholas A. Rattray
- Roudebush VA Medical Center,
Center for
Health Information and Communication
(CHIC), Indianapolis, IN, USA
- Department of Internal Medicine,
institution-id-type="Ringgold" />Indiana University School of
Medicine, Indianapolis, IN, USA
- institution-id-type="Ringgold" />Regenstrief Institute, Inc,
Indianapolis, IN, USA
| | - Edward J. Miech
- Roudebush VA Medical Center,
Center for
Health Information and Communication
(CHIC), Indianapolis, IN, USA
- Department of Internal Medicine,
institution-id-type="Ringgold" />Indiana University School of
Medicine, Indianapolis, IN, USA
- institution-id-type="Ringgold" />Regenstrief Institute, Inc,
Indianapolis, IN, USA
| | - Gala True
- South Central MIRECC Southeast Louisiana
Veterans Health Care System, New
Orleans, LA, USA
- Section of Community and Population
Medicine, Louisiana
State University School of Medicine,
New Orleans, LA, USA
| | - Diana Natividad
- Roudebush VA Medical Center,
Center for
Health Information and Communication
(CHIC), Indianapolis, IN, USA
| | - Brian Laws
- Roudebush VA Medical Center,
Center for
Health Information and Communication
(CHIC), Indianapolis, IN, USA
| | - Richard M. Frankel
- Roudebush VA Medical Center,
Center for
Health Information and Communication
(CHIC), Indianapolis, IN, USA
- Department of Internal Medicine,
institution-id-type="Ringgold" />Indiana University School of
Medicine, Indianapolis, IN, USA
- institution-id-type="Ringgold" />Regenstrief Institute, Inc,
Indianapolis, IN, USA
| | - Marina Kukla
- Roudebush VA Medical Center,
Center for
Health Information and Communication
(CHIC), Indianapolis, IN, USA
- institution-id-type="Ringgold" />IUPUI Department of Psychology,
Indianapolis, IN, USA
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10
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Sperber NR, Miech EJ, Clary AS, Perry K, Edwards-Orr M, Rudolph JL, Van Houtven CH, Thomas KS. Determinants of inter-organizational implementation success: A mixed-methods evaluation of Veteran Directed Care. HEALTHCARE (AMSTERDAM, NETHERLANDS) 2022; 10:100653. [PMID: 36108526 PMCID: PMC10174078 DOI: 10.1016/j.hjdsi.2022.100653] [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: 01/07/2022] [Revised: 06/16/2022] [Accepted: 08/24/2022] [Indexed: 11/19/2022]
Abstract
BACKGROUND Veteran Directed Care (VDC) aims to keep Veterans at risk for nursing home placement in their communities. VA medical centers (VAMCs) purchase VDC from third-party organizational providers who then partner with them during implementation. Experiences with VDC implementation have varied. OBJECTIVES We sought to identify conditions differentiating partnerships with higher enrollment (implementation success). METHODS We conducted a case-based study with: qualitative data on implementation determinants two and eight months after program start, directed content analysis to assign numerical scores (-2 strong barrier to +2 strong facilitator), and mathematical modeling using Coincidence Analysis (CNA) to identify key determinants of implementation success. Cases consisted of VAMCs and partnering non-VAMC organizations who started VDC during 2017 or 2018. The Consolidated Framework for Implementation Research (CFIR) guided analysis. RESULTS Eleven individual organizations within five partnerships constituted our sample. Two CFIR determinants- Networks & Communication and External Change Agent-uniquely and consistently identified implementation success. At an inter-organizational partnership level, Networks & Communications and External Change Agent +2 (i.e., present as strong facilitators) were both necessary and sufficient. At a within-organization level, Networks & Communication +2 was necessary but not sufficient for the non-VAMC providers, whereas External Change Agent +2 was necessary and sufficient for VAMCs. CONCLUSION Networks & Communication and External Change Agent played difference-making roles in inter-organizational implementation success, which differ by type of organization and level of analysis. IMPLICATIONS This multi-level approach identified crucial difference-making conditions for inter-organizational implementation success when putting a program into practice requires partnerships across multiple organizations.
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Affiliation(s)
- Nina R Sperber
- Center to Accelerate Discovery and Practice Transformation (ADAPT), Durham VA Health Care System, USA; Department of Population Health Sciences, Duke University, USA; Duke-Margolis Center for Health Policy, USA.
| | - Edward J Miech
- VA EXTEND QUERI, VA HSR&D Center for Health Information and Communication, Roudebush VA Medical Center, Indianapolis, USA
| | | | - Kathleen Perry
- Vagelos College of Physicians & Surgeons, Columbia University, USA
| | | | - James L Rudolph
- Brown University School of Public Health, USA; Providence VA Medical Center, USA
| | - Courtney Harold Van Houtven
- Center to Accelerate Discovery and Practice Transformation (ADAPT), Durham VA Health Care System, USA; Department of Population Health Sciences, Duke University, USA; Duke-Margolis Center for Health Policy, USA
| | - Kali S Thomas
- Brown University School of Public Health, USA; Providence VA Medical Center, USA
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11
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Damschroder LJ, Miech EJ, Freitag MB, Evans R, Burns JA, Raffa SD, Goldstein MG, Annis A, Spohr SA, Wiitala WL. Facility-level program components leading to population impact: a coincidence analysis of obesity treatment options within the Veterans Health Administration. Transl Behav Med 2022; 12:1029-1037. [PMID: 36408955 DOI: 10.1093/tbm/ibac051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Obesity is a well-established risk factor for increased morbidity and mortality. Comprehensive lifestyle interventions, pharmacotherapy, and bariatric surgery are three effective treatment approaches for obesity. The Veterans Health Administration (VHA) offers all three domains but in different configurations across medical facilities. Study aim was to explore the relationship between configurations of three types of obesity treatments, context, and population impact across VHA using coincidence analysis. This was a cross-sectional analysis of survey data describing weight management treatment components linked with administrative data to compute population impact for each facility. Coincidence analysis was used to identify combinations of treatment components that led to higher population impact. Facilities with higher impact were in the top two quintiles for (1) reach to eligible patients and (2) weight outcomes. Sixty-nine facilities were included in the analyses. The final model explained 88% (29/33) of the higher-impact facilities with 91% consistency (29/32) and was comprised of five distinct pathways. Each of the five pathways depended on facility complexity-level plus factors from one or more of the three domains of weight management: comprehensive lifestyle interventions, pharmacotherapy, and/or bariatric surgery. Three pathways include components from multiple treatment domains. Combinations of conditions formed "recipes" that lead to higher population impact. Our coincidence analyses highlighted both the importance of local context and how combinations of specific conditions consistently and uniquely distinguished higher impact facilities from lower impact facilities for weight management.
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Affiliation(s)
- Laura J Damschroder
- Veterans Affairs Center for Clinical Management Research, VA MIDAS QUERI Ann Arbor Healthcare System, Ann Arbor, MI, USA
| | - Edward J Miech
- Veterans Affairs Center for Health Information & Communication, VA EXTEND QUERI, Roudebush VA Medical Center, Indianapolis, IN, USA
| | - Michelle B Freitag
- Veterans Affairs Center for Clinical Management Research, VA MIDAS QUERI Ann Arbor Healthcare System, Ann Arbor, MI, USA
| | - Richard Evans
- Veterans Affairs Center for Clinical Management Research, VA MIDAS QUERI Ann Arbor Healthcare System, Ann Arbor, MI, USA
| | - Jennifer A Burns
- Veterans Affairs Center for Clinical Management Research, VA MIDAS QUERI Ann Arbor Healthcare System, Ann Arbor, MI, USA
| | - Susan D Raffa
- National Center for Health Promotion and Disease Prevention, Veterans Health Administration, Durham, NC, USA.,Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA
| | - Michael G Goldstein
- National Center for Health Promotion and Disease Prevention, Veterans Health Administration, Durham, NC, USA.,Department of Psychiatry and Human Behavior, Alpert Medical School, Brown University, Providence, RI, USA
| | - Ann Annis
- College of Nursing, Michigan State University, East Lansing, MI, USA
| | - Stephanie A Spohr
- National Center for Health Promotion and Disease Prevention, Veterans Health Administration, Durham, NC, USA
| | - Wyndy L Wiitala
- Veterans Affairs Center for Clinical Management Research, VA MIDAS QUERI Ann Arbor Healthcare System, Ann Arbor, MI, USA
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12
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Estabrooks C, Song Y, Anderson R, Beeber A, Berta W, Chamberlain S, Cummings G, Duan Y, Hayduk L, Hoben M, Iaconi A, Lanham H, Perez J, Wang J, Norton P. The Influence of Context on Implementation and Improvement: Protocol for a Mixed Methods, Secondary Analyses Study. JMIR Res Protoc 2022; 11:e40611. [PMID: 36107475 PMCID: PMC9523530 DOI: 10.2196/40611] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Revised: 07/13/2022] [Accepted: 07/30/2022] [Indexed: 12/05/2022] Open
Abstract
BACKGROUND Caring for the well-being of older adults is one of the greatest challenges in modern societies. Improving the quality of care and life for older adults and the work lives of their care providers calls for effective knowledge translation of evidence-based best practices. OBJECTIVE This study's purpose is to contribute to knowledge translation by better understanding the roles of organizational context (workplace environment) and facilitation (process or role) in implementation and improvement success. Our study has 2 goals: (1) to advance knowledge translation science by further developing and testing the Promoting Action on Research Implementation in Health Services framework (which outlines how implementation relies on the interplay of context, facilitation, and evidence) and (2) to advance research by optimizing implementation success via tailoring of modifiable elements of organizational context and facilitation. METHODS This is secondary analyses of 15 years of longitudinal data from the Translating Research in Elder Care (TREC) program's multiple data sources. This research is ongoing in long-term care (LTC) homes in western Canada. TREC data include the following: 5 waves of survey collection, 2 clinical trials, and regular ongoing outcome data for LTC residents. We will use a sequential exploratory and confirmatory mixed methods design. We will analyze qualitative and quantitative data holdings in an iterative process: (1) comprehensive reanalysis of qualitative data to derive hypotheses, (2) quantitative modeling to test hypotheses, and (3) action cycles to further refine and integrate qualitative and quantitative analyses. The research team includes 4 stakeholder panels: (1) system decision- and policy makers, (2) care home managers, (3) direct care staff, and (4) a citizen engagement group of people living with dementia and family members of LTC residents. A fifth group is our panel of external scientific advisors. Each panel will engage periodically, providing their perspectives on project direction and findings. RESULTS This study is funded by the Canadian Institutes of Health Research. Ethics approval was obtained from the University of Alberta (Pro00096541). The results of the secondary analyses are expected by the end of 2023. CONCLUSIONS The project will advance knowledge translation science by deepening our understanding of the roles of context, the interactions between context and facilitation, and their influence on resident and staff quality outcomes. Importantly, findings will inform understanding of the mechanisms by which context and facilitation affect the success of implementation and offer insights into factors that influence the implementation success of interventions in nursing homes. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) DERR1-10.2196/40611.
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Affiliation(s)
| | - Yuting Song
- School of Nursing, Qingdao University, Qingdao, China
| | - Ruth Anderson
- School of Nursing, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Anna Beeber
- School of Nursing, Johns Hopkins University, Baltimore, MD, United States
| | - Whitney Berta
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
| | | | - Greta Cummings
- Faculty of Nursing, University of Alberta, Edmonton, AB, Canada
| | - Yinfei Duan
- Faculty of Nursing, University of Alberta, Edmonton, AB, Canada
| | - Leslie Hayduk
- Faculty of Nursing, University of Alberta, Edmonton, AB, Canada
| | - Matthias Hoben
- Faculty of Nursing, University of Alberta, Edmonton, AB, Canada
| | - Alba Iaconi
- Faculty of Nursing, University of Alberta, Edmonton, AB, Canada
| | - Holly Lanham
- Department of Medicine, University of Texas Health Sciences Center San Antonio, San Antonio, TX, United States
| | - Janelle Perez
- School of Nursing, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Jing Wang
- School of Nursing, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Peter Norton
- Department of Family Medicine, University of Calgary, Calgary, AB, Canada
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13
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Mulrooney M, Smith M, Sobieraj D, Shipley B, Miech E. Factors Influencing Primary Care Organization Commitment to Technical Assistance Services for Clinical Pharmacist Integration Using Configurational Comparative Methods. J Am Pharm Assoc (2003) 2022; 62:1564-1571. [DOI: 10.1016/j.japh.2022.03.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Revised: 03/03/2022] [Accepted: 03/24/2022] [Indexed: 11/28/2022]
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14
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Knott CL, Miech EJ, Slade J, Woodard N, Robinson-Shaneman BJ, Huq M. Evaluation of organizational capacity in the implementation of a church-based cancer education program. GLOBAL IMPLEMENTATION RESEARCH AND APPLICATIONS 2022; 2:22-33. [PMID: 35392361 PMCID: PMC8983006 DOI: 10.1007/s43477-021-00033-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
Implementation evaluations have increasingly taken into account how features of local context help determine implementation outcomes. The purpose of this study was to determine which contextual features of organizational capacity led directly to the RE-AIM Framework implementation outcomes of intervention reach and number of days taken to implement, in an implementation trial of a series of cancer education workshops conducted across 13 African American churches in Maryland. We used a configurational approach with Coincidence Analysis to identify specific features of organizational capacity that uniquely distinguished churches with implementation success from those that were less successful. Aspects of organizational capacity (e.g., congregation size, staffing/volunteers, health ministry experience) were drawn from an existing measure of church organizational capacity for health promotion. Solution pathways leading to higher intervention reach included: having a health ministry in place for 1-4 years; or having fewer than 100 members; or mid-size churches that had conducted health promotion activities in 1-4 different topics in the past 2 years. Solution pathways to implementing the intervention in fewer number of days included: having conducted 1-2 health promotion activities in the past 2 years; or having 1-5 part-time staff and a pastor without additional outside employment; or churches with a doctorally prepared pastor and a weekly attendance of 101-249 members. Study findings can inform future theory, research, and practice in implementation of evidence-based health promotion interventions delivered in faith-based and other limited-resource community settings. Findings support the important role of organizational capacity in implementation outcomes in these settings.
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Affiliation(s)
- Cheryl L. Knott
- University of Maryland School of Public Health, Department of Behavioral and Community Health, 1234 School of Public Health Building, College Park, MD, 20742, USA.,Corresponding author: Cheryl L. Knott, PhD, University of Maryland School of Public Health, 1234W School of Public Health Building, College Park, MD 20742. Phone: 301-405-6659; Fax: 301-314-9167; ; Twitter: ChampUMD; Tumblr: champlabumd
| | - Edward J. Miech
- Center for Health Services Research, Regenstrief Institute, Indianapolis, IN, USA
| | - Jimmie Slade
- Community Ministry of Prince George’s County, PO Box 250, Upper Marlboro, MD 20773, USA
| | - Nathaniel Woodard
- University of Maryland School of Public Health, Department of Behavioral and Community Health, 1234 School of Public Health Building, College Park, MD, 20742, USA
| | | | - Maisha Huq
- University of Maryland School of Public Health, Department of Behavioral and Community Health, 1234 School of Public Health Building, College Park, MD, 20742, USA
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15
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Evans R, Burns J, Damschroder L, Annis A, Freitag MB, Raffa S, Wiitala W. Deriving Weight from Big Data: A Comparison of Body Weight Measurement Cleaning Algorithms (Preprint). JMIR Med Inform 2021; 10:e30328. [PMID: 35262492 PMCID: PMC8943548 DOI: 10.2196/30328] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Revised: 09/30/2021] [Accepted: 01/02/2022] [Indexed: 01/10/2023] Open
Abstract
Background Patient body weight is a frequently used measure in biomedical studies, yet there are no standard methods for processing and cleaning weight data. Conflicting documentation on constructing body weight measurements presents challenges for research and program evaluation. Objective In this study, we aim to describe and compare methods for extracting and cleaning weight data from electronic health record databases to develop guidelines for standardized approaches that promote reproducibility. Methods We conducted a systematic review of studies published from 2008 to 2018 that used Veterans Health Administration electronic health record weight data and documented the algorithms for constructing patient weight. We applied these algorithms to a cohort of veterans with at least one primary care visit in 2016. The resulting weight measures were compared at the patient and site levels. Results We identified 496 studies and included 62 (12.5%) that used weight as an outcome. Approximately 48% (27/62) included a replicable algorithm. Algorithms varied from cutoffs of implausible weights to complex models using measures within patients over time. We found differences in the number of weight values after applying the algorithms (71,961/1,175,995, 6.12% to 1,175,177/1,175,995, 99.93% of raw data) but little difference in average weights across methods (93.3, SD 21.0 kg to 94.8, SD 21.8 kg). The percentage of patients with at least 5% weight loss over 1 year ranged from 9.37% (4933/52,642) to 13.99% (3355/23,987). Conclusions Contrasting algorithms provide similar results and, in some cases, the results are not different from using raw, unprocessed data despite algorithm complexity. Studies using point estimates of weight may benefit from a simple cleaning rule based on cutoffs of implausible values; however, research questions involving weight trajectories and other, more complex scenarios may benefit from a more nuanced algorithm that considers all available weight data.
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Affiliation(s)
- Richard Evans
- Center for Clinical Management Research, Veterans Health Administration, Ann Arbor, MI, United States
| | - Jennifer Burns
- Center for Clinical Management Research, Veterans Health Administration, Ann Arbor, MI, United States
| | - Laura Damschroder
- Center for Clinical Management Research, Veterans Health Administration, Ann Arbor, MI, United States
| | - Ann Annis
- Center for Clinical Management Research, Veterans Health Administration, Ann Arbor, MI, United States
- College of Nursing, Michigan State University, Lansing, MI, United States
| | - Michelle B Freitag
- Center for Clinical Management Research, Veterans Health Administration, Ann Arbor, MI, United States
| | - Susan Raffa
- National Center for Health Promotion and Disease Prevention, Veterans Health Administration, Durham, NC, United States
- Department of Psychiatry & Behavioral Sciences, Duke University School of Medicine, Durham, NC, United States
| | - Wyndy Wiitala
- Center for Clinical Management Research, Veterans Health Administration, Ann Arbor, MI, United States
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