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Dodge J, Sullivan K, Miech E, Clomax A, Riviere L, Castro C. Exploring the Social Determinants of Mental Health by Race and Ethnicity in Army Wives. J Racial Ethn Health Disparities 2024; 11:669-684. [PMID: 36952121 PMCID: PMC10933139 DOI: 10.1007/s40615-023-01551-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 01/26/2023] [Accepted: 02/22/2023] [Indexed: 03/24/2023]
Abstract
OBJECTIVE To explore the social determinants of mental health (SDoMH) by race/ethnicity in a sample with equal access to healthcare. Using an adaptation of the World Health Organization's SDoMH Framework, this secondary analysis examines the socio-economic factors that make up the SDoMH by race/ethnicity. METHOD This paper employed configurational comparative methods (CCMs) to analyze various racial/ethnic subsets from quantitative survey data from (N = 327) active-duty Army wives. Data was collected in 2012 by Walter Reed Army Institute of Research. RESULTS Initial exploratory analysis revealed the highest-scoring factors for each racial/ethnic subgroup: non-Hispanic Black: employment and a history of adverse childhood events (ACEs); Hispanic: living off post and a recent childbirth; junior enlisted non-Hispanic White: high work-family conflict and ACEs; non-Hispanic other race: high work-family conflict and not having a military history. Final analysis showed four models consistently explained clinically significant depression symptoms and four models consistently explained the absence of clinical depression symptoms, providing a solution for each racial/ethnic minority group (non-Hispanic Black, Hispanic, junior enlisted non-Hispanic White, and non-Hispanic other). DISCUSSION These findings highlight that Army wives are not a monolithic group, despite their collective exposure to military-specific stressors. These findings also highlight the potential for applying configurational approaches to gain new insights into mental health outcomes for social science and clinical researchers.
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Affiliation(s)
- Jessica Dodge
- Center for Clinical Management Research, Health Services Research and Development, VA Ann Arbor Healthcare System, Ann Arbor, MI, USA.
| | - Kathrine Sullivan
- Silver School of Social Work, New York University, 1 Washington Square North, New York, NY, 10003, USA
| | - Edward Miech
- Regenstrief Institute, Center for Health Services Research, 1101 W 10th Street, Indianapolis, IN, 46202, USA
| | - Adriane Clomax
- Center for Innovation and Research on Veterans and Military Families, Suzanne Dworak-Peck School of Social Work, 669 West 34th Street, Suite 201D, Los Angeles, CA, 90089, USA
| | - Lyndon Riviere
- Walter Reed Army Institute of Research, 503 Robert Grant Ave., Silver Spring, MD, 20910, USA
| | - Carl Castro
- Center for Innovation and Research on Veterans and Military Families, Suzanne Dworak-Peck School of Social Work, 669 West 34th Street, Suite 201D, Los Angeles, CA, 90089, USA
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Wasmuth S, Belkiewitz J, Bravata D, Horsford C, Harris A, Smith C, Austin C, Miech E. Protocol for evaluating external facilitation as a strategy to nationally implement a novel stigma reduction training tool for healthcare providers. Implement Sci Commun 2022; 3:88. [PMID: 35962426 PMCID: PMC9372956 DOI: 10.1186/s43058-022-00332-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Accepted: 07/25/2022] [Indexed: 11/10/2022] Open
Abstract
Abstract
Background
Identity Development Evolution and Sharing (IDEAS) is a theatre-based intervention for reducing healthcare provider stigma. IDEAS films are created by collecting narratives from people who have experienced discrimination and healthcare inequity, partnering with professional playwrights to create theatrical scripts that maintain the words of the narratives while arranging them into compelling storylines involving several interviews, and hiring professional actors to perform and record scenes. IDEAS implementation requires a moderator to establish a respectful learning environment, play the filmed performance, set ground rules for discussion, and moderate a discussion between healthcare providers who viewed the film and invited panelists who are members of the minoritized population being discussed. IDEAS’ impact on provider stigma is measured via pre/post Acceptance and Action Questionnaire – Stigma (AAQ-S) data collected from participating providers. The objectives of this manuscript are to provide narrative review of how provider stigma may lead to healthcare inequity and health disparities, describe the conceptual frameworks underpinning the IDEAS intervention, and outline methods for IDEAS implementation and implementation evaluation.
Methods
This manuscript describes a hybrid type 3 design study protocol that uses the Consolidated Framework for Implementation Research (CFIR) to evaluate external facilitation, used as an implementation strategy to expand the reach of IDEAS. CFIR is also used to assess the impact of characteristics of the intervention and implementation climate on implementation success. Implementation success is defined by intervention feasibility and acceptability as well as self-efficacy of internal facilitators. This manuscript details the protocol for collection and evaluation of implementation data alongside that of effectiveness data. The manuscript provides new information about the use of configurational analysis, which uses Boolean algebra to analyze pathways to implementation success considering each variable, within and across diverse clinical sites across the USA.
Discussion
The significance of this protocol is that it outlines important information for future hybrid type 3 designs wishing to incorporate configurational analyses and/or studies using behavioral or atypical, complex, innovative interventions. The current lack of evidence supporting occupational justice-focused interventions and the strong evidence of stigma influencing health inequities underscore the necessity for the IDEAS intervention.
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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] [What about the content of this article? (0)] [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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Homoya B, Damush T, Rattray N, Miech E, Myers L, Marks D, Baskerville J, Fahner J, Perkins A, Murphy L, Cheatham A, Myers J, Williams L, Bravata D. Abstract WP452: Nurses Use Real-Time Patient Identification Tool to Improve Care Coordination for Transient Ischemic Attack Patients. Stroke 2020. [DOI: 10.1161/str.51.suppl_1.wp452] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background:
Programs emphasizing early evaluation and management have reduced 70% of transient ischemic attack (TIA) patients’ recurrent events. One barrier to guideline-concordant care is inadequate care coordination.
Purpose:
Our objective was to evaluate adoption of nurse care coordination programs on TIA care quality at two Veteran Health Administration (VHA) facilities.
Methods:
Nurse care coordination programs with real-time patient identification and using Consolidated Framework for Implementation Research (CFIR) to guide local adoption, were evaluated at 2 VHA facilities. Programs were coordinated by an Emergency Department (ED) Nurse Navigator or Neurology Stroke Nurse Coordinator. The nurses used a Patient Identification Tool which was updated daily and displayed: TIA patient’s name, event and discharge dates, diagnosis, visit type (ED or inpatient), and primary care team. Nurses reviewed patients’ charts for key care components (e.g., medications), identified gaps in care, and provided follow-up. TIA care quality was evaluated by Without Fail Rate (WFR) which describes the facility-level proportion of patients who received all eligible processes of care (anticoagulation for atrial fibrillation, antithrombotics, brain imaging, carotid artery imaging, hypertension control, moderate/high intensity statin, neurology consultation).
Results:
We compared the WFR before (Fiscal Year [FY] 2017) and after (FY2019) implementation of the care coordination programs: Site-1, 59.6% (N=48) to 71.4% (N=30), p=0.332 (not significant); Site-2, 15.9% (N=47) to 38.5% (N=29), p=0.045 (significant). The individual process of care with greatest improvement was high/moderate potency statin at Site-1 (68.4% to 82.6%, p=0.250 [not significant]) and neurology consultation at Site-2 (39.5% to 80.8%, p=0.001 [significant]).
Conclusions:
Nurse care coordination programs using real-time patient identification were associated with improved quality of care. These broadly generalizable programs were important components of a comprehensive, multidisciplinary quality improvement initiative. Healthcare systems interested in improving care for TIA patients may find real-time patient identification useful in coordinating their care.
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Williams LS, Patel H, Martin H, Rattray N, Miech E, Savoy A, Graham G, Martini S, Anderson J, Damush T. Abstract TP384: Effective Communication and Engagement Cultivates Teamwork Among Virtual Telestroke Providers. Stroke 2019. [DOI: 10.1161/str.50.suppl_1.tp384] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background:
In most hub-and-spoke telestroke systems, geographically co-located hub stroke specialists support regional spoke sites. In the VA’s National Telestroke Program (NTSP), a virtual hub of stroke specialists located around the country provides 24/7 consults nationwide. We examined how stroke specialists adapted to virtual teamwork, and identified factors important in developing and sustaining a high-functioning virtual team.
Methods:
Semi-structured, confidential interviews with hub stroke specialists were audiotaped and transcribed. Probes were used to explore the extent to which providers had developed a sense of a teamness or a community of practice, and what factors helped or hindered this development. Core elements of a high-functioning team were defined using Mitchell's taxonomy, developed as part of the IOM's Best Practices Innovation Collaborative. Each interview transcript was independently coded by two investigators using NVivo11. The constant comparative method and matrix displays were used to identify themes, with special attention to themes about team, communication, trust, and satisfaction.
Results:
Of 13 hub providers with > 8 months NTSP participation, 12 were interviewed; 7 had prior telestroke experience. Participants reported high levels of trust and sense of teamwork with their virtual colleagues, sometimes even more than with local colleagues. Factors facilitating perceived teamness included communicating via a weekly case conference call, a sense of transparency in discussing challenges, engagement in NTSP development tasks, and leadership support. Lack of in-person contact decreased perceived teamness, but having an in-person NTSP meeting helped mitigate this issue. Despite technical challenges, providers reported high levels of satisfaction with the NTSP.
Conclusions:
Practicing as a virtual Telestroke hub provider can provide an equal or greater sense of trust and sense of teamwork with colleagues compared with traditional practice. Engaging in transparent discussion of challenging cases and contributing to program improvements may be key to promoting high-functioning virtual teams. Ongoing surveys will assess providers’ satisfaction with program outcomes over time.
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Affiliation(s)
| | | | | | | | | | | | - Glenn Graham
- VA National Telestroke Program, San Francisco, CA
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Chambers D, Simpson L, Neta G, Schwarz UVT, Percy-Laurry A, Aarons GA, Neta G, Brownson R, Vogel A, Stirman SW, Sherr K, Sturke R, Norton WE, Varley A, Chambers D, Vinson C, Klesges L, Heurtin-Roberts S, Massoud MR, Kimble L, Beck A, Neely C, Boggs J, Nichols C, Wan W, Staab E, Laiteerapong N, Moise N, Shah R, Essock S, Handley M, Jones A, Carruthers J, Davidson K, Peccoralo L, Sederer L, Molfenter T, Scudder A, Taber-Thomas S, Schaffner K, Herschell A, Woodward E, Pitcock J, Ritchie M, Kirchner J, Moore JE, Khan S, Rashid S, Park J, Courvoisier M, Straus S, Blonigen D, Rodriguez A, Manfredi L, Nevedal A, Rosenthal J, Smelson D, Timko C, Stadnick N, Regan J, Barnett M, Lau A, Brookman-Frazee L, Guerrero E, Fenwick K, Kong Y, Aarons G, Lengnick-Hall R, Fenwick K, Henwood B, Sayer N, Rosen C, Orazem R, Smith B, Rosen C, Zimmerman L, Lounsbury D, Rosen C, Kimerling R, Trafton JA, Lindley S, Bhargava R, Roberts H, Gibson L, Escobar GJ, Liu V, Turk B, Ragins A, Kipnis P, Gruszkowski AK, Kennedy MW, Drobek ER, Turgeman L, Milicevic AS, Hubert TL, Myaskovsky L, Tjader YC, Monte RJ, Sapnas KG, Ramly E, Lauver DR, Bartels CM, Elnahal S, Ippolito A, Peabody H, Clancy C, Cebul R, Love T, Einstadter D, Bolen S, Watts B, Yakovchenko V, Park A, Lukesh W, Miller DR, Thornton D, Drainoni ML, Gifford AL, Smith S, Kyle J, Bauer MS, Eisenberg D, Liebrecht C, Barbaresso M, Kilbourne A, Park E, Perez G, Ostroff J, Greene S, Parchman M, Austin B, Larson E, Ferreri S, Shea C, Smith M, Turner K, Bacci J, Bigham K, Curran G, Ferreri S, Frail C, Hamata C, Jankowski T, Lantaff W, McGivney MS, Snyder M, McCullough M, Gillespie C, Petrakis BA, Jones E, Park A, Lukas CV, Rose A, Shoemaker SJ, Curran G, Thomas J, Teeter B, Swan H, Teeter B, Thomas J, Curran G, Balamurugan A, Lane-Fall M, Beidas R, Di Taranti L, Buddai S, Hernandez ET, Watts J, Fleisher L, Barg F, Miake-Lye I, Olmos T, Chuang E, Rodriguez H, Kominski G, Yano B, Shortell S, Hook M, Fleisher L, Fiks A, Halkyard K, Gruver R, Sykes E, Vesco K, Beadle K, Bulkley J, Stoneburner A, Leo M, Clark A, Smith J, Smyser C, Wolf M, Trivedi S, Hackett B, Rao R, Cole FS, McGonigle R, Donze A, Proctor E, Mathur A, Sherr K, Gakidou E, Gloyd S, Audet C, Salato J, Vermund S, Amico R, Smith S, Nyirandagijimana B, Mukasakindi H, Rusangwa C, Franke M, Raviola G, Cummings M, Goldberg E, Mwaka S, Kabajaasi O, Cattamanchi A, Katamba A, Jacob S, Kenya-Mugisha N, Davis JL, Reed J, Ramaswamy R, Parry G, Sax S, Kaplan H, Huang KY, Cheng S, Yee S, Hoagwood K, McKay M, Shelley D, Ogedegbe G, Brotman LM, Kislov R, Humphreys J, Harvey G, Wilson P, Lieberthal R, Payton C, Sarfaty M, Valko G, Bolton R, Lukas CV, Hartmann C, Mueller N, Holmes SK, Bokhour B, Ono S, Crabtree B, Gordon L, Miller W, Balasubramanian B, Solberg L, Cohen D, McGraw K, Blatt A, Pittman D, McCullough M, Hartmann C, Kales H, Berlowitz D, Hudson T, Gillespie C, Helfrich C, Finley E, Garcia A, Rosen K, Tami C, McGeary D, Pugh MJ, Potter JS, Helfrich C, Stryczek K, Au D, Zeliadt S, Sayre G, Gillespie C, Leeman J, Myers A, Grant J, Wangen M, Queen T, Morshed A, Dodson E, Tabak R, Brownson RC, Sheldrick RC, Mackie T, Hyde J, Leslie L, Yanovitzky I, Weber M, Gesualdo N, Kristensen T, Stanick C, Halko H, Dorsey C, Powell B, Weiner B, Lewis C, Powell B, Weiner B, Stanick C, Halko H, Dorsey C, Lewis C, Weiner B, Dorsey C, Stanick C, Halko H, Powell B, Lewis C, Stirman SW, Carreno P, Mallard K, Masina T, Monson C, Swindle T, Curran G, Patterson Z, Whiteside-Mansell L, Hanson R, Saunders B, Schoenwald S, Moreland A, Birken S, Powell B, Presseau J, Miake-Lye I, Ganz D, Mittman B, Delevan D, Finley E, Hill JN, Locatelli S, Bokhour B, Fix G, Solomon J, Mueller N, Lavela SL, Scott V, Scaccia J, Alia K, Skiles B, Wandersman A, Wilson P, Sales A, Roberts M, Kennedy A, Chambers D, Khoury MJ, Sperber N, Orlando L, Carpenter J, Cavallari L, Denny J, Elsey A, Fitzhenry F, Guan Y, Horowitz C, Johnson J, Madden E, Pollin T, Pratt V, Rakhra-Burris T, Rosenman M, Voils C, Weitzel K, Wu R, Damschroder L, Lu C, Ceccarelli R, Mazor KM, Wu A, Rahm AK, Buchanan AH, Schwartz M, McCormick C, Manickam K, Williams MS, Murray MF, Escoffery NC, Lebow-Skelley E, Udelson H, Böing E, Fernandez ME, Wood RJ, Mullen PD, Parekh J, Caldas V, Stuart EA, Howard S, Thomas G, Jennings JM, Torres J, Markham C, Shegog R, Peskin M, Rushing SC, Gaston A, Gorman G, Jessen C, Williamson J, Ward D, Vaughn A, Morris E, Mazzucca S, Burney R, Ramanadhan S, Minsky S, Martinez-Dominguez V, Viswanath K, Barker M, Fahim M, Ebnahmady A, Dragonetti R, Selby P, Farrell M, Tompkins J, Norton W, Rapport K, Hargreaves M, Lee R, Ramanadhan S, Kruse G, Deutsch C, Lanier E, Gray A, Leppin A, Christiansen L, Schaepe K, Egginton J, Branda M, Gaw C, Dick S, Montori V, Shah N, Korn A, Hovmand P, Fullerton K, Zoellner N, Hennessy E, Tovar A, Hammond R, Economos C, Kay C, Gazmararian J, Vall E, Cheung P, Franks P, Barrett-Williams S, Weiss P, Kay C, Gazmararian J, Hamilton E, Cheung P, Kay C, Vall E, Gazmararian J, Marques L, Dixon L, Ahles E, Valentine S, Monson C, Shtasel D, Stirman SW, Parra-Cardona R, Northridge M, Kavathe R, Zanowiak J, Wyatt L, Singh H, Islam N, Monteban M, Freedman D, Bess K, Walsh C, Matlack K, Flocke S, Baily H, Harden S, Ramalingam N, Alia K, Scaccia J, Scott V, Ramaswamy R, Wandersman A, Gold R, Cottrell E, Hollombe C, Dambrun K, Bunce A, Middendorf M, Dearing M, Cowburn S, Mossman N, Melgar G, Hopfer S, Hecht M, Ray A, Miller-Day M, BeLue R, Zimet G, Nelson EL, Kuhlman S, Doolittle G, Krebill H, Spaulding A, Levin T, Sanchez M, Landau M, Escobar P, Minian N, Selby P, Noormohamed A, Zawertailo L, Baliunas D, Giesbrecht N, Le Foll B, Samokhvalov A, Meisel Z, Polsky D, Schackman B, Mitchell J, Sevarino K, Gimbel S, Mwanza M, Nisingizwe MP, Michel C, Hirschhorn L, Lane-Fall M, Beidas R, Di Taranti L, Choudhary M, Thonduparambil D, Fleisher L, Barg F, Meissner P, Pinnock H, Barwick M, Carpenter C, Eldridge S, Grandes-Odriozola G, Griffiths C, Rycroft-Malone J, Murray E, Patel A, Sheikh A, Taylor SJC, Mittman B, Guilliford M, Pearce G, Korngiebel D, West K, Burke W, Hannon P, Harris J, Hammerback K, Kohn M, Chan GKC, Mafune R, Parrish A, Helfrich C, Beresford S, Pike KJ, Shelton R, Jandorf L, Erwin D, Charles TA, Parchman M, Baldwin LM, Ike B, Fickel J, Lind J, Cowper D, Fleming M, Sadler A, Dye M, Katzburg J, Ong M, Tubbesing S, McCullough M, Simmons M, Yakovchenko V, Harnish A, Gabrielian S, McInnes K, Smith J, Smelson D, Ferrand J, Torres E, Green A, Aarons G, Bradbury AR, Patrick-Miller LJ, Egleston BL, Domchek SM, Olopade OI, Hall MJ, Daly MB, Fleisher L, Grana G, Ganschow P, Fetzer D, Brandt A, Chambers R, Clark DF, Forman A, Gaber RS, Gulden C, Horte J, Long J, Lucas T, Madaan S, Mattie K, McKenna D, Montgomery S, Nielsen S, Powers J, Rainey K, Rybak C, Seelaus C, Stoll J, Stopfer J, Yao XS, Savage M, Miech E, Damush T, Rattray N, Myers J, Homoya B, Winseck K, Klabunde C, Langer D, Aggarwal A, Neilson E, Gunderson L, Escobar GJ, Gardner M, O’Sulleabhain L, Kroenke C, Liu V, Kipnis P. Proceedings from the 9th annual conference on the science of dissemination and implementation. Implement Sci 2017. [PMCID: PMC5414666 DOI: 10.1186/s13012-017-0575-y] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
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Bravata D, Myers L, Reeves M, Cheng E, Baye F, Ofner S, Miech E, Damush T, Sico J, Zillich A, Phipps M, Williams L, Chaturvedi S, Johanning J, Ferguson J, Yu Z, Arling G. Abstract 162: Processes of Care that are Associated With Reduced Risk of Recurrent Vascular Events Among Patients With a Transient Ischemic Attack and Minor Stroke. Stroke 2017. [DOI: 10.1161/str.48.suppl_1.162] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background:
Interventions that emphasize early evaluation and management of patients with TIA and minor stroke have demonstrated reductions in recurrent vascular events.
Objective:
To identify processes of care that were associated with reduced risk of recurrent vascular events after TIA or minor stroke.
Methods:
We identified patients with a TIA or minor stroke cared for in a Department of Veterans Affairs (VA) Emergency Department or inpatient ward (fiscal year 2011). Recurrent vascular events included ischemic stroke, myocardial infarction, heart failure, arrhythmia or death within 90-days and 1-year of discharge. 32 processes of care were examined. Defect-free care was assessed for a set of 6 processes (brain imaging, carotid artery imaging, hypertension management, high or moderate potency statin, antithrombotics, and anticoagulation for atrial fibrillation); patients who received all processes for which they were eligible passed the defect-free measure. Multivariable logistic regression with a random facility effect was used to model recurrent events. Clinically important potential confounders were forced into all models; other significant covariates were identified by backward selection.
Results:
Among 8107 patients, 14.0% had a recurrent vascular event within 90-days; 26.5% within 1-year. Three processes were associated with lower 90-day events after adjustment for 24 covariates: carotid artery imaging (adjusted OR, 0.74 [95%CI, 0.65-0.85], lipid measurement (0.80 [0.68-0.94]), and anticoagulation quality for atrial fibrillation (0.56 [0.35-0.88]). Three processes were associated with reduced 1-year events: carotid artery imaging (0.80 [0.71-0.89]), lipid measurement (0.85 [0.75-0.97]), and timely carotid stenosis intervention (0.49 [0.26-0.94]). The defect-free care rate, observed in 17.4%, was also associated with a reduction in recurrent vascular event risk both within 90-days (0.78 [0.65-0.93]) and 1-year (0.82 [0.71-0.94]).
Conclusions:
The delivery of a comprehensive set of clinical processes was associated with clinically meaningful reductions in short and longer-term risk of recurrent vascular events. Widespread implementation of these processes should be strongly considered.
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Affiliation(s)
- Dawn Bravata
- HSR&D Mail Code 11H, Richard L. Roudebush VA Med Cntr, Indianapolis, IN
| | - Laura Myers
- HSR&D Mail Code, Richard L. Roudebush VA Med Cntr, Indianapolis, IN
| | - Mat Reeves
- Dept of Epidemiology, Michigan State Univ, East Lansing, MI
| | - Eric Cheng
- Dept of Neurology, VA Greater Los Angeles Healthcare System, Los Angeles, CA
| | - Fitsum Baye
- Dept of Biostatistics, Indiana Univ Sch of Medicine, Indianapolis, IN
| | - Susan Ofner
- Dept of Biostatistics, Indiana Univ Sch of Medicine, Indianapolis, IN
| | - Edward Miech
- HSR&D Mail Code 11H, Richard L. Roudebush VA Med Cntr, Indianapolis, IN
| | - Teresa Damush
- HSR&D Mail Code 11H, Richard L. Roudebush VA Med Cntr, Indianapolis, IN
| | - Jason Sico
- Depts of Internal Medicine and Neurology, Yale Univ Sch of Medicine, New Haven, CT
| | - Alan Zillich
- Dept of Pharmacy Practice, Purdue Univ College of Pharmacy, West Lafayette, IN
| | - Michael Phipps
- Dept of Neurology, Univ of Maryland Sch of Medicine, Baltimore, MD
| | - Linda Williams
- HSR&D Mail Code 11H, Richard L. Roudebush VA Med Cntr, Indianapolis, IN
| | | | - Jason Johanning
- VA Nebraska-Western Iowa Health Care Sytem-Omaha Div, Omaha, NE
| | - Jared Ferguson
- HSR&D Mail Code 11H, Richard L. Roudebush VA Med Cntr, Indianapolis, IN
| | - Zhangsheng Yu
- HSR&D Mail Code 11H, Richard L. Roudebush VA Med Cntr, Indianapolis, IN
| | - Greg Arling
- Purdue Univ Sch of Nursing, West Lafayette, IN
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Chaturvedi S, Ofner S, Baye F, Myers LJ, Phipps M, Sico JJ, Damush T, Miech E, Reeves M, Johanning J, Williams LS, Arling G, Cheng E, Yu Z, Bravata D. Have clinicians adopted the use of brain MRI for patients with TIA and minor stroke? Neurology 2016; 88:237-244. [PMID: 27927939 DOI: 10.1212/wnl.0000000000003503] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2016] [Accepted: 10/10/2016] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND Use of MRI with diffusion-weighted imaging (DWI) can identify infarcts in 30%-50% of patients with TIA. Previous guidelines have indicated that MRI-DWI is the preferred imaging modality for patients with TIA. We assessed the frequency of MRI utilization and predictors of MRI performance. METHODS A review of TIA and minor stroke patients evaluated at Veterans Affairs hospitals was conducted with regard to medical history, use of diagnostic imaging within 2 days of presentation, and in-hospital care variables. Chart abstraction was performed in a subset of hospitals to assess clinical variables not available in the administrative data. RESULTS A total of 7,889 patients with TIA/minor stroke were included. Overall, 6,694 patients (84.9%) had CT or MRI, with 3,396/6,694 (50.7%) having MRI. Variables that were associated with increased odds of CT performance were age >80 years, prior stroke, history of atrial fibrillation, heart failure, coronary artery disease, anxiety, and low hospital complexity, while blood pressure >140/90 mm Hg and high hospital complexity were associated with increased likelihood of MRI. Diplopia (87% had MRI, p = 0.03), neurologic consultation on the day of presentation (73% had MRI, p < 0.0001), and symptom duration of >6 hours (74% had MRI, p = 0.0009) were associated with MRI performance. CONCLUSIONS Within a national health system, about 40% of patients with TIA/minor stroke had MRI performed within 2 days. Performance of MRI appeared to be influenced by several patient and facility-level variables, suggesting that there has been partial acceptance of the previous guideline that endorsed MRI for patients with TIA.
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Affiliation(s)
- Seemant Chaturvedi
- From the Miami VA Hospital (S.C.); Department of Neurology (S.C.), University of Miami Miller School of Medicine, FL; Departments of Biostatistics (S.O., F.B.), Internal Medicine (L.J.M., T.D., D.B.), Emergency Medicine (E.M.), and Neurology (L.S.W., D.B.), Indiana University School of Medicine, IUPUI; Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Stroke Quality Enhancement Research Initiative (QUERI) (L.J.M., T.D., E.M., M.R., L.S.W., G.A., D.B.); VA HSR&D Center for Health Information and Communication (CHIC) (L.J.M., T.D., E.M., L.S.W., D.B.), Richard L. Roudebush VA Medical Center, Indianapolis, IN; Department of Neurology (M.P.), University of Maryland School of Medicine, Baltimore; Clinical Epidemiology Research Center (J.J.S.), VA Connecticut Healthcare System, West Haven; Departments of Internal Medicine and Neurology (J.J.S.), Yale University School of Medicine, New Haven, CT; Regenstrief Institute (T.D., E.M., L.S.W., D.B.), Indianapolis, IN; Department of Epidemiology (M.R.), Michigan State University, East Lansing; VA Nebraska-Western Iowa Health Care System-Omaha Division (J.J.), Omaha; Department of Surgery (J.J.), University of Nebraska, Lincoln; Purdue University School of Nursing (G.A.), West Lafayette, IN; Department of Neurology (E.C.), University of California, Los Angeles School of Medicine; and SJTU-Yale Joint Center for Biostatistics (Z.Y.), New Haven, CT.
| | - Susan Ofner
- From the Miami VA Hospital (S.C.); Department of Neurology (S.C.), University of Miami Miller School of Medicine, FL; Departments of Biostatistics (S.O., F.B.), Internal Medicine (L.J.M., T.D., D.B.), Emergency Medicine (E.M.), and Neurology (L.S.W., D.B.), Indiana University School of Medicine, IUPUI; Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Stroke Quality Enhancement Research Initiative (QUERI) (L.J.M., T.D., E.M., M.R., L.S.W., G.A., D.B.); VA HSR&D Center for Health Information and Communication (CHIC) (L.J.M., T.D., E.M., L.S.W., D.B.), Richard L. Roudebush VA Medical Center, Indianapolis, IN; Department of Neurology (M.P.), University of Maryland School of Medicine, Baltimore; Clinical Epidemiology Research Center (J.J.S.), VA Connecticut Healthcare System, West Haven; Departments of Internal Medicine and Neurology (J.J.S.), Yale University School of Medicine, New Haven, CT; Regenstrief Institute (T.D., E.M., L.S.W., D.B.), Indianapolis, IN; Department of Epidemiology (M.R.), Michigan State University, East Lansing; VA Nebraska-Western Iowa Health Care System-Omaha Division (J.J.), Omaha; Department of Surgery (J.J.), University of Nebraska, Lincoln; Purdue University School of Nursing (G.A.), West Lafayette, IN; Department of Neurology (E.C.), University of California, Los Angeles School of Medicine; and SJTU-Yale Joint Center for Biostatistics (Z.Y.), New Haven, CT
| | - Fitsum Baye
- From the Miami VA Hospital (S.C.); Department of Neurology (S.C.), University of Miami Miller School of Medicine, FL; Departments of Biostatistics (S.O., F.B.), Internal Medicine (L.J.M., T.D., D.B.), Emergency Medicine (E.M.), and Neurology (L.S.W., D.B.), Indiana University School of Medicine, IUPUI; Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Stroke Quality Enhancement Research Initiative (QUERI) (L.J.M., T.D., E.M., M.R., L.S.W., G.A., D.B.); VA HSR&D Center for Health Information and Communication (CHIC) (L.J.M., T.D., E.M., L.S.W., D.B.), Richard L. Roudebush VA Medical Center, Indianapolis, IN; Department of Neurology (M.P.), University of Maryland School of Medicine, Baltimore; Clinical Epidemiology Research Center (J.J.S.), VA Connecticut Healthcare System, West Haven; Departments of Internal Medicine and Neurology (J.J.S.), Yale University School of Medicine, New Haven, CT; Regenstrief Institute (T.D., E.M., L.S.W., D.B.), Indianapolis, IN; Department of Epidemiology (M.R.), Michigan State University, East Lansing; VA Nebraska-Western Iowa Health Care System-Omaha Division (J.J.), Omaha; Department of Surgery (J.J.), University of Nebraska, Lincoln; Purdue University School of Nursing (G.A.), West Lafayette, IN; Department of Neurology (E.C.), University of California, Los Angeles School of Medicine; and SJTU-Yale Joint Center for Biostatistics (Z.Y.), New Haven, CT
| | - Laura J Myers
- From the Miami VA Hospital (S.C.); Department of Neurology (S.C.), University of Miami Miller School of Medicine, FL; Departments of Biostatistics (S.O., F.B.), Internal Medicine (L.J.M., T.D., D.B.), Emergency Medicine (E.M.), and Neurology (L.S.W., D.B.), Indiana University School of Medicine, IUPUI; Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Stroke Quality Enhancement Research Initiative (QUERI) (L.J.M., T.D., E.M., M.R., L.S.W., G.A., D.B.); VA HSR&D Center for Health Information and Communication (CHIC) (L.J.M., T.D., E.M., L.S.W., D.B.), Richard L. Roudebush VA Medical Center, Indianapolis, IN; Department of Neurology (M.P.), University of Maryland School of Medicine, Baltimore; Clinical Epidemiology Research Center (J.J.S.), VA Connecticut Healthcare System, West Haven; Departments of Internal Medicine and Neurology (J.J.S.), Yale University School of Medicine, New Haven, CT; Regenstrief Institute (T.D., E.M., L.S.W., D.B.), Indianapolis, IN; Department of Epidemiology (M.R.), Michigan State University, East Lansing; VA Nebraska-Western Iowa Health Care System-Omaha Division (J.J.), Omaha; Department of Surgery (J.J.), University of Nebraska, Lincoln; Purdue University School of Nursing (G.A.), West Lafayette, IN; Department of Neurology (E.C.), University of California, Los Angeles School of Medicine; and SJTU-Yale Joint Center for Biostatistics (Z.Y.), New Haven, CT
| | - Mike Phipps
- From the Miami VA Hospital (S.C.); Department of Neurology (S.C.), University of Miami Miller School of Medicine, FL; Departments of Biostatistics (S.O., F.B.), Internal Medicine (L.J.M., T.D., D.B.), Emergency Medicine (E.M.), and Neurology (L.S.W., D.B.), Indiana University School of Medicine, IUPUI; Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Stroke Quality Enhancement Research Initiative (QUERI) (L.J.M., T.D., E.M., M.R., L.S.W., G.A., D.B.); VA HSR&D Center for Health Information and Communication (CHIC) (L.J.M., T.D., E.M., L.S.W., D.B.), Richard L. Roudebush VA Medical Center, Indianapolis, IN; Department of Neurology (M.P.), University of Maryland School of Medicine, Baltimore; Clinical Epidemiology Research Center (J.J.S.), VA Connecticut Healthcare System, West Haven; Departments of Internal Medicine and Neurology (J.J.S.), Yale University School of Medicine, New Haven, CT; Regenstrief Institute (T.D., E.M., L.S.W., D.B.), Indianapolis, IN; Department of Epidemiology (M.R.), Michigan State University, East Lansing; VA Nebraska-Western Iowa Health Care System-Omaha Division (J.J.), Omaha; Department of Surgery (J.J.), University of Nebraska, Lincoln; Purdue University School of Nursing (G.A.), West Lafayette, IN; Department of Neurology (E.C.), University of California, Los Angeles School of Medicine; and SJTU-Yale Joint Center for Biostatistics (Z.Y.), New Haven, CT
| | - Jason J Sico
- From the Miami VA Hospital (S.C.); Department of Neurology (S.C.), University of Miami Miller School of Medicine, FL; Departments of Biostatistics (S.O., F.B.), Internal Medicine (L.J.M., T.D., D.B.), Emergency Medicine (E.M.), and Neurology (L.S.W., D.B.), Indiana University School of Medicine, IUPUI; Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Stroke Quality Enhancement Research Initiative (QUERI) (L.J.M., T.D., E.M., M.R., L.S.W., G.A., D.B.); VA HSR&D Center for Health Information and Communication (CHIC) (L.J.M., T.D., E.M., L.S.W., D.B.), Richard L. Roudebush VA Medical Center, Indianapolis, IN; Department of Neurology (M.P.), University of Maryland School of Medicine, Baltimore; Clinical Epidemiology Research Center (J.J.S.), VA Connecticut Healthcare System, West Haven; Departments of Internal Medicine and Neurology (J.J.S.), Yale University School of Medicine, New Haven, CT; Regenstrief Institute (T.D., E.M., L.S.W., D.B.), Indianapolis, IN; Department of Epidemiology (M.R.), Michigan State University, East Lansing; VA Nebraska-Western Iowa Health Care System-Omaha Division (J.J.), Omaha; Department of Surgery (J.J.), University of Nebraska, Lincoln; Purdue University School of Nursing (G.A.), West Lafayette, IN; Department of Neurology (E.C.), University of California, Los Angeles School of Medicine; and SJTU-Yale Joint Center for Biostatistics (Z.Y.), New Haven, CT
| | - Teresa Damush
- From the Miami VA Hospital (S.C.); Department of Neurology (S.C.), University of Miami Miller School of Medicine, FL; Departments of Biostatistics (S.O., F.B.), Internal Medicine (L.J.M., T.D., D.B.), Emergency Medicine (E.M.), and Neurology (L.S.W., D.B.), Indiana University School of Medicine, IUPUI; Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Stroke Quality Enhancement Research Initiative (QUERI) (L.J.M., T.D., E.M., M.R., L.S.W., G.A., D.B.); VA HSR&D Center for Health Information and Communication (CHIC) (L.J.M., T.D., E.M., L.S.W., D.B.), Richard L. Roudebush VA Medical Center, Indianapolis, IN; Department of Neurology (M.P.), University of Maryland School of Medicine, Baltimore; Clinical Epidemiology Research Center (J.J.S.), VA Connecticut Healthcare System, West Haven; Departments of Internal Medicine and Neurology (J.J.S.), Yale University School of Medicine, New Haven, CT; Regenstrief Institute (T.D., E.M., L.S.W., D.B.), Indianapolis, IN; Department of Epidemiology (M.R.), Michigan State University, East Lansing; VA Nebraska-Western Iowa Health Care System-Omaha Division (J.J.), Omaha; Department of Surgery (J.J.), University of Nebraska, Lincoln; Purdue University School of Nursing (G.A.), West Lafayette, IN; Department of Neurology (E.C.), University of California, Los Angeles School of Medicine; and SJTU-Yale Joint Center for Biostatistics (Z.Y.), New Haven, CT
| | - Edward Miech
- From the Miami VA Hospital (S.C.); Department of Neurology (S.C.), University of Miami Miller School of Medicine, FL; Departments of Biostatistics (S.O., F.B.), Internal Medicine (L.J.M., T.D., D.B.), Emergency Medicine (E.M.), and Neurology (L.S.W., D.B.), Indiana University School of Medicine, IUPUI; Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Stroke Quality Enhancement Research Initiative (QUERI) (L.J.M., T.D., E.M., M.R., L.S.W., G.A., D.B.); VA HSR&D Center for Health Information and Communication (CHIC) (L.J.M., T.D., E.M., L.S.W., D.B.), Richard L. Roudebush VA Medical Center, Indianapolis, IN; Department of Neurology (M.P.), University of Maryland School of Medicine, Baltimore; Clinical Epidemiology Research Center (J.J.S.), VA Connecticut Healthcare System, West Haven; Departments of Internal Medicine and Neurology (J.J.S.), Yale University School of Medicine, New Haven, CT; Regenstrief Institute (T.D., E.M., L.S.W., D.B.), Indianapolis, IN; Department of Epidemiology (M.R.), Michigan State University, East Lansing; VA Nebraska-Western Iowa Health Care System-Omaha Division (J.J.), Omaha; Department of Surgery (J.J.), University of Nebraska, Lincoln; Purdue University School of Nursing (G.A.), West Lafayette, IN; Department of Neurology (E.C.), University of California, Los Angeles School of Medicine; and SJTU-Yale Joint Center for Biostatistics (Z.Y.), New Haven, CT
| | - Mat Reeves
- From the Miami VA Hospital (S.C.); Department of Neurology (S.C.), University of Miami Miller School of Medicine, FL; Departments of Biostatistics (S.O., F.B.), Internal Medicine (L.J.M., T.D., D.B.), Emergency Medicine (E.M.), and Neurology (L.S.W., D.B.), Indiana University School of Medicine, IUPUI; Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Stroke Quality Enhancement Research Initiative (QUERI) (L.J.M., T.D., E.M., M.R., L.S.W., G.A., D.B.); VA HSR&D Center for Health Information and Communication (CHIC) (L.J.M., T.D., E.M., L.S.W., D.B.), Richard L. Roudebush VA Medical Center, Indianapolis, IN; Department of Neurology (M.P.), University of Maryland School of Medicine, Baltimore; Clinical Epidemiology Research Center (J.J.S.), VA Connecticut Healthcare System, West Haven; Departments of Internal Medicine and Neurology (J.J.S.), Yale University School of Medicine, New Haven, CT; Regenstrief Institute (T.D., E.M., L.S.W., D.B.), Indianapolis, IN; Department of Epidemiology (M.R.), Michigan State University, East Lansing; VA Nebraska-Western Iowa Health Care System-Omaha Division (J.J.), Omaha; Department of Surgery (J.J.), University of Nebraska, Lincoln; Purdue University School of Nursing (G.A.), West Lafayette, IN; Department of Neurology (E.C.), University of California, Los Angeles School of Medicine; and SJTU-Yale Joint Center for Biostatistics (Z.Y.), New Haven, CT
| | - Jason Johanning
- From the Miami VA Hospital (S.C.); Department of Neurology (S.C.), University of Miami Miller School of Medicine, FL; Departments of Biostatistics (S.O., F.B.), Internal Medicine (L.J.M., T.D., D.B.), Emergency Medicine (E.M.), and Neurology (L.S.W., D.B.), Indiana University School of Medicine, IUPUI; Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Stroke Quality Enhancement Research Initiative (QUERI) (L.J.M., T.D., E.M., M.R., L.S.W., G.A., D.B.); VA HSR&D Center for Health Information and Communication (CHIC) (L.J.M., T.D., E.M., L.S.W., D.B.), Richard L. Roudebush VA Medical Center, Indianapolis, IN; Department of Neurology (M.P.), University of Maryland School of Medicine, Baltimore; Clinical Epidemiology Research Center (J.J.S.), VA Connecticut Healthcare System, West Haven; Departments of Internal Medicine and Neurology (J.J.S.), Yale University School of Medicine, New Haven, CT; Regenstrief Institute (T.D., E.M., L.S.W., D.B.), Indianapolis, IN; Department of Epidemiology (M.R.), Michigan State University, East Lansing; VA Nebraska-Western Iowa Health Care System-Omaha Division (J.J.), Omaha; Department of Surgery (J.J.), University of Nebraska, Lincoln; Purdue University School of Nursing (G.A.), West Lafayette, IN; Department of Neurology (E.C.), University of California, Los Angeles School of Medicine; and SJTU-Yale Joint Center for Biostatistics (Z.Y.), New Haven, CT
| | - Linda S Williams
- From the Miami VA Hospital (S.C.); Department of Neurology (S.C.), University of Miami Miller School of Medicine, FL; Departments of Biostatistics (S.O., F.B.), Internal Medicine (L.J.M., T.D., D.B.), Emergency Medicine (E.M.), and Neurology (L.S.W., D.B.), Indiana University School of Medicine, IUPUI; Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Stroke Quality Enhancement Research Initiative (QUERI) (L.J.M., T.D., E.M., M.R., L.S.W., G.A., D.B.); VA HSR&D Center for Health Information and Communication (CHIC) (L.J.M., T.D., E.M., L.S.W., D.B.), Richard L. Roudebush VA Medical Center, Indianapolis, IN; Department of Neurology (M.P.), University of Maryland School of Medicine, Baltimore; Clinical Epidemiology Research Center (J.J.S.), VA Connecticut Healthcare System, West Haven; Departments of Internal Medicine and Neurology (J.J.S.), Yale University School of Medicine, New Haven, CT; Regenstrief Institute (T.D., E.M., L.S.W., D.B.), Indianapolis, IN; Department of Epidemiology (M.R.), Michigan State University, East Lansing; VA Nebraska-Western Iowa Health Care System-Omaha Division (J.J.), Omaha; Department of Surgery (J.J.), University of Nebraska, Lincoln; Purdue University School of Nursing (G.A.), West Lafayette, IN; Department of Neurology (E.C.), University of California, Los Angeles School of Medicine; and SJTU-Yale Joint Center for Biostatistics (Z.Y.), New Haven, CT
| | - Greg Arling
- From the Miami VA Hospital (S.C.); Department of Neurology (S.C.), University of Miami Miller School of Medicine, FL; Departments of Biostatistics (S.O., F.B.), Internal Medicine (L.J.M., T.D., D.B.), Emergency Medicine (E.M.), and Neurology (L.S.W., D.B.), Indiana University School of Medicine, IUPUI; Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Stroke Quality Enhancement Research Initiative (QUERI) (L.J.M., T.D., E.M., M.R., L.S.W., G.A., D.B.); VA HSR&D Center for Health Information and Communication (CHIC) (L.J.M., T.D., E.M., L.S.W., D.B.), Richard L. Roudebush VA Medical Center, Indianapolis, IN; Department of Neurology (M.P.), University of Maryland School of Medicine, Baltimore; Clinical Epidemiology Research Center (J.J.S.), VA Connecticut Healthcare System, West Haven; Departments of Internal Medicine and Neurology (J.J.S.), Yale University School of Medicine, New Haven, CT; Regenstrief Institute (T.D., E.M., L.S.W., D.B.), Indianapolis, IN; Department of Epidemiology (M.R.), Michigan State University, East Lansing; VA Nebraska-Western Iowa Health Care System-Omaha Division (J.J.), Omaha; Department of Surgery (J.J.), University of Nebraska, Lincoln; Purdue University School of Nursing (G.A.), West Lafayette, IN; Department of Neurology (E.C.), University of California, Los Angeles School of Medicine; and SJTU-Yale Joint Center for Biostatistics (Z.Y.), New Haven, CT
| | - Eric Cheng
- From the Miami VA Hospital (S.C.); Department of Neurology (S.C.), University of Miami Miller School of Medicine, FL; Departments of Biostatistics (S.O., F.B.), Internal Medicine (L.J.M., T.D., D.B.), Emergency Medicine (E.M.), and Neurology (L.S.W., D.B.), Indiana University School of Medicine, IUPUI; Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Stroke Quality Enhancement Research Initiative (QUERI) (L.J.M., T.D., E.M., M.R., L.S.W., G.A., D.B.); VA HSR&D Center for Health Information and Communication (CHIC) (L.J.M., T.D., E.M., L.S.W., D.B.), Richard L. Roudebush VA Medical Center, Indianapolis, IN; Department of Neurology (M.P.), University of Maryland School of Medicine, Baltimore; Clinical Epidemiology Research Center (J.J.S.), VA Connecticut Healthcare System, West Haven; Departments of Internal Medicine and Neurology (J.J.S.), Yale University School of Medicine, New Haven, CT; Regenstrief Institute (T.D., E.M., L.S.W., D.B.), Indianapolis, IN; Department of Epidemiology (M.R.), Michigan State University, East Lansing; VA Nebraska-Western Iowa Health Care System-Omaha Division (J.J.), Omaha; Department of Surgery (J.J.), University of Nebraska, Lincoln; Purdue University School of Nursing (G.A.), West Lafayette, IN; Department of Neurology (E.C.), University of California, Los Angeles School of Medicine; and SJTU-Yale Joint Center for Biostatistics (Z.Y.), New Haven, CT
| | - Zhangsheng Yu
- From the Miami VA Hospital (S.C.); Department of Neurology (S.C.), University of Miami Miller School of Medicine, FL; Departments of Biostatistics (S.O., F.B.), Internal Medicine (L.J.M., T.D., D.B.), Emergency Medicine (E.M.), and Neurology (L.S.W., D.B.), Indiana University School of Medicine, IUPUI; Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Stroke Quality Enhancement Research Initiative (QUERI) (L.J.M., T.D., E.M., M.R., L.S.W., G.A., D.B.); VA HSR&D Center for Health Information and Communication (CHIC) (L.J.M., T.D., E.M., L.S.W., D.B.), Richard L. Roudebush VA Medical Center, Indianapolis, IN; Department of Neurology (M.P.), University of Maryland School of Medicine, Baltimore; Clinical Epidemiology Research Center (J.J.S.), VA Connecticut Healthcare System, West Haven; Departments of Internal Medicine and Neurology (J.J.S.), Yale University School of Medicine, New Haven, CT; Regenstrief Institute (T.D., E.M., L.S.W., D.B.), Indianapolis, IN; Department of Epidemiology (M.R.), Michigan State University, East Lansing; VA Nebraska-Western Iowa Health Care System-Omaha Division (J.J.), Omaha; Department of Surgery (J.J.), University of Nebraska, Lincoln; Purdue University School of Nursing (G.A.), West Lafayette, IN; Department of Neurology (E.C.), University of California, Los Angeles School of Medicine; and SJTU-Yale Joint Center for Biostatistics (Z.Y.), New Haven, CT
| | - Dawn Bravata
- From the Miami VA Hospital (S.C.); Department of Neurology (S.C.), University of Miami Miller School of Medicine, FL; Departments of Biostatistics (S.O., F.B.), Internal Medicine (L.J.M., T.D., D.B.), Emergency Medicine (E.M.), and Neurology (L.S.W., D.B.), Indiana University School of Medicine, IUPUI; Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Stroke Quality Enhancement Research Initiative (QUERI) (L.J.M., T.D., E.M., M.R., L.S.W., G.A., D.B.); VA HSR&D Center for Health Information and Communication (CHIC) (L.J.M., T.D., E.M., L.S.W., D.B.), Richard L. Roudebush VA Medical Center, Indianapolis, IN; Department of Neurology (M.P.), University of Maryland School of Medicine, Baltimore; Clinical Epidemiology Research Center (J.J.S.), VA Connecticut Healthcare System, West Haven; Departments of Internal Medicine and Neurology (J.J.S.), Yale University School of Medicine, New Haven, CT; Regenstrief Institute (T.D., E.M., L.S.W., D.B.), Indianapolis, IN; Department of Epidemiology (M.R.), Michigan State University, East Lansing; VA Nebraska-Western Iowa Health Care System-Omaha Division (J.J.), Omaha; Department of Surgery (J.J.), University of Nebraska, Lincoln; Purdue University School of Nursing (G.A.), West Lafayette, IN; Department of Neurology (E.C.), University of California, Los Angeles School of Medicine; and SJTU-Yale Joint Center for Biostatistics (Z.Y.), New Haven, CT
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Chambers D, Simpson L, Hill-Briggs F, Neta G, Vinson C, Chambers D, Beidas R, Marcus S, Aarons G, Hoagwood K, Schoenwald S, Evans A, Hurford M, Rubin R, Hadley T, Barg F, Walsh L, Adams D, Mandell D, Martin L, Mignogna J, Mott J, Hundt N, Kauth M, Kunik M, Naik A, Cully J, McGuire A, White D, Bartholomew T, McGrew J, Luther L, Rollins A, Salyers M, Cooper B, Funaiole A, Richards J, Lee A, Lapham G, Caldeiro R, Lozano P, Gildred T, Achtmeyer C, Ludman E, Addis M, Marx L, Bradley K, VanDeinse T, Wilson AB, Stacey B, Powell B, Bunger A, Cuddeback G, Barnett M, Stadnick N, Brookman-Frazee L, Lau A, Dorsey S, Pullmann M, Mitchell S, Schwartz R, Kirk A, Dusek K, Oros M, Hosler C, Gryczynski J, Barbosa C, Dunlap L, Lounsbury D, O’Grady K, Brown B, Damschroder L, Waltz T, Powell B, Ritchie M, Waltz T, Atkins D, Imel ZE, Xiao B, Can D, Georgiou P, Narayanan S, Berkel C, Gallo C, Sandler I, Brown CH, Wolchik S, Mauricio AM, Gallo C, Brown CH, Mehrotra S, Chandurkar D, Bora S, Das A, Tripathi A, Saggurti N, Raj A, Hughes E, Jacobs B, Kirkendall E, Loeb D, Trinkley K, Yang M, Sprowell A, Nease D, Lyon A, Lewis C, Boyd M, Melvin A, Nicodimos S, Liu F, Jungbluth N, Lyon A, Lewis C, Boyd M, Melvin A, Nicodimos S, Liu F, Jungbluth N, Flynn A, Landis-Lewis Z, Sales A, Baloh J, Ward M, Zhu X, Bennett I, Unutzer J, Mao J, Proctor E, Vredevoogd M, Chan YF, Williams N, Green P, Bernstein S, Rosner JM, DeWitt M, Tetrault J, Dziura J, Hsiao A, Sussman S, O’Connor P, Toll B, Jones M, Gassaway J, Tobin J, Zatzick D, Bradbury AR, Patrick-Miller L, Egleston B, Olopade OI, Hall MJ, Daly MB, Fleisher L, Grana G, Ganschow P, Fetzer D, Brandt A, Farengo-Clark D, Forman A, Gaber RS, Gulden C, Horte J, Long J, Chambers RL, Lucas T, Madaan S, Mattie K, McKenna D, Montgomery S, Nielsen S, Powers J, Rainey K, Rybak C, Savage M, Seelaus C, Stoll J, Stopfer J, Yao S, Domchek S, Hahn E, Munoz-Plaza C, Wang J, Delgadillo JG, Mittman B, Gould M, Liang S, Kegler MC, Cotter M, Phillips E, Hermstad A, Morton R, Beasley D, Martinez J, Riehman K, Gustafson D, Marsch L, Mares L, Quanbeck A, McTavish F, McDowell H, Brown R, Thomas C, Glass J, Isham J, Shah D, Liebschutz J, Lasser K, Watkins K, Ober A, Hunter S, Lamp K, Ewing B, Iwelunmor J, Gyamfi J, Blackstone S, Quakyi NK, Plange-Rhule J, Ogedegbe G, Kumar P, Van Devanter N, Nguyen N, Nguyen L, Nguyen T, Phuong N, Shelley D, Rudge S, Langlois E, Tricco A, Ball S, Lambert-Kerzner A, Sulc C, Simmons C, Shell-Boyd J, Oestreich T, O’Connor A, Neely E, McCreight M, Labebue A, DiFiore D, Brostow D, Ho PM, Aron D, Harvey J, McHugh M, Scanlon D, Lee R, Soltero E, Parker N, McNeill L, Ledoux T, McIsaac JL, MacLeod K, Ata N, Jarvis S, Kirk S, Purtle J, Dodson E, Brownson R, Mittman B, Curran G, Curran G, Pyne J, Aarons G, Ehrhart M, Torres E, Miech E, Miech E, Stevens K, Hamilton A, Cohen D, Padgett D, Morshed A, Patel R, Prusaczyk B, Aron DC, Gupta D, Ball S, Hand R, Abram J, Wolfram T, Hastings M, Moreland-Russell S, Tabak R, Ramsey A, Baumann A, Kryzer E, Montgomery K, Lewis E, Padek M, Powell B, Brownson R, Mamaril CB, Mays G, Branham K, Timsina L, Mays G, Hogg R, Fagan A, Shapiro V, Brown E, Haggerty K, Hawkins D, Oesterle S, Hawkins D, Catalano R, McKay V, Dolcini MM, Hoffer L, Moin T, Li J, Duru OK, Ettner S, Turk N, Chan C, Keckhafer A, Luchs R, Ho S, Mangione C, Selby P, Zawertailo L, Minian N, Balliunas D, Dragonetti R, Hussain S, Lecce J, Chinman M, Acosta J, Ebener P, Malone PS, Slaughter M, Freedman D, Flocke S, Lee E, Matlack K, Trapl E, Ohri-Vachaspati P, Taggart M, Borawski E, Parrish A, Harris J, Kohn M, Hammerback K, McMillan B, Hannon P, Swindle T, Curran G, Whiteside-Mansell L, Ward W, Holt C, Santos SL, Tagai E, Scheirer MA, Carter R, Bowie J, Haider M, Slade J, Wang MQ, Masica A, Ogola G, Berryman C, Richter K, Shelton R, Jandorf L, Erwin D, Truong K, Javier JR, Coffey D, Schrager SM, Palinkas L, Miranda J, Johnson V, Hutcherson V, Ellis R, Kharmats A, Marshall-King S, LaPradd M, Fonseca-Becker F, Kepka D, Bodson J, Warner E, Fowler B, Shenkman E, Hogan W, Odedina F, De Leon J, Hooper M, Carrasquillo O, Reams R, Hurt M, Smith S, Szapocznik J, Nelson D, Mandal P, Teufel J. Proceedings of the 8th Annual Conference on the Science of Dissemination and Implementation : Washington, DC, USA. 14-15 December 2015. Implement Sci 2016; 11 Suppl 2:100. [PMID: 27490260 PMCID: PMC4977475 DOI: 10.1186/s13012-016-0452-0] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
A1 Introduction to the 8th Annual Conference on the Science of Dissemination and Implementation: Optimizing Personal and Population Health David Chambers, Lisa Simpson D1 Discussion forum: Population health D&I research Felicia Hill-Briggs D2 Discussion forum: Global health D&I research Gila Neta, Cynthia Vinson D3 Discussion forum: Precision medicine and D&I research David Chambers S1 Predictors of community therapists’ use of therapy techniques in a large public mental health system Rinad Beidas, Steven Marcus, Gregory Aarons, Kimberly Hoagwood, Sonja Schoenwald, Arthur Evans, Matthew Hurford, Ronnie Rubin, Trevor Hadley, Frances Barg, Lucia Walsh, Danielle Adams, David Mandell S2 Implementing brief cognitive behavioral therapy (CBT) in primary care: Clinicians' experiences from the field Lindsey Martin, Joseph Mignogna, Juliette Mott, Natalie Hundt, Michael Kauth, Mark Kunik, Aanand Naik, Jeffrey Cully S3 Clinician competence: Natural variation, factors affecting, and effect on patient outcomes Alan McGuire, Dominique White, Tom Bartholomew, John McGrew, Lauren Luther, Angie Rollins, Michelle Salyers S4 Exploring the multifaceted nature of sustainability in community-based prevention: A mixed-method approach Brittany Cooper, Angie Funaiole S5 Theory informed behavioral health integration in primary care: Mixed methods evaluation of the implementation of routine depression and alcohol screening and assessment Julie Richards, Amy Lee, Gwen Lapham, Ryan Caldeiro, Paula Lozano, Tory Gildred, Carol Achtmeyer, Evette Ludman, Megan Addis, Larry Marx, Katharine Bradley S6 Enhancing the evidence for specialty mental health probation through a hybrid efficacy and implementation study Tonya VanDeinse, Amy Blank Wilson, Burgin Stacey, Byron Powell, Alicia Bunger, Gary Cuddeback S7 Personalizing evidence-based child mental health care within a fiscally mandated policy reform Miya Barnett, Nicole Stadnick, Lauren Brookman-Frazee, Anna Lau S8 Leveraging an existing resource for technical assistance: Community-based supervisors in public mental health Shannon Dorsey, Michael Pullmann S9 SBIRT implementation for adolescents in urban federally qualified health centers: Implementation outcomes Shannon Mitchell, Robert Schwartz, Arethusa Kirk, Kristi Dusek, Marla Oros, Colleen Hosler, Jan Gryczynski, Carolina Barbosa, Laura Dunlap, David Lounsbury, Kevin O'Grady, Barry Brown S10 PANEL: Tailoring Implementation Strategies to Context - Expert recommendations for tailoring strategies to context Laura Damschroder, Thomas Waltz, Byron Powell S11 PANEL: Tailoring Implementation Strategies to Context - Extreme facilitation: Helping challenged healthcare settings implement complex programs Mona Ritchie S12 PANEL: Tailoring Implementation Strategies to Context - Using menu-based choice tasks to obtain expert recommendations for implementing three high-priority practices in the VA Thomas Waltz S13 PANEL: The Use of Technology to Improve Efficient Monitoring of Implementation of Evidence-based Programs - Siri, rate my therapist: Using technology to automate fidelity ratings of motivational interviewing David Atkins, Zac E. Imel, Bo Xiao, Doğan Can, Panayiotis Georgiou, Shrikanth Narayanan S14 PANEL: The Use of Technology to Improve Efficient Monitoring of Implementation of Evidence-based Programs - Identifying indicators of implementation quality for computer-based ratings Cady Berkel, Carlos Gallo, Irwin Sandler, C. Hendricks Brown, Sharlene Wolchik, Anne Marie Mauricio S15 PANEL: The Use of Technology to Improve Efficient Monitoring of Implementation of Evidence-based Programs - Improving implementation of behavioral interventions by monitoring emotion in spoken speech Carlos Gallo, C. Hendricks Brown, Sanjay Mehrotra S16 Scorecards and dashboards to assure data quality of health management information system (HMIS) using R Dharmendra Chandurkar, Siddhartha Bora, Arup Das, Anand Tripathi, Niranjan Saggurti, Anita Raj S17 A big data approach for discovering and implementing patient safety insights Eric Hughes, Brian Jacobs, Eric Kirkendall S18 Improving the efficacy of a depression registry for use in a collaborative care model Danielle Loeb, Katy Trinkley, Michael Yang, Andrew Sprowell, Donald Nease S19 Measurement feedback systems as a strategy to support implementation of measurement-based care in behavioral health Aaron Lyon, Cara Lewis, Meredith Boyd, Abigail Melvin, Semret Nicodimos, Freda Liu, Nathanial Jungbluth S20 PANEL: Implementation Science and Learning Health Systems: Intersections and Commonalities - Common loop assay: Methods of supporting learning collaboratives Allen Flynn S21 PANEL: Implementation Science and Learning Health Systems: Intersections and Commonalities - Innovating audit and feedback using message tailoring models for learning health systems Zach Landis-Lewis S22 PANEL: Implementation Science and Learning Health Systems: Intersections and Commonalities - Implementation science and learning health systems: Connecting the dots Anne Sales S23 Facilitation activities of Critical Access Hospitals during TeamSTEPPS implementation Jure Baloh, Marcia Ward, Xi Zhu S24 Organizational and social context of federally qualified health centers and variation in maternal depression outcomes Ian Bennett, Jurgen Unutzer, Johnny Mao, Enola Proctor, Mindy Vredevoogd, Ya-Fen Chan, Nathaniel Williams, Phillip Green S25 Decision support to enhance treatment of hospitalized smokers: A randomized trial Steven Bernstein, June-Marie Rosner, Michelle DeWitt, Jeanette Tetrault, James Dziura, Allen Hsiao, Scott Sussman, Patrick O’Connor, Benjamin Toll S26 PANEL: Developing Sustainable Strategies for the Implementation of Patient-Centered Care across Diverse US Healthcare Systems - A patient-centered approach to successful community transition after catastrophic injury Michael Jones, Julie Gassaway S27 PANEL: Developing Sustainable Strategies for the Implementation of Patient-Centered Care across Diverse US Healthcare Systems - Conducting PCOR to integrate mental health and cancer screening services in primary care Jonathan Tobin S28 PANEL: Developing Sustainable Strategies for the Implementation of Patient-Centered Care across Diverse US Healthcare Systems - A comparative effectiveness trial of optimal patient-centered care for US trauma care systems Douglas Zatzick S29 Preferences for in-person communication among patients in a multi-center randomized study of in-person versus telephone communication of genetic test results for cancer susceptibility Angela R Bradbury, Linda Patrick-Miller, Brian Egleston, Olufunmilayo I Olopade, Michael J Hall, Mary B Daly, Linda Fleisher, Generosa Grana, Pamela Ganschow, Dominique Fetzer, Amanda Brandt, Dana Farengo-Clark, Andrea Forman, Rikki S Gaber, Cassandra Gulden, Janice Horte, Jessica Long, Rachelle Lorenz Chambers, Terra Lucas, Shreshtha Madaan, Kristin Mattie, Danielle McKenna, Susan Montgomery, Sarah Nielsen, Jacquelyn Powers, Kim Rainey, Christina Rybak, Michelle Savage, Christina Seelaus, Jessica Stoll, Jill Stopfer, Shirley Yao and Susan Domchek S30 Working towards de-implementation: A mixed methods study in breast cancer surveillance care Erin Hahn, Corrine Munoz-Plaza, Jianjin Wang, Jazmine Garcia Delgadillo, Brian Mittman Michael Gould S31Integrating evidence-based practices for increasing cancer screenings in safety-net primary care systems: A multiple case study using the consolidated framework for implementation research Shuting (Lily) Liang, Michelle C. Kegler, Megan Cotter, Emily Phillips, April Hermstad, Rentonia Morton, Derrick Beasley, Jeremy Martinez, Kara Riehman S32 Observations from implementing an mHealth intervention in an FQHC David Gustafson, Lisa Marsch, Louise Mares, Andrew Quanbeck, Fiona McTavish, Helene McDowell, Randall Brown, Chantelle Thomas, Joseph Glass, Joseph Isham, Dhavan Shah S33 A multicomponent intervention to improve primary care provider adherence to chronic opioid therapy guidelines and reduce opioid misuse: A cluster randomized controlled trial protocol Jane Liebschutz, Karen Lasser S34 Implementing collaborative care for substance use disorders in primary care: Preliminary findings from the summit study Katherine Watkins, Allison Ober, Sarah Hunter, Karen Lamp, Brett Ewing S35 Sustaining a task-shifting strategy for blood pressure control in Ghana: A stakeholder analysis Juliet Iwelunmor, Joyce Gyamfi, Sarah Blackstone, Nana Kofi Quakyi, Jacob Plange-Rhule, Gbenga Ogedegbe S36 Contextual adaptation of the consolidated framework for implementation research (CFIR) in a tobacco cessation study in Vietnam Pritika Kumar, Nancy Van Devanter, Nam Nguyen, Linh Nguyen, Trang Nguyen, Nguyet Phuong, Donna Shelley S37 Evidence check: A knowledge brokering approach to systematic reviews for policy Sian Rudge S38 Using Evidence Synthesis to Strengthen Complex Health Systems in Low- and Middle-Income Countries Etienne Langlois S39 Does it matter: timeliness or accuracy of results? The choice of rapid reviews or systematic reviews to inform decision-making Andrea Tricco S40 Evaluation of the veterans choice program using lean six sigma at a VA medical center to identify benefits and overcome obstacles Sherry Ball, Anne Lambert-Kerzner, Christine Sulc, Carol Simmons, Jeneen Shell-Boyd, Taryn Oestreich, Ashley O'Connor, Emily Neely, Marina McCreight, Amy Labebue, Doreen DiFiore, Diana Brostow, P. Michael Ho, David Aron S41 The influence of local context on multi-stakeholder alliance quality improvement activities: A multiple case study Jillian Harvey, Megan McHugh, Dennis Scanlon S42 Increasing physical activity in early care and education: Sustainability via active garden education (SAGE) Rebecca Lee, Erica Soltero, Nathan Parker, Lorna McNeill, Tracey Ledoux S43 Marking a decade of policy implementation: The successes and continuing challenges of a provincial school food and nutrition policy in Canada Jessie-Lee McIsaac, Kate MacLeod, Nicole Ata, Sherry Jarvis, Sara Kirk S44 Use of research evidence among state legislators who prioritize mental health and substance abuse issues Jonathan Purtle, Elizabeth Dodson, Ross Brownson S45 PANEL: Effectiveness-Implementation Hybrid Designs: Clarifications, Refinements, and Additional Guidance Based on a Systematic Review and Reports from the Field - Hybrid type 1 designs Brian Mittman, Geoffrey Curran S46 PANEL: Effectiveness-Implementation Hybrid Designs: Clarifications, Refinements, and Additional Guidance Based on a Systematic Review and Reports from the Field - Hybrid type 2 designs Geoffrey Curran S47 PANEL: Effectiveness-Implementation Hybrid Designs: Clarifications, Refinements, and Additional Guidance Based on a Systematic Review and Reports from the Field - Hybrid type 3 designs Jeffrey Pyne S48 Linking team level implementation leadership and implementation climate to individual level attitudes, behaviors, and implementation outcomes Gregory Aarons, Mark Ehrhart, Elisa Torres S49 Pinpointing the specific elements of local context that matter most to implementation outcomes: Findings from qualitative comparative analysis in the RE-inspire study of VA acute stroke care Edward Miech S50 The GO score: A new context-sensitive instrument to measure group organization level for providing and improving care Edward Miech S51 A research network approach for boosting implementation and improvement Kathleen Stevens, I.S.R.N. Steering Council S52 PANEL: Qualitative methods in D&I Research: Value, rigor and challenge - The value of qualitative methods in implementation research Alison Hamilton S53 PANEL: Qualitative methods in D&I Research: Value, rigor and challenge - Learning evaluation: The role of qualitative methods in dissemination and implementation research Deborah Cohen S54 PANEL: Qualitative methods in D&I Research: Value, rigor and challenge - Qualitative methods in D&I research Deborah Padgett S55 PANEL: Maps & models: The promise of network science for clinical D&I - Hospital network of sharing patients with acute and chronic diseases in California Alexandra Morshed S56 PANEL: Maps & models: The promise of network science for clinical D&I - The use of social network analysis to identify dissemination targets and enhance D&I research study recruitment for pre-exposure prophylaxis for HIV (PrEP) among men who have sex with men Rupa Patel S57 PANEL: Maps & models: The promise of network science for clinical D&I - Network and organizational factors related to the adoption of patient navigation services among rural breast cancer care providers Beth Prusaczyk S58 A theory of de-implementation based on the theory of healthcare professionals’ behavior and intention (THPBI) and the becker model of unlearning David C. Aron, Divya Gupta, Sherry Ball S59 Observation of registered dietitian nutritionist-patient encounters by dietetic interns highlights low awareness and implementation of evidence-based nutrition practice guidelines Rosa Hand, Jenica Abram, Taylor Wolfram S60 Program sustainability action planning: Building capacity for program sustainability using the program sustainability assessment tool Molly Hastings, Sarah Moreland-Russell S61 A review of D&I study designs in published study protocols Rachel Tabak, Alex Ramsey, Ana Baumann, Emily Kryzer, Katherine Montgomery, Ericka Lewis, Margaret Padek, Byron Powell, Ross Brownson S62 PANEL: Geographic variation in the implementation of public health services: Economic, organizational, and network determinants - Model simulation techniques to estimate the cost of implementing foundational public health services Cezar Brian Mamaril, Glen Mays, Keith Branham, Lava Timsina S63 PANEL: Geographic variation in the implementation of public health services: Economic, organizational, and network determinants - Inter-organizational network effects on the implementation of public health services Glen Mays, Rachel Hogg S64 PANEL: Building capacity for implementation and dissemination of the communities that care prevention system at scale to promote evidence-based practices in behavioral health - Implementation fidelity, coalition functioning, and community prevention system transformation using communities that care Abigail Fagan, Valerie Shapiro, Eric Brown S65 PANEL: Building capacity for implementation and dissemination of the communities that care prevention system at scale to promote evidence-based practices in behavioral health - Expanding capacity for implementation of communities that care at scale using a web-based, video-assisted training system Kevin Haggerty, David Hawkins S66 PANEL: Building capacity for implementation and dissemination of the communities that care prevention system at scale to promote evidence-based practices in behavioral health - Effects of communities that care on reducing youth behavioral health problems Sabrina Oesterle, David Hawkins, Richard Catalano S68 When interventions end: the dynamics of intervention de-adoption and replacement Virginia McKay, M. Margaret Dolcini, Lee Hoffer S69 Results from next-d: can a disease specific health plan reduce incident diabetes development among a national sample of working-age adults with pre-diabetes? Tannaz Moin, Jinnan Li, O. Kenrik Duru, Susan Ettner, Norman Turk, Charles Chan, Abigail Keckhafer, Robert Luchs, Sam Ho, Carol Mangione S70 Implementing smoking cessation interventions in primary care settings (STOP): using the interactive systems framework Peter Selby, Laurie Zawertailo, Nadia Minian, Dolly Balliunas, Rosa Dragonetti, Sarwar Hussain, Julia Lecce S71 Testing the Getting To Outcomes implementation support intervention in prevention-oriented, community-based settings Matthew Chinman, Joie Acosta, Patricia Ebener, Patrick S Malone, Mary Slaughter S72 Examining the reach of a multi-component farmers’ market implementation approach among low-income consumers in an urban context Darcy Freedman, Susan Flocke, Eunlye Lee, Kristen Matlack, Erika Trapl, Punam Ohri-Vachaspati, Morgan Taggart, Elaine Borawski S73 Increasing implementation of evidence-based health promotion practices at large workplaces: The CEOs Challenge Amanda Parrish, Jeffrey Harris, Marlana Kohn, Kristen Hammerback, Becca McMillan, Peggy Hannon S74 A qualitative assessment of barriers to nutrition promotion and obesity prevention in childcare Taren Swindle, Geoffrey Curran, Leanne Whiteside-Mansell, Wendy Ward S75 Documenting institutionalization of a health communication intervention in African American churches Cheryl Holt, Sheri Lou Santos, Erin Tagai, Mary Ann Scheirer, Roxanne Carter, Janice Bowie, Muhiuddin Haider, Jimmie Slade, Min Qi Wang S76 Reduction in hospital utilization by underserved patients through use of a community-medical home Andrew Masica, Gerald Ogola, Candice Berryman, Kathleen Richter S77 Sustainability of evidence-based lay health advisor programs in African American communities: A mixed methods investigation of the National Witness Project Rachel Shelton, Lina Jandorf, Deborah Erwin S78 Predicting the long-term uninsured population and analyzing their gaps in physical access to healthcare in South Carolina Khoa Truong S79 Using an evidence-based parenting intervention in churches to prevent behavioral problems among Filipino youth: A randomized pilot study Joyce R. Javier, Dean Coffey, Sheree M. Schrager, Lawrence Palinkas, Jeanne Miranda S80 Sustainability of elementary school-based health centers in three health-disparate southern communities Veda Johnson, Valerie Hutcherson, Ruth Ellis S81 Childhood obesity prevention partnership in Louisville: creative opportunities to engage families in a multifaceted approach to obesity prevention Anna Kharmats, Sandra Marshall-King, Monica LaPradd, Fannie Fonseca-Becker S82 Improvements in cervical cancer prevention found after implementation of evidence-based Latina prevention care management program Deanna Kepka, Julia Bodson, Echo Warner, Brynn Fowler S83 The OneFlorida data trust: Achieving health equity through research & training capacity building Elizabeth Shenkman, William Hogan, Folakami Odedina, Jessica De Leon, Monica Hooper, Olveen Carrasquillo, Renee Reams, Myra Hurt, Steven Smith, Jose Szapocznik, David Nelson, Prabir Mandal S84 Disseminating and sustaining medical-legal partnerships: Shared value and social return on investment James Teufel
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Chaturvedi S, Ofner S, Baye F, Phipps M, Sico J, Damush T, Miech E, Reeves M, Johanning J, Williams LS, Bravata D. Abstract TP212: Have Clinicians Adopted the Use of Brain MRI for Patients With TIA and Minor Stroke? Stroke 2016. [DOI: 10.1161/str.47.suppl_1.tp212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background:
Use of MRI with diffusion weighted imaging (DWI) can identify infarcts in 30-50% of patients with transient neurovascular symptoms. Previous guidelines have indicated that MRI-DWI is the preferred imaging modality for patients with TIA symptoms. We assessed the frequency of MRI utilization and predictors of MRI performance in a national integrated health system.
Methods:
A review of TIA and minor stroke patients evaluated at Veterans Affairs Hospitals (fiscal year 2011) was conducted. Administrative data was reviewed with regard to demographic factors, past medical history, use of diagnostic imaging within two days of presentation, and in hospital care variables. Detailed chart abstraction was performed in a patient subset of large volume hospitals to assess clinical variables.
Results:
8427 patients with TIA or minor stroke were included in the administrative data cohort. Overall, 6817 patients (80.9%) had cranial imaging (either CT or MRI) within two days of presentation, with 3420 (50.2%) having CT without MRI and 3397 (49.8%) having MRI. 3.6% of patients with CT only had a pacemaker. Specific variables that were associated with CT performance (rather than MRI) in the administrative data cohort included the following: age>80 years, prior stroke, atrial fibrillation, dementia, and congestive heart failure (p<0.0001 for each). On chart review, diplopia as a complaint (87% with diplopia had MRI vs. 13% had CT only, p=0.03), neurological consultation in the Emergency Department (73% had MRI vs. 27% had CT only, p< 0.0001), and symptom duration of >6 hours (74% had MRI vs. 26% had CT only, p=0.0009) were associated with MRI performance.
Conclusions:
Within a large national health system, about 40% of patients with TIA or minor stroke had MRI performed within two days. Performance of MRI appears to be influenced by several variables, including age, nature of the symptoms, prior stroke, and neurological consultation in the ED. These data suggest that there has been partial acceptance of the previous guideline which endorsed MRI for patients with TIA.
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Affiliation(s)
| | | | - Fitsum Baye
- Dept of Neurology, Indianapolis VA Med Cntr, Indianapolis, IN
| | - Mike Phipps
- Dept of Neurology, Univ of Maryland Sch of Medicine, Baltimore, MD
| | - Jason Sico
- Dept of Neurology, Yale Univ Sch of Medicine, New Haven, CT
| | | | | | | | | | | | - Dawn Bravata
- Dept of Medicine, Indiana Univ Sch of Medicine, Indianapolis, IN
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Abrahamson K, Miech E, Davila HW, Mueller C, Cooke V, Arling G. Pay-for-performance policy and data-driven decision making within nursing homes: a qualitative study. BMJ Qual Saf 2015; 24:311-7. [PMID: 25749027 DOI: 10.1136/bmjqs-2014-003362] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2014] [Accepted: 02/19/2015] [Indexed: 11/03/2022]
Abstract
INTRODUCTION Health systems globally and within the USA have introduced nursing home pay-for-performance (P4P) programmes in response to the need for improved nursing home quality. Central to the challenge of administering effective P4P is the availability of accurate, timely and clinically appropriate data for decision making. We aimed to explore ways in which data were collected, thought about and used as a result of participation in a P4P programme. METHODS Semistructured interviews were conducted with 232 nursing home employees from within 70 nursing homes that participated in P4P-sponsored quality improvement (QI) projects. Interview data were analysed to identify themes surrounding collecting, thinking about and using data for QI decision making. RESULTS The term 'data' appeared 247 times in the interviews, and over 92% of these instances (228/247) were spontaneous references by nursing home staff. Overall, 34% of respondents (79/232) referred directly to 'data' in their interviews. Nursing home leadership more frequently discussed data use than direct care staff. Emergent themes included using data to identify a QI problem, gathering data in new ways at the local level, and measuring outcomes in response to P4P participation. Alterations in data use as a result of policy change were theoretically consistent with the revised version of the Promoting Action on Research Implementation in Health Services framework, which posits that successful implementation is a function of evidence, context and facilitation. CONCLUSIONS Providing a reimbursement context that facilitates the collection and use of reliable local evidence may be an important consideration to others contemplating the adaptation of P4P policies.
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Affiliation(s)
| | - Edward Miech
- Indiana University School of Medicine, Indianapolis, Indiana, USA
| | | | - Christine Mueller
- School of Nursing, University of Minnesota, Minneapolis, Minnesota, USA
| | - Valerie Cooke
- Minnesota Department of Human Services, Minneapolis, Minnesota, USA
| | - Greg Arling
- School of Nursing, Purdue University, West Lafayette, Indiana, USA
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Damush TM, Yu Z, Slaven J, Daggett V, Sager D, Plue L, Mathias M, Miech E, Williams LS. Abstract T P351: Stroke Care Team Associations with Acute Stroke Quality Improvement in Veterans Healthcare Administration. Stroke 2015. [DOI: 10.1161/str.46.suppl_1.tp351] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background and Objective:
We conducted standardized semi-structured baseline interviews to understand organizational constructs of stroke teams on a composite, acute stroke quality indicator across 11 VA Medical Centers (VAMCs).
Methods:
We conducted 104 semi-structured, in person, baseline interviews with clinical providers of acute stroke care services. Respondents were from nursing, emergency medicine, neurology, rehabilitation, inpatient care, medicine and quality management. We audiotaped the interviews, transcribed verbatim, and de-identified the data. Data were qualitatively coded using Nvivo software to tag segments of text into meaningful units based upon our Facilitating Best Practices Framework. Coders met regularly to review and consolidate emergent themes. Additionally a standardized team of chart abstractors collected 10 acute stroke quality indicators from a central location which comprised the composite. The follow up period included 6 (early response) and 12 (late response) months after a stroke collaborative.
Results:
At baseline, the VAMCs with a higher proportion of its respondents reporting regular monthly communication about stroke were associated with a late response in stroke quality improvement while sites with a lower proportion reporting regular monthly communication were associated with an early response in quality. VAMCs reporting the use of a designated nurse to promote guideline adherence and disease management were associated with an early response in quality. VAMCs reporting tracking their quality data and providing feedback to clinicians were associated with an early and late response in stroke quality improvement compared to those who did not. Finally, sites reporting the timely detection of acute stroke in the Emergency Department as a barrier at baseline were associated with no improvement in stroke quality.
Conclusion:
Our data suggests that clinical teams that wish to improve their quality may redesign their organization of care as structured to communicate regularly among their team, utilize nurses as designated for guideline adherence, track their quality data and provide feedback to clinicians, and triage presenting strokes in a timely manner.
Funded by VA HSRD QUERI SDP #09-105
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Affiliation(s)
- Teresa M Damush
- VA Stroke QUERI Cntr, Roudebush VAMC, Indiana Univ, Indianapolis, IN
| | | | | | | | | | - Laurie Plue
- VA Stroke QUERI Cntr, Roudebush VAMC, Indianapolis, IN
| | | | - Edward Miech
- VA Stroke QUERI Cntr, Roudebush VAMC, Indiana Univ, Indianapolis, IN
| | - Linda S Williams
- VA Stroke QUERI Cntr, Roudebush VAMC, Indiana Univ, Indianapolis, IN
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Daggett V, Williams L, Burrus N, Myers J, Plue L, Robinson J, Miech E, Woodward-Hagg H, Damush T. Abstract 90: Nursing Education: A Critical Need in the Delivery of High Quality Stroke Care. Stroke 2014. [DOI: 10.1161/str.45.suppl_1.90] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Objectives:
High quality stroke care is complex, and requires strong multidisciplinary teams, including nurses, to ensure care processes are timely and appropriate. The purpose of this study was to identify training needs of nurses who deliver care to patients who present with acute stroke and are admitted to inpatient units.
Methodology:
Using semi-structured interviews, we conducted a qualitative study for a formative evaluation in 12 Department of Veterans Affairs Medical Centers (VAMCs) that had ≥ 50 acute ischemic stroke admissions a year and were diverse in the structure of stroke care. The interviews focused on current context and structure of stroke care, including educational practices and training needs. Secondary analyses were conducted, targeting frontline nurse and physician respondents (N = 113) in emergency, acute care and rehabilitation units.
Results:
Respondents across the sites reported insufficient nurse education and training for acute stroke care as an overarching theme. Moreover, themes related to the acute stroke care quality indicators emerged as areas of competencies that nurses needed training on a continuum: a) timely recognition of acute stroke and transient ischemic attacks, b) NIH Stroke Scale and neurological exams, c) dysphagia screening, d) administration of tissue plasminogen activator and management post treatment, and e) deep vein thrombosis prophylaxis. Themes that were related to structure of stroke care and/or context also emerged and attributed to training challenges across the sites, listed in order of prevalence: a) centralized care versus decentralized care, b) low volume of acute strokes, c) nurse engagement, d) structured acute stroke care education, and e) release time.
Conclusions:
VA stroke care providers identify educational needs around specific stroke quality indicators, but also describe key barriers including lower volume, time for training and engagement of nursing staff in acute stroke care. Future programs to improve VA stroke care need to address these barriers to optimally support high quality multidisciplinary stroke care.
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Affiliation(s)
- Virginia Daggett
- VA/HSR&D Stroke QUERI/VA-CASE, Richard L. Roudebush VA Med Cntr, Indianapolis, IN
| | - Linda Williams
- VA/HSR&D Stroke QUERI, Richard L. Roudebush VA Med Cntr, Indianapolis, IN
| | | | - Jennifer Myers
- VA/HSR&D Stroke QUERI, Richard L. Roudebush VA Med Cntr, Indianapolis, IN
| | - Laura Plue
- VA/HSR&D Stroke QUERI, Richard L. Roudebush VA Med Cntr, Indianapolis, IN
| | | | - Edward Miech
- VA/HSR&D Stroke QUERI, Richard L. Roudebush VA Med Cntr, Indianapolis, IN
| | | | - Teresa Damush
- VA/HSR&D Stroke QUERI, Richard L. Roudebush VA Med Cntr, Indianapolis, IN
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Humbert AJ, Johnson MT, Miech E, Friedberg F, Grackin JA, Seidman PA. Assessment of clinical reasoning: A Script Concordance test designed for pre-clinical medical students. Med Teach 2011; 33:472-477. [PMID: 21609176 DOI: 10.3109/0142159x.2010.531157] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/30/2023]
Abstract
BACKGROUND The Script Concordance test (SCT) measures clinical reasoning in the context of uncertainty by comparing the responses of examinees and expert clinicians. It uses the level of agreement with a panel of experts to assign credit for the examinee's answers. AIM This study describes the development and validation of a SCT for pre-clinical medical students. METHODS Faculty from two US medical schools developed SCT items in the domains of anatomy, biochemistry, physiology, and histology. Scoring procedures utilized data from a panel of 30 expert physicians. Validation focused on internal reliability and the ability of the SCT to distinguish between different cohorts. RESULTS The SCT was administered to an aggregate of 411 second-year and 70 fourth-year students from both schools. Internal consistency for the 75 test items was satisfactory (Cronbach's alpha = 0.73). The SCT successfully differentiated second- from fourth-year students and both student groups from the expert panel in a one-way analysis of variance (F(2,508) = 120.4; p < 0.0001). Mean scores for students from the two schools were not significantly different (p = 0.20). CONCLUSION This SCT successfully differentiated pre-clinical medical students from fourth-year medical students and both cohorts of medical students from expert clinicians across different institutions and geographic areas. The SCT shows promise as an easy-to-administer measure of "problem-solving" performance in competency evaluation even in the beginning years of medical education.
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Affiliation(s)
- Aloysius J Humbert
- Department of Emergency Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA.
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