Protocol-guided Rapid Evaluation of Veterans Experiencing New Transient Neurological Symptoms (PREVENT) (QUE 15-280)
Phase: NA
Conditions: Transient Ischemic Attack, Stroke
Sponsor: VA Office of Research and Development

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Protocol-Guided Rapid Evaluation of Veterans Experiencing  
New Transient Neurological Symptoms (PREVENT) 
 
 
Clinicaltrials.gov Protocol ID: QUX 16-006 
Clinicaltrials.gov ID: NCT02769338 
 
Submitted to Clinicaltrials.gov: April 29, 2020 
 
 
ANALYSIS PLAN 
 
1. BACKGROUND 
Approximately 8,500 Veterans with transient ischemic attack (TIA) or stroke are cared for in a 
Department of Veterans Affairs (VA) Emergency Department (ED) or inpatient ward annually.1 
Patients with transient ischemic attack (TIA) are at very high risk of recurrent vascular events; 
over the long-term 11% per year will have a stroke, myocardial infarction or vascular death.2-4 
Because patients with TIA and minor stroke have little neurological impairment yet are at high 
risk of recurrent events, including disabling stroke, they are ideal candidates for interventions to 
reduce their risk of adverse events.  Several studies have demonstrated that interventions which 
deliver timely care reduce the risk of recurrent vascular events by 70%.5  
 
Our group has assessed the quality of care for Veterans with TIA and minor stroke cared 
nationwide and has found considerable gaps in care quality (e.g., 51% of eligible Veterans 
receive carotid imaging, 27% receive indicated antihypertensive medication intensification).6  In 
other words, Veterans are not receiving the timely, guideline concordant care they need to 
prevent recurrent vascular events. The objective of the PREVENT project is to develop and 
evaluate an intervention program to improve the quality of care for Veterans with TIA and minor 
stroke. 
 
2. SPECIFIC AIMS 
Aim 1. To develop a program to improve the care of Veterans with TIA or minor stroke that can 
be deployed nationwide. The program includes 5 components: (1) a reporting system that is 
based on validated electronic quality measures that allow staff to monitor the time-sensitive 
processes of care and outcomes of their Veterans with TIA; (2) clinical programs based on 
existing VHA infrastructure (e.g., a pharmacist-based TIA medication management program); 
(3) a staff education and training program; (4) protocols and templates for use by clinicians, 
nurses and pharmacists; and (5) quality improvement support including a virtual collaborative to 
share lessons learned across sites. We will measure users’ assessment of the PREVENT 
program in terms of usability, complexity, and relative advantage to deliver and improve care to 
Veterans with a recent TIA or minor stroke. We hypothesize that we can develop and facilitate 
the implementation of a program to improve guideline concordant care for Veterans with a 
recent TIA or minor stroke that achieves a high degree of staff satisfaction.  
 
Aim 2. To evaluate the effectiveness of an intervention program for Veterans with TIA or minor 
stroke against usual care. Teams at the 6 intervention sites will be given access to the 
intervention program in 3 waves of 2 sites per wave. The primary effectiveness outcome is the 
proportion of Veterans who received all of the guideline-concordant processes of care for which 
they are eligible referred to as the “Without-Fail” care rate.  We will compare the Without-Fail 

Page 2 of 22 
 
rate observed in the post-implementation phase to the baseline period. We hypothesize that the 
Without-Fail care rate will be improved by the intervention program. 
 
Aim 3. To evaluate the implementation of the intervention program across the 6 participating 
sites. The two primary implementation outcomes will be the number of implementation activities 
completed during the one-year active implementation period and the final level of team 
organization (defined as the Group Organization (GO Score)) for providing and improving TIA 
care at the end of the 12-month active implementation period. A covariate will include the 
degree of participation [Total # of calls attended/12 active implementation calls] in the monthly 
collaborative calls as noted in the call attendance. Implementation activities completed will be 
identified from multiple data sources: key updates and topics discussed during the collaborative 
calls; monthly action plan achievements and additional facilitator notes; the HUB implementation 
plan updates; and 6 and 12-month interviews.  We hypothesize that sites that engage in 
ongoing [positive] implementation strategies of reflecting and evaluating, goal setting, and 
planning will realize the greatest implementation success (defined across the two primary 
implementation outcomes: number of implementation activities and the Group Organization (GO 
score)).  We also hypothesize that sites with greatest implementation success will achieve the 
highest Without-Fail rate. We further plan to map implementation activities completed onto the 
key implementation strategies (reflecting and evaluating, goal setting, and planning) stratified by 
valence [positive & negative] based upon the mixed methodology coding.  
 
Secondary Aim To evaluate the sustainability of the program. Sustainability will be evaluated 
over a one-year period that begins after the one-year active implementation period.  We will 
compare the Without-Fail rate in the sustainability period to the post-implementation period. Our 
hypothesis is that sites that implement a facility-wide, TIA System of Care (reflected in a final 
12-month GO score between 8-10) will demonstrate the greatest program sustainability as 
measured by the Without-Fail rate. Further, sites that maintain their implementation activities 
involving PREVENT-related program elements during the sustainability period will demonstrate 
the greatest program sustainability as measured by the Without-Fail rate. 
 
3. RATIONALE 
Imperative to Provide Timely Care for Patients with TIA and Minor Stroke. Because the risk of 
recurrent vascular events is highest early after an index cerebrovascular event,4 preventive 
actions must be applied early to maximize the benefit. Several non-VA studies have 
demonstrated improved outcomes for TIA/minor stroke patients with programs that emphasize 
early evaluation and management including: lower stroke rate, reduced lengths of hospital stay, 
reduced costs, and improved vascular risk factor management.7-9 The EXPRESS study 
demonstrated that early assessment and management of TIA/minor stroke patients reduced the 
90-day stroke risk by 80% (from 10.3% to 2.1%).9 Similarly, the SOS-TIA study, found a 79% 
reduction in the 90-days stroke rate (from a predicted rate of 5.96% to an observed rate of 
1.24%).10 The FASTEST11 trial demonstrated that an electronic protocol for use in general 
practice improved care and outcomes for patients at lower cost than usual care; guideline 
adherence improved from 41% to 76% and the 90-day recurrent vascular event rate decreased 
from 11.9% to 3.5%.11 FASTEST is particularly relevant because it integrated care across 
settings and was designed to improve care for patients with limited access to specialists.11  
 
Strength of the Evidence Supporting the Intervention. Substantial evidence exists related to the 
design of our proposed intervention and the focus on specific processes of care. First, FASTER, 
SOS-TIA and EXPRESS all included algorithms or protocols that facilitate the timely delivery of 
care. In addition, numerous studies have demonstrated that nurse-administered, telephone-
delivered care can improve vascular risk factor control for Veterans.12,13  The planned 

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intervention similarly includes algorithms and protocols for the timely delivery of guideline 
concordant care. Finally, the processes of care that are the focus of the intervention are all 
supported by the AHA/ASA secondary prevention guidelines or other relevant professional 
organization guidelines.14 For each process in this project, evidence supports the association 
between the process of care and improved outcomes. Moreover, most of the processes were 
included in one of the prior trials that have demonstrated that protocol-based care dramatically 
reduces the risk of recurrent vascular events.11,15  
 
4. METHODS 
 
4.1 Aim 1 Methods (Program Development)  
The development of the PREVENT program was based on four main components: (1) 
interviews with VHA staff members involved in the care of patients with cerebrovascular 
disease;16 (2) validation of electronic quality measures against chart review for use in ongoing 
assessment of a broad range of processes of care at all VHA medical centers;17 (3) baseline 
quality of care data identifying potential gaps in care that should serve as targets for quality 
improvement;18 and (4) the existing literature regarding effective TIA clinical programs. 11-13,15   
 
As part of a prior project,16 we met with diverse staff members involved in the care of patients 
with stroke and TIA including: stroke team members (which included nursing, neurology, and 
ED members), pharmacy, primary care providers, hospitalists, radiology, vascular surgery, 
cardiology, ophthalmology, systems redesign, and quality management staff.  Based on 
interviews with these staff, we identified barriers to providing high quality TIA care including: 
gaps in knowledge; 
lack of performance 
data; uncertainty 
about how to 
engage in quality 
improvement; 
inadequate care 
coordination; and 
information 
technology 
barriers.16 The 
PREVENT 
intervention was 
designed to address 
each of these 
barriers; to utilize 
existing VHA 
resources to 
improve care for 
areas with 
demonstrated gaps 
in quality; and to 
include strategies 
which were successfully deployed in prior TIA intervention studies. 
 
PREVENT Intervention Components Description 
The PREVENT QI program includes 5 components: (1) a reporting system that is based on 
validated electronic quality measures that allow staff to monitor the time-sensitive processes of 

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care and outcomes of their Veterans with TIA; (2) clinical programs based on existing VHA 
infrastructure (e.g., a pharmacist-based TIA medication management program); (3) a staff 
training program; (4) protocols and templates for use by clinicians, nurses and pharmacists; and 
(5) quality improvement support including a virtual collaborative to share lessons learned across 
sites.  
 
Implementation Strategies 
The PREVENT program employs three primary implementation strategies: (1) team activation 
via (a) audit and feedback, (b) reflecting and evaluating, (c) planning, and (d) goal setting; (2) 
external facilitation; and (3) building a community of practice.  In addition, PREVENT allows for 
local adaptation of the intervention and also takes advantage of peer pressure while providing 
facilitation support to the site champion. During the active implementation period, we are 
tracking the adopted and adapted PREVENT program elements chosen by each site across the 
waves. Adoption is defined as PREVENT program elements chosen to be implemented at a 
local site. Adaptation is defined as site specific modifications made to the chosen PREVENT 
program elements during implementation. 
 
Aim 1 Evaluation 
Our assessment of the program development is based on the end-user evaluation of the 
usability, and complexity of the program to deliver and to improve care to Veterans with TIA.19  
We will obtain these data during interviews conducted 6-months after the start of active 
implementation and again at the end of active implementation. 
 
Aim 1 Assessments: staff satisfaction with the intervention 
Obtained at 6-months and 1-year after the start of active implementation 
 
Participant perceptions and overall experience with each of the following elements of 
PREVENT as well as:  the ease of use, how useful each element is to providing or improving 
care, and whether they are using each element: 
1. PREVENT overall 
2. The five components 
3. Kick-Off 
4. Hub (overall perceptions, usability, how are they using the hub) 
5. Virtual collaborative/monthly calls 
6. External facilitation 
Participant perceptions of PREVENT program complexity and usability  
Describe any sharing of tools with peers or with leadership at own facility, with other facilities 
Which components of PREVENT are the most helpful to you as you work to improve 
outcomes for your Veteran patients with TIA/minor stroke? 
Specific quality improvement activities planned for next 6 months  
 
Audience-response system (ARS) feedback about program components and staff written 
evaluations obtained during the Kick-Off will also inform the assessment of staff satisfaction with 
the intervention and implementation strategies. 
 
Aim 1 Analysis 
Aim 1 Hypothesis: that we can develop a program to improve guideline concordant care for 
Veterans with a recent TIA or minor stroke that achieves a high degree of staff satisfaction 

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(defined as users’ assessment of the PREVENT program in terms of usability, complexity, and 
relative advantage to deliver and improve care to Veterans with a recent TIA or minor stroke). 
 
The assessment of staff satisfaction with the PREVENT program and its components will utilize 
mixed methods.  We will seek to identify the components of the intervention that were 
considered to be most useful and/or most important to the local PREVENT program in both the 
6-and 12-month interviews as well as the staff program evaluations completed at the end of the 
day long site kick off.  
 
Interviews with facility stakeholders will be conducted in person during site visits or by 
telephone. Key stakeholders are defined as front line staff, managers, and leadership affiliated 
with the delivery of TIA care.  We will also accept “snowball” referrals from key stakeholders. 
Upon receipt of verbal consent, all interviews will be audio recorded. The audio recordings will 
be transcribed verbatim.  All transcripts will be de-identified and imported into an Nvivo11 
project file for data coding and analysis. Project team members will independently read and 
code identical transcripts using a common codebook derived from the semi-structured interview 
guide and project analysis plan. We plan to code for the presence or absence of constructs as 
well as the magnitude and valence each specified Consolidated Framework for Implementation 
Research (CFIR) constructs. Each coded transcript will be merged into a single file, and the 
project team will meet as a group to review and discuss similarities and differences in the coding 
selections until a shared understanding of each item in the codebook had been developed. All 
codes will be defined with examples in a common codebook and updated as needed by team 
agreements on modifications. At a minimum, two coders per interview will be assigned to each 
interview to best capture the specified constructs. Completed coded interviews from each site 
will be merged into Facility level estates and ultimately, all Facility level estates will be merged 
into a Project Universe file for analysis. 
 
Coding for Usability and Complexity. We will derive the users’ assessment of the intervention 
using the Intervention Characteristics domain from the Consolidated Framework for 
Implementation Research (CFIR). We will code statements on the presence of Intervention 
specific CFIR constructs about how the PREVENT program was useful for their local adopted 
program to delivery TIA care as well as statements on how it was not helpful; we will code 
statements about how complex the PREVENT program components were to implement as well 
as statements on the lack of complexity/ease of the components’ implementation to improve the 
7-key metrics of TIA related care. 
 
Coding for Context. We will continue to use the CFIR coding methodology to denote the 
presence or absence of the local context including the following from the inner setting: structural 
characteristics, networks and communications, culture, learning climate, leadership 
engagement, and available resources as well as champions in the implementation process. 
 
Key Implementation Strategies and CFIR constructs. We will expand the CFIR coding to include 
valence (positive + and negative -) influences on implementation for our key implementation 
strategies: reflecting and evaluation; goal setting and feedback; planning; and champions. 
 
 
4.2 Aim 2 Methods (Effectiveness)  
 
Design  
This five-year stepped-wedge20,21 evaluation includes a total of 6 sites, where active 
implementation is initiated in 3 waves each of which includes 2 sites.  The project involves three 

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phases at each of the six sites: a one year-baseline phase, a one-year active implementation 
phase, and a sustainability phase of at least one year in duration follows the end of active 
implementation.  
 
 
 
Power and Sample Size 
The six site, stepped wedge design provides >90% power to detect an improvement in the 
mean facility Without-Fail rate from 25% during the baseline data period to >50% during the 
active implementation data period. The goal for the sample size was to recruit sites with at least 
50 TIA patients per year, however, power was preserved with at least 30 TIA patients per year.  
 
The figures below provide the plots of the power calculated based on the modified formula for 
testing the intervention effect 𝐻0: 𝜃= 0, 𝐻1:𝜃= 𝜃𝑀 for the intervention effect size 𝜃𝑀 ranging 
from 0.1 to 0.3 when taking account for a potential decrement in intervention effect over time 𝛾. 
The plot was based on a total of 6 clusters with a cluster sample size of 30, 50 and 70, 
respectively. The results demonstrated that this variant of SWD generally has a reasonable 
power (greater than or equal to 0.90) for detecting the intervention effect when the effect size is 
at least 0.15 with a cluster size no less than 30. The coefficient of variation (CV) was set at 0.2, 
0.4, 0.6, and 0.8 to cover a wide range of the between-hospital variation. The CV seemed to 
have little effect on power.  
 
 

Page 7 of 22 
 
 
 
 
 
Site Selection  
Sites were invited to participate on the basis the basis of demonstrated gaps in quality of care 
(identified using the validated eQMs). Specifically, sites were invited to participate if they had 
baseline without-fail rates of <50%.  Invitations were sent via email to higher volume sites first 
and recruitment continued until 6 participating sites were identified.  No minimum threshold on 
volume was employed because our goal was to include sites which were diverse so that the 
results might be widely generalizable across the full spectrum of VHA facilities. 
 
 
Allocation of Sites to Waves 
Although some stepped-wedge trials randomly assign facilities to waves, PREVENT sites were 
allocated to waves on the basis of the pragmatics of the ability to schedule baseline and Kick-
Off meetings.   
 
Intervention Implementation 
The multi-faceted PREVENT intervention (described above) will be implemented via a Kick-Off 
meeting which includes all relevant staff members at participating sites and then through 
monthly telephone conference calls which include all members of the teams at the participating 
sites after the Kick-Off. Participants in the collaborative calls receive CME (Continuing Medical 

Page 8 of 22 
 
Education) for clinicians and pharmacists or CEU (Continuing Education Units) for nurses.  All 
data, quality improvement plans, professional education materials and other resources will be 
shared with the sites through the web-based portal, referred to as the PREVENT hub.   
 
Focus on Staff/Facilities  
The intervention targets participating site staff members.  Individual patients are not the target of 
the intervention or the implementation activities. 
 
Effectiveness Outcome: The Without-Fail Rate 
The primary effectiveness outcome, referred to as the Without-Fail care rate, is the proportion of 
Veterans who received all of the care for which they are eligible from among 7 key processes of 
care: brain imaging, carotid artery imaging, neurology consultation, hypertension control, 
anticoagulation for atrial fibrillation, antithrombotics, and high/moderate potency statins.  The 
Without-Fail rate is calculated at the facility level based on electronic health record data using 
validated algorithms.17  Data from all TIA patients cared for in the participating facilities’ 
Emergency Departments (ED) or inpatient settings are included in the measurement of the 
without-fail rate. 
 
Effectiveness Data Period Definitions 
Sites 
Baseline Data 
Period 
(Control Period) 
Date of 
Baseline 
Site Visit 
Pre-
implementation 
Data Period 
Date of 
Kick-Off 
Post-
Implementation 
Data Period 
Sustainability 
Data Period 
1 year before 
the baseline 
visit 
Time between 
baseline visit 
and Kick-Off 
1 year after Kick-
Off: Months 2-13 
after the Kick-Off 
Variable period: 
Months 14 after 
the Kick-Off until 
9/30/19 
A 
8/21/15-
8/21/16 
8/22-23/16 
8/24/16-7/10/17 
7/11/2017 
8/11/17-8/10/18 
8/11/18-9/30/19 
B 
8/29/15-
8/29/16 
8/30-9/1/16 
9/2/16-7/25/17 
7/26/2017 
8/26/17-8/25/18 
8/26/18-9/30/19 
C 
7/30/16-
7/31/17 
8/1-2/17 
8/3/17-10/17/17 
10/18/2017 
11/18/17-
11/17/18 
11/18/18-9/30/19 
D 
6/12/16-
6/12/17 
6/13-14/17 
6/15/17-11/1/17 
11/2/2017 
12/2/17-12/1/18 
12/2/18-9/30/19 
E 
8/23/16-
8/23/17 
8/24-25/17 
8/26/17-12/6/17 
12/7/2017 
1/7/18-1/6/19 
1/7/19-9/30/19 
F 
1/30/2017-
1/30/2018 
1/31-2/1/18 
2/2/2018-
4/12/2018 
4/13/18 
5/13/18-5/12/19 
5/13/19-9/30/19 
 
 
Primary Aim 2 Analysis:  
Descriptive Analysis: The Without-Fail care rate will be estimated at each site for each of the 
three periods (baseline, post-implementation, and sustainability) to exam the temporal trends in 
the intervention effectiveness. The 95% confidence intervals for the rates will be provided.  
 
Statistical Models: Due to the variation of sample size across the sites and across the 
implementation phases, generalized mixed-effects models (GLMM) at patient level with 
multilevel hierarchical random effects will be developed to analyze the intervention effects on 
the Without-Fail care rate during the post-implementation period and sustainability period 
compared with the baseline period.        

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The baseline data period is the one-year prior to the date of the baseline site visit.  The active 
implementation phase data period extends for one year from month 2-13 after the Kick-Off 
event.  For the primary effectiveness analysis, the main comparison is the mean facility Without-
Fail rate across the six sites during the baseline data (control) period (blue shading above) 
versus the mean facility Without-Fail rate across the six sites during the post-implementation 
data period including the active implementation and one year after the active implementation 
phases (green and pink shadings above).  We propose to model the “Without-Fail” care rate by 
 
𝑙𝑜𝑔
𝑃(𝑌𝑖𝑗,𝑘= 1|𝑋𝑖𝑗,𝑘, 𝑍𝑖𝑗,𝑘, 𝑊𝑖𝑗,𝑘)
1 −𝑃(𝑌𝑖𝑗,𝑘= 1|𝑋𝑖𝑗,𝑘, 𝑍𝑖𝑗,𝑘, 𝑊𝑖𝑗,𝑘) = µ + 𝛼𝑖+ 𝛽𝑗+ 𝑋𝑖𝑗,𝑘𝜃+ 𝑍𝑖𝑗,𝑘𝛾+ 𝑊𝑖𝑗,𝑘
𝑡𝜏 
 
where  𝑖 indexes the site (𝑖= 1,2,3,4,5,6); 𝑗  the implementation phase (1: baseline period; 2: 
active implementation phase; 3: one year after the active implementation phase); 𝑘 the 
encounter at the 𝑖𝑡ℎsite and the 𝑗𝑡ℎphase (𝑘= 1,2, … , 𝑛𝑖𝑗); 𝑛𝑖𝑗is the total number of encounters 
at the 𝑖𝑡ℎsite and the 𝑗𝑡ℎphase; 𝑋𝑖𝑗,𝑘and 𝑍𝑖𝑗,𝑘 the indicators of the active implementation phase 
and one year after the active implementation phase, respectively; 𝑊𝑖𝑗,𝑘the vector of the 𝑘𝑡ℎ 
encounter’s characteristics at the 𝑖𝑡ℎsite and the 𝑗𝑡ℎphase that could include the site 
characteristics; 𝑌𝑖𝑗,𝑘= 1the indicator of observation of “Without-Fail” care process on the 𝑘𝑡ℎ 
encounter at the 𝑖𝑡ℎsite and the 𝑗𝑡ℎphase. For this model, µ represents the average log odds of 
Without-Fail care across the 6 sites at baseline; θ the log odds ratio between the active 
implementation phase and the baseline indicating the intervention effect during the active 
implementation phase; and 𝛾 the log odds ratio between one year after the active 
implementation phase and the baseline indicating the intervention sustainability effect post the 
implementation; 𝛼𝑖 and 𝛽𝑗 are the site and phase specific random effects that are assumed to be 
multivariate normal. After fitting the model, the normal theory can be applied to test the 
intervention effect at the active implementation phase and the intervention sustainability effect.    
 
Secondary Aim 2 Analyses: Several secondary effectiveness analyses are planned.  
 
Comparison to Matched Controls 
Six control sites will be matched to each of the six PREVENT active implementation sites on the 
basis of: TIA patient volume, facility complexity (i.e., teaching status, intensive care unit level), 
and quality of care (measured by the without-fail rate). The total number of control sites will be 
36. The definition of the baseline period (the specific start and end dates of the one-year 
baseline period) for each matched control site will be identical to the definition used for the 
PREVENT active site to which the controls are matched. We will compare changes in quality 
and outcomes at control sites to changes at PREVENT sites as a method for assessing 
temporal trends. 
 
Changes in Individual Processes of Care 
An examination of the care rate of facility process for each of the seven primary processes of 
care across the six sites from the baseline period to post-implementation period will be 
conducted using the same analytical template as outlined for the primary analysis. A single risk 
adjustment model will be developed for use in evaluating the seven processes of care and will 
focus on baseline patient characteristics as follows: 
 
Process 
Risk Adjustment Variable 
Anticoagulation for atrial fibrillation 
Past history of atrial fibrillation (versus new afib) 

Page 10 of 22 
 
Use of anticoagulation prior to index event 
PMH of GI or intracranial hemorrhage 
Age 
Dementia 
Antithrombotics 
PMH of CAD, MI 
PMH of diabetes 
Anti-platelet or anticoagulant prior to index 
Brain imaging 
PMH of stroke or TIA 
Carotid artery imaging 
PMH CEA or stent 
PMH of PVD 
High or moderate potency statin 
Use of statin prior to index event 
PMH of CAD, MI 
PMH of diabetes 
History of intracranial hemorrhage 
LDL-cholesterol 
Age 
Hypertension control 
Kidney disease, dialysis 
PMH diabetes 
PMH of CAD, MI 
Antihypertensive meds before index event 
BP before the event and at discharge 
Homeless 
PCP visit 
Neurology consult 
Neurology FTE 
 
General 
Hospice, comfort care, AMA 
Admitted versus ED 
Transferred into or out of our facility 
Nights/weekends presentation 
 
 
 
90-Day Recurrent Stroke Rate 
(1) The 90-Day recurrent stroke rate will be estimated at each site before (baseline and pre-
implementation phase) and after (active implementation phase and one year after the active 
implementation phase) the intervention to examine the temporal trends in intervention 
effectiveness for reducing the 90-day recurrent stroke rate. The 95% confidence intervals for the 
rates will be provided. 
 
(2) The similar GLMM at patient level as described for the primary analysis will be developed for 
the incidence of 90-day recurrent stroke across the six sites and the whole study period to study 
the mean change of this rate. For this model, the indicator of Without Fail care at the encounter 
level will be incorporated into the model as the main exploratory variable to examine if the 
improvement of the Without Fail care rate will result in significant reduction of the 90-Day 
recurrent stroke rate.     
 
90-Day Mortality 
The analysis plan for the 90-day recurrent stroke rate (described above) will also be 
implemented for the 90-Day Mortality.  
 

Page 11 of 22 
 
Disease-free Survival Analysis 
We will examine disease-free survival over the course of 1-year after the index event.  We will 
use Cox proportional hazards modeling, censoring patients for either death or recurrent stroke 
and examine the relationship between quality of care and disease-free survival. 
 
Temporal Trends in Effectiveness  
An examination of the mean Without-Fail rate for the baseline data period through sustainability 
for all non-participating VA sites with at least 10 TIA patients per year.  Given that Indianapolis 
VAMC has served as the coordinating center, we would not include that site in the analyses. 
 
Consolidated Quality Measure   
A consolidated measure of quality defined as the number of passes divided by the number of 
eligible patients across the seven primary processes of care will be compared for baseline 
versus post-implementation periods using the same approach described above for the Without-
Fail rate analysis. 
 
 
Secondary Processes of Care   
An examination of the secondary processes of care: baseline versus active implementation data 
periods. 
 
Sensitivity Analyses 
The primary analysis will include the first TIA event per patient during the entire study period.  In 
sensitivity analysis, we will include (1) the first event per period and (2) all TIA events in the 
analysis. 
 
4.3 Aim 3 Methods (Implementation)  
Implementation is being guided by the Consolidated Framework for Implementation Research 
(CFIR), which serves as the project’s conceptual framework.  We will use a mixed methods 
approach to evaluate implementation.  Based on data from sites visits, observations made 
during Kick-Offs and collaborative telephone calls, and interviews at 6-months and 12-months 
after active implementation, we will assess: the number of improvement initiatives completed; 
the level of team organization for providing and improving TIA care; the degree to which sites 
engage in ongoing reflecting and evaluating, goal setting, and planning; participation in the 
monthly collaborative calls; the local adoption and adaptability of the program over the course of 
the study; and contextual factors to identify optimal context associated with implementation 
success. The two primary implementation outcomes will be the number of implementation 
activities completed and the level of team organization [GO Score] for providing and improving 
TIA care.  
 
 
Implementation 
Outcome 
Domain 
Measurement 
Implementation 
Activities 
 
• 
Kick-Off plans & plan updates on Hub 
• 
Collaborative call updates – action plans and FAST 
• 
Interviews at 6- and 12-months 
• 
Facilitator tracking sheet and updates 
Team activation  
Overall team 
activation 
• 
GO score based on interview data, reports from sites 
(e.g., emails), and updates from monthly 
collaborative calls, facilitator tracking sheet 

Page 12 of 22 
 
• 
Kick-Off participation 
Audit and feedback 
• 
Hub usage—data pages; user interviews 
• 
Interviews at 6 and12 months 
• 
Relevant discussion from Collaborative Calls 
captured on FAST 
• 
Facilitator notes and tracking sheet 
Reflecting and 
evaluating 
• 
Meeting as a team to discuss data: obtained from 
updates during monthly calls captured on FAST and 
6 & 12-month interviews   
• 
Facilitator notes and tracking sheet 
Planning 
• 
Hub usage—planning tool 
• 
6 & 12-month Interview questions and any relevant 
input from Collaborative Calls captured on FAST. 
• 
Facilitator notes and tracking sheet 
Goal setting 
• 
Obtained from 6 and 12 month interviews  
• 
Kick off WF goal 
• 
Any relevant discussion from Collaborative Calls and 
on FAST template 
• 
Facilitator tracking sheet and notes 
External facilitation 
 
• 
Dose, Temporality, Target: Tracking sheet  
Community of 
practice  
 
• 
Participation in monthly calls 
• 
Posting projects and other locally developed 
resources on the hub 
• 
Presenting on collaborative calls or SQUINT calls 
• 
Sharing/discussing best practices with other facilities 
outside of collaborative calls [6 and 12-month 
interviews; Facilitator notes and tracking sheet 
Cosmopolitanism 
Local adaptation 
 
• 
A site-specific PREVENT program description of 
adopted elements developed based on updates 
during monthly calls and this will be reviewed during 
interview with sites after active implementation. 
Adaptation based upon program contents, settings, 
temporality, and roles. 
Peer pressure 
 
• 
Evaluated during debriefs from Kick-Offs and after 
monthly conference calls and at the end of active 
implementation interviews 
• 
FAST template recording from calls 
Clinical champion 
 
• 
CHAMP measure at baseline and end of active 
implementation interviews 
Culture 
 
• 
OCAI measured at baseline and end of active 
implementation interviews 
 
GO Score – Group Organization Score22 for Providing and Improving TIA Care is a measure of 
team activation on a 1-10 scale for either improving or providing TIA Care based on specified 
provider practices sustained at a given time period. A score between 1-3 denotes a beginning 
level with no facility wide approach. A score between 4-5 reflects a developing approach. A 
score of 6-7 denotes a basic proficiency and a score of 8 indicates an intermediate proficiency. 
Finally, a score of 9-10 reflects a TIA system that is implemented facility wide and can sustain 
key personnel turnover. 

Page 13 of 22 
 
 
FAST – Fast Analysis & Synthesis Template. This template serves as a rapid, systematic 
method for extracting key concepts across data sources and is derived from A. Hamilton 
methodology23 and used most recently to summarize qualitative findings across regions (HSRD 
Summer 2017 featured presentation). In a similar manner, we will utilize the FAST template to 
capture key concepts from the Collaborative Calls, Stakeholder interviews, and other data 
sources in a condensed manner that accords with interview guides. 
 
Aim 3 Primary Implementation Analysis 
As described above, interviews will be audio-recorded. Audio recordings will be transcribed 
verbatim and transcripts will be de-identified and imported into an Nvivo11 project file for data 
coding and analysis. Project team members will independently read and coded identical 
transcripts using a common codebook derived from the semi-structured interview guide. Each 
coded transcript will be merged into a single file, and the project team will meet as a group to 
review and discuss similarities and differences in the coding selections until a shared 
understanding of each item in the codebook had been developed.  
 
 
In addition to qualitative coding, the analysis team will directly apply implementation science 
constructs to the qualitative data. Individual members of the analysis team will rate interview 
transcripts first for construct and valence (i.e., positive, neutral or negative).24,25 When all the 
interviews in a site visit have been rated, the analysis team will review those ratings and then 
score each VAMC with a facility-level valence (i.e., positive, neutral, or negative) for the key 
implementation strategies and CFIR constructs: reflecting and evaluating, goal setting and 
feedback, planning, and champions.24-26  
 
CFIR. From the 5 CFIR Domains, we are interested in the local implementation of the novel 
Intervention domain within the Inner Setting, i.e., each of the VAMCs. Within the Implementation 
Processes domain, we are interested in the clinical provider self-efficacy (Individual Domain) to 
implement PREVENT and to perform the 7 clinical processes upon which the without fail rate is 
calculated, and the organization’s cosmopolitanism (External Setting), the degree to which an 
organization is networked with other external organizations. The table below offers examples of 
how the CFIR construct for “Champions” has been coded, rated, and scored.  
 
Example of Valence Ratings. 
Champions 
(Process) 
Definition: Individuals who dedicate themselves to 
supporting, marketing, and driving through an 
implementation, overcoming indifference or resistance 
that the intervention may provoke in an organization.   
 
Positive 
Neutral 
Negative 
Examples 
• Presence of multiple 
champions in different 
disciplines that communicate 
regularly 
• Individuals that don’t take 
“No” for answer; constantly 
talk to others about stroke 
• Clinicians with deep, 
sustained interest in ACS 
 
• Potential stroke 
champions have been 
identified, but impact is 
limited/limited 
• Respondents identify 
champions but in 
ambiguous or neutral 
manner. 
 
• The absence of champions 
has a detrimental effect on 
ACS 
• Individuals may be having 
negative roles or stymying 
improvement efforts 
• “Anti”-champions exist 
Sample 
Quotes 
My motto is that if the rules 
weren't made to be broken, 
We were hoping to get 
sort of a champion, 
I will fault my own leadership 
as being lacking. this was 

Page 14 of 22 
 
they're made to be bent, and 
I certainly bend a lot of them. 
(1000SV2, +2) 
 
Wherever I am, I'm talking 
about stroke. If I'm in the 
beauty shop and saying, 'Hey 
you know the warning signs 
of stroke?' (900SV2, +2) 
 
We have a team of stroke 
champions, multidisciplinary, 
most of which originated from 
the workgroup that 
developed the care path. We 
meet weekly to run through 
our stroke patients for that 
week and kind of do 
Multidisciplinary Team 
rounds, but then also just to 
talk about any issues that 
arise. (200SV3, +2) 
someone who would  
gather statistics and give 
feedback on a real timely 
basis when we do get 
patients who are admitted 
with stroke to see 
whether they received 
TPA, and if not, why not 
and answer questions 
like that. (700SV3, 0) 
 
I guess [Stroke Director], 
I would see her as the 
closest to that. I guess 
just because she has 
been our point of contact 
and she does seem to 
have a real vested 
interest in making sure 
the process runs 
smoothly. (700SV1, 0) 
just an added responsibility. 
It wasn't like, you're going to 
get some support or some 
time to work on this stuff. I 
understand that resources 
are limited, but if you want a 
five-star meal you can't shop 
at Aldi, right? You've got to 
have some - you've got to 
spend some money and get 
some good ingredients. 
(500SV1, -2) 
 
Part of the problem has been 
there has been a lot of bad 
blood between the 
administration and [CHIEF 
OF NEUROLOGY]. It’s 
personal sort of rift.  So in a 
sense, I don’t really like you, 
I’m not really going to 
support your stuff.  
(1100SV2, -2) 
 
  
DOMAIN: INTERVENTION 
 
Complexity 
 
Perceived difficulty of implementation, reflected by 
duration, scope, radicalness, disruptiveness, 
centrality, and intricacy and number of steps 
required to implement. 
 
Design Quality & Packaging 
 
Perceived excellence in how the intervention is 
bundled, presented, and assembled as noted from 
the staff evaluations. 
 
Usability 
Perceived degree of usefulness to the development 
and implementation of the local PREVENT program 
 
DOMAIN:  INNER SETTING – Local context 
Construct 
Short Description 
 
Structural Characteristics 
 
The social architecture, age, maturity, and size of an 
organization. 
 
Networks & Communications 
 
The nature and quality of webs of social networks 
and the nature and quality of formal and informal 
communications within an organization. 
 
Culture 
 
Norms, values, and basic assumptions of a given 
organization. 

Page 15 of 22 
 
 
Goals & Feedback 
 
The degree to which goals are clearly 
communicated, acted upon, and fed back to staff, 
and alignment of that feedback with goals. 
Learning Climate 
A climate in which: a) leaders express their own 
fallibility and need for team members’ assistance 
and input; b) team members feel that they are 
essential, valued, and knowledgeable partners in 
the change process; c) individuals feel 
psychologically safe to try new methods; and d) 
there is sufficient time and space for reflective 
thinking and evaluation. 
 
Leadership Engagement 
 
Commitment, involvement, and accountability of 
leaders and managers with the implementation. 
 
Available Resources 
 
The level of resources dedicated for implementation 
and on-going operations, including money, training, 
education, physical space, and time. 
 
 
 
DOMAIN:  IMPLEMENTATION PROCESS 
Construct 
Short Description 
Planning  
The degree to which a scheme or method of 
behavior and tasks for implementing an intervention 
are developed in advance, and the quality of those 
schemes or methods.  
Champions 
Individuals who dedicate themselves to supporting, 
marketing, and ‘driving through’ an implementation, 
overcoming indifference or resistance that the 
intervention may provoke in an organization. 
Reflecting & Evaluating 
Quantitative and qualitative feedback about the 
progress and quality of implementation 
accompanied with regular personal and team 
debriefing about progress and experience. 
 
Domain: INDIVIDUAL 
Self-efficacy 
One’s believe in their ability to perform a specific 
behavior 
 
Categorical data captured by the analysis team will include individual-level data (e.g., job 
position, primary clinical area, etc.) for each of the interviews. We will use NVivo11 to integrate 
the tagged qualitative data, the scored construct data, the standardized survey data (e.g., OCAI 
measure), the categorical data, and the quantitative outcome data in a single, unified project file 
with multiple codebooks (qualitative, scored constructs, quantitative, categorical). We will use 
the NVivo11 “matrix query” feature to explore relationships between the qualitative, construct, 
quantitative and categorical data, and through this direct cross-referencing of qualitative and 

Page 16 of 22 
 
quantitative data iteratively analyze how specific combinations of intervention components, 
implementation strategies and features of local context influence project outcomes.  
 
Aim 3 Hypothesis A: that sites that engage in ongoing reflecting and evaluating, goal setting, 
and planning will realize the greatest implementation success (based on the number of 
implementation activities completed and the level of team organization for providing and 
improving TIA care at 12 months).   
 
As described above, the degree to which sites engage in reflecting and evaluating, goal setting, 
and planning will be assessed using an approach to qualitative coding of CFIR constructs that 
assigns valence and in this way each site will be assigned a designation that varies from -2 to 
+2 for the four constructs ((a) reflecting and evaluating, (b) goal setting, (c) planning, and (d) 
champions).  The level of team organization is based on the GO score which varies from 1 
(least complex level of organization) to 10 (most complex level of organization). 
 
Example Table: Aim 3A  
Site 
Final Construct Score 
(possible range: -2 to +2) 
PRIMARY IMPLEMENTATION 
OUTCOMES 
Number of 
Improvement 
Initiatives 
Completed 
Final GO 
Score 
Reflecting 
and 
Evaluating 
Goal 
Setting 
Planning 
A 
 
 
 
 
 
B 
 
 
 
 
 
C 
 
 
 
 
 
D 
 
 
 
 
 
E 
 
 
 
 
 
F 
 
 
 
 
 
 
 
Aim 3 Hypothesis B: that sites with greatest implementation success (based on the number of 
implementation activities completed and the level of team organization for providing and 
improving TIA care at 12 months) will achieve the highest Without-Fail rate.  The measures of 
implementation success will be included in the GLMM model described above as cluster-level 
(aka facility-level) covariates. Specifically, the change in GO score from baseline to post-
implementation as well as the number of implementation activities during the active 
implementation phase will be included in the model along with the covariate of the number of 
collaborative calls attended. 
 
Example Table: Aim 3B  
Site 
 
PRIMARY IMPLEMENTATION OUTCOMES 
Final 
Without-Fail 
Rate 
Number of 
Implementation 
Activities 
Completed 
Number of 
Collaborative 
Calls 
Attended 
Final 
GO 
Score 
Provide 
Final 
Go 
Score 
Improve 
A 
 
 
 
 
 
B 
 
 
 
 
 
C 
 
 
 
 
 
D 
 
 
 
 
 

Page 17 of 22 
 
E 
 
 
 
 
 
F 
 
 
 
 
 
 
 
Aim 3 Secondary Implementation Analyses 
 
Example Table: Aim 3C  
Strategies Used 
Final Without Fail Rate 
High 
Low 
Reflecting (+/-) 
 
 
Goal Setting (+/-) 
 
 
Planning (+/-) 
 
 
Facilitation Dose 
 
 
Collaborative Calls (Dose)  
 
 
Use of Hub  (Data Pages) 
 
 
Clinical Champion (scale rating) 
 
 
OCAI organizational profiles 
 
 
 
Identification of Effective Implementation Strategies 
As described above, PREVENT employs three primary implementation strategies: (1) team 
activation via (a) audit and feedback, (b) reflecting and evaluating, (c) planning, and (d) goal 
setting; (2) external facilitation; and (3) building a community of practice.  In addition, PREVENT 
allows for local adaptation of the intervention and also takes advantage of peer pressure. 
The identification of successful implementation strategies will be based on a mixed methods 
assessment where the change in the Without-Fail rate will be used to define implementation 
success. As shown in Table 3C, we will compare facilities based upon a High Final Without Fail 
rate as defined as 50% or higher compared to those defined as low final rate (less than 50%) by 
the degree of engagement in implementation strategies and dose received as well as strength 
of clinical champion and organizational culture. Similarly, we will compare the rate of change [% 
of change] from baseline to end of active implementation. 
 
 
External Facilitation 
We will describe the dose, type, and temporal trends in external facilitation that is provided to 
each of the sites over the course of the one-year active implementation period.  We will also ask 
participants to describe their experience with and their assessment of the external facilitation 
that was provided by the PREVENT program staff during the interviews at 6-months and 12-
months post-implementation. 
 
Community of Practice: Collaborative Call Assessment 
Given that a key component of the implementation plan was the development of a virtual 
collaborative via monthly conference calls, we are particularly interested in the perceived value 
of the collaborative calls. 
 
As part of the interviews at 6-months and 12-months post-implementation we will code the 
interviews to elicit the following emerging topics based upon the program element evaluation 
and motivation questions: 
• 
Did the calls increase your utilization of the hub? 
• 
Did the calls create a sense of profession community? 

Page 18 of 22 
 
• 
Did the calls serve to maintain your interest and enthusiasm about TIA quality 
improvement? 
• 
What was the single most important element of PREVENT participation for you working 
in your facility: kickoff, monthly process data on the hub, having access to the PREVENT 
community, the monthly calls, the library of resources and materials on the hub? 
 
As part of the secondary implementation analysis we will examine whether participation in the 
calls (number of participants per site per call and presenting on the calls) relate to the Go Score. 
We will also examine whether hub usage (by date) increased just prior to or immediately 
following the calls.  Similarly, we will examine whether email contact with the PREVENT team 
increased just prior to or immediately following a collaborative call.  Finally, we will describe the 
“eureka moments” that occurred during or as a result of the calls. 
 
Use of the HUB 
Qualitative interview data from 6 months post-implementation and 1-year post-implementation 
will be used to understand how sites used the hub for data review and project planning.  We will 
also identify whether and how the resources included in the hub library were used.   
We will also examine data collected by the hub itself to identify the pages that are most 
commonly visited. Moreover, we will interview key users from each site with in depth usability 
questions. 
 
4.4 Secondary Aim Methods (Sustainability) 
The sustainability analysis will include: a comparison of the change in the Without-Rail rate from 
the baseline data period to the sustainability period (blue versus pink shading above).  We will 
build multilevel models as described above for the Aim 2 analysis as described above. 
 
We will explore whether sites with the greatest use of their own quality data (e.g., did they 
generate their own data, the frequency with which they reviewed the process of care data on the 
hub, whether they incorporated process of care data into routine work flow, did they conduct 
their own chart reviews) demonstrate the greatest program sustainability.  Again, these cluster-
level characteristics will be included in the GLMM model described above. 
 
4.5 Risk Score  
As part of the PREVENT program, participating sites are provided with their patient risk score 
which is a measure of the risk of 1-year mortality.  We are interested in two analyses related to 
the risk score. 
 
1. How did the sites use the patient risk score?  This assessment will be based on 
qualitative interviews with sites at 6-months and 1-year post-implementation. 
 
2. Risk score validation.  For this analysis, all VAMCs will be included (not only PREVENT 
sites).  Predicted risk scores, with their 95% confidence intervals, will be compared with 
observed 1-year mortality and its 95% confidence interval. 
 
 
 
 

Page 19 of 22 
 
TABLE SHELLS 
 
Table 1. Baseline Characteristics: at the Facility-Level 
 
 
Baseline 
(Control) 
Pre-
Implementation 
Post-
Implementation 
(Active 
Implementation) 
Sustainability 
Patient Characteristics 
 
 
 
 
Facility Characteristics 
 
 
 
 
90-Day Mortality Rate  
 
 
 
 
90-Day Recurrent 
Stroke Rate 
 
 
 
 
90-Day Recurrent TIA 
Rate 
 
 
 
 
90-Day Recurrent 
Stroke or TIA Rate 
 
 
 
 
 
 
Table 2. Unadjusted Effectiveness: at the Facility-Level 
THIS IS THE PRIMARY ANALYSIS in terms of the data periods being compared. 
 
 
Baseline 
(Control) 
Post-
Implementation 
(Active 
Implementation) 
P-
VALUE 
Individual Processes of Care 
 
 
 
Anticoagulation for Atrial 
Fibrillation 
 
 
 
Antithrombotics 
 
 
 
Brain Imaging 
 
 
 
Carotid Artery Imaging 
 
 
 
High/Moderate Potency Statin 
 
 
 
Hypertension Control 
 
 
 
Neurology Consultation 
 
 
 
Mean Facility Consolidated 
Measure Rate 
 
 
 
Mean Facility Without-Fail Rate 
 
 
 
 
 
 
 Table 3. Hierarchical Model: Includes adjustment for patient and facility characteristics 
 
The same approach described for the modelling the without-fail rate can be used to model the 
outcome rates. 
 
 
 
 
 

Page 20 of 22 
 
 
Table 4. Temporal Trends in Quality of Care: Unadjusted 
 
 
Baseline 
(Control) 
Pre-
Implementation 
Post-
Implementation 
(Active 
Implementation) 
Sustainability 
Individual Processes 
of Care 
 
 
 
 
Anticoagulation for 
Atrial Fibrillation 
 
 
 
 
Antithrombotics 
 
 
 
 
Brain Imaging 
 
 
 
 
Carotid Artery Imaging 
 
 
 
 
High/Moderate 
Potency Statin 
 
 
 
 
Hypertension Control 
 
 
 
 
Neurology 
Consultation 
 
 
 
 
Mean Facility 
Consolidated 
Measure Rate 
 
 
 
 
Mean Facility 
Without-Fail Rate 
 
 
 
 
 
 
 
 
 
 
 
 

Page 21 of 22 
 
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