Alignment of Treatment Preferences and Repair Type for Veterans With AAA
Phase: NA
Conditions: Abdominal Aortic Aneurysm
Sponsor: VA Office of Research and Development

Contact PD/PI: Goodney, Philip 
 
1 
 
 
 

Contact PD/PI: Goodney, Philip 
 
2 
 
IIR 15-
085 
    
Preferences for Open Vs. Endovascular 
Repair for Abdominal Aortic Aneurysm 
Document Date 
4/10/2023 
NCT 
3115346 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Contact PD/PI: Goodney, Philip 
 
3 
 
 
 
 
 
Protocol 16-16 HSRD (Goodney)  
Alignment of Treatment Preferences and Repair Type for Veterans with AAA 
Funding Agency: HSR&D 
Principal Investigator/Study Chair: Philip P. Goodney, MD 
[Version Number 1.2] 
 
 
 
 
 
 
 
 

Contact PD/PI: Goodney, Philip 
 
4 
 
 
Abstract 
 
 
Nearly 5,000 Veterans undergo abdominal aortic aneurysm (AAA) repair each year in VA hospitals. 
Randomized trials, including the VA-based Open Versus Endovascular Repair (OVER) Trial, have found 
endovascular AAA repair (EVAR), is associated with lower perioperative morbidity and mortality, less pain, 
and shorter length of stay than open surgical repair (OSR) However, OSR is more durable, has fewer long-
term complications such as late rupture, and Veterans treated with EVAR and OSR have similar survival 
within two years following surgery. Given these tradeoffs, controversy remains as to which method is best 
suited for an individual Veteran who AAA repair, and preliminary analyses needs have found broad 
variations across VA hospitals in how Veterans are treated for AAA.  
 
Treatment decisions for AAA need to be aligned with Veterans' preferences. For example, a Veteran for 
whom a rapid recovery is of primary importance and long-term durability a lesser concern has a treatment 
preference which aligns most closely with EVAR. Similarly, a Veteran who wishes to avoid repeated follow-
up visits and late re-interventions has a treatment preference that aligns most closely with OSR. However, 
while AAA treatment type varies across VA hospitals, it is unknown if these treatment variations occurs as 
a result of Veterans preferences, or independent of Veterans' preferences. Surgeon preferences for repair 
type have been poorly described, especially for surgeons treating Veterans. 
 
In preliminary work, we have performed observational analyses, surveys, and cognitive interviews. This 
works has demonstrated variation in AAA repair type in VA and refined qualitative methods to better 
understand Veterans' and surgeons’ treatment decisions. In this proposal, in a cohort of Veterans who are 
candidates for either repair type (OSR or EVAR), we will use a survey explore Veterans' knowledge and 
preferences for AAA repair, and determine if Veterans who receive a decision aid as well as the survey are 
more likely to receive their treatment choice. 
 
We describe a cluster-randomized trial comparing two ways to better align Veterans' preferences and 
treatments for AAA: (1) a validated decision aid describing AAA repair types with a survey measuring 
Veterans' preference for repair type -- versus (2) the survey alone. Enrolled Veterans will be candidates for 
either endovascular or open repair, and be followed at VA hospitals by vascular surgery teams who 
regularly perform both types of repair. In Aim 1, we will determine Veterans' preferences for endovascular 
or open repair and identify domains associated with each repair type. In Aim 2, we will compare 
agreement between Veterans' preferences and repair type between the decision aid+survey and survey-
alone groups. We will identify factors associated with agreement. Our findings will be reported to the 
National Surgery Office Vascular Surgery Advisory Board to help ensure Veterans' preferences remain at 
the center of AAA treatment decisions. We have recruited 20 VA Medical Centers and their vascular 
surgery teams who are anxious to participate in this important trial to help Veterans make the best 
decisions. 
 
 
 
 
 
 
 
 
 
 
 

Contact PD/PI: Goodney, Philip 
 
5 
 
List of Abbreviations 
 
 
AAA: Abdominal aortic aneurysm 
 
LSI: Local Site Investigator 
 
NIH: National Institute of Health 
 
NHLBI: National Heart, Lung and Blood Institute 
 
PHI: Protected Health Information 
 
TDI: The Dartmouth Institute for Health Policy & Clinical Practice  
 
SVS: Society for Vascular Surgery  
 
VISN: Veterans Integrated Service Network 
 
 

Contact PD/PI: Goodney, Philip 
 
6 
 
  
 
 
 
Table of Contents  
Contents 
1. 
Introduction ............................................................................................................................................................................ 7 
2. 
Study Team .......................................................................................................................................................................... 11 
3. 
Study Sites ........................................................................................................................................................................... 14 
4. 
Study Design ........................................................................................................................................................................ 16 
5. 
Study Committees ................................................................................................................................................................. 22 
6. 
Coding Guide and Data Management Plan ............................................................................................................................. 22 
7. 
Data Analysis ...................................................................................................................................................................... 23 
8. 
References .......................................................................................................................................................................... 27 
 
 
Appendices 
1. Site Enrollment Guide 
2. Survey Instruments for Intervention and Control Groups 
3. International Patient Decision Aid Standards Criteria Checklist 
4. Shared Decision Making Training Course Summary 
5. Study Introduction Script 
 
 
 

Contact PD/PI: Goodney, Philip 
 
7 
 
1. Introduction 
 
Background 
 
Abdominal aortic aneurysm is the 14th leading cause of 
death among men over age 60, and a common 
condition among United States Veterans.4, 5 
Approximately 250,000 Veterans have AAA, and 
nearly 5,000 patients are treated for AAA annually to 
prevent rupture.1, 6-9 
 
Before the advent of endovascular devices in the late 
1990s, open surgical repair of AAA was the only 
treatment option for patients with AAA. In open 
surgical repair, a large abdominal incision is 
necessary, and clamps are applied to the aorta - the 
largest blood vessel in the body. Surgical 
reconstruction is performed as shown in Figure 1. The 
risk of perioperative death is 3-5% for open AAA 
repair, even in hospitals skilled in this major operation. 
The chance of major complications such as bleeding, 
need for further surgery, or heart attack, can 
approach 20% within the first year.10-13 
 
 
The development of endovascular AAA repair (called 
EVAR) in the 1990s changed the treatment options 
available for patients with AAA14. Stent-grafts could 
be placed through small incisions in the groins to 
exclude the aneurysm from blood flow, without any 
need for a large abdominal incision or aortic clamping 
(Figure 2). Short term recovery was now much 
simpler, and vascular surgeons rapidly adopted this 
new technique. 
 
Equipoise between repair types for AAA: 
Endovascular repair and open surgery have been 
compared extensively in a variety of settings, 
including large randomized trials within VA1-3, 9. In 
these studies, the less-invasive nature of endovascular repair demonstrated several advantages: lower 
rates of perioperative mortality (less than 2% versus 5%), shorter length of stay (2 versus 7 days), and 
better patient quality of life earlier after AAA treatment15. However, endovascular repair had clear 
disadvantages as well. For example, Veterans treated with EVAR commonly develop leaks around their 
graft called endoleaks, which can require secondary procedures, and can result in late aneurysm rupture16-
21. 
 
These tradeoffs have made it difficult to find a clear “winner” between endovascular repair and open 
surgery. While the randomized trials gave surgeons and Veterans important information about the 
short and long-term outcomes of each approach, they failed to identify a single AAA repair type that 
would be best for all Veterans with AAA. Because of these tradeoffs, equipoise still remains as to the 
optimal AAA repair type. 
 
Variation in treatment type for AAA: This equipoise in AAA repair type has led to variation in AAA 
repair type across VA hospitals (Figure 3). While many have studied changes in AAA repair type in 
Medicare patients39-41, variation in repair type in VA hospitals has received less attention. Therefore, to 
explore this variation, we performed preparatory-to-research analyses42. Our work demonstrated four-
fold variation in repair type across different VISNs.  For example, in 2009, nearly 80% of AAAs were 
Figure 1: Open AAA Repair
Figure 2: Endovascular AAA Repair

Contact PD/PI: Goodney, Philip 
 
8 
 
repaired with open surgery in VISN 8, and 20% 
underwent endovascular repair (Figure 3). 
However, in VISN 1, the opposite wastrue – 
fewer than 20% of AAAs were repaired using 
open repair, and more than 80% were repaired 
with endovascular repair. The results seen at 
the VISN level were similar in a recent survey 
of the twenty sites in our study. Preliminary 
analyses also showed us that measuring AAA 
repair within the VA itself is necessary. For 
example, we measured the proportion of AAA 
treated with open repair in VA in the last five 
years. We found that the proportion of AAA 
repaired with open repair declined by 3% in 
absolute terms, from 36% to 33%42. When 
compared to patients treated at non-VA 
hospitals, using data from the Society for 
Vascular Surgery43, the decline in open repair was 19% in absolute terms (from 40% 21%). These data 
suggest that treatment preferences for Veterans differ from non-Veteran populations. As such, using 
data from non-Veterans is unlikely to be a good substitution, and it would be best to learn about our 
Veterans’ preferences directly – from our Veterans themselves. 
 
Why we need to understand Veterans’ preferences: After our preparatory-to-research analyses, two 
findings were clear: (1) high-quality randomized trials have demonstrated that outcomes such as aneurysm- 
related mortality and overall mortality are equivalent between endovascular and open repair, and (2) 
significant variation in AAA repair type exists across VA. One might ask, why does it matter if there is 
variation in AAA repair type if the two repair types are similar, based on traditional procedure-related 
outcomes? 
 
The best answer to this question integrates three important concepts: the disparate nature of the two 
repair types, the risks inherent to each repair type, and the need to align treatment for AAA with Veterans’ 
preferences. Open repair requires a large abdominal incision, a greater physiologic challenge during 
surgery, and a more prolonged recovery when compared to endovascular repair, but is more durable than 
endovascular repair. A Veteran who must travel long distances for appointments, for whom reliable follow-
up is not possible, or who has chronic worry and anxiety, has treatment preferences likely to align with 
open repair. Conversely, endovascular repair, while less invasive, requires close follow-up with multiple 
imaging tests for several years after repair, with the potential for late complications years following the 
initial treatment. A Veteran who needs to return to work quickly to ensure that his or her job is not 
endangered by a prolonged recovery has a treatment preferences likely to align with endovascular repair. 
Therefore, aligning Veteran preference and repair type is necessary to achieve the best patient-centered 
outcomes. 
 
Have Veterans’ preferences for AAA repair type been examined before? Significant attention has been 
dedicated towards determining the comparative effectiveness of endovascular and open repair. However, 
less attention has been given to understanding Veterans’ preferences for repair type. In fact, other than 
measuring quality of life metrics in the context of VA randomized trials23, to the best of our knowledge, 
Veterans’ preferences for repair type remain undescribed. Three studies outside of VA – two surveys of 
National Health Service beneficiaries in England44, 45 and a report of six focus groups in Canadian 
patients46 – have begun to study patient preferences for AAA repair type. However, these findings may, or 
may not, represent the preferences seen in US Veterans. These preliminary analyses suggest studies 
within the VA are necessary. 
 
Why would a Veteran receive an AAA repair type that is not aligned with his/her preference? To better 
understand why a Veteran might receive a repair that was not aligned with his or her preferences, we 
performed two preliminary cognitive interviews with Veterans who underwent endovascular or open 
repair in recent years. Findings from these interviews led us to develop a theoretical model built upon 
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
V08
V06
V09
V12
V04
V18
V15
V01
Endovascular AAA repair 
(EVAR) 
Open Surgical Repair
VISN
Proportion 
of All AAA 
Repairs 
Figure 3: Variation in Repair Type in VA Hospitals in 2009

Contact PD/PI: Goodney, Philip 
 
9 
 
two well-known theories outlined by experts in shared decision making: a lack of informed choice 
(described by Fowler9 and Weinstein 47, 48) and an overestimate or underestimate of risks (described by 
Barry and Elwyn5, 6, 8). 
 
Lack of informed choice: First, the Veteran may not have a preference because he or she was never given 
the opportunity to clearly understand the options for treatment47, 48. If the Veteran has not been fully 
apprised of the treatment options, he or she is not capable of making a truly “informed” decision. 
 
For example, during our interview, one Veteran at our center described his interaction: 
 
The surgeon simply told me, “Your aneurysm needs to be repaired, and it is best for us to fix it 
using the new way, endovascular.”  I never knew there was a choice, and they never gave me an 
option” 
 
Given the time constraints of current surgical practice, surgeons often use paternalistic care patterns to 
assign patients with the treatment the surgeon feels is “best” – without reviewing other options with 
patients. Surgical decisions, especially those made in the context of cardiovascular diseases which 
require time tradeoffs and competing risks, can be especially difficult for physicians to explain 6, 49, 50. 
Therefore, this lack of informed choice does little to foster shared decision-making with Veterans about 
ways to repair AAA48, 49. 
 
• 
Overestimate or underestimate risks: Even if a physician actually attempts to engage a patient in 
sharing knowledge about a health care decision, two tendencies can “derail” the process of shared 
decision making. First, the description can be biased in a way that reflects the providers’ beliefs and 
assumptions, rather than the patients51. Second, patients may not understand the magnitude of the 
risks, as patients tend to overestimate benefits and underestimate risks 6, 49, 50. These tendencies can 
result in providers following the “letter of the law” in shared decision-making, but still ending up with a 
decision that is unlikely to be aligned with the Veterans’ preferences for treatment. 
 
My surgeon explained, “Your aneurysm is now large enough that we should repair it. While there 
are two ways to fix the aneurysm, the better choice for you is an endovascular, because you will 
recover more quickly.” But I ended up having to come back for many visits over the years, 
because of leaks. I even needed a second procedure Maybe it would have been better to just fix 
it the old-fashioned way.” 
 
How considering Veterans’ preferences will help to improve outcomes: Misalignment of treatment 
preferences can result in poorer satisfaction with surgery52, 53. This dissatisfaction can have real effects 
for Veterans. For example, Veterans treated with open repair may have more complications, more work 
loss, greater rates of depression, and more social isolation because of the longer recovery time32, 54-56. 
Similarly, for Veterans treated with endovascular repair, the need for continued surveillance with 
radiation-based CT scans, worries about complications, and the need for family support can have 
deleterious effects as well24, 25, 40. 
 
Shared decision-making is an approach where clinicians and patients share the best available evidence 
when faced with the task of making decisions, and where patients are supported to consider options to 
achieve informed preferences57, 58. The Veterans Health Administration has urged the adoption of shared 
decision- making for decisions facing elderly Veterans, such as decisions for long-term care59. These 
efforts in VA were developed along with the Informed Medical Decisions Foundation, which is led by Dr. 
Michael Barry. Dr. Barry is a Co-Investigator in this proposal, and represents an important link to the VA’s 
existing work in shared- decision making10. Our proposal will help advance this science by determining 
how to best use shared decision-making models in the treatment of Veterans with vascular disease in 
VA. Poor decision satisfaction and limited shared decision-making are likely to result when treatment 
decisions are made without considering patient preferences60, 61. We hypothesize that overestimating or 
underestimating risk may result in poor alignment between Veterans’ preferences and the repair type 
they receive for treatment of their AAA. 
 
 

Contact PD/PI: Goodney, Philip 
 
10 
 
 
Specific Aims 
We describe a cluster-randomized trial comparing two ways to better align Veterans' preferences 
and treatments for AAA: (1) a validated decision aid describing AAA repair types with a survey 
measuring Veterans' preference for repair type -- versus (2) the survey alone. Enrolled Veterans will 
be candidates for either endovascular or open repair, and be followed at VA hospitals by vascular 
surgery teams who regularly perform both types of repair. The conceptual framework for our study is 
illustrated in Figure 4. 
Figure 4: Conceptual Model 
  
 
 
 
Aim 1: To identify Veteran and surgeon factors associated with preference for endovascular or 
open repair. We will use validated survey instruments to determine repair type preference (endovascular 
or open) for Veterans and surgeons, and identify domains in our survey associated with each repair type. 
 
Hypothesis (H1): We hypothesize Veterans who prioritize concerns about pain or disability will prefer 
endovascular repair, and Veterans who prioritize concerns about durability will prefer open repair. 
 
Aim 2: To determine the effect of the decision aid on agreement between preference and repair 
type. AAA growth rate estimates suggest 85% of our cohort will undergo repair within our two – year 
study period. Among patients in the intervention and control groups who undergo repair, we will compare 
how commonly Veterans receive the repair type they indicated as their preference. We will study 
potential explanatory variables from our survey, such as AAA knowledge, between the intervention and 
control groups. Patient satisfaction and shared decision making will be assessed in both the intervention 

Contact PD/PI: Goodney, Philip 
 
11 
 
and control groups. 
 
Hypothesis (H2): Our intervention will be associated with better agreement between preference and 
treatment type for Veterans with AAA, as well as higher post-operative satisfaction and greater shared 
decision-making. 
 
2. Study Team 
 
Dr. Goodney, the Principal Investigator, is a VA vascular surgeon and Co-Director of the VA Outcomes Group 
in White River Junction.  A current NIH K08 awardee in health services research, he is experienced in 
conducting multicenter, cluster-randomized clinical trials61, 62. He is currently the Principal Investigator of a 
multicenter cluster-randomized trial of a smoking cessation quality improvement intervention funded by the 
Society for Vascular Surgery62. Dr. Goodney has assembled a team (Table 1) with extensive expertise in 
survey research (Dr. Sirovich), shared decision- making (Dr. Barry), and analyzing outcomes in VA (Drs. West 
and Mackenzie).  Finally, Dr.Goodney and his team members have worked together before in several 
projects63, 64, many of which have studied physician practice64-66 , so they are well prepared to collaborate 
effectively in this study. Their team, including 20 site PIs, have collaborated on several projects which have 
studied physician practice71-73 and each has significant time dedicated towards the proposal. 
Table 1: Key Personnel 
 
 
 
 
Team Member 
Role 
Skill Set 
Task 
Aims 
Philip Goodney, MD, MS 
Principal 
Investigator 
Vascular surgery, 
quantitative analyses, 
cluster‐randomized trials 
Overall project execution 
1, 2 
Brenda Sirovich, MD, MS Co‐ 
Investigator 
Assessing physician practice, 
preference‐sensitive care 
using surveys 
Interpret survey results in 
Aim 1 
1 
Michael Barry, MD 
Co‐ 
Investigator 
Shared Decision‐Making, 
decision aids 
Interpret survey results in 
Aim 1 and Aim 2 
1,2 
Alan West, PhD 
Co‐ 
Investigator 
Statistician and 
Epidemiologic Support, VA 
data architecture 
Implementation of pilot trial, 
randomized trial design, 
VINCI data 
2 
Todd Mackenzie, PhD 
Co‐ 
Investigator 
Biostatistics, observational 
dataset analyses, cluster trial 
design 
Observational analyses, 
cluster trial design, statistical 
1,2 

Contact PD/PI: Goodney, Philip 
 
12 
 
KEY PERSONNEL 
Philip P. Goodney, MD, MS Principal Investigator. Dr. Goodney is an Associate Professor of Vascular 
Surgery and Co-Director of the VA Outcomes Group at the White River Junction VA. He is an affiliated 
faculty at The Dartmouth Institute for Health Policy & Clinical Practice (TDI) at the Geisel School of 
Medicine at Dartmouth. He received a Career Development Award in 2010 from the National Heart, Lung 
and Blood Institute (NHLBI) (K08HL05676) and the 2011 Lifeline Award from the Society for Vascular 
Surgery (SVS) to study variation in treatment and intensity in vascular care. In 2012, he was appointed 
Director of Surgical Outcomes Research at Dartmouth-Hitchcock Medical Center, and in 2013 he was 
named the Co-Director of the VA Outcomes Group at the White River Junction VA. In 2014, he received 
the Multicenter Trials Planning Grant from the SVS, and in 2015 he received funding from PCORI and 
FDA for patient-centered research. He has experience in studying the delivery of vascular care, surgical 
quality improvement efforts, and cluster- randomized trials in patients with vascular disease. In this study, 
Dr. Goodney will lead the team's efforts in a cluster-randomized trial that will compare the effect of two 
different strategies (decision aid plus survey versus survey alone) in helping determine the best ways to 
align Veterans’ preferences for repair type in abdominal aortic aneurysm with their treatment.  Dr. 
Goodney will devote 3.6 calendar months of his time to the project in each of the four years. 
 
Brenda Sirovich, MD, MS Co-Investigator / Survey Research and Veterans’ Preferences. Dr. Sirovich is 
Co- Director of the VA Outcomes Group at the White River Junction VA Medical Center (in partnership 
with Dr. Goodney). She is also Associate Professor of Medicine and Community and Family Medicine at 
Geisel School of Medicine at Dartmouth. With funding from HSR&D and the National Institutes on Aging, 
she is a nationally recognized researcher studying clinical practice intensity – a measure of practice 
patterns of physicians, with a focus on their thresholds to make invasive and non-invasive treatment 
decisions. Her work examining Pap smear screening practices and geographic variation in physician 
practice has been cited widely in the medical and lay media, and has been included in CME training 
programs. She has led research teams conducting two large successful national physician surveys, and 
has served on the VISN1 Specialty Consult Utilization Council. Given her broad expertise in survey 
research, she will assist Drs. Goodney, Barry, West, and MacKenzie in the development and execution of 
the cluster-randomized trial. She will devote 3.6 calendar months of her time in each of the four years of 
the project. 
 
Michael Barry, MD (IPA) Co-Investigator / Decision Aids and Shared Decision-Making. Dr. Barry is the 
President of the Foundation for Informed Medical Decisions, the Chief Scientific Officer of Healthwise, 
and an internationally recognized expert on decision aids and shared decision-making.  He has extensive 
experience in the development, testing, and implementation of decision aids to foster shared decision-
making, especially regarding treatments related to surgery.  He has collaborated with Dr. Goodney in prior 
work on the Dartmouth Atlas of Healthcare, and will extend these collaborations to this work as well. 
Specifically, he will work closely with Dr. Goodney to implement the survey and decision aid. He will 
subsequently analyze and interpret the results of the cluster-randomized trial. He will share his expertise 
in determining the domains that influence patient preferences. He will also be instrumental in interpreting 
findings related to the agreement between patient preferences and treatments and will help shape the 
recommendations that emanate from these findings. He will not have access to PHI. Dr. Barry will 
dedicate .6 calendar months in year 1, .3 calendar months in years 2 and 3, and 1.2 calendar months in 
year 4 of the project. 
 
Alan N. West, PhD Co-Investigator / Quantitative Research. Dr. West is an experienced health services 
researcher who has been awarded three HSR&D IIR awards examining practice patterns in VA and non-
VA healthcare, especially in comparison to Medicare claims (HSR&D IR 11-319, 07-233, and 04-306). Dr. 
West was Deputy Director of the Veterans Rural Health Resource Center (Eastern Region) and has 
published widely on health care access and utilization among VA patients. Given his extensive knowledge 
of VA administrative and clinical datasets, Dr. West will collaborate with Dr. Goodney to perform the 
cluster-randomized trial as outlined in Aim 1 and Aim 2, and will construct secure infrastructure for the 
conduct and receipt of study-related datasets.  Dr. West will devote 1 calendar month of his time in all four 
years of the project. 

Contact PD/PI: Goodney, Philip 
 
13 
 
Todd A. MacKenzie, PhD Co-Investigator / Biostatistician (IPA). Dr. MacKenzie, a Senior Biostatistician at 
Geisel School of Medicine at Dartmouth, has a long history of collaboration with Dr. Goodney, Dr. West, 
and other VA HSR&D investigators. He has extensive expertise in providing statistical collaboration in 
clinical trials and multilevel hierarchical modeling. Further, he has previously collaborated with Dr. Goodney 
and his team on analyses incorporating large observational datasets, including VA datasets, Medicare 
claims and clinical registry data.  Specifically, he has served as a biostatician on Dr. Goodney’s NHLBI 
career development award, and they currently collaborate on a cluster-randomized trial funded by the 
Society for Vascular Surgery. In this study, in collaboration with Dr. Goodney and Dr. West, Dr. MacKenzie 
will oversee the implementation of statistical analyses, especially in the multilevel models described in Aim 
1, as well as any weighted kappa calculations that are necessary in Aim 2. Dr. MacKenzie will devote 1.2 
calendar months of his time in all four years of the project. 
 
OTHER PERSONNEL 
 
Cory Gaudette Central Study Coordinator: Our cluster-randomized trial entails the need for extensive 
coordination, oversight, and technical support for the study participants. To most effectively accomplish 
this goal, we will use a Central Study Coordinator. The Central Study Coordinator will be responsible for 
maintaining IRB approval of the Study Protocol, coordinating training meetings for Site Study 
Coordinators, implementing the randomization scheme, and overseeing enrollment and follow-up goals at 
each of the study sites. Further, the Central Study Coordinator will work with each of the Site Study 
Coordinators to receive and catalogue survey data forms and case report forms. As the survey data 
forms will contain the first initial of patients’ last name and last 4 digits of their SSN, Ms. Gaudette will 
have access to this PHI. The Central Study Coordinator will also work with Dr. Goodney in coordination of 
study processes files between the study participants, assist in project analyst supervision, and coordinate 
the editorial process for manuscripts and reports. Ms. Gaudette is ideal for this role, having managed 
several large projects in her role as the Administrative Officer of the VA Outcomes Group, and she 
coordinated the study sites for this proposal. Ms. Gaudette will devote 6 calendar months of her time in all 
four years of the project. She will retain her VA appointment at the White River Junction VA Medical 
Center.  
 
Amy Voorhees, MS Programmer / Analyst.  Amy Rose is a program analyst at the White River Junction 
VA and currently works within the VA Outcomes Group. Ms. Rose has several years of experience 
designing research protocols and analyzing complex administrative and clinical databases in the 
Department of Veterans Affairs and in the private sector. Her analytic skills include proficiency in SAS 
programming, and she is highly knowledgeable regarding VHA databases. Ms. Rose will access and 
construct the VA analytic files and work with Dr. Goodney and Dr. West to construct analytic datasets from 
the study information within Aim 1 and Aim 2. Ms. Rose will also be responsible for data analyses. Ms. 
Voorhees will devote 2.4 calendar months of her time in all four years of the project. 
 
Kayla Moore, MPH Research Project Director. Kayla Moore is a seasoned program manager with ten 
years’ experience coordinating federal and privately funded health programs at academic and 
nongovernmental organizations. She currently works with Dr. Goodney and other surgical investigators at 
The Dartmouth Institute for Health Policy and Clinical Practice to operationalize surgical health services 
research projects. For this study, she will be responsible for managing start-up and administrative 
operations and facilitating IRB approval. Ms. Moore is in the process of receiving a VA WOC appointment at 
the White River Junction VA Medical Center. She will not have access to PHI.  
 
To Be Named Central Research Nurse Coordinator. Our cluster-randomized trial will also require a 
Central Research Nurse Coordinator. The Central Research Nurse Coordinator will also help to support 
each of the Site Study Coordinators for clinical support. Specifically, the Central Research Nurse 
Coordinator will partner with the Central Study Coordinator to perform biweekly support calls and assist 
Site Coordinators with measuring study outcomes, especially measuring outcomes pertinent to Aim 2 
(i.e., determining when Veterans undergo AAA repair). The Central Research Nurse Coordinator will 
dedicate 4.2 calendar months of their time in all four years of the project. 
 
 

Contact PD/PI: Goodney, Philip 
 
14 
 
OTHER PERSONNEL: LOCAL SITE INVESTIGATORS AND SITE STUDY COORDINATORS FOR 
TWENTY STUDY SITES 
 
Each Local Site Investigator, named in Table 2 below, is a vascular surgeon in active practice at one 
of the 20 local VA hospitals participating in the study. Each Local Site Investigator regularly performs the 
procedures studied in this trial in routine practice. They will lead enrollment activities at their local site and 
will provide administrative support to the Site Study Coordinator in all four years of the project. Each Local 
Site Investigator will dedicate .6 calendar months in years 1 and 2, and .3 calendar months in years 3 and 
4 of the study. 
 
To Be Named The Site Study Coordinator is a role that will be filled by a portion of a research nurse, 
physician assistant, nurse, or nurse practitioner at each site. The Site Study Coordinator will be 
responsible for IRB submission, patient enrollment and consent, study intervention, and data submission 
from each site. Each Site Study Coordinator will identify and follow twelve Veterans from each site and 
receive specific training and biweekly oversight from the Principal Investigator and the study team.  The 
Site Study Coordinator will dedicate 1.2 calendar months in each year of the study. 
 
Who will have access to protected health information 
 
Local Site Investigators and Site Study Coordinators will have access to protected health information (PHI) 
for participants only at their sites during recruitment for eligibility screening and during follow-up data 
collection. They will also have access to patient’s records for care received while undergoing treatment for 
AAA that is not part of this research. Local Site Investigators and Site Study Coordinators will not have 
access to study data or PHI from any study sites other than their own.  Ms. Cory Gaudette, the Central Study 
Coordinator who receives and catalogues the surveys will also have access to PHI.  On the PI team, Dr. 
West will have access to PHI for the purpose of assigning unique study IDs to code study data. . All VA 
protocols for maintaining privacy and confidentiality of PHI will be strictly adhered to and the study key will be 
maintained behind VA firewalls and accessible only to VA credentialed personnel.  
 
CONSULTANTS 
Michael Barry, MD, Co-Investigator will be hired as a consultant. As described on page 10 above, his role 
is to provide expertise regarding the implementation of the survey and decision aid and interpretation of 
results. As stated on page 10, he will not have access to PHI. 
 
3. Study Sites 
 
We have recruited a nationally representative sample from twenty VA hospitals across the country (Table 
2). Our preparatory-to-research analyses indicate that hospital volumes in AAA repair have been constant 
(varied by <10% in the last five years), suggesting that our findings will be applicable towards treatment 
decisions for Veterans with AAA for several years in the future. In a pre-proposal survey, as well as 
assessment using CDA data, we confirmed that each study site performs at least five aortic repairs and 
fifteen endovascular repairs (or similar) per year, ensuring adequate ability at these sites to perform either 
repair type for Veterans. Contact information on each of the sites is listed below. 
 
 

Contact PD/PI: Goodney, Philip 
 
15 
 
 
Table 2 Local Sites  
 
Surgery Site 
City/State 
Complex/Interme 
diate 
Site Investigator 
Contact 
Information 
Annual AAA 
Volume 
(Direct) FY 
2014 
Annual 
AAA 
Volume 
(Endovasc 
ular) FY 
2014 
VA Western New York 
Healthcare System at 
Buffalo 
Buffalo, NY 
Complex 
Dr. Hasan Dosluoglu 
(716) 862‐8937 
4 
39 
Valley Division ‐ 
Sacramento VA Medical 
Center 
Mather, CA 
Complex 
Dr. Eugene Lee 
(916) 843‐7202 
0 
21 
VA Boston Healthcare 
System, West Roxbury 
Campus 
West Roxbury, MA 
Complex 
Dr. Joseph Raffetto 
(857) 203‐6200 
27 
42 
VA Ann Arbor Healthcare 
System 
Ann Arbor, MI 
Complex 
Dr. Peter Henke 
(734) 845‐5939 
21 
33 
VA Puget Sound Health 
Care System, Seattle 
Division 
Seattle, WA 
Complex 
Dr. Gale Tang 
(206) 764‐2245 
13 
18 
Durham VA Medical 
Center 
Durham, NC 
Complex 
Dr. Leila Mureebee 
(919) 681‐2800 
9 
27 
Michael E. DeBakey VA 
Medical Center 
Houston, TX 
Complex 
Dr. Panagiotis 
Kougias 
(713) 791‐1414 
2 
49 
VA Palo Alto Health Care 
System 
Palo Alto, CA 
Complex 
Dr. Wei Zhou 
(640) 849‐0507 
2 
27 
Omaha VA Medical 
Center 
Omaha, NE 
Complex 
Dr. Jason Johanning 
(402) 995‐3607 
4 
14 
Atlanta VA Medical 
Center 
Decatur, GA 
Complex 
Dr. Shipra Arya 
(404) 321‐6111 
4 
30 
Malcom Randall VA 
Medical Center 
Gainesville, FL 
Complex 
Dr. Salvatore Scali 
(352) 376‐1611 
19 
37 
White River Junction VA 
Medical Center 
White River Junction, 
VT 
Intermediate 
Dr. David Stone 
(802) 295‐9363 
0 
11 
VA Connecticut 
Healthcare System, West 
Haven Campus 
West Haven, CT 
Complex 
Dr. Alan Dardik 
(203) 932‐5711 
2 
15 
Jesse Brown VA Medical 
Center 
Chicago, IL 
Complex 
Dr. Melina Kibbe 
(312) 569‐8387 
3 
9 
VA Pittsburg Healthcare 
System 
Pittsburg, PA 
Complex 
Dr. Ulka Sachdev 
(412)‐802‐3333 
7 
33 
Phoenix VA Health Care 
System 
Phoenix, AZ 
Complex 
Dr. Vivienne Halpern 
(602) 277‐5551 
7 
36 
Minneapolis VA Health 
Care System 
Minneapolis, MN 
Complex 
Dr. Steven Levin 
(612) 725‐2000 
4 
94 
VA Greater Los Angeles 
Healthcare System, West 
Los Angeles Medical 
Center 
Los Angeles, CA 
Complex 
Dr. Jessica O'Connell 
(310) 268‐3445 
3 
14 
George E. Wahlen VA 
Medical Center 
Salt Lake City, UT 
Complex 
Dr. Benjamin Brooke 
(801) 582‐1565 
0 
15 
James A. Haley Veterans 
Hospital 
Tampa, FL 
Intermediate 
Dr. Peter Nelson 
(813) 972‐2000 
11 
71 
 
 
 

Contact PD/PI: Goodney, Philip 
 
16 
 
 
4. Study Design 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Study Design: Our cluster-randomized trial has two Specific Aims.  First, we will test the effect of an 
intervention (decision aid + survey) versus the survey alone on preferences for repair type (Aim 1). We 
hypothesize that the intervention will be associated with a greater preference for open repair among 
Veterans who value long-term durability in their repair type. 
 
In Aim 2, we will test the effect of the intervention (decision aid +survey) versus the survey alone on 
agreement between Veterans’ preference and actual treatment (Aim 2). We hypothesize that the 
intervention will be associated with greater agreement between Veterans preferences and the repair type 
they receive. 
 
Our instrument – both the decision aid and survey- was developed and validated by the Picker Institute 
in England28. We modified to use United States English language (Appendix 1). In preparatory-to-
research work, we pilot-tested the instrument in two cognitive interviews at White River Junction and 
administered the instrument to five patients at three sites. We will test the effect of our intervention 
(versus control) on the following outcomes: (1) Veteran preference for repair type, and the domains 
associated with preference for each repair type, (2) the agreement between Veterans’ preferences and 
their actual repair type, and (3) the Decision Regret Scale, administered 30 days after repair to assess 
decision satisfaction. 
 
Definition of “Usual Care”: In both the intervention and control groups, Veterans will have “usual care” for 
the treatment of their AAA. This is defined as a routine outpatient consultation with a VA vascular surgeon 
for their AAA and AAA repair at the discretion of the surgeon during the study period. Estimates from the 
MASS trial80 and RESCAN meta analyses 81, 82 suggest that 85% of enrollees will progress to repair 
during the study. In this study, usual care will be provided by the study team.   
 
Study Location: Our study will be based in the VA Outcomes Group in White River Junction, Vermont. We 
Veterans with 
Existing AAA 
≥5.0 cm
Open/Endovasc
Candidate
Control:
1. Repair Preferences Survey*
2. Vascular Surgery Consultation
3. Surgeon Survey, Decision Process Score
When repair occurs: record if Preferred  Repair Type = Actual Repair Type
Thirty Days After Discharge from Repair: Record PDQ-18 Questionnaire 
Aim 1:
To identify factors associated with a 
preference for Endovascular and a 
preference for Open.
Hypothesis 1:
Most veterans will prioritize concerns over pain or 
disability and have preferences for Endovascular; 
however, Veterans with concerns about durability 
will prefer Open Repair.
Aim 2:  
To determine how commonly preferences 
align with treatment for Veterans who 
undergo AAA repair.
Hypothesis 2:
Intervention will result in better alignment of 
preferences and treatments, better treatment 
satisfaction, and more shared decision-making.
^= Picker AAA preference survey (Picker)
~= Among patients  in the cohort who undergo AAA repair
*= includes pre-survey of initial preferences
Figure 5: 
Study Design
Intervention:
1. Pre-Survey, Decision Aid, Repair Preferences Survey*
2. Vascular Surgery Consultation
3. Surgeon Survey, Decision Process Score

Contact PD/PI: Goodney, Philip 
 
17 
 
will use our secure VA Research Server under the direction of Dr. West as the Study Data Core. All study 
related committees will meet at the offices of the VA Outcomes Group, either in person or using existing 
secure teleconference facilities. Web-based study team meetings will be held every other week, and will 
use videoconference to minimize expense. Two study meetings will be held at the annual meetings of the 
Association of VA Surgeons and at the Society for Vascular Surgery during each year of the study. This 
will serve as a cost-effective way for our group to meet biannually during the study period. 
 
Characteristics and selection of the study population: Our study population will be Veterans and vascular 
surgeons enrolled at the ten intervention sites and ten control sites in our cluster-randomized trial. The 
inclusion criteria for patients will be Veterans with a >5.0 cm AAA that are candidates for endovascular 
and open repair. Step C of the Study Procedures describe the recruitment procedures and inclusion 
criteria in detail.  
 
 
STUDY PROCEDURES 
 
Step A: Recruitment of Surgeons Twenty VA hospitals that currently perform both endovascular and 
open repair are the study sample. Each local site investigator has been interviewed and their credentials 
vetted by the PI, and has accepted to participate in the study. Local site investigators may invite one or 
two additional surgeons whom they work with at their site to participate in the study.  Site Study 
Coordinators will provide surgeons the Study Invitation and Information Sheet at the start of the study 
period and document the date. A waiver of documentation of informed consent for surgeons will be 
requested since the surgeon’s participation involves no procedures other than completion of a survey 
and presents no more than minimal risk.  
 
Step B: Selection of Intervention Centers: In Aim 1, we will conduct the intervention in 120 patients 
across 10 VA hospitals randomly assigned to the intervention arm. We will have a 9:1 stratified 
randomization scheme, so that we have a similar proportion of Complex and Intermediate Surgical VA 
hospitals in the intervention and control arms. These are the only two types of VA hospitals that perform 
AAA repair. Sites will be randomized at IRB approval in a rolling fashion. Site specific Study Coordinators 
will use the Study Protocol to facilitate IRB approval.3, 15. 
 
Step C: Recruitment of Patients: We are requesting a waiver of informed consent for recruitment since 
potential participants will be identified through the screening process described as follows.  
 
i. 
Potential candidate referred to VA vascular surgery clinic. The first contact with potential 
participants will occur when a referring physician indicates that they should be seen by a vascular 
surgeon for treatment of their AAA, and the patient is given an appointment for a consultation 
with a vascular surgeon at a study site.  
 
ii. 
Identification of 12 Veterans with a >5.0 cm AAA who are candidates for endovascular and open 
repair. The Site Study Coordinator will screen all new consultations made to VA vascular surgery 
clinics for Veterans with AAA that meet size criteria of ≥ 5.0 cm. Baseline audits at three clinics 
indicate ~15 new AAA referrals per vascular surgeon per month, and 60% of Veterans have an 
AAA that meets size criteria. Assuming a refusal rate of 50%, we anticipate we will enroll fully 
three months after enrollment begins, with a screening rate of 8 patients per site per month and 
an enrollment rate of four patients per site per month. 
 
iii. 
Ensuring Veterans with AAA are candidates for both endovascular and open surgical repair. 
Radiologic reports for new AAA consultations will be reviewed by the Study Coordinator 
according to the Site Recruitment Guide (Appendix 1). If a patient has an AAA that meets these 
size criteria (≥5.0 cm in diameter, the Study Coordinator will contact the Site Principal 
Investigator.  The Site Principal Investigator will review imaging tests and the Veteran’s electronic 
health record to ensure the Veteran is a candidate for endovascular and open repair using 
anatomic and clinical criteria defined according the Instructions for Use for each individual aortic 
endoprosthesis. These criteria derive from the Instructions-For-Use protocols determined by the 

Contact PD/PI: Goodney, Philip 
 
18 
 
Food and Drug Administration83. Site Principal Investigators will have discretion in interpretation 
for placement of an endovascular prosthesis outside of IFU guidelines. If the Veterans meets 
criteria for both open and endovascular repair, the Site Principal Investigator will inform the Study 
Coordinator. 
 
iv. 
Inviting Veterans who are candidates to participate in the study: Once a candidate has been 
identified, the Study Coordinator will note the time of the Veteran’s appointment. When the 
Veteran arrives for their appointment, they will check in as usual and proceed to the waiting room.  
The first contact with potential participants will be made by The Study Coordinator or other Study 
Team member who will take the Veteran to a consult room. Once in the consult room, the Study 
Coordinator or other Study Team Member will use the Study Introduction Script (Appendix 5), to 
describe the intervention to the Veteran (decision aid and survey) and invite them to participate. 
Veterans will be offered some time to review the consent form. If they wish to have more time to 
discuss it with their family and friends, they may reschedule their appointment and return on a later 
day.  The Veteran will be informed that they will be remunerated $50 at the completion of their first 
appointment for their time spent completing study documents and surveys. 
 
v. 
Consent process: Once a Veteran has expressed interest in the study, the Study Coordinator or 
other Study Team Member will review the consent form with them, answer any questions, and 
obtain consent. For any Veterans who are unable to read, the study coordinator will read the 
consent form to them in the presence of a witness. A witness is required to be present during the 
entire consenting process for illiterate participants and the witness will sign the informed consent 
to indicate he/she witnessed the participant “making their mark” consenting to be in the study.  
After consent has been obtained by the study coordinator, the Veteran will be taken through the 
survey process.  
  
Step D: Survey administration at intervention and control sites: 
 
Process at the Intervention Sites:  
 
Step 1: The Pre-Survey will be administered with the Veteran by the Study Coordinator. (2 
minutes) 
Step 1a: The Study Coordinator will review the Decision Aid with the Veteran. (5-10 minutes) 
Step 1b: The Study Coordinator will administer the Survey. (10 minutes) 
Step 2: The Study Coordinator will escort the patient to the visit with the vascular surgeon. 
Step 3: After the Visit, the Study Coordinator will complete the Decision-Process Score with 
the Veteran. (5 minutes) 
Step 4: Thirty days after AAA repair, the Study Coordinator will complete the PSQ-18 with the 
Veteran. (5 minutes). 
 
The decision aid is available in English and Spanish. 
 
The patient will be remunerated at completion of the enrollment visit. Data will be recorded 
securely by the Site Study Coordinator. 
 
The Veteran will be thanked for their participation by the study team via a formal letter mailed 
from the Principal Investigator. 
 
Process at the Control Sites: 
 
Step 1: The Study Coordinator will administer the Survey. (10 minutes) 
Step 2: The Study Coordinator will escort the patient to the visit with the vascular surgeon. 
Step 3: After the Visit, the Site-Specific Research Coordinator will complete the Decision-
Process Score with the Veteran. (5 minutes) 
Step 4: Thirty days after AAA repair, the Study Coordinator will complete the PSQ-18 with the 

Contact PD/PI: Goodney, Philip 
 
19 
 
Veteran. (5 minutes) 
 
The patient will be remunerated at completion of the enrollment visit. Data will be recorded 
securely by the Site Study Coordinator. 
 
The Veteran will be thanked for their participation by the study team via a formal letter mailed from the Principal 
Investigator. 
 
Surgeon survey administration at both the intervention and control sites: 
 
Step 1:  The Study Coordinator will administer the Pre-Visit Survey to the surgeon (1 minute, 
according to pilot testing at four sites in the trial, and two sites outside the trial). 
Step 2:  The surgeon will have the clinic visit with the Veteran. 
 
Step 3: After the Visit, the Study Coordinator will complete the Post-Visit Survey with the 
surgeon (1 minute). 
 
Data will be recorded securely by the Study Coordinator. 
 
Recruitment Target: We will recruit 12 Veterans per site (4 Veterans per site per month for 3 months) at 10 
sites in the intervention arm for a total of 120 Veterans in the intervention arm. We will recruit 12 Veterans 
per site (4 Veterans per site per month for 3 months) at 10 sites in the control arm for a total of 120 
Veterans in the control arm. The unit of analysis will be the Veteran. Randomization will occur at the site 
level, in a stratified 9:1 randomization scheme, based on the VA hospital’s Surgical Complexity 
designation. We will enroll 8 Complex and 2 Intermediate sites per arm.  Randomization will occur at the 
time of IRB approval. Weekly conference calls with Site Study Coordinators will assess study enrollment 
rates and help with problem-solving.   
 
Exclusion Criteria: Veterans with AAA who are not a candidate for both endovascular and open surgical 
repair will be excluded. Veterans who have already undergone AAA repair will be excluded. We will 
include Veterans who speak English and Spanish, using a translated survey instrument (Appendix 2). 
Veterans who cannot read will be offered participation by allowing the Site Study Coordinator to 
administer the survey. 
 
Time Frame: Our study timeline is shown in Figure 6. IRB approval and site randomization will occur 
during the first 0-3 months of Project Year (PY1). Enrollment will begin at PY1 Month 3, and will be 
completed by the end of PY1 at all sites (a conservative estimate). After two-year follow-up on all sites in 
our cohort during PGY2-3, we will examine our final outcomes and complete reports and manuscripts in 
PY4. 
 
 

Contact PD/PI: Goodney, Philip 
 
20 
 
 
Figure 6: Timeline 
Project Year 1 
Project Year 2 
Project Year 3 
Project Year 4 
Q1 
Q2 
Q3 
Q4 
Q1 
Q2 
Q3 
Q4 
Q1 
Q2 
Q3 
Q4 
Q1 
Q2 
Q3 
Q4 
Study Milestones 
IRB approval at Sites 1-20 
Study Coordinator Training 
Enrollment Sites 1-20 
25% 
50% 
75% 
100% 
Aim 1 (Intervention, Survey) 
25% 
50% 
75% 
100% 
Aim 2 (Follow-up) 
25% 
50% 
75% 
100% 
Training and Analytic Milestones 
IRB submissions 
Dataset repository construction 
Accept initial enrollees 
Patient Screening/Enrollment 
Data Collection / Assessment 
DSMB Auditing 
Fidelity testing by DSMB 
Results testing by DSMB 
Manuscripts, reports, future funding 
 
 
Risk to Subjects (Veterans and Surgeon Participants). 
 
Human Subjects Involvement and Characteristics. 
Aim 1: Cluster-Randomized Trial of a Decision Aid and Survey (versus Survey alone) for different types of 
AAA Repair 
In our study, we will identify Veterans presenting to Vascular Surgery Clinic with abdominal aortic 
aneurysms who are candidates for endovascular or open repair.  
 
Sources of Materials. 
Aim 1 and Aim 2 Survey Results 
The materials for Aim 2 will be the results from our survey administered as described in Aim 1 and Aim 2. 
In accordance with our Data Management Plan, all will be coded to protect PHI, with study entrants being 
assigned a study identifier throughout the data management process. The study key that allows identification 
between individual study patients and their protected health information (PHI) will remain behind VA firewalls 
and will not be routinely used as part of the study analyses. We will create individual random identifiers for 
each study patient, and all study dates will be removed and replaced with time-to-event variables to limit any 
potential PHI contained in study datasets. 
Potential Risks for Veterans.  
Decision Aid and Survey 
Our cluster-randomized trial will compare the effect of a patient educational tool (the decision aid) on 
survey responses describing patients’ preferences for different types of AAA repair. Both types of AAA repair 
are commonly performed across VA, and both are commonly accepted alternatives for the treatment of AAA. 
The intervention consists of provision of standardized information to patients, compared to taking the survey 
alone. Given that the intervention consists only of a standardized delivery of information that is commonly 
shared with patients during a routine vascular surgery clinic consultation, there are minimal risks to the 
Veterans who will participate in our survey. All sites and surgeons will be assigned unique study IDs in our 
dataset, and indexed only through anonymous identifiers.  Further, our data will be stored on VA servers, 
behind VA firewalls. 
Potential Risks for Surgeons.  

Contact PD/PI: Goodney, Philip 
 
21 
 
Surgeon Survey 
In both the intervention and control groups, we will examine surgeon preferences for repair type for each 
Veteran. The surgeon’s name associated to a randomly generated identifier, and a key at each site will be 
kept to allow the surgeon to remain unidentifiable in research datasets. 
 
All surgeons participating in the study will receive the Study Invitation and Information Sheet from the Site 
Study Coordinator at the time of study initiation. We anticipate IRB approval for a waiver of documentation of 
informed consent. 
 
For Veterans, there is an control arm (survey alone) and intervention arm (survey + decision aid). For 
surgeons, however, all will receive the same surgeon survey. This is simply a validated survey which records 
the factors they use to make their decisions. Given that the intervention consists only of a standardized 
delivery of information that is commonly shared with patients during a routine vascular surgery clinic 
consultation, there are minimal risks to the surgeons who will participate in our survey. No identifiable data 
will be made available, placing no risk on study surgeons. All sites and surgeons will be assigned unique 
study IDs in our dataset, and indexed only through anonymous identifiers. Further, our data will be stored on 
VA servers, behind VA firewalls. 
 
 
Adequacy of Protection from Risk. 
Recruitment and Informed Consent. 
For our survey, we will perform recruitment at the 20 sites, as described in our study procedures. Our Site 
Study Coordinator will obtain consent prior to administering the intervention. Explanation of the anonymous 
nature of the interviews will be provided to the subjects. Informed consent will be logged electronically and 
secured at our central server behind the VA firewall. 
Protection Against Risk. 
The risk of a confidentiality breach is minimized by the fact that these data will be maintained on the White 
River Junction VAMC’s dedicated research server, behind the VA firewall. Only summary statistical 
analyses are ever exported from the server. Data analysts for this project will use only the anonymous 
study IDs to distinguish individual subjects; they will not have access to any other personal identifiers, nor 
will they be able to convert Study IDs to SSNs. The risk of a data breach that will compromise personal 
information is minimal.  
 
Potential Benefits of Research to Subjects and Others. 
There are no direct benefits to Veterans or surgeons participating in this research. There is a potential 
benefit for Veterans enrolled in the intervention arm of this study, which is clearer pathway for 
communicating their preferences about their abdominal aortic aneurysm to the surgeon treating their 
aneurysm.  Further, the information to be derived will be of great value for the planning of future 
interventions and resource allocation to provide Veterans the best access to the highest quality care for 
high-risk surgical interventions such as AAA repair.  
 
Importance of Knowledge to be Gained. 
This study will yield new information about outcomes for expensive and high-risk conditions/ procedures 
to support the planning of optimal resource allocation. It will distinguish VA facilities that achieve the best 
outcomes for further study, and it will identify the components of inpatient services that yield the best 
outcomes for Veterans with AAA. The knowledge to be gained will help VA planners improve access to care 
for patients with high-risk surgical conditions, and the benefits will greatly outweigh the limited risks to 
confidentiality and patient safety. 
 
 

Contact PD/PI: Goodney, Philip 
 
22 
 
 
Data and Safety Monitoring Plan. 
As this study involves a survey only, we do not anticipate any serious adverse events related to the research, 
and that any adverse events which occur during the study period are likely to be related to underlying, pre-
existing medical conditions, and/or the surgery. Therefore, we will not routinely collect any data to assess 
harms. The Data and Safety Monitoring Committee will be responsible for ensuring that data conduct is 
commensurate with any potential benefits or harms evident in quarterly analysis of study datasets. Any 
unanticipated problems which may arise involving risks to subjects or others, related to research 
(including data integrity/security issues) will be documented and reported to the IRB within 5 
business days after becoming aware of the event, in accordance with VHA Handbook 1058.01 
Paragraph 6. This study will adhere to the VA Central IRB Table of Reportable Events. Data accuracy and 
integrity will meet the standards for VA or Medicare administrative treatment files.   
 
 
5. Study Committees 
 
We have established a study committee structure as outlined below, consisting of three central committees: 
A Steering Committee, A Data Safety Monitoring Board, and a Publications Committee. The committees are 
staffed by Key Personnel and six experienced, VA-funded surgical investigators (Zhou, Nelson, Johanning, 
Rafetto, Dardik, and Henke). Each Committee will meet quarterly during the study period.  
 
AAA Survey Study Steering Committee, 
 
Philip Goodney,  
Brenda Sirovich, 
Michael Barry, 
Alan West, 
Wei Zhou, 
Peter Nelson, 
Jason Johanning, 
Joseph Raffetto, 
Alan Dardik 
Peter Henke 
 
AAA Survey Study Data Safety Monitoring Board 
 
Alan West 
Todd Mackenzie 
Richard Powell (external auditor) 
 
AAA Survey Study Publications Committee: 
 
Philip 
Goodney 
Brenda Sirovich 
Michael Barry 
 
 
6. Coding Guide and Data Management Plan 
 
 
Procedures for managing the flow of information from participating sites is detailed below. Any deviation from 
these procedures that might be relevant to participant protection will be reported to the PI within 24 hours. The 
PI will have 24 hours to investigate the occurrence and convey the information to the VA Central IRB. All study 

Contact PD/PI: Goodney, Philip 
 
23 
 
team members must adhere to the VA Central IRB Table of Reportable Events all documented VA security 
policies and protocols. Removal of access to research study data will be accomplished for study personnel 
when they are no longer part of the research team. 
 
Step 1: 
 
Each completed survey and consent form will be completed by the Veteran under the supervision of the 
site-specific Study Coordinator. 
 
Step 2: 
 
A PDF of the survey document will be created and sent via secure email to a file maintained on our 
Research Server by the Data Coordinating Center (led by Dr. West and Dr. Goodney at White River 
Junction).  
 
Step 3: 
 
After confirming secure receipt and upload of the PDF onto our Research Server, the Site Study 
Coordinator will store the original documents in a locked file until study conclusion. Original documents will 
be destroyed in accordance with the VA Records Control schedule.  
 
Step 4: 
 
The survey data will be extracted by our Central Study Coordinator and imported into analytic software 
files (SAS) to allow for analysis by Drs. West and Mackenzie. A Coordinating Center Research Nurse will 
facilitate this effort as well, and hold biweekly technical support calls with the Central Site Study 
Coordinator with all sites during the study period. All research datasets will be destroyed in accordance 
with the VA Records Control Schedule. 
 
 
Long term follow-up Data Collection: 
 
To inform the agreement between preferences and repair type, we will compare the preference identified 
for each Veteran in Aim 1 and the actual AAA repair type the Veteran receives. 
 
This will be done at each site by the Site Study Coordinator who will have access to PHI of participants 
enrolled only at their site for the purpose of follow-up. They will not have access to study data or PHI from 
any other study sites. 
 
Every three months during the Study Period, each site-specific Study Coordinator will audit CPRS for each 
enrolled Veteran at that site.  
 
If no record of repair exists, the Site Coordinator will contact the enrolled patients via phone to 
ensure repair has not been performed outside of VA. 
 
Patients who do not undergo repair or who die prior to repair will be excluded from this step in the 
analysis. 
 
 
7. Data Analysis 
 
(Please note: The following sections are described separately for Aim 1 and Aim 2).  
Aim 1: To identify Veteran and surgeon factors associated with preference for endovascular or 

Contact PD/PI: Goodney, Philip 
 
24 
 
open repair. 
Aim 1. Dependent and Independent Variables: The main dependent variable in Aim 1 is the preference 
for repair type (endovascular or open) as expressed by Veterans and surgeons in their respective 
survey instruments. Each survey instrument has a validated coding algorithm which will be used to 
categorize survey responses into preference for endovascular or open repair (Appendix 2) 44. 
Independent variables, such as age, gender, race, ethnicity, and other descriptive variables are 
recorded as part of the survey instrument by the Site Study Coordinator. Hospital and surgeon 
characteristics such as annual hospital and surgeon volume of endovascular and open repair for each 
participating site will be collected via VINCI by Dr. West. These variables will be measured at the 
hospital level, as in prior analyses.65, 97-100 
 
 
Aim 1:.Data analytic strategy: tests, strengths, limitations, and alternative approaches: In Aim 1, our 
main outcome variable will be Veteran and surgeon preference for repair type (endovascular or open 
repair). The preference will be defined as either preference for endovascular or preference for open 
repair. Repair type preference will be categorized from several questions in our survey instruments. 
Several questions allow for differing degrees of choice (e.g., strongly/slightly favor open repair).  For 
these responses, we will use variables that allow this category. We will use a coding algorithm 
(Appendix 2) which deconstructs survey questions into components that generate binary outcomes 
(i.e., preference for open or endovascular repair) and allows sensitivity analyses using the gradients. 
We will compare the proportion choosing each repair type in the intervention and control groups to test 
the effect of the decision aid on repair type preference. The proportions preferring each repair type will 
be compared between the two groups accounting for clustering of patients within center and/or 
surgeon; in particular, we will used the Mantel-Haenszel test (for stratified contingency tables, 
equivalent to partial likelihood ratio test from fixed effects logistic regression) or a mixed effects logistic 
regression with fixed effect of group, and random intercept for center effects. 
 
Aim 1 Data Collection Strategy: potential problems and solutions Refer to Section 6 of this Protocol 
Coding Guide and Data Management Plan. 
 
To identify patient characteristics (such as survey responses) associated with preference for 
endovascular or open repair we will use multivariable mixed effects logistic regression. The use of 
mixed effects is to account for clustering within individual VA centers using a random intercept, e.g. 
logit Pr[Y_ij=1]=X_ij β+μ_i where Y_ij is the binary preference variable in subject j from cluster i, X_ij is 
a vector of characteristics, μ_i is a random intercept from a zero mean distribution with standard 
deviation to be estimated (e.g. normal), and β is a vector of coefficient(s). We will explore the feasibility 
(e.g. convergence) and sensitivity of findings of patient characteristics of using ether a random 
intercept for surgeon, or for center, or for surgeon nested within center. We will report both unadjusted 
and adjusted estimates, after identifying one or more models to adjust for using for instance stepwise 
regression or LASSO. Stata (e.g.,xtmelogit) and/or R (library lme4 or nlme) software will be used.  Dr. 
MacKenzie has extensive experience in these strategies. 
Missing Data: To accommodate missing data where justified (e.g. the variable with missing data is 
predictive and deserves to be adjusted for, and furthermore the data is believed to be missing at 
random) we shall use multiple imputation methods, such as implemented in the Stata mi routine. 
Power Analysis: Comparing the effect of the decision aid on repair type preference. Because the 
decision aid will inform Veterans more fully about the long-term disadvantages of endovascular repair, 
we hypothesize that the decision aid will reduce the proportion of Veterans who prefer endovascular 
repair by 25%, based on similar decision aids studied in surgical settings in breast cancer and back 
pain16-18. 
 
Table 3 Sample size and power calculations (assuming a 90% baseline rate of EVAR preference) 
Number of 
clusters 
Number of 
patients per 
cluster 
Total Number of 
Patients 
Proportion 
Choosing 
Endovascular 
Repair At 
Decision Aid 
Effect Size 
(in relative 
decline in 
preference 
Proportion 
Choosing 
Endovasc 
Repair at 
Power To 
detect 
significant 
difference 
Power To 
detect 
significant 
difference 
Power To 
detect 
significant 
difference 

Contact PD/PI: Goodney, Philip 
 
25 
 
Intervention 
Control 
Intervention 
Control 
Intervention 
Control 
Control Sites 
for 
endovascular 
repair)
Intervention 
Sites 
(ICC 0.01) 
(ICC 0.05) 
(ICC 0.10) 
10 
10 
12 
12 
120 
120 
0.9 
0.25 
0.68 
0.96 
0.86 
0.81 
10 
10 
12 
12 
120 
120 
0.9 
0.20 
0.73 
0.88 
0.75 
0.62 
10 
10 
12 
12 
120 
120 
0.9 
0.15 
0.78 
0.71 
0.50 
0.39 
 
 
We adjusted our sample size calculations for our cluster-randomized trial to account for intra-cluster 
correlation, and allow for variable enrollment size within each cluster. As shown in Table 8, we 
anticipate that we will have 96% likelihood of detecting a 25% effect size, assuming an ICC of 0.01. 
Sensitivity analyses around our ICC assumption of 0.01 demonstrate that even if our ICC is ten times 
higher (ICC=0.10), our sample size would still yield an 81% likelihood of detecting a 25% effect size 
between intervention/control. 
Aim 2:  To determine the effect of the decision aid on agreement between preferences and repair 
type. 
Aim 2 Dependent and Independent Variables: After identifying Veterans’ preference for endovascular or 
open repair, we will determine the agreement between their preferences and the repair types they 
receive. The dependent variable will be the kappa statistic (ĸ), measuring agreement between the 
preferred repair type and the repair type the Veteran ultimately receives. Cohen’s kappa will be 
compared between the intervention and control groups. Kappa will be calculated overall and by hospital 
(using a weighted sum of the kappas for each hospital in that arm. As a secondary outcome, Site Study 
Coordinators will administer two surveys to the Veteran. These two surveys will examine patient 
satisfaction (PDQ-18) and shared decision making (Decision Process Score, or DPS)87, 104. Our group 
has used these or similar instruments in prior work104, 105. A survey administration training guide for 
each Site Study Coordinator has been developed.  The DPS will be administered at the end of the visit, 
and the PDQ-18 will be completed at 30-day follow-up visits which are already standard practice after 
AAA repair for both repair types. Completing the surveys in this context will not require any extra visits 
by Veterans, an important strength given the elderly population of patients involved in our proposal. 
Aim 2 Data Collection Strategy: potential problems and solutions: To inform the agreement between 
preference and repair type, we will compare the preference identified for each Veteran and the actual 
AAA repair type the Veteran receives at each site. We anticipate that 85% of Veterans will undergo 
repair within three months after the study visit in which they are enrolled. However, we estimate that 15% 
of patients will not undergo repair within 3 months of enrollment. Therefore, to ensure we capture the 
repair type for these patients, each Site Study Coordinator will audit CPRS every three months during the 
study period. At the end of the two years of audits, the site specific Site Study Coordinator will contact the 
enrolled patients via phone to ensure repair has not been performed outside of VA. Patients who do not 
undergo repair or who die prior to repair will be excluded. Sample size calculations incorporate a dropout 
rate of 10% for this effect. Re-survey will occur for a delay in repair greater than 3 months, if the pre- 
survey shows a change in Veteran repair preference from the original enrollment survey. 
Aim 2 Data analytic strategy: After we have measured the necessary elements for agreement 
(preferences for repair type and the actual repair type), we will then calculate Cohen’s kappa. We will 
stratify these analyses for surgeon agreement with the actual repair type (surgeon-preferred repair type 
matches the actual repair type, surgeon-preferred repair type does not match the actual repair type, and 
surgeon has no preference in repair type). Of note, Question #8 in the Decision Process Score allows us 
to measure incidents where discussion with the surgeon changed the Veteran’s preference after the 
survey. We will perform sensitivity analyses including and excluding Veterans who changed preferences. 
To account for possible agreement of preference and choice with age, gender and race, we will estimate 
the association of choice with preference in a multivariable binary regression model that includes age, 
gender and race, and report the odds ratio (via logistic link) and rate ratio (via Poisson link). The fitted 
value from the logistic regression model will be used to calculate the four proportions used in the 
calculation of Kappa agreement using the method of average predictions (fitted values). Bootstrapping 
methods, as described by Efron and Tibshirani106, will be performed if individual hospital samples are 
small. 

Contact PD/PI: Goodney, Philip 
 
26 
 
Power analysis in Aim 2: We hypothesized that Veterans who receive the decision aid will be 25% more 
likely to have a treatment that aligns with their preferences, based on effect sizes seen in similar 
decision aids16-18. This would increase kappa from a baseline of ĸ=0.7 in the control group to ĸ=0.88 in 
the treatment group. Using a nomogram by Sim and Wright107, we assumed a 2-tailed test for a null 
value of ĸ=0.7 in the control group, and ĸ=0.88 in the intervention group. We would have 80% power to 
detect a difference assuming a 50% positive response rate at 101 patients in each arm. Our sample of 
120 patients is powered to detect a difference in kappa, accounting for dropout (10%) and patients who 
do not undergo repair (15%). 
 
 

Contact PD/PI: Goodney, Philip 
 
27 
 
 
8. References 
 
1. 
Faggioli G, Scalone L, Mantovani LG, et al. Preferences of Patients, Their Family Caregivers and 
Vascular Surgeons in the Choice of Abdominal Aortic Aneurysms Treatment Options: The Prefer Study. 
Eur J Vasc Endovasc Surg. 2011;42(1):26-34. PMID: 21334928. 
2. 
Elwyn G, O'Connor A, Stacey D, et al. Developing a Quality Criteria Framework for Patient 
Decision Aids: Online International Delphi Consensus Process. BMJ. 2006;333(7565):417. PMID: 
16908462; 
3. 
Volk RJ, Llewellyn-Thomas H, Stacey D, et al. Ten Years of the International Patient Decision Aid 
Standards Collaboration: Evolution of the Core Dimensions for Assessing the Quality of Patient Decision 
Aids. BMC Med Inform Decis Mak. 2013;13 Suppl 2:S1. PMID: 24624947; PMCID: 4044280. 
4. 
Elwyn G, O'Connor AM, Bennett C, et al. Assessing the Quality of Decision Support Using the 
International Patient Decision Aid Standards.PLoS One. 2009;4(3):e4705. PMID: 19259269; PMCID: 
2649534. 
5. 
Elwyn G, Frosch D, Thomson R, et al. Shared Decision Making: A Model for Clinical Practice. J 
Gen Intern Med. 2012;27(10):1361-7. PMID: 22618581; PMCID: 3445676. 
6. 
Barry MJ, Edgman-Levitan S. Shared Decision Making--Pinnacle of Patient-Centered Care. N 
Engl J Med. 2012;366(9):780-1. PMID: 22375967. 
7. 
Barry M, Levin C, MacCuaig M, et al. Shared Decision Making: Vision to Reality. Health 
Expect. 2011;14 Suppl 1:1-5. PMID: 21323818. 
8. 
Barry MJ. Health Decision Aids to Facilitate Shared Decision Making in Office Practice. Ann Intern 
Med. 2002;136(2):127-35. PMID: 11790064. 
9. 
Wagner EH, Barrett P, Barry MJ, et al. The Effect of a Shared Decisionmaking Program on 
Rates of Surgery for Benign Prostatic Hyperplasia. Pilot Results. Med Care. 1995;33(8):765-70. PMID: 
7543638. 
10. 
The Veterans Administration Makes Shared Decision Making Resources Available to Help with 
Long Term Care Choices: The Informed Medical Decisions Foundation; [cited 2014]. Available from: 
http://www.informedmedicaldecisions.org/2013/03/28/the-veterans-administration-makes-shared-
decision- making-resources-availableto-help-with-long-term-care-choices/. 
11. 
Veterans' Adminstration Website for Shared Decision Making 2015. Available 
from: (http://www.va.gov/geriatrics/guide/longtermcare/Shared_Decision_Making.asp. 
12. 
Legare F, Thompson-Leduc P. Twelve Myths About Shared Decision Making. Patient Educ 
Couns. 2014;96(3):281-6. PMID: 25034637. 
13. 
Legare F, Politi MC, Drolet R, et al. Training Health Professionals in Shared Decision-
Making: An International Environmental Scan. Patient Educ Couns. 2012;88(2):159-69. PMID: 
22305195. 
14. 
Wexler R, Editor. Providers Benefit from Online Shared Decision Making Skills Course. 
ISDM/ISEHC Conference in Sydney, 2015; 2015; Syndey, Austrailia. 
15. 
Volk RJ, Shokar NK, Leal VB, et al. Development and Pilot Testing of an Online Case-Based 
Approach to Shared Decision Making Skills Training for Clinicians. BMC Med Inform Decis Mak. 
2014;14:95. 
16. 
Weinstein JN, Lurie JD, Tosteson TD, et al. Surgical Vs Nonoperative Treatment for Lumbar 
Disk Herniation: The Spine Patient Outcomes Research Trial (SPORT) Observational Cohort. 
JAMA. 2006;296(20):2451-9. PMID: 17119141; PMCID: 2562254. 
17. 
Weinstein JN, Tosteson TD, Lurie JD, et al. Surgical Vs Nonoperative Treatment for Lumbar 
Disk Herniation. JAMA. 2006;296(20):2441-50. PMID: 17119140; PMCID: 2553805. 
18. 
Whelan T, Levine M, Willan A, et al. Effect of a Decision Aid on Knowledge and Treatment 
Decision Making for Breast Cancer Surgery: A Randomized Trial. JAMA. 2004;292(4):435-41. PMID: 
15280341. 
19. 
Birkmeyer NJ. Improving Patient Decisions About Bariatric Surgery. PCORI Grant for Decision 
Support in Bariatric Surgery (https://www.clinicaltrials.gov/ct2/show/NCT02364128). 
20. 
Goodney PP, Newhall KA, Farber A, et al. Characteristics of Patients Enrolled in a 
Cluster- Randomized Trial of a Smoking Cessation Intervention. J Vasc Surg. 2015;(in press). 
21. 
Newhall KA, Farber A, Goodney PP. Smoking Cessation Counseling in Vascular Surgical 

Contact PD/PI: Goodney, Philip 
 
28 
 
Practice Using the Results of Interviews and Focus Groups in the VAPORTrial. J Vasc Surg. 
2015;(in press). 
22. 
O'Malley J, Goodney PP, Mackenzie TA, et al. Advancing Patient Centered Outcomes Research 
in Survival Data with Unmeasured Confounding. Patient Centered Outcomes Research Institute 
(PCORI); 2015. 
23. 
Lederle FA, Freischlag JA, Kyriakides TC, et al. Long-Term Comparison of Endovascular and 
Open Repair of Abdominal Aortic Aneurysm. N Engl J Med. 2012;367(21):1988-97. PMID: 23171095. 
24. 
Lederle FA, Freischlag JA, Kyriakides TC, et al. Outcomes Following Endovascular Vs Open 
Repair of Abdominal Aortic Aneurysm: A Randomized Trial. JAMA. 2009;302(14):1535-42. PMID: 
19826022. 
25. 
Lederle FA, Johnson GR, Wilson SE, et al. The Aneurysm Detection and Management Study 
Screening Program: Validation Cohort and Final Results. Aneurysm Detection and Management 
Veterans Affairs Cooperative Study Investigators. Arch Intern Med. 2000;160(10):1425-30. PMID: 
10826454. 
26. 
Eliason JL, Upchurch GR, Jr. Endovascular Abdominal Aortic Aneurysm Repair. 
Circulation. 2008;117(13):1738-44. PMID: 18378627. 
27. 
Ailawadi G, Eliason JL, Upchurch GR, Jr. Current Concepts in the Pathogenesis of Abdominal 
Aortic Aneurysm. J Vasc Surg. 2003;38(3):584-8. PMID: 12947280. 
28. 
De Martino RR, Goodney PP, Nolan BW, et al. Optimal Selection of Patients for Elective 
Abdominal Aortic Aneurysm Repair Based on Life Expectancy. J Vasc Surg. 2013;58(3):589-95. 
PMID: 23642927. 
29. 
Newton WB, 3rd, Shukla M, Andrews JS, et al. Outcomes of Acute Intraoperative Surgical 
Conversion During Endovascular Aortic Aneurysm Repair. J Vasc Surg. 2011;54(5):1244-50; discussion 
50. 
30. 
Beck AW, Goodney PP, Nolan BW, et al. Predicting 1-Year Mortality after Elective Abdominal 
Aortic Aneurysm Repair. J Vasc Surg. 2009;49(4):838-43; discussion 43-4. PMID: 19341875. 
31. 
Parodi JC, Criado FJ, Barone HD, et al. Endoluminal Aortic Aneurysm Repair Using a 
Balloon- Expandable Stent-Graft Device: A Progress Report. Ann Vasc Surg. 1994;8(6):523-9. 
PMID: 7865389. 
32. 
Lederle FA, Wilson SE, Johnson GR, et al. Design of the Abdominal Aortic Aneurysm Detection 
and Management Study. ADAM VA Cooperative Study Group. J Vasc Surg. 1994;20(2):296-303. PMID: 
8040955. 
33. 
Aljabri B, Al Wahaibi K, Abner D, et al. Patient-Reported Quality of Life after Abdominal 
Aortic Aneurysm Surgery: A Prospective Comparison of Endovascular and Open Repair. J Vasc 
Surg. 2006;44(6):1182-7. PMID: 17145419. 
34. 
Jackson RS, Chang DC, Freischlag JA. Comparison of Long-Term Survival after Open 
Vs Endovascular Repair of Intact Abdominal Aortic Aneurysm among Medicare Beneficiaries. 
JAMA. 2012;307(15):1621-8. PMID: 22511690. 
35. 
Schermerhorn ML, O'Malley AJ, Jhaveri A, et al. Endovascular Vs. Open Repair of Abdominal 
Aortic Aneurysms in the Medicare Population. N Engl J Med. 2008;358(5):464-74. PMID: 18234751. 
36. 
Goodney PP, Tavris D, Lucas FL, et al. Causes of Late Mortality after Endovascular and Open 
Surgical Repair of Infrarenal Abdominal Aortic Aneurysms. J Vasc Surg. 2010;51(6):1340-7 e1. PMID: 
20385469. 
37. 
Park BD, Azefor NM, Huang CC, et al. Elective Endovascular Aneurysm Repair in the Elderly: 
Trends and Outcomes from the Nationwide Inpatient Sample. Ann Vasc Surg. 2013. PMID: 24189191. 
38. 
Chadi SA, Rowe BW, Vogt KN, et al. Trends in Management of Abdominal Aortic Aneurysms. J 
Vasc Surg. 2012;55(4):924-8. PMID: 22226189. 
39. 
Sethi RK, Henry AJ, Hevelone ND, et al. Impact of Hospital Market Competition on 
Endovascular Aneurysm Repair Adoption and Outcomes. J Vasc Surg. 2013;58(3):596-606. PMID: 
23684424. 
40. 
Ng TT, Mirocha J, Magner D, et al. Variations in the Utilization of Endovascular Aneurysm 
Repair Reflect Population Risk Factors and Disease Prevalence. J Vasc Surg. 2010;51(4):801-9, 9 
e1. 
41. 
Shah H, Kumar SR, Major K, et al. Technology Penetration of Endovascular Aortic Aneurysm 
Repair in Southern California. Ann Vasc Surg. 2006;20(6):796-802. PMID: 17136631. 
42. 
Goodney PP, West A. Prepatory to Research Analyses (Personal Communication) 2014. 

Contact PD/PI: Goodney, Philip 
 
29 
 
43. 
The Vascular Quality Initiative (VQI) 2013. Available from: www.vascularqualityinitiative.org. 
44. 
The Picker Institute. Survey of Patient Preference for Method of Abdominal Aortic Aneurysm 
Repair. 
45. 
Winterborn RJ, Amin I, Lyratzopoulos G, et al. Preferences for EVAR or Open repair among 
Patients with Abdominal Aortic Aneurysms under Surveillance. J Vasc Surg. 2009;49(3):576-81 e3. 
PMID: 19268761. 
46. 
Dubois L, Novick TV, Power AH, et al. Identification of Patient-Derived Outcomes after Aortic 
Aneurysm Repair. J Vasc Surg. 2014;59(6):1528-34. PMID: 24447539. 
47. 
Weinstein JN, Clay K, Morgan TS. Informed Patient Choice: Patient-Centered Valuing of Surgical 
Risks and Benefits. Health Aff (Millwood). 2007;26(3):726-30. PMID: 17485750; PMCID: 2918374. 
48. 
Weinstein JN. Partnership: Doctor and Patient: Advocacy for Informed Choice Vs. Informed 
Consent. Spine (Philadelphia, PA 1976). 2005;30(3):269-72. PMID: 15682004. 
49. 
Barry MJ. Shared Decision Making: Informing and Involving Patients to Do the Right Thing in 
Health Care. J Ambul Care Manage. 2012;35(2):90-8. PMID: 22415282. 
50. 
Barry MJ, Roberts WC. Michael John Barry, Md: A Conversation with the Editor on Shared 
Decision Making. Proc (Bayl Univ Med Cent). 2012;25(4):383-8. PMID: 23077396; PMCID: 3448587. 
51. 
Barry M. Six Steps of Shared Decision-Making: The Foundation For Informed Decision 
Making. Available from: http://www.slideshare.net/fimdm/six-steps-of-shared-decision-making. 
52. 
Lantz PM, Janz NK, Fagerlin A, et al. Satisfaction with Surgery Outcomes and the Decision 
Process in a Population-Based Sample of Women with Breast Cancer. Health Serv Res. 2005;40(3):745-
67. 
53. 
Katz SJ, Lantz PM, Janz NK, et al. Patient Involvement in Surgery Treatment Decisions for 
Breast Cancer. J Clin Oncol. 2005;23(24):5526-33. PMID: 16110013. 
54. 
Malas MB, Freischlag JA. Interpretation of the Results of over in the Context of Evar Trial, Dream, 
and the Eurostar Registry. Semin Vasc Surg. 2010;23(3):165-9. PMID: 20826293. 
55. 
Parodi JC. Endoluminal Stent Grafts: Overview. J Invasive Cardiol. 1997;9(3):227-9. PMID: 
10762904. 
56. 
Lederle FA, Stroupe KT, Open Versus Endovascular Repair Veterans Affairs Cooperative Study 
G. Cost-Effectiveness at Two Years in the Va Open Versus Endovascular Repair Trial. Eur J Vasc 
Endovasc Surg. 2012;44(6):543-8. PMID: 23116986. 
57. 
Elwyn G, Laitner S, Coulter A, et al. Implementing Shared Decision Making in the NHS. 
BMJ. 2010;341:c5146. PMID: 20947577. 
58. 
O'Connor AM, Wennberg JE, Legare F, et al. Toward the 'Tipping Point': Decision Aids and 
Informed Patient Choice. Health Aff (Millwood). 2007;26(3):716-25. PMID: 17485749. 
59. 
Guihan M, Hedrick S, Miller S, et al. Improving the Long-Term Care Referral Process: Insights 
from Patients and Caregivers. Gerontol Geriatr Educ. 2011;32(2):135-51. PMID: 21598147. 
60. 
Brehaut JC, O'Connor AM, Wood TJ, et al. Validation of a Decision Regret Scale. Med Decis 
Making. 2003;23(4):281-92. PMID: 12926578. 
61. 
O'Connor AM. Validation of a Decisional Conflict Scale. Med Decis Making. 1995;15(1):25-30. 
62. 
Powell JT, Sweeting MJ, et al. Endovascular or Open Repair Strategy for Ruptured Abdominal 
Aortic Aneurysm: 30 Day Outcomes from Improve Randomised Trial. BMJ. 2014;348:f7661. 
63. 
Becquemin JP. The Ace Trial: A Randomized Comparison of Open Versus Endovascular 
Repair in Good Risk Patients with Abdominal Aortic Aneurysm. J Vasc Surg. 2009;50(1):222-4; 
discussion 4. 
64. 
Sheldon H, Garratt E. Patient Preferences for Alternative Surgical Techniques for Abdominal 
Aortic Aneurysm Repair: Report of a Patient Survey2008. 
65. 
Nallamothu BK, Gurm HS, Ting HH, et al. Operator Experience and Carotid Stenting 
Outcomes in Medicare Beneficiaries. JAMA. 2011;306(12):1338-43. PMID: 21954477; PMCID: 
3208144. 
66. 
Goodney PP, Lucas FL, Birkmeyer JD. Should Volume Standards for Cardiovascular Surgery 
Focus Only on High-Risk Patients? Circulation. 2003;107(3):384-7. PMID: 12551859. 
67. 
Goodney PP, Lucas FL, Stukel TA, et al. Surgeon Specialty and Operative Mortality with 
Lung Resection. Ann Surg. 2005;241(1):179-84. PMID: 15622006; PMCID: 1356861. 
68. 
Goodney PP, Travis LL, Malenka D, et al. Regional Variation in Carotid Artery Stenting 
and Endarterectomy in the Medicare Population. Circ Cardiovasc Qual Outcomes. 
2010;3(1):15-24. 

Contact PD/PI: Goodney, Philip 
 
30 
 
69. 
Eslami MH, Doros G, Goodney PP, et al. Using Vascular Quality Initiative (Vqi) as a 
Platform for Organizing Multicenter, Prospective, Randomized Clinical Trials: Overpar Trial. Ann 
Vasc Surg. 2014. 
70. 
SVS Multicenter Clinical Trials Planning Grant 2013. Available from: 
http://www.vascularweb.org/about/SVSFoundation/Pages/Grant-
recipients.aspx. 
71. 
Goodney PP, Goodman DC, Barry M. Variation in the Care of Surgical Conditions: A Dartmouth 
Atlas Report. Hanover, NH: 2014 June 1, 2014. 
72. 
Goodney PP, Woloshin S, Schwartz LM. Fractional Flow Reserve-Guided Pci in Stable 
Coronary Disease. N Engl J Med. 2012;367(24):2355; author reply 6. PMID: 23234520. 
73. 
Birkmeyer JD, Stukel TA, Siewers AE, et al. Surgeon Volume and Operative Mortality in the 
United States. N Engl J Med. 2003;349(22):2117-27. PMID: 14645640. 
74. 
Lederle FA, Johnson GR, Wilson SE, et al. Rupture Rate of Large Abdominal Aortic 
Aneurysms in Patients Refusing or Unfit for Elective Repair. JAMA. 2002;287(22):2968-72. PMID: 
12052126. 
75. 
Lederle FA, Kane RL, MacDonald R, et al. Systematic Review: Repair of Unruptured Abdominal 
Aortic Aneurysm. Ann Intern Med. 2007;146(10):735-41. PMID: 17502634. 
76. 
Rigberg DA, Zingmond DS, McGory ML, et al. Age Stratified, Perioperative, and One-Year 
Mortality after Abdominal Aortic Aneurysm Repair: A Statewide Experience. J Vasc Surg. 
2006;43(2):224-9. 
77. 
Cowan JA, Jr., Dimick JB, Henke PK, et al. Epidemiology of Aortic Aneurysm Repair in the 
United States from 1993 to 2003. Ann N Y Acad Sci. 2006;1085:1-10. PMID: 17182917. 
78. 
VA Health Services Research and Development Website. Available from: 
http://www.hsrd.research.va.gov/research/abstracts.cfm?Project_ID=2141698717#.UoaZP9Qo6M8
. 
79. 
Bush RL, DePalma RG, Itani KM, et al. Outcomes of Care of Abdominal Aortic Aneurysm in 
Veterans Health Administration Facilities:. Am J Surg. 2009;198(5 Suppl):S41-8. PMID: 19874934. 
80. 
Westvik TS, Krause LK, Pradhan S, et al. Malnutrition after Vascular Surgery: Are Patients with 
Chronic Renal Failure at Increased Risk? Am J Surg. 2006;192(5):e22-7. PMID: 17071176. 
81. 
Elwyn G, Tsulukidze M, Edwards A, et al. Using a 'Talk' Model of Shared Decision Making to 
Propose an Observation-Based Measure: Observer Option 5 Item. Patient Educ Couns. 2013;93(2):265-
71. 
82. 
Elwyn G, Lloyd A, Joseph-Williams N, et al. Option Grids: Shared Decision Making Made 
Easier. Patient Educ Couns. 2013;90(2):207-12. PMID: 22854227. 
83. 
Couet N, Desroches S, Robitaille H, et al. Assessments of the Extent to Which Providers 
Involve Patients in Decisions: A Systematic Review Using the Option Instrument. Health Expect. 
2013. 
84. 
Schwartz LM, Woloshin S, Birkmeyer JD. How Do Elderly Patients Decide Where to Go for 
Major Surgery? Telephone Interview Survey. BMJ. 2005;331(7520):821. PMID: 16192286; PMCID: 
1246083. 
85. 
Suckow B, Goodney PP, Nolan B, et al. Domains That Determine Quality of Life in Vascular 
Amputees. J Vasc Surg. 2015;(in press). 
86. 
Elwyn G, Edwards A, Wensing M, et al. Shared Decision Making: Developing the Option Scale 
for Measuring Patient Involvement. Qual Saf Health Care. 2003;12(2):93-9. PMID: 12679504; PMCID: 
1743691. 
87. 
Vrijhoef HJ, Berbee R, Wagner EH, et al. Quality of Integrated Chronic Care Measured by 
Patient Survey: Identification, Selection and Application of Most Appropriate Instruments. Health 
Expect. 2009;12(4):417-29. PMID: 19709315. 
88. 
Schnurr PP. The Rocks and Hard Places in Psychotherapy Outcome Research. J Trauma 
Stress. 2007;20(5):779-92. PMID: 17955539. 
89. 
Watts BV, Schnurr PP, Zayed M, et al. A Randomized Controlled Clinical Trial of a Patient 
Decision Aid for Posttraumatic Stress Disorder. Psychiatr Serv. 2014. PMID: 25322473. 
90. 
Ronconi JM, Shiner B, Watts BV. Inclusion and Exclusion Criteria in Randomized Controlled 
Trials of Psychotherapy for Ptsd. J Psychiatr Pract. 2014;20(1):25-37. PMID: 24419308. 
91. 
Hoagland TV. The Principles in Psychotherapy with Veterans. J Mich State Med Soc. 
1952;51(1):62-4. 

Contact PD/PI: Goodney, Philip 
 
31 
 
92. 
Littlewood C, et al. A Study to Evaluate the Clinical and Cost-Effectiveness of a Self-Managed 
Exercise Programme Versus Usual Physiotherapy. BMC Musculoskelet Disord. 2012;13:62. PMID: 
22545990; 
93. 
Thompson SG, Ashton HA, Gao L, et al. Final Follow-up of the Multicentre Aneurysm Screening 
Study (MASS) Randomized Trial of Abdominal Aortic Aneurysm Screening. Br J Surg. 2012;99(12):1649-
56. 
94. 
Thompson SG, Brown LC, Sweeting MJ, et al. Systematic Review and Meta-Analysis of the 
Growth and Rupture Rates of Small Abdominal Aortic Aneurysms: Implications for Surveillance Intervals 
and Their Cost-Effectiveness. Health Technol Assess. 2013;17(41):1-118. PMID: 24067626. 
95. 
Collaborators R, Bown MJ, Sweeting MJ, et al. Surveillance Intervals for Small Abdominal 
Aortic Aneurysms: A Meta-Analysis. JAMA. 2013;309(8):806-13. PMID: 23443444. 
96. 
Schanzer A, Greenberg RK, Hevelone N, et al. Predictors of Abdominal Aortic Aneurysm 
Sac Enlargement after Endovascular Repair. Circulation. 2011;123(24):2848-55. PMID: 
21478500. 
97. 
Goodney PP, Lucas FL, Travis LL, et al. Changes in the Use of Carotid Revascularization 
among the Medicare Population. Arch Surg. 2008;143(2):170-3. PMID: 18283142. 
98. 
Goodney PP, Holman K, Henke PK, et al. Regional Intensity of Vascular Care and Lower 
Extremity Amputation Rates. J Vasc Surg. 2013;57(6):1471-79, 80 e1-3; discussion 9-80. PMID: 
23375611; 
99. 
Stone DH, Goodney PP, Kalish J, et al. Severity of Chronic Obstructive Pulmonary 
Disease Is Associated with Adverse Outcomes in Patients Undergoing EVAR. J Vasc Surg. 
2013;57(6):1531-6. 
100. 
Goodney PP, Beck AW, Nagle J, et al. National Trends in Lower Extremity Bypass 
Surgery, Endovascular Interventions, and Major Amputations. J Vasc Surg. 2009;50(1):54-60. 
PMID: 19481407. 
101. 
West AN, Lee PW. Associations between Childbirth and Women Veterans' VAa and 
Non-VA Hospitalizations for Major Diagnostic Categories. Mil Med. 2013;178(11):1250-5. 
PMID: 24183775. 
102. 
Lee PW, Markle PS, West AN, et al. Use and Quality of Care at a Va Outreach Clinic in 
Northern Maine. J Prim Care Community Health. 2012;3(3):159-63. PMID: 23803775. 
103. 
West AN, Weeks WB, Wright SM, et al. When Va Patients Have Non-Va Hospitalizations, Who 
Pays for What Services, and What Are the Research Implications? A New York Case Study. Med Care. 
2008;46(8):872 
104. 
Fowler FJ, Jr., Gallagher PM, Bynum JP, et al. Decision-Making Process Reported by 
Medicare Patients Who Had Coronary Artery Stenting or Surgery for Prostate Cancer. J Gen 
Intern Med. 2012;27(8):911-6. PMID: 22370767; PMCID: 3403150. 
105. 
Faerber AE, Horvath R, Stillman C, et al. Development of a Health Information Technology 
Tool for Patients with carotid stenosis. BMC Med Inform Decis Mak. 2015;15(1):20. PMID: 25890090; 
106. 
Efron B, Tibshirani R. Improvements on Cross-Validation: The .632+ Bootstrap Method. J Am 
Stat Assoc. 1997;92(438):548-60. 
107. 
Sim J, Wright CC. The Kappa Statistic in Reliability Studies: Use, Interpretation, and Sample 
Size Requirements. Phys Ther. 2005;85(3):257-68. PMID: 15733050.