Evaluation of the National Randomized Proton Pump Inhibitor De-prescribing (RaPPID) Program
Phase: NA
Conditions: Proton Pump Inhibitors
Sponsor: VA Office of Research and Development

 
 
 
 
Evaluation of the National Randomized Proton Pump 
Inhibitor De-Prescribing (RaPPID) Program  
National Clinical Trial (NCT) Identified Number:  NCT03719170 
Principal Investigators: Sameer D. Saini (contact), Yu-Xiao Yang, Loren Laine 
Sponsor: VA Health Services Research & Development 
Grant Title: Evaluation of the National Randomized Proton Pump Inhibitor De-
Prescribing (RaPPID) Program 
Grant Number*: HX002693 
Funded by: VA Office of Research & Development 
Version Number:  v.1.0 (final) 
28 May 2019 
 

Evaluation of the National Randomized Proton Pump Inhibitor De-Prescribing (RaPPID) Program 
  
NCT03719170 
 
 
 
 
 
Table of Contents 
1 
PROTOCOL SUMMARY ............................................................................................................................... 1 
1.1 
Synopsis ................................................................................................................................................ 1 
1.2 
Schema ................................................................................................................................................. 2 
2 
INTRODUCTION ............................................................................................................................................ 3 
2.1 
Study Rationale .................................................................................................................................... 3 
2.2 
Background ........................................................................................................................................... 3 
2.2.1 
Preliminary work ............................................................................................................... 4 
2.3 
Risk/Benefit Assessment .................................................................................................................... 5 
2.3.1 
Known Potential Risks ..................................................................................................... 5 
2.3.2 
Known Potential Benefits ................................................................................................ 5 
2.3.3 
Assessment of Potential Risks and Benefits ................................................................ 6 
3 
PRIMARY OBJECTIVES AND ENDPOINTS ............................................................................................. 6 
4 
STUDY DESIGN ............................................................................................................................................. 7 
4.1 
Overall Design ...................................................................................................................................... 7 
4.1.1 
PROCEDURES ................................................................................................................ 7 
4.1.2 
Provider Educational Material Excerpt .......................................................................... 8 
4.2 
Justification for Intervention ............................................................................................................... 9 
4.3 
End-of-Study Definition ....................................................................................................................... 9 
5 
STUDY POPULATION .................................................................................................................................. 9 
5.1 
Inclusion Criteria .................................................................................................................................. 9 
5.2 
Exclusion Criteria ............................................................................................................................... 10 
6 
EXPERIMENTAL MANIPULATIONS ........................................................................................................ 10 
6.1 
Experiment .......................................................................................................................................... 10 
6.2 
Measures to Minimize Bias: Randomization and Blinding ........................................................... 11 
6.3 
Participant Withdrawal from the Study & LoST TO follow-up ..................................................... 11 
7 
PROCEDURES AND STUDY ASSESSMENTS ...................................................................................... 11 
7.1 
Procedures ......................................................................................................................................... 11 
7.2 
Data collection .................................................................................................................................... 11 
7.2.1 
Variables & data sources .............................................................................................. 12 
7.2.2 
Study assessments ........................................................................................................ 12 
8 
STATISTICAL ANALYSES ......................................................................................................................... 13 
8.1 
Sample Size Determination .............................................................................................................. 13 
8.1.1 
Primary outcome ............................................................................................................ 13 
8.1.2 
Veteran surveys ............................................................................................................. 13 
8.1.3 
FINAL REPORT UPDATE: RCT CONSORT DIAGRAM ......................................... 14 
8.1.4 
FINAL REPORT UPDATE: SURVEYS CONSORT DIAGRAM .............................. 15 
8.2 
Populations for Analyses .................................................................................................................. 16 
8.3 
Statistical Analyses ............................................................................................................................ 16 
8.3.1 
Baseline Descriptive Statistics ..................................................................................... 16 
9 
SUPPORTING DOCUMENTATION .......................................................................................................... 16 
9.1 
Regulatory, Ethical, and Study Oversight Considerations ........................................................... 16 
9.2 
Protocol deviations ............................................................................................................................ 17 
9.3 
Publication and data sharing policy ................................................................................................. 17 
9.4 
Conflict of interest policy ................................................................................................................... 17 
9.5 
Abbreviations and Special Terms ................................................................................................... 17 

Evaluation of the National Randomized Proton Pump Inhibitor De-Prescribing (RaPPID) Program 
  
NCT03719170 
 
 
 
 
 
9.6 
Protocol Amendment History ........................................................................................................... 20 
10 
REFERENCES ............................................................................................................................................. 20 

Evaluation of the National Randomized Proton Pump Inhibitor De-Prescribing (RaPPID) Program 
  
NCT03719170 
 
 
 
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1 
PROTOCOL SUMMARY 
1.1 
SYNOPSIS  
Background  
Proton pump inhibitors (PPIs) are among the most commonly prescribed medications in the Veterans Health 
Administration (VHA), accounting for over 11 million 30-day prescriptions and nearly $50 million in medication costs 
annually. Though effective for treatment of acid-related disorders such as gastroesophageal reflux disease (GERD), PPIs 
have been associated with a number of possible harms in observational studies (e.g., enteric infections such as 
Clostridium difficile colitis, pneumonia, chronic kidney disease, fractures, dementia, and a recent VA study reported 
increased mortality in Veterans receiving PPIs). Unfortunately, PPIs continue to be used without an appropriate 
indication or for longer and at higher doses than necessary. Accordingly, in September 2019, VHA Pharmacy Benefits 
Management Services (PBM) deployed the Randomized PPI De-Prescribing (RaPPID) Program – a national, multi-level PPI 
de-prescribing initiative targeting patients for whom chronic PPI therapy may not be necessary. This program, modeled 
after a successful initiative in one Veterans Integrated Service Network (VISN), comprises 3 key components: (1) 
activation of clinical pharmacy specialists; (2) provider education and targeted notifications and academic detailing; and, 
(3) patient education.  
 
Objectives 
We sought to evaluate RaPPID through a cluster-randomized trial of PPI de-prescribing involving 17 VISNs to (1) 
identifying barriers and facilitators to implementation of RaPPID; and (2) understanding whether the program is 
effective at improving appropriate use of PPIs and whether there are any unintended consequences, (3) assessing how 
successfully the program components are delivered, a critical question in understanding why the program did or did not 
work as intended; and, (4) estimating the costs and possible savings associated with the program and with PPI de-
prescribing in general. 
 
Methods 
We evaluated RaPPID in the context of a nationwide, stratified cluster-randomized controlled trial that incorporated 
assessments of both effectiveness and implementation (hybrid type II; cluster = VISN). Initially, the dashboard algorithm 
was validated and evaluated, the dashboard was user-tested and refined (months 1-11), the program was deployed 
nationally in a cluster-randomized fashion (months 12-24), and subjects were followed for 12 months (months 24-36). In 
months 18-30, we conducted a process evaluation. Data sources included VA Corporate Data Warehouse (CDW), patient 
surveys, and interviews with VISN Pharmacy Executives, PBM Academic Detailers, pharmacists, and primary care 
providers.  
 
Impact 
This approach allowed us to simultaneously understand barriers and facilitators to implementation of a program focused 
on stopping use of a specific treatment (de-implementation), share data with VA PBM so they could refine the program 
to maximize fidelity and consistency of implementation, measure important clinical outcomes, and improve the health 
of Veterans at scale. The study also provided broader lessons about how to effectively undertake other such nation-wide 
interventions.  
 
 
 

Evaluation of the National Randomized Proton Pump Inhibitor De-Prescribing (RaPPID) Program 
  
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1.2 
SCHEMA  
 
Months 1-11 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Month 12 
 
 
 
 
 
 
Months 12-24 
 
 
 
 
Months 15-27  
 
 
 
 
Months 24-36 
 
 
 
 
 
Months 36-42 
 
 
 
Data Analyses 
 
Control 
N = 8 VISNs 
Intervention 
N = 9 VISNs 
Randomize 
Activate VISN Pharmacy Executives, Clinical Pharmacy Specialists & Academic 
Detailers 
Make Dashboard Available to Intervention Sites 
12-month Follow-up of Enrolled Patients 
Validate PPI Dashboard Algorithm & Test User Interface 
Develop Educational Materials 
Electronically Enroll Patients in Dashboard  
Send Baseline Surveys to Patients of 2 VISNs (1 from each arm) 
Send 3-Month Follow-up Surveys to Patients of 2 VISNs (1 from each arm) 

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2 
 
INTRODUCTION 
2.1 
STUDY RATIONALE  
 
Focusing VHA resources more efficiently through de-implementation of low-value care is one of VHA’s top 5 strategic 
priorities. But, to date, large-scale, programmatic initiatives to reduce the use of low-value care had been uncommon (24). 
This partnered evaluation gave VHA the opportunity to reduce the use of a low-value service, thereby improving the health 
of Veterans, while also making several key scientific contributions. First, it provided real-time insights into barriers and 
facilitators of a large-scale de-implementation effort from the perspective of Veterans, providers, and systems. The 
knowledge gained was “fed back” to our partners in PBM to further enhance future efforts to de-prescribe in other clinical 
contexts (such as de-prescribing of anti-hypertensives and diabetes medications in older adults) (25). Notably, this was 
among the largest de-prescribing initiatives ever conducted. Additionally, this is a topic of high priority for our partners at 
PBM, the VHA GI Program Office, and the Chief Research and Development Officer (CRADO). A second major contribution 
of the study was the ability to make generalizable conclusions about the risk-benefit ratio of PPI de-prescribing, as well as 
the true risks posed by PPIs, by virtue of the study’s large (VHA-wide) scale, cluster-randomized design, and duration. Prior 
randomized trials of PPI deprescribing have been relatively small and short in duration, limiting their ability to detect 
serious but uncommon harms of de-prescribing, such as upper GI bleeding or increased healthcare utilization. Additionally, 
we planned to rigorously assess the impact of reduced PPI use on selected adverse effects. Whether PPIs truly cause the 
harms with which they have been associated remains a major unresolved scientific question. Thus, the proposed work 
aligned well with VHA’s broader goal of becoming a Learning Health System and leveraging electronic health record (EHR) 
data to conduct an evaluation of the planned implementation of a high-priority national clinical program. 
 
2.2 
BACKGROUND  
Proton pump inhibitors (PPIs) are among the most commonly used medications in the United States. While these 
medications are highly effective for acid peptic disorders, observational studies suggest that they can cause harm. Prior 
studies have reported harms associated with PPI use, including vitamin B12 deficiency, hypomagnesemia, fractures, 
enteric infections (e.g., C. difficile colitis), pneumonia, and myocardial infarctions (1,2). More recent studies have 
reported additional associations with chronic kidney disease, dementia, stroke, and death (3,9–11). 
Despite data on possible harms, PPIs are overused. Given the possible harms associated with PPIs, identification of 
patients unlikely to benefit from long-term daily use is a top priority. The Choosing Wisely® Campaign stated that more 
than half of those who take PPIs may not need them, and that if gastroesophageal reflux disease (GERD) symptoms 
resolve after a few weeks, patients should stop their PPIs. Despite such recommendations, preliminary data suggest that 
>33% of Veterans who use PPIs do not have a clear indication or have well-controlled, uncomplicated GERD. Given that 
~15% of Veterans take PPIs chronically, large numbers of Veterans may be incurring harm with little or no benefit. 
Efforts to de-prescribe PPIs have shown efficacy but have failed to be widely adopted. The data on PPI overuse and 
harms have generated interest in de-prescribing – “the process of withdrawal of an inappropriate medication, 
supervised by a healthcare professional with the goal of managing polypharmacy and improving outcomes.” (12) De-
prescription of PPIs has been evaluated in small trials of patients with GERD. For example, a prospective study 
conducted at the VA Ann Arbor Healthcare System (VAAAHS) in 2001 evaluated de-prescription in 71 patients with well-
controlled GERD. 58% of these 71 patients were successfully de-prescribed at 1 year, but most (73%) required H2-
receptor antagonists (H2RAs) or prokinetics for control of symptoms. De-prescription did not reduce quality of life or 
worsen disease severity (13). In another study of 117 VA patients with well-controlled GERD on twice-daily PPI, 80% 
were symptom-free 6 months after stepping-down to once-daily dosing (14). Finally, in one VISN, a pharmacy-led 
program that leveraged clinical pharmacy specialist (CPS) providers, academic detailing, and patient education showed a 

Evaluation of the National Randomized Proton Pump Inhibitor De-Prescribing (RaPPID) Program 
  
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reduction in PPI use in an uncontrolled analysis (33% relative reduction in PPI use compared to the average VISN, per 
PBM), and this reduction has been sustained over several years such that that VISN has the lowest PPI use nationally.  
Stopping PPIs in the wrong patients can cause harm. By blocking the production of gastric acid, PPIs are highly effective 
at preventing and treating peptic ulcer disease (PUD) and its complications (e.g., upper gastrointestinal (GI) bleeding and 
subsequent need for hospitalization, transfusion, endoscopic therapy, surgery). As a corollary, stopping PPIs in patients 
who are at increased risk for PUD can promote upper GI bleeding, the most common cause of GI hospitalization in the 
United States. The widespread use of antiplatelet agents for cardiovascular prevention and the growing use of direct 
anticoagulants means that many Veterans are now at increased risk for upper GI bleeding. Moreover, bleeding is not the 
only potential unintended consequence of stopping PPIs. A 2017 Cochrane review of randomized trials of PPI de-
prescription included 6 studies of de-prescription in patients with PPI-responsive GERD (15). Those randomized to de-
prescription followed by on-demand therapy showed a 58% reduction in PPI pill use (3.79 vs 6.57 pills per week), but 
they also experienced an increase in poor symptom control (RR=1.71; 95% CI: 1.31-2.21). These data suggest that any 
PPI de-prescribing program must: (1) ensure appropriate de-prescribing – that patients who are taking PPIs for GERD are 
offered a trial off PPI therapy while those who are at increased risk for GI bleeding are NOT inadvertently taken off their 
PPIs; and, (2) assess for potential unintended consequences including worsening in upper GI symptoms or quality of life 
(assessed through patient-reported outcomes (PROs)) and an increase in upper GI bleeding events. Further refinement 
and validation of an existing electronic algorithm to identify candidates for appropriate de-prescribing was a core 
deliverable from this study. 
Due to concern about PPI overuse and harms, PBM deployed a national program to appropriately de-prescribe PPIs in 
2019-2020. In light of the data on overuse and PPI harms, PBM deployed a national de-prescribing program in 2019 – 
the Randomized PPI De-Prescribing (RaPPID) Program. RaPPID was modeled after the successful experience of a VISN 
program, with modifications to ensure that de-prescribing is appropriate and efficient (using the electronic algorithm 
developed by our team) and that randomization and deployment was feasible at the national level. Specifically, the 
program leveraged PBM infrastructure at multiple levels of the health system, including their national network of clinical 
pharmacy specialist (CPS) providers, an electronic dashboard system, PBM’s academic detailing capabilities, and patient 
education. We worked closely with the Director of Center for Medication Safety at PBM to coordinate the evaluation of 
RaPPID. PBM’s planned de-prescribing program offered a rare opportunity to study the effectiveness of PPI de-
prescribing and the barriers and facilitators of a large-scale de-implementation effort. 
 
2.2.1 PRELIMINARY WORK  
PPIs are among the most commonly used medications in VHA. Working with PBM, we examined the prevalence of PPI 
use in Veterans as well as associated costs. Based on these data, PPIs were used regularly (> 270 days per year) in 15.4% 
of Veterans. While the cost of these drugs was low on a per-pill basis, their widespread use incurred significant cost – 
approximately $50,000,000 per year in direct drug costs alone. At least one-third of Veterans using PPIs had no clear 
indication or had only uncomplicated GERD. Together, these Veterans (using PPI for no indication or for uncomplicated 
GERD without risk factors for upper GI bleeding) were the focus of RaPPID. 
PPIs have the potential to cause long-term, debilitating harms. Multiple PD/PIs Drs. Yang and Laine have published 
multiple pivotal studies investigating the adverse effects of PPIs (16–20). Although these epidemiological studies cannot 
definitively address whether these adverse effects are truly caused by PPIs, there are biologically plausible mechanisms 
linking these potent acid suppressants to a number of physiological changes that could mediate the reported adverse 
effects. Therefore, PPI therapy in patients without an appropriate indication is a low-value, potentially harmful practice 
that is not recommended. 

Evaluation of the National Randomized Proton Pump Inhibitor De-Prescribing (RaPPID) Program 
  
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Most patients using PPIs are concerned about adverse effects. In 2017, co-investigator Jacob Kurlander surveyed 755 
patients using PPIs for GERD in an online survey sample (manuscript under review at JAMA-IM). Of these 755 patients, 
54% reported awareness of one or more PPI-related adverse effects, most commonly chronic kidney disease (17%), and 
78% reported at least some concern about PPI adverse effects. Only 24% reported that a physician had discussed PPI 
risks and benefits with them, and only 9% had been encouraged to stop by a physician. Independent predictors of a prior 
attempt to stop included: (1) physician recommendation (OR 3.26, 95% CI: 1.82-5.83); and (2) concern about PPI-related 
adverse effects (OR 12.0, 95% CI: 6.51-22.2). Notably, patients at high risk of upper GI bleeding, who require long-term 
PPIs for gastroprotection, were just as likely to have stopped their PPI as others (OR 0.97, 95% CI: 0.66-1.44). This study 
underscores the prevalence of public concern about PPI-related harms and the potential dangers of self-directed 
attempts at PPI discontinuation, which could be harmful in the wrong patients. 
Providers are also concerned about PPI-related adverse effects but inappropriately recommend withdrawing PPIs 
from high-risk patients. We surveyed a representative sample of internists in the United States (N=487, response rate 
53%) to evaluate how physicians were changing their PPI prescribing practices due to concern about adverse effects 
(21). Of the sample, 63% reported sometimes or often taking steps to reduce their patients’ exposure to PPIs by 
reducing the dose, switching to an H2RA, or stopping the PPI altogether. Providers were also asked to report how likely 
they would be to recommend PPI de-prescription in a patient with bone loss (a potential PPI adverse effect) in vignettes 
of patients at low, intermediate, and high risk for upper GI bleeding. Surprisingly, providers were more likely to stop PPI 
in the high-risk vignette (62%) than in the intermediate-risk vignette (47%) or the low-risk vignette (32%). These findings 
show the importance of having an algorithm that can identify patients who are at high risk for GI bleeding to guide 
appropriate de-prescribing of PPIs. 
An electronic algorithm can reliably identify candidates for PPI de-prescription in a pilot study. Dr. Yang, and co-
investigator, Brian Sauer, have previously used CDW data to identify candidates for PPI de-prescribing. For example, Drs. 
Yang and Sauer developed an electronic algorithm to identify Veterans who had been prescribed PPIs in 2012. They 
identified ~3,000,000 Veterans who had at least one PPI prescription in the prior year, 33% of whom did not have an 
appropriate indication. In other work, Dr. Yang undertook pilot development and validation of an algorithm to identify 
appropriate candidates for PPI de-prescribing (i.e., chronic PPI users with uncomplicated GERD or without clear 
indication – the target population for RaPPID) at the Philadelphia VA Medical Center. A CDW-based algorithm was 
developed to identify candidates for de-prescribing, and validation was performed through manual record review of 100 
patients randomly selected from over 9,000 PPI users. The sensitivity of the CDW algorithm for identifying appropriate 
de-prescribing candidates was 100% (95% CI: 90%-100%), and the specificity was 97% (95% CI: 89%-100%). While these 
results were impressive, they were obtained at a single center. Additional refinement and validation were performed 
during our planning period. Given the large number of Veterans using PPIs, it was imperative that the algorithm used to 
identify de-prescribing candidates in RaPPID have high specificity to prevent alert fatigue and obsolescence among 
providers. 
2.3 
RISK/BENEFIT ASSESSMENT  
2.3.1 KNOWN POTENTIAL RISKS  
There were no physical risks from participation. The study’s chief risk is the psychosocial/financial/legal risk of potential 
loss of confidentiality. We stored electronic files that contain personal identifiers. The investigative team used their  
considerable experience in maintaining the confidentiality of large datasets and adhered to all VHA established procedures 
in place to ensure data confidentiality. 
2.3.2 KNOWN POTENTIAL BENEFITS  
No direct benefits to the subjects themselves were anticipated, as they were not being treated. However, this study’s 
findings directly enhanced all Veterans’ care by gaining insights about how to appropriately de-prescribe PPIs and how to 

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effectively undertake other such interventions to “unlearn” entrenched clinical practices in the future. Thus, the benefit 
to future VA patients was likely to be substantial.  
 
2.3.3 ASSESSMENT OF POTENTIAL RISKS AND BENEFITS  
Risk Minimization 
The risks to subjects were minimal and were addressed by following strict privacy and confidentiality procedures regarding 
how data are collected, stored, and used throughout the course of this project. There were no physical risks to 
participation in this study. There was potential risk of psychological, financial, or legal harm due to exposure of personally 
identifying information (PII) or protected health information (PHI). However, the risk of a breach of confidentiality was 
low. Throughout the study, VHA, IRB, and HIPAA guidelines were followed to ensure the privacy and integrity of the 
information collected. Any breach would have been immediately reported to the PD/PIs and the appropriate IRBs. To 
minimize the risk of a breach of confidentiality, we performed the following steps. First, as soon as the cohort was defined 
by the data manager, each patient in the cohort was assigned a unique study ID unrelated to any identifying information. 
We then created a limited access electronic tracking file that mapped the study participant’s identifying information to 
the study ID.  
 
Importance of Knowledge to be Gained 
VHA has long been a leader in measuring and delivering high-quality care. In recent years, however, it has become 
increasingly apparent that efforts to promote quality have inadvertently led to the use of not only high-value, but also 
low-value care. To date, however, large-scale, programmatic initiatives to reduce the use of low-value care have been 
uncommon. This partnered evaluation gave VHA the opportunity to simultaneously address the use of a low-value clinical 
service and to understand multi-level barriers to de-implementation of a commonly prescribed medication. Additionally, 
by randomizing the program, VHA ensured that efforts to de-prescribe PPIs do not cause unintended harms (such as upper 
GI bleeding) and assess the effect of reduced PPI use on selected adverse effects (such as enteric infections, fractures, 
pneumonia, and hypomagnesemia). Notably, this was the largest de-prescribing initiative ever conducted. Studying its 
effects in real time yielded valuable generalizable knowledge about how systems can effectively de-implement low-value 
care. Moreover, the randomized evaluation yielded clinical knowledge about the balance of benefit and harm for PPIs, 
knowledge that was unlikely to be acquired in any other evaluation. 
 
3 
PRIMARY OBJECTIVES AND ENDPOINTS  
 
 
OBJECTIVES 
ENDPOINTS 
JUSTIFICATION FOR ENDPOINTS 
Primary 
Proportion of days PPIs are 
prescribed at or above the 
baseline daily dosing-
frequency, over the 12 
months following the index 
visit. 
 
We hypothesize (H1) that the 
proportion of days will be lower 
in intervention group than in the 
control group (i.e., that the 
outcome will be superior in the 
intervention vs control group). 
This outcome is analogous to the 
medication possession ratio. 
This is the appropriate measure of 
success of de-prescribing because it 
captures a variety of results in a single 
endpoint, including discontinuation 
without resumption, discontinuation with 
intermittent or on-demand use, and 
resumption of daily PPI at or above 
baseline dosing frequency. 
 
 
 

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4 
STUDY DESIGN 
4.1 
OVERALL DESIGN 
 
Study Design: We evaluated RaPPID in the context of a nationwide, stratified cluster-randomized controlled trial that 
incorporated assessments of both effectiveness and implementation (hybrid type II) (28). RaPPID was a multi-level de-
prescribing program modeled after a similar initiative developed and deployed in one VISN in 2015. After validating and 
testing the deprescribing algorithm and dashboard, developing educational materials and randomization (months 1-11), 
the program was deployed nationally in a cluster-randomized fashion (months 12-24). During the randomization and 
subsequent follow-up period (months 24-36), we assessed the program’s impact on a variety of clinical outcomes.  
 
Study Population and Sample: De-prescribing of PPIs has potential clinical and economic benefits (by reducing 
unnecessary daily use of a medication with possible long-term harms). However, de-prescribing may also be harmful due 
to worsening upper GI symptoms and increased risk of upper GI bleeding. To maximize potential benefit and minimize 
potential harm, RaPPID focused on “chronic PPI users” (defined as daily PPI for ≥ 90 days during the 120-day period prior 
to PCP visit) with uncomplicated GERD, OR with no clear indication for PPI. Those who had acceptable indications for 
chronic PPI therapy (e.g., NSAID use, anti-thrombotic use, PUD, Barrett’s esophagus, erosive esophagitis, eosinophilic 
esophagitis) were excluded. Identification of candidates for appropriate de-prescription was facilitated by a high-
specificity electronic algorithm, as discussed in Section 2.2, Background. 
4.1.1 PROCEDURES 
Overview of RaPPID: RaPPID was a multi-level program modeled after a successful de-prescribing initiative in one VISN. 
The program had 3 main components: (1) activation of VISN Pharmacy Executives (VPEs) and their subsequent activation 
of Clinical Pharmacy Specialist (CPS) providers at VA Healthcare Systems within their VISNs; (2) provider education with 
targeted academic detailing and notifications; and, (3) patient education. CPS providers are pharmacists with training and 
expertise in medication stewardship, quality improvement, and medication-use evaluation. Many CPS providers have a 
broad scope of practice that allows them to prescribe and de-prescribe medications, deliver provider and patient 
education, and provide professional-to-professional academic detailing, and they often work with other clinical providers 
and patients to improve appropriate medication use (29). PBM has successfully used CPS providers in several national 
medication safety initiatives. In RaPPID, PBM leveraged this national network of experienced CPS providers to undertake 
this initiative focused on safely de-prescribing PPIs. Specifically, PBM asked VPEs randomized to the intervention to 
identify local CPS providers to champion the program at their respective facilities. CPS providers were then be “activated” 
with a variety of standardized tools (see below). It is important to note that while PBM had extensive experience in 
conducting medication evaluations, RaPPID was novel in several ways: (1) it was randomized – PBM had experience 
conducting randomization in the context of research studies using similar tools, (2) it involved one of the most commonly 
prescribed medications in VHA – prior evaluations had been significantly smaller in scale; and, (3) it involved appropriate 
de-prescribing – prior de-prescribing efforts had focused on acute medication safety issues, where de-prescribing 
recommendations were less nuanced and less apt to cause harm (such as upper GI bleeding due to inappropriate de-
prescribing of PPIs). 
 
Activation of CPS Providers: CPS providers were “activated” with a variety of standardized tools, including: (1) the PPI 
Dashboard; (2) educational materials to help CPS providers promote RaPPID to PCPs and clinical staff at their facilities; 
and, (3) educational materials for patients who were de-prescribed, to provide guidance and support for managing 
bothersome symptoms in the period immediately after de-prescribing. The PPI Dashboard served several important 
purposes. It allowed the CPS providers to efficiently identify PPI de-prescribing candidates up to 4 weeks ahead of a 
scheduled primary care visit. It also allowed CPS providers to track patients who had been de-prescribed and monitor 
adoption of de-prescribing by individual providers. Data on adoption allowed the CPS providers to deliver academic 

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detailing (using local and regional academic detailing resources managed by PBM) to providers who appeared to be slow 
to adopt de-prescribing recommendations. 
 
RaPPID De-Prescribing Regimen: The RaPPID de-prescribing regimen varied according to whether the Veteran was 
receiving once-daily or twice-daily PPI therapy. For patients on twice-daily PPI, the dosing frequency was reduced to once-
daily and maintained at that dose (i.e., 50% dose reduction). For patients on once-daily PPI, the dose was to first be tapered 
to once-daily PPI every other day for 2 weeks, followed by discontinuation. All patients were to be prescribed H2RAs to 
be taken as needed for intermittent upper GI symptoms. Written educational information regarding de-prescription was 
to be provided to patients by the primary care team. The recommended de-prescribing regimen and appropriate 
management of recurrent symptoms was a key component of provider and patient education and (as needed) academic 
detailing. 
 
Deployment of RaPPID: CPS providers used a variety of methods to initiate contact with PCPs at healthcare systems within 
VISNs randomized to RaPPID, including direct contact at primary care staff meetings and electronic contact via email. PCPs 
were to be educated and trained on: (1) the scientific justification for RaPPID; (2) VHA’s national commitment to the 
program; (3) the protocol for de-prescribing; and, (4) resources for Veterans who are de-prescribed (educational materials, 
consultation with CPS providers). CPS providers adapted (as needed) standardized educational materials to their local sites 
and worked with primary care leadership at their sites to devise efficient methods for disseminating these materials (e.g., 
during team meetings). Additionally, the VHA National Program Office for Gastroenterology notified VHA GI Section Chiefs 
and providers of the effort as part of national field calls and email listserv updates. Once RaPPID was deployed, CPS 
providers used the Dashboard to identify and track candidates for de-prescribing and notified PCPs of candidates using 
locally adapted approaches (e.g., note in CPRS, email). 
 
4.1.2 PROVIDER EDUCATIONAL MATERIAL EXCERPT 
The text and table below were part of the educational materials for Pharmacy and Primary Care providers. 
It is recommended that patients meeting inclusion-exclusion criteria should be deprescribed using one of the methods 
below. Some patients with GERD are expected to have recurrence of frequent bothersome symptoms intermittently 
in the coming months or years. Studies have suggested such patients can be well-managed by intermittent courses of 
once-daily PPI for up to 4 weeks. On-demand PPI therapy (in which the patient takes PPIs as they determine is needed 
based on symptoms and response) is also shown to be well accepted by patients with GERD. Only a minority of GERD 
patients should require daily maintenance PPI therapy to provide acceptable symptom relief.  
Patients Taking PPIs 
Once Daily 
Twice Daily 
 Taper to every other day for 2 weeks and then 
discontinue  
 Prescribe H2-receptor antagonists (e.g., 
famotidine, ranitidine) to take as needed for 
intermittent recurrent symptoms 
 Taper to once daily PPI, taken 30-60 minutes 
before a meal 
Patients should be cautioned that they may have rebound symptoms for a few weeks after discontinuation.  
 

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4.2 
JUSTIFICATION FOR INTERVENTION 
Proton pump inhibitors (PPIs) are among the most commonly prescribed medications in the Veterans Health 
Administration (VHA), accounting for over 11 million 30-day prescriptions and nearly $50 million in medication costs 
annually. Though effective for treatment of acid-related disorders such as gastroesophageal reflux disease (GERD), PPIs 
have been associated with possible harms in observational studies (e.g., enteric infections such as Clostridium difficile 
colitis, pneumonia, chronic kidney disease, fractures, dementia) (1,2), and a 2017 VA study reported increased mortality 
in Veterans receiving PPIs (3). Unfortunately, PPIs continue to be used without an appropriate indication or for longer and 
at higher doses than necessary (4,5).  Accordingly, in 2019, VHA Pharmacy Benefits Management Services (PBM) deployed 
the Randomized PPI De-Prescribing (RaPPID) Program – a national, multi-level PPI de-prescribing initiative targeting 
patients for whom chronic PPI therapy may not be necessary. This program, modeled after a successful initiative in one 
VISN, was comprised of 3 key components: (1) activation of clinical pharmacy specialists; (2) provider education and 
targeted notifications and academic detailing; and (3) patient education. 
 
RaPPID was among the largest concerted efforts at de-prescribing ever undertaken in VHA. Prospective evaluation of the 
program therefore presented a unique opportunity not only to enhance the program itself, but also to gain insights into 
how to reduce the use of low-value services more broadly, a key VHA priority for the coming decade. Indeed, estimates 
suggest that 10% of all healthcare spending in the U.S. pays for unnecessary care (6). But reducing the use of low-value 
care is challenging for many reasons. Programs to reduce low-value care often employ multiple interacting components, 
deployed in active healthcare delivery contexts, and they require patients, providers, and systems to “unlearn” well-
established behaviors and expectations about healthcare delivery (7,8). These challenges are compounded when efforts 
are scaled to the level of an entire health system. 
4.3 
END-OF-STUDY DEFINITION 
The end of the study is defined as completion of the 12-month follow-up period of the last enrolled subject.  
5 
STUDY POPULATION 
5.1 
INCLUSION CRITERIA 
The target population was chronic proton pump inhibitor (PPI) users who had a scheduled primary care visit.  
Chronic PPI Users 
Defined as: ≥90-day prescription during the 120-day period prior to a scheduled primary care visit 
Patients Who Take PPIs 
Once Daily 
Meeting any of the following criteria: 
Twice Daily 
Meeting any of the following criteria:  
 
No clear indication for PPIs 
 
Uncomplicated GERD (i.e., no erosive esophagitis, 
 
stricture, dysphagia, or Barrett’s esophagus) 
 
No clear indication for PPIs 
 
Any indication (except Zollinger-Ellison) 
 
Inclusion of Women, Minorities, and Children 
Racial and ethnic minority patients were represented in the VA National Patient Care Database and other VA datasets. 
2017 estimates were that 11% of the VHA population was Black, 6% were Hispanic/Latino, and 4% were of another 
minority group. At 8%, women constitute a minority of the VHA population. However, this number is increasing, and all 
women Veterans who met inclusion criteria were included in this study. No children were included in this study. 

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5.2 
EXCLUSION CRITERIA 
The RaPPID Program avoided de-prescribing PPIs in patients for whom chronic PPI therapy was recommended by 
guidelines, consensus statements, and/or expert opinion. Stopping PPIs in these patients could have caused harms 
such as upper GI bleeding. Patients taking PPIs were excluded from the dashboard if they had one or more of the 
characteristics listed in the table below. 
Twice-daily PPI Users with Zollinger-Ellison  
Once-daily PPI Users with any the following characteristics: 
 Eosinophilic esophagitis 
 Esophagitis  
 Barrett’s esophagus 
 Peptic ulcer  
 Zollinger-Ellison 
 Idiopathic pulmonary fibrosis 
 Pancreatic enzyme replacement 
 Esophageal ulcer 
 Esophageal stenosis/stricture 
 Dysphagia (other than oropharyngeal) 
OR 
NSAID Users 
Meeting any of the following criteria: 
Low-dose Aspirin Users 
Meeting any of the following criteria:  
 age > 65 years of age 
 Take a 2nd NSAID  
 Take daily aspirin 
 Take an anti-thrombotic drug 
 Take an oral steroid 
 age ≥ 60 years of age  
 Take NSAIDs regularly  
 Take an anti-thrombotic drug 
 Take a corticosteroid 
 
6 
EXPERIMENTAL MANIPULATIONS 
6.1 
EXPERIMENT 
 
Experiment: Behavioral 
Intervention Arm 
PPI De-prescribing Program 
Control Arm 
Usual Care/No PPI De-prescribing Program 
 
Alerts to clinical pharmacy specialists and primary 
 
care providers informing them of individual 
 
patients scheduled for upcoming primary care 
 
visits who meet criteria for PPI de-prescription 
 
Activation of clinical pharmacy specialists 
 
Education of primary care providers 
 
Patient Education 
 
Usual Care 
 
Did not receive the national de-prescribing 
 
program 
 
 
The study focused on the effect of the operational intervention, RaPPID, as compared to usual care. See Section 4.1.1 for 
detailed descriptions of intervention components.  

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6.2 
MEASURES TO MINIMIZE BIAS: RANDOMIZATION AND BLINDING 
Randomization of VISNs (regions) was done by the study biostatistician. The investigators and operational partners were 
informed of the assignments after randomization was finalized.  
There was no blinding once randomization was complete. 
6.3 
PARTICIPANT WITHDRAWAL FROM THE STUDY & LOST TO FOLLOW-UP 
Not applicable for RCT as all subjects electronically enrolled were analyzed. 
For patient reported outcomes, we expected some missing data. Our initial analyses only used observed data, but for 
missing data for items within scales, we used recommended imputation strategies. For missing 3-month survey 
assessments, we used logistic regression with missing follow-up as a dependent variable to see if missingness is associated 
with baseline variables, including facility-level variables. We included baseline variables found to be predictive of 
missingness in the longitudinal data model, and if missingness was at random, longitudinal mixed-effects provided an 
unbiased estimate of the study group effect. If the extent of missingness is more than 20%, we conducted a secondary 
analysis by combining results based on multiply imputed data using sequential regression multivariate imputation method,  
 
7 
PROCEDURES AND STUDY ASSESSMENTS 
7.1 
PROCEDURES 
It was recommended that patients meeting inclusion-exclusion criteria should be deprescribed using one of the 
methods below. Some patients with GERD were expected to have recurrence of frequent bothersome symptoms 
intermittently in the coming months or years. Studies have suggested such patients can be well-managed by 
intermittent courses of once-daily PPI for up to 4 weeks. On-demand PPI therapy (in which the patient takes PPIs as 
they determine is needed based on symptoms and response) was also shown to be well accepted by patients with 
GERD. Only a minority of GERD patients should require daily maintenance PPI therapy to provide acceptable symptom 
relief. The table below was part of the educational materials for Pharmacy and Primary Care providers. 
Patients Taking PPIs 
Once Daily 
Twice Daily 
 Taper to every other day for 2 weeks and then 
discontinue  
 Prescribe H2-receptor antagonists (e.g., 
famotidine, ranitidine) to take as needed for 
intermittent recurrent symptoms 
 Taper to once daily PPI, taken 30-60 minutes 
before a meal 
Patients should be cautioned that they may have rebound symptoms for a few weeks after discontinuation.  
 
7.2 
DATA COLLECTION  
 
Data was collected from several sources, including: (1) VHA Corporate Data Warehouse (CDW); (2) surveys of Veterans; 
and (3) semi-structured interviews with CPS providers, GI providers, and PCPs as part of the process evaluation. Key 
measures are shown the table below.  

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7.2.1 VARIABLES & DATA SOURCES 
Variable 
Description 
Time 
Frame 
Data Source 
Primary Outcome 
PPI de-prescribing  Proportion of days PPI prescribed after index visit (H1) 
12 mo 
CDW 
Secondary Outcomes 
Utilization of 
outpatient care 
Outpatient visit, ED visit, or upper endoscopy (EGD) for: (1) upper GI 
symptoms/conditions; (2) any cause 
12 mo 
CDW 
Utilization of 
inpatient care 
Hospital admission for: (1) upper GI symptoms/conditions; (2) any 
cause 
12 mo 
CDW 
Serious GI 
complications 
Complications of peptic ulcer disease (bleeding, obstruction, 
perforation) 
12 mo 
CDW 
PPI-related harms 
E.g., fractures, enteric infections, pneumonia, kidney disease, dementia 12 mo 
CDW 
Upper GI symptoms  Upper GI symptoms (RDQ) 
0, 3 mo 
Surveys 
Cost 
Healthcare expenditures related to VA and non-VA care 
24 mo 
Calculated 
Reach 
Proportion of patients offered de-prescribing 
3 mo 
Post Survey 
Adoption 
Reduction in PPI use before / after program deployment 
3, 12 mo 
CDW 
Implementation 
Implementation fidelity and consistency at each site (process) 
3, 12 mo Staff Interviews 
 
7.2.2 STUDY ASSESSMENTS - VETERAN SURVEYS 
One potential unintended consequence of PPI de-prescription is worsening upper GI symptoms. Worsening symptoms can 
substantially affect quality of life and promote use of medications and healthcare resources. Importantly, these 
medications and healthcare resources need not be sought within VA. For example, medications to alleviate heartburn may 
be obtained over-the-counter (OTC) or from a non-VA provider. Therefore, we used surveys to assess and track outcomes 
that could not be measured electronically, including upper GI symptoms, quality of life, and use of non-VA healthcare 
resources. We developed two surveys with distinct elements: (1) a pre-visit survey, to be completed 1-2 weeks prior to 
the index primary care visit; and (2) a post-visit survey, to be completed 3 months after the index primary care visit. 
Surveys were administered to subjects in the VISN with the most Dashboard activity (a high participation VISN) and a 
comparable control VISN.  
 
Pre-Visit/Baseline Survey 
The pre-visit survey included several established scales and individual survey items. Upper GI symptoms were assessed 
using the Reflux Disease Questionnaire (RDQ), a validated PRO scale. Quality of life was assessed using the Short Form-12 
(SF-12). We also included single items to assess baseline trust in PCP, concern about PPI-related harms, and receptiveness 
to de-prescribing of PPIs, all taken from an existing survey instrument. 
 
Post-Visit Survey 
For the 3-month follow-up survey, we again assessed symptoms and quality of life using the RDQ and SF-12, respectively. 
As a measure of “reach” for our process evaluation, we developed a single item to assess whether the patient recalls a 
discussion with the PCP about PPI de-prescription. Furthermore, we developed items to assess use of non-VA medications 
for symptom control (PPIs, H2RAs, antacids) and the use of non-VA healthcare. We also asked Veterans to report the 
source of payment for these services (e.g., out of pocket, private insurance).  

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8 
STATISTICAL ANALYSES 
We hypothesized that RaPPID will reduce the use of PPIs without a clinically meaningful increase in upper GI symptoms 
or upper GI complications such as bleeding. 
Primary outcome measure: The primary outcome was the proportion of days PPIs are prescribed at or above the 
baseline daily dosing-frequency, over the 12 months following the index visit. We hypothesized (H1) that the proportion 
of days would be lower in intervention group than in the control group (i.e., that the outcome would be superior in the 
intervention vs control group). This outcome is analogous to the medication possession ratio. This was the appropriate 
measure of success of de-prescribing because it captured a variety of results in a single endpoint, including 
discontinuation without resumption, discontinuation with intermittent or on-demand use, and resumption of daily PPI 
at or above baseline dosing frequency. Secondary outcome measures: We also measured a variety of secondary 
outcomes to assess unintended, adverse events related to PPI de-prescribing. We hypothesize that utilization of 
outpatient care (H2) and the patient reported outcome (PRO) of upper GI symptoms (H3) will be non-inferior in the 
intervention vs control group. 
Utilization of outpatient and inpatient care: Using CDW data, we assessed utilization of outpatient care – clinic visits or 
emergency department visits (using stop codes) for predefined upper GI symptoms/diagnoses (based on ICD-10 codes) 
or upper endoscopies (based on CPT codes). We also assessed use of inpatient care (i.e., hospital admissions) for 
predefined upper GI symptoms/diagnoses (based on ICD-10 codes). 
Upper GI symptoms and quality of life: We assessed upper GI symptoms using the RDQ, a validated PRO instrument 
(30,31). We also measured generic quality of life using the SF-12 (32). 
Serious GI complications: We assessed upper GI complications (bleeding, perforation, obstruction) using ICD-10 codes. 
PPI-related harms: To ensure that we captured all relevant harms, we reviewed published observational studies of PPI 
harms to identify relevant diagnoses and ICD-9/10 codes. 
Covariates: Covariates included demographics (age, sex, race/ethnicity), Charlson comorbidity index, indication for PPI 
use (uncomplicated GERD vs no indication), and baseline PPI dosing frequency (once-daily vs twice-daily). We also 
collected covariates on a subset of patients (1 intervention VISN and 1 control VISN), using our survey questionnaires, 
including baseline RDQ symptom score, trust in provider, baseline concern about PPI harms, and receptiveness to de-
prescribing of PPIs. 
8.1 
SAMPLE SIZE DETERMINATION 
8.1.1 PRIMARY OUTCOME 
Assuming approximately the same number of eligible subjects in each VISN (with an average of 10,563 candidates per 
VISN) and an ICC of 0.12, randomizing 17 VISNs will give more than 80% power to detect % days on PPI of 75% vs. 50%, 
85% vs. 60%, 80% vs. 55%, or 70% vs. 45%, but to detect a difference between 70% vs. 50%, power is only 61% using 0.05 
level 2-sided test.  
8.1.2 VETERAN SURVEYS 
Recruitment numbers were based on a power calculation in which patient-reported symptoms, as measured by the Reflux 
Disease Questionnaire, were treated as a continuous variable rather. Based on previous research, we assumed an RDQ 
score Standard Deviation (SD)=1.3 for GERD patients for this calculation. To detect the between-group difference of 0.71 
vs. 1.13, assuming SD=1.3 with 90% power and alpha=0.01, we need 287 surveys completed per group (574 in total) at 3 
months and 820 in total surveys returned at baseline to account for 30% dropout by month 3. We estimated a 50% 
response rate for the baseline survey and a 70% response rate for the follow-up survey. we mailed 1,722 baseline surveys 
and approximately 850 follow-up (3 month) surveys. 

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8.1.3 FINAL REPORT UPDATE: RCT CONSORT DIAGRAM 
 

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8.1.4 FINAL REPORT UPDATE: SURVEYS CONSORT DIAGRAM 
 
 
 
 
 
 
Patients randomized and charts screened for eligibility (n=2187) 
 
 
 
 
Intervention (n=1251) 
 
 
 
 
Control (n=992) 
Patients sent survey (n= 1722) 
• Intervention (n= 893) 
• Control (n=829) 
 
Patients excluded (n=521) 
Intervention (n=358) 
 
• Ineligible appointment (n=306) 
• Canceled appointment before survey sent (n=50) 
• Inpatient (n=2) 
Control (n=163) 
• Ineligible appointment: (n=113) 
• Canceled appointment before survey sent (n=48) 
• Inpatient (n=2) 
Patients excluded (n=712) 
• Lost to follow up (n=691) 
• Mail returned to sender (n=1) 
• Opted out (n=20) 
Patients completed baseline survey (n=1010) 
• Intervention (n=540) 
• Control (n=470) 
Patients excluded (n=160) 
Intervention (n=75) 
• Did not complete visit (n=70) 
• Patient died (n=1) 
• Survey returned late (n=4) 
Control (n=85) 
• Did not complete visit (n=78) 
• Survey returned late (n=7) 
Patients completed survey and PCP appointment  
(n=850) 
• Intervention (n=465) 
• Control (n=385) 
Returned (n=370) 
  
Intervention (n=465) 
 
Patients sent 3-month follow-up survey (n=850) 
Control (n=385) 
 
Returned (n=288) 
  
Lost to follow 
up: (n=95) 
Lost to follow 
up: (n=97) 

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8.2 
POPULATIONS FOR ANALYSES 
 
• 
Intention-to-Treat (ITT) Analysis Population  
• 
Repeated Measures 
o In addition to intent-to-treat, patient reported outcomes will be measured through surveys over time. 
 
8.3 
STATISTICAL ANALYSES 
 
Analyses proceeded in 3 phases. In the 1st phase, we examined the distribution of all study variables to assess extreme 
values, missing data, variances, possible coding errors, skewness, and type of distribution. In the 2nd phase, we evaluated 
bivariate associations between study arm and outcomes, as well as between each covariate and outcomes, using 
generalized linear models with generalized estimating equations to account for clustering. This was done to determine 
unadjusted measures of effect, assess possible confounders, and anticipate any collinearity in subsequent analyses. In the 
final phase, we fit multivariable models to identify the effects of the intervention. 
 
Primary outcome (H1): To assess the primary outcome (proportion of days PPIs are prescribed), we used an intent-to-treat 
analysis with a mixed-effects model, with proportion of PPI days over 12 months as the dependent variable. The primary 
independent variable was study arm. Because randomization was done at the VISN (regional) level, we anticipated that 
patients seen at the same facility will show a positive intraclass correlation (ICC). The mixed-effects model accounted for 
such clustering by including VISNs as random intercepts. It also controlled for VISN strata variables used in randomization. 
We did not account for patient dropout since all data collection is done electronically and does not require further patient 
participation. 
 
To assess secondary outcomes (utilization of outpatient care and upper GI symptoms patient reported outcomes), we 
used generalized linear mixed-effects models with logit link (hierarchical logistic regression) to account for VISN-level 
clustering and randomization strata. The primary independent variable was study arm. For each outcome, an odds ratio 
(OR) for adverse events in the intervention group relative to the control group was obtained from each logistic regression 
model, where a significant OR less than 1.0 will favor the intervention group. For analyses of the patient reported 
outcomes, the outcome of interest was the RDQ score assessed at 3 months. For both outcomes, non-inferiority was 
assessed by comparing the effect estimate and its 90% CI with a non-inferiority margin.  
 
8.3.1 BASELINE DESCRIPTIVE STATISTICS 
Intervention and control groups were compared on demographics of age, race, ethnicity, marital status, education, and 
Charlson Comorbidity Index (CCI). 
 
9 
SUPPORTING DOCUMENTATION 
9.1 
Regulatory, Ethical, and Study Oversight Considerations 
 
Study documents were and will be retained in accordance with the Records Control Schedule (RCS) 10-1 which provides 
Veterans Health Administration (VHA) records retention and disposition requirements for VHA Central Office, Program 
Offices, and field facilities. 
 

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9.2 
PROTOCOL DEVIATIONS 
 
Final report update: no SAEs were reported throughout the duration of the study.   
 
Because this was a minimal risk study with the intervention being implemented as part of VHA clinical operations and 
involving only use of paper and telephone surveys and telephone interviews about PPI de-prescribing experiences, we did 
not anticipate any serious adverse events (SAEs). Serious adverse events to be monitored included the following: 1) a 
breach of a participant’s confidentiality or privacy that involved potential risk to that participant or others, 2) deviations 
from VA IRB regulations and policies, and 3) unanticipated problems (UAPs) that involved social or economic harm instead 
of the physical or psychological harm associated with adverse events. SAEs were prospectively tracked according to the 
following plan: reports of SAEs and protocol deviations were made by the study team member who discovered the event, 
the site PI, or site project manager (if applicable) to the primary site (Ann Arbor) project manager. The primary site project 
manager and PI would report the event to the Ann Arbor VA IRB (Primary Site IRB). Any SAEs and UAPs meeting the 
definition of serious would be reported within 5 business days of discovery to the Ann Arbor VA IRB. AEs and UAPs that 
did not meet the definition of serious were to be reported to Ann Arbor project manager as they were discovered, and 
would be reported to the Ann Arbor VA IRB in summary at the time of continuing review/project closure. Protocol 
deviations/violations that were likely to substantially adversely affect 1) the rights, safety, or welfare of a participant; 2) a 
participant’s willingness to continue participation; or 3) the integrity of the research data, including VA information 
security requirements will all be reported within 5 working days of being made aware of the occurrence. 
9.3 
PUBLICATION AND DATA SHARING POLICY 
 
This study will comply with all Department of Veterans Affairs regulations and policies.  
9.4 
CONFLICT OF INTEREST POLICY 
 
Final report update: no conflicts were reported throughout the duration of the study. 
 
The independence of this study from any actual or perceived influence was critical. Therefore, any actual conflict of 
interest of persons who had a role in the design, conduct, analysis, publication, or any aspect of this trial was disclosed 
and managed. Furthermore, persons who had a perceived conflict of interest was required to have such conflicts managed 
in a way that was appropriate to their participation in the design and conduct of this trial. The study leadership in 
conjunction with the Department of Veterans Affairs has established policies and procedures for all study group members 
to disclose all conflicts of interest and an established mechanism for the management of all reported dualities of interest. 
 
9.5 
ABBREVIATIONS AND SPECIAL TERMS 
 
AE 
Adverse Event 
ANCOVA 
Analysis of Covariance 
BIA 
Budget Impact Analysis 
CAR 
Clinical Analytics and Reporting 
CBOC 
Community Based Outpatient Clinic 
CCMR 
VA Ann Arbor Center for Clinical Management Research 
CDW 
Corporate Data Warehouse 
CFIR 
Consolidated Framework for Implementation Research 
CFR 
Code of Federal Regulations 
CI 
 Confidence Interval  

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CKD 
Kidney Disease 
CLIA 
Clinical Laboratory Improvement Amendments 
CMCVAMC 
Corporal Michael J. Crescenz VA Medical Center 
CMP 
Clinical Monitoring Plan 
CMS 
Centers for Medicare Services 
COC 
Certificate of Confidentiality 
Co-I 
Co-Investigator 
COIN 
Center of Innovation 
CONSORT 
Consolidated Standards of Reporting Trials 
CPS 
Clinical Pharmacy Specialist 
CPT 
Current Procedural Terminology 
CRADO 
Chief Research and Development Officer 
CRF 
Case Report Form 
CSR&D 
Clinical Science Research & Development 
DART 
Data Access Request Tracker 
DCC 
Data Coordinating Center 
DHHS 
Department of Health and Human Services 
DSMB 
Data Safety Monitoring Board 
DRE 
Disease-Related Event 
EC 
Ethics Committee 
eCRF 
Electronic Case Report Forms 
ED 
Emergency Department 
EHR 
Electronic Medical Records 
FAC 
Field Advisory Committee 
FDA 
Food and Drug Administration 
FDAAA 
Food and Drug Administration Amendments Act of 2007 
FFR 
Federal Financial Report 
GCP 
Good Clinical Practice 
GEE 
Generalized Estimating Equations 
GERD 
Gastroesophageal Reflux Disease 
GI 
Gastroenterology/Gastrointestinal 
GLM 
Generalized Linear Model 
GLP 
Good Laboratory Practices 
GMP 
Good Manufacturing Practices 
GWAS 
Genome-Wide Association Studies 
H2RA 
Histamine-2 Receptor Antagonist 
HCUP 
Healthcare Cost and Utilization Project 
HIPAA 
Health Insurance Portability and Accountability Act  
HRQOL 
Health-Related Quality of Life 
HSR&D 
Health Services Research & Development 
IB 
Investigator’s Brochure 
ICC 
Intraclass Correlation Coefficient 
ICD-9 
International Classification of Diseases, Ninth Revision 
ICD-10 
International Classification of Diseases, Tenth Revision 
ICH 
International Council on Harmonisation  
ICMJE 
International Committee of Medical Journal Editors 
IDE 
Investigational Device Exemption 
IDEAS 
Informatics, Decision-Enhancement and Analytic Sciences Center 
IHPI 
Institute for Healthcare Policy and Innovation 
IIR 
Investigator Initiated Research 
IND 
Investigational New Drug Application 

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IOM 
Institute of Medicine 
IRB 
Institutional Review Board 
ISM 
Independent Safety Monitor 
ITT 
Intention-To-Treat 
LSMEANS 
Least-squares Means 
MedDRA 
Medical Dictionary for Regulatory Activities 
MI 
Myocardial Infarction 
MOP 
Manual of Procedures 
MUE 
Medication Use Evaluation  
NCRC 
NCRC – North Campus Research Complex 
NCT 
National Clinical Trial 
NSAID 
Non-Steroidal Anti-Inflammatory Drug 
NIH  
National Institutes of Health 
NIH IC 
NIH Institute or Center 
OHRP 
Office for Human Research Protections 
OR 
Odds Ratio 
OTC 
Over-the-Counter 
PBM 
Pharmacy Benefits Management Services 
PCP 
Primary Care Provider 
PD/PI 
Project Director/Principal Investigator 
PI 
Principal Investigator 
PIE 
Partnerships for Implementation and Evaluation 
PP 
Per Protocol 
PPI 
Proton Pump Inhibitor 
PRO 
Patient Reported Outcome 
PUD 
Peptic Ulcer Disease 
QA 
Quality Assurance 
QC 
Quality Control 
QOLRAD 
Quality of Life in Reflux and Dyspepsia 
QUERI 
Quality Enhancement Research Initiative 
QuEST 
Qualitative Evaluation for Systematic Translation 
RAPID 
VA Office of Reporting, Analytics, Performance Improvement, and Deployment 
RAPPID 
Randomized Proton Pump Inhibitor De-Prescribing Program 
RA 
Research Assistant 
RDQ 
Reflux Disease Questionnaire  
RCT 
Randomized Controlled Trial 
RE-AIM 
Reach Effectiveness Adoption Implementation Maintenance Framework  
RR 
Relative Risk 
RRP 
Rapid Response Proposal 
SAE 
Serious Adverse Event 
SAP 
Statistical Analysis Plan 
SD 
Standard Deviation 
SDR 
Service Directed Research 
SF-12 
Short Form Health Survey (12 Items) 
SMC 
Safety Monitoring Committee 
SOA 
Schedule of Activities 
SOC 
System Organ Class 
SOP 
Standard Operating Procedure 
UP 
Unanticipated Problem 
US 
United States 
TDF 
Theoretical Domains Framework 

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VA 
Veterans Affairs 
VAAAHS 
VA Ann Arbor Healthcare System 
VACHS 
VA Connecticut Healthcare System 
VAMedSAFE 
VA Center for Medication Safety 
VAPSHCS 
VA Puget Sound Health Care System 
VASLC 
VA Salt Lake City Healthcare System 
VERAM 
Veterans Education and Research Association of Michigan 
VHA 
Veterans Health Administration 
VISN 
Veterans Integrated Service Network 
VREC 
Veteran Research Engagement Council 
 
9.6 
PROTOCOL AMENDMENT HISTORY 
 
Version 
Date 
Description of Change  
Brief Rationale 
1.0 
4/26/2019 
Randomization changed from facility 
level to VISN level 
Operational partner decision 
based on feasibility of 
implementation of intervention 
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