TRANSFORM3: Evaluation of Implementation Strategies of Teaching, Technology, and Teams to Optimize Medical Therapy in Cardiovascular Disease (T3)
Phase: NA
Conditions: Heart Failure, Type 2 Diabetes, Atrial Fibrillation
Sponsor: American College of Cardiology

 
 
9/30/2022 
 
 
 
TRANSFORM3: Evaluation of Imple-
mentation Strategies of Teaching, 
Technology, and Teams to Optimize 
Medical Therapy in Cardiovascular 
 

1 
 
 
 
TRANSFORM3: Evaluation of Implementation Strategies of 
Teaching, Technology, and Teams to Optimize Medical Ther-
apy in Cardiovascular Disease (T3) 
 
Study Protocol 
 
Primary Investigator(s):   
Ankeet S. Bhatt, MD, MBA, Kaiser Permanente, Oakland, CA 
James L. Januzzi, Jr, MD, FACC, FESC, Massachusetts General Hospital, Boston, MA  
Mikhail Kosiborod, MD, Saint Luke’s Health System, Kansas City, MO  
Jagmeet P. Singh, MD, ScM, PhD – Professor of Medicine, Harvard Medical School, Massachu-
setts General Hospital Division of Cardiology  
Muthiah Vaduganathan, MD, MPH –Brigham and Women’s Hospital and Harvard Medical 
School, Boston, MA  
Megan J. Welch, MD – Fellow in Cardiovascular Medicine, Harvard Medical School, Massachu-
setts General Hospital Division of Cardiology  
  
 Joseph Allen—Senior Director, Science and Quality, American College of Cardiology  
Katherine Byrd – TRANSFORM Patient Content, American College of Cardiology  
Lindsey Hill—TRANSFORM Project Manager, American College of Cardiology  
Shilpa Patel-TRANSFORM Quality Ambassador, American College of Cardiology  
 
Study Overview 
 
This initiative supports a quality improvement effort evaluating the use of strategies (including 
technology-based decision support, referral to a virtual GDMT team, and general educational 
tools/resources for clinicians and patients) to improve use of guideline-directed therapeutics 
known to lower cardiovascular (CV) events among patients with cardiovascular diseases of heart 
failure, atrial fibrillation and type 2 diabetes (T2D)/ASCVD with a specific focus on underserved 
populations and those with a history of health care disparities. 
 
 
 
 

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Patient Recruitment 
TRANSFORM3 
750  
(250 HFrEF, 250 HFpEF, 500 Atrial Fibrillation, 
250 T2D/ASVCD) 
 
Intervention 
Patients Randomized – 3 Quality Improvement Arms 
Arm 
Duration 
 
Surveys 
Primary Out-
come 
Secondary Out-
come 
Teaching - CardioSmart 
Resources + Clinician 
Education
9 months 
 
 
Patient percep-
tion 
QOL 
 
 
GDMT baseline 
to 9 month 
change in average 
composite end-
point of receiving  
the main classes 
of drugs (50% or 
higher of target 
doses for HF) 
among eligible 
patients  
 
QOL 
Individual drug im-
provements 
Patient perception 
Cost/cost effective-
ness 
 
 
Technology - Facilitated 
Solution  
(Existing Team)
Teams - Protocol-Sup-
ported Team, (Virtual 
GDMT Team) 
 
List of Abbreviations 
ACCF  
 
 
American College of Cardiology Foundation 
ACE-I  
 
 
Angiotensin-converting enzyme inhibitors 
ASCVD  
 
 
Atherosclerotic Cardiovascular Disease 
ARB  
 
 
Angiotensin II receptor blockers 
CV  
 
 
Cardiovascular  
CVD  
 
 
Cardiovascular Disease 
CVRiD  
 
 
CV Risk in Diabetes 
DCR  
 
 
Diabetes Collaborative Registry 
EHR  
 
 
Electronic Health Record 
ESRD  
 
 
End Stage Renal Disease 
ECDP 
 
 
Expert Consensus Decision Pathway 
GDMT 
 
 
Guideline Directed Medical Therapy 
GLP1-RA  
 
 
Glucagon-like peptide-1 receptor agonists 
GPP  
 
 
Good Pharmacoepidemiology Practice 
HF  
 
 
Heart Failure 
LVEF  
 
 
Left Ventricle Ejection Fraction 
SGLT-2I  
 
 
Sodium glucose cotransporter-2 inhibitors 
SI  
 
 
System Integration 
SIM CVRiD  
 
Success in Managing CV Risk in Diabetes 
T2D  
 
 
Type 2 Diabetes 
VAD  
 
 
Ventricular Assist Device 
 

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Rationale and Background 
 
TRANSFORM3 is a Quality Improvement initiative conducted in parallel to the current TRANS-
FORM CVRiD study and aligned with its goals of using a real-world population study to enable 
the American College of Cardiology Foundation (“ACCF”) to better identify impactful ways to 
improve guideline directed medical therapy for patients.  TRANSFORM3 is focused on improv-
ing GDMT use in underserved patients and patients with a history of health care disparities who 
have one or more of the following: heart failure, atrial fibrillation, and ASCVD/Type 2 diabetes.   
 
There is a significant disconnect between increasing availability of effective and safe therapeu-
tics that significantly reduce CV event risk in patients with Heart Failure, T2D and ASCVD, and 
Atrial Fibrillation—and clear guideline recommendations endorsing these therapies—but very 
low adoption in clinical practice with the majority of eligible patients that are most likely to ben-
efit from these therapies not receiving them.  A high proportion of patients have more than one 
of these conditions further reducing the chances of receiving optimal guideline directed medical 
therapy and avoiding the CV events they are designed to prevent.   
 
Heart Failure (HF) 
HF is the cardiovascular epidemic of the 21st century, affecting millions of patients worldwide. 
It is the #1 diagnosis leading to hospitalization among Medicare beneficiaries. In addition to be-
ing increasingly prevalent, HF has a poor outlook after initial diagnosis and is associated with 
poor quality of life (QOL) in affected patients; this not only leads to burden on patients, family 
and other caregivers, but also on the healthcare system.  
 
Although clinical practice guidelines clearly articulate optimal GDMT for care of patients with 
HF, implementation of GDMT into the management of such patients has proven to be subopti-
mal, with most patients under-treated relative to goal therapy. 
 
To evaluate contemporary status of GDMT delivery for HFrEF, the recent Change the Manage-
ment of Patients with Heart Failure (CHAMP-HF) registry included 3518 patients from 150 pri-
mary care and cardiology practices (1,2). The mean age of this cohort was 66 ± 13 years, 29% 
were female, and mean EF was 29 ± 8%, thus representing a very characteristic population of pa-
tients with HFrEF.  In CHAMP-HF, the investigators found 27%, 33%, and 67% of eligible pa-
tients were not prescribed angiotensin converting enzyme inhibitor (ACEI)/angiotensin II recep-
tor blocker (ARB)/angiotensin receptor/neprilysin inhibitor (ARNI), beta-blocker, and mineralo-
corticoid receptor antagonist (MRA) therapy, respectively. Furthermore, when medications were 
prescribed, few patients were receiving target doses of ACEI/ARB (17%), ARNI (14%), and 
beta-blocker (28%); most patients were receiving target doses of MRA therapy (77%). Most no-
tably, among patients eligible for all classes of medication, only 1% were simultaneously receiv-
ing target doses of renin-angiotensin system inhibitors (RASi; ACE/ARB/ARNI), beta-blocker, 
and MRA. Remarkably, little improvement in GDMT was noted over a 6 to 12-month period and 
(importantly) no use of the newest HFrEF GDMT, sodium glucose cotransporter-2 inhibitors 
(SGLT2i) was reported. 
 

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In HFpEF, the MRA spironolactone could be considered for use based on the TOPCAT trial 
(America’s region). Similarly, the ARBs (based on CHARM-Preserved and I-Preserve) appear to 
modestly lower HF events in patients with HFpEF. The US FDA has expanded labelling for 
ARNI to all patients with chronic HF noting that patients with an LVEF below normal are most 
likely to benefit. This regulatory labelling change was based on the PARAGON-HF trial which 
showed modest clinical benefits of this therapy when studied against valsartan. The SGLT2i em-
pagliflozin was shown to be beneficial in reducing HF events or cardiovascular death among pa-
tients with HF with mildly reduced or preserved EF. 
  
Atrial Fibrillation (AF) 
AF, the most common arrhythmia in adults, is a top priority for the TRANSFORM3 program. 
The estimated risk of developing atrial fibrillation over a lifetime is 1 in 4, and a diagnosis of 
atrial fibrillation confers a 5-fold increase in ischemic stroke risk. 
 
Anticoagulation reduces the risk of stroke by 60-70%, which is a benefit that outweighs the risk 
of bleeding for the majority of patients. The American College of Cardiology (ACC), American 
Heart Association (AHA), and Heart Rhythm Society (HRS) recommend the use of the 
CHA2DS2-VASc score to estimate stroke risk and to start an anticoagulant in anyone with a 
score greater than or equal to 2 in men and greater than or equal to 3 in women. The proportion 
of patients at elevated stroke risk based on the CHA2DS2-VASc score who receive oral antico-
agulation (OAC) therapy is a performance metric used by cardiovascular societies and the Joint 
Commission to assess the quality of cardiovascular care being delivered.  Despite the clear bene-
fits of oral anticoagulation for stroke prophylaxis of atrial fibrillation, only 50-60% of eligible 
patients receive an anticoagulation prescription. 
 
Type 2 Diabetes Mellitus (T2D) 
Over 34 million Americans have T2D and >7 million have established cardiovascular disease. 
T2D is associated with diminished life expectancy (by up to 6-7 years for an average 60-year-old 
patient).  
 
Patients with T2D have traditionally been managed with diet/lifestyle optimization, glycemic 
control, other risk factor control (including of blood pressure, weight, and smoking cessation), 
statin therapy, and renin-angiotensin-system inhibitors (in select patients). The SGLT2i and the 
GLP-1RA are 2 classes of antihyperglycemic therapies that have demonstrated clinically im-
portant improvements in cardiovascular, kidney, and mortality outcomes among high-risk pa-
tients with T2D. Despite their availability and a strong evidentiary base, their uptake in clinical 
practice remains suboptimal. Even with expanding insurance coverage and accruing clinical 
practice guideline support (across specialties), recent national data have suggested that only ~10-
15% of eligible patients are on 1 of these risk reduction therapies. Innovative strategies are 
needed to promote optimal care practices among high-risk patients living with T2D. 
 
 
We designed the TRANSFORM3 as a US-based multi-center trial with the goal of defining opti-
mal implementation strategies to integrate GDMT across disease states, especially in under-
served populations or those with health care disparities historically. The study was designed spe-
cifically to capture patients across broad integrated health systems encountering multiple 

5 
 
clinician types.  All quality improvement initiatives will be remotely deployed directly to clini-
cians caring for eligible patients by trained Study Managers. 
 
The lack of effective implementation is in part related to therapeutic inertia and lack of effective 
clinical care models that promote and incentivize adoption of guideline-directed medical thera-
pies (GDMT).  Furthermore, while treatment changes are often exclusively made during clinician 
encounters, this study attempts to evaluate strategies that target the large time periods spent out-
side of defined ambulatory care encounters. Clinicians may have multiple competing priorities 
during these short clinic visits and allowing for sufficient time needed to effectively optimize 
medical therapies may be challenging within the time-constrained context of such a visit.  We 
will seek to investigate a range of currently available clinician-facing implementation strategies 
(including patient/clinician education, technology-based support, and facilitated referral to a 
team [specifically virtual GDMT nurse/pharmacy] to determine the potential of various imple-
mentation approaches to rethink the 20-minute office visit more broadly and improve use of 
GDMT among patients with one or more high-risk cardiovascular conditions. 
 
Study Design 
 
TRANSFORM3 will enroll patients, especially those in underserved populations and those with 
health care disparities historically, to address guideline directed medical therapy in one or more 
of the following disease states: HF, ASCVD/diabetes, and AF. 
 
The study will address the following key objectives among patients with Heart Failure 
Atrial Fibrillation, and/or T2D and ASCVD: 
1. Evaluate strategies to improve adoption of evidence-based CV-risk reduction and disease 
management therapies for HF, AF, and T2D/ASCVD. 
 
The research objectives of this study are outlined below: 
Multi-faceted Implementation Study: In this quality improvement initiative, we will 
test 3 currently available quality improvement strategies designed to improve implemen-
tation of the guideline-concordant care for patients with Heart Failure, Atrial Fibrillation, 
and/or T2D and ASCVD. Across select participating health systems, participants with 
Heart Failure, Atrial Fibrillation, and/or T2D and ASCVD, will be randomized to 1 of 3 
implementation strategies:  
a. Teaching Based Improvement: Clinician and Patient Education alone;  
b. Technology-Facilitated Improvement: Technology Guided Care to provide sug-
gestions for care optimization + Education; or  
c. Team Based Improvement:  Referral to a third party virtual GDMT team con-
tracted by study partner Biofourmis for care optimization utilizing the same 
technology based standardized suggestions + Education.  
  
Key goals of the study will be to: 
 
 Evaluate uptake or intensification of guideline-concordant cardiovascular risk 
lowering therapies 

6 
 
 Understand guideline consistent comprehensive care for patients with co-related 
cardiovascular conditions, especially in underserved populations or those with 
health disparities historically   
 Understand barriers and drivers to optimal care  
 
Population:  
750 total with comorbidity overlap (250 HFrEF, 250 HFpEF, 500 AF, 250 T2D/ASVD) 
 
Inclusion criteria: 
1. Age ≥18 years 
2. Personal access to a computer and/or smartphone for app download 
3. Heart Failure (reduced and preserved ejection fraction) AND/OR 
4. Atrial Fibrillation with CHA2DS2-VASc score greater than or equal to 2 in men 
and greater than or equal to 3 in women AND/OR 
5. T2D and ASCVD, defined as follows: 
a. Known CAD, prior ACS, or coronary artery revascularization 
b. Prior TIA/stroke or known carotid or intracerebral atherosclerosis 
c. Prior PAD including requiring revascularization 
 
Exclusion criteria: 
o All patients 
 Current or anticipated participation in an interventional clinical trial of a 
drug/device 
 Currently receiving comfort care or enrolled in hospice 
 Life expectancy <1 year 
 Pregnancy or active breastfeeding 
 Current or anticipated participation in an interventional clinical trial (other 
than TRANSFORM3 GDMT) 
 Patients without a clinical encounter within three years of study start date 
o Heart Failure patients: 
 History of or plan for heart transplantation or left ventricular assist device 
 Palliative chronic inotropic therapy 
 NYHA Class 4 heart failure 
o Atrial Fibrillation patients: 
 Current prescription for OAC 
 Reversible cause of atrial fibrillation, such as post-cardiothoracic surgery 
or thyrotoxicosis 
 History of ischemic stroke in prior 7 days  
 Transient ischemic attack in prior 3 days  
 Platelet count <70,000/ml  
 Hemoglobin concentration <8g/dl  
 History of or condition associated with increased bleeding risk, such as he-
mophilia 
 History of mechanical valve replacement  
 Major surgical procedure or trauma within 14 days  
 Clinically significant gastrointestinal bleeding within 8 weeks   

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 History of intracranial, intraocular, spinal, or atraumatic intra-articular 
bleeding   
 
o T2D/ASCVD patients with or without HF or AF: 
 Current prescription for SGLT2i and GLP-1RA 
 Current or planned hemodialysis 
 Decompensated end stage liver disease 
 Type 1 diabetes 
 Prior diabetic ketoacidosis 
 Gestational diabetes 
 History of pancreatitis or pancreatic cancer 
 
 
Data Sources 
 
This is a prospective implementation trial in which patients in 4-6 large health systems will be 
randomized to various quality improvement strategies to optimize cardiovascular guideline di-
rected medical therapy.  
 
In all arms clinician choice will not be restricted and care recommendations will not be man-
dated. All interventions are clinician-facing, already available in current care, and promote best 
practice / guideline recommended care. All clinicians will be informed at the start of the study 
about the various quality improvement interventions from which they can “opt out”. All patients 
will be requested to provide informed consent to allow for data acquisition and follow-up. Data 
over 9 months in the 3 quality improvement groups will be mapped to pre-specified data fields, a 
data extractor (external vendor or study site) will extract the EHR data and may be used to sup-
plement data recorded in the Biofourmis  patient management platform. Adverse events (should 
they occur) will be captured at the clinical site level. Patients reporting adverse events will ad-
dress these with their providing physician. There is no Data Safety Monitoring Board for this 
study. 
 
Data Analysis 
 
At study completion, a data set across study visits will be provided to the contracted analytic 
center using a analytic plan developed by the study team. 
 
Research Question, Objectives & Aims 
 
The goal of this implementation trial is to evaluate several clinician and patient-facing imple-
mentation strategies to increase adherence to guideline recommended care and to increase pre-
scription of evidence-based therapies proven to reduce the risk of cardiovascular outcomes in pa-
tients, HF, AF and T2D/ASCVD. 
 
Patients will be randomized to 1 of 3 implementation strategies conducted over 9 months: 1) cli-
nician and patient education; 2) technology + clinician and patient education +; 3) referral to 

8 
 
third party virtual team (GDMT team) contracted by  Biofourmis+ clinician and patient educa-
tion. Patients will be followed for 9-months to evaluate for changes in the % of patients who ever 
receive new CV risk reduction therapies by type of strategy. We hypothesize that care of patients 
with HF, AF, and T2D/ASCVD, including underserved populations and those with health care 
disparities historically, can be effectively and safely optimized with support outside traditional 
ambulatory care encounters.  
 
Primary Objective  
The primary objective of this multi-faceted implementation trial is to determine the impact, if 
any, of use of teaching, technology or facilitated referral to a dedicated third party team (virtual 
GDMT) contracted by Biofourmis on:  
  
TRANSFORM3:  GDMT baseline enrollment to 9 month change in prescription of the main 
classes of drugs (receiving 50% or higher of target doses for HF patients) for the relevant disease 
states among eligible patients   
  
Subanalysis for each disease state:  
T2D/ASCVD:   
a. the proportion of treatment-naïve patients who are newly prescribed a 
SGLT2i and/or GLP-1RA over 9-months  
b. Rate of medication persistence: % of patients on a SGLT2i and/or GLP-
1RA at baseline who remained on a SGLT2i and/or GLP-1RA during the 
study period  
  
HFrEF: For those with HFrEF, baseline to 9 months change in average composite endpoint of at 
least 50% target dose achievement for the main classes of drugs (RASi/beta block-
ers/MRA/SGLT2i) among eligible patients.  
a. Goal doses will be based on the 2020 ACC Expert Consensus Decision 
Pathway for Optimization of Heart Failure Treatment (4).  
b. To calculate this composite:  
i.Numerator = receiving ARNI/ACEI/ARB at 50% or higher of target 
dose + receiving evidence-based beta blocker at 50% or higher of 
target dose + receiving MRA at 50% or higher of target dose + re-
ceiving SGLT2i at 50% or higher of target dose.  
 
 
ii. Denominator = eligible to receive ARNI/ACEI/ARB, eligible to 
receive evidence-based beta blocker, and eligible to receive MRA,  
 
 
and eligible to receive SGLT2i.  
 
 
iii. Using this approach, each patient may contribute to the numerator 
 
 
or be in the denominator 1, 2, 3 or 4 times, depending on meeting cri
 
 
teria and if eligible in that domain. An advantage of this composite  
 
 
approach is that it allows for a holistic view of all classes of drugs  
 
 
considered and allows for assessment not only of up-titration but also 
 
 
down-titration as well.  
 
c. Rate of medication persistence: % of patients on medications at baseline who re
 
mained on medications during the study period  
Page Break  

9 
 
  
HFpEF:  
For those with HFpEF, baseline to 9 months change in average composite endpoint of target dose 
achievement for the main classes of drugs (RASi/MRA/SGLT2i) among eligible patients.  
  
a. Goal doses will be based on the 2020 ACC Expert Consensus Decision 
Pathway for Optimization of Heart Failure Treatment (4) and 2022 Heart Fail-
ure Guidelines.  
b. Calculation similar to the above for HFpEF using the three relevant classes  
c. Rate of medication persistence: % of patients on medications at baseline 
who remained on medications during the study period  
  
AF:  Total proportion of eligible patients with an OAC prescription at baseline and 9 months   
a. Rate of OAC initiation: % of patients not on OAC at baseline who were 
started on OAC during the study period  
b. Rate of OAC persistence: % of patients on OAC at baseline or  who started 
OAC thereafter who remained on OAC during the study period  
  
All outcomes data will be stratified by the following subgroups: age, race, sex, socioeconomic 
status, English vs non-English speaking.  
 
Secondary Objective 
TRANSFORM3:  
1. Difference in patient reported outcome scores specifically;   
a) Difference in patient reported outcomes on Morisky Medication Adherence Scale 
(MMAS-4) from baseline, 3 and at 9 months  
b) Difference in patient reported outcomes on Patient Activation Measure® (PAM) from 
baseline, 3 and at 9 months  
c) Difference in patient-reported outcome/KCCQ-12 scores from baseline to 9 months 
(applicable to HFrEF and HFpEF study cohorts only)  
  
By Disease State:  
T2D/ASCVD:   
 
1. greater use of guideline-directed cardioprotective therapies  
 
2. improved metabolic parameters (body weight, BMI, HbA1c, systolic BP, lipid 
 
levels)  
 
3. lower total daily insulin dose (among patients on any insulin at baseline)  
 
4.Proportion of eligible patients with visits with an opportunity to discuss GDMT 
 
during the study period  
  
HFrEF:    
1. Relative change in actual achieved doses of individual classes of pivotal therapies 
(RASi/beta blocker/ MRA/SGLT2i).  
2. Relative change in achievement of target doses (yes/no) of pivotal therapies (RASi/beta 
blocker/MRA/SGLT2i).  

10 
 
3. Proportion of eligible patients with visits with an opportunity to discuss GDMT during 
the study period  
  
HFpEF  
1. Relative change in actual achieved doses of individual classes of pivotal therapies 
(RASi/MRA/SGLT2i).  
2. Relative change in achievement of target doses (yes/no) of pivotal therapies (RASi/ 
/MRA/SGLT2i).  
3. Proportion of eligible patients with visits with an opportunity to discuss GDMT 
during the study period  
  
AF:  
1. Proportion of eligible patients with visits with an opportunity to discuss OAC dur-
ing the study period  
  
Implementation Efficacy Measures:  
 We will assess engagement with the technology and referral completion rates by 
patients   
 Short questionnaires (PAM, MMAS-4, KCCQ-12, CardioSmart E-Diary) will be 
completed at baseline by patient participants to determine any patient factors that may 
modify the responses to each of the intervention arms (centered around baseline per-
ception of care optimization, perceived cardiovascular risk, willingness to take new 
therapy, clinician trust / therapeutic relationship). See appendix.  
 
Research Methods 
 
All eligible patients (see detailed inclusion/exclusion criteria above) with HF, AF and/or with 
T2D/ASCVD, who are not currently treated on optimal GDMT will be identified across all 
health systems.   
 
All eligible patients will be randomized to 1 of the 3 implementation approaches and remain un-
der the randomized strategy for the remainder of the study (following intention-to-treat princi-
ples). Even if the patient changes PCP or cardiologist (expected low frequency), patients will 
continue to receive the care under the arm in which they were randomized to. The interventions 
will be clinician-facing and we chose to select PCP and cardiologists as the target for quality im-
provement for several reasons: 1) PCPs represent a large cohort of clinicians across health sys-
tems, serving as the entry of care and access point for specialty referrals; 2) Patients are unlikely 
to change PCPs and cardiologist during the short-term duration of the study; 3) Most or all pa-
tients are assigned a PCP  in a health system thus allowing for clear clinician attribution; 4) PCPs 
and cardiologists may have sufficient exposure and comfort with prescription of these risk reduc-
tion therapies to allow successful intervention to action. If patients leave the health system en-
tirely, then the participant will be censored as lost to follow-up.  
 
Randomization Scheme: Patients will be randomized 1:1:1 to the 3 quality improvement strate-
gies using a standardized randomization software within the Biofourmis platform. To ensure ade-
quate power, enrollment will only end when all three arms have met their individual targets for 

11 
 
patient accrual in both disease categories and representation of underserved populations and 
those with health care disparities historically across sites. Enrollment of patients with comorbidi-
ties will be accomplished through prospective patient identification of patients eligible by disease 
state and focus populations.  
 
A) Clinician and Patient Education: This implementation strategy will support engaging 
the patients with their existing clinicians using a CardioSmart materials to guide treat-
ment expectations.    Clinicians also will receive education on the latest medications for 
CV risk management.  There is no “placebo” arm.  
 
B) Technology + Education: This implementation strategy will leverage technology to ap-
ply “audit and feedback” of prior care to inform recommendations for future care. These 
suggestions will encompass the domains of GDMT medications based on eligibility and 
potential opportunity for an SGLT2i, GLP-1RA, ACEi/ARB, antiplatelet or antithrom-
botic therapy, and statin therapy, beta blocker, RASi, MRA and DOAC or warfarin. The 
incorporation of technology for opportunities for GDMT will be utilized to identify tai-
lored opportunities for each CV medication based on guideline recommendations. Clini-
cians will be presented individual patient-specific recommendation(s) for further optimi-
zation of GDMT approximately every two weeks.  
 
Specifically, an EHR data extractor or data entry form will process data to Biofourmis, 
where a dashboard will be created.  This dashboard will include a) lists of eligible pa-
tients for the study and b) an update on opportunities for further medication optimization.  
The latter information will be based on guideline-directed medical targets as articulated 
in the ACC clinical policy. Guidance regarding post-initiation monitoring strategies will 
be additionally included.  A patient facing tool will be connected to the dashboard for pa-
tient education, surveying, medication adherence, patient reported outcomes, and patient 
recorded data.  
 
C) Referral Support + Education: Each site will have referral access to a virtual GDMT 
team (TRANSFORM3). Primary care physicians or cardiologists caring for patients ran-
domized to this intervention strategy will receive notification of the referral. All patients 
randomized to this group will be considered in this group whether or not the referral to 
the virtual GDMT team is completed.  Care in this group will be supported by the same 
technology as arm B with the same standardized opportunities for improvement.  The vir-
tual GDMT team will have access to data entered into the Biofourmis platform from the 
EHR and/or supplemented by standard patient interviews.  The virtual team will follow 
an every two week medication review schedule for possible adjustments until GDMT op-
timization has been completed.    
 
In order to standardize education about best practices surrounding GDMT directed care (to estab-
lish a cognitive baseline), educational materials will include a “suite of tools” shared with all cli-
nicians.  
 
Quality Improvement strategies and resources for all arms will include: 
 Population Identification & Reporting  

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 Quality Ambassadors  
 Communications  
 Education 
 
Mixed Methods Evaluation of Implementation Outcomes 
 
We will conduct secondary analyses to understand patient-level (age, sex, race, insurance, etc.), 
clinician/health system-level (academic/non-academic, urban/rural setting, etc.), and interven-
tion-level (timing of delivery of prompt, etc.) predictors of “success” (prescription of an evi-
dence-based CV risk reduction therapy) by each implementation approach where applicable. 
 
In addition, clinicians engaging with any of the implementation interventions, we will assess use 
of the technology and referral completion rates to the virtual GDMT team. Specifically, we will 
attempt to track the following elements: 
 
1. Time from referral order to first appointment in GDMT team 
2. Attendance rate GDMT team appointment (patient leakage) 
3. Timing from message to new appointments/new messages from provider to patient, 
which helps determine if this inter-visit time is actually a ‘semi-hot’ state. 
 
We will collect data and assess relative timelines of intervention, clinic visits, and timing of 
medication prescriptions. This would help us understand if changes in prescription are clustered 
around the time of the intervention (even in the absence of a scheduled visit) or if visits are 
scheduled after intervention to discuss therapeutic changes. 
 
Short questionnaires will also be completed by patient participants (See Appendix).  
 
Treatment of Patients 
 
All care decisions will be left to the treating clinician, and no care recommendations will be 
mandated. We will leverage the Biofourmis platform to manage patients and provide referral to a 
virtual GDMT team.  
 
Site based procedures and Study Managers:  
 
A) Patient-Level Randomization Stratified by Study Site: The unit of allocation will be 
the patient. However, to ensure balance of participants and account for any large baseline 
variation in care practices across health systems, the analysis will be stratified by study 
site. 
B) Study Manager: In quality improvement arm A, Study Managers may facilitate access 
of CardioSmart materials to the patient.  In quality improvement arm B, Study Managers 
will enroll patients in technology guided care using standardized language. In study arm 
C, Study Managers will create e-referrals to the virtual GDMT team.  
C) Qualitative Surveys: The sites will participate with the quality ambassadors in any sur-
veys, including the qualitative survey, and provide regular feedback to the ambassadors 
for any challenges and/or best practices discovered. In addition, patient participants will 

13 
 
complete a brief baseline assessment of perceptions around care quality, cardiovascular 
risk, willingness to take another therapy, and therapeutic relationships. 
 
Rationale for Selection Criteria 
 
The study was designed to identify patients at risk for cardiovascular events who meet eligibility 
criteria for treatment optimization for GDMT. The exclusion criteria are employed to minimize 
potential risks of individuals and reduce the number of patients who may be intolerant or ineligi-
ble for therapy. 
 
Withdrawal criteria 
 
All PCPs and cardiologists (target clinicians for the quality improvement initiative) will receive a 
correspondence prior to the start of the study describing the initiative. Any clinician who does 
not wish to receive the quality improvement communication will be allowed to opt-out such that 
all patients under their direct care will not be eligible for the study. At any time during the study, 
clinicians may decide to similarly opt-out. All patients who have already been randomized prior 
to clinician withdrawal will be analyzed in the originally randomized arm (intention-to-treat ap-
proach). 
 
Risk/Benefit Assessment 
 
As study procedures reflect CV medication management via guideline recommendations sup-
ported by the clinical judgment of the managing physician, there is no envisioned procedural risk 
to patients through involvement in the study.  No testing, time, risk, or procedures beyond those 
required for routine care will be imposed. The primary risk associated with this project is the po-
tential for a breach of patient confidentiality. The ACCF has established a robust plan for ensur-
ing appropriate and commercially reasonable physical, technical, and administrative safeguards 
are in place to mitigate such risks as described in the Quality Control section of this protocol. 
 
Data Sources 
 
Data sources will be EMR, other data in the technology solution, electronic informed consent 
forms and patient survey questionnaires administered by the Biofourmis patient app.  
 
Statistical Methods 
The final Statistical Analysis Plan (SAP) will be finalized prior to the study completion. 
 
Patient-Level Randomization to 3 Quality Improvement Initiative: Simple (traditional) ran-
domization minimizes variation in clinical profiles of patients included in each arm. While clus-
ter randomization at the clinician level may limit the potential for contamination bias (chance 
that clinicians caring for patients randomized to one implementation approach may influence the 
care of another patient on their panel), the number of eligible patients under each individual cli-
nician’s care is anticipated to be small. 
 

14 
 
Power Estimates: In this 3-arm trial, stratified by study site, we estimated the sample size of pa-
tients needed to show a difference between the quality improvement arms.  
 
Current estimates of use of either SGLT2i or GLP-1RA among eligible patients is 15%%. As-
suming an alpha of 0.05, we would require 121 patients in each of the 3 arms to show 80% 
power to detect at least an absolute difference of 15% between education alone and the education 
+ decision support arms and a 15% between education alone and the education + decision sup-
port + facilitated referral group. Assuming a 20-25% loss to follow-up rate, 750 patients would 
be required.  
 
Current estimates of optimal GDMT prescription and titration for HFrEF are 2%.  The differ-
ences for each arm are expected to be greater than the SGLT2i or GLP-1RA classes. 
 
Given the evolving evidence for HFpEF, there are no established rates for GDMT. 
 
Current estimates of optimal use of anticoagulation medication for AF is 60-65%.  The study 
does not anticipate reaching power for this disease state. 
 
The primary comparison will be between the education alone arm (1) and the education + deci-
sion support + referral group (3). Secondary analyses will compare education alone (1) with the 
education + decision support group (2). The study will be powered for both primary and second-
ary comparisons for T2D/ASCVD and HF (HFrEF and HFpEF combined). 
 
Rates of Primary Endpoint Over 9 months 
Estimated Number of Patients in 
Each of 3 Arms 
Education 
Alone (1) 
Education 
+Decision 
Support 
(2) 
Education+Decision+Referral 
Support (3) 
80% power 
90% power 
1 vs 2 1 vs 3
1 vs 2
1 vs 3 
0.05  
0.075 
0.1 
1471 
435 
1969 
582 
0.1  
0.15 
0.2 
686 
199 
918 
266 
0.125 
0.1875 
0.25 
529 
152 
708 
203 
0.15  
0.3 
0.3 
424 
121 
568 
161 
 
Quality Control 
 
TRANSFORM3 collaborators have established a robust plan for ensuring appropriate and com-
mercially reasonable physical, technical, and administrative safeguards are in place to maintain 
the integrity of study data stored and used. 
 
All study data shall be maintained on secure servers with appropriate safeguards in place. The 
ACCF project team will periodically review all activities involving Protected Health Information 
to ensure that such safeguards including standard operating procedures are being followed. The 

15 
 
partners shall also communicate to all study personnel the procedure for notifying the ACCF of 
any breach of confidentiality and immediate mitigation standards that need to be followed.  
 
ACCF shall limit access to Protected Health Information, and to equipment, systems, networks, 
applications and media that contain, transmit, process or store Protected Health Information 
(“Equipment, Systems and Media”), to those employees of ACCF who need to access the Pro-
tected Health Information for purposes of performing ACCF’s obligations to Covered Entities 
(“Participants”) who are in a contractual relationship with the ACCF. ACCF shall implement dis-
cretionary access controls designed to permit each user access to Equipment, Systems and Me-
dia, which are specifically necessary to accomplish only assigned tasks on behalf of study partic-
ipants. ACCF shall strictly control physical and electronic access to Equipment, Systems and 
Media in the following manner: 
 
Physical access 
a. All Protected Health Information, and all Equipment, Systems and Media must be 
stored in a secure facility or secure area within ACCF’s facilities which has separate 
physical controls to limit access, such as locks or physical tokens (“Secured Areas”). 
b. ACCF shall limit access to Secured Areas to those of its employees or agents who have 
a legitimate business need to access the secure area, and after ACCF has made an ad-
ministrative determination of the employee’s trustworthiness. Such determination of 
trustworthiness may include: checking references, checking education and employ-
ment history, and searches of public records. 
c. Access to Secured Areas by individuals other than those who have been authorized to 
access Secured Areas shall only be permitted if there is a legitimate business need, and 
only if such access is continuously monitored by an employee who has been author-
ized. 
d. Secured Areas must be monitored 24 hours per day, 7 days per week, either by em-
ployees or agents of ACCF by video surveillance, or by intrusion detection systems. 
 
Electronic access 
a. Each user who has access to Equipment, Systems and Media (“User”) must have a 
unique identifier. 
b. Users must be authenticated by one of the following methods: unique token or unique 
password. ACCF shall prohibit generic user accounts and shall implement inactivity 
time-outs, where technically feasible, for User devices that access study data. 
 
Wireless Devices 
Encryption of wireless network data transmission and authentication of wireless devices 
containing study data ACCF’s network is required. 
 
Transmission of Protected Health Information 
Protected Health Information may only be transmitted off ACCF’s premises to approved 
parties, Electronic Protected Health Information may only be transmitted via encrypted 
and authenticated channels, such as VPN, encrypted FTP, SSL or HTTPS. 
 
External Access 

16 
 
Internet 
If any Equipment, Systems or Media have Internet connectivity, users must be advised 
that their unique identifier and authentication tool (e.g. password) must not be shared 
with others.  Where password authentication is employed to authenticate Users, ACCF 
access and communication to or from the Internet must occur through an actively man-
aged Internet firewall service. 
 
Remote access  
If any employees or agents of ACCF have remote access to Protected Health Information, 
or to Equipment, Systems and Media, from offsite locations, ACCF shall adopt systems 
and procedures to secure such connections and transmissions. At a minimum, ACCF 
must ensure the following: 1) dial-up access will occur through a technical security ser-
vice such as Remote Authentication Dial-In User Service (RADIUS); 2) access via the 
Internet will be controlled via secure technologies to include authentication and encryp-
tion. Acceptable technologies include firewalls and virtual private network services; and 
3) ACCF shall require users who access Protected Health Information via personally 
owned devices and remote access services to take responsibility for the integrity and se-
curity of their systems and employ anti-virus software and apply operating system service 
packs as they are released.  Protected Health Information may not be stored on personally 
owned devices. 
 
Software Controls 
Virus Protection 
ACCF shall employ virus protection on systems or networks that store, process, access or 
transmit Protected Health Information, and such protection systems must include real-
time or periodic scans. 
 
Service Packs and Security Patches 
ACCF shall apply operating system service packs and security patches to systems or net-
works that store, process, access or transmit Protected Health Information as soon as 
practicable after they are released. 
 
Audit 
ACCF shall implement technical features or controls to record security-relevant activity.  
ACCF periodically reviews activity logs, investigates and resolves incidents where unau-
thorized access and attempts are identified. ACCF shall maintain audit logs. 
 
Violations 
ACCF shall have a process in place for employees to report instances of violations of pri-
vacy and security policies and procedures to the appropriate ACCF personnel. 
 
Transportation and Transmission of Protected Health Information 
Protected Health Information, and Equipment, Systems and Media may not be trans-
ported off of ACCF’s premises unless such Protected Health Information is encrypted.   
 
Disposal of files or media which contain Protected Health Information. 

17 
 
If ACCF is required to destroy files or media containing Protected Health Information 
pursuant to the Business Associate Agreement, such destruction shall be performed in the 
following manner: 
 
Magnetic Media  
Magnetic Media such as tapes, diskettes, hard drives, must be purged of all information 
such that the data is no longer reasonably retrievable from the media. Degaussing is an 
acceptable method of purging information from magnetic media. 
 
 
Non-Magnetic Media 
Non-magnetic media such as hard copies, CDs or DVDs must be physically destroyed 
such that the data is no longer reasonably retrievable from the media. Acceptable meth-
ods of physical destruction include shredding.  
 
TRANSFORM3 participating collaborators shall employ comparable safeguards that store, pro-
cess, access or transmit Protected Health Information with real-time protection. No printed mate-
rials will be generated as part of this study. 
 
Informed Consent 
 
In all arms, clinician choice will not be restricted and care recommendations will not be man-
dated. These quality improvement initiatives are all clinician-facing to promote best practice / 
guideline recommended care and supported by a linked patient application, to support data col-
lection and clinician engagement.  All study arms can be considered standard of care, and no in-
vestigation intervention or therapy is being provided. All PCPs and cardiologists will receive a 
correspondence prior to the start of the study describing the initiative. Any clinician who does 
not wish to receive the quality improvement communication will be allowed to opt-out such that 
all patients under their direct care will not be eligible for the study. At any time during the study, 
clinicians may decide to similarly opt-out. 
 
Eligible patients will be enrolled via paper consent or electronically utilizing software services 
provided by Biofourmis.  
  
Consent materials will be provided with sufficient time for the patient to consider their participa-
tion in the study. All consent materials will be in the patients’ native language and will describe 
the quality improvement nature of the study and that data collection of therapies will be tracked.   
  
If the patient agrees to participation in the study via paper, the informed consent and signature 
will be stored at the study site and/or the Biofourmis platform.  
  
If the patient agrees to participation in the study electronically, their informed consent will be 
recorded through e-consent processes with signature stored at Biofourmis with a copy to the 
study site.  At any time, patients may withdraw consent.  In such a circumstance, patients will be 
analyzed per intent to treat. Only those patients capable of giving informed consent will be en-
rolled in the study.  

18 
 
  
There are no costs or compensation to the patient for participation in the TRANSFORM3 study.  
 
References 
Das SR, Everett BM, Birtcher KK, Brown JM, Januzzi JL Jr, Kalyani RR, Kosiborod M, Mag-
wire M, Morris PB, Neumiller JJ, Sperling LS. 2020 Expert Consensus Decision Pathway on 
Novel Therapies for Cardiovascular Risk Reduction in Patients With Type 2 Diabetes: A Report 
of the American College of Cardiology Solution Set Oversight Committee. J Am Coll Cardiol. 
2020 Sep 1;76(9):1117-1145. doi: 10.1016/j.jacc.2020.05.037. Epub 2020 Aug 5. PMID: 
32771263; PMCID: PMC7545583.  
 
Writing Committee, Maddox TM, Januzzi JL Jr, Allen LA, Breathett K, Butler J, Davis LL, 
Fonarow GC, Ibrahim NE, Lindenfeld J, Masoudi FA, Motiwala SR, Oliveros E, Patterson JH, 
Walsh MN, Wasserman A, Yancy CW, Youmans QR. 2021 Update to the 2017 ACC Expert 
Consensus Decision Pathway for Optimization of Heart Failure Treatment: Answers to 10 Piv-
otal Issues About Heart Failure With Reduced Ejection Fraction: A Report of the American Col-
lege of Cardiology Solution Set Oversight Committee. J Am Coll Cardiol. 2021 Feb 
16;77(6):772-810. doi: 10.1016/j.jacc.2020.11.022. Epub 2021 Jan 11. PMID: 33446410. 
 
Desai AS, Maclean T, Blood AJ, et al. Remote Optimization of Guideline-Directed Medical 
Therapy in Patients With Heart Failure With Reduced Ejection Fraction. JAMA Cardiol. 
2020;5(12):1430-1434. doi:10.1001/jamacardio.2020.3757 
 
Lloyd-Jones DM, Huffman MD, Karmali KN, et al. Estimating Longitudinal Risks and Benefits 
From Cardiovascular Preventive Therapies Among Medicare Patients: The Million Hearts Lon-
gitudinal ASCVD Risk Assessment Tool: A Special Report From the American Heart Associa-
tion and American College of Cardiology [published correction appears in Circulation. 2017 Mar 
28;135(13):e824-e825]. Circulation. 2017;135(13):e793-e813. 
doi:10.1161/CIR.0000000000000467 
 
 
 

19 
 
APPENDIX  
PDF/Printable Materials   
  
Heart Failure   
Action Plans  
Your Action Plan for Heart Failure With Preserved Ejection Fraction (HFpEF)  
Your Action Plan for Heart Failure With Reduced Ejection Fraction (HFrEF)  
  
Worksheets  
Heart Failure: Making the Most of Your Follow-Up Visits  
Your Heart Failure Daily Tracker  
Your Heart Failure Checklist  
  
Quick Tips  
Quick Tips Sheet: Daily Weight Check  
Quick Tips Sheet: Minding Your Emotional Health  
Quick Tips: Exercise and Your Heart  
Quick Tips: Heart Failure Medications  
Quick Tips: Limiting Salt  
Quick Tips: Heart Failure Signs and Symptoms  
Quick Tips: Triggers and What To Do  
  
More Resources  
Heart Failure, The Basics   
Heart Failure: Questions to Ask   
Heart Failure: Frequently Asked Questions   
Heart Failure: What Your Treatment Plan Might Include  
Heart Failure: Caregivers   
  
  
Atrial Fibrillation  
Action Plan  
 Your Action Plan for Managing Atrial Fibrillation  
  
Worksheets  
 AFib Medication List  
 10 Steps You Can Take to Manage Atrial Fibrillation  
 Keeping Track of Symptoms and How AFib Affects Your Life  
 AFib Symptom Diary   
  
Diabetes and Risk of Heart Disease  
Action Plan  
 Your Action Plan for Managing Diabetes and Protecting Your Heart  
Worksheets   
 Diabetes and Heart Disease: What You Need to Know:   
 10 Steps to Lower Your Chance of Diabetes-Related Heart Problems:   
 My Medication List:   

20 
 
Patient Survey Questions  
  
CardioSmart E-Diary  
Source: Cardiosmart.org   
  
1. Here is how I would describe I feel today  
a) A good day with heart failure  
b) A bad day with heart failure   
c) My worst day with heart failure  
2. On a scale from 0 to 10, my stress or anxiety level is (0-10)  
3. On a scale from 0 to 10, how sad or depressed have I been feeling? (0-10)  
4. Generally, how am I coping with my [heart disease] diagnosis?  
a) Very poorly  
b) Poorly  
c) Ok  
d) Pretty well  
e) Very well, all things considered  
5. Overall, describe the stage you are at in living with [heart disease]  
a) Acceptance  
b) Denial  
c) Anger  
d) Depressed  
  
Morisky Medication Adherence Scale (MMAS-4) (Yes/No)  
Source: 1569058438 (768×1024) (scribdassets.com)  
  
1. Do you ever forget to take your medicine?  
2. Are you careless at times about taking your medicine?  
3. Sometimes, if you feel worse when you take your medicine, do you stop taking it?  
4. When you feel better, do you sometimes stop taking your medicine?  
Page Break  
Patient Activation Measure (PAM)   
Source: https://www.insigniahealth.com/research/research-licenses   
(Disagree Strongly, Disagree, Agree, Agree Strongly)  
  
1. When all is said and done, I am the person who is responsible for taking care of my health  
2. Taking an active role in my own health care is the most important thing that affects my health  
3. I am confident I can help prevent or reduce problems associated with my health  
4. I know what each of my prescribed medications do  
5. I am confident that I can tell whether I need to go to the doctor or whether I can take care of a 
health problem myself  
6. I am confident that I can tell a doctor concerns I have even when he or she does not ask  
7. I am confident that I can follow through on medical treatments I may need to do at home  
8. I understand my health problems and what causes them  
9. I know what treatments are available for my health problems  
10. I have been able to maintain (keep up with) lifestyle changes, like eating right or exercising  
11. I know how to prevent problems with my health  

21 
 
12. I am confident I can figure out solutions when new problems arise with my health  
13. I am confident that I can maintain lifestyle changes, like eating right and exercising even dur-
ing times of stress  
  
  
Kansas City Cardiomyopathy Questionnaire (KCCQ-12