Personalizing Intervention to Reduce Clinical Inertia in the Treatment of Hypertension
Phase: NA
Conditions: Hypertension
Sponsor: Brigham and Women's Hospital

 
Reduce clinical inertia in hypertension treatment          
Version 4 
PIs: Haff/Choudhry  
 
         October 11, 2022 
 
 
1 
 
 
CLINICAL TRIAL PROTOCOL 
 
Personalizing intervention to reduce clinical inertia in the treatment of hypertension 
 
National Clinical Trial (NCT) Identified Number: NCT04603560 
 
 
Principal Investigators: 
Nancy Haff, MD, MPH 
Niteesh K. Choudhry, MD, PhD 
Center for Healthcare Delivery Sciences and Division of Pharmacoepidemiology and 
Pharmacoeconomics, Brigham and Women’s Hospital and Harvard Medical School 
 
Funded by the National Institute on Aging 
Grant Number: P30AG064199 
Version Number: 4 
October 11th, 2022 
 
 

 
Reduce clinical inertia in hypertension treatment          
Version 4 
PIs: Haff/Choudhry  
 
         October 11, 2022 
 
 
2 
 
TABLE OF CONTENTS 
SUMMARY OF CHANGES FROM PREVIOUS VERSION ...................................................................... 4 
1. BACKGROUND AND RATIONALE ................................................................................................... 5 
2. STUDY AIMS ..................................................................................................................................... 6 
3. STUDY DESIGN ................................................................................................................................ 6 
3.1 STUDY SITE ..................................................................................................................................... 6 
3.2 OVERALL DESIGN ............................................................................................................................. 7 
3.2.1 Aim 1 Design ........................................................................................................................... 7 
3.2.2 Aim 2 Design ........................................................................................................................... 7 
3.3 STUDY SCHEMA ............................................................................................................................... 8 
3.4 SCIENTIFIC RATIONALE FOR STUDY DESIGN ....................................................................................... 10 
3.5 JUSTIFICATION FOR INTERVENTION .................................................................................................. 10 
3.6 END-OF-STUDY DEFINITION ............................................................................................................. 10 
3.7 DATA SOURCES ............................................................................................................................. 10 
3.8 SCHEDULE OF ACTIVITIES ............................................................................................................... 11 
4. STUDY POPULATION ..................................................................................................................... 12 
4.1 INCLUSION CRITERIA ...................................................................................................................... 12 
4.2 EXCLUSION CRITERIA ..................................................................................................................... 12 
4.3 RECRUITMENT AND RETENTION ....................................................................................................... 13 
4.3.1 Informed consent considerations ........................................................................................... 13 
4.3.2 Inclusivity of study subjects ................................................................................................... 13 
5. STUDY INTERVENTIONS ............................................................................................................... 14 
5.1 THERAPEUTIC AREAS ..................................................................................................................... 14 
5.2 STUDY INTERVENTIONS .................................................................................................................. 14 
5.3 MEASURES TO MINIMIZE BIAS: RANDOMIZATION AND BLINDING ............................................................. 14 
6. STUDY ASSESSMENTS AND PROCEDURES ................................................................................ 15 
6.1 
BASELINE DATA .......................................................................... ERROR! BOOKMARK NOT DEFINED. 
6.2  
OUTCOMES ............................................................................... ERROR! BOOKMARK NOT DEFINED. 
6.3 
ADVERSE EVENTS AND UNANTICIPATED PROBLEMS ........................ ERROR! BOOKMARK NOT DEFINED. 
7. STATISTICAL CONSIDERATIONS ......................................... ERROR! BOOKMARK NOT DEFINED. 
7.1  
STATISTICAL HYPOTHESES.......................................................... ERROR! BOOKMARK NOT DEFINED. 
7.2  
SAMPLE SIZE DETERMINATION ..................................................... ERROR! BOOKMARK NOT DEFINED. 

 
Reduce clinical inertia in hypertension treatment          
Version 4 
PIs: Haff/Choudhry  
 
         October 11, 2022 
 
 
3 
 
7.3  
STATISTICAL ANALYSES .............................................................. ERROR! BOOKMARK NOT DEFINED. 
7.3.1 
ANALYSIS OF THE PRIMARY ENDPOINT ....................................... ERROR! BOOKMARK NOT DEFINED. 
7.3.2 
ANALYSIS OF SECONDARY ENDPOINTS ....................................... ERROR! BOOKMARK NOT DEFINED. 
7.3.3 
BASELINE DESCRIPTIVE ANALYSES ............................................ ERROR! BOOKMARK NOT DEFINED. 
7.3.4 
SUBGROUP ANALYSES ............................................................. ERROR! BOOKMARK NOT DEFINED. 
7.3.5 
EXPLORATORY ANALYSES ........................................................ ERROR! BOOKMARK NOT DEFINED. 
8. ETHICAL AND REGULATORY REQUIREMENTS ................... ERROR! BOOKMARK NOT DEFINED. 
8.1 
ETHICAL CONDUCT ..................................................................... ERROR! BOOKMARK NOT DEFINED. 
8.2 
INFORMED CONSENT................................................................... ERROR! BOOKMARK NOT DEFINED. 
8.3  
CONFIDENTIALITY AND PRIVACY ................................................... ERROR! BOOKMARK NOT DEFINED. 
8.4 SAFETY OVERSIGHT ......................................................................... ERROR! BOOKMARK NOT DEFINED. 
8.5 BENEFIT RISK ASSESSMENT .............................................................. ERROR! BOOKMARK NOT DEFINED. 
8.5.1 KNOWN POTENTIAL RISKS .............................................................. ERROR! BOOKMARK NOT DEFINED. 
8.5.2 KNOWN POTENTIAL BENEFITS ......................................................... ERROR! BOOKMARK NOT DEFINED. 
8.5.3 ASSESSMENT OF POTENTIAL RISKS AND BENEFITS ............................ ERROR! BOOKMARK NOT DEFINED. 
9. LIST OF REFERENCES .................................................................................................................. 27 
 
 
 
 

 
Reduce clinical inertia in hypertension treatment          
Version 4 
PIs: Haff/Choudhry  
 
         October 11, 2022 
 
 
4 
 
Summary of Changes from Previous Version 
 
Date of 
submission 
Summary of Revisions 
Made 
Rationale for modification 
Approval 
date 
02-09-21 
Randomization changed to 
tertiles of sessions practiced 
per week 
 
Based on a review of current practice patterns 
for our providers, stratifying based on number of 
sessions that a physician practices per week 
(which is proportional to panel size) is a more 
practical and predictable measure to use 
prospectively (since number of sessions per 
week changes less than visit volumes). Further, 
tertiles of panel size will be easier to implement 
with a 3-arm trial than quintiles. The intent of 
stratification is the same, but our proposed 
change will be easier to operationalize.   
02-18-21 
02-09-21 
 Inclusion/exclusion criteria 
 
To ensure that we enroll only actively-practicing 
outpatient providers who are able to receive 
weekly interventions and who care for a 
sufficient volume of patients, we propose to 
exclude providers who practice less than one 
session per week or whose total panel size is 
less than 100 patients. 
02-18-21 
02-09-21 
Revisions of interventions 
We have shortened the text in the two 
interventions to make it easier and faster for 
providers to read (social norming, academic e-
detailing) 
02-18-21 
06-02-21 
Revision of intervention 
frequency 
We have altered the frequency with which we 
send out the dashboard component of the social 
norming intervention from weekly to every 2-4 
weeks. This frequency will more accurately 
reflect the rate of change of the percentage of 
uncontrolled hypertensive patients among 
PCPs. 
 
09-28-21 
Revision of 
inclusion/exclusion criteria 
 
Revision of goal blood 
pressure 
 
Addition of subject lines to 
intervention messages 
 
Changed sample size 
determination calculations 
 
Modified study timeline 
To ensure we have a large enough pool of 
participants to draw from, we have altered the 
study timeline and the eligibility criteria of 
providers to include those with at least 2 
patients meeting the eligibility criteria, instead of 
the original requirement of at least 10. 
Additionally, we have modified our blood 
pressure goal to be <140/90 for all patients to 
streamline identification of eligible patients. 
Finally, we have modified our sample size and 
power calculations to allow us to detect a larger 
effect size. 
 
 
 
 

 
Reduce clinical inertia in hypertension treatment          
Version 4 
PIs: Haff/Choudhry  
 
         October 11, 2022 
 
 
5 
 
1. Background and Rationale 
Hypertension is a large contributing factor to cardiovascular morbidity and mortality among older 
adults, yet more than half of patients with hypertension have blood pressures above clinical goal.1 
The failure of physicians to initiate or intensify treatment regimens when clinically indicated is often 
referred to as clinical inertia, and is a well-described phenomenon in the treatment of this 
condition.2-5 
 
Interventions to reduce clinical inertia and improve blood pressure control, including education, 
reminders, feedback, ambulatory blood pressure monitoring, and pharmacist-driven interventions, 
have been shown to be effective but only modestly so.5 One hypothesis for this limited 
effectiveness is that physicians may have different underlying behavioral factors that contribute to 
their inertia behavior. A qualitative analysis of cases of clinical inertia in hypertension care 
identified seven distinct categories of physician justifications for non-intensification.6 
 
Behavioral science research suggests that individuals are influenced by factors of which they are 
not consciously aware. When describing reasons for their own behavior, people generally over-
value personal introspection rather than context7,8 and generate explanations of their behaviors to 
help resolve cognitive dissonance or the discomfort of an “explanatory vacuum”.9 In the case of 
inertia, multiple and/or variable underlying behavioral tendencies, such risk aversion, 
conscientiousness, burnout, or need for closure, are likely more relevant explanations for physician 
behavior than physician-provided justifications. Thus, rather than relying on justifications, an 
alternative approach is to measure behavioral factors through surveys and empirically elucidate 
which physician behavior characteristics are correlated with clinical inertia and with a physician’s 
responsiveness to different interventions intended to address this problem. 
 
Further, physicians are likely influenced by context and may behave differently with different 
patients. For example, a physician may not intensify treatment with a healthy patient who strongly 
prefers to try diet/exercise, but that same physician might consider blood pressures values that are 
just a few points higher than goal to be “close enough” for older patients that have many 
comorbidities. 
 
Accordingly, we propose to measure physician behavioral factors using survey instruments, test 
interventions for clinical inertia in hypertension care, and identify characteristics of patients and 

 
Reduce clinical inertia in hypertension treatment          
Version 4 
PIs: Haff/Choudhry  
 
         October 11, 2022 
 
 
6 
 
physicians that are associated with the likelihood of treatment intensification and their 
responsiveness to different interventions. This information could then be used to more effectively 
design and target interventions to those most likely to respond.  
 
2. Study Aims 
The main aims are to 1) test two interventions to reduce clinical inertia in hypertension prescribing 
compared to control and 2) develop a model to predict intervention responsiveness based on 
physician and patient characteristics.  
 
The objectives and endpoints for this project are summarized below. 
OBJECTIVES 
ENDPOINTS 
JUSTIFICATION FOR ENDPOINTS 
Aim 1 
To determine the effectiveness 
of two interventions to reduce 
hypertension clinical inertia 
compared to control 
Primary: Intensification of 
hypertension treatment medications 
(i.e. dose increase or medication 
addition) at the time of the patient’s 
visit 
 
Secondary: Mean change in systolic 
blood pressure in each intervention 
group compared to control over 6 
months 
These outcomes are directly related to 
the interventions, are clinically 
meaningful, and are measurable using 
routinely collected data in the 
Electronic Health Record (EHR)  
Aim 2 
To identify patient and 
physician clusters and 
determine association of those 
clusters with intervention 
responsiveness 
Characteristics of patient and 
physician predictors that are 
associated with 1) clinical inertia in 
HTN care and 2) intervention 
responsiveness  
A model predicting intervention 
responsiveness could be used to tailor 
future interventions specifically to 
physicians in order to increase 
intervention effectiveness 
 
 
3. Study Design 
3.1 Study site 
Study participants will be recruited from primary care physicians (PCPs) at Massachusetts General 
Hospital (MGH). MGH is part of Mass General Brigham (MGB), a large integrated delivery network 
in Boston, MA. 
 

 
Reduce clinical inertia in hypertension treatment          
Version 4 
PIs: Haff/Choudhry  
 
         October 11, 2022 
 
 
7 
 
3.2 Overall design 
We propose a pragmatic randomized controlled trial to test two interventions targeting clinical 
inertia in hypertension compared to control, followed by predictive modeling to identify factors 
that are associated with intervention responsiveness. 
 
For Aim 1, we will use Electronic Health Record (EHR) data to identify physicians of patients 
whose hypertension treatment was not intensified despite their having persistently elevated 
blood pressure. We will then randomize primary care physicians to one of three arms: 
academic e-detailing, social norming, or no intervention (control). 
 
For Aim 2, we will conduct interviews with select physicians from each arm. We will then 
identify patient and physician characteristics that are associated with inertia and with 
responsiveness to each intervention. 
 
3.2.1 Aim 1 Design 
In Aim 1 of the study, we will conduct a three-arm randomized controlled trial to compare the 
effectiveness of two interventions compared to control on clinical inertia in hypertension treatment. 
We will recruit 45 primary care physicians (PCPs) in the Mass General Hospital (MGH) system 
caring for patients who are potentially in need of hypertension treatment intensification.  
 
Using EHR data, we will first identify patients: (1) aged 18-79; (2) for whom the recent blood 
pressure (BP) history in the last 18 months is above goal, (3) whose most recent BP at an 
outpatient visit was above goal, and (4) who did not have their hypertension treatment 
regimens intensified (dose increase, new medication added, or medication exchange) at or 
since that time. 
 
The BP goal for this study will be <140/90 for all patients. If there are multiple blood pressures 
on the same day, we will select which BP to use for the study. This will either be the lowest BP 
from that day (if this is routinely available in the EDW) or the last BP measured that day (this is 
available in the EDW).  The choice of which BP to use will be applied uniformly to all patients 
after reviewing preliminary data on BP availability in the EDW. To accommodate changes in 
care delivery that occurred during the COVID surge, outpatient visits will include in-office and 
virtual visits that had vitals recorded in the EHR the same day. We will exclude patients who, 

 
Reduce clinical inertia in hypertension treatment          
Version 4 
PIs: Haff/Choudhry  
 
         October 11, 2022 
 
 
8 
 
based upon EHR data, are excluded from the hypertension registry, are pregnant or post-
partum 6 months, or who are receiving hospice care.   
 
In order to ensure that sufficient patient visits occur during the intervention period for Aim 1 and 
enough patients per physician for our prediction model development in Aim 2, primary care 
physicians will need to have at least 2 patients on their panel meeting these criteria to be 
eligible for the study.  We will also exclude physicians with fewer than 100 patients on their 
primary care panel or who practice less than 1 session per week.  
 
Physicians will be informed about the study and agree to participate using an online consent 
process through RedCap, and then will be asked to complete a set of behavioral surveys 
administered through RedCap. PCPs will then be randomized to one of the two intervention arms 
or control arm. To minimize imbalance between treatment groups, we will use block stratified 
randomization.  Based on the number of sessions per week, providers will be determined to have a 
small (1-2 sessions), medium (3-4 sessions), or large (5 or more sessions) panel. Within each 
stratum, we will array physicians into blocks of 3 (note: could also be multiples of 3). All possible 
balanced combinations of assignment within the block will be allowed in each stratum. Ultimately, 
within each block and each stratum, physicians will have an equal probably of being assigned to 
one of the 3 arms. 
3.2.2 Aim 2 Design 
In Aim 2, we will conduct semi-structured interviews with select physicians across all study arms to 
further develop our understanding of what data elements are likely to be the most helpful or 
significant inputs for the predictive modeling analysis. Each interview will be moderated using a 
semi-structured interview guide.  
 
Following this, we will develop a regression model to evaluate the association of patient and 
physician characteristics with a) the likelihood of hypertension treatment intensification overall and 
b) the responsiveness to the study interventions. Finally, we will construct a model to predict the 
most likely intervention to elicit treatment intensification given physician demographics, with or 
without patient data. This model, if successful, could assist health systems in selecting the most 
appropriate individualized intervention to improve treatment intensification. 
3.3 Study Schema 
 

 
Reduce clinical inertia in hypertension treatment          
Version 4 
PIs: Haff/Choudhry  
 
         October 11, 2022 
 
 
9 
 
Aim 1 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Aim 2 
 
 
 
Conduct consent process.  
Baseline questionnaires. 
Qualitative interviews 
 
Arm 1 
Academic 
E-detailing 
Block Randomization of PCPs 1:1:1 
45 PCPs with opportunities to intensify HTN treatment 
 
Regression or predictive modeling to: 
a) Identify patient and physician clusters 
b) Develop responsiveness profiles 
Arm 2 
Social 
Norming 
 
Arm 3 
Control 

 
Reduce clinical inertia in hypertension treatment          
Version 4 
PIs: Haff/Choudhry  
 
         October 11, 2022 
 
 
10 
 
 
3.4 Scientific rationale for study design 
The use of a randomized trial design will be able to both provide stronger evidence of causality in 
the effectiveness of the interventions and allow for empiric derivation of patient and physician 
characteristics that may influence intervention responsiveness. An observational study design or 
physician self-report of factors that influence intervention responsiveness are more subject to bias.  
 
3.5 Justification for intervention 
Social norming10,11 and academic detailing10,12,13 interventions are effective tools to change 
physician behavior and improve hypertension management. However, few studies have evaluated 
specific patient and physician characteristics that might influence intervention effectiveness. With 
the results of this study, we hope to be able to target interventions more precisely to increase their 
effectiveness. This research could provide direct benefit to patients through improved blood 
pressure control and may increase physicians’ awareness and knowledge of hypertension 
treatment.  
 
3.6 End-of-study definition 
The active interventions in aim 1 are expected to last for no more than 6 months, and the post-
intervention qualitative interviews will be completed within 2 months after the intervention period is 
complete. Study data collection for the secondary outcome of blood pressure control will continue 
for 6 months after the intervention period is complete. Development of the prediction models will be 
done concurrently during that time.  We expect to complete the full study including all analyses by 
July 2022. Participants will be notified by email of study completion. 
 
3.7 Data sources 
Sources of research material, data that will be recorded, when data will be collected 
Data regarding patients' medical history, disease control, medication use and health care 
utilization will be obtained from EHR data, supported by Epic Systems, Inc. The data 
warehouses for this organization reside in an Oracle 9i environment and consists of the Clarity 
and Payer databases. The Clarity database is a relational database that contains clinical and 
financial information from the Epic Suite of products; including the electronic medical record 
system (EpicCare), the appointment scheduling system (Cadence), the patient accounting 

 
Reduce clinical inertia in hypertension treatment          
Version 4 
PIs: Haff/Choudhry  
 
         October 11, 2022 
 
 
11 
 
system (Resolute), the patient web portal and the master patient index (Identity). The various 
tables within the Clarity database are refreshed on a daily, weekly or monthly basis.  
 
Linkages to subjects, access to subject identities 
Individually-identifiable data are maintained for patient care purposes within the MGB network 
and are needed to identify patients for evaluation and to monitor care recommendations by 
physicians. Without this linkage, we could not fulfill the study’s objectives. To protect the 
confidentiality of these data, only the minimal necessary research staff will have access to 
personal identifiers. This will be necessary for linking data and contacting physicians. After 
linkage is completed and study variables are created, all identifiable information will be deleted 
from the study database. All research staff are properly trained in research management and 
will be approved by the IRB. All personally identifiable health information will be kept under 
lock and key.  
 
3.8 Schedule of activities 
 
 
 
 
 
 
 
 
 
 
 
Screening 
 
 
Enrollment 
Intervention 
Analysis 
Identification of eligible physicians 
X 
 
 
 
Recruitment of physicians 
X 
 
 
 
Consent Process 
 
X 
 
 
Physician surveys 
 
X 
 
 
Randomization 
 
X 
X 
 
Control & Experimental Interventions 
 
 
X 
 
Physician Interviews 
 
 
 
X 
Primary outcome analysis 
 
 
 
X 
Predictive modeling analysis 
 
 
 
X 

 
Reduce clinical inertia in hypertension treatment          
Version 4 
PIs: Haff/Choudhry  
 
         October 11, 2022 
 
 
12 
 
4. Study Population 
The study will include primary care physicians at MGH.  
 
4.1 Inclusion Criteria 
We will include primary care physicians meeting the following criteria: 
1. Practicing in primary care at Massachusetts General Hospital. 
2. Caring for at least 2 patients: (1) aged 18-79, (2) for whom the recent BP history in the last 
18 months is above goal, (3) whose most recent BP at an outpatient visit was above goal, 
and (4) who did not have their hypertension treatment regimens intensified (dose increase, 
new medication, or medication exchange) at or since that time. The BP goal will be <140/90 
for all patients. To accommodate changes in care delivery that occurred during the COVID 
surge, outpatient visits will include in-office and virtual visits that had vitals recorded in the 
EHR the same day. We will exclude patients who were excluded from the hypertension 
registry, are pregnant or post-partum 6 months, or who are receiving hospice care. 
 
4.2 Exclusion Criteria 
Providers will be excluded if they have fewer than 100 patients on their primary care panel or 
practice less than one session per week. These will be identified using data available from the 
primary care tableau dashboard and/or the baseline surveys.    
 
Patients will not directly receive intervention, but their clinical parameters will be used to identify 
eligible providers and upcoming visits with potential opportunities for treatment intensification. For 
this study, we plan to exclude patients age 80 and older. The SPRINT14 and HYVET15 trials 
enrolled patients aged ≥75 and ≥80 years respectively and demonstrated the safety and efficacy of 
blood pressure control to <130/80 or <150/80, suggesting that medication intensification in this age 
group is safe and effective. However, another recent trial of de-prescribing for patients >80 years 
with controlled BP on two or more medications was non-inferior to usual care,16 suggesting that 
medication de-escalation may also be appropriate for some patients. In both of these cases, 
patients who participated in these trials were selected by their physicians who had detailed 
knowledge of their clinical history and functional status. Because we will not be directly seeking 
PCP input on patients to include in this trial, and because blood pressure treatment decisions are 
more nuanced and individualized in this age range, we will exclude patients ≥80 years of age from 
this pilot study. 
 

 
Reduce clinical inertia in hypertension treatment          
Version 4 
PIs: Haff/Choudhry  
 
         October 11, 2022 
 
 
13 
 
4.3 Recruitment and retention 
We will send email invitations to eligible Primary Care Physicians in the MGH healthcare system. 
Based on preliminary data, we expect that 100 or more physicians will have at least 2 qualifying 
patients each and thus will be eligible for the study. Assuming approximately 50% of physicians will 
agree to participate, we expect to be able to recruit 45 physicians for the study. Our research team 
includes the Chief of the MGH Division of General Internal Medicine and Associate Medical Director 
of the Massachusetts General Physician Organization, who will help us achieve our enrollment 
targets and retention rates. 
 
Physicians will receive $75 for completion of the baseline surveys. After that time, physicians will 
receive the interventions and will be able to choose whether or not to incorporate that information 
into their routine clinical practice, but they will not be required to complete any additional study-
specific tasks. We expect that the compensation for their time and minimal study-specific tasks will 
help ensure retention. 
 
4.3.1 Informed consent considerations 
Potentially eligible physicians will be contacted by email and provided with an informational fact 
sheet. Physicians will then click a link to a RedCap form that will contain the same information in 
the fact sheet.  The fact sheet includes information about baseline questionnaires, potential study 
interventions (if randomly assigned to one of these arms), and potential for contact at the end of 
the study to participate in a semi-structured interview. We have allocated approximately 12 weeks 
for the process of recruitment and consent. 
 
4.3.2 Inclusivity of study subjects  
MGH primary care consists of over 200 PCPs who care for more than 200,000 patients across the 
Boston area. Based on preliminary data, we expect that 100 or more physicians will have at least 2 
qualifying patients each and thus will be eligible during the proposed study period. We expect that 
≥50% of the physicians will agree to participate and that therefore we will be able to recruit 45 
physicians for the study. Providers will be excluded if they have fewer than 100 patients on their 
primary care panel or practice less than one session per week. These will be identified using data 
available from the primary care tableau dashboard and/or the baseline surveys. The chief of the 
MGH Division of General Internal Medicine (DGIM), and the Director of Population Health and 

 
Reduce clinical inertia in hypertension treatment          
Version 4 
PIs: Haff/Choudhry  
 
         October 11, 2022 
 
 
14 
 
Quality for MGH DGIM are engaged in support of this project and will help with study recruitment and 
retention.  
 
5. Study Interventions 
5.1 Therapeutic areas 
The focus on the proposed study is uncontrolled hypertension treatment guidelines, defined based 
upon MGH hypertension treatment quality metrics.  
 
5.2 Study interventions 
Eligible physicians who agree to participate will be randomized to one of three treatment groups: 
• 
In arm 1 (academic e-detailing), we will first generate a list of patients who meet the 
definition for clinical inertia in hypertension care and have an upcoming visit with the PCP in 
the next few weeks. An MGH clinical pharmacist will then review each patient’s chart in 
advance and provide a personalized recommendation for how to modify the specific 
patient’s antihypertensive regimen based on clinical practice guidelines. For example, the 
clinical pharmacist might recommend adding an additional medication based on the 
patient’s comorbid conditions and could suggest a starting dose and timeframe for dose 
escalation. The academic e-detailing recommendations will be sent via an Epic in-basket 
message for each patient 1-3 days in advance of the patient’s scheduled visit. 
• 
In arm 2 (social norming), a report of the physician’s hypertension control rates compared 
to benchmarks will be displayed using principles of social norming.  The dashboards will be 
prepared using EHR data to calculate blood pressure control rates for each individual PCP 
and for his or her practice mean and practice top performer. Every Thursday, we will send 
each PCP a list of patients who meet the definition for clinical inertia in hypertension care 
and have an upcoming visit that week. Every 2-4 weeks, we will additionally attach the 
physician performance review dashboard. 
• 
In arm 3 (control), physicians will not receive outreach.  
5.3 Measures to minimize bias: randomization and blinding 
Physicians will be informed about the study and agree to participate using an online consent 
process through RedCap, and then will be asked to complete a set of behavioral surveys also 
administered through RedCap. PCPs will then be randomized to one of the two intervention arms 

 
Reduce clinical inertia in hypertension treatment          
Version 4 
PIs: Haff/Choudhry  
 
         October 11, 2022 
 
 
15 
 
or the control arm. To minimize imbalance between treatment groups, we will use block stratified 
randomization. Based on the number of sessions per week, providers will be determined to have a 
small (1-2 sessions), medium (3-4 sessions), or large (5 or more sessions) panel. Within each 
stratum, we will array physicians into blocks of 3 (note: could also be multiples of 3). All possible 
balanced combinations of assignment within the block will be allowed in each stratum. Ultimately, 
within each block and each stratum, physicians will have an equal probably of being assigned to 
one of the 3 arms. 
 
It will not be possible to blind physicians to the interventions, as they will directly receive either e-
consults, dashboards, or no intervention. Because physicians have individual panels, hypertension 
is typically treated via routine follow-up visits with the PCP, and the interventions are specific to 
each physician, risk of practice-level contamination is low.  
 
6. Study Assessments and Procedures 
6.1 
Baseline data 
We will collect baseline data using a combination of provider surveys and the EHR. From the 
provider surveys, we will collect physician age, gender, race/ethnicity, years in practice, practice 
location, and the behavioral scales detailed below. We will also collect data on providers from the 
EHR, including, but not limited to: hypertension prescribing trends (frequencies of medications 
utilized, BP control rates, time to treatment intensification) and information about the PCP’s panel 
such as panel size, demographic characteristics (e.g. age, gender, race/ethnicity), and clinical 
characteristics (e.g. comorbidities). We will also collect data specific to the patients who meet the 
definition for clinical inertia and whose visits are targeted by the interventions. This will include 
sociodemographic data, medical history and comorbidities, baseline resource utilization in prior 12 
months (i.e., number of visits), and biometric values (e.g., serum creatinine, systolic/diastolic blood 
pressures).  
 
The surveys that physicians will complete were selected to capture personality traits and 
behavioral tendencies that might contribute to clinical inertia or intervention responsiveness.  
These surveys will include measures of: 
• 
risk aversion (Physicians’ Reactions to Uncertainty Scale)17 
• 
long and short term orientation (Individual Cultural Values Scale)18 
• 
conscientiousness (Ten-Item Personality Inventory)19 

 
Reduce clinical inertia in hypertension treatment          
Version 4 
PIs: Haff/Choudhry  
 
         October 11, 2022 
 
 
16 
 
• 
need for cognition (Need for Cognition Scale)20 
• 
resistance to change (Resistance to Change Scale)21 
• 
susceptibility to social norms (Social-Norm Espousal Scale)22  
• 
burnout (Professional Fulfilment Index)23 
• 
automaticity (Self-Report Behavioural Automaticity Index).24  
6.2  Outcomes 
The primary outcome will be whether physicians intensified treatment at the visit targeted by the 
intervention. Intensification of treatment will include an increase in dose of an existing 
antihypertensive medication, adding an additional medication, or rotation of one medication to 
another that is stronger or more appropriate for the patient (e.g. changing hydrochlorothiazide to 
furosemide for a patient with chronic kidney disease). These will be measured using prescribing 
information from the EHR on the day of the patient’s visit. 
 
The secondary outcome will be the change in systolic blood pressure over 6-months of follow-up in 
each intervention arm compared to control. The initial value will be the systolic blood pressure at 
the time of enrollment that determined the patient’s eligibility for participation. The follow-up blood 
pressure will be the last blood pressure available in the EHR within 6 months after the visit targeted 
by the intervention. Based on prior studies in a similar local healthcare system, we anticipate 
approximately 20% missingness rate for the follow-up blood pressure within 6 months, and that this 
will likely be non-differential between treatment arms.25 Should there be sufficient missing data 
(e.g., >10%), we will use multiple imputation to handle this. In specific, we will use 20 imputations 
with Proc MI in SAS to impute any estimated values using fully conditional specification. Analyses 
will then be conducted on each imputed dataset and combined using Rubin’s rules.26 We will 
perform a complete case analysis as a sensitivity analysis. 
 
Each post-intervention interview will be moderated by trained study staff using a semi-structured 
interview guide that asks physicians about barriers to hypertension treatment intensification, 
perspectives on different intervention arms, and suggestions for improvement.  
 
We will use results from the physician interviews and study staff expertise to select variables for 
inclusion in the predictive modeling analysis. These variables will all be available in either the EHR 
or baseline physician surveys and will include, but are not limited to: physician age, gender, 

 
Reduce clinical inertia in hypertension treatment          
Version 4 
PIs: Haff/Choudhry  
 
         October 11, 2022 
 
 
17 
 
practice setting, baseline trends in hypertension prescribing, practice location, and patient case-
mix. We will also collect patient data that include but are not limited to: sociodemographic data, 
medical history and comorbidities, baseline resource utilization in prior 12 months (i.e., number of 
visits), and biometric values (e.g., serum creatinine, systolic/diastolic blood pressures).   
 
6.3 
Adverse events and unanticipated problems 
Oversight: 
Oversight of the pilot will be the responsibility of Drs. Haff and Choudhry, the Principal 
Investigators. 
 
The PIs and study team will meet on a regular basis throughout the study period and will be in 
direct contact with clinical leadership involved in the project to obtain ongoing feedback.  
 
De-identified study data will be accessible at all times for the MGH PI and coinvestigators to 
review, if applicable. We will also ensure that all protocol deviations for the pilot study are reported 
to the NIH and the IRB according to the applicable regulatory requirements. Compliance of 
regulatory documents and study data accuracy and completeness will be maintained through an 
internal study team quality assurance process. 
 
Definition: 
Adverse Event (AE): Any untoward or unfavorable medical occurrence in a human study 
participant, including any abnormal sign (e.g. abnormal physical exam or laboratory finding), 
symptom, or disease, temporally associated with the participants’ involvement in the research, 
whether or not considered related to participation in the research. 
• 
Adverse Events will be classified using the following rating scales: 
o Severity: Mild, Moderate or Severe 
• 
Mild: Awareness of signs or symptoms but are easily tolerated 
• 
Moderate: Events introduce a low level of inconvenience or concern but may 
interfere with daily activities but are usually improved by simple therapeutic 
measures. 
▪ 
Severe: Events interrupt the participants’ normal daily activities and 
generally require systemic drug therapy 
o Expectedness: Unexpected or Expected 

 
Reduce clinical inertia in hypertension treatment          
Version 4 
PIs: Haff/Choudhry  
 
         October 11, 2022 
 
 
18 
 
• 
Unexpected: nature or severity of the event is not consistent with the 
condition under study 
• 
Expected: event is known to be associated with the intervention or condition 
under study. 
Serious Adverse Event (SAE): Any adverse event that: 
• 
results in death 
• 
is life threatening, or places the participant at immediate risk of death from the event as it 
occurred 
• 
requires or prolongs hospitalization 
• 
causes persistent or significant disability or incapacity 
• 
results in congenital anomalies or birth defects 
• 
is another condition which investigators judge to represent significant hazards. 
Determination: 
Given the minimal risk nature of the study which aims to increase guideline concordant care for 
patients with persistently elevated blood pressures, we do not anticipate any SAEs or AEs. 
Patients’ own primary care physicians will have ultimate decision-making authority for prescribing 
choices, as they would in routine clinical practice, and we expect any adverse events related to 
hypertension medication intensification, such as hypotension or bradycardia, to be the same or 
less as those experienced in routine clinical care, given the focus on patients with clinical inertia. In 
the SPRINT14 trial, which tested intensive BP control among patients age 75 or older, similar rates 
of serious adverse events occurred in the intensive-treatment group and in the standard-treatment 
group. In this study, we are using standard blood pressure targets and include a younger patient 
sample who have persistently elevated blood pressure.  
 
Reporting: 
As previously described, any adverse events as part of this study are expected to be similar, or 
lower, than those anticipated in routine hypertension care. The study team will not be providing any 
direct care to patients and all treatment decisions will ultimately be made by the patients’ medical 
teams at Massachusetts General Hospital. Any adverse event will be handled in the course of 
regular clinical care. Because we are not directly intervening upon patients and will have no patient 
contact during this study, prospectively tracking adverse events is infeasible. However, physicians 
will have contact information for our research team to report any concerns, and we will be in 

 
Reduce clinical inertia in hypertension treatment          
Version 4 
PIs: Haff/Choudhry  
 
         October 11, 2022 
 
 
19 
 
regular contact with practice and DGIM leadership to monitor for any adverse events that come to 
attention through any of those channels. Therefore, while we will not be actively monitoring the 
occurrence of adverse events, which if done would require patient contact and detailed patient-
level chart-reviews, we anticipate that the study team will be informed of any AEs or SAEs that do 
occur. Daniel Horn, MD Director of Population Health and Quality for MGH DGIM and the Associate 
Medical Director of the Massachusetts General Physician Organization is engaged in support of this 
project and will help with monitoring of physician feedback that gets routed through traditional 
departmental channels.  
 
If we become aware of any AEs or SAEs throughout the course of the study, we will collect this 
information. Any reports of deaths will be submitted to the NIA Program Officer and to the Safety 
Officer (SO) within 24 hours. Any unexpected SAEs will be reported to the NIA PO, SO and the 
IRB within 48 hours of the study’s knowledge of the SAE. All other reported SAEs and AEs 
received by the study team will be reported to the NIA Program Officer and to the SO quarterly, 
unless otherwise requested by the Safety Officer or Roybal Center Program Data Safety 
Monitoring Board (DSMB). 
 
7. Statistical Considerations 
 
7.1  Statistical Hypotheses 
The null hypothesis is that rates of hypertension treatment intensification will be equal in each of 
the intervention groups when compared to control.  
 
7.2  
Sample size determination 
Because we are selecting specifically for patients with clinical inertia, we expect the control arm 
rate of medication intensification at the target office visit to be no more than 15%. Assuming an 
ICC of 0.05, a type I error rate of 5%, and 12 patients per physician over the study period, a 
sample size of 45 physicians (i.e. 15 per arm) will provide more than 80% power to detect a 15% 
difference in treatment intensification between each intervention group and control. If the control 
arm intensification rate is higher than anticipated, we will still be sufficiently powered for reasonable 
effect sizes (i.e. if the rate of the primary outcome in the control arm was 0.2%, we will be able to 
detect an effect size of 17%). These data are intended to provide pilot data for larger evaluations, 
and any positive signal from this pilot trial will help inform next steps. If we have more eligible and 

 
Reduce clinical inertia in hypertension treatment          
Version 4 
PIs: Haff/Choudhry  
 
         October 11, 2022 
 
 
20 
 
consented physicians than originally anticipated, we will adjust our allocation scheme so that 
additional physicians are allocated to the control arm to maximize power. 
 
7.3  
Statistical analyses 
7.3.1 Analysis of the primary endpoint 
The primary outcome of this trial will be whether physicians intensified treatment at the visit 
targeted by the intervention. These data will be collected through EHR data from MGB. We will 
evaluate the primary outcome using generalized estimating equations (GEE) to adjust for provider-
level clustering and multiple patient observations per physician with a logit link function and binary 
distributed errors; these models will also adjust for the block-randomized design. Because this is a 
randomized trial, our primary analyses are planned as unadjusted; however, if there are strong 
predictors of the outcomes not balanced by block randomization, we will adjust for these in the 
primary analyses. We will conduct analyses using intention-to-treat principles and each intervention 
arm will be compared to control. Given the nature of the data and how the outcome is being 
measured, there should not be missing values for our primary outcome. 
 
7.3.2 Analysis of secondary endpoints 
The secondary outcome of this trial is change in systolic blood pressure control in each 
arm over 6 months. For this secondary outcome, we will use GEE with an identity link 
function and normally-distributed errors to account for provider-level clustering, adjusting 
for the block-randomized design. As in the primary analysis, we will perform analyses 
unadjusted and adjusted for provider and patient-level covariates to accommodate any 
imbalance across arms. We will conduct analyses using intention-to-treat principles and 
each intervention arm will be compared to control. Based on prior studies in a similar local 
healthcare system, we anticipate approximately 20% missingness rate for the follow-up blood 
pressure within 6 months, and that this will likely be non-differential between treatment arms.25 
Should there be sufficient missing data (e.g., >10%), we will use multiple imputation to handle this. 
In specific, we will use 20 imputations with Proc MI in SAS to impute any estimated values using 
fully conditional specification. Analyses will then be conducted on each imputed dataset and 
combined using Rubin’s rules.26 We will perform a complete case analysis as a sensitivity analysis.    

 
Reduce clinical inertia in hypertension treatment          
Version 4 
PIs: Haff/Choudhry  
 
         October 11, 2022 
 
 
21 
 
 
7.3.3 Baseline descriptive analyses 
We will report the means and frequencies of baseline variables for physicians and their eligible 
patients. 
 
7.3.4 Subgroup analyses 
In subgroup analyses, we will explore whether there were any modifiers of the effects of the 
different intervention arms both using standard methods and predictive modeling. For example, we 
will explore whether providers that score highly on a measure of conscientiousness were more 
likely to respond to the social norming intervention, or if there were observable differences in 
patients who were less likely to receive treatment intensification, such as gender or race/ethnicity. 
 
7.3.5 Exploratory analyses 
Additional exploratory analyses will be performed based on predictive modeling analyses to 
develop a predictive model for responsiveness to each intervention.  
 
8. Ethical and regulatory requirements 
8.1 
Ethical conduct 
General oversight of the project by the principal investigators (Drs Haff and Choudhry) will occur 
throughout the study period, including regular contact with clinical leadership to obtain ongoing 
feedback. In addition, this protocol will undergo Institutional Review Board (IRB) evaluation by an 
institutional IRB. Study data will be accessible at all times for the principal investigators and co-
investigators to review, if applicable. The principal investigator will review study conduct (e.g., 
protocol deviations) on a monthly basis. The principal investigators will also ensure that all protocol 
deviations for the trials are reported to the NIH and the IRB according to the applicable regulatory 
requirements. 
 
We believe that the risks to participation for both physicians and patients are no more than minimal 
for several reasons. First, the interventions aim to emphasize guideline-recommended treatments 
for patients with persistently elevated blood pressure. Second, all treatment decisions will 
ultimately be made by licensed primary care physicians. Finally, the intervention is specifically 
physician-focused and delivered through interventions that use information already available to 

 
Reduce clinical inertia in hypertension treatment          
Version 4 
PIs: Haff/Choudhry  
 
         October 11, 2022 
 
 
22 
 
physicians. We believe there is no more than minimal risk involved to the physician subjects, as the 
physicians will simply be given tools to alter their behaviors towards guideline recommended care. 
All medical decisions are ultimately made by the physician. This trial will not interfere with the 
ordinary workings of the primary care practices.  
 
There is a small risk associated with altering hypertension medication prescribing, including 
hypotension, bradycardia, allergic reactions, and others. However, as noted above, in prior 
trials that increase intensification of blood pressure regimens, the risks have been similar in 
intervention and control arms. We believe the potential risks of treatment intensification as part 
of this trial are the same, or less than what is encountered during routine, guideline-concordant 
hypertension care, given the focus on patients with persistently elevated blood pressure. Final 
prescribing decisions will always be at the discretion of the patient’s PCP. 
 
The primary risk to patients will be privacy of health information. We will minimize the risk to 
privacy by taking appropriate steps to limit access to data to study investigators. Clinical data on 
the care for patients will be retrieved from the EHR. The data extracts obtained are continuously 
used by MGH clinical operations staff for quality assessment and improvement, and undergo 
routine, rigorous review by experienced data analysts to ensure accuracy and completeness. Dr 
Haff will work with the research project staff to ensure the accuracy of these data throughout the 
study period. For the purpose of conducting analyses of the study outcomes, this will involve 
creating scrambled patient and physician identifiers and sharing only limited Protected Health 
Information (PHI) with investigators for the purposes of analysis. All team members have received 
appropriate training in data privacy. 
 

 
Reduce clinical inertia in hypertension treatment          
Version 4 
PIs: Haff/Choudhry  
 
         October 11, 2022 
 
 
23 
 
8.2 
Informed consent 
This study involves enrolling physician-subjects and the use of routinely collected data from 
patient-subjects.  
Physician subjects: 
Physician subjects will be invited to participate via email.  A fact sheet will be attached to the email 
with information about the study, their participation, and the names and contact information for 
study staff who can be reached for a phone or video conversation if they have any questions or 
concerns.  In the email, if interested in participating, physicians will be asked to click on a link to 
open a secure RedCap survey.  There, physicians will again view an electronic copy of the fact 
sheet.  If the physician agrees to participate, he or she will click a button indicating “I agree”.  
The fact sheet will include information about baseline questionnaires, receipt of study interventions, 
and potential for contact at the end of the study to participate in a semi-structured interview. We 
will provide sufficient information to the prospective physician-subjects about the nature of the 
study and their rights. We will obtain IRB approval for all consent materials that are used.  
Physicians can keep the copy of the fact sheet in the invitation email for their records.  
 
For this consent process, we therefore request a waiver of documentation of informed consent for 
physician subjects in this study.  We feel this is appropriate for this study because it is minimal risk, 
the surveys and interventions are similar to existing quality initiatives for which physicians do not 
need to provide consent, physician subjects are knowledgeable about randomization and study 
design, and requiring a formal consent conversation with documentation would be a barrier to 
participation that would limit the sample size and generalizability of the study.   
 
Patient subjects: 
For use of routinely collected patient data, we request waiver of patient consent and HIPAA 
authorization.  We plan to use routinely collected EHR data to identify eligible providers, administer 
interventions, and assess study outcomes.  Because this is of minimal risk to patients, the study 
team will have no interaction with patients, and it would be impracticable to obtain patient consent, 
we feel that a waiver of consent and HIPAA authorization is needed for this study.  This is similar to 
what we have done in prior work. We believe this waiver is justified as investigators will have no 
direct patient contact and all prescribing decisions are made under the care of licensed physicians. 

 
Reduce clinical inertia in hypertension treatment          
Version 4 
PIs: Haff/Choudhry  
 
         October 11, 2022 
 
 
24 
 
Finally, the goal of this project is to improve existing decision support for hypertension control, 
consistent with MGH-specific professional guidelines and quality metrics. Therefore, the 
intervention is exclusively provider-facing with the underlying goal of promoting chronic disease 
management in accordance with widely adopted clinical practice guidelines.  
 
8.3  Confidentiality and privacy 
This study involves physician subjects who will receive the study interventions and data from 
physicians and patients. We believe that the risks to participation are no more than minimal. The 
primary risk to patients will be privacy of health information. We will minimize this risk as follows: 
 
For Aim 1, we request a HIPAA waiver of patient authorization to access the EHR data necessary 
for study completion. 
 
For Aim 2, all interviews will take place on a secure MGB Zoom platform. Only audio will be 
recorded from the interviews and will be used to generate transcriptions which will be de-identified. 
The data will be securely stored in a manner determined by the IRB, and audio recordings will be 
destroyed after study completion.    
 
Data for the study will be safeguarded by state-of-the-art security protocols. The facilities have 24-
hour security and are protected by locked entrances. MGB has computer networks in place that 
employ up to date virus protection software and enable password protected access only to study 
investigators. The setup for analysis of these data will be the same as all the other IRB applications 
that our MGB research division submits for secondary use of data. All the datasets, including 
limited protected health information (PHI), will be stored only on secure servers at MGB’s data 
center and will only be accessed by a limited number of individuals in the study team from this 
division who are all trained in data security and patient privacy.  
 
To ensure the confidentiality and security of all data, the research team operates a secure, state-
of-the-art computing facility housed at MGB’s data center. The MGB data center is a secure facility 
that houses both computing environments as well as clinical systems and electronic medical 
records for several large hospitals in Eastern Massachusetts. Entry into the computer room 
requires staffed computer room security. The Division’s computers are connected to the MGB 
networking backbone with 10 gigabit-per-second fiber links. Network security is overseen by 

 
Reduce clinical inertia in hypertension treatment          
Version 4 
PIs: Haff/Choudhry  
 
         October 11, 2022 
 
 
25 
 
electronic medical records systems to the research team’s data. All data are transmitted to 
programmers’ workstations in an encrypted state. Backups are created using 256-bit AES 
encryption, the current Department of Defense standard for data security, and are stored in a 
locked facility. The redundancy, extensive data power, and security of our computer facility confirm 
our capacity to collect and manage data and ensure confidentiality for all project participants. 
 
We will also safeguard any identifiable information from the physicians in accordance with IRB 
practices, limit access to any information in accordance with IRB practices, limit access to the 
information to study investigators actively involved in the research who have all undergone human 
subjects research training, and destroy any recordings from the qualitative interviews upon 
completion of the research.  
 
All members of the research team have completed or will complete appropriate human subjects 
research training and patient privacy training related to the Health Insurance Portability and 
Accountability Act (HIPAA). The setup for analysis of these HIPAA-limited data will be exactly the 
same as all of the other IRB applications that our MGB research division submits for secondary use 
of data. All of the datasets, including limited PHI, will be stored only on secure servers at the MGB 
data center and will only be accessed by a limited number of individuals in the study team from this 
division who are all trained in data security and patient privacy.  
 
8.4 
Safety oversight 
General oversight of these particular projects by the PIs (Dr. Haff and Choudhry) will occur 
throughout the study period, including regular contact with clinical primary care leadership to obtain 
ongoing feedback. In addition, this protocol will undergo Institutional Review Board (IRB) 
evaluation. Our trial has been registered with clinicaltrials.gov. 
 
We will have oversight from both the NIA Director-approved Roybal Centers Program Data Safety 
Monitoring Board (DSMB) and a Program Officer-approved independent Safety Officer (SO) for all 
aspects of this research. The DSMB will act in an advisory capacity to the NIA to monitor 
participant safety, evaluate the progress of the study, and review procedures and management of 
the study. The SO will provide the Program DSMB with periodic safety reports. Our plan for data 
and safety monitoring also includes oversight by the project principal investigators (Drs. Choudhry 
and Haff) throughout the study period.  

 
Reduce clinical inertia in hypertension treatment          
Version 4 
PIs: Haff/Choudhry  
 
         October 11, 2022 
 
 
26 
 
 
Meetings of the DSMB will be held regularly (e.g., every six to nine months) at the call of NIA or the 
DSMB Chair and review data related to study protocols and ensure protection of patient 
confidentiality and safety. At each meeting, the DSMB will make recommendations as to whether 
the studies should continue or if changes to the protocol are necessary for continuation. The 
DSMB will also review periodic safety reports from SO, as needed. This trial has been registered 
with clinicaltrials.gov.  
 
8.5 Benefit risk assessment 
8.5.1 Known potential risks 
We believe there is no more than minimal risk involved to the physician subjects, as the physicians 
will receive interventions designed to help with the provision of guideline-concordant hypertension 
care. In terms of patient-subjects, all medical decisions are ultimately made by the physician. This 
trial will otherwise not interfere with the usual workings of primary care practices.  
 
8.5.2 Known potential benefits 
Social norming and academic e-detailing interventions could help reduce clinical inertia in 
managing chronic hypertensive patients. Thus, the research could have both immediate benefits 
for physicians by increasing hypertension awareness and treatment knowledge, as well as for their 
patients who might benefit from improved blood pressure control. 
 
8.5.3 Assessment of potential risks and benefits 
We will enroll physician-subjects based on their being employed by MGB. We will provide 
physicians with information about the study and they can choose whether or not to participate. We 
also request a HIPAA waiver of patient authorization to access the EHR data necessary for 
outcome evaluation.  
 
To protect against the risk of inappropriate disclosure of personal health information, the 
investigators at MGH will only access study data with encrypted identifiers. As described, all 
members of the research team have completed or will complete appropriate human subjects 
research training and patient privacy training related to the Health Insurance Portability and 
Accountability Act (HIPAA). We have a history of collaborative evaluations with delivery 

 
Reduce clinical inertia in hypertension treatment          
Version 4 
PIs: Haff/Choudhry  
 
         October 11, 2022 
 
 
27 
 
organizations that involves transfer of the minimum data necessary to complete rigorous 
evaluations, involving the use of encrypted identifiers to ensure patient confidentiality.  
 
To ensure the confidentiality and security of all data, the research team operates a secure, state-
of-the-art computing facility housed at MGB’s data center. The MGB data center is a secure facility 
that houses both computing environments as well as clinical systems and electronic medical 
records for several large hospitals in Eastern Massachusetts. Entry into the computer room 
requires staffed computer room security. The Division’s computers are connected to the MGB 
networking backbone with 10 gigabit-per-second fiber links. Network security is overseen by 
electronic medical records systems to the research team’s data. All data are transmitted to 
programmers’ workstations in an encrypted state. Backups are created using 256-bit AES 
encryption, the current Department of Defense standard for data security, and are stored in a 
locked facility. The redundancy, extensive data power, and security of our computer facility confirm 
our capacity to collect and manage data and ensure confidentiality for all project participants.  
 
We will also safeguard any identifiable information from the physicians in accordance with IRB 
practices, limit access to any information in accordance with IRB practices, and limit access to the 
information to study investigators actively involved in the research who have all undergone human 
subjects research training. 
 
9. List of references 
REFERENCES 
1.  
Heart Disease and Stroke Statistics—2019 Update: A Report From the American Heart 
Association | Circulation. Accessed February 20, 2020. 
https://www.ahajournals.org/doi/10.1161/CIR.0000000000000659 
2.  
Phillips LS, Branch WT, Cook CB, et al. Clinical Inertia. Ann Intern Med. 2001;135(9):825. 
doi:10.7326/0003-4819-135-9-200111060-00012 
3.  
Lebeau J-P, Cadwallader J-S, Aubin-Auger I, et al. The concept and definition of 
therapeutic inertia in hypertension in primary care: a qualitative systematic review. BMC 
Fam Pract. 2014;15(1):130. doi:10.1186/1471-2296-15-130 
4.  
Berlowitz DR. Clinical inertia and the 2017 ACA/AHA guideline. J Clin Hypertens. 
2018;20(10):1392-1394. doi:10.1111/jch.13373 
5.  
Milman T, Joundi RA, Alotaibi NM, Saposnik G. Clinical inertia in the pharmacological 
management of hypertension. Medicine (Baltimore). 2018;97(25). 
doi:10.1097/MD.0000000000011121 

 
Reduce clinical inertia in hypertension treatment          
Version 4 
PIs: Haff/Choudhry  
 
         October 11, 2022 
 
 
28 
 
6.  
Lebeau J-P, Cadwallader J-S, Vaillant-Roussel H, et al. General practitioners’ 
justifications for therapeutic inertia in cardiovascular prevention: an empirically grounded 
typology. BMJ Open. 2016;6(5). doi:10.1136/bmjopen-2015-010639 
7.  
Pronin E. Chapter 1 The Introspection Illusion. In: Advances in Experimental Social 
Psychology. Vol 41. Academic Press; 2009:1-67. doi:10.1016/S0065-2601(08)00401-2 
8.  
Pronin E, Kugler MB. Valuing thoughts, ignoring behavior: The introspection illusion as a 
source of the bias blind spot. J Exp Soc Psychol. 2007;43(4):565-578. 
doi:10.1016/j.jesp.2006.05.011 
9.  
Oettingen G, Grant H, Smith PK, Skinner M, Gollwitzer PM. Nonconscious goal pursuit: 
Acting in an explanatory vacuum. J Exp Soc Psychol. 2006;42(5):668-675. 
doi:10.1016/j.jesp.2005.10.003 
10.  Fiscella K, Volpe E, Winters P, Brown M, Idris A, Harren T. A novel approach to quality 
improvement in a safety-net practice: concurrent peer review visits. J Natl Med Assoc. 
2010;102(12):1231-1236. doi:10.1016/s0027-9684(15)30778-1 
11.  Perl S, Riegelnik V, Mrak P, et al. Effects of a multifaceted educational program on blood 
pressure and cardiovascular risk in hypertensive patients: the Austrian herz.leben project. 
J Hypertens. 2011;29(10):2024-2030. doi:10.1097/HJH.0b013e32834aa769 
12.  Huebschmann AG, Mizrahi T, Soenksen A, Beaty BL, Denberg TD. Reducing Clinical 
Inertia in Hypertension Treatment: a Pragmatic Randomized Controlled Trial. J Clin 
Hypertens Greenwich Conn. 2012;14(5):322-329. doi:10.1111/j.1751-7176.2012.00607.x 
13.  Lüders S, Schrader J, Schmieder RE, Smolka W, Wegscheider K, Bestehorn K. 
Improvement of hypertension management by structured physician education and 
feedback system: cluster randomized trial. Eur J Cardiovasc Prev Rehabil Off J Eur Soc 
Cardiol Work Groups Epidemiol Prev Card Rehabil Exerc Physiol. 2010;17(3):271-279. 
doi:10.1097/HJR.0b013e328330be62 
14.  A Randomized Trial of Intensive versus Standard Blood-Pressure Control. N Engl J Med. 
2015;373(22):2103-2116. doi:10.1056/NEJMoa1511939 
15.  Beckett NS, Peters R, Fletcher AE, et al. Treatment of Hypertension in Patients 80 Years 
of Age or Older. N Engl J Med. 2008;358(18):1887-1898. doi:10.1056/NEJMoa0801369 
16.  Sheppard JP, Burt J, Lown M, et al. Effect of Antihypertensive Medication Reduction vs 
Usual Care on Short-term Blood Pressure Control in Patients With Hypertension Aged 80 
Years and Older: The OPTIMISE Randomized Clinical Trial. JAMA. 2020;323(20):2039-
2051. doi:10.1001/jama.2020.4871 
17.  Gerrity MS, White KP, DeVellis RF, Dittus RS. Physicians’ Reactions to Uncertainty: 
Refining the constructs and scales. Motiv Emot. 1995;19(3):175-191. 
doi:10.1007/BF02250510 

 
Reduce clinical inertia in hypertension treatment          
Version 4 
PIs: Haff/Choudhry  
 
         October 11, 2022 
 
 
29 
 
18.  Yoo B, Donthu N, Lenartowicz T. Measuring Hofstede’s Five Dimensions of Cultural 
Values at the Individual Level: Development and Validation of CVSCALE. J Int Consum 
Mark. 2011;23(3-4):193-210. doi:10.1080/08961530.2011.578059 
19.  Gosling SD, Rentfrow PJ, Swann WB. A very brief measure of the Big-Five personality 
domains. J Res Personal. 2003;37(6):504-528. doi:10.1016/S0092-6566(03)00046-1 
20.  Lins de Holanda Coelho G, H. P. Hanel P, J. Wolf L. The Very Efficient Assessment of 
Need for Cognition: Developing a Six-Item Version. Assessment. Published online August 
10, 2018:1073191118793208. doi:10.1177/1073191118793208 
21.  Oreg S. Resistance to change: Developing an individual differences measure. J Appl 
Psychol. 2003;88(4):680-693. doi:10.1037/0021-9010.88.4.680 
22.  Bizer GY, Magin RA, Levine MR. The Social-Norm Espousal Scale. Personal Individ 
Differ. 2014;58:106-111. doi:10.1016/j.paid.2013.10.014 
23.  Trockel M, Bohman B, Lesure E, et al. A Brief Instrument to Assess Both Burnout and 
Professional Fulfillment in Physicians: Reliability and Validity, Including Correlation with 
Self-Reported Medical Errors, in a Sample of Resident and Practicing Physicians. Acad 
Psychiatry. 2017;42. doi:10.1007/s40596-017-0849-3 
24.  Gardner B, Abraham C, Lally P, de Bruijn G-J. Towards parsimony in habit measurement: 
Testing the convergent and predictive validity of an automaticity subscale of the Self-
Report Habit Index. Int J Behav Nutr Phys Act. 2012;9(1):102. doi:10.1186/1479-5868-9-
102 
25.  Choudhry NK, Isaac T, Lauffenburger JC, et al. Effect of a Remotely Delivered Tailored 
Multicomponent Approach to Enhance Medication Taking for Patients With 
Hyperlipidemia, Hypertension, and Diabetes: The STIC2IT Cluster Randomized Clinical 
Trial. JAMA Intern Med. Published online August 6, 2018. 
doi:10.1001/jamainternmed.2018.3189 
26.  Newgard CD, Lewis RJ. Missing Data: How to Best Account for What Is Not Known. 
JAMA. 2015;314(9):940-941. doi:10.1001/jama.2015.10516