Pragmatic Trial Comparing Telehealth Care and Optimized Clinic-Based Care for Uncontrolled High Blood Pressure
Phase: NA
Conditions: Hypertension
Sponsor: HealthPartners Institute

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Pragmatic Trial Comparing Telehealth Care and Optimized Clinic-Based Care for Uncontrolled High Blood Pressure 
Short Title: Hyperlink 3 (15-103) 
PCORI Award IHS-150731146 
HealthPartners Institute, PI Dr. Karen Margolis 
VERSION 2018.07 
STUDY PROTOCOL 
1.
Background and Significance .......................................................................................................3 
1.A.  Background ................................................................................................................................................................ 3 
1.B.  Significance ................................................................................................................................................................. 5 
2.
Objectives ..................................................................................................................................7 
2.A. Aim 1 ........................................................................................................................................................................... 7 
2.B. Aim 2 ............................................................................................................................................................................ 7 
3.
Study Design ..............................................................................................................................7 
4.
Study Population ........................................................................................................................8 
4.A. Setting ......................................................................................................................................................................... 8 
4.B. Recruitment and randomization of clinics ................................................................................................................. 8 
4.C. Inclusion and exclusion criteria .................................................................................................................................. 8 
4.D. Enrollment of patients ................................................................................................................................................ 9 
5.
Interventions ............................................................................................................................ 10 
5.A. Best Practice Clinic-Based care ................................................................................................................................. 10 
5.A.1. Current infrastructure and policies ................................................................................................................... 10 
5.B. Telehealth care .......................................................................................................................................................... 11 
6.
Training .................................................................................................................................... 14 
7.
Outcomes ................................................................................................................................. 15 
7.A. Primary Aim 1 outcome ............................................................................................................................................ 15 
7.B. Secondary Aim 1 outcomes ...................................................................................................................................... 15 
7.C. Aim 1 other outcomes ............................................................................................................................................... 16 
7.D. Aim 2 outcomes ........................................................................................................................................................ 16 
8.
Measurements ......................................................................................................................... 16 
8.A. EHR for clinical measures ......................................................................................................................................... 16 
8.B. Patient Survey for patient-reported outcomes ....................................................................................................... 17 
9.
Evaluation Reporting ................................................................................................................ 17 
10. Analysis .................................................................................................................................... 17 
10.A Aim 1 Primary and Secondary Analyses .................................................................................................................. 18 
10.B. Aim 2 Analysis Plan. ................................................................................................................................................ 22 

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10.C. Reporting Plan (IR-6). .............................................................................................................................................. 23 
11. Data Management .................................................................................................................... 23 
12. Key Milestones and Timeline .................................................................................................... 24 
12.A. Study Start-up ......................................................................................................................................................... 24 
12.B. Enrollment and Interventions ................................................................................................................................ 24 
12.C. Key reporting milestones ........................................................................................................................................ 24 
12.D. Publication and Dissemination ............................................................................................................................... 24 
13. Organization ............................................................................................................................. 25 
14. Human Subjects Protection ......................................................................................................... 26 
14.A. Protected Health Information and sources of data ............................................................................................... 26 
14.B. Potential risks to subjects ....................................................................................................................................... 27 
14.C. Adequacy of Protection Against Risks .................................................................................................................... 27 
14.D. Potential Benefits of the Proposed Research to Human Subjects and Others ..................................................... 30 
14.E. Importance of Knowledge to be Gained................................................................................................................. 30 
14.F. Inclusion and accessibility ....................................................................................................................................... 30 
15. Data and Safety Monitoring Plan – Approved by DSMB April 17, 2017 ........................................ 31 
1. 
Clinic recruitment, randomization and characteristics of clinics .............................................................................. 31 
2. 
Patient enrollment/accrual ....................................................................................................................................... 32 
3. 
Intervention implementation ................................................................................................................................... 33 
4. 
Patient outcomes and safety monitoring ................................................................................................................. 33 
16. Publication and Dissemination .................................................................................................. 36 
16.A. PCORI Publication Policy......................................................................................................................................... 36 
16.B. Key Journal Publication Milestones. ...................................................................................................................... 36 
16.C. Making Research Findings Publicly Available. ....................................................................................................... 36 
16.D. In-Person Presentation(s) and Other PCORI-Initiated Events. .............................................................................. 37 
16.E. Manuscript development and authorship. ............................................................................................................ 37 
17. References ............................................................................................................................... 38 
 
 
Supplemental appendices compiled in separate document, saved here: x Protocol - appendix attachments\2017.11 
Hyperlink 3 Protocol Appendices.pdf  

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1. Background and Significance 
1.A.  Background 
1.A.1. Impact of the condition on the health of individuals and populations. Abnormally high blood pressure 
(hypertension) is the most common chronic condition for which patients see primary care physicians, affecting 80 
million (about one in three) U.S. adults, and is a major risk factor for heart attacks, stroke, heart failure, and kidney 
failure.1 The estimated direct and indirect cost of high blood pressure (BP) in 2011 in the U.S. was $46.4 billion. 
Compared with other modifiable cardiovascular (CV) risk factors, poorly controlled hypertension is the leading cause of 
death among women and the second leading cause of death among men after smoking.2 About half of patients with 
hypertension in the U.S. do not have their BP controlled to recommended levels, and control rates are even lower in 
racial/ethnic minority and low socioeconomic status populations.3-6 Attaining BP control to recommended levels has 
been shown to lower the risk of future CV events (heart attacks and strokes), the most common global cause of death 
and disability.1  
1.A.2. Previous research and gaps in evidence addressed by the proposed trial. National data from 2003-2012 has 
shown some improvement in the control of hypertension to just over 50%,3-6 well below the goals set by Healthy People 
2020 (61.2% by 2020), the Million Hearts Initiative (65% by 2017), and the American Medical Group Association Measure 
Up/Pressure Down campaign (80% by 2016).7-9 Although access to health care remains a barrier to attaining control, 
recent evidence suggests that 89% of people with uncontrolled hypertension have a regular source of health care, and 
85% had insurance.3 Although high BP usually doesn’t have symptoms, more than 80% of people with hypertension are 
aware they have it, and men, women, and Hispanic and black Americans all had awareness levels above 80%.5 Similarly, 
most patients with hypertension are being treated with medication (76%). There is currently little difference in 
treatment rates by race/ethnicity, although more women (81%) than men (71%) are treated. Patients with hypertension 
visit a physician, on average, 4 or more times a year,10 which should provide ample opportunity to detect and address 
uncontrolled hypertension. However, clinicians are often slow to start antihypertensive drugs or increase treatment 
intensity with higher doses and combinations of drugs, even when BP is elevated at several clinic visits, a complex 
phenomenon dubbed “clinical inertia.”11 Patients also contribute by resisting advice to change their lifestyle, start 
medication, or take their medication as prescribed. Sometimes this resistance is related to stressful lives, side effects, 
medication costs, or not being convinced that their BP is a problem.12-14  
Thus, while improving access to care, awareness of hypertension and initiation of treatment for hypertension are 
important, addressing these factors in isolation is likely to result only in small improvements in hypertension control. 
Rather, the best current opportunities to improve BP control center on the way clinicians and patients interact in the 
health care setting. Research over the last several decades has shown that the most potent interventions are those that 
reorganize clinical practice to empower non-physician practitioners and patients to work together to encourage self-
management, adjust antihypertensive therapy, and conduct follow up in a team-based approach to hypertension care.15-
18 In a 2006 meta-analysis of 28 studies, most of which included a nurse or a pharmacist team member as a care 
manager, average BP dropped by 10/4 mm Hg, and the absolute proportion of patients achieving BP control improved 
by 20%.15 The largest BP effects were seen in studies in which the care manager was able to recommend treatment 
changes without further direct action by the physician. A recently updated meta-analysis including 31 additional studies 
confirmed these findings, albeit with somewhat smaller BP reductions (5/2 mm Hg, proportion achieving BP control 
improved by 12%).19 However, several of the studies included in the meta-analysis also suggested that team-based care 
for hypertension may simultaneously reduce cholesterol levels and improve blood sugar control in adults with diabetes, 
thus reducing long-term CV risk even further than would be achieved based on BP reductions alone. A modeling study 

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found that nationwide adoption of team-based care for uncontrolled hypertension could reduce uncontrolled 
hypertension by 13% and prevent 638,000 CV events over 10 years. 20 Based on this strong evidence, the Community 
Preventive Services Task Force recommended team-based care to improve BP control.21 A key research gap identified in 
this systematic review was the need for more evidence on scalability of team-based care in large and diverse 
populations, multiple sites, and multiyear evaluations. In addition, few studies have measured patient-reported 
outcomes of team-based care, and the results of such measurements have been inconsistent.19 
Self-measured home BP monitoring has been identified as a useful, cost-saving adjunct to team-based care for 
hypertension in comprehensive evidence reviews.15,16,22-26 A recent systematic review concluded that home BP 
monitoring alone results in small BP reductions at 6 months compared with usual care (a difference of -3 mm Hg for 
systolic BP [SBP, the top number]  and  -2 mm Hg for diastolic BP [DBP, the bottom number]). In contrast, improved BP 
outcomes were greater in high-quality studies that combined home BP monitoring with additional support interventions 
for as long as 12 months (SBP reductions of  -3.4 to -8.9 mm Hg, DBP reductions of -1.9 to -4.4 mm Hg).27 Additional 
support was defined as patient education, counseling, or telemedicine support. An individual patient data meta-analysis 
conducted by members of this research team reached similar conclusions.28 The biggest research gaps identified were 
the need to determine the long-term effects of home BP monitoring beyond 12 months and in key subgroups that are 
more likely to have difficulty with BP control (eg, older persons, those with more severe hypertension, those with CV 
disease, diabetes, or kidney disease).  
Both patients and health care organizations are increasingly interested in alternatives to traditional clinic visits. Home BP 
monitoring is an essential ingredient for such alternatives for hypertension care. Our previous work on the Hyperlink 
study (R01 HL090965) used telemonitoring and telephone for communication between patients and pharmacists based 
in primary care clinics. Patients with uncontrolled hypertension in the intervention group safely achieved double the rate 
of sustained BP control compared with patients who continued to receive routine primary care.29 Previous research in 
other care settings has shown similar improvement in BP control without the need for clinic visits.30-33 However, some 
group practices have achieved very high rates of BP control using quality-improvement methods without routine use of 
home BP monitoring, telehealth, or expanded care teams.34,35 Thus, it is unclear whether these improve care for 
uncontrolled hypertension compared with clinic-based care that is organized according to current best practices.  
National strategic planning groups for comparative effectiveness studies have identified the research gaps noted above 
as high priority topics. The Institute of Medicine has called for studies comparing the effectiveness of various strategies 
aimed at integrating pharmacists into primary care (eg, pharmacist-provided medication management to improve 
condition-specific outcomes).36 The Agency for Healthcare Research and Quality has cited self-measured BP as a topic 
needing future research, specifically calling for longer-term randomized controlled trials to examine clinical outcomes, 
identify subgroups likely to benefit, and clarify what types of additional support are most effective.37  
This pragmatic trial is aimed at improving hypertension care in a large health system and will address these research 
gaps by: 1) Comparing two different organizational models for team-based care, one that incorporates current best 
practices but relies primarily on the physician-medical assistant dyad and face-to-face visits (clinic-based care) and one 
that extends team-based care outside the confines of the clinic by adding telehealth care coordinated by a pharmacist 
(telehealth care). 2) Incorporating self-measured home BP telemonitoring as a systematic part of the telehealth care 
intervention in a long-term evaluation that is large enough to determine its effects in key subgroups. 3) Measuring 
patient-centered outcomes as well as traditional clinical outcomes (eg, BP, other CV risk factors). 4) Measuring and 
evaluating the implementation of a pragmatic, large-scale, long-term program of clinic-based care and telehealth care 
for patients with uncontrolled hypertension in the primary care setting using electronic data sources. 

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1.B.  Significance  
1.B.1. Potential for the study to improve health care and outcomes. This study will compare the clinical effectiveness 
and effects on patient-reported outcomes of two different models of team-based care for uncontrolled hypertension 
and study how the interventions are implemented in the real-world setting of a large health system. A large body of 
evidence from both observational and interventional studies has shown that even small reductions in BP result in 
substantial reductions in rates of heart disease and stroke. The estimated effect of  lowering BP by 5 mm Hg diastolic 
reduces the relative risk of stroke by 34% and heart disease by 21%38 and stroke deaths by 40% and vascular disease 
deaths by 30%.39 Even SBP and DBP reductions as small as 2-3 mm Hg are predicted to reduce stroke by 10%-28% and 
heart disease by 5%-9%.39-42 
Numerous stakeholders have endorsed the need to improve hypertension care in the primary care setting, where most 
patients receive care. “Controlling high blood pressure” is a key national quality measure in the Healthcare Effectiveness 
Data and Information Set (HEDIS). This measure is publicly reported in Minnesota for all medical groups and published 
on the Minnesota Community Measurement Web site.35 Practice-based quality measures generally show higher levels of 
BP control than national levels because they include only diagnosed patients receiving care in the previous 2 years. 
These are useful for assessing important variations in practice. For example, in the state of Minnesota for 2015 dates of 
service, the average publicly reported rate of meeting recommended goals for hypertension control by all reporting 
medical groups is 77%, but individual medical groups range from 37% to 91%. HealthPartners clinics fell in the average 
range, at 75%, and also show substantial between-clinic variation. There is an 8% gap in BP control rates between white 
and black patients (unpublished data). The primary care, nursing, and pharmacy departments, each represented in this 
project as stakeholders, convened a working group to redesign primary care systems to improve hypertension control 
and make care more consistent. Our group faced uncertainty about the best methods to improve BP outcomes in clinical 
practice, a dilemma likely shared by many others. 
1.B.2. Evidence for efficacy or effectiveness of the interventions being compared 
1.B.2.1. Best practice clinic-based care. The clinic-based care approach we adapted for this project is based on elements 
from several programs that have been shown to be effective in other settings, albeit based mostly on observational 
evidence. Kaiser Permanente’s hypertension program was gradually implemented over more than a decade in Northern 
and Southern California and includes the following key elements: use of evidence-based guidelines, a comprehensive 
hypertension registry, regular measurement and feedback on performance metrics, medical assistant visits for BP 
measurement, and promotion of a simple treatment algorithm based on single-pill combination pharmacotherapy.34,43,44 
This program was associated with improvement in hypertension control, according to the HEDIS measurement, from 
44% in 2001 to 80% in 2009 in Northern California and from 54% in 2004 to 86% in 2012 in Southern California. Racial, 
ethnic, and language disparities in BP control were reduced. There was much less concomitant improvement in 
hypertension control in California at non-Kaiser practices (63.4% to 69.4%) and nationally (55.5% to 64.1%) during the 
same period. 
Other groups have put forth similar recommendations for reorganizing clinic-based hypertension care: the American 
Medical Association’s STEPSforward program for clinical practice redesign,45 the American Medical Group Association’s 
Measure Up/Pressure Down campaign,46 and the Million Hearts program for controlling hypertension.47 Key elements 
include: 1) promotion of accurate BP measurement; 2) repeat measurement when BP is elevated; 3) addressing elevated 
BP at every visit; 4) use of an evidence-based standardized protocol, including low-cost medications and single-pill 
combination therapy, when possible; 5) reassessing the patient every 2 to 4 weeks until BP is controlled; and 6) 
partnering with patients and families to improve self-monitoring, adherence, and lifestyle changes. Registries are also 
considered an important component to track patients over time and between visits. Consistency with guidelines from 

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other national organizations suggests that these constitute current best practices for clinic-based care.48-50 However, 
most of the individual elements of the recommendations are based on expert opinion, and even the well-publicized 
Kaiser model results are based on observational studies. Therefore, the evidence for best-practice clinic-based care 
would be strengthened greatly by comparing it to another care model using a rigorous research design.  
1.B.2.2. Telehealth Care.  We and others have found nurse- or pharmacist-led telehealth care with home BP monitoring 
to be a particularly effective intervention for lowering BP in patients with uncontrolled hypertension.51 A recent study 
among U.S. veterans compared a telemonitoring intervention with various types of nurse management to usual care.31 
The largest effect was observed for combined behavioral and medication management in patients with uncontrolled BP 
(SBP was 15 mm Hg lower at 12 months and 8 mm Hg lower at 18 months than control). In 387 urban African-Americans 
with uncontrolled BP randomly assigned to community nurse-managed telemonitoring or usual care, intervention group 
patients had a 5 mm Hg greater reduction in SBP at 12 months.52 A trial conducted in UK primary care practices included 
automated text messages or email as part of a home BP telemonitoring intervention.53 BP was 4/2 mm Hg lower in the 
intervention patients than in the usual care patients after 6 months. In another recent study conducted in a managed 
care setting, patients randomly assigned to home BP telemonitoring combined with pharmacist-led care had greater 
reductions in SBP (-21 mm Hg) than usual care (-8 mm Hg) over a 6-month intervention period.30  
Two randomized trials conducted by members of this research team also strongly support combining telehealth care 
with home BP self-monitoring and management support by pharmacists. Margolis, et al conducted a cluster-randomized 
trial at HealthPartners comparing pharmacist-led care management plus home BP telemonitoring with usual primary 
care in 450 patients with uncontrolled hypertension.29 Unlike many previous studies, there were few exclusion criteria, 
and patients with a broad range of comorbidities and hypertension severity were enrolled. The intervention patients had 
an 11/6 mm Hg greater drop in BP than the usual care patients at 6 months (P<0.001), and a much higher proportion 
had controlled BP (72% vs. 45%, P<0.001). The improved BP results were sustained with less intensive pharmacist 
contact at 12 months and 18 months (6 months after the intervention ended). A trial by Green, et al in a managed care 
setting used secure email messaging to send home BP data to pharmacists for 12 months.33 The intervention group had 
lower BP (14/7 mm Hg vs. 5/4 mm Hg, P<0.001) and better BP control (56% vs. 31%, P<0.001) than usual care. 
The effect of telehealth care on patient-centered outcomes is much less well-studied than BP outcomes. A qualitative 
analysis of the UK trial of telemonitoring with automated patient decision support found that intervention patients and 
clinicians felt more confident in treatment decisions based on home BP. Before the intervention, they were hesitant to 
increase medication based on BP measurements taken on a single day in the clinic.54 Conversely, they perceived that 
multiple telemonitoring measurements were more accurate, were difficult to ignore, and led to action. In the previous 
study at HealthPartners, the intervention was associated with significant improvements in patient satisfaction with 
aspects of their care (clinicians listening carefully, explaining things clearly, and respecting what the patients said).29 
Patients also reported feeling more able to communicate with their health care team, to incorporate home BP 
monitoring into their routine, and to keep their BP under control. In the study by Green, patients who worked with 
pharmacists reported strong and consistent improvements in the way their care reflected principles outlined for high-
quality chronic illness care.55  
Members of the investigator team for this proposal have conducted a meta-analysis and computer-model simulation to 
predict outcomes of team-based care for hypertension in large populations. This suggests sizable potential for benefit of 
interventions for uncontrolled hypertension that include a pharmacist or nurse who can adjust medications, provide 
education and counseling on adherence and lifestyle, and support self-management.  Based on data from 30 studies, 
these interventions led to, on average, a reduction of SBP of about 8 mm Hg, reductions in LDL-cholesterol (“bad” 
cholesterol) by about 12 mg/dL, and increases in HDL-cholesterol (“good” cholesterol) by about 1 mg/dL.20 The analysis 

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showed that, over 10 years, widespread adoption of this type of team-based care would reduce the number of persons 
with uncontrolled hypertension by 4.7 million (about 13%) and avert 192,000 heart attacks and 204,000 strokes. 
1.B.2.3. Need for a study comparing clinic-based and telehealth care models. In summary, we have identified gaps that 
support the need for a comparative effectiveness trial. 1) Although clinic-based care has achieved high levels of BP 
control in some highly integrated, large health systems, few practices have achieved the same outcomes. Rigorous 
evidence supporting most of the best practices is lacking. 2) Despite strong evidence from research studies showing that 
nurse- and pharmacist-led team-based care and telehealth interventions result in large and lasting improvements in BP, 
it is unclear how successfully these can be implemented at scale in real-world settings without research support. 3) It is 
also uncertain whether such resource-intensive care achieves better clinical results, and 4) it is not known how it affects 
patient experience compared with traditional clinic-based care if best practices were adopted. The research will directly 
compare long-term outcomes of two different organizational models for team-based care, one that incorporates current 
best practices but relies primarily on the physician-medical assistant dyad and face-to-face visits (clinic-based care), and 
one that extends care outside the confines of the clinic using telehealth care, systematic home BP telemonitoring, and 
care coordination by a pharmacist or nurse practitioner (telehealth care). HealthPartners, the setting for the study, 
already uses some of the components of best practice in its clinic-based care, but further improvement in BP results is 
needed. HealthPartners is therefore poised to adopt other elements of best practice for clinic-based care (eg, protocols 
to promote consistent treatment and follow up for elevated BP, a hypertension registry to improve population 
management), but there are no plans to adopt telehealth care for hypertension widely in clinical practice without the 
research infrastructure to compare it rigorously with clinic-based care provided by this proposal. The study will support 
systematic data collection and analysis on implementation and outcomes, but intervention clinical care costs are 
supported by HealthPartners. 
2. Objectives 
2.A. Aim 1 
In a pragmatic cluster-randomized trial in patients with uncontrolled hypertension, compare the effects of two evidence-
based strategies on lowering blood pressure and other outcomes important to patients: best-practice clinic-based care 
and home-based telehealth care.   
Hypothesis 1.1: Compared with patients in clinics assigned to clinic-based care, patients in clinics assigned to 
telehealth care will have a 5 mm Hg greater change in systolic blood pressure over 12 months of follow up. 
Hypothesis 1.2: Compared with patients in clinics assigned to clinic-based care, patients in clinics assigned to 
telehealth care will report: a) fewer treatment side effects; b) better ratings of patient experience of hypertension 
care; and c) higher self-monitoring rates and confidence in self-care. 
 
2.B. Aim 2 
Conduct an evaluation of reach, adoption, implementation, and maintenance of the telehealth care and clinic-based 
care interventions using a mixed-methods approach supported by the RE-AIM framework and the Consolidated 
Framework for Implementation Research (CFIR) 
3. Study Design 
The study compares two alternative health care service designs emerging as the dominant choices for clinicians and 
health systems wanting to redesign and improve hypertension care outcomes. It builds on previous hypertension quality 
improvement initiatives and the Hyperlink study, which used telemonitoring and telephone communication between 
patients and clinical pharmacists. The study design incorporates many elements of pragmatic trials: few exclusion 

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criteria, flexible interventions delivered in routine care, and routine follow up to determine outcomes.56 It is a cluster-
randomized comparative effectiveness trial in 20 primary care clinics (Figure 1). [Note that 21 primary care clinics were 
eligible to participate (see section 4.B.) and agreed to be randomized. Four of the clinics were co-located in two 
buildings (two practices in each) and had shared nursing leadership. Each of the co-located clinics were randomized as 
one unit; therefore there are 19 units of randomization. For simplicity throughout the rest of this protocol we will 
continue to refer to the study as including 20 primary care clinics.] The clinic-based care approach will use 
recommended best practices in ~10 clinics and ~1000 patients. It relies primarily on the physician-medical assistant dyad 
and face-to-face visits. The telehealth care approach adapts and implements a successful research-tested model in ~10 
clinics and ~1000 patients. It differs from clinic-based care through the systematic use of home BP telemonitoring and 
home-based telehealth care coordinated by a pharmacist. Aim 1 compares outcomes that are important to patients and 
other stakeholders, including BP lowering, treatment side effects, patient experience, and self-care. Aim 2 evaluates the 
extent and between-clinic variability of the adoption, implementation, maintenance, and reach of the interventions. 
Data collected for Aim 2 will also be used to monitor and improve fidelity to the interventions. Please see Appendix F for 
a high level overview of the study design. 
To ensure that the study addresses the relevant questions and concerns of patients, caregivers, clinicians, and other 
healthcare stakeholders, the research team includes two patient investigators, a patient advisory board (PAB), and a 
stakeholder advisory board. The roles, structure and function of these individuals and groups are described more fully in 
section 13 (Organization) and Appendix I. 
 
4. Study Population 
4.A. Setting  
HealthPartners is a nonprofit integrated health system in Minnesota and western Wisconsin serving more than 1.5 
million health plan members and more than 1 million patients. It includes a multispecialty group practice of more than 
1,700 physicians, seven hospitals, and 47 primary care clinics. HealthPartners accepts all forms of commercial insurance, 
Medicaid, and Medicare, and the patients are diverse by age, race/ethnicity, and socioeconomic status. 
4.B. Recruitment and randomization of clinics 
The population of interest is patients with uncontrolled hypertension cared for by HealthPartners primary care providers 
(PCPs) at 20 representative primary care study clinics. Clinics will be eligible to participate if they have a Medication 
Therapy Management (MTM) pharmacist onsite at least one half-day per week and use standardized methods to 
measure BP with validated oscillometric BP monitors. Eligible clinics will be contacted via their leadership and invited to 
participate if they are willing to be randomly assigned to clinic-based care or telehealth care, participate in training, 
participate in limited data collection activities, and receive periodic feedback on implementation of the elements of 
clinic-based care or telehealth care according to their randomized assignment. Eligible clinics will be assigned to strata 
based on the proportion of hypertensive patients with controlled BP and the number of days per week that a pharmacist 
is available. Each stratum will include at least 4 clinics. The study statistician will assign a random unique identifier to 
each eligible clinic and then randomly and equally assign them to clinic-based care or telehealth care within strata.  
4.C. Inclusion and exclusion criteria  
Patients who meet the study inclusion criteria for uncontrolled hypertension will be identified in real-time at primary 
care encounters based on EHR data. Patients who meet the study inclusion criteria: 1) are aged 18 to <=85; 2) had two 
or more qualifying encounters with a hypertension diagnosis code within the last 24 months; 3) had a visit with their 

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assigned PCP in the last 12 months with or without a hypertension diagnosis code; 4) meet high BP study criteria at the 
current visit in the study primary care clinic where their assigned PCP practices; and 5) met high BP study criteria at their 
most recent previous qualifying encounter.  
According to the nursing protocol for BP measurement, BPs are repeated if the first BP is elevated, defined as an SBP > 
140 or DBP > 90.  Study criteria for high BP for patients are defined as SBP > 150 or DBP > 95 in the first BP and in a 
repeated BP within an encounter.  A qualifying previous encounter is defined as an office visit with a medical assistant 
(MA), nurse, physician, nurse practitioner, or physician assistant in internal medicine, family medicine, pediatrics, 
geriatrics, cardiology, endocrinology, or nephrology clinics. Study criteria for high BP are based on estimates of the 
number of eligible patients and capacity of the study clinics to accommodate additional follow-up referrals. They may be 
adjusted if warranted by changes in patient volume or clinic capacity. 
The study will exclude 1) pregnant patients, since they require specialized obstetric care, 2) patients with end-stage 
kidney disease, who need specialized care from kidney disease specialists, 3) patients in hospice care, and 4) patients 
who permanently reside in a nursing home. The population of interest is broadly represented since these criteria 
eliminate only a small fraction of hypertensive patients. These four groups of patients are also excluded from quality 
improvement measurements based on HEDIS and from MN Community Measurement publicly reported data. 
 
4.D. Enrollment of patients  
For patients who have an elevated BP at a primary care encounter (nurse or provider) but do not yet meet the study’s 
high BP criteria for two consecutive qualifying visits, providers and clinic staff are encouraged to use a standardized 
hypertension referral order that facilitates scheduling a BP follow up with a provider of their choice (nurse, primary care 
provider, MTM pharmacist, or specialist).   
If the patient meets all study inclusion and exclusion criteria, the patient will be identified automatically upon BP entry 
through algorithms within a web-service and flagged as “eligible” for Hyperlink.  The MA will receive a best practice alert 
(BPA) that if accepted will open an order for hypertension follow up.  The MA will “pend” this order for the provider.  
Once pended, the order can be removed or signed, but must be addressed by the provider before the encounter can be 
closed. The follow-up BP order contains defaults to nurse, PCP, or MTM as dictated by appropriate clinic-based care or 
telehealth care depending on the clinic assignment (see section 5 on Interventions.)  The defaults can be modified by the 
provider prior to signing order using their professional judgement.  Once the order is signed and the encounter is closed, 
the patient is flagged as “enrolled” in the study.  
Enrollment will occur in two phases, Vanguard and Main Trial.  Vanguard Phase enrollment will begin at the start of Year 
2 with 2-4 Vanguard clinics to test procedures and make adjustments so that they are running smoothly. Enrollment of 
patients will continue until the study sample of 2000 eligible patients has been enrolled in the main trial from the 20 
study clinics (Figure 1). In order to avoid very unequal distribution of cluster sizes, enrollment will continue for each 
clinic until a cap is met (e.g., 200 in a large clinic) or until a minimum is met (e.g., 40 in a small clinic). An average-sized 
clinic would need to enroll about 8-10 patients per month (or 2-3 patients per week) over 12 months to achieve our 
sample size. 
Enrollment uses existing clinic resources, but to ensure that the study population represents the diversity of the 
HealthPartners population with uncontrolled hypertension, additional resources are budgeted for outreach and 
transportation for low-income and minority patients to attend visits and to promote their equal participation and 
retention in the study. Given that there are no special study visits to attend and that BP checks, pharmacist 
consultations, and any equipment will be provided without charge, we do not believe that these costs will be substantial 

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barriers to participation.  
 
5. Interventions 
 
Both care models we propose to study have been shown to reduce BP substantially. Best practices for clinic-based care 
are based primarily on expert opinion and observational studies. Telehealth care has generally been studied in relatively 
small studies and for limited durations. These models were selected because they represent the dominant choices for 
clinicians and health systems that want to redesign hypertension care, but they have not been directly compared, and 
there is little information about patient preferences. Thus, our main research question is which approach to treating 
people with uncontrolled high BP produces the best outcomes. Both are rooted in the Chronic Care Model developed 
and refined by Wagner and colleagues.57 This model identifies delivery system design, decision support, information 
systems, and self-management support as essential elements for improving chronic illness care in health systems. These 
elements foster productive interactions between informed patients and prepared practice teams. Both models use 
multiple levels of delivery system design to create positive feedback loops whereby uncontrolled BP is recognized and 
prompts timely treatment adjustment and BP re-measurement until BP control is attained. 
 
5.A. Best Practice Clinic-Based care 
The components of best practice clinic-based care are based on a review of the literature and current guidelines (section 
1.B.2.1.). They were further discussed in a HealthPartners working group to improve hypertension care that includes 
nurses, pharmacists, physicians, administrators, and researchers. The best practices are achievable by motivated 
primary care practices of all sizes using readily available EHR technology. Similar models are being promoted and 
disseminated by the professional organizations that are stakeholders in this project. 
 
As operationalized for this project the best practices fall into two categories: a) infrastructure and policies that promote 
high quality care, and b) hypertension care processes that promote recognition, timely treatment adjustment, and 
follow-up of uncontrolled BP until control is attained. 
 
5.A.1. Current infrastructure and policies 
1. Accurate BP measurement is promoted by the consistent use of validated oscillometric BP monitors (Omron 
HEM 907XL) according to a standard nursing protocol. The protocol includes proper cuff size, proper positioning 
of the patient, and requires a repeat BP measurement after 5 minutes of rest when the initial BP is elevated. 
Both automated EHR alert and physical reminders are used to prompt repeat BP measurement at the same visit 
when the initial BP is elevated. (See Appendix A for Nursing BP Measurement Protocol) 
2. Patients have access to no-cost blood pressure recheck visits with an MA and consultations with a clinical 
pharmacist trained in medication therapy management (MTM) to follow up on uncontrolled BP at clinic 
encounters. MTM pharmacist consultations are face-to-face visits in the patient’s primary care clinic and 
generally do not include ongoing follow up. Patients may self-refer or can be referred by a PCP, MA, or RN. 
3. A hypertension registry is used to enumerate the patient population with hypertension (controlled and 
uncontrolled). The registry is used to identify and contact patients who need follow-up for uncontrolled 
hypertension. (See Appendix D for Hypertension Registry Standard Operating Procedure, Appendix E for 
Hypertension Registry Technical Specifications 
4. PCPs use an evidence-based hypertension treatment algorithm that promotes low-cost generic medication and 
single-pill combination therapy, when possible. If BP is uncontrolled at an MA visit, the MA may consult a 
registered nurse (RN) or MTM pharmacist. RNs and pharmacists have separate protocols to adjust hypertension 

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treatment. If the RN or pharmacist is unavailable at the time of the MA visit, the patient may be contacted by 
telephone and/or scheduled for a return visit to the PCP. (See Appendix B for MTM Hypertension Protocol, 
Appendix C for ICSI Guidelines for Hypertension Management) 
5. PCP and clinic performance on BP control is measured with monthly feedback. Clinic managers have access to 
monthly reports and routinely download and distribute them to PCPs. BP control is a high priority performance 
measure, with open comparison within and between clinics. 
6. Home BP monitoring may be encouraged by individual clinicians, but is not supported by infrastructure or 
policies.  
All of the above infrastructure and policy elements are currently in place in all HealthPartners primary care clinics. 
Elements 1, 3, 4, and 6 may vary in implementation between and within clinics and will therefore be measured for 
implementation fidelity as described in section 7.D and Table 2. 
5.A.2. Hypertension care processes 
The study will create and enhance automated EHR tools to promote the following iterative process: 
1. Recognition of uncontrolled BP and high BP study criteria at primary care encounters 
2. Therapeutic action to address uncontrolled BP at primary care encounters (may include medication adjustment, 
addressing non-adherence, and counseling on lifestyle changes) 
3. Follow-up visits to re-assess uncontrolled BP within 2-4 weeks. Follow-up visits may be scheduled with a PCP, 
MA, or MTM pharmacist. 
Blood pressure in the ambulatory primary care setting at HealthPartners is measured by the MA during the rooming 
process for a clinic appointment, or at the time of a nurse blood pressure check using an electronic, automated monitor. 
If an initial BP  > 140/90 is entered into the EHR vital signs field it will trigger an automated BPA pop up to remind the 
MA to repeat the BP if the initial BP is elevated after 5 minutes of rest. If the study inclusion/exclusion criteria are met 
on the repeat BP, a new BPA appears on the computer screen prompting the MA to open and pend an order for 
hypertension follow up. The default follow-up interval is 2 weeks unless the BP is > 180/110 in which case the default 
follow up interval is set to 1 week.  The type of provider for the follow up visits defaults to nurse, PCP, or MTM 
depending on the clinic randomization.  All defaults can be changed by the MA or at provider discretion if desired by 
clicking a different options within the order, but the patient is enrolled by any signed order.   
Implementation and fidelity to hypertension care processes will be measured as described in Section 7.D and Table 2 
using EHR vital sign, diagnosis, current medications, medication order, and encounter data stored and linked to 
individual study patient IDs and encounters. The study will foster reliable processes in all study clinics through training, 
measurement, and feedback to improve the consistency with which the hypertension follow up orders are pended, 
signed, scheduled, and completed. 
5.B. Telehealth care 
The design of the telehealth care intervention is based on our experience and the literature reviewed in section 1.B.2.1. 
The Chronic Care Model domain that differs most from clinic-based care is the strong self-management support built 
into the telehealth care intervention. Recent systematic reviews found that home BP monitoring alone resulted in small 
and non-sustained BP reduction, while adding support resulted in larger BP reduction that was sustained for at least 12 
months.58 Therefore, there is ample evidence from efficacy trials that the combination of home BP monitoring and 
telephone or online follow up is synergistic. The combination creates a powerful feedback loop that permits sequential 
trials of treatment changes and rapid assessment of their effect on BP, side effects, and other outcomes. It is critical to 
have a dedicated health care provider to receive, interpret, and act on the home BP monitoring data in collaboration 

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with patients. Our analyses of Hyperlink and e-BP have shown that the strongest predictors of BP lowering in these trials 
were the intensity of home BP monitoring, communication between patients and pharmacists, and medication 
treatment intensification.59  
In our previous research on telehealth care for uncontrolled high BP, we conducted focus groups with patients and 
pharmacists in the study. Several key themes emerged that suggested ways to improve the intervention to better meet 
patients’ needs. Focus group patients told us that trust in the relationship is important to them, whether working with a 
PCP or an MTM pharmacist. Patients reported having more trust in pharmacists if they understood their qualification to 
treat high blood pressure. They were dissatisfied when they perceived poor communication between the pharmacist 
and their PCP. Second, patients have highly personal needs when it comes to initiating medication or finding the best 
medication. They value clinicians who listen and engage instead of just “pushing pills”, an attribute that was also 
strongly endorsed by the pharmacists. Patients have varying goals related to medication; many want to avoid or 
discontinue medications, if possible, in favor of lifestyle interventions. Side effects of medications are a major concern. 
Therefore, patients want a flexible approach rather than a one-size-fits-all model for treating hypertension, and this in 
turn supports acceptance, adherence, and satisfaction with treatment. Finally, patients benefited from both seeing their 
BP data (reinforcement) and having a trusted provider see their data (accountability). These led to long-term adoption of 
regular self-monitoring and specific strategies to keep their BP under control; therefore, patients strongly preferred to 
keep the BP monitor after they stop regularly working with the pharmacist.  
Suggestions from the focus groups and analyses of study data were used to modify our previous telehealth care 
intervention29 in the following ways.  1) The qualifications of pharmacists to treat hypertension and the collaborative 
nature of their work with the patient’s PCP will be emphasized. 2) In order to remove barriers for team care, home BP 
data will be transmitted and stored in the HealthPartners Epic EHR, rather than in a password-protected third-party Web 
site. Home BP data will be maintained in a flowsheet that is separate from BP measured during clinic visits. 3) 
Trajectories of BP during the Hyperlink study showed maximum BP lowering after an average of about 3 months, with 
little additional BP lowering during the remainder of the 6 months of intensive intervention and 6 additional months of 
maintenance. Therefore, rather than having a fixed duration, the telehealth care intervention will be flexible and 
tailored to individual patients’ needs. 4) Patients will have several options for transmitting home BP data (further details 
below). In any case, patients will be given their own BP monitor for long-term use.  
Telehealth care clinics will offer best-practice clinic-based care, but eligible patients in these clinics will be referred for 
telehealth care with systematic home BP telemonitoring and BP management through the MTM pharmacist. Referrals 
will take place using the same hypertension follow up orders used for clinic-based care, but the default will be MTM 
pharmacist follow-up. There is currently a high rate of appointment completion following referral to MTM pharmacists. 
As in the clinic-based care group, the study will foster reliable processes to improve the consistency with which the 
order set is used and uncontrolled BP is re-assessed by an MTM pharmacist within 4 weeks. Following an initial face-to-
face intake visit, the MTM pharmacist and patient will communicate by telephone or secure e-mail (according to patient 
preference) at regular intervals, adjusting medication using established care protocols and collaborative practice 
agreements until BP control has been achieved. Pharmacists will also support lifestyle changes and adherence to 
treatment. Other CV risk factors including smoking, hyperlipidemia, hyperglycemia in diabetic patients, and use of 
aspirin will be addressed as needed using evidence-based protocols, since this is the customary practice of MTM 
pharmacists at HealthPartners. 
5.B.1. Intake visit with MTM pharmacist 

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1. The pharmacist in telehealth care clinics will receive an EHR alert that the patient is a Hyperlink-3 study patient. The 
pharmacist follows standard MTM procedures for assessment of new patient including measurement of BP and 
determination of correct BP cuff size.  
2. The pharmacist emphasizes that the PCP has referred the patient and that they will be collaborating on the patient’s 
care, explains the pharmacist’s training and qualifications to treat hypertension, determines if patient is willing to 
use home BP monitoring equipment and communicate by phone or email, and complete appropriate documentation 
in EHR.  
3. The pharmacist determines with the patient the most appropriate method for home monitoring and instructs the 
patient on proper use of equipment, positioning, and BP cuff size. 
4. The patient is advised to check blood pressure 6 times weekly (eg, 3 days each week, morning and evening), with 
duplicate measurements each time if possible. 
5. Pharmacists instructs patient on individualized BP level indicating control (5 mm Hg lower than clinic goal for SBP 
and <85 mm Hg for DBP goal) and goal to have 75% of home BP readings below that level. 
6. Pharmacist orders BP monitoring equipment and obtains consent for data sharing if needed.  
7. MTM pharmacist follows a slightly modified version of the current HealthPartners MTM hypertension management 
protocol regarding lifestyle counseling, medication initiation, titration, labs, and follow up plan.  (Appendix B for 
MTM Hypertension Protocol) 
5.B.2. Follow-up visits with MTM pharmacist 
Follow-up visits will typically be done by phone or secure e-mail on the HealthPartners EHR portal. In some cases in-
person visits may be preferable due to patient communication needs (eg, patient is severely hearing impaired, requires 
interpreter).  Visits will be documented in the EHR using a visit template and routed to the PCP. The first 3 follow-up 
visits will be at 2 week intervals, then may be spaced at longer intervals every 2-4 weeks for up to 6 months as decided 
by the pharmacist and patient. Based on our experience, we anticipate that most patients will only need telehealth care 
management for 3 or 4 months. 
1. Pharmacist reviews lifestyle, medication adherence, and BP readings with patient. 
2. Pharmacist adjusts medications as needed based on aim to have > 75% of BP readings at controlled level. If this is 
not the case, discuss options with patients with emphasis on the most effective action that is clinically appropriate 
(add new medication, increase medication dose, improve adherence, intensify lifestyle management). The superior 
effectiveness of adding a new low-dose medication makes this the preferred option in many circumstances.  
3. Subsequent follow up visits by phone every 2-4 weeks. 
4. When > 75% of BP readings are controlled at 3 consecutive follow-up visits, begin transition back to clinic-based care 
with PCP visit to document clinic BP. 
5. If BP is not controlled in 3 months, schedule follow-up appointment with PCP to determine next steps. 
5.B.3. Communication with primary care team and transition from telehealth care: 
Clear communication among team members will take place by formal and informal discussions and shared notes in the 
EHR. When patients attain stable BP control in 3 consecutive telehealth visits, they will transition to routine clinic-based 
care and will be given a high-quality non-data transmitting home BP monitor if they do not already have one. The entire 
episode of telehealth care will be summarized in the EHR using a standard note template. Patients may re-enter the 
telehealth care intervention if clinic BP reverts to uncontrolled levels or if they detect recurrence of uncontrolled home 
BP by continued self-monitoring. 
5.B.4. Home BP monitoring options: 

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A note on cost: Patients will not be billed in any way for their MTM visit or for blood pressure monitoring equipment. 
HealthPartners does not charge patients for MTM visits. Blood pressure monitoring equipment will be provided free of 
cost to the patient using study resources. Given that we are testing a program that we hope will be adopted by 
HealthPartners if it improves hypertension outcomes, we must pay attention to keeping equipment costs as low as 
feasible. 
 
1. Non-transmitting BP monitor (LifeSource 767) with manual data entry into MyChart:  This is the lowest cost option 
for the study budget, but it requires that patients are willing and able to manually enter BP into the EHR portal 
(MyChart) for viewing by the MTM pharmacist.  This option also requires internet and computer access. 
2. Bluetooth BP monitor (Lifesource 767pbt-ci) with automated data upload to MyChart via AMC Health: This option is 
the most expensive for the study budget due to a monthly fee, but it will work well for patients who do not have 
access to the internet at home or who are unwilling or unable to accurately manually enter home BP data. 
Telemonitoring equipment will be supplied by the vendor AMC Health.   
3. Bluetooth BP monitor (models to be determined) with automated data upload via smartphone app: This option has 
the potential to be as inexpensive for the study budget as Option 1 and as simple as Option 2. However, it requires 
the patient to have a smartphone with the correct app. We do not currently have capability or permission to use this 
option at HealthPartners, but will be working intensively to make it available during the study. 
Implementation and fidelity to hypertension telehealth care processes will be measured as described in Section 7.D and 
Table 2 using EHR vital sign, diagnosis, current medications, medication order, and encounter data stored and linked to 
individual study patient IDs and encounters.  
6. Training   
All 20 clinics will receive hands-on, in-person intervention training for their staff, conducted by a physician investigator, a 
project manager or coordinator, and the clinic’s Care Delivery Supervisor. Training will be conducted in June and July of 
2017, prior to the official start of the study interventions.  
All clinics will receive training on: 
• 
The hypertension management workflow, including best practice alerts and referral orders for hypertension care 
• 
Communication with patients about hypertension care referrals  
• 
Follow-up with patients regarding unscheduled or missed referral visits 
• 
Omron BP machine best-practice use, re-emphasize need for second BP when elevated 
Telehealth clinics will receive training on:  
• 
Details of telemonitoring program for discussion with patients 
• 
Operation of telemonitoring equipment and technical support options 
• 
Use of patient-entered vitals flowsheet (in EMR)  
We will include all primary care team members in these initial trainings, including PCPs, RNs, MA/LPNs, and MTMs. We 
will keep a roster of all staff in these positions at each clinic, and monitor attendance at trainings. The best training 
format will be determined by the clinic Care Delivery Supervisor. We will record a webinar presentation of our basic 
training to supplement the in-person/hands-on training, for review by staff who couldn’t attend or for use as a 
reference. After each in-person training we will collect evaluation feedback to determine whether the training is 
meeting the needs of each clinic. 

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Care Delivery Supervisors will be provided with a simple 1-2 page “guide” for the hypertension care interventions, so 
they may continue to support their staff in reinforcing best practices.  
Need for follow-up trainings will be determined at the conclusion of the initial in-person training. 
The following training materials will be developed by the study team with input from stakeholders by May 2017:  
1. Detailed outline of training objectives 
2. Scripts for patient communication about interventions (central outreach, nursing, physicians, pharmacists) 
3. After Visit Summary content with patient instructions 
4. Frequently Asked Questions for both interventions  
5. Guide for Care Delivery Supervisors 
6. Instructions for set-up and use of Telemonitoring Equipment (Telehealth Clinics only)  
Further training will be provided during in-person visits from the study staff to clinics throughout the intervention 
period. At least 10 clinics will receive a quarterly in-person visit by a study coordinator and all clinics receive in-person 
visits for continued training and evaluation every six months. The content and objectives of these in-person visits is to be 
determined. 
7. Outcomes  
The study outcomes have been selected based on input directly elicited from patients and other stakeholders 
participating in this project. The Aim 1 outcomes address the relative effectiveness of clinic-based care and telehealth 
care in improving key clinical and patient-reported outcomes (Table 1). The Aim 2 outcomes are directed toward 
evaluating intervention implementation fidelity (Table 2) and other RE-AIM measures (Table 3). No additional research 
visits will take place to gather outcomes data.  
7.A. Primary Aim 1 outcome 
The primary outcome is change in SBP after 12 months of follow-up (H1.1). SBP values that are routinely collected in 
primary care will be extracted from the vital signs field in the EHR at the two qualifying encounters and at all subsequent 
qualifying encounters over the next 24 months for all enrolled patients.  
 
7.B. Secondary Aim 1 outcomes 
Aim 1 patient-reported secondary outcome measures are treatment side effects; experiences and satisfaction with 
hypertension care; home BP self-monitoring; and confidence in self-care. These outcome data will be collected using 
patient surveys. These patient-reported secondary outcome measures were selected based on 1) patient ratings of 
importance, 2) evidence that previous similar telehealth interventions led to improvements, 3) importance of the 
measure as a potential mediator of intervention effect, and 4) the measure cannot be obtained from the EHR, claims or 
any other routinely collected patient data. All enrolled patients will be mailed a baseline survey that includes primary 
patient-reported outcome measures within one week of their qualifying encounter, with telephone follow-up of non-
responders.  They will also be asked to complete follow-up surveys 6, 12 and 24 months later that will be administered 
by mail, telephone or electronically according to the patient’s preference. The secondary Aim 1 analyses will focus on 
patient reports in the baseline and 6 month surveys.  A draft of the patient survey is included in Appendix H.  
Patients’ reports of BP treatment-related side effects will be assessed using the Treatment Satisfaction Questionnaire for 
Medication (TSQM) and a side effect symptom checklist modeled after the PERSYVE questionnaire.58 The TSQM global 
satisfaction and effectiveness, side effects, and convenience subscales demonstrate adequate internal consistency 

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(Cronbach α = .86-.90) and positive correlation with self-reported health. Among patients with hypertension, all three 
subscales were correlated with global medication satisfaction.59 
Patient Assessment of Chronic Illness Care (PACIC). The PACIC 60 will quantify patient experience of hypertension care, 
including self-management support, along dimensions in the Chronic Care Model. The overall PACIC scale has 
demonstrated excellent internal consistency (Cronbach α = .93; subscale α=.77-.90) and adequate test-retest reliability 
over 3 months (overall .58; subscales .47-.68). It has been shown to be highly responsive to a telehealth intervention for 
hypertension. 
Satisfaction with health care provider communication will be measured with the 6 items from the Clinic & Group 
Consumer Assessment of Healthcare Providers and Systems (CG-CAHPS). The CG-CAHPS survey is a product of the 
Agency for Healthcare Research and Quality's CAHPS program, which is a public-private initiative to develop and 
maintain standardized surveys of patients' experiences with ambulatory and facility-level care. The scale has good 
internal consistency (Cronbach α = .89), is highly correlated with overall physician ratings, and the scale items have been 
shown to be responsive to a previous telehealth care intervention.61  In addition, this subset of items is currently in use 
to assess patient satisfaction with care at HealthPartners clinics and other medical groups nationally as part of the NRC 
Picker ‘Connect Experience’ survey.  BP self-monitoring rates and confidence in self-care will be measured by items used 
in previous research29,55 that have been shown to be responsive to intervention.  
 
 7.C. Aim 1 other outcomes 
Other clinical outcomes include cardiovascular risk factors other than systolic BP (DBP, lipid levels, statin use, 
antihypertensive medication use, smoking, and overall cardiovascular risk based on 10-year AHA/ACC pooled risk 
equations 62 and the Framingham 30-year risk equation 63 that may be influenced directly or indirectly by telehealth care 
relative to clinic-based care. The study will also monitor laboratory abnormalities in electrolytes and kidney function that 
may be affected by hypertension medications, as well as low blood pressure (hypotension) and fainting that might result 
from overly aggressive blood pressure lowering. All secondary clinical outcome values and dates are routinely 
documented in the EHR as they are measured at clinic encounters or are returned as laboratory values. 
The patient survey will also include some items and scales that do not meet the criteria for secondary outcomes but 
have been identified by patients or investigators as potentially important, as well as all responses from the 12 and 24 
month surveys. 
7.D. Aim 2 outcomes 
The Aim 2 analyses are directed toward evaluating intervention uptake and providing timely feedback to clinic and care 
teams to improve fidelity to both interventions. We will rely on two well-accepted frameworks, the RE-AIM framework64 
and the Consolidated Framework for Implementation Research (CFIR)65 to identify barriers and facilitators to adoption, 
implementation, and maintenance;  monitor intervention implementation progress and adaptations; and interpret 
reasons for variations in implementation success or failure.  The reach, adoption, implementation and maintenance of 
both interventions will be evaluated using the definitions of each measure found in Tables 2 and 3.  
8. Measurements  
8.A. EHR for clinical measures 
The primary outcome, SBP, and other clinical outcomes will be extracted from data documented in the electronic health 
record (EHR). An EHR tool that operates in HealthPartners primary care clinics is automatically triggered when vital sign 

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data are saved to the EHR. The tool searches the EHR to gather the most recent vital signs (e.g., SBP, DBP) and 
laboratory values (e.g., total cholesterol, LDL, potassium, sodium, creatinine), current medications (e.g., 
antihypertensive medications, statins), lifestyle data (e.g., smoking status, BMI), safety events (hypotension, fainting), 
and socio-demographic information (e.g., age, ethnicity, race). These data elements are used to calculate total 
cardiovascular risk (e.g., 10 year Hard CV risk via the ACC/AHA risk model; 30 year lifetime risk via the Framingham 
model) and to alert the provider to abnormalities (e.g., potassium, sodium, creatinine values that are out of range). The 
EHR tool documents the information that was aggregated for each triggering event, including the dates that were 
associated with each data element (e.g., date of cholesterol test). The tool also assigns a random unique identifier to 
each patient so that data elements stored in the EHR as part of routine care may be readily extracted and re-assembled 
to describe within-person changes in clinical outcomes over time.  
8.B. Patient Survey for patient-reported outcomes  
All study-enrolled patients (n=2000) will be invited to complete a series of surveys that will be the source of the patient-
reported primary outcomes (i.e., treatment side effects, experiences and satisfaction with hypertension care, self-
management support, confidence in self-care). Appendix H Figure 1 describes the process for collecting survey data from 
patients The EHR tool will identify patients at the visit when they are enrolled in the study and transmit their contact 
information to the HealthPartners Survey Research Center (SRC). The SRC will mail a letter to request their participation 
in a series of surveys, a paper questionnaire and a $2 non-contingent incentive, a practice known to increase response 
rates and reduce the likelihood of non-response error.66,67 The SRC’s professional phone interviewers will call patients 
who do not return the paper survey to attempt to complete a survey via phone within 2 weeks of enrollment.68 At the 
end of the survey, respondents will be asked what mode they prefer for follow-up surveys 6, 12 and 24 months later. 
First contact for follow-up surveys will be made via the respondent’s preferred mode. Non-respondents to the 
enrollment survey will not receive further surveys. All four surveys (enrollment, 6, 12, and 24 months) will include the 
patient reported outcome measures. The secondary analyses (H1.2) will make use of data collected from the enrollment 
and 6m surveys while other outcome analyses will make use of data collected at all four time points. Patients who 
complete enrollment, 6, 12, and 24 month surveys will be mailed a $10 gift card. Patients who are on the HealthPartners 
Institute Exclusion List will not receive a survey. 
 
9. Evaluation Reporting  
Clinic managers and primary care physician chiefs will be provided with a monthly summary of measures pertaining to 
their blood pressure care and the study interventions.  The reports will include measures found in Tables 2 and 3, and 
will be linked to clinics’ blood pressure control performance measures provided by HealthPartners. At 12 and 24 
months, a more extensive report will be populated that will include a summary of field observations, focus group and 
interview data, and other data supporting recommendations for the clinics.  
Field observations will be made by study staff visiting clinics in-person and speaking with clinic managers and staff as 
feasible and observing the rooming process. The study team will meet to discuss observations and other sources of data 
prior to compiling monthly reports or making recommendations.  Reports will be available and shared online, and 
viewable across clinics.  
 
10. Analysis  

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10.A Aim 1 Primary and Secondary Analyses 
The Aim 1 hypotheses pertain to the effectiveness of telehealth care, predicting that, relative to clinic-based care, it will 
improve SBP by a practically meaningful 5 mm Hg after 12 months of follow up (H1.1) and patient-reported outcomes 
(PRO) after 6 months of follow up (H1.2). H1.1 will be tested using random coefficients models in which post-enrollment 
SBP values will be predicted from clinic-randomized treatment group (Telehealth), time elapsed from enrollment to the 
SBP (YEARS), and the treatment by time interaction. The most basic form of the H1.1 model will be:   
SBPij = γ00 + γ10 Telehealthi + γ01YEARSj + γ11 Telehealthi*YEARSj + [ui0 + eij], 
where EHR-derived SBP values documented at all qualifying encounters for 24 months will vary randomly across 
randomized clinics (ui0) and time (eij). Enrolled patients will be assigned to the treatment group to which their clinic is 
randomly assigned, regardless of their adherence to any component of the clinic-based care or telehealth care 
approaches. YEARS will be scaled so that 0 represents the date of the primary care encounter at which the patient was 
enrolled in the study and 1 represents 365 days later. Parameter γ01 will therefore estimate the annual rate of change in 
SBP among clinic-based care patients, and parameter γ11 will estimate the difference in rate of SBP change among 
telehealth relative to clinic-based care patients. The H1.1 model will be adapted for H1.2 by replacing the YEARS 
component of γ01 and γ11 with a dummy indicator (6M) for whether the PRO is an enrollment or 6-month survey 
response.  
SBP and PRO are expected to be approximately normally distributed, although the suitability of alternate error 
distributions and link functions will be assessed if their distributions depart from expectations. Should we observe an 
imbalance between study groups in the characteristics of randomized clinics, particularly in factors that moderate the 
fidelity with which the care models may be implemented, we may include clinic-level variables (e.g., % patients >65) as 
covariates or treatment modifiers, as appropriate. 
SBP values are expected to decline over time among clinic-based care patients so that γ01<0. H1.1 will be most strongly 
supported if γ11 ≤-5.0 and P<.05, so that the estimated rate at which SBP values improved over 12 months was at least 5 
mm Hg greater among telehealth patients relative to clinic-based patients. PROs are expected to be similar at baseline 
but months to have improved among telehealth patients by 6 months so that γ1 >0 and P<.05. 
 
10.A.1. Aim 1 Other Analyses  
We plan to explore whether treatment effects differ among patient groups defined by age, race/ethnicity, 
socioeconomic status, and comorbidity. While we anticipate that on average across all patient groups telehealth care 
will reduce SBP by 5 mm Hg more than clinic-based care, we will separately quantify the treatment effect for all H1 
outcomes among targeted patient subgroups. The H1 analytic models can be easily adapted to include parameters for 
patient covariates as well as interactions of patient covariates with time or time by treatment.  
The H1 analytic models can be readily adapted for secondary and sensitivity analyses. As presented, H1.1 assumes a 
linear rate of change in SBP over time. The model can be readily adapted to assess the immediate effectiveness of 
telehealth during the first 6 months following eligibility separately from the 6- to 12- and 12- to 24-month periods, when 
short-term improvements in SBP or PROs may be differentially maintained over a longer time frame. Similarly, 
parameters γ01 and γ11 can be allowed to vary randomly so that the rate of SBP change is different for each of the 20 
randomized clinics. We could then assess, for example, whether clinic-specific rates of change are related to clinic 
characteristics or the fidelity with which the care model was implemented. 

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10.A.2. Per Protocol Analysis Plan  
Given the pragmatic, unblinded, cluster-randomized study design, there is potential in this study for otherwise-eligible 
patients to not be enrolled, and for enrolled patients to subsequently seek treatment interventions (including no 
treatment) outside of their assigned protocol.  Furthermore, we would like to know what the impact of actual receipt of 
the intervention (as opposed to clinic-level assignment) has on study outcomes.  Therefore it will be desirable to conduct 
a per-protocol analysis (average effect of telehealth vs. best practice, had everyone followed the trial protocol) to 
complement the intention to treat (ITT) results of the primary analysis.69,70  Preliminary data suggests that the ITT 
approach in this study may be subject to bias due to 1) differential likelihood of enrollment based on provider 
knowledge of treatment assignment, and/or 2) differential self-selection of patients following through with the assigned 
treatment intervention.  Because these processes operate post-randomization, the randomization scheme cannot 
ensure confounder balance by enrollment or treatment status, and the study population can be considered as analogous 
to an observational cohort. 
Directed acyclic graphs (DAGs) have been used to depict causal relationships and illustrate potential sources of bias in 
epidemiologic studies.71  Briefly, DAGs consist of nodes (e.g., treatment, outcome, other variables) presented in 
temporal sequence and connected by arrows, which indicate potential causal pathways.  If there is no arrow connecting 
two nodes, it can be assumed that no causal relationship exists.  Where ‘backdoor’ paths can be identified, estimation of 
causal effects may be biased4.72  For this study a DAG might be drawn as depicted in Figure 1, where: 
 
Z is randomized treatment assignment; 
 
S=1 represents selection (enrollment) into the study; 
 
A is actual treatment receipt (patient adherence to assigned intervention); 
 
Y represents BP-related study outcomes; 
 
L is a vector of observed patient prognostic factors (e.g., age, comorbidities); 
 
U represents a vector of (possibly unmeasured) patient characteristics predictive of adherence to the assigned 
intervention protocol. 
 
 
Figure 1. Directed acyclic graph representing the primary study aims. 
 
For the per-protocol analysis, we are interested in estimating the effect of A on Y (as opposed to the ITT effect of 
randomized assignment Z on Y).  The DAG above shows multiple backdoor paths from A to Y: 1) through L, 2) through 
conditioning on the collider S and then through L, and 3) through U.  To account for these sources of potential bias, we 
will use inverse probability weighting to estimate the per-protocol effect of the telehealth intervention on blood 
pressure outcomes.72,73 
Inverse probability weighting can be used to estimate unbiased measures of effect where selection bias or confounding 
is present, under specific assumptions.74,75  To estimate the per-protocol effect of the telehealth intervention on BP 

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outcomes, we will use a two-stage modeling process.  In the first stage, we will construct logistic regression models for 
1) enrollment, and 2) patient adherence to the assigned treatment.  Candidate variables for inclusion in these models 
will be specified a priori; from these candidate variables, models will be optimized using Lasso selection based on the 
Bayesian Information Criterion.  Individual probabilities of enrollment/adherence can then be calculated based on each 
patient’s vector of covariate values.  Stabilized inverse probability weights will then be calculated, combined (enrollment 
IPW * adherence IPW), and diagnostically evaluated as previously described.75,76   
Based on contextual knowledge and preliminary summaries of the study population, we anticipate that the variables 
listed in Table 1 (in addition to clinic assignment of telehealth vs. best practice) may be associated with enrollment 
and/or treatment adherence.  All will be considered for model inclusion.  Patient-reported outcome measures (PROMs) 
will be available only for patients who are enrolled (and complete a survey), thus, these will be considered for the 
patient adherence model, but not the model for enrollment. 
 
Table 1. Candidate Covariates for Inverse Probability Weight Models for Enrollment and Adherence 
Demographics 
 Age 
 Gender 
 Insurance Status 
 Race/Ethnicity 
 SES 
 Primary Language 
Comorbidities 
 Comorbidity 
Index (e.g., 
Charlson, 
Elixhauser) 
 CVD/CHD 
 CV Risk Score 
 Smoking 
Labs / Vital Signs 
 Baseline BP 
 BMI 
 eGFR 
 Creatinine 
Other 
 BP Meds 
 Med Count 
 Utilization 
 Clinical 
characteristics 
(e.g., % BP 
control) 
 Provider 
characteristics 
(e.g., 
Specialty) 
 Calendar time 
Survey PROMs 
 Self-Rated 
Health 
 Prior BP 
Monitoring 
 Education 
 Employment 
 Life 
Satisfaction 
 Self-Efficacy 
 
 
In the second stage of analysis we will apply the weights to generalized linear regression models to estimate the effect 
of per-protocol treatment on study outcomes.  This model will be restricted to study patients who followed their 
assigned protocol (MTM visit if intervention, no MTM visit if best practice).  By weighting individuals by their inverse 
probability of enrollment/adherence, we essentially create a pseudo-population for analysis, in which factors that were 
unbalanced in those who were enrolled/adherent vs. those who were not are no longer unbalanced.  The effect 
estimate from this weighted model then represents the unbiased effect of actual, per-protocol treatment on BP 
outcomes. 
The validity of inverse probability weighting depends on the assumptions of consistency, positivity, correct model 
specification, and exchangeability.74,75,77  Consistency (the outcome observed for a given patient is consistent with their 
true outcome given their actual treatment status) is generally assumed to hold in this context.76  The positivity 
assumption requires a non-zero probability of receiving every level of exposure (telehealth, best practice) for every 
combination of covariate histories, which can be evaluated empirically.76  If we detect violations (or near-violations) of 
positivity, we will report these in tabular form, attempt to diagnose these as deterministic (a group of patients who 
would never be treated) or stochastic (random zeroes due to insufficient sample size), and implement one or more of 
the following approaches: 1) restrict the study population to patients with some likelihood of receiving  telehealth;77,78 2) 
re-specify the models and/or confounding variables, and/or truncate weights, in an effort to achieve acceptable balance 

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in bias due to nonpositivity vs. confounding;76,78 3) modify the definition of treatment;78 and/or 4) use alternative 
estimation methods which are less sensitive to nonpositivity (e.g., g-computation, g-estimation of structural nested 
models, targeted maximum likelihood estimation).79-82   The potential for model misspecification to bias results can be 
mitigated by conducting a series of sensitivity analyses similar to those demonstrated in Cole and Hernan,76 with the 
objective of optimizing the bias-variance tradeoff. 
Exchangeability refers to the assumption that comparison groups (telehealth vs. best practice) are ‘exchangeable’ with 
respect to distributions of risk factors for outcomes (BP), possibly conditional on measured covariates.76  This 
assumption is more generally recognized as ‘no unmeasured confounding,’ which applies to most epidemiologic studies.  
Although this assumption is untestable, we believe it will be reasonably defensible for several reasons.  First, the model 
for enrollment is likely to be largely dependent on clinic-level treatment assignment and patient clinical characteristics, 
which would have been available to the provider, and will be available for analysis.  Second, although the model for 
treatment adherence is more likely to be driven by factors that are not routinely captured in clinical data, we will have 
several relevant patient-reported survey measures (see Table 1) available for study participants.  Third, we will 
implement bias analyses as well as upper/lower bounds for the per-protocol effect, which will provide a range of 
plausible values under various sets of realistic assumptions to complement the per-protocol effect estimate.83,84 
10.A.3. Power for Aim 1 Analyses  
A power analysis estimated the minimum detectable standardized effect (MDSE) for γ11 in the H1.1 model under a range 
of assumptions about the number of SBP values from each eligible patient and the intraclass correlation (ICC) in SBP 
values due to patients’ receiving care at the same clinics. We used data from patients (age 18-85, diagnosed with 
hypertension, current visit BP ≥ 150/95, most recent previous encounter BP ≥ 150/95, ≥ 1 follow-up visit) seen 5/1/2017 
through 2/28/2018 in the randomized Hyperlink clinics to inform power analysis assumptions. These patients (N=4967) 
had M=3.3 SBP over 10 months (Median=3, range 1-23), index MSBP=159.9, index SDSBP=16.1, all BP MSBP=150.7, all BP 
SDSBP=20.4, and a 3-level variance components model of SBP estimated ICCclin=.003 and ICCpt=.28. For power estimates,  
conservatively assumed n=100 eligible patients in each of 20 clinics, 3 SBP per patient over 24 months and ICCclin=.01-.03 
in a 2-level variance components model.   
Under these assumptions, the H1.1 analysis is powered (80%, α2=.05) to detect γ11<-.124 (when ICCclin = .01) and γ11<-
.174 (when ICCclin=.03) so that an annual reduction in SBP that is 20.4*(.124-.174)=2.53-3.55 mm Hg greater among 
patients in telehealth relative to clinic-based care clinics will be statistically detectable. Based on our previous research 
and systematic reviews, we believe a 5 mm Hg greater reduction in SBP will be achieved in eligible patients in telehealth 
care compared with clinic-based care.19,29,85 We assert that 5 mm Hg is a clinically important reduction in BP that 
substantially lowers the risk of stroke and heart disease, and even smaller reductions of 2 or 3 mm Hg have clinically 
important effects.38-42 The analysis should be sufficiently powered to observe clinically meaningful between-group 
differences in SBP reduction. 
Patient-reported outcomes from the eligibility and 6 month surveys, corresponding to the beginning and end of 
intensive intervention, will be analyzed using the H1.2 model . We conservatively estimate 60% and 75% eligibility and 6 
months response rates.   Relative to the biologically based SBP, we anticipate higher clinic-based variance components 
for PROs (eg, ICCclin=0.02-.03) for PROs. The MDSE comparing 6-month PROs among telehealth relative to clinic-based 
care patients are γ11=.239-.270. We expect to be able to detect 6-month differences of about 4.5 to 6 points (scale range 
= 0-100) on the TQSM (subscale SDs=18.7-22.6) and about 0.25 points (scale range = 1-5; SD=1.0) on the PACIC. For self-
reported outcomes, a between-groups difference of Cohen’s d = .20-.30 is small, consistent with the goal of detecting 
meaningful differences in patient-reported side effects, care experiences, and self-management. 

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10.A.4 Missing data 
Rich pre-enrollment EHR data will enable a detailed assessment of the demographic and clinical characteristics of 
patients who engage in each component of the clinic-based and telehealth care approaches. While the specific reasons 
for engagement, or lack of engagement, are not captured, it will be possible to quantify the likelihood of engagement for 
well-defined segments of the eligible population. Among enrolled patients, the absence of documentation of a care 
process or vital sign in the EHR should not be interpreted as a missing value, but rather as indicative of a care process or 
test not having been performed within the health system. Truly missing observations (e.g., SBP measured, value not 
available) will be extremely rare, undetectable, and assumed to be missing at random (MAR). EHR derived data fields 
will be treated as complete for these reasons.  
The HealthPartners Survey Research Center will employ state-of-the-art methods to minimize unit and item 
nonresponse for patient-reported outcomes. The disposition of each contact attempt to complete a survey will be 
documented by the Survey Research Center. For mailings and email, this includes undeliverable addresses and active 
refusals or volunteered ineligibility due to language that are returned via these modes. For telephone surveys, these 
dispositions include noncontact, refusal, ineligibility, and bad telephone number. For item nonresponse, we expect less 
than 5% missing data on any single item. We will use a fully conditional specification approach to build a multiply 
imputed H1.2 dataset that assumes unobserved values resulting from item-non-response are MAR. The imputation 
model will include all predictors from the H1.2 analytic model as well as EHR-derived auxiliary predictors that may be 
correlated with PROs to improve imputation precision. 
The H1.1 and H1.2 analytic models rely on maximum likelihood approaches to estimate all parameters. These models 
are sufficiently flexible to accommodate unbalanced data (e.g., outcomes per patient, patients per clinic) and rely on 
covariance structures for model estimation so that all available data from the intent-to-treat sample contribute to 
parameter estimation. Mixed models are predicated on a MAR assumption which is all but certain to be met in the case 
of H1.1, and possibly met in the imputed H1.2 dataset.  
Non-random processes such as dislike, subpar implementation, or feelings of pressure to report favorably on a care 
approach model may result in missing PROs, and may differentially operate across study groups. We will thoroughly 
examine all available EHR and survey data fields for relationships with the likelihood of missingness and values of 
available data. These data fields will be included in a series of multiple imputation models that add sensitivity 
parameters that quantify increasingly severe departures from randomness to the imputed values. We will quantify the 
impact of these hypothetical departures on the conclusions drawn from the MNAR imputed datasets and assess the 
plausibility of MNAR processes that would undermine conclusions drawn from assumed-MAR data.86 
 
10.B. Aim 2 Analysis Plan.  
We will compare adoption, implementation, maintenance, and reach over time and between care models using both 
quantitative and qualitative data collected throughout the intervention period.  A “Learning Evaluation” approach 
includes gathering data describing changes and how they are implemented, collecting relevant process and outcome 
data, assessing multi-level contextual factors affecting implementation, supporting sites in using the data to make 
improvements, and developing sustainable measurement strategies.87 Under the guidance of Dr. Crabtree, our study will 
collect data relevant to each component of a Learning Evaluation, and we will use a mixed-methods presentation of our 
data to provide real-time monitoring and feedback to stakeholders to support intervention fidelity and a summary 
assessment of how fully each care model was implemented.88,89 The modality to achieve a systematic and responsive 
evaluation will be “joint reports” organized by components of the RE-AIM framework (adoption, implementation, 
maintenance and reach), produced and distributed monthly over 24 months.90,91 Summary level data describing care 

23 – Version 2018.07 
processes, care outcomes, changes, and contextual factors will be presented in aggregate and by study site. The 
integrated reports will include interpretation and recommendations from our team to each clinic to support 
development of a successful care model, and will be disseminated to stakeholders in webinars and written form. 
Stakeholder feedback will be collected and interpretations adjusted accordingly. Over time, these reports will present a 
historical record of summary-level data, key events and adaptations, recommendations, and assessments of success to 
describe the implementation process and provide sites with a methodological framework to continue improvement in 
BP care in the future. 
Adoption will be described by clinic characteristics (e.g. geographic region, size, patient mix, pre-implementation 
performance metrics), field observation notes (clinic site visits, meeting minutes, and notes on organizational context) 
and interviews with clinicians and clinic leaders about barriers to adoption and willingness to be randomized.  
Implementation and Maintenance will be described by metrics representing elements of the care approach to which 
clinics have been assigned.  Implementation fidelity is expected to be similar for some (eg, BP accuracy, free BP checks, 
repeat elevated BP, re-assessed elevated BP, registry use) while others may be more frequent in one group (clinic-based 
or telehealth). Field observation notes (site visits, chart audits), interviews with clinicians, and patient focus groups will 
provide insights into differences in the metrics, but also perspectives at the clinic and organizational level about the 
implementation and maintenance process itself (eg, barriers or disagreement with the care process, factors promoting 
success, adaptations to clinicians protocols, and description of the care patients report receiving). We will produce key 
aggregate summaries of these data at 12 months (Implementation) and 24 months (Maintenance), along with statistical 
comparison between groups with 95% CIs. 
Reach will be quantified as the proportion and 95% CI of eligible patients who pass through each step of engagement in 
their clinic’s care approach: attend BP check, have uncontrolled BP, follow up with PCP (clinic based) or pharmacist/NP 
(telehealth). We expect similar proportions of patients in each care approach to meet these criteria both monthly and in 
aggregate over 24 months. We will examine eligible patient characteristics for evidence of disparities in Reach, and field 
observations, interviews, and patient focus groups will be examined for barriers to engagement, reasons for any 
disparity in engagement, and potential solutions. 
By the end of the study period, we will have accrued 24 months of integrated data reports that we will use to construct 
recommendations to clinics to continue improvement in BP care. Our final report will include data stratified and 
summarized on several dimensions describing key events over the course of implementation: context (time and setting), 
approach to care models by clinics and clinicians, patient experiences, barriers, objections, and factors promoting 
success. These data will be used to compare how fully each care model was implemented and to recommend strategies 
for clinics to monitor their own progress in improving BP care in the future using standardized reports. 
10.C. Reporting Plan (IR-6).  
Reports of the trial design and outcomes will include sufficient information to allow assessments of the study’s internal 
and external validity. The external validity can be assessed in part by conformity to PRECIS2 criteria, including broad 
eligibility criteria, a real-world health care system setting, enrollment and flexible interventions carried out by clinical 
staff, and follow up conducted without additional research visits.56 Reports of the trial outcome will conform to the 
CONSORT guidelines, including the extensions for patient-reported outcomes and cluster-randomized trials.92-94 
11. Data Management  

24 – Version 2018.07 
The overwhelming majority of data used to assess implementation and test the Aim 1 and 2 hypotheses are derived 
from electronic sources whose primary function is to deliver and document care delivered in a health care setting. Clinic 
staff update missing or invalid values as needed at each clinic encounter. Fields used to characterize patients included in 
the preliminary analyses were virtually 100% populated, with race being the most frequently missing (4%). 
EHR-based data are identified by encounter- and patient-specific (ie, medical record number, MRN) identifiers that link 
information across tables. The study programmer will maintain a crosswalk that associates each MRN with a HIPAA-
compliant random identifier that uniquely identifies patients in the analytic datasets and survey sampling frames.  
 
12. Key Milestones and Timeline 
Below are dates for key study activities. See Appendices J, K and L for full timeline, enrollment timeline, and milestones 
as reported to PCORI. 
12.A. Study Start-up 
• 
Jan 1, 2017: Protocol and research application completed, submitted to IRB 
• 
March 1, 2017: IRB approved study protocol  
• 
Jan-Feb 2017: AMC vendor testing and Epic vitals flowsheet development  
• 
May 2017: Pilot test patient survey 
 
12.B. Enrollment and Interventions 
• 
May-July 2017: Recruitment and training of clinics (site visits to n=20 clinics)  
• 
July 2017: First clinics “go live” with interventions as randomized for Vanguard Phase 
• 
November 2017: Main Trial enrollment begins 
• 
March 1, 2019: Patient enrollment complete 
• 
March 1, 2021: Final Patient Surveys collected (24-months)  
• 
“Implementation Phase” of Interventions (0-12 months): August 2017-July 2018 
• 
“Maintenance Phase” of Interventions (12-24 months): August 2018-July 2019 
• 
Evaluation Reports to clinics: Monthly, September 2017-August 2019 
 
12.C. Key reporting milestones 
• 
Reporting Periods for Interim reports to PCORI: January 1 and July 1 annually, 2017-2021 
• 
DSMB Meetings: Twice annually, August and February 2017-2021 
• 
Patient Advisory and Stakeholder Advisory Board Meetings: Once/quarter, April, July, October and January 
2017-2021. 
 
12.D. Publication and Dissemination  
See below section 16 for details on milestones related to publication and dissemination. 
 

25 – Version 2018.07 
13. Organization 
This study represents a unique collaboration between research organizations, care systems, patient co-investigators and 
advisors, and other interested stakeholders.  The study teams are organized to draw on strengths of all collaborators.  
Collaborators include:  
• 
HealthPartners Institute 
• 
HealthPartners Medical Group, Health Plan, and Pharmacy Departments 
• 
Patient Investigators 
• 
Patient Advisors (from HealthPartners and nationally via Health eHeart Alliance)  
• 
University of California San Francisco and Health eHeart Alliance  
• 
Researchers from Group Health Institute, Robert Wood Johnson Medical School, University of Mississippi 
Medical Center 
• 
Professional representatives from American Society of Hypertension, AMC Health, American Medical 
Association, American Heart Association 
Team members and stakeholders will be arranged around a core team with smaller topic sub-groups that will shift 
according to the study’s needs, and additionally a Patient Advisory Board and Stakeholder Advisory Board that will each 
have some cross-over with the study team. See Appendix I for an org chart of the study team. Scopes of work are 
described below. 
13A. Steering Committee/Core Team.  
The Steering Committee will consist of the Principal Investigator, co-investigators, representatives from each 
subcommittees, and project managers. This group will lead the direction of the study and have leaders of each of the 
below workgroups represented in most research team meetings. Core team meetings occur weekly.  
13.A.1. Clinic Operations workgroup. The Clinic Operations Team will co-develop the intervention workflows for 
patients with hypertension and develop an implementation plan for the two interventions. This team will also review 
clinic performance over time and offer recommendations to the research team about how to best support intervention 
success in the clinics.  
13.A.2 Technology and Informatics workgroup. This team will identify device vendors and develop infrastructure for BP 
telemonitoring and home BP monitoring data transfer into Epic.  This team will also design electronic tools to track 
patient data and ensure consistent intervention processes.  The team will work closely with HP to test and gain approval 
for use of systems and tools developed for the study. 
13.A.3. Measurement and analysis workgroup. The Measurement and Analysis Team will develop and refine measures 
to successfully carry out Aims 1 and 2. Measures will include EHR and claims electronic data, patient-reported data 
collected by surveys, and qualitative data collected by focus groups and field observations. This team will also be 
responsible for developing monitoring reports to clinical partners to support intervention fidelity and assess intervention 
implementation using the RE-AIM model.  
13.A.4. Engagement workgroup. The Engagement Team will work to determine the best ways to engage patients and 
other stakeholders including those on the Patient and Stakeholder Advisory Boards and other stakeholders in order to 
ensure full implementation of the interventions and clear dissemination of results.  

26 – Version 2018.07 
13.B. Patient Advisory Board 
The PAB consists of two patient investigators and 6-9 patient advisors from HealthPartners and Health eHeart Alliance 
(administered at University of California at San Francisco).  The Health eHeart Alliance will facilitate the convening of the 
study PAB and ongoing meetings. Over the course of the project, the PAB will advise the research team about the 
patient perspective on all aspects of the study including: implementation, communication strategies and reporting of 
results.  
Specific key goals for the PAB include: advising on patient reported outcomes, vetting and testing the patient survey, 
advising on communication with patients about the interventions, reviewing interim results and identifying 
opportunities for maximizing the interventions’ “reach” and success in engaging a wide diversity of patients. The PAB 
will advise the study team on disseminating results to a wide variety of organizations and stakeholders, especially 
patients.  
Meetings will take place by teleconference at quarterly intervals following a series of introductory teleconferences. 
There will also be one in-person meeting before the interventions begin for the PAB to give concentrated input on the 
study intervention design. PAB members will be compensated at a rate of $50/hour for each hour of meeting time. 
Payments will be disbursed twice per year from Health eHeart.  
13.C. Stakeholder Advisory Board  
The SAB will consist of representatives from the organizations listed above.  These advisors will be consulted in smaller 
sub-groups for specific feedback on study design, study progress, and dissemination throughout the life of the project. 
We want to ensure our study remains responsive to the needs and priorities of these stakeholders, so the research 
remains practical and relevant when study funds no longer support this work. 
 
Specifically we aim to gather formal input from:  
• 
Clinical stakeholders (physicians, nurses, clinic administration) 
• 
Health plan stakeholders (supplying telemonitoring equipment) 
• 
IS&T stakeholders(supporting Epic and other technical needs for the project) 
• 
External stakeholders (our vendors, professional organizations like American Heart Association, etc) 
 
We will meet with each of these groups of stakeholders on an ongoing basis, and compile twice annual reports to PCORI 
about stakeholder input and response to our project. Groups of stakeholders will be brought together for joint 
discussions as needed to gather the type of input that would benefit from diverse viewpoints. Stakeholder Advisors are 
not compensated for their participation in these meetings, as they are primarily professional colleagues. 
 
14. Human Subjects Protection 
14.A. Protected Health Information and sources of data  
All necessary data to determine study eligibility, conduct the study interventions, and test the study hypotheses among 
n=2000 enrolled patients are derived from (a) the EHR, (b) health plan pharmacy claims, and (c) surveys of eligible 
patients in both study arms. Limited EHR data will include demographics, vital signs, orders, diagnoses, encounters, and 
laboratory data for specified periods.  
Among a smaller group of consenting participants, we will collect focus group data on their experiences receiving BP 
care. Additional qualitative data will be collected using field observations in clinics, short surveys and interviews with 

27 – Version 2018.07 
pharmacists and physicians. These data will be used to assess the impact of study interventions on outcomes. A detailed 
description of the inclusion and exclusion criteria for study subjects can be found in section 4.c. We anticipate accessing 
up to 5000 patient records to achieve n=2000 enrolled patients. 
14.B. Potential risks to subjects 
Potential risks to subjects relate to the treatment of hypertension and consist principally of adverse events related to 
medications, which can potentially be severe or even fatal. However, all treatment in the study in both intervention 
groups is evidence-based and limited to FDA-approved treatment. Although patients in the telehealth group may be 
treated with greater numbers and higher doses of antihypertensive therapy, previous telehealth trials with pharmacist 
or nurse management have not reported greater adverse events in the telehealth group. In the previous telehealth trial 
conducted by this research team there were several more episodes of hypotension in the telehealth group than in the 
usual care group, although this difference was not statistically significant. All such episodes occurred in patients with 
diabetes or kidney disease who had a lower BP treatment goal (<130/80 mm Hg) than is the goal in this study (<140/90 
mm Hg). Therefore, the risks of participating in the study are considered minimal and no greater than those incurred 
through routine treatment of hypertension. We have described below the methods used to minimize this risk.  
Additional risks to patients are also minimal and include principally the risk of violation of confidentiality. Measures to 
minimize these risks are also discussed below. 
Study participants may choose alternative treatments and procedures with their treating clinician. Participants in the 
telehealth group are free to decline telemonitoring or any component of the telehealth care intervention. 
14.C. Adequacy of Protection Against Risks 
14.C.1. Protection of Informed Consent 
14.C.1.a EHR and claims data collection 
We have been granted a partial waiver of documentation of informed consent from the HealthPartners 
Institutional Review Board (IRB) for the collection of electronic health record and claims data following reasons:  
1. The clinic-based care model is considered a standard of care and has not been shown to have any risks 
greater than routine care for hypertension;  
2. The telehealth care intervention has been studied in multiple settings and has not been shown to have 
any risks greater than routine care for hypertension using current guidelines for BP control;  
3. The enrollment of patients by clinic staff in the routine care setting would make it impractical to obtain 
informed consent; and 
4. We will not require special research visits to collect data from participants and will use health data that 
is routinely recorded in the EHR.  
This means that patients will receive care at their clinic according to their clinic’s randomization status and will 
not be aware of any relationship between research and their clinic care for their blood pressure at the time of 
their clinic visit. 
These conditions apply for patients until they are contacted and respond to our mailed survey. Once a patient 
responds to the survey, the 3rd criteria above no longer applies. Therefore we have included a question at the 
end of the survey to request consent to use medical record data. See Appendix H.  

28 – Version 2018.07 
 
14.C.1.b Patient Surveys 
Participants will consent to the surveys through an affirmation demonstrated by the survey completion. The first 
(enrollment) participant survey will be mailed to an individual patient within 1 week of the clinic visit that 
qualified them to be enrolled in this study (see section on surveys). That initial survey mailing will include a cover 
letter explaining the purpose of the survey and why that patient is receiving it. It will include all the elements of 
consent that would normally be included in a consent form, and an explanation that returning or completing this 
survey includes the patient’s agreement that their responses and EHR data related to hypertension can be used 
for research purposes. Patients who are identified and enrolled by Wizard but who are on the HPI Exclusion List 
will not be sent a survey. (See Appendix H for draft survey instrument and other patient materials). 
14.C.1.c. Patient focus groups and HealthPartners employee interviews 
Focus group participants will be recruited from among patients completing surveys. They will undergo a 
documented consent process prior to participating in any focus group. During the recruitment process for 
participation in focus groups they will be told the basic elements of consent (e.g. time required, privacy risks, 
audio recording and transcription, de-identification, incentive, etc). Upon arriving to the focus group, the patient 
will be given time to review the entire consent form and will have an opportunity to sit privately with a research 
coordinator to ask any questions. Only participants who agree and consent to participate will be included in the 
group. Anyone who chooses to decline will be offered an incentive for their time for attending.  
HealthPartners employees who may be interviewed for evaluation purposes will not be asked to sign a formal 
consent because their interviews will be considered part of a continuing process improvement effort in 
partnership with the system stakeholders invested in this project. However, these employees will be assured of 
their privacy and will only be interviewed upon their personal agreement.  
14.C.1.d. HIPAA protections  
In addition to the internal HP Institute policies, HIPAA itself makes specific provision for waiver of authorization 
to use PHI for research recruitment purposes under some specific conditions, all of which this study meets: “For 
research uses and disclosures of personal health identifiers (PHI), an IRB or privacy board may approve a waiver 
or an alteration of the authorization requirement in whole or in part. A complete waiver occurs when the IRB or 
privacy board determines that no authorization is required for a covered entity to use and disclose PHI for a 
particular research project. A partial waiver of authorization occurs when an IRB or privacy board determines 
that a covered entity does not need authorization for all PHI uses and disclosures for research purposes, such as 
disclosing PHI for research recruitment purposes. An IRB or privacy board may also approve a request that 
removes some PHI, but not all, or alters the requirements for an authorization (an alteration).” See: 
http://privacyruleandresearch.nih.gov/pr_08.asp#8 
14.C.2. Protection of safe medical treatment  
All hypertension care provided in the study follows evidence-based guidelines and HealthPartners policies and 
procedures for high-quality care. All staff affected by the study will receive appropriate training, either through 
HealthPartners or by the study team (see section 6). MTM Pharmacists in the telehealth clinics will use an established 
protocol for managing hypertension and other CV risk factors, in accordance with long-standing HealthPartners policy 

29 – Version 2018.07 
and their collaborative practice or supervisory agreements with clinic physicians (see appendices A-C for evidence-based 
treatment guidelines) 
The study will monitor for adverse effects of study interventions by extracting EHR laboratory data on potassium, 
sodium, and kidney function, and diagnoses for hypotension and fainting (see section 15 about data safety and 
monitoring) 
14.C.3. Protection of confidentiality and data security 
In compliance with HIPAA regulations, no personally identifiable health information (PHI) will be shared outside of the 
affiliated covered entities (ACE) without obtaining a data use agreement or business associates agreement. 
HealthPartners Institute and HealthPartners are each one component of a larger organization defined as an ACE under 
HIPAA regulations. This allows researchers at the Institute to use HealthPartners medical records data for purposes such 
as those in this study in compliance with HIPAA regulations (i.e., following the concept of “minimally necessary” use of 
PHI). 
The study team has extensive experience in health services research and clinical research with human subjects, with 
procedures to safeguard privacy and personal information. All study records are protected by:  
• 
Locked storing all paper records in a secure location 
• 
Use of untraceable study ID numbers instead of names wherever possible, and  
• 
Password protection as well as firewalls,  
• 
Strong user login authentication on all electronic devices, and  
• 
Physical security for all electronic devices containing personal information.  
Data will be retained in secure storage following the completion of the study in accordance with Minnesota and federal 
law. We guard against the potential for breach of subject confidentiality through a multi-layered system of data 
protection policies, processes, staff training, software safeguards and physical security measures for both paper and 
electronic data involved in research. 
The following measures will be taken to protect subjects from the risk of breach of confidentiality:  
• 
All data collected in the study will be identified by using a previously assigned arbitrary and unique subject 
identification number to each participant.  
• 
A file containing a link between the study ID and individually identifying information will be maintained at by a 
programmer who is member of the study team through the conclusion of the study.  
• 
A cross-walk table linking the study ID to a patient identity will be destroyed within 6 months after the linked 
databases needed to test study hypotheses are completed.  
• 
All electronic study data will be maintained in a computerized database residing on a username- and password-
protected file-server to which only the researchers involved in the study will have access.  
• 
All study-related paper documents containing individually identifiable information will be maintained in locked 
file cabinets. 
For protection of confidentiality of focus group participants, we will ask participants to maintain the privacy of other 
participants by not sharing others’ information outside of the group as a requirement of participation. However, we will 
also clearly explain in the informed consent the risk of loss of privacy should other participants disregard the instruction 

30 – Version 2018.07 
not to share personal information outside of the group. Any focus group participant can choose to use a pseudonym 
during the focus group, if he or she desires, for this reason.  
To protect the confidentiality of any HealthPartners employees participating in an interview, we will not allow anyone 
outside of the research team to know the identity of those interviewed. All of the protection to electronic data sources, 
described above, also apply to the audio recordings and transcripts. 
14.D. Potential Benefits of the Proposed Research to Human Subjects and Others 
Patients in the study will have no defined personal benefit from participating in this project. Compensation for the time 
to complete surveys and focus groups will be minimal but appropriate according to effort involved with participation. All 
patients receiving a survey following enrollment will receive a small $2 incentive with their mailed baseline survey to 
increase initial response rates. Patients completing a survey by either mail, phone, or online will receive a $10 gift card 
for their time for each survey completed.  Focus group participants will be offered compensation of a $40 gift card for 
their time plus a meal.  
To bolster access of the interventions, some patients may receive transportation assistance to attend a BP check visit to 
become eligible for the study.  Although some patients may receive better management of hypertension as a result of 
the study interventions, no claim of clinical benefit to an individual patient can or will be made. 
14.E. Importance of Knowledge to be Gained 
If this study reveals that telehealth care does not result in improved outcomes, practices and care systems can 
concentrate on optimal implementation of clinic-based care. If telehealth care results in measurably improved 
outcomes, the study results should lead to greater diffusion of similar care models. The long-term goal of improved 
hypertension control is to prevent CV and kidney disease, and uncontrolled hypertension is one of the largest 
contributors to these conditions. 
14.F. Inclusion and accessibility 
By its nature, telehealth stands to serve the purpose of increasing access of care to patients who may have difficulty 
attending clinic visits or adhering to treatment protocols. Therefore we aim to ensure inclusion and accessibility of our 
interventions. This falls under the “reach” measures we describe in Tables 2 and 3.   
14.F.1 Women. The eligible study population of patients with uncontrolled hypertension is roughly 50% female; 
therefore, we expect that at least 50% of the study population will be female as described in the enrollment table.  
14.F.2 Children. People ages 18-20 will be included and eligible if they are under the care of a non-pediatric primary care 
physician. We do not plan to exclude children under the age of 21 if they are receiving adult care, which is standard 
practice at HealthPartners.  
14.F.3 Ethnic and/or racial minorities. The eligible patient population includes about 25% self-identifying people of 
ethnic/racial minorities. We have allocated additional recruitment resources to increase accessibility of research to this 
group and enroll at least 25% ethnic/racial minority patients. We plan to bolster minority inclusion in a number of ways. 
First, we will regularly assess the degree of minority inclusion in our enrolled population. The process measures 
described in section XYZ can be viewed by patient demographic, so where we locate disparities in participation we can 
support clinics in addressing it. For example, by targeting outreach from the hypertension registry to minority patients, 
ensuring follow-up with minority patients who have not attended their intended follow-up visits, and talking specifically 

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with clinics that serve majority patients of ethnic/racial minority about the barriers they are facing in supporting 
patients’ success with BP care. We will provide transportation support as needed, and we will also consult with our 
Patient Advisory Board about meeting the needs of patients of ethnic/racial minority backgrounds.  
14.F.4 Non-English speaking patients. We will also regularly assess access by primary language. We will not be limiting 
enrollment and survey participation to only English-speaking patients. All HealthPartners clinics have interpreter services 
available for in-person clinic visits. Because much of the telehealth intervention is telephone-based, we will encourage 
use of a Language Line or support non-English speaking patients to attend MTM visits in person with support for 
transportation costs from the study. Telemonitoring instructions, other intervention materials, and written surveys will 
be available in English and Spanish. Phone surveys conducted in Spanish will be conducted by bilingual interviewers. We 
will examine feasibility of material translation into other common languages like Somali and Hmong based on the clinics’ 
populations likely to be enrolled.  
14.F.5 Physical Disability. We will support inclusion of patients with physical disability, like vision and hearing 
impairment or disability that limits mobility, by ensuring these patients receive proper follow up and resources 
necessary to communicate with their care team and participate in telehealth.  We have monetary resources to support 
the participation of these patients as needed. 
 
15. Data and Safety Monitoring Plan – Approved by DSMB April 17, 2017 
 
Plan for monitoring study conduct and safety 
 
1. Clinic recruitment, randomization and characteristics of clinics 
 
1.1 Clinic recruitment. Clinics will be eligible to participate if they have a Medication Therapy Management (MTM) 
pharmacist onsite at least one half-day per week and use standardized methods to measure BP with validated 
oscillometric BP monitors. Eligible clinics will be contacted via their leadership and invited to participate if they are 
willing to be randomly assigned to clinic-based care or telehealth care, participate in training, participate in limited data 
collection activities, and receive periodic feedback on implementation of the elements of clinic-based care or telehealth 
care according to their randomized assignment. 
 
Twenty eligible clinics will be identified for randomization into clinic-based or telehealth care. Four clinics will function as 
vanguard clinics. Study algorithms will be implemented in the electronic health record systems of these four clinics prior 
to August 1, 2017. Vanguard clinic staff will have two months to observe how the algorithms modify work flow and offer 
suggestions for improvement. The study team will incorporate changes as needed based on user feedback prior to 
implementing the algorithms in the remaining 16 clinics by November, 2017.  
 
1.2 Cluster randomization. Given the relatively limited number of randomization units, we wish to ensure that clinics are 
not imbalanced across treatment groups on factors related to the primary outcome, the ability to implement the 
intervention or potential treatment modifiers. Stratifying on clinic BP control should ensure that the treatment groups 
are similar with respect to the primary outcome (SBP) at the time the intervention is implemented. Clinic BP control is 
likely related to the how effectively clinical practices that support provision of recommended care are currently 
implemented, so that balance on clinic BP control may also balance factors related to the likelihood that the 
interventions will be implemented successfully. Clinic BP control is correlated with the proportion of clinic patients who 
are members of racial or ethnic minority groups, and with the proportion who have comorbid conditions that complicate 
hypertension treatment, so that balance on clinic BP control may also balance these potential treatment modifiers. An 
added practical consideration to incorporate into the randomization scheme is that the vanguard clinics must be split 
evenly between clinic-based care and telehealth care. 

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We plan to stratify the clinics first into the 4 vanguard and 16 main study clinics.  Participants enrolled in the early 
Vanguard Phase of the study will not be included in the main trial results. Among the main study clinics we will create 2-
4 more small strata of at least 4 clinics each based on the proportion of clinic patients on the hypertension registry 
whose SBP and DBP meet clinical recommendations for control in the month prior to randomization. The study 
statistician will assign the clinics within each stratum equally to clinic-based care or telehealth care based on values of 
randomly generated numbers. The main study clinics in clinic-based care and telehealth care (8 each) should be 
balanced on clinic BP control. However, the simple randomization of the 4 vanguard clinics may perturb the balance in 
clinic BP control that could otherwise be attained through stratified randomization of all 20 clinics. We acknowledge that 
some of the precision gained through stratified randomization may be lost but assert that the opportunity to fine tune 
the algorithms, work flow or user interface will strengthen the intervention sufficiently to counteract this loss.  
 
1.3 Characteristics of randomized clinics. Administrative and hypertension registry data will characterize each 
randomized clinic (e.g., MTM days per week, urban setting,) as well as clinic providers (e.g., n of internal medicine, 
family practice, advance practice; percent female or ethnic / racial minority) and patients (e.g., SBP, DBP, age, gender, 
ethnic composition and privately insured among all patients and those in hypertension registry). These data will be 
captured to represent the characteristics of clinics in the month just prior to randomization.  
 
2. Patient enrollment/accrual  
 
2.1 Patient enrollment status. The population of interest is patients meeting high BP study criteria cared for by 
HealthPartners PCPs at 20 representative primary care study clinics. Very few exclusion criteria are in place to maximize 
the likelihood that study findings are applicable to the population of interest.  
 
We will monitor the characteristics of three patient groups for departures of the study sample from the population of 
interest. “Registry eligible” patients are adult patients with a hypertension diagnosis and elevated blood pressure at the 
time they sought care in a HealthPartners primary care clinic. “Hyperlink eligible” patients are the subset of registry 
eligible patients who also meet study eligibility criteria.  A key tool that the study uses to track enrollment and initiate 
the study interventions is a modified version of an existing “hypertension follow-up order”. This order will be 
automatically generated and populated with default values appropriate to each treatment group for Hyperlink eligible 
patients. Accordingly, the “Hyperlink enrolled” patients are the subset of Hyperlink eligible patients whose provider 
signed a condition-appropriate hypertension follow-up order initiated by the study. The follow-up order only needs to 
be signed by the provider, not necessarily completed by the patient, to be Hyperlink enrolled.  
 
We will rely on Clarity data to identify and characterize patients from all randomized clinics who fall into each of these 
three categories. The Hyperlink algorithms gather Clarity data to calculate and store the fields needed to identify registry 
eligible and Hyperlink eligible patients. Some of these fields will be joined with data from a separate Clarity extract to 
identify Hyperlink enrolled patients and characterize patients in all three categories.  
 
2.2 Patient enrollment. Hyperlink patient enrollment will begin in the vanguard clinics in August, 2017, and in all 20 
clinics for main trial beginning in November, 2017. The study timeline accommodates an 18 month enrollment period so 
that the last Hyperlink patient would enroll in March, 2019. The total targeted main trial enrollment across the 20 clinics 
is N=2000.  
 
We will monitor monthly and cumulative enrollment and calculate the proportion of patients who progress from registry 
eligible to Hyperlink eligible to Hyperlink enrolled, study-wide and by treatment group and clinic. We do not plan to 
institute clinic-specific enrollment targets but we will need a sufficient number of patients from the smaller clinics to 
enroll and contribute data to the primary analysis (n≈50 patients). Similarly, we will need to enroll a sufficient number of 
patients who are members of racial or ethnic minority groups to support the planned secondary analyses that estimate 
treatment heterogeneity. We will consider supplemental recruitment methods should the enrollment rate among 
patients at smaller clinics or among members of racial or ethnic minority groups lag the study-wide enrollment rate.  
 

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2.3 Patient characteristics. Demographic and clinical characteristics of registry eligible, Hyperlink eligible and Hyperlink 
enrolled, in aggregate and by treatment group, will be presented. 
 
3. Intervention implementation 
 
3.1 Intervention implementation fidelity. Reports that rigorously quantify key measures of intervention fidelity within 
three subgroups of patients (Registry eligible, Hyperlink eligible, Hyperlink enrolled) will be prepared using routinely 
collected electronic data captured by the Hyperlink algorithms, through supplemental electronic health record data pulls 
or via patient surveys. Measures of the extent to which clinic infrastructure and policies are implemented will be 
calculated using data from relevant subsets of adult patients in all randomized clinics. The reports will be provided to 
clinic managers and primary care physician chiefs on a monthly or quarterly basis and formatted so that clinic 
performance relative to goals and to other clinics over time may be easily assessed. Table 2 provides more detail 
regarding the denominators, numerators and data sources for each measure. 
 
Reports that document the hypertension care processes that are part of the current standard of care for hypertension 
and common to the interventions delivered in clinic-based care and telehealth care clinics will rely on data from registry 
eligible, Hyperlink eligible or Hyperlink enrolled patients in all randomized clinics. These reports will also be provided to 
clinic leaders on a monthly basis and presented so that time trends in clinic performance relative to goals and other 
clinics are easily assessed. More fine-grained reports that calculate these metrics separately for registry eligible, 
Hyperlink eligible and Hyperlink enrolled patients, and potentially by provider, will be prepared so that the study team 
can work with clinic staff to improve performance as needed.  
 
Reports documenting telehealth care intervention delivery will be prepared using data from Hyperlink enrolled patients 
in the telehealth care clinics. These monthly reports will be provided to clinic staff and provide an opportunity for the 
study team and clinic staff to collaborate on approaches for improving or maintaining intervention implementation.  
 
DSMB members will be asked to review trends in all three sets of measures to identify potential concerns and make 
recommendations to the study team if there is potential for significant unequal benefit to patients in one of the 
treatment arms. 
 
4. Patient outcomes and safety monitoring  
 
4.1 Effectiveness, clinical outcomes. The primary clinical effectiveness analyses will quantify the extent to which there is 
a larger reduction, or less of an increase, in systolic blood pressure in the 12 months following Hyperlink enrollment 
among patients in telehealth relative to clinic-based care clinics. Secondary analyses will address whether similar 
changes are observed in clinical outcomes such as diastolic blood pressure, lipid levels and cardiovascular risk; whether 
antihypertensive or lipid medications are more aggressively managed among telehealth patients; and whether 
telehealth patients are less likely to be current smokers. Table 1 summarizes all primary and secondary outcomes. For 
each clinical outcome, we plan to include all available data in the 24 months following enrollment in the analyses. 
However, effectiveness will be assessed via a comparison of the rate of change in the first 12 months post-enrollment.  
 
All clinical outcomes data will be documented in the electronic health record or the Hyperlink data repository as 
observations accrue. Their immediate availability will make it feasible to check assumptions of the clinical effectiveness 
analyses such as balance on key covariates prior to intervention exposure; the central tendency, variance and 
distribution of clinical outcomes; the number and timing of observations per person; the viability of assuming a linear 
rate of change in outcomes, and how non-linear trends might be addressed; and the magnitude of the design effects 
introduced by cluster randomization and repeated measures within patients. These assumptions can be investigated in 
aggregate as data accrue, and by treatment group or clinic at the DSMB’s request, to inform the conduct of the primary 
effectiveness analyses.  
 
4.2 Effectiveness, patient outcomes. The effectiveness of the clinic-based care and telehealth care interventions at 
improving patient reports of side effects, satisfaction with care and confidence in self-care will be assessed by comparing 

34 – Version 2018.07 
self-reports of these outcomes from patient surveys. Similar to the clinical effectiveness analyses, patient reported 
outcomes (PROs) will be collected at enrollment and then 6, 12 and 24 months later but the contrast of interest is the 
enrollment to 6 month change among telehealth care relative to clinic-based care patients. Missing values resulting from 
non-consent, non-response, loss to follow-up and item non-response increase the likelihood of misestimating PRO 
models. The patient survey sampling frame will include a wealth of demographic and clinical information so that we can 
identify characteristics that are associated with each source of missingness and develop a plan for handling missing data 
(e.g., multiple imputation).  
 
4.3 Equity of patient benefit. The clinic-based care and telehealth care intervention have both been shown effective in 
improving hypertension outcomes. The purpose of this work is to estimate their relative effectiveness in improving 
clinical and patient reported outcomes. It is not expected that either of these approaches will be sufficiently superior to 
the other to warrant developing stopping rules for clinical benefit. Similarly, the anticipated effect sizes are sufficiently 
modest and accrue over a time frame such that stopping the trial early for futility would more likely result in a Type II 
error than offer patients a more beneficial alternative treatment.  
 
4.4 Safety outcomes monitoring. Both interventions have been implemented in primary care settings or systematically 
studied with no evidence of increased likelihood of risk to patients. It is possible nonetheless that incident diagnoses 
related to hypertension and antihypertensive medications (e.g., hypotension / fainting, electrolyte disturbances, renal 
failure) and changes in lab measures indicative of antihypertensive medication (e.g., Na, K, eGFR) may be more evident 
among patients in one of these two treatment groups, or among patients who are exposed to the intervention as 
intended. The electronic health record will document each of these safety outcomes as they occur over the course of the 
study. Because these are more likely to be documented in outpatient than inpatient settings the lag between occurrence 
and documentation will be minimal.  
 
We will periodically extract data (vitals, diagnosis codes, lab results) from the electronic medical records of Hyperlink 
enrolled patients to identify the occurrence of each of these safety outcomes in the year prior to and in the time since 
enrollment. For each outcome and time period, we will calculate the number of events, proportion of patients 
experiencing the event, rate at which events occur or other metrics in a manner appropriate to their distribution. 
Outcomes will be compared across treatment groups and time periods with emphasis on whether there are pre- to post-
enrollment changes that differ across treatment groups. 
 
4.5 Reporting and analysis plan. DSMB meetings will occur semi-annually through the end of the 24 month observation 
period of the last enrolled study participant. We propose that summary data described in the Randomization and 
Enrollment sections of Table 4 be provided to the DSMB for review and discussion in open session at all meetings as data 
become available. Randomization data are clinic-aggregated measures collected prior to randomization. Presenting this 
information in open session should not jeopardize the implementation of the interventions or clinical outcome 
measures. Similarly, Enrollment and Fidelity data will be reviewed by study investigators, and some shared with clinic 
personnel, on a regular basis. Presenting this information in open session will not divulge outcomes information to the 
investigators.  
 
The summaries described in the clinical outcomes section primarily make use of post-enrollment patient outcomes. We 
propose that aggregated summary data, not presented by treatment group or trended across time, be presented in 
open session. Summaries that disaggregate by treatment group or time remain in closed session until the primary 
effectiveness analysis comparing trends from enrollment through 6 months is carried out. Similarly, summaries of PROs 
that provide aggregate information may be presented in open session while those that disaggregate by treatment group 
or time be presented in closed session until the primary effectiveness analysis comparing change in PROs from baseline 
to 6 months by treatment group is carried out.  
 
We propose that the rates at which safety outcomes occur be discussed fully in open session. Investigators could 
meaningfully participate in discussions of how to mitigate differences in risk that may be discovered.  
 

35 – Version 2018.07 
There will be a very limited time frame between the end of the 24 month observation period  and the end of the study 
period. For this reason, we plan to conduct the primary analyses as soon as is feasible without divulging information that 
could threaten internal validity. The data needed to estimate whether SBP trends in the 12 months following enrollment 
differ by treatment group should be available in April, 2020. We propose to prepare these data for analysis as soon as 
they are available so that the planned comparison that estimates the relative effectiveness of these two treatments (not 
the full H1.1 model) can be carried at that time. We would like to present these results in open session at the Spring or 
Fall 2020 DSMB meeting. By the time 12 months of clinical outcomes data are available for all enrolled patients, none of 
the patients will still be participating in any study-related activities. The likelihood that investigator knowledge of these 
findings could contaminate the care that is delivered to patients or their later clinical outcomes is extremely low. 
However, any risks outweigh the benefit that could be gained by discussing patterns in SBP in the year post-enrollment 
among study investigators and with the DSMB, and having time to fully carry out and learn from secondary analyses.  
 
The data needed to carry out the H1.2 analyses comparing change in PROs from baseline to 6 months by treatment 
group will be available in October, 2019. We propose to prepare these data for analysis in early 2020 and present the 
results along with the effectiveness comparison in open session at the Spring, 2020 DSMB meeting. 
 
The data needed to carry out the full H1.1 model estimating SBP trends in the 24 months following enrollment will 
become available in April, 2021, when the 24 month observation period  ends. The 24 month survey data will also be 
available at that time. We plan to carry out the full H1.1 analyses and describe PROs at these later time points in Spring, 
2021.  
 
Table 4. Proposal for reports and analyses to share with DSMB in open and closed sessions.  
Randomization 
clinic characteristics 
treatment, clinic a 
open  
provider characteristics 
treatment, clinic a 
open  
 
 
 
Enrollment 
registry eligible n 
cumulative, monthly; 
aggregate and by treatment, clinic a 
open  
Hyperlink eligible n 
cumulative, monthly; 
aggregate and by treatment, clinic a 
open  
enrolled n 
cumulative, monthly; 
aggregate and by treatment, clinic a 
open  
patient demographics 
enrollment status, treatment, clinic a 
open  
clinical measures at enrollment 
enrollment status, treatment, clinic a 
open  
 
 
 
Fidelity 
infrastructure and policies 
monthly by treatment 
open  
hypertension care processes 
monthly by treatment 
open  
telehealth care processes 
monthly within telehealth 
open  
 
 
 
Clinical outcomes, post-enrollment 
patient covariates (enrollment) 
aggregate, treatment b 
open  
outcome counts 
aggregate 
open  
 
treatment 
closed  
outcome variance 
aggregate 
open  
outcome descriptives 
aggregate 
open  
 
treatment by month 
closed  
 
 
 
Patient reported outcomes, post-enrollment 
outcome counts 
aggregate 
open  

36 – Version 2018.07 
 
treatment, missing mechanisms 
closed  
outcome descriptives 
aggregate  
open  
 
treatment by time 
closed  
 
 
 
Safety outcomes 
diagnoses 
aggregate by time, treatment by time, as 
treated by time b 
open 
lab measures 
aggregate by time, treatment by time, as 
treated by time b 
open 
 
 
 
Primary analyses 
H1.1 12m clinical effectiveness 
treatment by time trend interaction 
enrollment to 12m 
open 
H1.2 PRO change 
treatment by time interaction, B-6m 
open 
H1.1 effectiveness full model 
treatment by time trend interaction 
enrollment to 24m 
open 
Aim 2 PRO maintenance 
12m, 24m descriptives 
open 
 
 
 
a Clinics will be identified by number rather than name. 
b Treatment groups will be identified by random labels rather than “clinic-based” or “telehealth”  
 
 
 
 
16. Publication and Dissemination 
16.A. PCORI Publication Policy  
PCORI’s policy on research project findings indicates we cannot publish “practice guidelines, coverage 
recommendations, payment, or policy recommendations” and shall “not include any data which would violate the 
privacy of research participants or any confidentiality agreements made with respect to the use of data.” The following 
items are outlined in our contract with PCORI. 
16.B. Key Journal Publication Milestones.  
We will adhere to two key publication milestones outlined in our contract with PCORI:  
• 
Design/Methods Paper, published by Nov 1, 2019 
• 
Primary outcomes paper, published by Sept 1, 2021 
We also intend to publish a paper with the baseline characteristics of the clinics and patients, anticipated to be 
published by September 2019, about 6 months after enrollment is completed.  
Given the scope of the project, we will most likely complete several additional manuscripts. Publication of scientific 
findings from the study will proceed in a timely fashion once relevant analyses are complete. 
16.C. Making Research Findings Publicly Available.   
16.D.1. Public Summary of Findings. Besides our primary outcomes paper, we will also produce a summary of 
research findings for patients, consumers and the general public in order to convey our findings in a 

37 – Version 2018.07 
“comprehensible and useful manner to patients and providers in making health care decisions”. PCORI will help 
us develop this summary and ensure it is available in public-access format. 
16.D.2. Public access to Journal Articles. An electronic copy of the final peer-reviewed publication of our 
primary outcomes will be submitted to the National Library of Medicine’s PubMed Central to be made available 
publicly. Costs for this are provided by PCORI. 
16.D. In-Person Presentation(s) and Other PCORI-Initiated Events.  
We will attend PCORI meetings or other events to present research findings as requested by PCORI. Expenses for these 
trips will be covered by PCORI.  
16.E. Manuscript development and authorship.  
The Steering Committee/Core Team will act in the role of a Publication Committee, and will evaluate all proposals for 
manuscripts not specifically enumerated in 6.B. Recognition through authorship will be distributed among the study 
investigators so that all study investigators and team members have equitable opportunity to lead and co-author study 
publications. We will support development of manuscripts by anyone involved with the project as long as the 
appropriate research team members are involved in the writing and review of the manuscript. The publications arising 
from the study should avoid overlap and conflicting representation of study findings. Standards for authorship on study 
publications will adhere to the Uniform Requirements for Manuscripts Submitted to Biomedical Journals of the 
International Committee of Medical Journal Editors (NEJM 1997;336:309-315) and those established by the destination 
journals.   

 
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