Implementing Integrated Diabetes and Hypertension Management in Guatemala Using the HEARTS Model
Phase: NA
Conditions: Diabetes Mellitus, Type 2, Hypertension, Cardiovascular Diseases
Sponsor: University of Michigan

Study Title: Implementing HEARTS in Guatemala 
NCT:  NCT06080451
PI: Dr. David Flood, University of Michigan
IRB Approval Date of Protocol Version:  9/15/2023

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Implementing integrated hypertension and diabetes management using the World Health 
Organization’s HEARTS model: Protocol for a pilot feasibility study in the Guatemalan 
national primary care system  
Principal Investigator: David Flood1-3 
Co-Primary Mentors: Dr. Manuel Ramírez-Zea2 and Dr. Michele Heisler1,4 
Study team: Irmgardt Alicia María Wellmann Castellanos2, José Javier Rodríguez2, Luis 
Fernando Ayala2, Timothy C. Guetterman4, Eduardo Palacios5, Mark D. Huffman6-8, Peter 
Rohloff3,9, Vilma Irazola10 
1. Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA
2. INCAP Research Center for Prevention of Chronic Diseases, Institute of Nutrition of
Central America and Panama, Guatemala City, Guatemala
3. Center for Indigenous Health Research, Wuqu’ Kawoq, Tecpán, Guatemala
4. Department of Family Medicine, University of Michigan, Ann Arbor, Michigan, USA
5. Programa Nacional de Enfermedades Crónicas, Ministerio de Salud y Asistencia Social
(MSPAS), Guatemala City, Guatemala
6. Department of Medicine and Global Health Center, Washington University in St Louis, St
Louis, Missouri, USA
7. Department of Preventive Medicine, Northwestern University Feinberg School of
Medicine, Chicago, Illinois, USA
8. The George Institute for Global Health, University of New South Wales, Sydney,
Australia
9. Division of Global Health Equity, Brigham and Women’s Hospital, Boston,
Massachusetts, USA
10. Institute for Clinical Effectiveness and Health Policy (IECS), Buenos Aires, Argentina
Trial registration: [to be registered on clinicaltrials.gov] 
Protocol version: September 10, 2023 
Funding: National Heart, Lung, And Blood Institute of the National Institutes of Health 
(K23HL161271) and the University of Michigan Caswell Diabetes Institute. 
Competing interests: MDH has pending patents for heart failure polypills. George Health 
Enterprises Pty Ltd (GH) and its subsidiary, George Medicines Pty Ltd, have received 
investment funds to develop fixed‐dose combination products, including combinations of blood 
pressure‐lowering drugs. GH is the social enterprise arm of The George Institute for Global 
Health. 
Contact information: 
David Flood 
dcflood@umich.edu 
Department of Medicine 
University of Michigan 
Ann Arbor, MI 48109 USA 
734-647-2892

 
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TABLE OF CONTENTS 
 
1. 
PROTOCOL SUMMARY ................................................................................................ 3 
2. 
ABBREVIATIONS .......................................................................................................... 4 
3. 
BACKGROUND AND RATIONALE ................................................................................ 5 
4. 
STUDY OBJECTIVE ...................................................................................................... 5 
5. 
METHODS ..................................................................................................................... 6 
5.1. 
Study design ....................................................................................................... 6 
5.2. 
Study setting ....................................................................................................... 6 
5.3. 
Participant eligibility criteria ................................................................................. 9 
5.4. 
Intervention ......................................................................................................... 9 
6. 
OUTCOMES..................................................................................................................12 
6.1. 
Primary outcomes ..............................................................................................12 
6.2. 
Secondary outcomes .........................................................................................13 
7. 
STUDY PROCEDURES ................................................................................................15 
7.1. 
Study overview ..................................................................................................15 
7.2. 
Recruitment and sampling .................................................................................15 
7.3. 
Study visits.........................................................................................................16 
7.4. 
Data collection and management .......................................................................18 
8. 
SAMPLE SIZE CONSIDERATIONS ..............................................................................18 
9. 
ANALYSIS PLAN ..........................................................................................................19 
10. 
DATA AND SAFETY MONITORING PLAN ...................................................................19 
10.1. Adverse event reporting .....................................................................................19 
10.2. Monitoring the study ...........................................................................................20 
11. 
ETHICAL AND OVERSIGHT CONSIDERATIONS ........................................................20 
11.1. Plan for multiple IRBs ........................................................................................20 
11.2. Study coordination with MOH .............................................................................20 
11.3. Potential risks ....................................................................................................20 
11.4. Potential benefits ...............................................................................................21 
11.5. Informed consent ...............................................................................................22 
11.6. Post-trial care .....................................................................................................22 
12. 
DISSEMINATION OF RESULTS AND SCALE-UP PLANNING .....................................23 
13. 
DATA SHARING ...........................................................................................................23 
14. 
REFERENCES ..............................................................................................................24 
15. 
SUPPLEMENTARY FILES ............................................................................................30 

 
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1. 
PROTOCOL SUMMARY 
Background: The HEARTS Technical Package was developed by the World Health 
Organization to address the implementation gap of cardiometabolic care in low- and middle-
income countries. Guatemala is a middle-income country that is currently implementing 
HEARTS. National authorities are interested in exploring how hypertension and diabetes 
management can be integrated in HEARTS implementation. The objective of this study is to 
conduct a feasibility and acceptability pilot trial of integrated hypertension and diabetes 
management based on HEARTS in the publicly funded primary care system in Guatemala. 
 
Methods: A single-arm pilot trial for 6 months will be carried out in 11 Ministry of Health primary 
care facilities starting in August 2023. A planned sample of 100 adult patients diagnosed with 
diabetes (n=45), hypertension (n=45), or both (n=10) will be enrolled. The intervention will 
consist of HEARTS-aligned components: Training health workers on Healthy-lifestyle 
counseling and  Evidence-based treatment protocols; strengthening Access to medications and 
diagnostics; training on Risk-based cardiovascular disease management; Team-based care and 
task sharing; and Systems monitoring and feedback, including implementation of a facility-
based electronic monitoring tool at the individual level. Co-primary outcomes of feasibility and 
acceptability will be assessed using quantitative data, qualitative data, and mixed methods. 
Secondary outcomes include clinical effectiveness (glycemic and blood pressure control), key 
implementation outcomes (adoption, fidelity, usability, and sustainability), and patient-related 
outcome measures (diabetes distress, disability, and treatment burden). Using an 
implementation mapping approach, a Technical Advisory Committee will develop 
implementation strategies for subsequent scale-up planning. 
 
Discussion: This trial will produce evidence on implementing HEARTS-aligned hypertension 
and diabetes care in the MOH primary care system in Guatemala. Results also may inform 
HEARTS implementation efforts in other low- and middle-income countries. 
 
 

 
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2. ABBREVIATIONS 
AEs 
Adverse events 
AIM  
Acceptability of Intervention Measure 
APEASE 
Acceptability, feasibility, effectiveness, cost-effectiveness, side effects 
or unintended consequences, safety, and equity 
CSAT 
Clinical Sustainability Assessment Tool 
DBP 
Diastolic blood pressure 
DDS 
Diabetes Distress Scale 
DHIS2 
District Health Information System 2 
FBG  
Fasting blood glucose 
FIM 
Feasibility of Intervention Measure 
HbA1c 
Hemoglobin A1c 
HEARTS 
Healthy lifestyle counseling, Evidence-based protocols, Access to 
medicines, Risk-based management, Team care and task sharing, and 
Systems monitoring (World Health Organization’s model for the primary 
care management of cardiometabolic diseases) 
INCAP 
Institute of Nutrition of Central America and Panama 
IRB 
Institutional review board 
LMICs 
Low- and middle-income countries 
MOH 
Ministry of Health 
MULTIPleS 
Multimorbidity Illness Perceptions Scale 
NIH 
National Institutes of Health 
ORIO 
Other reportable information or occurrence 
PAHO 
Pan American Health Organization 
PI 
Principal investigator 
PROEDUSA 
Department of Health  Training and Education 
PSAT  
Program Sustainability Assessment Tool 
REDCap 
Research Electronic Data Capture 
SBP  
Systolic blood pressure 
SIAS 
Comprehensive Health Care System 
SIGSA 
Health Management Information System 
TAC 
Technical Advisory Committee 
TICD 
Tailored Implementation in Chronic Diseases 
WHO 
World Health Organization 
 
 
 

 
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3. BACKGROUND AND RATIONALE 
Approximately 80% of the global burden of hypertension and diabetes occurs in low- and 
middle-income countries (LMICs).1 Widespread adoption of evidence-based treatment of these 
diseases in high-income countries contributes to markedly better outcomes than in LMICs, 
where adoption is often limited.2-6 To address this implementation gap, the World Health 
Organization (WHO) developed the HEARTS Technical Package.7 HEARTS is an integrated 
model for the primary care management of cardiometabolic diseases. The model has six 
components: Healthy lifestyle counseling, Evidence-based protocols, Access to medicines, 
Risk-based management, Team care and task sharing, and Systems monitoring. The HEARTS 
components align with successful multicomponent interventions such as the U.S. Kaiser 
Permanente hypertension program.8 HEARTS was designed to be a flexible platform to improve 
cardiometabolic care within national primary care systems. 
 
Through its “Hearts in the Americas” initiative, the Pan American Health Organization (PAHO) 
has spearheaded efforts to implement HEARTS in national health systems throughout the 
Americas region.9 HEARTS implementation projects to date have focused on hypertension as it 
the highest-burden cardiovascular disease risk factor.10 To further its impact, HEARTS can be 
expanded to integrate management of other cardiometabolic diseases such as diabetes.11 The 
HEARTS-D module primarily focuses on clinical diabetes recommendations. Given the diversity 
of health systems where HEARTS is implemented, there is thus a need for generalizable 
evidence on how integrated hypertension and diabetes care can be achieved, scaled, and 
sustained.11 
 
Guatemala is a middle-income country with the highest burden of cardiometabolic diseases in 
Central America.12 An estimated 32.2%4 and 13.1%13 of Guatemalan adults have hypertension 
and diabetes, respectively, and the two diseases account for one-quarter of national deaths.12 
This project builds on prior hypertension control projects in Guatemala by study investigators 
and collaborators in the Ministry of Health (MOH) and PAHO. From 2017-2022, study team 
members implemented a HEARTS-aligned multicomponent hypertension project across MOH 
primary care facilities in 5 of the country’s 22 departments.14-16 In 2021, study team members 
initiated a HEARTS pilot in 6 MOH primary care facilities. Finally, in November 2022, HEARTS 
was officially launched by the MOH and PAHO.17 While HEARTS in Guatemala initially focuses 
on hypertension, national authorities are interested to exploring how diabetes can be integrated 
into ongoing implementation efforts. This trial will pilot the Integrated Hypertension and Diabetes 
Primary Care Model based on HEARTS in the publicly funded primary care system in 
Guatemala. 
4. STUDY OBJECTIVE 
The primary objective of this study is to test the feasibility and acceptability of an integrated 
model  hypertension and diabetes management based on HEARTS in the publicly funded 
primary care system in Guatemala. The terms feasibility can refer to different concepts and 
domains in pilot studies.18 In this protocol, we use the term specifically in reference to 
implementation outcomes. Secondary objectives of this study are to rehearse study procedures 
and to engage with key stakeholders to develop implementation strategies for a subsequent 
scale-up project. 

 
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5. METHODS 
This protocol follows SPIRIT guidelines for clinical trial protocols.19 Guidance on reporting non-
randomized pilot studies, conducting pilot implementation studies and applying mixed methods 
to pilot studies also were applied as appropriate.20,21 
5.1. Study design 
A single-arm pilot trial over 6 months duration will be carried out in 11 Ministry of Health (MOH)-
led primary care facilities. A single-arm design was chosen as most appropriate to evaluate 
feasibility and acceptability and to align with recommendations for pilot projects in the HEARTS 
Implementation Guide.22 
5.2. Study setting 
5.2.1. Participating health facilities 
This study will be carried out in 11 MOH primary care facilities in two health districts (Figure 1). 
The two health districts were selected in consultation with the MOH and PAHO. Each health 
district includes one second-level primary health facility (health center) and referring first-level 
primary health facilities (health posts). A breakdown of these primary care facilities is shown in 
Table 1. Both health districts were sites where the study team previously implemented 
HEARTS-aligned hypertension control projects. The two health districts were purposefully 
selected to represent important areas of diversity in Guatemala across location and ethnicity. 
Neither health district was part of the initial wave of HEARTS implementation in Guatemala (see 
5.1: Context of HEARTS implementation in Guatemala). It was also important that each site had 
motivated MOH leadership.22 The selected health district in Sololá (San Pablo La Laguna) is 
located in the Central Highlands and has a primarily indigenous Maya population. The selected 
health district in Chiquimula (Esquipulas) is located in Eastern Guatemala and has a primarily 
non-Indigenous population. Both health districts have poverty rates of 60-70%23 with large rural 
populations.24 
 

 
7
 
 
5.2.2. Study context 
Most poor patients with hypertension and diabetes in Guatemala depend on the Ministry of 
Health-led system for health care. The MOH system is a national, publicly funded system 
consisting of multiple levels.25 The first two levels are the primary care levels where this project 
will be conducted. Primary care in the MOH system is coordinated by the Comprehensive 
Health Care System (Sistema Integral de Atención en Salud [SIAS]), which is a department in 
the MOH responsible for health service delivery. The National Program for the Prevention of 
Chronic Non-Communicable Diseases and Cancer coordinates hypertension and diabetes 
policies in the MOH.26 
 
The first level of the MOH system are health posts. Health posts are located in rural 
villages, are typically open during business hours on weekdays, and are staffed by 1-2 
auxiliary nurses. Auxiliary nurses are full-time MOH employees and have similar training to 
Figure 1: Map of study setting 
 
Table 1: MOH primary care sites for implementation 
Department 
(health area) 
Health 
district 
Health 
centers, n 
Health 
posts, n 
Location 
Population of 
health district 
Ethnic group 
Sololá 
San Pablo 
La Laguna 
1 
5 
Central 
Highlands 
88,623 
94.5% Maya 
Indigenous 
Chiquimula 
Esquipulas 1 
4 
Eastern 
Guatemala 
55,556 
96.3% non-
Indigenous 
Total 
 
2 
9 
 
 
 

 
8
nursing assistants in the U.S. health care system. Their scope of practice includes a wide 
range of basic preventative and curative primary care services, though auxiliary nurses 
typically do not provide pharmacological management of non-communicable diseases such 
as diabetes or hypertension. 
 
• 
The second level of the MOH system are health centers. Health centers are located in 
urban or semi-urban areas in mid-sized towns, are open 24/7 for emergencies, and are 
staffed by professional nurses, general physicians, physicians-in-training, or a combination 
thereof. Professional nurses have similar training to registered nurses in the U.S. health 
care system, and their scope of practice encompasses that of auxiliary nurses with 
additional responsibility for more complex patient management . Health centers manage 
uncomplicated diabetes or hypertension cases. Available resources typically include oral 
medications and tools for measuring blood glucose and blood pressure. 
 
• 
The third level of the MOH system are hospitals. Hospitals are located in regional capital 
cities and in Guatemala City, are open 24/7, and have additional staffing above health 
centers, including physician specialists. MOH hospitals have both inpatient and outpatient 
services for complex patients. Patients needing insulin therapy, acute inpatient care, or 
specialist management of diabetes or hypertension complications are referred to this level 
of care per the MOH protocols describe below.  
 
Clinical guidelines. The MOH regularly releases clinical guidelines for primary care clinicians in 
Guatemala. The most recent hypertension and diabetes guidelines were released in 2018, were 
updated in 2023,27 and are generally consistent with international guidelines.28 The main 
challenge relating to clinical guidelines in Guatemala is the need for investments to support 
guideline implementation, including staffing, training and supervision, and equipping primary 
care facilities with clinical resources. 
 
Clinical data systems. At present, there is no standardized paper or electronic patient medical 
record in the MOH-led health system. As a result, there is difficulty tracking individual patients 
over time or between health system levels. There is also no official diabetes or hypertension 
registry. The MOH has an electronic tool, the Health Management Information System, that is 
primarily used to monitor patient volume and to manage staffing needs (Sistema de Información 
Gerencial de Salud [SIGSA]). However, the SIGSA system is not designed to capture 
longitudinal patient data, and thus clinicians cannot use the system to provide clinical care with 
information from prior encounters with the health system. 
 
Availability and cost of medications and diagnostics. Guatemalan laws guarantee that health 
care is free of charge at MOH health facilities.25 The MOH thus is responsible for ensuring the 
availability of quality medications and supplies relating to hypertension and diabetes. At the 
primary care level, the most commonly available medications for hypertension are 
hydrochlorothiazide, enalapril, and losartan; the most commonly available medications for 
diabetes are metformin and glimepiride. Tests such as hemoglobin A1c (HbA1c), creatinine, or 
cholesterol are not available at MOH-led primary care facilities, though patients sometimes 
present results obtained at private laboratory facilities. Stockouts of medications and diagnostics 
commonly occur.29 
 
Context of HEARTS implementation in Guatemala. In November 2022, with support from 
PAHO, the Guatemalan MOH committed to participate in the “Hearts in the Americas” 
initiative.17 The MOH plans a stepped implementation of HEARTS across the country. The first 
36 health districts across 6 of 22 departments in the country were enrolled in late 2022 and 

 
9
2023. (“Departments” are first-level political subdivisions in Guatemala and are analogous to 
U.S. states.; each department has an corresponding administrative “health area” in the MOH 
system.) As noted above, neither of the sites in this pilot were included in the initial wave of 
HEARTS implementation in Guatemala. The MOH has committed resources to HEARTS, in 
particular to improve access to medications and supplies. To date, HEARTS implementation in 
Guatemala has focused only on hypertension management at MOH health centers. Diabetes 
management is not currently part of the MOH’s HEARTS strategy. 
5.3. Participant eligibility criteria 
5.3.1. Patient participants 
Inclusion criteria: All non-pregnant adults aged ≥18 years with diagnoses of type 2 diabetes, 
hypertension, or both conditions who present for routine care at participating MOH primary 
health facilities between over a 6-month period will be included (“patient participants”). 
 
Both previously diagnosed and newly diagnosed patients will be eligible. Previously diagnosed 
patients will be identified by MOH primary care clinicians who take medical histories as part of 
routine care. Newly diagnosed patients will be identified by MOH primary care clinicians who 
apply hypertension and diabetes diagnostic criteria from national guidelines.27,28  
 
• 
Diabetes diagnostic criteria for newly diagnosed patients: fasting glucose ≥126 md/dl, 
two-hour post-prandial glucose ≥200 md/dl, HbA1c ≥6.5%. 
• 
Hypertension diagnostic criteria for newly diagnosed patients: include systolic blood 
pressure ≥130 mmHg or diastolic blood pressure ≥80 mmHg. A new hypertension 
diagnosis must be based on the average of at least two measurements performed on 
two separate occasions. 
 
Exclusion criteria: Participants with confirmed or suspected type 1 diabetes or who are pregnant 
will be excluded, as these patients are not managed at MOH health centers or health posts. 
Participants with a prior history of cardiovascular disease will not be excluded. 
5.3.2. Other participants 
All MOH staff (physicians, nurses, auxiliary nurses) and stakeholders on the Technical Advisory 
Committee will be eligible for participation in the implementation assessment of the pilot (“MOH 
participants”). Details on the Technical Advisory Committee members are provided in 7.3.5. 
5.4. Intervention 
We designed the intervention (“Integrated Hypertension and Diabetes Primary Care Model” 
[Modelo Integral de Hipertensión y Diabetes en la Atención Primaria]) based the study team’s 
prior implementation research projects14-16,30,31 and discussions with the MOH and PAHO. Each 
of the components previously has been tested in the study team’s prior hypertension projects, 
but the focus on integrated diabetes management is novel in this project. The intervention 
consists of five HEARTS-aligned components (Figure 2). These components together comprise 
the evidence-based clinical intervention we seek to implement, which we define as: 
“pharmacological and non-pharmacological treatment of hyperglycemia and hypertension in 
primary care.” 
 

 
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5.4.1. Training health workers on hypertension and diabetes management 
This component includes training on healthy-lifestyle counseling, evidence-based treatment 
protocols, and risk-based cardiovascular disease management. Training workshops will be 
conducted for first and second level health workers, including auxiliary nurses, professional 
nurses, and physicians, to provide instruction in standardized screening, diagnostic, and 
treatment protocols for hypertension and diabetes in MOH guidelines.27,28 Initial workshops will 
be divided into two blocks, each lasting two days, in the first month of the project. A refresher 
training session also will be provided in the fourth month of the project. Sessions will be 
delivered separately at each health district’s office headquarters. The sessions will be provided 
separately The training will adapt a curriculum previously used in the study team’s HEARTS-
aligned projects and approved by the Department of Health Training and Education 
(Departamento de Promoción y Educación en Salud [PROEDUSA]), which is the unit in the 
MOH/SIAS charged with continuing medical education. Workshop content will include the 
following topics: an introduction to hypertension and diabetes, diagnostic criteria, use of stepped 
treatment protocols, treatment targets, medication side effects, counseling to promote lifestyle 
changes, motivational interviewing, team-based care, capture and use of electronic patient data, 
and other topics. Participants will knowledge assessments before and after training workshops. 
Of note, MOH treatment targets for diabetes are fasting glucose 70-115 mg/dL, post-prandial 
glucose 70-160 mg/dl, or HbA1c <7.0; MOH treatment targets for hypertension are <130/80 
mm/Hg.28,32,33 
Figure 2: Intervention components 

 
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5.4.2. Team-based care and task sharing 
To implement hypertension and diabetes care in health posts, we will implement a team-based, 
task-sharing care model between auxiliary nurses staffing health posts and prescribing 
clinicians (i.e., physicians or professional nurses) at health centers. This intervention component 
was implemented in the study team’s prior hypertension project and has been approved by the 
MOH.15 Physicians or professional nurses will make initial patient treatment plans. Auxiliary 
nurses working in health posts will implement treatment plans by dispensing medications, 
monitoring glycemic or blood pressure control, and titrating medications under physician 
supervision. Monthly care coordination meetings will be held in-person or remotely at least once 
per month to review patient registries and make recommendations for patients whose 
hypertension or diabetes is not adequately controlled according to MOH guidelines.27,28 In our 
prior projects, monthly meetings have been difficult to operationalize.34 Therefore, we may 
suggest an alternative approach in which auxiliary nurses at health posts communicate with 
physicians at health centers in real-time via text messages or phone calls to make treatment 
changes for uncontrolled patients. 
 
5.4.3. Strengthening access to medications and diagnostics 
We have extensive experience collaborating with the MOH to improve medication procurement 
and logistics at MOH health centers and health posts. In the study team’s hypertension project 
in five departments, nearly 100% availability of key medications was achieved in MOH facilities 
over a course of three years. In the current project, we will expand the scope to improve access 
to diagnostics and medications for diabetes at participating MOH primary care facilities. We will 
coordinate with and train MOH staff on topics that include forecasting demand, seasonal 
budgeting, storage, shipping, and other topics. The focus will be on a small set of MOH priority 
medications and diagnostics. Drugs include antihypertensive medications (i.e., 
hydrochlorothiazide, enalapril, losartan) and oral hypoglycemic agents (i.e., metformin and 
glimepiride). Diagnostics including blood pressure cuffs and monitors, glucometers, lancets, and 
glucose strips. As noted in 5.1.2, all medications and diagnostics are provided freely to patients 
in the MOH. The implementation of a facility-based electronic monitoring tool, described below, 
also functions to improve available of medications and diagnostics by providing enhanced data 
to monitor supply and demand at primary care facilities. 
5.4.4. Facility-based electronic monitoring tool at the individual level 
As described above, there is currently no electronic or paper medical record system in primary 
care in the MOH system. There is also no registry of patients with diabetes or hypertension, and 
thus, it is not possible to monitor patient or population data on diabetes or hypertension 
awareness, treatment, and control in the MOH. To address this gap, the study team previously 
has collaborated with the MOH to pilot the District Health Information System 2 (DHIS2) in 
health centers and health posts. DHIS2 is an open-source, facility-based electronic monitoring 
tool that can monitor key indicators at the individual and aggregate levels.35 We will implement 
the DHIS2 system including both hypertension and diabetes modules in MOH primary care 
facilities. Registries of patients with hypertension and diabetes will be constructed at each MOH 
facilities. The project will provide hardware (e.g., tablets or desktop computers), internet 
connectivity, technical support, and training and supervision of MOH staff. The DHIS2 system 
will be hosted on a centralized server, allowing for trained health workers to enter data and 
monitor patient data in real time. In the WHO classification system for digital health 

 
12
interventions, this intervention component is a healthcare provider intervention focusing on 
client health records.36 
5.4.5. Systems monitoring and feedback of key indicators 
HEARTS requires the use of routine administrative clinical data to monitor key indicators and to 
iteratively improve the quality of hypertension and diabetes care.37 Each month, we will present 
aggregate reports of key indicators using data drawn from DHIS2 to MOH stakeholders at the 
health district (i.e., municipal) and health area (i.e., departmental) levels. The key indicators will 
be the same as the HEARTS-aligned secondary outcomes described below. We will use a suite 
of DHIS2 visualization tools built by PAHO, including maps, graphs, and dashboards. In the 
WHO classification system for digital health interventions, this intervention component is a 
health system manager intervention focusing on facility management.36 Facility-level monitoring 
using DHIS2 will be complemented by ongoing health worker training (5.3.1) and site 
supervision visits (5.3.4). 
6. OUTCOMES 
6.1. Primary outcomes 
Primary outcomes will be feasibility and acceptability as defined in the Implementation 
Outcomes Framework (Table 2).38 These outcomes will be assessed using quantitative data, 
qualitative data, and mixed methods (integrated qualitative and quantitative data). Given the 
study team’s prior experience with HEARTS-aligned projects, the focus of the feasibility and 
acceptability assessments will be on integrating diabetes into the HEARTS model. 
 
Feasibility is the extent to which a new intervention can be successfully carried out in an 
organization.38 Among MOH participants, feasibility will be assessed through the four-item 
Feasibility of Intervention Measure (FIM) questionnaire39 and semi-structured interviews. Among 
patient participants, feasibility will be assessed using enrollment data. 
 
Acceptability is the stakeholders’ perception that a new intervention is agreeable or 
satisfactory.38 Among MOH participants, acceptability will be assessed using the Acceptability of 
Intervention Measure (AIM) questionnaire39 and semi-structured interviews. Among patient 
participants, acceptability will be assessed using follow-up visit data and semi-structured 
interviews. 
 
Table 2: Measures of feasibility and acceptability and their benchmarks 
Measure 
Minimum benchmark 
Feasibility 
 
Feasibility questionnaire (FIM) among MOH participants 
Median ≥3.5a 
Reasons for perceptions of feasibility/infeasibility 
N/A 
Number of patient participants with diabetes enrolled per health 
districtb 
25 
Number of patient participants with hypertension enrolled per 
health districtb 
25  
Acceptability 
 
Acceptability questionnaire (AIM) among MOH participants 
Median ≥3.5a 

 
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Table 2: Measures of feasibility and acceptability and their benchmarks 
Measure 
Minimum benchmark 
Proportion of patient participants with subsequent follow-up 
visit within 3 months (among those enrolled with ≥3 months 
remaining in pilot) 
75% 
Reasons for perceptions of acceptability/infeasibility among 
patient and MOH participants 
N/A 
Reasons for dropouts among patient participants 
N/A 
Primary outcomes in this pilot study are feasibility and acceptability as defined in the 
Implementation Outcomes Framework. aThe FIM and AIM scales range from 1 to 5 with higher 
values implying greater feasibility or acceptability, respectively; scores are averaged within each 
participant. bEnrollment is defined by a patient having at least one clinic visit entered in the 
DHIS2 or equivalent longitudinal medical record system; a given patient may have both diabetes 
and hypertension and thus count toward each benchmark. Abbreviations: AIM: Acceptability of 
Intervention Measure; FIM: Feasibility of Intervention Measure; MOH: Ministry of Health. 
 
6.2. 
Secondary outcomes 
Secondary outcomes include clinical outcomes, implementation outcomes, and patient-related 
outcome measures (Table 3). 
 
Clinical effectiveness outcomes are based on recommended HEARTS monitoring indicators.37,40 
Clinical outcomes are assessed to provide pilot data to key MOH stakeholders and to rehearse 
study procedures rather than to evaluate effectiveness. 
 
Implementation outcomes38 will assess facility-level adoption and the fidelity of implementation 
of each intervention component. 
 
Patient-related outcomes measures relating to diabetes will be conducted to translate and 
validate questionnaires in Guatemalan Spanish and Mayan Kaqchikel. Measures include 
diabetes distress, quality of life, and self-care assessments. We will use validated Spanish or 
professionally translated Mayan language versions of each instrument. These assessments are 
exploratory to refine the study team’s use of these instruments in rural Guatemala. 
 
Table 3: Outcomes and data sources 
Outcome 
Description and data sources 
Primary outcomes 
 
Feasibility 
FIM questionnaires and MOH data from DHIS2 
(quantitative); semi-structured interviews with MOH 
participants (qualitative)  
Acceptability 
AIM questionnaires and MOH data from DHIS2 
(quantitative); semi-structured interviews with patient 
and MOH participants (qualitative) 
Secondary outcomes 
 
Clinical outcomes 
 

 
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Table 3: Outcomes and data sources 
Outcome 
Description and data sources 
Number of patients receiving 
hypertension medication 
treatment per month 
(“hypertension treatment rate”) 
MOH data from SIGSA (quantitative) 
Number of patients receiving 
diabetes medication treatment 
per month (“diabetes treatment 
rate”) 
MOH data from SIGSA (quantitative) 
Proportion achieving glycemic 
control (FBG <115 mg/dl or 
RBG <160 mg/dl) among 
patients with diabetes 
MOH data from DHIS2 (quantitative) 
Proportion achieving control of 
blood pressure (<130/80 
mmHg) among patients with 
hypertension 
MOH data from DHIS2 (quantitative) 
Mean SBP and DBP among 
patients with hypertension 
MOH data from DHIS2 (quantitative) 
Implementation outcomes 
 
Adoption 
Number of participating health facilities, defined as 
having enrolled at least one patient with hypertension or 
diabetes (quantitative); reasons for variation (qualitative) 
Fidelity (health worker training 
on hypertension and diabetes 
treatment protocols) 
Proportion of health workers in each district attending all 
training sessions, chart audit of prescriptions to assess 
guideline concordance (quantitative); reasons for 
variation (qualitative) 
Fidelity (team-based care and 
task sharing) 
Proportion of primary health districts conducting at least 
one care coordination meeting; reasons for variation 
(qualitative) 
Fidelity (access to medicines 
and diagnostics) 
Monthly availability of MOH medications and diagnostics 
(quantitative) and reasons for variation (qualitative) 
Fidelity (facility-based 
electronic monitoring tool) 
Proportion of patient visits captured in DHIS2 each 
month compared to comprehensive records in SIGSA 
(quantitative) and reasons for variation (qualitative) 
Fidelity (systems monitoring 
and feedback) 
Proportion of quarterly reports viewed by health district 
administrators (quantitative) and reasons for variation 
(qualitative) 
Usability (facility-based 
electronic monitoring tool) 
System Usability Scale41,42 (quantitative) and reasons for 
variation (qualitative) 
Sustainability 
Program Sustainability Assessment Tool (PSAT)43,44 and 
Clinical Sustainability Assessment Tool (CSAT),45,46 
select questions 

 
15
Table 3: Outcomes and data sources 
Outcome 
Description and data sources 
Patient-related outcomes measures  
Diabetes distress 
Diabetes Distress Scale (DDS),47,48 2-item screening and 
physician distress subscale 
Disability 
WHO Disability Assessment Schedule (WHODAS 2.0)49 
Multimorbidity treatment 
burden 
Multimorbidity Illness Perceptions Scale 
(MULTIPleS),50,51 treatment burden subscale 
Abbreviations: CSAT: Clinical Sustainability Assessment Tool; DBP: diastolic blood pressure; 
DHIS2: District Health Information System; FBG: fasting blood glucose; MOH: Ministry of 
Health; PSAT: Program Sustainability Assessment Tool; RBG; random blood glucose; SBP: 
systolic blood pressure; SIGSA: Health Management Information System; WHO, World Health 
Organization. 
7. STUDY PROCEDURES 
7.1. Study overview 
A summary of study procedures is shown in Figure 3. 
 
 
7.2. Recruitment and sampling 
This project is embedded in MOH-led standard routine primary care services. All new or existing 
patients with diabetes or hypertension receiving care at the participating MOH primary care 
facilities will be enrolled in the DHIS2 system. Recruitment activities will be carried out that align 
with the routine outreach activities of each MOH health facility; these activities may include 
Figure 3: Schematic of study design 
 

 
16
meetings with local leaders, public posters, and brief announcements on social media platforms 
or the radio. 
 
A subset of patient participants (n=10, of whom n=5 from each health district) will be recruited 
for questionnaire assessments and interviews. These patient participants will be purposively 
selected among individuals who had enrolled in the first two months of the study and had high 
versus low numbers of patient visits (i.e., explanatory sequential mixed methods sampling). 
Study fieldworkers who are not MOH employees will make an initial contact via home visit, 
phone calls, or encounters at MOH health facilities. Participants who express interest in this part 
of the study will then receive a visit by study fieldworks to complete informed consent and 
interview assessments. This visit will occur in the patient’s home or another convenient private 
location, depending on the patient’s preference. 
 
All MOH participants and members of the Technical Advisory Committee will be asked to 
complete a structured questionnaire. The study team will use lists of personnel participating in 
trainings and contacts at each health district to identify MOH participants. Members of the 
Technical Advisory Committee will be recruited using INCAPs local contacts and connections 
from prior projects with the MOH. Subsequently, a subsample of approximately 20 MOH 
participants will be purposively selected for semi-structured interviews based on high versus low 
perceptions of intervention feasibility (i.e., explanatory sequential mixed methods sampling). 
Mixed-methods procedural diagrams are shown in Figure 4. 
 
 
7.3. Study visits  
7.3.1. Baseline visits at primary health care facilities 
At baseline, study staff will visit all participating health centers and health posts to complete a 
baseline needs and readiness assessment based on HEARTS monitoring guidelines and the 
WHO Service Availability and Readiness Assessment tool.22,37,52 Topics covered include 
population served, clinical services offered, available resources, staffing, and other topics 
relating to HEARTS. 
7.3.2. Monthly follow-up visits at primary health care facilities 
Study staff will conduct monthly follow-up visits at each primary health care facility to monitor 
the availability of medications and supplies, review patient registration in the DHIS system, 
assess implementation of collaborative care meetings, and provide support for any 
Figure 4: Mixed-methods procedural diagram 

 
17
implementation issues relating to HEARTS. Study fieldworkers will also maintain a field log with 
notes from primary health facility visits. 
7.3.3. Closing interviews with diabetes patient participants 
Interviews consisting of structured and semi-structured questions lasting approximately 45 
minutes will be carried out with a subsample of approximately 10 patients with diabetes at the 
project’s termination. The focus will be on diabetes, as the study team has conducted extensive 
interviews with hypertension patients in prior HEARTS-aligned projects. The structured portion 
will cover patient reported outcome measures, and the semi-structured portion will cover to 
acceptability and determinants of implementation (i.e., barriers and facilitators). The Tailored 
Implementation in Chronic Diseases (TICD) checklist will guide the semi-structured interviews.53 
Visits will be carried out in-person the patient’s home or another convenient location. Interviews 
will be in Kaqchikel, Tz’utujil, or Spanish. 
7.3.4. Closing interviews with MOH health workers and administrators 
All MOH participants participating in the pilot will be invited to complete a structured 
questionnaire, focusing on feasibility (FIM instrument), sustainability (PSAT/CSAT instrument), 
and usability of the facility-based electronic monitoring tool (System Usability Scale). 
Additionally, a subsample of approximately 20 MOH staff will be purposely selected to 
participate in semi-structured interviews lasting approximately 45 minutes. The TICD checklist 
will guide the semi-structured interviews.53 Interviews may be conducted in-person or virtually. 
7.3.5. Technical Advisory Committee meetings 
We will establish a Technical Advisory Committee to provide high-level coordination with 
national authorities, as recommended in the HEARTS implementation guide.22 The Technical 
Advisory Committee will play a critical role to provide guidance and to plan for future scale-up. 
Members will likely include MOH administrators at the national, departmental, and health district 
levels; physicians and professional nurses working in each health district, representatives of the 
Guatemalan PAHO office, and other stakeholders (10-15 total members). Study staff at INCAP 
will organize meetings every two months during the trial and a post-trial closing meeting. 
Meetings will be conducted virtually and will be recorded for members who cannot attend a 
given session. Written meeting notes also will be shared after each session. 
 
During the meetings, study staff will present project updates for open discussion. Using an 
implementation mapping approach,54 members then will discuss the implementation 
determinants (i.e., barriers and facilitators) that emerge during the trial, design implementation 
strategies to address these determinants, clarify the causal mechanisms through which 
implementation strategies operate, and provide feedback on a consolidated implementation 
package the study team creates after the trial concludes. Study staff will guide discussions of 
implementation strategies using different structured tools: 
• 
The Expert Recommendations for Implementing Change (ERIC) compilation and prior 
mappings of ERIC to lower-middle-income countries will be used as a foundation for 
proposed implementation strategies.55,56 
• 
Guidance from Proctor et al. will be used to specify implementation strategies.57 
• 
The APEASE (acceptability, feasibility, effectiveness, cost-effectiveness, side effects or 
unintended consequences, safety, and equity) tool will be used to prioritize implementation 
strategies.58 

 
18
• 
Causal pathway models will be presented to link implementation strategies, mechanisms, 
and key implementation outcomes.59,60 
7.3.6. Chart audits 
Each week, a data manager will review all new data entered into the DHIS2 system for 
missingness and errors. Physicians on the study team also will perform a clinical audit of at 
least 25% of patient visits. The physicians will use a structured checklist to rate the guideline-
concordance of clinical care and adequacy of data entry. 
7.4. Data collection and management 
Data will be collected using different collection methods. 
 
• 
Clinical data from patient participants will be entered into DHIS2 by MOH health workers 
who provide standard clinical care during routine visits. DHIS2 data are stored on INCAP’s 
server, as approved by the MOH. 
• 
Data from structured assessments will be collected electronically using a cloud-based 
version of REDCap hosted at INCAP. Structured assessments include health facility 
monitoring, chart audits, and questionnaire data from closing interviews with patients and 
MOH staff. Data entry and quality control checks will be performed by study staff on all 
structured data entered into REDCap 
• 
Qualitative data from semi-structured interviews will be collected in the field by a trained 
qualitative researcher on the study team. Other qualitative data will include field notes, 
meeting notes, and study team reflections implementation progress and challenges.61 
Qualitative data will be securely stored on the University of Michigan’s institutional Dropbox 
account with routine back-ups to an encrypted hard drive. 
8. SAMPLE SIZE CONSIDERATIONS 
Primary health facilities. The sample of health facilities will include nine health posts and 2 
health centers for a total 11 primary health facilities. No formal sample size calculation was 
performed.62,63 This sample of health facilities and population size of pilot health districts is 
consistent with recommendations in the HEARTS Implementation Guide.22 
 
Table 4: Semi-structured interview sample 
Actor 
Numbera 
Participants with diabetes 
10 
MOH physicians or physicians-in-training 
4 
MOH professional nurses 
4 
MOH auxiliary nurses 
10 
MOH administrators 
2 
Total 
30 
aThe interview sample will be stratified by sex (target of 50% men and women by actor) and by 
health district (target of 50% from each health district). 
 
Patient participants. The target sample of patient participants will be approximately 100 
individuals, or 50 participants per health district. Based on the study team’s prior experience, the 

 
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anticipated breakdown is n=45 patients with hypertension only, n=45 with diabetes only, and 
n=10 patients with both hypertension and diabetes. However, it is possible that the improved 
clinical services may attract a greater number of patients to MOH care than anticipated for the 
pilot. Of these, a subsample of 10 participants with low versus high retention levels (defined by 
number of clinical visits within the study time period) will be selected for semi-structured 
interviews at the close of the study. To improve understanding of how diabetes can be 
integrated into the HEARTS hypertension primary care model, we will purposely sample patient 
participants with diabetes. 
 
MOH participants. The anticipated sample of MOH participants working to implement HEARTS 
will be approximately 50 participants. Of these, a subsample of 20 will be selected for semi-
structured interviews at the close of the study using the breakdown shown in Table 4. 
 
Including patient and MOH participants, a total of 30 semi-structured interviews are planned to 
achieve thematic saturation.64,65 The interview sample will be sex-stratified with a target of 50% 
men and women by actor. Interviews will be analyzed as they are conducted, and more may be 
added if saturation is not achieved.66 
9. ANALYSIS PLAN 
Quantitative analysis: Questionnaire data will be analyzed using descriptive statistics. Clinical 
data will be analyzed using multilevel linear and logistic regression models of individual-level 
data adjusting for clustering of participants within primary health facilities. Sociodemographic 
variables such as age, sex, education level, and other characteristics may be explored in 
regression models if sample sizes permit. Stata will be used for quantitative analyses. 
 
Qualitative analysis: Semi-structured interviews will be recorded and analyzed in Spanish using 
qualitative directed-content analysis.67,68 We will only transcribe recordings if the interview were 
undertaken in a Mayan language (Kaqchikel or Tz’utujil), in which cases professional linguists 
will translate and transcribe into Spanish for analysis. Constructs from the Tailored 
Implementation in Chronic Diseases checklist will guide qualitative coding.53 Two members of 
the research team proficient in Spanish will independently code transcripts, and the PI will 
reconcile differences. 
 
Mixed methods analysis of primary outcomes: Quantitative and qualitative findings of primary 
outcomes will be integrated using joint displays, which are a mixed-methods visual technique.69 
Joint displays will show quantitative data next to illuminating participant quotes. Examination of 
quantitative, qualitative, and mixed-methods data will permit the study team to draw meta-
inferences regarding the projects’ feasibility and facilitate future implementation planning. 
10. DATA AND SAFETY MONITORING PLAN 
10.1. 
Adverse event reporting 
Because the proposed research is considered no more than minimal risk, adverse events (AEs) 
related to the proposed strategies are not anticipated. The intervention in this study is focused 
on improving standard-of-care treatment of diabetes or hypertension delivered by the MOH 
health workers in MOH facilities. Therefore, it will be the responsibility of the MOH staff to 
provide care for patient participants who experience an adverse event (e.g., hypotension, 
hypoglycemia, or other adverse drug effects as noted in 11.3) to manage these patients 
according to MOH protocols. In our reporting role, the study team will review from MOH records 

 
20
all serious AEs, unanticipated problems, and other reportable information or occurrence (ORIO) 
using an event form and reported using to the University of Michigan IRB using the standard 
timetable and grading scale, consistent with federal guidelines.70 
10.2. 
Monitoring the study 
The study team will conduct monthly scheduled assessments of study recruitment, data integrity 
and quality, adverse events, withdrawals, and compliance with protocol. Research staff and 
MOH staff will be instructed to report in person or by telephone all complaints, protocol 
deviations, or unanticipated problems to the study coordinators. The study coordinator will be 
charged with gathering necessary information from this initial report and contacting the PI at the 
time of the event. No interim analyses are planned. The trial will not employ stopping rules or a 
Data Safety Monitoring Board because the study carries no more than minimal risk to 
participants. If there is available funding and the study investigators and Technical Advisory 
Committee think there would be potential benefit in extending the pilot trial, then an extension to 
may be considered (e.g., from 6 months to 12 months in duration). 
11. ETHICAL AND OVERSIGHT CONSIDERATIONS 
11.1. 
Plan for multiple IRBs 
For this project, the study team will pursue ethics approval from the IRB of the Ministry of Health 
in Guatemala, as well as the IRBs at INCAP and the University of Michigan. Protocol revisions 
will be submitted for approval by all three IRB committees. 
11.2. 
Study coordination with MOH 
This study will be tightly coordinated with the MOH and other authorities through Technical 
Advisory Committee (TAC) meetings (Section 8.1.5). 
11.3. 
Potential risks 
This study involves a multilevel, multicomponent intervention to improve standard care of 
hypertension and diabetes at MOH primary care facilities in Guatemala. All clinical care will be 
provided in accordance with existing MOH protocols, by MOH health workers, in MOH-operated 
primary health facilities. There is no control arm. Participants include both patients receiving 
standard care and MOH staff who deliver or supervise standard care. The risks in participating 
in this study are no more than minimal because the probability and magnitude of harm or 
discomfort are not greater than those ordinarily encountered in routine daily life: 
 
Psychological risks: Participants invited to participate in structured and semi-structured 
interviews may experience minor stress or discomfort answering certain questions. An example 
of a potentially uncomfortable topic for MOH participants may include interview questions 
relating to the quality of MOH care. An example of a potentially uncomfortable topic for patient 
participants might be questions about medical history, quality of life, or experiences of 
discrimination or abuse in the health system. We will protect against this risk by reminding 
participants that they can skip questions or end interview participation at any time. All research 
staff will complete and provide proof of completion of appropriate human subjects protection 
training approved by their home institution. 
 

 
21
Risk of lost personal productivity due to the time burden of participation: Structured and semi-
structured interviews are structured to last 45 minutes but may last 60 minutes or longer. 
Participants invited to participate in these interviews may perceive this time involvement to be a 
burden interfering with their other responsibilities. We will protect against this risk by offering 
flexible appointments for interviews, including on evenings or weekends. The study team also 
will be available to coordinate study visits at participants’ homes or another private location 
requested by participants. 
 
Loss of confidentiality risks: There is the unlikely risk of accidental disclosure of confidential 
data. Currently, Guatemala does not have a specific national regulation on electronic medical 
records or telemedicine cybersecurity.71 To protect against breach of confidentiality, all non-
clinical patient data will be maintained using a unique study identification. Structured data will be 
securely collected using REDCap on an encrypted tablet and stored on INCAP’s secure cloud 
server. Qualitative data from semi-structured interviews will be collected using an encrypted 
mobile device and stored on the University of Michigan’s institutional Dropbox account. An 
electronic spreadsheet with the unique identification numbers will be maintained on the U-M’s 
institutional Dropbox account, and only the PI and study coordinators will have access. Clinical 
patient data usually will be entered into the DHIS2 tool by MOH staff during routine clinical 
visits. Some MOH primary facilities may choose an asynchronous strategy in which patient data 
are collected using paper records and entered into DHIS2 after the routine clinical visit. These 
paper forms will be stored in a locked filing cabinet in a locked room at the MOH facility. The 
DHIS2 system will be hosted on an INCAP’s secure cloud server. Password-access to DHIS2 
will be restricted to relevant MOH staff, the PI, and study coordinators. 
 
Physical risks to patient participants: A potential risk to blood glucose collection might include 
adverse response to a capillary blood draw, including lightheadedness, minor bleeding, or 
infection at the lancet site. A potential risk to patients receiving diabetes or hypertension 
medication treatment might include hypotension, hypoglycemia, or other adverse drug effects 
that have previously been described. To protect against these risks, all patients enrolled in the 
trial who experience these symptoms will be managed at the nearest MOH facility by MOH 
health workers according to national guidelines. This risk will be no higher than standard care 
because prescriptions will be made by MOH health workers using available medications with 
known, widely accepted safety profiles. The antihypertensive medications used by MOH health 
workers in primary health facilities include hydrochlorothiazide, enalapril, and losartan. The 
glucose-lowering agents used by MOH health workers include metformin and glimepiride. 
Insulin, which confers a higher risk of hypoglycemia, will not be used in this study because it is 
not available in MOH health centers or health posts. 
11.4. 
Potential benefits 
Patient participants will benefit from improved hypertension and diabetes services at MOH 
primary health facilities. Based on MOH guidelines, tangible patient benefits include free access 
to oral antihypertensive and glucose-lowering medications, glucose and blood pressure 
monitoring, receipt of care from health workers who have received additional training in 
hypertension and diabetes, and other benefits. 
 
MOH participants will benefit mostly indirectly from this project through their altruism in helping 
to improve the implementation of hypertension and diabetes care in Guatemala. They also will 
receive training on clinical management of these diseases, which may contribute to their job 
satisfaction and professional development. 

 
22
11.5. 
Informed consent 
11.5.1. Patient participants receiving MOH standard clinical care 
Informed consent will not be obtained from patient participants receiving routine care at MOH 
primary care facilities. A waiver of informed consent is justified because the research meets all 
five required criteria in the revised Common Rule.72 
 
1. The research involves a single-arm trial of improving the implementation of standard 
care in the MOH, and as such the trial confers no more than minimal risk. 
2. The research could not practicably be carried out without an informed consent waiver. 
There are a few reasons why this is the case. The intervention to be tested will be 
embedded in standard care across 11 geographically distant MOH primary health 
facilities. It is not feasible to hire full-time study staff to be physically present at all health 
facilities to consent potentially eligible patients. There is no appointment system in the 
MOH, so it would not be practical to coordinate patient clinical encounters with visits 
from study staff. It would not be ethically practical to restrict access to MOH standard 
care based on the availability of study staff to consent patients. 
3. This research requires identifiable private information because a key component of the 
intervention is the implementation of a health facility monitoring tool with individual-level 
data used in routine care by MOH clinicians. As such, the research could not be 
practicably carried out without using such information or biospecimens in an identifiable 
format. 
4. The research will not adversely affect the rights and welfare of patient participants 
receiving routine MOH-led care. 
5. Participants and their clinicians will be provided with pertinent written information during 
the trial. This information will include instructions on how patient participants can contact 
study staff to request that their data not be included in research outputs of the project. 
11.5.2. Patients and MOH staff participating in interviews 
Verbal consent will be obtained from participants interviewed at the study conclusion and from 
stakeholders participating in the Technical Advisory Committee and. A study staff will read the 
consent script, which explains the purpose of the study, mentions that ongoing clinical care (in 
the case of patients) or employment (in the case of MOH participants) is not conditional on 
participation in the study, and reiterates that there will be no repercussions for declining to 
participate in the study. Verbal consent procedures will occur in the language of the participant’s 
choosing. All MOH participants speak Spanish proficiently, but some patient participants may 
prefer a Mayan language. In lieu of written documents in Mayan languages, we will use 
extensive preparatory practice sessions to ensure smooth contemporaneous translation from 
Spanish to Mayan. This is the method that we have used in Guatemala for many years on 
numerous prior projects, including large projects funded by NIH. Once verbal informed consent 
is obtained, the study staff member will record the date of verbal consent on the informed 
consent form, sign the form, and provide a copy of the form to the participant either as a 
physical copy (in-person interviews) or an electronic copy (virtual interviews). 
11.6. 
Post-trial care 
This trial is embedded in standard MOH primary care. All patient participants will be able to 
continue receiving diabetes or hypertension care according to national standards after the study 

 
23
closes. Depending on patient volume and logistics in the MOH, some health posts participating 
in the trial may refer patients to health centers for continuation of care. 
12. DISSEMINATION OF RESULTS AND SCALE-UP PLANNING 
Project results will be shared through a structured dissemination strategy that includes the 
following components: 
 
• 
Information about this study will be shared via timely registration, updates, and results 
reporting on ClinicalTrials.gov. 
• 
Project results will be shared with patient and MOH participants through a meeting in 
each health district at the end of the project. MOH stakeholders will also have results 
disseminated through the TAC. 
• 
The investigators will disseminate findings at academic research conferences and in 
peer-reviewed journal articles. Open access journals will be prioritized for publication. 
Eligibility for authorship on academic products will be guided by International Committee 
of Medical Journal Editors guidelines. 
• 
A non-technical report in Spanish and English will be prepared and shared with 
representatives from the MOH, PAHO, and INCAP’s Board of Directors (who include the 
Ministers of Health of the eight countries of the Central American region). This report will 
include an implementation toolkit for integrated hypertension and diabetes care. 
• 
Findings also will be disseminated through established non-communicable disease 
research and policy networks in which INCAP participates. 
 
The study investigators and HEARTS stakeholders also will use results for implementation and 
scale-up planning. Issues to be considered will be a phased versus national approach, funding, 
how to incorporate implementation strategies into operative plans, and other topics outlined in 
the HEARTS Implementation Guide.22 It also will be important to consider research designs to 
balance causal estimates while balancing ethical and practical considerations of HEARTS 
implementation in the Guatemalan context.73 
13. DATA SHARING 
This project will produce multiple types of data, including patients’ clinical information, health 
facility assessments, and structured and semi-structured interviews. Deidentified data, analytic 
code, and data dictionaries will be made available on the NHLBI BioLINCC data repository 
(https://biolincc.nhlbi.nih.gov/) after the study concludes. Semi-structured interview transcripts 
and structured questionnaire data will not be shared due to privacy concerns and risk for re-
identification. 

 
24
14. REFERENCES 
1. 
Thomas H, Diamond J, Vieco A, et al. Global Atlas of Cardiovascular Disease 2000-
2016: The Path to Prevention and Control. Glob Heart 2018; 13(3): 143-63. 
2. 
Murray CJL, Aravkin AY, Zheng P, et al. Global burden of 87 risk factors in 204 countries 
and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. 
The Lancet 2020; 396(10258): 1223-49. 
3. 
Yusuf S, Rangarajan S, Teo K, et al. Cardiovascular risk and events in 17 low-, middle-, 
and high-income countries. N Engl J Med 2014; 371(9): 818-27. 
4. 
Zhou B, Carrillo-Larco RM, Danaei G, et al. Worldwide trends in hypertension 
prevalence and progress in treatment and control from 1990 to 2019: a pooled analysis of 1201 
population-representative studies with 104 million participants. The Lancet 2021. 
5. 
Flood D, Seiglie JA, Dunn M, et al. The state of diabetes treatment coverage in 55 low-
income and middle-income countries: a cross-sectional study of nationally representative, 
individual-level data in 680 102 adults. Lancet Healthy Longev 2021; 2(6): e340-e51. 
6. 
Marcus ME, Manne-Goehler J, Theilmann M, et al. Use of statins for the prevention of 
cardiovascular disease in 41 low-income and middle-income countries: a cross-sectional study 
of nationally representative, individual-level data. Lancet Glob Health 2022; 10(3): e369-e79. 
7. 
WHO. Hearts: Technical package for cardiovascular disease management in primary 
health care. Geneva: World Health Organization, 2016. 
8. 
Jaffe MG, Lee GA, Young JD, Sidney S, Go AS. Improved blood pressure control 
associated with a large-scale hypertension program. JAMA 2013; 310(7): 699-705. 
9. 
Ordunez P, Campbell NR, Giraldo Arcila GP, et al. HEARTS in the Americas: 
innovations for improving hypertension and cardiovascular disease risk management in primary 
care. Rev Panam Salud Publica; 46, mayo 2022 Special Issue HEARTS 2022. 
10. 
Yusuf S, Joseph P, Rangarajan S, et al. Modifiable risk factors, cardiovascular disease, 
and mortality in 155 722 individuals from 21 high-income, middle-income, and low-income 
countries (PURE): a prospective cohort study. Lancet 2020; 395(10226): 795-808. 
11. 
Flood D, Edwards EW, Giovannini D, et al. Integrating hypertension and diabetes 
management in primary health care settings: HEARTS as a tool. Rev Panam Salud Publica 
2022; 46: e150. 
12. 
Institute for Health Metrics and Evaluation. GBD Compare | Viz Hub. 2023. 
https://vizhub.healthdata.org/gbd-compare/ (accessed April 10, 2023). 
13. 
International Diabetes Federation. IDF Diabetes Atlas, 10th edition: International 
Diabetes Federation, 2021. 
14. 
Fort MP, Paniagua-Avila A, Beratarrechea A, et al. Stakeholder Engagement in the 
Translation of a Hypertension Control Program to Guatemala's Public Primary Health Care 
System: Lessons Learned, Challenges, and Opportunities. Glob Heart 2019; 14(2): 155-63. 

 
25
15. 
Paniagua-Avila A, Fort MP, Glasgow RE, et al. Evaluating a multicomponent program to 
improve hypertension control in Guatemala: study protocol for an effectiveness-implementation 
cluster randomized trial. Trials 2020; 21(1): 509. 
16. 
Fort MP, Mundo W, Paniagua-Avila A, et al. Hypertension in Guatemala's Public Primary 
Care System: A Needs Assessment Using the Health System Building Blocks Framework. BMC 
Health Serv Res 2021; 21(1): 908. 
17. 
Pan American Health Organization. Implementarán iniciativa Hearts para la prevención y 
el control de las enfermedades cardiovasculares (ECV) en Guatemala. 2022. 
https://www.paho.org/es/noticias/11-11-2022-implementaran-iniciativa-hearts-para-prevencion-
control-enfermedades (accessed May 15, 2023). 
18. 
NCCIH. Pilot Studies: Common Uses and Misuses. 
https://www.nccih.nih.gov/grants/pilot-studies-common-uses-and-misuses (accessed June 14, 
2023). 
19. 
Chan AW, Tetzlaff JM, Gotzsche PC, et al. SPIRIT 2013 explanation and elaboration: 
guidance for protocols of clinical trials. BMJ 2013; 346: e7586. 
20. 
Lancaster GA, Thabane L. Guidelines for reporting non-randomised pilot and feasibility 
studies. Pilot Feasibility Stud 2019; 5: 114. 
21. 
Aschbrenner KA, Kruse G, Gallo JJ, Plano Clark VL. Applying mixed methods to pilot 
feasibility studies to inform intervention trials. Pilot Feasibility Stud 2022; 8(1): 217. 
22. 
WHO. HEARTS Technical package for cardiovascular disease management in primary 
health care: implementation guide. Geneva: World Health Organization, 2018. 
23. 
Instituto Nacional de Estadística. Encuesta Nacional de Condiciones de Vida 2014 
(ENCOVI): Principales resultados. Guatemala, Central America: Instituto Nacional de 
Estadística, 2015. 
24. 
Instituto Nacional de Estadística Guatemala. Resultados del XII Censo Nacional de 
Población y VII de Vivienda: Principales Resultados Censo 2018. 2019. 
https://www.censopoblacion.gt/archivos/Principales_resultados_Censo2018.pdf (accessed May 
29, 2023). 
25. 
Avila C, Bright R, Gutierrez J, et al. Guatemala Health System Assessment, August 
2015. Bethesda, MD: Health Finance & Governance Project, Abt Associates Inc., 2015. 
26. 
Ministerio de Salud Pública y Asistencia Social. Plan estratégico nacional para la 
prevención de enfermedades no transmisibles 2015-2020. Guatemala City, Guatemala: 
Comisión Nacional para la Prevención de Enfermedades Crónicas no Transmisibles y Cáncer, 
2016. 
27. 
Ministerio de Salud Pública y Asistencia Social/Guatemala. Lineamientos para 
implementar intervenciones v seleccionar medicamentos para atender las morbilidades de 
enfermedades cronicas no transmisibles. Guatemala City: MSPAS, 2023. 

 
26
28. 
Ministerio de Salud Pública Asistencia Social. Normas de Atención Salud Integral Para 
Primero y Segundo Nivel 2018: MSPAS, 2018. 
29. 
Anson A, Ramay B, Esparza AR, Bero L. Availability, prices and affordability of the 
World Health Organization’s essential medicines for children in Guatemala. Global Health 2012; 
8. 
30. 
Chary A, Greiner M, Bowers C, Rohloff P. Determining adult type 2 diabetes-related 
health care needs in an indigenous population from rural Guatemala: a mixed-methods 
preliminary study. BMC Health Serv Res 2012; 12(1): 476. 
31. 
Flood D, Mux S, Martinez B, et al. Implementation and Outcomes of a Comprehensive 
Type 2 Diabetes Program in Rural Guatemala. PLoS One 2016; 11(9): e0161152. 
32. 
Ministerio de Salud Pública y Asistencia Social/Guatemala. Algoritmo para el manejo de 
los enfermos con diabetes mellitus, 2021. 
33. 
Ministerio de Salud Pública y Asistencia Social/Guatemala. Algoritmo para el manejo de 
los enfermos con hipertensión arterial, 2021. 
34. 
Paniagua-Avila A, Shelton RC, Guzman AL, et al. Assessing the implementation of a 
multi-component hypertension program in a Guatemalan under-resourced dynamic context: An 
application of the RE-AIM/PRISM extension for sustainability and health equity. Res Sq 2023. 
35. 
Nigeria Ministry of Health, University of Oslo, WHO Nigeria, Resolve to Save Lives. 
DHIS2 Package for Hypertension Control Programs. https://s3.eu-west-
1.amazonaws.com/content.dhis2.org/Publications/DHIS2+for+Hypertension+Control+Programs.
pdf (accessed February 4, 2023). 
36. 
World Health Organization. Classification of digital health interventions v1. 0: a shared 
language to describe the uses of digital technology for health: World Health Organization, 2018. 
37. 
WHO. HEARTS Technical package for cardiovascular disease management in primary 
health care: systems for monitoring. Geneva: World Health Organization, 2018. 
38. 
Proctor E, Silmere H, Raghavan R, et al. Outcomes for implementation research: 
conceptual distinctions, measurement challenges, and research agenda. Adm Policy Ment 
Health 2011; 38(2): 65-76. 
39. 
Weiner BJ, Lewis CC, Stanick C, et al. Psychometric assessment of three newly 
developed implementation outcome measures. Implement Sci 2017; 12(1): 108. 
40. 
WHO. HEARTS-D: Diagnosis and management of type 2 diabetes. Geneva: World 
Health Organization, 2020. 
41. 
Brooke J. SUS-A quick and dirty usability scale. Usability evaluation in industry 1996; 
189(194): 4-7. 
42. 
Sevilla-Gonzalez MDR, Moreno Loaeza L, Lazaro-Carrera LS, et al. Spanish Version of 
the System Usability Scale for the Assessment of Electronic Tools: Development and Validation. 
JMIR Hum Factors 2020; 7(4): e21161. 

 
27
43. 
Program Sustainability Assessment Tool v2. 2013. https://sustaintool.org/wp-
content/uploads/2016/12/Sustainability-ToolV2_w-scoring_12.11.13.pdf (accessed April 25, 
2023). 
44. 
Luke DA, Calhoun A, Robichaux CB, Elliott MB, Moreland-Russell S. The Program 
Sustainability Assessment Tool: a new instrument for public health programs. Prev Chronic Dis 
2014; 11: 130184. 
45. 
Clinical Sustainability Assessment Tool. 2019. https://sustaintool.org/wp-
content/uploads/2020/01/CSAT-tool-and-scoring_1.14.20.pdf (accessed April 26, 2023). 
46. 
Malone S, Prewitt K, Hackett R, et al. The Clinical Sustainability Assessment Tool: 
measuring organizational capacity to promote sustainability in healthcare. Implement Sci 
Commun 2021; 2(1): 77. 
47. 
Polonsky WH, Fisher L, Earles J, et al. Assessing psychosocial distress in diabetes: 
development of the diabetes distress scale. Diabetes Care 2005; 28(3): 626-31. 
48. 
Fisher L, Glasgow RE, Mullan JT, Skaff MM, Polonsky WH. Development of a brief 
diabetes distress screening instrument. Ann Fam Med 2008; 6(3): 246-52. 
49. 
WHO. WHO disability assessment schedule 2.0 (WHODAS 2.0). Geneva: World Health 
Organization, 2016. 
50. 
Gibbons CJ, Kenning C, Coventry PA, et al. Development of a multimorbidity illness 
perceptions scale (MULTIPleS). PLoS One 2013; 8(12): e81852. 
51. 
Mejías-Trueba M, Fernández-Rubio B, López-Hermoso C, Fernández-Rubio G, 
Jiménez-De Juan C, Rodríguez-Perez A. Cross-cultural adaptation into Spanish of the 
MULTIPleS scale in elderly patients with multimorbidity. Medicina Clínica (English Edition) 2022; 
159(7): 327-9. 
52. 
WHO. Service availability and readiness assessment (SARA): an annual monitoring 
system for service delivery: reference manual. Genvea: World Health Organization, 2013. 
53. 
Flottorp SA, Oxman AD, Krause J, et al. A checklist for identifying determinants of 
practice: a systematic review and synthesis of frameworks and taxonomies of factors that 
prevent or enable improvements in healthcare professional practice. Implement Sci 2013; 8: 35. 
54. 
Fernandez ME, Ten Hoor GA, van Lieshout S, et al. Implementation Mapping: Using 
Intervention Mapping to Develop Implementation Strategies. Front Public Health 2019; 7: 158. 
55. 
Powell BJ, Waltz TJ, Chinman MJ, et al. A refined compilation of implementation 
strategies: results from the Expert Recommendations for Implementing Change (ERIC) project. 
Implement Sci 2015; 10: 21. 
56. 
Gyamfi J, Iwelunmor J, Patel S, et al. Implementation outcomes and strategies for 
delivering evidence-based hypertension interventions in lower-middle-income countries: 
Evidence from a multi-country consortium for hypertension control. PLoS One 2023; 18(5): 
e0286204. 

 
28
57. 
Proctor EK, Powell BJ, McMillen JC. Implementation strategies: recommendations for 
specifying and reporting. Implement Sci 2013; 8: 139. 
58. 
Michie S, Atkins L, West R. The Behaviour Change Wheel: A Guide to Designing 
Interventions. Great Britain: Silverback Publishing, 2014. 
59. 
Lewis CC, Klasnja P, Powell BJ, et al. From Classification to Causality: Advancing 
Understanding of Mechanisms of Change in Implementation Science. Front Public Health 2018; 
6: 136. 
60. 
Sales AE, Barnaby DP, Rentes VC. Letter to the editor on "the implementation research 
logic model: a method for planning, executing, reporting, and synthesizing implementation 
projects" (Smith JD, Li DH, Rafferty MR. the implementation research logic model: a method for 
planning, executing, reporting, and synthesizing implementation projects. Implement Sci. 
2020;15 (1):84. Doi:10.1186/s13012-020-01041-8). Implement Sci 2021; 16(1): 97. 
61. 
Finley EP, Huynh AK, Farmer MM, et al. Periodic reflections: a method of guided 
discussions for documenting implementation phenomena. BMC Med Res Methodol 2018; 18(1): 
153. 
62. 
Hertzog MA. Considerations in determining sample size for pilot studies. Res Nurs 
Health 2008; 31(2): 180-91. 
63. 
Billingham SA, Whitehead AL, Julious SA. An audit of sample sizes for pilot and 
feasibility trials being undertaken in the United Kingdom registered in the United Kingdom 
Clinical Research Network database. BMC Med Res Methodol 2013; 13(5): 104. 
64. 
Francis JJ, Johnston M, Robertson C, et al. What is an adequate sample size? 
Operationalising data saturation for theory-based interview studies. Psychol Health 2010; 
25(10): 1229-45. 
65. 
Guest G. How Many Interviews Are Enough?: An Experiment with Data Saturation and 
Variability. Field Methods 2006; 18(1): 59-82. 
66. 
Creswell JW, Creswell JD. Research Design: Qualitative, Quantitative, and Mixed 
Methods Approaches. Fifth Edition ed. Thousand Oaks, California: SAGE Publications, Inc., 
2018. 
67. 
Nevedal AL, Reardon CM, Opra Widerquist MA, et al. Rapid versus traditional qualitative 
analysis using the Consolidated Framework for Implementation Research (CFIR). Implement 
Sci 2021; 16(1): 67. 
68. 
Neal JW, Neal ZP, VanDyke E, Kornbluh M. Expediting the Analysis of Qualitative Data 
in Evaluation. American Journal of Evaluation 2014; 36(1): 118-32. 
69. 
Fetters MD, Curry LA, Creswell JW. Achieving integration in mixed methods designs-
principles and practices. Health Serv Res 2013; 48(6 Pt 2): 2134-56. 
70. 
Office of Research, University of Michigan Medical School. Standard Adverse Event 
Reporting Guidelines for INTERNAL AEs Occurring at UM. 2018. 
https://az.research.umich.edu/sites/default/files/Adverse%20Event%20Reporting%20Guidelines

 
29
%20for%20INTERNAL%20AEs%20Occurring%20at%20UM_1152018%20OUTWARD%20facin
g.pdf (accessed April 27, 2023). 
71. 
Ministerio de Salud Pública y Asistencia Social/Guatemala. Estrategia Nacional de 
Salud Digital en Guatemala 2022-2023: Hacia la transformación digital de los servicios de 
salud, 2022. 
72. 
Code of Federal Regulations: Part 46 ‐ Protection of Human Subjects. 2023. 
https://www.ecfr.gov/current/title-45/subtitle-A/subchapter-A/part-46 (accessed April 18, 2023). 
73. 
Handley MA, Lyles CR, McCulloch C, Cattamanchi A. Selecting and Improving Quasi-
Experimental Designs in Effectiveness and Implementation Research. Annu Rev Public Health 
2018; 39: 5-25. 

 
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15. SUPPLEMENTARY FILES 
The following supplementary files are included with this protocol. 
 
1. 
Spirit checklist 
2. 
DHIS2 visit forms 
3. 
Baseline health facility assessments 
4. 
Follow-up health facility assessments 
5. 
Chart audit form 
6. 
Technical Advisory Committee meetings agenda and discussion prompts 
7. 
Structured questionnaire and semi-structured interview guide for patient participants 
8. 
Structured questionnaire for MOH participants 
9. 
Semi-structured interview guide for MOH participants 
10. 
Consent form: Patient and MOH participants who are interviewed 
11. 
Consent form: Technical Advisory Committee members 
12. 
Patient participant handout at primary health facilities 
13. 
Poster at health facilities

 
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