Dissemination and Implementation of Decision Support for the Management of Overweight and Obesity in Pediatric Primary Care - Improving Pediatric Obesity Practice Using Prompts
Phase: NA
Conditions: Obesity, Childhood
Sponsor: Yale University

APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026
STUDY PROTOCOL
Social Behavioral Template
Implementation of Decision Support for the 
Management of Obesity in a National Pediatric 
Primary Care Research Network
 Protocol Number
2000033551
 
Protocol Version
1/16/2026
 1.11
Clinical Trials Registration Number: NCT05627011
Confidentiality Statement: This document is confidential communication. Acceptance of 
this document constitutes agreement by the recipient that no unpublished information 
contained herein will be published or disclosed without prior approval of the Principal 
Investigator or other participating study leadership and as consistent with the NIH terms of 
award.
APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026

APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026
Protocol Number 2000033551
1/16/2026 Version 1.11
2
Synopsis
Purpose
This study, Improving Pediatric Obesity Practice Using Prompts (iPOP-UP), will evaluate 
a newly-optimized intervention, including electronic health record (EHR)-based clinical 
decision support tools (CDS) to improve adherence to national guidelines for 
management of childhood obesity, among 81 primary care practices, grouped into 71 
clusters, affiliated with three health systems serving children with racial and ethnic, socio-
economic, rural-urban, and geographic diversity. 
Objectives
Primary Objective: To evaluate the effectiveness of the iPOP-UP implementation 
package in improving clinical care and child BMI in pediatric primary care settings
Secondary Objective: To assess the impact of the implementation strategy on the reach, 
adoption, fidelity, cost, and maintenance of the intervention
Study Population
The unit of randomization in this study is pediatric primary care practice. 
Clinician-participants: Within the participating 71 clusters of 81 practices, pediatric primary 
care clinicians working at the implementation sites will be invited to participate in post-
intervention surveys and interviews assessing their knowledge, attitudes, and practice. In 
addition, limited data (to include dates and geographic information but no facial identifiers) 
will be queried and analyzed for the above-described pediatric primary care clinicians, 
Patient-participants: Limited data (to include dates and geographic information but no 
facial identifiers) will be queried and analyzed for all children 1) age 2.0 to ≤18 years-old 
at baseline, 2) with a well-child visit, during which height and weight are measured, at one 
of the participating practices during the study period, and 3) with a BMI ≥85th percentile for 
age/sex (CDC criteria for overweight/obesity). 
Parent/caregiver-participants: Parents/caregivers of patient-participants seen for a well-
child care visit at an intervention site will be invited to participate in an interview exploring 
their perceptions of the care delivered during their child’s recent visit, including how they 
felt about conversations about weight, growth, healthy behaviors and any bias/stigma they 
perceived during these clinical encounters. 
Number of Participants
Number of practices: 81, grouped into 71 clusters
Number of primary care clinicians at these practices at baseline: ~800
Estimated number of pediatric patients at these practices at baseline:  ~188,800
Number of parents/caregivers to be interviewed: approximately 60 (sample will depend on 
thematic saturation)
APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026

APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026
Protocol Number 2000033551
1/16/2026 Version 1.11
3
Study Design
This multi-site, parallel 2-arm cluster randomized controlled “Hybrid Type 2” effectiveness-
implementation trial will use mixed methods (EHR data analysis, surveys, and 
interviews/focus groups) to allow the study team to simultaneously evaluate (1) the 
effectiveness of the iPOP-UP implementation package in improving clinical care and 
children’s BMI outcomes in pediatric primary care setting and (2) the impact of the 
implementation strategy on the reach, adoption, fidelity, cost, and maintenance of the 
intervention.
Study Duration
The entire study, including data analysis, will last about three years. 
Patient and clinician participation will be up to 24 months. 
Parent/caregiver participation will be limited to one interview.
Outcome Variables
●
One-year change in BMI, measured as a percentage of the 95th percentile for age 
and sex
●
Change in clinicians’ objective practice around managing elevated BMI in primary 
care using EHR data
●
Change in clinicians’ self-reported knowledge, attitudes, and practice around 
managing elevated BMI in primary care
●
Utilization of CDS tools
●
Cost of implementation
Locations/Facilities
We will randomize 71 clusters representing 81 practices that have agreed to participate in 
the study from the three participating health systems, which represent rich heterogeneity 
in practice type, geographic region, rural-urban distribution, race/ethnicity, and insurance 
type (a marker of SES) of the patients they serve. The study will not involve practices 
outside of the United States.
APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026

APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026
Protocol Number 2000033551
1/16/2026 Version 1.11
4
Abbreviations
Abbreviation 
Explanation
AVS
After-visit summary 
CDS
clinical decision support
EHR
electronic health record
APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026

APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026
Protocol Number 2000033551
1/16/2026 Version 1.11
5
Glossary of Terms
Glossary
Explanation
iPOP-UP
Improving Pediatric Obesity Practice Using 
Prompts, the intervention being tested
APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026

APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026
Protocol Number 2000033551
1/16/2026 Version 1.11
6
Table of Contents
Preface
2
Synopsis
3
Purpose
3
Objectives
3
Study Population
3
Number of Participants
3
Study Design
3
Study Duration
3
Outcome Variables
3
Locations/Facilities
3
Abbreviations
4
Glossary of Terms
5
Protocol Revision History
9
1
Background
10
1.1
Background
10
1.2
Prior Experience (if applicable) 
10
2
Rationale/Significance
11
2.1
Rationale and Study Significance
11
2.2
Risks
11
2.3
Anticipated Benefits
11
3
Study Purpose and Objectives
12
3.1
Purpose
12
3.2
Hypothesis
12
3.3
Objectives
12
4
Study Design
13
4.1
Study Duration
15
4.2
Outcome Variables/Endpoints
15
4.2.1
Primary Outcome Variables/Endpoints
15
APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026

APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026
Protocol Number 2000033551
1/16/2026 Version 1.11
7
4.2.2
Secondary and Exploratory Outcome Variables/Endpoints (if applicable)
15
5
Study Participants
16
5.1
Study Population
16
5.2
Number of Participants
16
5.3
Eligibility Criteria
16
5.4
Recruitment Procedures 
17
5.5
Consent/Assent Procedures/HIPAA Authorization
17
6
Study Methods/Procedures
20
6.1
Study Procedures
20
6.1.1
Data Collection
21
6.2
Method of Assignment/Randomization (if applicable)
21
6.3
Adverse Events Definition and Reporting
21
6.4
Reaction Management
21
6.5
Withdrawal Procedures
22
6.6
Locations/Facilities
22
7
Statistical Design
23
7.1
Sample Size Considerations
23
7.2
Planned Analyses
23
7.2.1
Secondary Objective Analyses (if applicable)
23
7.2.2
Analysis of Subject Characteristics (if applicable)
23
7.2.3
Interim Analysis (if applicable)
23
7.3
Data Relevance
24
7.4
Data Coding
24
7.5
Data Analysis Tools
24
7.6
Data Monitoring
24
7.7
Handling of Missing Data
24
8
Data/Specimen Handling and Record Keeping
25
8.1
Subject Data Confidentiality
25
8.2
Data Quality Assurance
26
8.3
Data or Specimen Storage/Security
26
APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026

APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026
Protocol Number 2000033551
1/16/2026 Version 1.11
8
8.4
Study Records
26
8.5
Access to Source
26
8.6
Retention of Records
26
8.7
Data and Safety Monitoring Plan
27
9
Study Considerations
28
9.1
Institutional Review Board (IRB) Review
28
9.2
Research Personnel Training
28
9.3
Study Monitoring
28
9.4
Unanticipated Problems and Protocol Deviations
29
9.5
Study Discontinuation
30
9.6
Study Completion
30
9.7
Conflict of Interest Management Plan
30
9.8
Funding Source
31
9.9
Publication Plan
31
10
Appendices
32
11
List of Tables
33
APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026

APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026
Protocol Number 2000033551
1/16/2026 Version 1.11
9
Protocol Revision History
Version 
Date
Summary of Substantial Changes
Version 1.0
10/27/2022
--
Version 1.01 
02/02/2023
Updated to reflect final number of practices (and associated 
clinicians and patients) that agreed to participate in trial, and add 
NCT#.
Version 1.02
8/21/2023
Updated to reflect that qualitative components of the study 
summative evaluation will begin at six months, and not occur at 12 
and 18 months, and to clarify expected duration of summative 
evaluation mixed methods efforts. 
Version 1.03
9/13/2023
Updated to add in-person survey recruitment and clinic-level 
incentives.
Version 1.04
11/2/2023
Updated to reflect additional logistics around in-person survey 
recruitment
Version 1.05
3/7/2024
Updated to address contradictions in earlier versions of the protocol 
regarding email addresses queried from the EHR and study 
participant contact information. Revisions can be found on page 32.
Version 1.06
5/28/2024
Updated with change to incentive amount for qualitative summative 
evaluation participants
Version 1.07
7/11/2024
Updated to add snowball sampling as recruitment method for 
qualitative summative evaluation
Version 1.08
12/02/2024
Updated to add qualitative exploration of families’ experiences with 
care
Version 1.09
2/18/2025
Updated to add additional detail around site-specific practices for 
recruitment.
Version 1.10
5.30.2025
Updated to add IU Health as part of one of our study sites for 
recruitment purposes
Version 1.11
Updated errors/outdated details present in the protocol (e.g., number 
of practices, inclusion criteria for patient data query etc.)
APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026

APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026
Protocol Number 2000033551
1/16/2026 Version 1.11
10
1.16.2025
APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026

APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026
Protocol Number 2000033551
1/16/2026 Version 1.11
11
1.
Background
1.
Background
CDS tools are seen as a key piece of the potential inherent in EHRs to improve the quality of 
healthcare overall1, and could benefit the quality of pediatric obesity management given 
studies finding low rates of documentation and treatment2-4. In terms of CDS tools specific for 
pediatric obesity, the evidence is mixed: while some studies have demonstrated that EHR-
based CDS tools can be effective in increasing adherence to clinical recommendations in 
pediatric obesity5-9, not all CDS implementations have impacted care as desired10, 11. The 
studies with positive results, however, were mostly implemented in limited settings, so it may 
be difficult to replicate their results on a wider scale. As such, this study is designed to test, 
on a larger scale, an optimized version of a previously studied CDS tool that yielded positive 
results8. Based on this tool’s effectiveness, it has been further refined and optimized into the 
iPOP-UP intervention based on a formative evaluation conducted with clinicians and other 
stakeholders at three health systems representing more than 80 heterogeneous clinics. This 
trial has the potential to advance the effectiveness and implementability of CDS tools for 
pediatric obesity, the need for which has never been greater given the increase in already-
alarming prevalence of and inequities within this epidemic nationwide. 
2.
Prior Experience (if applicable) 
The EHR-based CDS tools included in the iPOP-UP intervention were originally tested, and 
found to be effective, in a small-scale pilot study at one health system.8 Prior to the study 
described in this protocol, the study team led a formative evaluation, the results of which 
informed the optimization of the CDS tools being studied.
2.
Rationale/Significance
1.
Rationale and Study Significance 
Nearly 1 in 3 children and adolescents in the United States are affected by overweight or 
obesity, and low-income, non-Hispanic Black, Hispanic/Latino and rural children are 
disproportionately impacted.12 Despite guidance from the US Preventive Services Task Force 
and expert committees, pediatric primary care clinicians often do not follow available guidance 
for managing children with obesity.13 EHRs have the potential to improve clinicians’ diagnosis 
and management of obesity by providing tools such as reminders and clinical decision support. 
We have demonstrated that the Improving Pediatric Obesity Practice Using Prompts (iPOP-
UP) intervention package, consisting of EHR-based CDS tools for pediatricians and 
educational materials for parents, improved BMI among children in two clinical trials at a 
multisite group practice in Massachusetts.8 However, little is known regarding the 
effectiveness of the iPOP-UP intervention in various pediatric primary care settings, 
particularly those serving children from populations disproportionately impacted by obesity, or 
regarding the specific factors that influence the successful adoption and implementation of 
APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026

APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026
Protocol Number 2000033551
1/16/2026 Version 1.11
12
these tools. In partnership with a national practice-based research network, we aim to 
capitalize on advances in the field of Implementation Science to apply and evaluate iPOP-UP 
for childhood obesity among 81 primary care practices grouped into 71 clusters affiliated with 
three health systems serving children with racial/ethnic, socio-economic, rural-urban, and 
geographic diversity. We hypothesize that the CDS tools included in the iPOP-UP intervention 
will improve primary care clinicians’ management of pediatric obesity by increasing adherence 
to evidence-based clinical recommendations. The clinical outcome of interest is one-year 
change in BMI for children who receive primary care at the enrolled clinics. 
The iPOP-UP intervention will include a set of CDS tools as well as training documentation 
and patient-facing materials to promote clinician adherence to upcoming guidelines from the 
American Academy of Pediatrics (AAP) for the management of childhood overweight and 
obesity (scheduled for publication December 2022), as described in the below table. 
Table 1. Intervention Components 
EHR-based Clinical Decision 
Support Tools 
In-line BestPractice® advisory with notice of BMI≥95th %tile and links to: 
- SmartSets®  
- Note template 
- Evidence-based childhood overweight and obesity guidelines; 
SmartSet® and well-child obesity note template facilitate: 
- Documentation/coding of obesity-related diagnoses; 
- Orders for obesity-related screening laboratory tests, medications and referrals to weight 
management programs, nutrition, subspecialists for eligible patients; 
- Counseling using motivational interviewing and goal setting per the AAP guidelines with 
educational materials on healthy behaviors for the after-visit summary provided to families 
and links to resources available through the AAP
- Health maintenance tools that can remind families, via the patient portal and/or AVS, of 
ordered and/or overdue labs, upcoming visits, etc.
Provider Training 
To include a variety of modalities, including tip sheets on the new EHR tools, video recorded
demonstrations of the tools, and presentations during clinical meetings. Clinicians will also 
be encouraged to use training materials available to all clinicians from the AAP.
2.
Risks
We anticipate minimal risk associated with study data collection. For the purposes of 
recruitment, providing incentives to participants, and tracking changes in participants’ pre-
post survey responses, we will track identifiable information of invitees, including names and 
email addresses. These will be kept separate from all transcripts and analyses. All paper-
based survey data will be scanned and securely transferred to Yale staff, who will then enter 
it into REDCap; scanned surveys will include the study-specific de-identified ID to facilitate 
REDCap entry. All survey data will be kept in the secure, password-protected REDCap 
system and/or in password-protected files on Yale-managed servers. All qualitative data 
from interviews/focus groups will be kept on secure, institution-managed servers with 
recordings stored on Yale and/or UFL servers, and transcripts stored on Yale servers. 
Existing patient-and clinician-level data will be collected by EHR data warehouse staff at 
sites, who will remove all facial identifiers (e.g., names, street addresses, telephone 
numbers, email addresses, social security numbers, medical record numbers, facial photos, 
APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026

APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026
Protocol Number 2000033551
1/16/2026 Version 1.11
13
etc.) prior to transfer to the Yale Data Coordinating Center. Because this data will be 
collected at sites but analyzed at Yale, we will use encrypted secure file transfer procedures 
to transfer the limited datasets. We will keep electronic data on a restricted server that is on 
a password protected network at all times. None of this data will be individually identifiable 
by study investigators.
As we will not analyze identifiable information, we anticipate minimal risks associated with 
the intervention and trial. For clinicians, there is a risk that the decision support and other 
tools could have unexpected adverse consequences such as creation of more work, 
unfavorable workflow issues, and overdependence on the technology. Although important to 
consider (and we will explore these themes in our mixed methods evaluation), these issues 
are balanced by the evidence suggesting the effectiveness of computerized CDS tools to 
improve the quality of patient care. In addition, it is essential to point out that the iPOP-UP 
intervention is an enhancement of the existing electronic health record, not the 
implementation of a whole new system of care; therefore, the risks to clinicians and patients 
are expected to be negligible. Specifically, for clinicians, the intervention has the risk of 
slowing down the operating speed of the EHR or disrupting the workflow of clinicians who 
view the alerts. 
For the patients, the risks are those that are typically undertaken in the receipt of general 
medical care. That is, it is conceivable that the intervention could result in a change in 
management (e.g., decision to obtain a screening laboratory test or refer to a weight 
management program), which may lead to a side-effect, but in fact is more likely to lead to a 
clinical benefit. There also is the possibility of psychological risk to patients associated with 
being labeled as having an elevated BMI; however, this risk is outweighed by the potential 
benefits associated with better identification, evaluation, and treatment of obesity by their 
clinicians and we will engage patients/parents in the user-centered design to avoid this. 
For the parent/caregiver participants, there is a risk that the interview questions we ask could 
be emotionally laden, given the stigma and bias associated with overweight/obesity. None of 
the interview questions will be required, and participants will be able to end the interview at 
any time without consequence. 
Another important risk we have considered is the risk created by the randomized controlled 
trial design of the proposed study. The withholding of effective EHR tools from practices and 
clinicians in one study arm versus the other. However, there remains equipoise regarding 
the benefit EHR-based CDS tools in different practice settings and patient populations, both 
in general and specifically for treatment of obesity. Therefore, a cluster randomized 
controlled trial is justifiable and necessary to assess the true benefit of the intervention. 
3.
Anticipated Benefits
This dissemination and implementation study is based on a prior cluster randomized 
controlled trial in pediatric primary care practices in Massachusetts which demonstrated 
improved BMI using EHR-based CDS tools to support the adoption of prior expert 
recommendations for the management of obesity in primary care. We expect that practices 
and clinicians in the intervention arm of the trial will be supported in their workflows to 
provide more efficient and high quality care and that children seen in these practices during 
APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026

APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026
Protocol Number 2000033551
1/16/2026 Version 1.11
14
the trial will see both short- and long-term benefits from improved treatment of obesity that 
could reduce their weight gain and help with the management of other chronic conditions. 
This research has the potential benefit of improving the diagnosis and treatment of obesity 
among patients at the practice sites which ultimately could reduce their weight gain and help 
with the management of other chronic conditions. Patients at other pediatric primary care 
sites may ultimately benefit as well through the dissemination of our results and the iPOP-
UP intervention itself.
Long-term potential benefits to society as a whole include lower health-care costs, given the 
many complex and costly physical and mental health sequelae tied to pediatric 
overweight/obesity. Interviews with parents/caregivers are expected to yield important 
insights into how primary care clinicians can manage overweight/obesity in pediatric 
populations while minimizing any unintended harm via stigmatizing care. 
3.
Study Purpose and Objectives
1.
Purpose
This study will evaluate iPOP-UP, a newly-optimized intervention to improve adherence to 
national guidelines for the management of childhood obesity, among 71 clusters of 81 
primary care practices affiliated with three health systems serving children with racial and 
ethnic, socio-economic, rural-urban, and geographic diversity.
2.
Hypothesis
We hypothesize that in practices randomized to receive the iPOP-UP intervention, primary 
care clinicians’ management of pediatric obesity and adherence to evidence-based clinical 
recommendations will increase, and that children with obesity who receive primary care at 
intervention sites will have more of an improvement in one-year change in BMI compared to 
children at control sites. Specific key questions that the study is expected to answer include:
1.
To what extent will 2-18 year-old children with elevated BMI seen during the 
intervention period be more likely to have problem list/visit diagnoses indicating high 
BMI, orders for recommended obesity-related laboratory tests, medications, follow-up 
visits, and referrals among the intervention vs. usual care practices?
2.
To what extent will patients with elevated BMI seen in the intervention versus control 
practices have a slower one-year increase in BMI?
3.
To what extent will baseline practice and patient-level factors such as practice type, 
urban-rural location, and size and patient’s race/ethnicity, insurance status, the 
severity of overweight/obesity and neighborhood characteristics be associated with the 
impact of the intervention and implementation strategy?
3.
Objectives
APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026

APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026
Protocol Number 2000033551
1/16/2026 Version 1.11
15
Primary Objective: To evaluate the effectiveness of the iPOP-UP implementation package 
in improving clinical care and child BMI outcomes in pediatric primary care settings affiliated 
with three health systems serving children with racial and ethnic, socio-economic, rural-
urban, and geographic diversity
Secondary Objective: To assess the impact of the implementation strategy on the reach, 
adoption, fidelity, cost, and maintenance of the intervention
APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026

APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026
Protocol Number 2000033551
1/16/2026 Version 1.11
16
4.
Study Design
Trial design: a large-scale, multi-site, parallel 2-arm cluster randomized controlled trial 
“Hybrid Type 2” effectiveness-implementation study to simultaneously evaluate (1) the 
effectiveness of iPOP-UP in improving clinical care and child weight outcomes in pediatric 
primary care setting and (2) the impact of the implementation strategy on the reach, adoption, 
fidelity, cost, and maintenance of the intervention.
Method for assigning participants to study groups: covariate-constrained randomization14
●
Clusters will be randomized 1:1 using a covariate constrained randomization to help 
maintain balance across treatment arms on key practice characteristics. We will 
consider the following characteristics of practices and evaluate correlations to identify 
a parsimonious set of key characteristics: health system, proportion of patients that are 
publicly insured, proportions non-Hispanic Black, proportions Hispanic/Latino, 
proportions non-Hispanic White, geographic location (rural versus urban/suburban), 
practice size/volume, and academic vs. non-academic. Since randomization will be at 
the practice level, but the analysis will be conducted at the individual level, we will 
assess the adequacy of the randomization by comparing baseline demographic and 
clinical characteristics between the two treatment groups.
●
Randomization method: covariate constrained randomization
●
Unit of randomization: practice cluster
●
Role responsible for generating and implementing the randomization schema: study 
statistician
●
How randomization errors will be handled: We will employ a SAS macro for covariate 
constrained randomization and use a random seed to generate the randomization.  All 
sites will be identified at the same time as to which treatment arm they have been 
assigned. We will handle any unforeseen errors in randomization by maintaining our 
intent-to-treat analysis approach and may conduct sensitivity analyses to evaluate 
protocol deviations.15   
Number of study groups: two (one intervention, one control)
Name and brief description of study intervention: The study intervention, iPOP-UP, 
involves EHR-based CDS tools refined through a formative evaluation and user-centered 
design process that immediately preceded this study.
Control group: practices assigned to usual care that will not have access to the iPOP-UP 
CDS tool but will have access to many opportunities available to all pediatric clinicians 
nationally around the release of the new American Academy of Pediatrics guidelines for 
obesity management. We have timed the launch of our study to coincide with the launch of 
these guidelines.  
Stratifications planned: We will assess the extent to which baseline practice and patient-
level factors (such as practice type, urban-rural location, and size and patient’s race and 
ethnicity, insurance status, the severity of overweight/obesity, and neighborhood 
APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026

APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026
Protocol Number 2000033551
1/16/2026 Version 1.11
17
characteristics) are associated with the impact of the intervention and implementation 
strategy.
.
Study flowchart: 
APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026

APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026
Protocol Number 2000033551
1/16/2026 Version 1.11
18
1.
Study Duration
The entire study, including data analysis, will last about three years. Patient and clinician 
participation will be up to 24 months. 
2.
Outcome Variables/Endpoints
1.
Primary Outcome Variables/Endpoints
OBJECTIVES
ENDPOINTS
RATIONALE FOR ENDPOINTS
To evaluate the effectiveness of 
our intervention package in 
improving clinical care and child 
weight outcomes in pediatric 
primary care setting caring for 
low-SES and racial/ethnic 
minority children 
1.1: Change in BMI, 
measured as a percentage 
of the 95th percentile for age 
and sex, over one year
1.2: Composite measure of 
adherence to clinical 
guidelines at 6 months post-
intervention, for visits 
completed among children 
2-18 years-old with BMI 
≥85th percentile. Adherence  
defined as evidence of 
recommended obesity-
related care during the 
study period including all of 
the following:
1.
Inclusion of 
diagnosis code 
indicating high BMI 
in problem list 
(cumulative) or visit 
diagnosis (every 
visit)
2.
Recommended 
screening lab orders 
for obesity related 
comorbidities, if 
eligible 
We hypothesize that:
1.1: patients with elevated BMI 
seen in the intervention vs. 
control practices will have a 
slower one-year increase in BMI 
measures
1.2: Clinicians in intervention vs. 
control practices will be more 
likely to  adhere to clinical 
guidelines during visits for 
patients with elevated BMI.
APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026

APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026
Protocol Number 2000033551
1/16/2026 Version 1.11
19
OBJECTIVES
ENDPOINTS
RATIONALE FOR ENDPOINTS
3.
Appropriate BP 
screening in children 
3 and older
4.
Counseling 
diagnosis codes or 
structured 
documentation 
(every visit)
5.
Follow-up visit 
requested (every 
visit) or referral 
(need to look back) 
for further 
management of 
obesity 
2.
Secondary and Exploratory Outcome Variables/Endpoints 
OBJECTIVES
ENDPOINTS
JUSTIFICATION FOR 
ENDPOINTS
To assess the impact of the 
implementation strategy on the 
reach, adoption, fidelity, cost, 
and maintenance of the 
intervention
2.1: Composite measure of 
adherence to clinical 
guidelines at 12 and 18 
months post-intervention, 
for visits completed among 
children 2-18 years-old with 
BMI ≥85th percentile. 
2.2. Visits completed 
among children with BMI 
≥85th percentile with 
evidence of recommended 
obesity-related care during 
the study period:
1.
Inclusion of 
diagnosis code 
indicating high BMI 
in problem list 
(cumulative) or visit 
We hypothesize that:
2.1: Clinicians in intervention vs. 
control practices will be more 
likely to maintain adherence to 
clinical guidelines.
2.2: Clinicians in intervention vs. 
control practices will be more 
likely to adhere to the 
components of clinical 
guidelines.
2.3. Clinicians in intervention vs. 
control practices will be less 
likely to order lab tests that are 
not routinely recommended.
2.4. Clinicians in intervention vs. 
control practices will be more 
likely to be more likely to 
APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026

APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026
Protocol Number 2000033551
1/16/2026 Version 1.11
20
OBJECTIVES
ENDPOINTS
JUSTIFICATION FOR 
ENDPOINTS
diagnosis (every 
visit)
2.
Screening lab orders 
for obesity related 
comorbidities, if 
eligible 
3.
Appropriate BP 
screening in children 
3 and older
4.
Counseling 
diagnosis codes or 
structured 
documentation 
(every visit)
5.
Follow-up visit 
requested (every 
visit) 
6.
Referral (need to 
look back) for further 
management of 
obesity 
7.
Weight loss 
medication orders, if 
eligible
8.
Bariatric surgery 
program referrals, if 
eligible
2.3: Visits completed 
among children with BMI 
≥85th percentile with lab 
orders for laboratory tests 
not routinely recommended 
including insulin test and 
thyroid function tests
2.4. Change in clinicians’ 
knowledge attitudes and 
improve their self-reported 
knowledge, attitudes, and 
practice.  
2.5: We aim to describe CDS 
utilization post-intervention.
2.5. We will estimate costs of 
implementation and delivery of 
the iPOP-UP intervention 
compared with usual care. If 
effective, we will also estimate 
the cost-effectiveness of the 
iPOP-UP intervention compared 
with usual care.
APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026

APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026
Protocol Number 2000033551
1/16/2026 Version 1.11
21
OBJECTIVES
ENDPOINTS
JUSTIFICATION FOR 
ENDPOINTS
practice around elevated 
BMI in primary care
2.5: EHR measures of CDS 
utilization
2.6: Cost and cost-
effectiveness of 
implementation
3.
Study Population
Clinician-participants: clinicians (including physicians-in-training (residents and fellows), 
physicians, nurse practitioners (NP), and advanced practice registered nurses (APRNs)) who 
work at study sites during the intervention. 
Patient-participants: all eligible patients who receive well-child care at the study sites via a 
limited data set which will exclude all “facial” identifiers. 
Parent/caregiver-participants: Parents/caregivers of patient-participants seen for a well-child 
care visit at an intervention site within about two weeks to one month of data collection 
4.
Number of Participants
CHOP
Duke
IU
Total
Practices
21
47
13
81
Practice clusters
19
44
8
71
Clinician-participants
 ~230
~400
~170
~800
Patient-participants
~ 89,600
~ 71,360
~ 29,600
~188,800 
Parent/caregiver-participants
~15-25
~15-25
~10-20
~60
APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026

APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026
Protocol Number 2000033551
1/16/2026 Version 1.11
22
5.
Eligibility Criteria
Inclusion criteria:
Primary Care Practices: all primary care practices using the EHR system of one of the 3 
health systems participating in the study that agree to participate in the iPOP-UP trial (see 
recruitment information below)
Clinician-participants: all clinicians who delivery pediatric primary care at the participating 
practices, including physicians and physicians-in-training (residents and fellows), nurse 
practitioners (NP), and advanced practice registered nurses (APRNs)
Patient-participants: all patients ages 2-18 with overweight/obesity seen during the study 
period may be impacted by the intervention. A limited dataset will be collected for the 
subset of these patients with at least one visit at any point during the study period (Feb 
2021 – December 14, 2024 ) with the following criteria:
●
Visit conducted by a prescribing clinician (physician (MD/DO, including 
residents and fellows), NP, PA)
●
Any completed visit type in a primary care department participating in 
iPOP-UP (control and intervention)
●
height and weight measurement present
●
patient age of 2 to 18 years old, inclusive
●
BMI ≥ 85th percentile for age and sex
Parent/caregiver-participants: English- or Spanish-speaking parents/caregivers of 
patient-participants seen for a well-child care visit at an intervention site within one 
month of data collection who meet the following inclusion criteria:
1.
Parents/caregivers of children age between 2-18 years inclusive
2.
Child with BMI at or above 85th percentile 
3.
Parents/caregivers who confirm that their child’s weight or growth was discussed 
in their most recent pediatric clinic visit 
4.
Date of last pediatric clinic well visit within last month
5.
Able to communicate verbally in English or Spanish
6.
Has phone or internet access necessary to complete an interview by video chat 
or phone
7.
Has opted in/did not opt out to being contacted for participation in pediatric 
healthcare research
Exclusion Criteria: 
Clinician & patient-participants: None – exclusion criteria are purposefully limited in this real-
world implementation study
APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026

APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026
Protocol Number 2000033551
1/16/2026 Version 1.11
23
Parent/caregiver-participants: Parents/caregivers who do not meet our inclusion criteria.
6.
Recruitment Procedures 
Practice-level recruitment: The study teams at each participating health system decided 
upon the best recruitment approach given local policies and preferences. Two contacted all 
pediatric primary care practices affiliated with their health systems to invite them to participate 
in the study. This contact was personalized, with teams contacting each practice’s leadership 
individually to invite their participation and answer all questions. Contact methods included 
phone, Zoom, or in-person discussion. The site teams have pre-existing relationships with 
many of these practices, and as such, personalized their recruitment to the greatest extent 
possible. The third presented the study to system leadership to get buy-in and approval for 
the affiliated sites to participate. 
Individual-level recruitment:
Clinician-participants: The only individual-level recruitment of clinicians in this study will be for 
the post-intervention study surveys and post-intervention interviews/focus groups. Study staff, 
including site investigators and Yale research team members, will invite all clinicians at all 
participating practices to participate in the study surveys; qualitative recruitment will be 
targeted to key informants and will be led collaboratively by Yale research team members and 
site study staff. All qualitative research will be conducted remotely on Zoom or another similar 
platform. Key informants may be defined by their level of use of the iPOP-UP intervention CDS 
tools (e.g., early adopters, late adopters, never adopters), by their engagement in the 
intervention overall (e.g., local Epic super users or other clinicians who provide trainings to 
colleagues, clinicians who participated in various training methodologies, etc.), or be identified 
via snowball sampling at the end of each interview. Recruitment will occur via email and/or in-
person. Before site study staff visit a clinic participating in the trial to recruit for the survey in-
person, Yale study staff will share the names and de-identified study IDs of clinicians who 
have yet to complete the survey so that site study staff do not recruit clinicians who have 
already completed the survey. Qualitative interviews/focus groups will most likely be led by 
Jessica Ray, study team member based at UFL, and may instead be facilitated by study team 
members at Yale or study sites who have unique and in-depth insight into the topic being 
explored (e.g., a Duke team member may lead a focus group with Duke Epic super users). 
Invitees will be offered a $10 or $75 electronic gift card, to be provided via email within ten 
business days of the completion of the survey or interview/focus group, respectively. In 
addition, for every clinician who completes a survey, we will provide that clinician’s clinic with 
a $20-$50 credit, based on available funds, toward their team’s choice of a patient- or staff-
facing prize (including Reach Out and Read books, stickers, and/or obesity-related clinical 
management guides). 
Parent/caregiver-participants: Recruitment and data collection is expected to commence late 
2024 to early 2025. Each site will query patients to be contacted for recruitment based off the 
eligibility criteria and date of last well-visit. Details of eligible patients which will be queried, all 
accessed/obtained from the electronic medical record of the pediatric patients, will include:
APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026

APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026
Protocol Number 2000033551
1/16/2026 Version 1.11
24

Phone number

Child name and date of birth

Age

Sex

BMI classification

Race and ethnic background

Primary language

Insurance status

Family residence census track

Primary care practice in which the visit occurred
Sites will use internal processes to manage their recruitment lists and tracking. For instance, 
the Duke site will use MaestroCare/Epic (including pre-consent statuses) and/or RedCap to 
internally track eligible participants and approaches/recruitment of participants prior to 
consenting them. 
Using this list, staff at each study site will contact the parents/caregivers of eligible patients 
via: (i) phone or (ii) in-person.  After consent is obtained, eligibility will be further assessed, 
and basic information will be recorded using a REDCap questionnaire. Additional 
demographic 
information 
and 
contact 
information 
for 
scheduling 
will 
also 
be 
captured/confirmed prior to scheduling the interview.  Study site partners may also perform 
chart reviews of EHR data of interviewees for variables of interest such as care quality and 
stigmatizing care (e.g., did the primary care clinician counsel on nutrition and physical activity, 
did the visit note include stigmatizing language). The linking of EHR charts to interviewees 
would also allow for corroboration and further analysis of content that may be captured during 
the interview.
The REDCap tool is submitted with this protocol for IRB review/approval. Participant lists 
queried by partner study sites will be stored on HIPAA-compliant REDCap servers at their 
respective local institutions. The tool will be used either by study staff (if recruited by phone or 
in person) to:
1.
Provide basic study information 
2.
Screen potential participants for study eligibility
3.
Collect study participant demographic information to confirm the accuracy of their 
linked EHR data
4.
Link to an online calendar of the interviewer’s availability to schedule the interview at 
a time that works for the participant
5.
Create a de-identified study ID which will be used to link transcripts with participant 
characteristics (e.g., will not connect names)
The one-on-one interviews will be led by Yale team members and, where needed, translators. 
A semi-structured interview guide with probing questions will be utilized to explore the 
experiences of parents and their children (by proxy) during well child visits in which growth, 
weight, or obesity are discussed, exploring perceptions of weight bias or stigma. The interview 
APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026

APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026
Protocol Number 2000033551
1/16/2026 Version 1.11
25
guide will be piloted with parents/caregivers from patient and public involvement and 
engagement (PPIE) groups to ensure the content is appropriate and relevant. Interviews are 
expected to last 30-45 minutes and will be audio recorded for subsequent professional 
transcription. Upon completion of the interview, participants will also be offered a $50 
electronic gift card. This will be provided via email (or by text, for those with no email address) 
within ten business days following the completion of the interview. Participants are responsible 
for paying state, federal, or other taxes for the payments they receive for being in this study. 
Taxes are not withheld from their payments.
Afterwards, no further involvement or follow-up with the participants will be undertaken. 
7.
Sampling Strategy
Parent/caregiver-participants: Sampling will involve both purposive and maximum variation 
approaches to ensure inclusion of heterogenous perspectives, with particular attention to the 
inclusion of participants from demographic backgrounds disproportionately affected by obesity 
and populations that may experience differences in care delivery. As such, participant factors 
which will be sampled for will include: race, ethnicity, primary language spoken (purposive 
sampling criteria) as well as children’s age, sex, BMI category, insurance status, and clinic 
site and parent’s health literacy.
8.
Consent/Assent Procedures/HIPAA Authorization
We will only collect a limited data set, without “facial” identifiers, for patient-level EHR data or 
for clinician-level use of the iPOP-UP CDS tool and given the low risk to participants; as such, 
we plan to obtain a waiver of consent for participants involved in the main clinical trial. 
For the survey, we will attach an information sheet to the emailed invitation to participate in 
the survey and will provide a copy of the information sheet when recruiting in-person. Consent 
will be implied by completing the survey itself; as such, we plan to obtain a waiver of consent 
for the survey.
For the interviews/focus groups with clinicians, we will attach an information sheet to the 
emailed invitation to participate. Verbal consent will be confirmed prior to beginning the 
interview.
Parent/caregiver interviews
For parent/caregiver interviews, a waiver of HIPAA authorization/consent is requested to 
access the patient information for screening and recruitment purposes, and to record 
information of interested caregivers prior to consent. For parent/caregivers who express 
interest in participating after being approached for recruitment, the study information sheet will 
first be reviewed with participants recruited in person or by phone by a member of the site 
study staff. Participants will be given the opportunity to ask questions prior to the consent 
APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026

APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026
Protocol Number 2000033551
1/16/2026 Version 1.11
26
process. Afterwards, site study staff will confirm verbal consent with the participant and 
proceed to scheduling the interview. 
Verbal consent will be confirmed again by the Yale researcher prior to the interview session 
as well. For Spanish-speaking parents/caregivers, the consenting process will be completed 
either with a Spanish-speaking site study staff or a non-Spanish speaking site study staff 
accompanied by a translator.
5.
Study Methods/Procedures
8.
Study Procedures
Schedule Table 
Day -30
Day 1
Month 1 Month 6 Month 12Month 18
Clinic randomization
X
CDS tool launch
x
CDS tool training
X
EHR data query
x
X
x
x
Clinician survey
X
X*
Clinician interviews/focus groups
X
x**
Parent/caregiver interviews
x**
x**
*Survey expected to stay open up to three months
**Interviews/focus groups will continue until thematic saturation is reached
1.
Data Collection
We will collect EHR data from all participating sites to assess:
- Measures of obesity-related care: e.g., blood pressure measurements, visit diagnoses, 
problem list entries, and orders placed and their relevant dates and results, including labs, 
medications, imaging, and referrals. 
- Clinicians' utilization of the CDS tools
- Patient characteristics: age, sex, race and ethnicity, primary language, insurance type, zip 
code, census tract, EHR patient portal status
APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026

APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026
Protocol Number 2000033551
1/16/2026 Version 1.11
27
- Clinician-level characteristics: e.g., specialty, clinician type, patient volume and/or primary 
care sessions during the study period.
Using surveys and interviews/focus groups of clinicians, we will collect information on 
attitudes, beliefs, and practices specific to obesity care prior to and beginning 6 months after 
implementation. We will also collect qualitative data around how to improve the tools post-
intervention.
Costs related to implementation and changes in care delivery will be gathered from study team 
logs and from clinician surveys.
We will explore the perceptions and experiences of parents/caregivers regarding their child’s 
most recent well-visit with their primary care clinician, including how they felt about how the 
clinician discussed growth, weight, and healthy behaviors. These interviews will be primarily 
qualitative, with some cognitive interviewing used in pilot testing potential future survey 
questions. The interview guide, including questions to be piloted, is submitted for IRB 
review/approval with this protocol modification. 
The one-on-one interviews will be digitally recorded using video conferencing software (e.g., 
Zoom) and then subsequently professionally transcribed by a trusted service provider affiliated 
with Yale. The resultant transcripts will then be thematically analyzed afterwards by the 
primary researcher. The audio recordings will be only stored temporarily to allow for 
professional transcription services to complete the transcription process and then 
subsequently destroyed afterwards. All electronic files (i.e. consent forms and transcripts) will 
be securely stored on encrypted servers belonging to the Yale School of Medicine. Access to 
these files will only be possible by the study’s principal investigator (Dr. Mona Sharifi) and the 
other collaborating members of the immediate research team.
9.
Method of Assignment/Randomization (if applicable) 
Practices (clusters) will be randomized 1:1 using a covariate constrained randomization by 
site and key practice characteristics to ensure that different practice types will have a nearly 
even distribution between the usual care and intervention arm. We will consider the following 
variables for this randomization: health system, proportion of patients that are publicly 
insured, proportions non-Hispanic Black, proportions Hispanic/Latino, proportions non-
Hispanic White, geographic location (rural versus urban/suburban), practice size/volume, 
and academic vs. non-academic. Since randomization will be at the practice level, but the 
analysis will be conducted at the individual clinician or patient level, we will assess the 
adequacy of the randomization by comparing baseline demographic and clinical 
characteristics between the two treatment groups.
10.
Adverse Events Definition and Reporting
An adverse event (AE) is any undesirable and unintended negative consequence or harm 
suffered by a participant from participation in the study. 
APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026

APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026
Protocol Number 2000033551
1/16/2026 Version 1.11
28
An adverse event (AE) or suspected adverse reaction is considered “serious” if, in the view 
of either the investigator or sponsor, it results in any of the following outcomes: death, a life-
threatening adverse event, inpatient hospitalization or prolongation of existing 
hospitalization, a persistent or significant incapacity or substantial disruption of the ability to 
conduct normal life functions, or a congenital anomaly/birth defect. 
For adverse events (Aes) not included in the protocol defined grading system, the following 
guidelines will be used to describe severity. 
Mild – Events require minimal or no treatment and do not interfere with the 
participant’s daily activities. 
Moderate – Events result in a low level of inconvenience or concern with the 
therapeutic measures. Moderate events may cause some interference with 
functioning.
Severe – Events interrupt a participant’s usual daily activity and may require systemic 
drug therapy or other treatment. Severe events are usually potentially life-threatening 
or incapacitating.  Of note, the term “severe” does not necessarily equate to 
“serious”.
All adverse events (AEs) will have their relationship to study procedures, including the 
intervention, assessed by the study PI, an appropriately-trained clinician, based on temporal 
relationship and her clinical judgment. The degree of certainty about causality will be graded 
using the categories below. 
•
Related – The AE is known to occur with the study procedures, there is a reasonable 
possibility that the study procedures caused the AE, or there is a temporal relationship 
between the study procedures and the event. Reasonable possibility means that there 
is evidence to suggest a causal relationship between the study procedures and the 
AE.
•
Not Related – There is not a reasonable possibility that the study procedures caused 
the event, there is no temporal relationship between the study procedures and event 
onset, or an alternate etiology has been established.
All AEs, not otherwise precluded per the protocol, will be captured on the appropriate case 
report form (CRF). Information to be collected includes event description, time of onset, 
clinician’s assessment of severity, relationship to study procedures (assessed only by those 
with the training and authority to make a diagnosis), and time of resolution/stabilization of the 
event. All AEs occurring while on study will be documented appropriately regardless of 
relationship. All AEs will be followed to adequate resolution.
All serious and related AEs will be reported to the sIRB within 5 business days of the 
investigator becoming aware of the event. Non-serious AEs that have taken place with greater 
frequency or severity than expected should be reported to the sIRB when identified. 
11.
Reaction Management
APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026

APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026
Protocol Number 2000033551
1/16/2026 Version 1.11
29
Since this trial involves intervention at the practice-level to support the implementation of 
national guidelines for the management of pediatrics overweight/obesity, we do not expect 
any emergency situations or situations of induced stress above those encountered during 
routine clinical care at the practices for which all sites have existing systems in place. 
12.
Withdrawal Procedures
While unexpected, if a clinic were to exit from the site health system network during the study 
period, no data would be collected from that site after its exit, as it would no longer have the 
EHR support needed to maintain the CDS tool in the event of an EHR downtime or upgrade. 
If a participant resigns from a study site during the study, their EHR utilization data will be 
studied until their date of departure. 
While not expected, if a parent/caregiver-participant decides to terminate their participation 
mid-interview, we will include the responses they did provide prior to termination in our data 
analysis unless the participant requests otherwise. 
Parent/Caregiver interviews
The authorization to use and disclose your health information collected during your 
participation in this study will never expire.  However, the participant may withdraw or take 
away their permission at any time. The participant may withdraw your permission by telling 
the study staff or by writing to Dr Mona Sharifi (mona.sharifi@yale.edu) at the Yale University, 
New Haven, CT 06520.
If the participant withdraws their permission, they will not be able to stay in this study but the 
care you get from your doctor outside this study will not change.  No new health information 
identifying the participant will be gathered after the date the participant withdraws. Information 
that has already been collected may still be used and given to others until the end of the 
research study to ensure the integrity of the study and/or study oversight.  
13.
Locations/Facilities
Table 3. Characteristics of Sites Selected for Implementation 
Site
Duke’s Primary 
Care Network 
CHOP’s Primary Care 
Research Network 
Eskenazi Health / 
Indiana University / 
IU Health
Geographic Region 
Southeast 
Northeast 
Midwest 
States 
NC 
PA & NJ 
IN 
Range among 
practices in 
25% - 73% 
5% - 48% 
14% - 74% 
7% - 8% 
16% - 78% 
9% - 65% 
APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026

APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026
Protocol Number 2000033551
1/16/2026 Version 1.11
30
Race/Ethnicity of 
patients, % 
Non-Hispanic Black 
Hispanic/Latino 
Non-Hispanic White 
14% - 46% 
9% - 65% 
5% - 23% 
Range among 
practices in % of 
patients covered by 
Medicaid 
10% - 80% 
10 – 73% 
80% - 88% 
Other characteristics 
of practices 
3 academic; 1 
FQHC; urban, 
suburban, & rural 
3 academic; 
urban, suburban, & rural 
9 academic and 
FQHCs; 
no rural but 8 in 
Primary Care Health 
Professional 
Shortage 
In addition to the three above-described study sites, study procedures will also involve Yale 
University and University of Florida. Yale will serve as the primary coordinating site for data 
and study operations. Study staff at University of Florida will be involved with the intervention 
evaluation.
6.
Statistical Design
8.
Sample Size Considerations
We plan to randomize 71 clusters of 81 clinical practices (35-36 clusters in treatment and 35-
36 control) across 3 sites, with an average of 10 physicians and a minimum of 1220 eligible 
children per practice. This was based on baseline data collected from patient visits at all 
primary care practices affiliated with the 3 participating health systems.  All calculations were 
adjusted for clustering effects using an intra-cluster correlation (ICC) of 0.1 for the physicians 
and 0.05 for the practice. All calculations were carried out using PASS 19 (Kaysville, Utah).
Hypothesis 1. We hypothesize that the implementation of the iPOP-UP intervention package will 
be associated with improved adherence to guidelines among primary care practices randomized to 
intervention versus usual care control. With a type I error rate of 0.025 (adjusted for 2 primary 
outcomes), we will have > 90% power to detect at a 7-10% increase in the adherence at 6-
months  over a control rate range of adherence from 10%-60%, assuming at least 1 visit per 
individual . This is based on data from estimates provided by the 3 sites. 
Hypothesis 2. We expect that patients with elevated BMI seen in intervention versus control 
practices will have a slower one-year increase in BMI. Data collected as part of the STAR 
intervention revealed standard deviations of approximately 1.8 kgs/m2 for one-year change 
APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026

APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026
Protocol Number 2000033551
1/16/2026 Version 1.11
31
in BMI. Assuming a 30% loss to follow-up ratea two-sided type I error rate of 0.025, we will 
have 90% power to detect differences in one-year change in BMI of about 0.35 kgs/m2 
(smaller than the observed value in our prior work.The USPSTF found the amount of 
absolute or relative weight change associated with moderate intensity obesity interventions 
was 0.85–3.3 kg/m2 difference in mean BMI 6–12 months after starting treatment, compared 
with controls.13 Thus, our sample size will allow for ample power to examine change in BMI.
Hypothesis 3 (Aim 3): We hypothesize that baseline practice and patient-level factors such 
as practice type, urban-rural location, and size and patient’s race/ethnicity, insurance status, 
severity of overweight/obesity and neighborhood characteristics will be associated with the 
effectiveness of the intervention and implementation strategy. The heterogeneity of the 
practices at the participating sites and above calculations suggest sufficient sample size to 
examine interaction terms and to conduct stratified analyses by baseline practice and 
clinician characteristics.
9.
Planned Analyses
Overall we will follow an intent-to-treat principle; we will analyze the practice based on 
the randomization and any patient who has a well-child visit in a participating practice 
during the implementation period will be considered a participant in the analysis, 
regardless of clinicians’ utilization of the EHR-based CDS tools. We will present 
descriptive statistics for cluster and individual level characteristics. Given that this is a 
cluster randomized trial, we will compare baseline characteristics of participants to 
determine whether there are differences across treatment groups.  We will adjust for 
individuals level covariates that are different, after taking into account multiple testing, 
during sensitivity analyses.  All analyses will be conducted using SAS version 9.4 and 
the latest version of R.
For hypothesis 1 (clinical care outcomes), we will determine whether there is a 
difference in adherence to guidelines at 6-months for visits in the treatment and control 
arms.  We will use generalized linear mixed models for binary outcomes, adjusting for a 
set of practice characteristics, which may include health system, proportion of patients 
that are publicly insured, proportions non-Hispanic Black, proportions Hispanic/Latino, 
proportions non-Hispanic White, geographic location (rural versus urban/suburban), 
practice size/volume, and academic vs. non-academic, and accounting for clustering of 
visits within physician and physician within a given practice. We will adjust for multiple 
testing using a two-sided, 2.5% type I error rate for each outcome and present 97.5% 
confidence intervals.
For hypothesis 2 (change in child BMI outcome), to make use of all data collected 
during the intervention period, we will analyze the %BMIp95 outcome using a linear 
mixed model adjusting for the covariate constrained randomization variables and the 
same a priori covariates as for the adherence outcome, time (month), the time by 
treatment interaction and clustering of individuals within practice .  and repeated 
APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026

APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026
Protocol Number 2000033551
1/16/2026 Version 1.11
32
measures over individuals over time. A contrast to test the comparison at the primary 
time point of 12 months (-/+ 3 months; utilizing “closest” measure to 12 mo) will be 
employed. Overall significance will be tested at a two-sided, 0.025 level and we will 
report 97.5% confidence intervals.
1.
Secondary Objective Analyses (if applicable)
For secondary analyses, we will use the same generalized linear mixed model approaches 
as the primary outcomes.  We will use a conservative type I error rate of 0.01 to control for 
multiple testing and present 99% confidence intervals.
Data from physician surveys will be presented descriptively and use generalized linear 
models adjusting for covariate constrained variables to compare changes in physician 
practices.
Table 3. Measurement of RE-AIM and CFIR constructs
 
RE-AIM construct
Quantitative Measures
Qualitative Measures
Reach: the extent to which the 
population included in the study 
reflects the target population.
Compare characteristics of practices 
and patients in the participating sites 
with all eligible practices/patients.
Adoption: Utilization of Epic CDS 
tools
EHR data and Provider survey 
questions regarding utilization and 
usability
Implementation:
·        Fidelity
·        Barriers to and Facilitators 
of implementation
·        Costs associated with 
implementation
 
Formal tracking of adaptations
Cost analysis
Maintenance: Proportion of sites 
that sustained the program after 
initial adoption
Interviews and focus 
groups to collect 
clinician perspectives 
on barriers to and 
facilitators of adoption, 
implementation, and 
maintenance
Staff interviews/focus 
groups: closed-ended 
question regarding 
continued program 
delivery at the time of 
staff interview/focus 
group
CFIR constructs
Quantitative Measure: 
Organizational Readiness to 
Change Assessment (ORCA)94 
mapped to CFIR domains:
Qualitative Measures
APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026

APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026
Protocol Number 2000033551
1/16/2026 Version 1.11
33
Characteristics of Intervention
ORCA items: Evidence Strength & 
Quality, Relative Advantage
System Usability Scale
Outer Setting
ORCA items: Patient Needs and 
Resources
Inner Setting
ORCA item: Structural 
Characteristics, Networks & 
Communications, Culture, 
Implementation Climate, Readiness 
for Implementation
Characteristics of the 
Individuals
 
Process of Implementation
ORCA item: Planning, Engaging, 
Reflecting & Evaluating
Structured interview  
and focus group 
guides with questions 
and probes assessing 
all 5 CFIR constructs 
adapted from guide 
available at 
cfirguide.org
2.
Analysis of Subject Characteristics (if applicable)
We anticipate describing the study sample using means and proportions. Example table:
Demographic Characteristics of Patients
Overall
Health 
System 1
Health 
System 2
Health 
System 3
Age at index visit, years, mean (SD)
Sex, N (%)
Male
Female
Race/ethnicity, N (%)
Non-Hispanic Black
Non-Hispanic White
Non-Hispanic Other
Non-Hispanic Multi
Hispanic/Latino
Hispanic/Latino Milti
Non-hispanic Asian
Other
Missing/not reported
Primary Language, N (%)
English
Spanish
Other
APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026

APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026
Protocol Number 2000033551
1/16/2026 Version 1.11
34
Missing
Primary Insurance, N (%)
Public/Medicaid
Private/Commercial
Other/Self-Pay/uninsured
Missing
Clinical characteristics of patients at 
index visit
BMI Measures, mean (SD)
BMI, kg/m2
BMI %ile
BMI z-score
%BMIp95
BMI Category, N (%)
Overweight
Class 1 Obesity
Class 2 Obesity
Class 3 Obesity
Characteristics of Primary Care Clinicians
Total number conducting index visits, 
mean (SD)
Specialty, N (%)
Pediatrics
Meds-Peds
Family Medicine
Emergency Medicine
Urgent Care
Other
3.
Interim Analysis (if applicable)
N/A
10.
Data Relevance
The data we plan to collect are directly related to the research questions by allowing our 
study team to assess the impact of iPOP-UP implementation in intervention vs control sites.  
11.
Data Coding
Data will be coded using de-identified study IDs. These IDs will include one component to 
indicate participant site, and a second component to indicate the individual participant. The 
APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026

APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026
Protocol Number 2000033551
1/16/2026 Version 1.11
35
IDs will be linked across data types (e.g., survey, EHR, interview). The key linking study ID 
to any identifying information (e.g., email address collected to facilitate providing incentive) 
will be kept in a separate folder on a Yale-managed, password-protected server. 
12.
Data Analysis Tools
All analyses will be performed using SAS v9.4 or the latest version of R. Qualitative data will 
be analyzed using Dedoose software.
13.
Data Monitoring
The study principal investigator (PI) is responsible for monitoring the data, assuring protocol 
compliance, and conducting safety reviews throughout this minimal risk study on at least a 
quarterly basis.  During the review process the PI will evaluate whether the study should 
continue unchanged, require modification/amendment, or close to enrollment. The PI and 
the Institutional Review Board (IRB) have the authority to stop or suspend the study or 
require modifications.
14.
Handling of Missing Data
We anticipate loss to follow-up and missing data for children who do not present within the 
one-year follow-up visit window of 9-15 months. We will utilize mixed models that employ the 
assumption of missing at random and plan to include all available data for individuals in the 
model regardless of whether it is complete (i.e. has 12 month information).  Further, we will 
explore patterns of missing data, and conduct sensitivity analyses using techniques for 
models that assume missing not at random (e.g. pattern mixture model).
7.
Data/Specimen Handling and Record 
Keeping
8.
Subject Data Confidentiality
Participant confidentiality and privacy are strictly held in trust by the entire study team. This 
confidentiality is extended to the data being collected as part of this study. Data that could be 
used to identify a specific study participant will be held in strict confidence within the research 
team. No personally-identifiable information from the study will be released to any 
unauthorized third party without prior written approval of the sponsor/funding agency. 
All research activities will be conducted in as private a setting as possible.
Data confidentiality procedures will vary based on data type:
Study survey data
APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026

APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026
Protocol Number 2000033551
1/16/2026 Version 1.11
36
The intervention surveys will be built on the Yale instance of REDCap.  Only Yale study staff 
will have access to the survey data in REDCap.
Qualitative data from interviews/focus groups
Interview audio recordings and transcripts will be saved on Yale managed, password-
protected servers. Interviews/focus groups will either be recorded by study staff at Yale or at 
University of Florida, and will be stored on institution-managed, password-protected servers. 
Queried EHR data
Limited data from participants’ queried medical record for analyses will be securely transferred 
from each site to Yale using OneDrive or another HIPAA-compliant modality that aligns with 
Yale’s data transfer policies. Yale will manage and securely store the data from all three sites 
for analysis.
Clinician email addresses, queried from the EHR along with the number of relevant visits they 
had during the trial period, will be used for survey recruitment and for linking study IDs across 
data types (e.g., survey, EHR, interview). Email addresses will be kept separate from the other 
queried data on Yale’s server.
Participants’ contact information (including name and email address) will be shared with Yale 
study staff for survey recruitment tracking, and will be securely stored at each study site for 
internal use during the study. At the end of the study, all records will continue to be kept in a 
secure, password-protected location for as long a period as dictated by the reviewing IRB, 
Institutional policies, or sponsor/funding agency requirements.
Study participant research data will be securely transmitted to and stored at Yale in password-
protected, Yale-compliant tools such as Box at Yale for statistical analysis and scientific 
reporting. These data will not include the participant’s contact or identifying information except 
as described elsewhere in this protocol. The study data entry and study management systems 
used by clinical sites and by Yale research staff will be secured and password protected. At 
the end of the study, all study databases will be de-identified and archived at Yale.
Measures Taken to Ensure Confidentiality of Data Shared per the NIH Data Sharing Policies 
It is NIH policy that the results and accomplishments of the activities that it funds should be 
made available to the public (see https://grants.nih.gov/policy/sharing.htm). The PI will ensure 
all mechanisms used to share data will include proper plans and safeguards for the protection 
of privacy, confidentiality, and security for data dissemination and reuse (e.g., all data will be 
thoroughly de-identified and will not be traceable to a specific study participant). Plans for 
archiving and long-term preservation of the data will be implemented, as appropriate. 
9.
Data Quality Assurance
All data to be analyzed in this trial (EHR data, surveys, and interviews/focus groups) will be 
collected into instruments built by the central (Yale) study team for this study specifically. 
Each site will collect data into these instruments to ensure data consistency across sites. 
APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026

APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026
Protocol Number 2000033551
1/16/2026 Version 1.11
37
SOPs will be written for each of the individual instruments, and staff training will be provided 
as requested. 
10.
Data or Specimen Storage/Security
Data storage/security is covered above, in the Subject Data Confidentiality section.
11.
Study Records
Study records include participant-level program data (surveys and queried EHR data). Study 
staff at each site will be responsible for maintaining these study documentation, and central 
(Yale) study staff will be responsible for maintaining all study documentation transferred 
to/held by Yale for analyses.
12.
Access to Source
Participants will complete the study surveys in REDCap or on paper with prompt entry into 
REDCap. All survey source data will remain in REDCap. Paper-based surveys will be 
shredded after entry into REDCap. EHR data that is queried from the sites will be transferred 
to Yale via Yale’s preferred method of secure data transfer. These data will be transferred 
directly to the study data manager, who will store the data on a Yale-managed HIPAA-
protected server. 
13.
Retention of Records
Records will be stored in accordance with Yale and NIH policies regarding data retention. 
14.
Data and Safety Monitoring Plan 
The principal investigator is responsible for monitoring the data, assuring protocol 
compliance, and conducting the safety reviews throughout the minimal risk study on at least 
a quarterly basis.  During the review process the principal investigator will evaluate whether 
the study should continue unchanged, require modification/amendment, or close to 
enrollment. The principal investigator and the Institutional Review Board (IRB) have the 
authority to stop or suspend the study or require modifications.
8.
Study Considerations
8.
Institutional Review Board (IRB) Review
The protocol will be submitted to the IRB for review and approval. Approval of the protocol 
must be obtained before initiating any research activity. Any change to the protocol will 
APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026

APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026
Protocol Number 2000033551
1/16/2026 Version 1.11
38
require an approved IRB amendment before implementation.  The IRB will have final 
determination whether informed consent and HIPAA authorization are required.  
Study closure will be submitted to the IRB after all research activities have been completed.    
Other study events (e.g. data breaches, protocol deviations) will be submitted per Yale 
policies.
9.
Research Personnel Training
Individuals assisting with the conduct of the research will be trained on all relevant aspects 
related to the trial before the trial begins, and on an as-needed basis after the trial has 
launched. Anticipated trainings include appropriate use of the data collection instruments 
and trial training materials that they may present to local participants. These trainings will be 
led by Yale study staff virtually (e.g., over Zoom). In addition, study SOPs will be developed 
and proactively shared with site study staff.
10.
Study Monitoring 
The study principal investigator (PI) is responsible for monitoring the data, assuring protocol 
compliance, and conducting safety reviews throughout this minimal risk study on at least a 
quarterly basis. During the review process the PI will evaluate whether the study should 
continue unchanged, require modification/amendment, or close to enrollment. The PI and 
the Institutional Review Board (IRB) have the authority to stop or suspend the study or 
require modifications.
11.
Unanticipated Problems and Protocol Deviations
This protocol presents minimal risks to the subjects and Unanticipated Problems Involving 
Risks to Subjects or Others (UPIRSOs), including adverse events, are not anticipated. In the 
unlikely event that such events occur, Reportable Events (which are events that are serious 
or life-threatening and unanticipated (or anticipated but occurring with a greater frequency 
than expected) and possibly, probably, or definitely related) or Unanticipated Problems 
Involving Risks to Subjects or Others that may require a temporary or permanent interruption 
of study activities will be reported immediately (if possible), followed by a written report within 
5 calendar days of the Principal Investigator becoming aware of the event to the IRB any 
appropriate funding and regulatory agencies. The investigator will apprise fellow 
investigators and study personnel of all UPIRSOs and adverse events that occur during the 
conduct of this research project through regular study meetings and/or via email as they are 
reviewed by the principal investigator.
APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026

APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026
Protocol Number 2000033551
1/16/2026 Version 1.11
39
Protocol deviations are expected in this real-world implementation study of an intervention 
embedded into routine care delivery. We will track these adaptations using an established 
framework from the field of implementation science and will generate hypotheses in our 
summative evaluation about how these adaptations may have influenced effectiveness and 
implementation outcomes.16
12.
Study Discontinuation
The principal investigator is responsible for monitoring the data, assuring protocol 
compliance, and conducting the safety reviews throughout the study on at least a quarterly 
basis.  During the review process the principal investigator will evaluate whether the study 
should continue unchanged, require modification/amendment, or close to enrollment. The 
principal investigator and the Institutional Review Board (IRB) have the authority to stop or 
suspend the study or require modifications.
13.
Study Completion
The end of the study is defined as the 24-month follow-up EHR query shown in the Schedule 
of Activities. The PI or proxy will notify the IRB and sponsor upon study completion.
14.
Conflict of Interest Management Plan 
The independence of this study from any actual or perceived influence, such as by the 
pharmaceutical industry, is critical. Therefore, any actual conflict of interest of persons who 
have a role in the design, conduct, analysis, publication, or any aspect of this trial will be 
disclosed and managed. Furthermore, persons who have a perceived conflict of interest will 
be required to have such conflicts managed in a way that is appropriate to their participation 
in the design and conduct of this trial. The study leadership has established policies and 
procedures for all study group members to disclose all conflicts of interest and will establish 
a mechanism for the management of all reported dualities of interest. All investigators will 
follow the applicable conflict of interest policies.
15.
Funding Source
National Institute on Minority Health and Health Disparities (5R01MD014853)
16.
Publication Plan
The PI holds the primary responsibility for publishing the study results. The NIH public 
access policy requires scientists to submit final peer-reviewed journal manuscripts that arise 
from NIH funds to PubMed Central immediately upon acceptance for publication. In addition 
APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026

APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026
Protocol Number 2000033551
1/16/2026 Version 1.11
40
to presentations at national meetings and publication of results, the study PI will be 
responsible for ensuring that the proposed research study is registered and that information 
about the results is submitted to ClinicalTrails.gov. The study will be registered in 
ClinicalTrials.gov no later than 21 calendar days after the enrollment of the first participant. 
Information about the results of the study will be submitted within one year after the study’s 
primary completion date. Any informed consent documents will include a specific statement 
relating to posting of clinical trial information at ClinicalTrials.gov.
APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026

APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026
Protocol Number 2000033551
1/16/2026 Version 1.11
41
9.
Appendices
Appendix #
Title
Section
Topic
APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026

APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026
Protocol Number 2000033551
1/16/2026 Version 1.11
42
10. List of Tables
11. References
1.
Rothman B, Leonard JC, Vigoda MM. Future of electronic health records: 
implications for decision support. The Mount Sinai journal of medicine, New York. 
2012;79:757-768.
2.
O'Brien SH, Holubkov R, Reis EC. Identification, evaluation, and management of 
obesity in an academic primary care center. Pediatrics. 2004;114:e154-159.
3.
Chelvakumar G, Levin L, Polfuss M, Hovis S, Donohoue P, Kotowski A. Perception 
and documentation of weight management practices in pediatric primary care. WMJ : 
official publication of the State Medical Society of Wisconsin. 2014;113:149-153; quiz 
154.
4.
Patel AI, Madsen KA, Maselli JH, Cabana MD, Stafford RS, Hersh AL. 
Underdiagnosis of pediatric obesity during outpatient preventive care visits. 
Academic pediatrics. 2010;10:405-409.
5.
Shaikh U, Berrong J, Nettiksimmons J, Byrd RS. Impact of electronic health record 
clinical decision support on the management of pediatric obesity. American journal of 
medical quality : the official journal of the American College of Medical Quality. 
2015;30:72-80.
6.
Young EL. Increasing Diagnosis and Treatment of Overweight and Obese Pediatric 
Patients. Clinical pediatrics. 2015;54:1359-1365.
7.
Gentile N, Cristiani V, Lynch BA, et al. The effect of an automated point of care tool 
on diagnosis and management of childhood obesity in primary care. Journal of 
evaluation in clinical practice. 2016;22:958-964.
8.
Taveras EM, Marshall R, Kleinman KP, et al. Comparative effectiveness of childhood 
obesity interventions in pediatric primary care: a cluster-randomized clinical trial. 
JAMA pediatrics. 2015;169:535-542.
9.
Ayash CR, Simon SR, Marshall R, et al. Evaluating the impact of point- of-care 
decision support tools in improving diagnosis of obese children in primary care. 
Obesity (Silver Spring, Md.). 2013;21:576-582.
10.
Kaufman TK, Gentile N, Kumar S, et al. Impact of Point-of-Care Decision Support 
Tool on Laboratory Screening for Comorbidities in Children with Obesity. Children 
(Basel, Switzerland). 2020;7.
11.
Wray CV, Brauer PM, Heuberger RA, Logomarsino JV. Improving Documentation of 
Pediatric Height, Weight, and Body Mass Index by Primary Care Providers. Canadian 
journal of dietetic practice and research : a publication of Dietitians of Canada = 
Revue canadienne de la pratique et de la recherche en dietetique : une publication 
des Dietetistes du Canada. 2018;79:186-190.
APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026

APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026
Protocol Number 2000033551
1/16/2026 Version 1.11
43
12.
Ogden CL, Carroll MD, Kit BK, Flegal KM. Prevalence of childhood and adult obesity 
in the United States, 2011-2012. Jama. 2014;311:806-814.
13.
Whitlock EP, O'Connor EA, Williams SB, Beil TL, Lutz KW. Effectiveness of weight 
management interventions in children: a targeted systematic review for the USPSTF. 
Pediatrics. 2010;125:e396-418.
14.
Moulton LH. Covariate-based constrained randomization of group-randomized trials. 
Clinical trials (London, England). 2004;1:297-305.
15.
Greene EJ. A SAS Macro for Covariate-Constrained Randomization of General 
Cluster-Randomized and Unstratified Designs. Journal of statistical software. 
2017;77.
16.
Wiltsey Stirman S, Baumann AA, Miller CJ. The FRAME: an expanded framework for 
reporting adaptations and modifications to evidence-based interventions. 
Implementation science : IS. 2019;14:58.
APPROVED BY THE YALE UNIVERSITY IRB 1/21/2026