Specialty Medical Homes to Improve Outcomes for Patients With IBD and Behavioral Health Conditions
Phase: NA
Conditions: Inflammatory Bowel Disease, Behavioral Symptoms
Sponsor: University of Pittsburgh

 
 
Study Title: Specialty Medical Homes to Improve Outcomes for Patients with Inflammatory 
Bowel Disease and Behavioral Health Conditions 
 
 
 
 
 
 
 
 
Contract Number: PCORI IHS-2017C3-8930 
Date: August 1, 2025 
 
Sponsor:  
 
Patient-Center Outcomes Research Institute (PCORI) 
 
1828 L St. NW, DC 20036 
 
Principal Investigators, Research Team, and Study Site: 
Eva Szigethy, MD, PhD 
Co-Principal Investigator 
 
Laurie Keefer, PhD  
Co-Principal Investigator 
 
Jane Kogan, PhD  
Co-Investigator 
 
Cara Nikolajski, PhD  
Co-Investigator 
 
Benjamin Cohen, MD, MAS 
Co-Investigator 
 
Meredith Wallace, PhD  
Co-Investigator  
 
Marla Dubinsky, MD 
Co-Investigator 
 
Stephen Lupe, PsyD 
Co-Investigator 
UPMC Center for High-Value Health Care 
U.S. Steel Tower 
600 Grant St. 
Pittsburgh, PA 15219 
 
University of Pittsburgh 
4200 Fifth Avenue 
Pittsburgh, PA 15260 
 
Icahn School of Medicine at Mount Sinai 
1 Gustave Levy Place 
New York, NY 10029 
 
Cleveland Clinic 
9500 Euclid Avenue 
Cleveland, OH 44195 
 
List of Common Abbreviations in Protocol: 
• BH: Behavioral health 
• IBD: Inflammatory bowel disease  
• SMH: Specialty medical home 
• UPMC ISD: UPMC Insurance Services Division  

 
 
 
Table of Contents: 
Research Synopsis………………………………………………………………………………………………………………….….1 
Background and Significance………………………………………………………………………………………………….….2 
Objectives……………………………………………………………………………………………………………………………….…3 
Aims…………………………………………………………………………………………………………………………………….…….3 
Interventions Compared………………………………………………………………………………………………………….…4 
Study Design/Methodology……………………………………………………………………………………………………….4 
Randomization Procedure………………………………………………………………………………………………………….4 
Measures…………………………………………………………………………………………………………………………………..5 
Study Population……………………………………………………………………………………………………………………….7 
Inclusion/Exclusion Criteria………………………………………….……………………………………………..…………….7 
Study Duration/Study Timeline………………………………….………………………………………………………………7 
Statistical Analysis Plan………………………………………………………………………………………………..……………8 
Informed Consent Process……………………………………………………………………………………….………………11 
Privacy and Confidentiality…………………………………………………………………………………………….………..12 
Risk/Benefit…………………………………………………………………………………………………………………….……….12 
Compensation for Participation………………………………………………………………………….……………………14 
Data Safety Monitoring……………………………………………………………………………………………………………14 
Conflict of Interest…………………………………………………………………………………………………..………………14 
Publication and Presentation Plans……………………………………………………………….…………………………13 
References………………………………………………………………………………………………………………….……………15 
 
 
 
 
 
 

1 
 
Research Synopsis 
Study Population: This research study will examine the impact of two existing approaches for 
delivering care within a specialty medical home (SMH) clinical model for patients with 
inflammatory bowel disease (IBD) and behavioral health (BH) conditions. Care approaches 
available to patients include traditional high-touch care delivered by a multidisciplinary team of 
IBD and BH clinicians (TEAM) and a health technology-based (TECH) approach that uses 
telemedicine and other evidence-based digital tools designed to deliver accessible, convenient 
care. This study seeks to understand the differential impact of TEAM and TECH on important 
health outcomes such as IBD and BH symptom severity, functional impairment, health care 
service utilization and costs, patient quality of life, and patient disease self-management. 
 
Study Design: A comparative effectiveness study using an individual-level randomized design 
along with a pragmatic, mixed-methods approach to compare two evidence -based SMH care 
strategies (e.g. high-touch multidisciplinary care and low-human touch technology-enhanced 
care). Quantitative (e.g. self-report, electronic health record, process) and qualitative (e.g. 
interviews) data will be collected across multiple time points during the study period. 
 
Sample Size: We expect to enroll 675 individuals.  
 
Study Duration: The contract period begins February 1, 2019 and concludes September 30, 
2026. Participants were actively enrolled in the study between July 1, 2019 and February 28, 
2024.  
 
Primary Aim 1: Examine the impact of TEAM vs. TECH on two main patient-centered outcomes 
of IBD and BH symptom severity and secondary outcomes of functional impairment, healthcare 
utilization, quality of life, and self-efficacy. 
Hypothesis 1: Both TEAM and TECH approaches will result in clinically meaningful 
improvement across all outcomes.  
 
Primary Aim 2: Examine the impact of patient characteristics on clinical response to TEAM or 
TECH approaches and establish subgroups of patients who will benefit most from each 
approach. The study focused on baseline IBD activity and age as primary moderators but 
secondarily explored site, IBD diagnosis, and health literacy. 
 
Hypothesis 2a: The TEAM approach will show greater effects in those with active IBD, while 
TECH will show greater effects in those with inactive IBD. 
Hypothesis 2b: The TECH approach will improve outcomes more in younger patients. 
 
Primary Aim 3: Examine IBD patient and provider perspectives on facilitators and barriers to 
efficient and effective implementation of TEAM and TECH and the potential for scaling the 
interventions and SMH model to other common chronic diseases and community care settings 
to inform high-quality, efficient ongoing implementation and dissemination. 

2 
 
Background and Significance 
Inflammatory bowel diseases, including Crohn’s disease (CD) and ulcerative colitis (UC), are 
among the most costly gastrointestinal (GI) conditions in the United States (US) and are life-
long chronic diseases that, if not well managed, can significantly disrupt the lives of individuals. 
IBD afflicts three million U.S. patients and families with incidence rising globally, especially 
among younger age groups, during a critical social and career development period.1,2 IBD is a 
relapsing and remitting condition associated with varying degrees of GI inflammation (disease 
activity) and related symptoms of abdominal pain, diarrhea, nutritional deficits and fatigue. In 
the presence of anxiety and depression, IBD symptom load is even higher, even when 
inflammation is mild or absent.3 IBD carries a financial burden between $14-31 billion annually 
in the U.S.,4,5 with about 30% of adult IBD patients accounting for more than 80% of IBD-related 
healthcare spend; the largest drivers of cost are surgeries and hospitalizations, many of which 
are preventable.6,7 Prior studies have shown that medical utilization (both emergency 
department (ED) visits and unplanned hospitalizations) is driven by serious disease and IBD 
activity requiring steroids, biologics, or surgery, chronic unexplained pain and related opioid 
use, and unaddressed or undertreated behavioral health (BH) problems.8-13  
 
IBD patients exhibit higher rates of comorbid BH conditions, especially anxiety and depression, 
than healthy counterparts – these further compound disease complexity.14 Indeed, when 
present, BH issues directly and negatively impact medical/surgical treatment response, 
adherence to treatment regimens, care utilization including surgeries, and disease-related 
quality of life and functioning.15-19 Emerging adults with IBD are a large and uniquely vulnerable 
subpopulation who, if not effectively integrated into an adult-centered healthcare system, are 
at significantly higher risk for poor disease outcomes,20 including high rates of anxiety and 
depression. Beginning in 2020, BH symptoms were further exacerbated by the COVID-19 
pandemic, particularly for IBD patients who reported elevated levels of anxiety surrounding 
their vulnerability and concerns about securing needed care.21-23  
 
Unfortunately, BH care has been siloed, falling short of the seamless, integrated health care 
necessary for complex patient populations. Most existing models of chronic, lifelong disease 
management do not adequately address psychosocial issues, nor necessarily address the 
individualized, whole health needs of patients at different stages of their lives, despite the 
recognized importance of these issues and their impact on health outcomes.24-26 Healthcare 
systems have not found optimal ways to provide integrated behavioral support in routine care, 
leading to unidentified or undermanaged psychological issues, impaired disease self-
management, and poor healthcare access and coordination.27-33 
 
In recent years, there has been transformative and widely accepted change around how care is 
organized and delivered with emphasis on meeting patients where they are.34-37 In primary 
care, medical home models have growing evidence for clinical efficacy, improved care quality, 

3 
 
and reduction in medical utilization and costs.37-42 Published studies show that these results are 
also attainable in specialty medical homes (SMH)43-48 including those focused on IBD.17,33,49  
Despite proven success, such intensive, highly staffed and resourced models are expensive to 
implement and may not be necessary for all chronically ill patients.50 Workforce limitations and 
patient concerns related to time, distance, and cost suggest that on-site multidisciplinary teams 
alone may not be sufficient to provide effective and efficient patient-centered care for the 
growing number of individuals with chronic diseases like IBD. Health technology, including 
digital interventions, remote monitoring of health outcomes, and telemedicine visits, is one 
way to address this gap with growing evidence linking its use to improved access and 
adherence to BH care and better outcomes.51-55 Patient preference results already support 
team-based care and health technology within SMHs,38,45,56,57  but less is known about how 
these models impact the outcomes that patients care about most and how to efficiently and 
effectively implement, maintain, and disseminate these approaches.  
 
Objectives 
 
The goal of this collaborative study is to provide evidence on the impact of two-evidence based 
SMH approaches on patient-centered disease and healthcare utilization outcomes at three 
academic medical centers in the northeastern US – UPMC in Pittsburgh, PA, Mount Sinai 
Hospital (MSH) in New York, NY, and the Cleveland Clinic Foundation (CCF) in Cleveland OH. 
 
To ensure our study’s focus was patient-centered, the study team worked closely with patient-, 
provider-, and system-level stakeholders to develop all aspects of this study protocol, including 
the early development efforts of in-person and technology-supported care approaches, the 
research questions, the study outcomes, the evaluation procedures, and the dissemination 
strategies included in this protocol.  
 
Aims 
This study aimed to compare the effectiveness of two evidence-based, patient-centered 
behavioral approaches implemented within three existing medical homes: TEAM, a high-human 
touch multidisciplinary team-based approach delivered at point-of-care, and TECH, a low-
human touch technology-based approach delivered at the patient’s convenience with the 
guidance of health coaches. The study focused on patient-centered outcomes, impact on 
healthcare utilization, determining which intervention worked best for whom, and potential 
scalability of the model to other healthcare environments and for other chronic conditions. 
 
Primary Aim 1: Examine the impact of TEAM vs. TECH on two main patient-centered outcomes 
of IBD and BH symptom severity and secondary outcomes of functional impairment, healthcare 
utilization, quality of life, and self-efficacy. 
Hypothesis 1: Both TEAM and TECH approaches will result in clinically meaningful 
improvement across all outcomes.  
 

4 
 
Primary Aim 2: Examine the impact of patient characteristics on clinical response to TEAM or 
TECH approaches and establish subgroups of patients who will benefit most from each 
approach. The study focused on baseline IBD activity and age as primary moderators but 
secondarily explored site, IBD diagnosis, and health literacy. 
 
Hypothesis 2a: The TEAM approach will show greater effects in those with active IBD, while 
TECH will show greater effects in those with inactive IBD. 
Hypothesis 2b: The TECH approach will improve outcomes more in younger patients. 
 
Primary Aim 3: Examine IBD patient and provider perspectives on facilitators and barriers to 
efficient and effective implementation of TEAM and TECH and the potential for scaling the 
interventions and SMH model to other common chronic diseases and community care settings 
to inform high-quality, efficient ongoing implementation and dissemination 
Interventions Compared 
TEAM is a high-human touch, multidisciplinary SMH approach that connects participants 
with a personalized care team including gastroenterologists, advanced practice providers 
(APP)s, BH specialists, dietitians, registered nurses, pharmacists, and health coordinators who 
provide intensive support and resources for patients. 
 
TECH is a low-human touch approach leveraging behavioral digital tools – primarily a digital 
cognitive behavioral therapy-focused mobile application with embedded health coaches – to 
deliver BH care at the patient’s convenience. 
 
Study Design/Methodology 
This multi-center study will involve an individual-level randomized design along with a 
pragmatic, mixed-methods approach to compare two existing care approaches, TEAM (high-
human touch) and TECH (technology-supported care), for delivering IBD and behavioral health 
services to individuals with IBD within and SMH model. Participants will be actively enrolled in 
the study for 12 months. Study participants will receive care from the IBD SMH clinical team per 
usual care delivery processes established for TEAM and TECH for the duration of the study.  
 
Randomization Procedure 
Eligible participants who consent to participate in the study will be stratified by age (18-30, 
31+), IBD disease activity (active/inactive), and IBD type (UC or Crohn’s) which will be assessed 
at enrollment and before randomization to ensure that intervention arms are balanced with 
respect to these variables. The age cut-off of 30 was chosen because it includes the age-range 
patients are most often transitioned from pediatric to adult care; 18 is the age patients have 
the right to make their own health choices, and age 30 is usually when patients transition off 
their parents’ health insurance. Within each stratum, random block sizes of two and four will be 
used to maximize balance between groups while minimizing the ability to unmask investigators 
to next treatment assignment, triggering an automated alert to staff on which approach to use. 

5 
 
We will monitor the randomization process throughout the study period to ensure there are no 
systematic differences between study arms and selection or assignment biases.  
 
Measures 
 
Primary outcomes 
IBD symptom severity will be captured from the IBD Complexity Composite Score58,59 which is a 
disease complexity grid developed for primary care patients that is used with IBD patients in 
order to quantify biological, psychosocial, and health system access domains of IBD, considering 
both history and current status so that integrated treatment can be personalized. It includes 
PROMIS GI symptoms scale60, a self-report of breadth and depth of GI symptoms and Harvey 
Bradshaw Index (HBI)61 and Ulcerative Colitis Activity Index (UCAI),62 provider-rated scales for 
IBD disease activity. IBD disease activity will also be assessed using the PRO-2 disease severity 
index, which is a brief, recently validated patient-reported assessment for individuals with 
Chron’s disease and ulcerative colitis.63,64  
Behavioral health symptom severity will be measured using scores from IBD Complexity Grid 
which uses the Patient Health Questionnaire Anxiety-Depression Scale (PHQ-ADS)65 – which 
combines the PHQ-8 and GAD-7 scales – as a composite measure of depression and anxiety. 
The Patient Health Questionnaire 8-item depression scale (PHQ-8)66 and 7-item Generalized 
Anxiety Disorder scale (GAD-7)67 are among the best validated and most commonly used 
depression and anxiety measures, respectively. The PHQ-ADS is the sum of the PHQ-8 and GAD-
7. 
Secondary outcomes 
Functional impairment will be measured using the Short Form 12 Health Survey Version 2 (SF-
12v2)68 which includes 12 items from the Short-Form 36 Health Survey and yields a physical and 
mental composite score as well as 8 subscale values: physical functioning, role-physical, bodily 
pain, general health, vitality, social functioning, role-emotional, and mental health. Lower 
scores correspond with poorer health-related functioning/quality of life.  
IBD-IBS Symptom Severity. The Irritable Bowel Syndrome Symptoms Severity Scale (IBS-SSS)69 
more accurately captures IBD symptom severity for many individuals with IBD, particularly 
those with inactive IBD but persistent functional GI symptoms (e.g., IBD-IBS). The IBS-SSS scores 
pain severity, pain frequency, abdominal bloating, bowel satisfaction and interference with life 
on a 0-100 scale with a total score of 500. A 50-point or more reduction in this score is 
considered clinically meaningful. 
Health care utilization will be captured categorically via medical record data including ED visits 
and hospitalizations.   

6 
 
Patient engagement will be measured using the IBD Self-efficacy Scale70 which assesses one’s 
confidence level in managing stress and emotions, managing medical care, managing symptoms 
and disease, and maintaining remission. 
Quality of life will be measured using the Short Quality of Life in Inflammatory Bowel Disease 
Questionnaire (SIBDQ)71.  
Covariates 
Patient demographic and clinical characteristics will be obtained through existing clinical and 
administrative data on age, gender, race/ethnicity, insurance type, IBD age of onset, surgical 
history, and presence of ostomy.  
e-health literacy will be measured using the eHealth Literacy Scale (eHEALS),72 which is an 8-
item measure of eHealth literacy developed to measure consumers’ combined knowledge, 
comfort, and perceived skills at finding, evaluating, and applying electronic health information 
to health problems.  
Engagement in interventions will be assessed using automatically generated usage statistics, 
administrative/utilization data routinely collected for in-person visits, remote monitoring 
activity, and other intervention technologies. The integrity of care delivery for both approaches 
will be evaluated with existing checklists as part of weekly team huddles.      
Resiliency will be measured using the Connor-Davidson Resilience Scale (CD-RISC 10),73 a 
validated, clinician-administered, EHR-integrated tool that quantifies, on a 100-point scale, an 
individual’s personal strengths (high resiliency) vs. complexity (low resiliency). 
Physical and behavioral health comorbidity will be assessed using the DSM-5 Cross-Cutting 
Symptom Measure74 which is an informant-rated measure that assesses current mental health 
domains across psychiatric diagnoses. ICD 10 codes will be used for current and past psychiatric 
diagnoses from initial SMH visit and past year ICD 10 codes for medical diagnoses. 
Medications will include the use of psychotropic, opioid, and IBD medications. 
Transition Readiness will be measured using the Transition Readiness Assessment 
Questionnaire75 (TRAQ), a self-reported assessment of health and skills needed for 
management of chronic disease and will evaluate patient readiness to change from traditional 
care to patient-centered care where patients and a provider team collaborate on treatment 
decisions. 
Clinic/clinician characteristics will be assessed using clinician self-report years of experience and 
site-level patient load data. This information will be coupled with the “Engagement in 
interventions” variables described above. 
 

7 
 
Process measures 
Patient participant and ICT staff perceptions/experience will be assessed via telephonic 
qualitative interviews with a sample of patient participants and SMH clinical staff to examine 
perceived barriers and facilitators to efficient and effective implementation of TEAM and TECH 
and to identify strategies for improvement and scalability of SMH to other chronic diseases.    
Integrity of care/fidelity: For both interventions, we will track usage information such as time 
spent on each session in each arm, techniques covered in practice, techniques practiced, and 
total number of sessions and techniques completed. For the TEAM arm, the social workers will 
track if other types of therapy modalities were included from a comprehensive list that can be 
quantified. For the TECH arm, text messaging from the behavioral coaches will be reviewed for 
fidelity as part of routine care. Prescription of adjunctive psychotropic medications as part of 
stepped behavioral care will be tracked in both arms. 
 
Study Population 
Our study population will comprise IBD patients receiving care at one of the three included 
SMHs with a confirmed diagnosis of Crohn’s or UC, age 18 to 60 with BH symptom severity in 
the mild to severe range, defined as a score of >=6 on either depressive or anxiety severity 
scales (PHQ-4). 
 
Inclusion/Exclusion Criteria  
Inclusion Criteria 
Individuals who (1) are age 18-60; (2) have a diagnosis of Crohn’s or UC; (3) have mild-to-severe 
behavioral health symptoms, defined as >=6 on either depressive or anxiety severity scales 
(PHQ-4); (4) consent to be randomized; (5) must have a smartphone; and (6) speak English.  
 
Exclusion Criteria 
Individuals who are (1) not able to speak English; (2) do not have a smartphone; and/or (3) 
exhibiting acute BH symptoms that require a higher level of treatment (e.g., suicidality, active 
eating disorder).  
 
Study Duration/Study Timeline 
February 1, 2019 – June 30, 2019: Pre-Implementation Period 
July 1, 2019 – March 28, 2025: Implementation Period  
March 29, 2025 – September 30, 2026: Post-Implementation Period 
 
 
 
 
 
 
 
 

8 
 
Statistical Analysis Plan 
Sample Size and Power Calculations 
The bundles of TEAM and TECH services have been tested as packages. For the TEAM approach, 
we evaluated the feasibility, durability, and impact of the IBD specialty medical home for 346 
IBD patients after one year of enrollment.58 In the year following enrollment, there was a 
significant reduction in IBD disease activity for both UC (p=.0003) and CD (p=.002), unplanned 
care (both ER visits (p<.0001) and hospitalizations (p=.008), while there was an observed 
improvement in health-related quality of life (p<.0001), depression (p<.0001) and anxiety 
(p=.02). For the TECH approach, a combination of digital tools- an app based cognitive 
behavioral program, remote monitoring and telepsychiatry (TECH) was compared to behavioral 
treatment as usual (control) using a randomized trial prospective design for patients with IBD 
with anxiety and/or depression. There was a significantly greater reduction in anxiety in the 
TECH group over 3 months (delta 5.6); CI (3.9, 7.6); p<.0001; n=34) than in the control group 
(delta 2.5; CI (0.5, 4.6); p=.02; n=35. There was also a greater reduction in depression (delta 2.6 
CI (0.6, 4.6); p=.01 in the active versus control group (delta=.0.4; CI (-2.2, 3.1); NS).76 Ninety-six 
percent of patients in TECH group engaged with the digital CBT program and participated in 
remote monitoring with 69% completing a clinically meaningful number of sessions. Both 
studies were conducted in “real world” clinical setting and powerfully show how both 
approaches can provide powerful solutions in improving health care delivery in sustainable 
ways. 
 
Aim 1: We calculated statistical power for the target sample size of 675, with approximately 
337 participants enrolled into both TEAM and TECH. After adjusting for the multiple testing in 
Aim 1 (2 tests) and considering 25% attrition, a sample size of 505 (approximately 252 per 
treatment group) will provide over 99.9% power for the hypothesis test for Aim 1. Among 
patients enrolled in the specialty medical home at that time who met active behavioral criteria 
(PHQ-4 >= 6), there was a significantly greater change in TECH (n=73; ES .49) versus TEAM 
(n=106; ES .36) for the behavioral composite but both approaches were associated with 
significant change over time (p=.005). Both approaches were also associated with significant 
improvement in the biological composite for both TEAM (ES .22) and TECH (ES .16). With the 
IBD SMH models of care being clinically operational at all three sites, we are collecting ongoing 
useful and robust information that has been published. In our most recent analyses of our 
clinical research registry tracking our TEAM approach (n=280), our most recent analyses show 
effect sizes comparable to these initial findings for both approaches.   
 
Aim 2: We considered both subgroup analyses and formal tests of moderation. Subgroup 
analyses – Based on current data, our subgroups are relatively evenly proportioned. We expect 
that the smallest subgroup will be 42% of the sample and the largest will be 58% of the sample. 
Thus, our expected subgroup sizes after 25% attrition are between 212 and 293 for projected 
enrollment. For this range of subgroup Ns, we expect 0.80 power to detect small treatment 
effects ranging between 0.26 and 0.30. Moderation – We used Monte Carlo methods (100 runs) 
to simulate the binary moderator (M) and treatment (X) (both p=0.5), assuming M independent 
of X as expected in a randomized trial. Considering a range of effect sizes for B1, B2, and B3, we 
estimated the outcome Y as Y=B1*X+B2*M+B3*X*M+ ε, where ε~N(0,1). We averaged across 

9 
 
scenarios to determine the typical effect of B3 that can be detected with our current and 
projected sample sizes after 25% attrition. B3 can be interpreted as the difference between the 
treatment effect size among those with M=0 (D0=B1). With our projected sample sizes (N=505 
after 25% attrition), we expect 0.80 power to detect a significant interaction when the 
magnitude of B3 is at least 0.50. To provide context for these effect sizes, we note that a B3 of 
0.50 could correspond, for example, to a moderate effect of X in one subgroup (e.g., D1=0.60) 
and a small effect of X in the other subgroup (e.g., D0=0.10). 
 
Our sample size calculations are consistent with the literature for both TEAM and TECH for 
behavioral and physical disease severity outcomes77-82 and there is literature supporting 
engagement and better outcomes with TECH approach with the younger cohort and those with 
higher eHealth-literacy.62 However, the research proposed will be beneficial even if we do not 
prove our hypotheses. For example, even if TEAM and TECH do not differ in Aim 1, the results 
can still suggest that TECH is feasible and allows TEAM to be utilized more efficiently. In Aim 2, 
even if we do not show a strong differential impact of the interventions based on IBD activity, 
we will still learn valuable information about which subgroups of behaviorally complex IBD 
patients have highest engagement and impact with each approach. 
 
Quantitative Analysis 
We will conduct descriptive analyses and multivariate modeling of data to examine changes in 
outcomes over time and explore moderating variables. All analyses will be intent to treat and 
conducted as described in our analytic plan and associated protocol. If diagnostic or sensitivity 
analyses dictate changes to those plans, we will clearly identify subsequent analyses as ad hoc 
or otherwise deviating from an a priori plan, including labeling subgroup and interaction 
analyses as confirmatory, exploratory, or post hoc. Our statistician will remain masked to study 
arm to reduce bias.   
 
Prior to hypothesis testing for Aims 1 and 2, data will be explored by descriptive data analysis. 
Summary statistics including means, standard deviations, medians, and ranges for continuous 
variables, or frequencies and percentages for categorical variables, will be presented for the 
entire sample and stratified by approach at each time point. We will assess the balance of key 
covariates by visually assessing the standardized differences. We will conduct baseline data 
analysis for each outcome to explore any pre-intervention differences in outcomes between 
TEAM and TECH at baseline. Two-sided Wald T-test or Wald F-test using the generalized linear 
mixed models (GLMMs) with normally distributed random effects for three sites will be used. 
This estimating method using GLMMs will produce consistent estimations of the regression 
parameters under the missing at random (MAR) or missing completely at random (MCAR) 
mechanism. The MAR assumption will be verified in the sensitivity analysis (see handling 
missing data in quantitative analyses). Distributions of outcomes and key covariates over time 
will also be visually examined to identify systematic departures from normality and overall 
pattern over time, assisting us in evaluating the distribution of data and determining if 
assumptions are met for subsequent modeling approaches. We will conduct statistical analysis 
on transformed outcomes using Box Cox- or log-transformation to address any asymmetry.  
 

10 
 
Aim 1 will examine the impact of TEAM vs. TECH on the primary and secondary outcomes and 
will determine if changes in outcomes over time are different between the two groups. We will 
fit the GLMMs to associate each outcome with the intervention (TEAM vs. TECH) and other 
covariates of interest. To account for the within-patient correlation in longitudinal data and to 
reflect potential differences among three sites, we will add normally distributed random effects 
for patients and sites in addition to the fixed effects for intervention and covariates of interest. 
An inference of the intervention effects for each outcome will be carried out using Wald test 
based on the either F-distribution or Chi-square distribution as appropriate. For each outcome, 
the null hypothesis of homogeneous change in outcomes overtime between TEAM and TECH 
will be examined by testing the treatment-by-time interaction effect on each outcome. In the 
absence of significant interaction effects, the marginal difference in outcomes between TEAM 
and TECH will be examined using the same GLMMs without the interaction effect. All 
hypothesis tests for Aim 1 will be conducted at the overall significance level of 0.05. The score 
changes from baseline to each time point and their difference between TEAM and TECH will be 
estimated with 95% confidence intervals.  
 
Given our study Aim 2 to understand how TEAM and TECH provide different benefits to 
individuals with different characteristics, we will explore potential heterogeneity of treatment 
effects in clinical response between subgroups of patients defined using patients’ baseline 
characteristics. All co-variates will be identified a-priori. For Aim 2.a, we will examine whether 
and how the effect of TEAM and TECH approaches on BH symptom severity varies between 
patients with a high level of IBD disease activity (HBI or UCAI score > 4) and patients with low 
disease activity (HBI or UCAI score <=4) at baseline. IBD disease activity and effect of TEAM and 
TECH approach will also be assessed using a recently developed, validated, and preferred 
measure of disease activity for Crohn’s disease and UC (PRO-2).63,64 For statistical inference, we 
will fit the same GLMMs as described in Aim 1 and will include the higher order interaction 
terms with subgroups of patients defined by IBD activity. The null hypothesis of homogenous 
treatment effect between patients with high and low IBD activity in each outcome will be 
examined via interaction analysis (three-way interaction of time, treatment, and subgroup of 
IBD severity; two-way interaction of treatment and subgroup of IBD severity in the absence of a 
significant three-way interaction effect) using Wald test based on either F-distribution or Chi-
square distribution as appropriate at the significance level of 0.05. In the presence of 
statistically significant treatment heterogeneity, the score change in BH symptom severity from 
baseline to each time point and their difference between TEAM and TECH will be estimated 
with 95% confidence intervals for subgroup of patients defined by IBD severity. For Aim 2.b, we 
will explore whether and how the effect of TEAM and TECH approaches on primary outcomes 
varies between young (age<=30) and older (age>30) patients. We will also examine the impact 
of TEAM and TECH on patients with differing IBD diagnoses, namely ulcerative colitis and 
Crohn’s disease. Further, we will explore the effect of site differences, behavioral health 
history, insurance type (public vs. not), e-health literacy, and medications on response to TEAM 
or TECH intervention as secondary and exploratory analyses. For statistical inference, the same 
hypothesis test and statistical model described in Aim 2.a will be used. We will make a 
Bonferroni correction for multiple testing in order to conduct subgroup analyses at the overall 
significance level of 0.05. In the presence of statistically significant treatment heterogeneity, 

11 
 
estimation of score changes in each outcome and their difference between TEAM and TECH will 
be presented with 95% confidence intervals for each subgroup of patients.  
 
In handling missing data in quantitative analyses, we will attempt to determine the reasons for 
missing data and dropouts. The MAR assumption will be examined by comparing baseline 
characteristics between participants with and without missing data and conducting sensitivity 
analysis by repeating the main analyses without participants with missing data. If we observe 
statistical evidence that data are not MAR, we will stratify the participants into subgroups that 
share the same missing data pattern and estimate the statistical model separately for each 
missing data pattern. The results of all missing data analyses will be presented, and the 
sensitivity of our inference to the assumptions and approaches will be included in the 
interpretation of results. 
 
COVID Considerations for Aims 1-2: Of our 675 projected participants, 32 were enrolled and 
completed their 6-month/primary outcomes surveys before the beginning of the COVID-19 (i.e., 
prior to March 12, 2020); 211 are potentially COVID-confounded (i.e., enrolled prior to or 
during the acute phase of the pandemic and were followed during it), and 432 were enrolled in 
the post-COVID phase of the study (after June 2021). Primary analyses will focus on the full 
sample of N=675, controlling for whether the participant was COVID-confounded. In sensitivity 
analyses, we will include only participants enrolled during the post-COVID phase. Effect sizes 
from sensitivity analyses will be assessed to evaluate whether findings are similar to those from 
the primary analyses. 
 
Qualitative Analysis 
For Aim 3, qualitative interviews will be transcribed verbatim to support the analytic process. 
Separate codebooks for patients and provider interviews will be constructed and follow 
standard editing methods,83 including audit trails to document creation of codes during the 
iterative process. Two trained independent analysts will code the interviews in Dedoose, an 
qualitative analysis software. After each transcript is coded, coders will meet to process and 
adjudicate differences until agreement is achieved. Codes determined through this process will 
be recorded in a master file to be used in final analysis. For each qualitative cohort and wave of 
data, we will examine key topics to better understand barriers and facilitators to intervention 
implementation and how SMHs impact patients’ ability to manage IBD and behavioral health 
conditions. In addition, for each subsequent wave of data collection, we will examine changes 
and consistency across the data waves. 
 
Informed Consent Process 
If a patient is eligible and is interested in participating in the study, the research 
assistants/research staff will provide the patient with a copy of the consent form to review and 
obtain informed consent during a clinic visit. Patients will be given the opportunity to take the 
consent form home to further consider participation in the study. Participants may return the 
signed consent form by using a prepaid envelope provided by the study team or in-person at 
later clinic visit. 

12 
 
Study participants will be given a copy of the informed consent to read and research staff will 
be available to describe its content and answer any questions about the study. Any questions 
that cannot be answered by research staff will be referred to the PI prior to proceeding with the 
consent process. All participants will be given an opportunity to take the informed consent 
document home for further consideration before consenting. Research staff will provide 
participants with contact information for research staff and the PI so that any questions they 
may have can be answered before providing consent. Research staff will make it clear to 
participants that their decision to participate or not in the study will have no impact on the 
medical care they receive and will stress to the participant that participation in the study is 
voluntary (their choice). Research staff will also make it clear to participants that they may 
withdraw their consent at any time during the course of the study. 
 
Privacy and Confidentiality 
Self-report and qualitative data collected for this study will be used for research purposes only. 
Access to the data will be restricted to the PI, Co-Is, and other Research Team members trained 
in UPMC and University of Pittsburgh HRPO Human Subject Research Training requirements. 
Research staff will sign confidentiality agreements as required. Identifying links to all data will 
be maintained at baseline and other data collection time points using a secure password-
protected server, accessible only by authorized members of the study team. Once the data is 
collected, the file containing the link between identifying information and the participant's data 
will be destroyed. 
Qualitative data will be audio recorded using digital recording devices, transferred to a 
secure server immediately following recording and deleted as soon as it is fully transcribed. 
Interviews will be audio recorded, transcribed, and scrubbed of identifying information. 
Participants will be asked not to include any identifying information in their responses, and 
coders will not code any identifying information that may be provided inadvertently.  
All data obtained over the course of the study will be confidential and secure. Paper study 
records will be secured using the “double-lock” method (i.e., in a locked cabinet within a locked 
office). Data stored on computers will be password protected and stored on a secure server 
behind the organization’s firewall. Each Research Team member has a unique network account 
and a secure password that complies with existing institutional policies and procedures. Only 
members of the team who are authorized by the PI will have access to the secured files. 
Identities of participants will not be revealed in the publication or presentation of any results 
from this study. 
 
Risk/Benefit 
Risk to Participants 
Infrequent (Rare) Risks:  
- 
The risks associated with this study include the potential for a breach of confidentiality 
for both groups in the study. To reduce the risk of that happening, we will protect the 
confidentiality of this information by giving all participants a unique study ID that will be 
kept separate from any identifying information. The final data set will be de-identified 
prior to analysis and done so according to HIPAA standards. 

13 
 
- 
Participants will be asked questions about private, personal matters and information 
related to their health. They may feel uncomfortable answering questionnaires or 
assessments or discussing their health with the research team. They may also feel tired 
from answering questionnaires or having discussions with the research team. There are 
no known psychological or physical risks associated with the questionnaires and 
assessments that will be used for this study. Participants will be given the option to stop 
the assessments or take a break at any time.  
- 
Participants will be monitored by the PI and other members of the research team 
throughout the duration of the research study. If a participant reports clinical distress to 
a member of the research team (via study assessment or other form of communication), 
then the research team will immediately contact the PI. The PI will contact the 
participant personally to ensure their immediate safety and offer referral for 
appropriate care. If a clinically significant, unexpected disease or condition is identified 
during the conduct of the study, members of the IBD SMH will systematically monitor 
the physical health status of all participating patients through routine care management 
and patient-level interactions. The assessment of adverse medical sequelae will be 
managed through a participant's existing and routine care. If during research 
assessments a high level of medical risk is identified, the research team will attempt to 
ascertain the nature and level of risk and immediately contact IBD SMH clinical staff for 
direct follow-up with the participant. The IBD SMH clinical staff will directly contact the 
participant and refer them to the appropriate level of care in accordance with 
established protocols 
- 
Electronic or smartphone communications (e.g., text messages, emails, video visits) or 
internet communication that may happen as part of normal IBD care cannot be 
guaranteed as confidential. It is possible that confidential information may be collected 
and used by individuals who do not have permission to do so. All study sites take 
precautions to prevent this from happening, but there is still a risk that confidentiality 
may be breached. All electronic study records will be password protected and stored on 
secure institutional networks or REDCap Cloud, a HIPAA-compliant and secure web-
based data collection platform. Paper-based records will be stored in locked filing 
cabinets and only accessible to members of the research team. 
Unknown Risks:  
- 
In addition to the risks listed above, there may be other risks to participant health or 
well-being that are unknown at this time. They study team proactively monitors 
participant safety during participation in this research study. 
 
Benefits to Participants  
Participants may not directly benefit from research procedures but may benefit from the 
clinical care approaches being studied in terms of improved physical and behavioral health 
symptoms, quality of life, and satisfaction with their care. 
 
 
 

14 
 
Compensation for Participation 
Total possible compensation for the entire study: $140 
 
 
Timepoint 1: $20 for baseline self-report measures  
Timepoint 3: $20 for 6-month self-report measures 
Timepoint 4: $40 for 12-month self-report measures 
 
Timepoint 1: $30 for baseline interview  
Timepoint 2: $30 for 6-month interview 
 
Data Safety Monitoring 
Dr. Szigethy (Co-PI) will be responsible for data and safety monitoring. She will meet with the 
study team to review all data protocols and policies, including informed consent and data 
confidentiality procedures. Co-investigator leads at each participating research site will likewise 
regularly meet with their respective research teams to review all data protocols and policies. All 
key personnel will adhere to the National Institutes of Health (NIH) policy on education in the 
protection of human subject participants in the conduct of research. Additionally, we will 
convene biannual Data Safety and Monitoring Board (DSMB) meetings to ensure any issues 
related to participant or data safety are fully addressed.  
 
Conflict of Interest 
Drs. Laurie Keefer (Co-PI) and Marla Dubinsky (Co-I) are named inventors on the patented 
technology entitled "GRITTIBD" (the technology being investigated in this study). The GRITT-IBD 
technology has been licensed to Trellus Health by the Icahn School of Medicine at Mount Sinai. 
Trellus Health is a public, for-profit company that develops digital health solutions to manage 
chronic conditions such as Inflammatory Bowel Disease (IBD). Dr. Keefer is a co-founder, equity 
owner, consultant, and scientific advisory board member of Trellus Health. Dr. Dubinsky is CEO, 
a co-founder, equity owner of Trellus Health. Dr. Dubinsky is also co-founder, scientific advisor, 
and equity owner at MiTest Health. In addition, the Icahn School of Medicine at Mount Sinai 
has equity ownership in Trellus Health. A Data Management Plan was developed to ensure 
appropriate management. 
 
Publication and Presentation Plans 
We will form a Stakeholder Dissemination Committee in Year 5 of the study. The committee will 
be comprised of members from the Stakeholder Advisory Board, the Site Working Groups, and 
additional stakeholders with interest/expertise in SMH models. Collaborators include the 
Crohn’s and Colitis Foundation, the Pediatric IBD Foundation, Connecting to Cure Crohn’s and 
Colitis, and UPMC Health Plan.  
 
 

15 
 
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