Integrating Community Health Workers Into Primary Care Teams to Improve Diabetes Prevention in Underserved Communities
Phase: NA
Conditions: Diabetes Mellitus
Sponsor: NYU Langone Health

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Study: Integrating Community Health Workers to Improve Diabetes Prevention 
NCT Number: NCT03006666 
Document Date: March 21, 2019 
Research Protocol 
 
Purpose of the Study and Background 
 
Purpose of the Study 
Type 2 Diabetes Mellitus (DM) is a preventable chronic disease that affects 9.3% of US adults and children. It is 
estimated that 86 million American adults are prediabetic (37%), and thus at risk of DM and cardiovascular 
disease. DM is a leading cause of death, one of the major causes of heart disease and stroke, and severely 
threatens quality of life. DM more than doubles the health care costs compared to the general population. 
Safety-net institutions like Bellevue Hospital Center (BH) and the VA NY Harbor Healthcare System (VA) care 
for populations with a disproportionate burden of DM and DM risk. Nearly 25% of the 8.7 million US veterans 
have DM and the rate among Bellevue’s 30,000 primary care adult patients is more than 15%. 
 
Despite the potential for reduced morbidity and cost-savings, primary care systems must overcome several 
barriers to systematically deliver these proven, preventive strategies to patients at highest risk of DM. 
Employing community health worker (CHW) coaches to conduct behavioral counseling, follow-up referral to 
programs, and education is a promising approach that could extend the capacity of health systems to better 
prevent and manage chronic conditions. Despite the potential for peer-led intervention to enhance DM 
prevention efforts within the patient-centered medical home (PCMH) model, there is need for high quality, 
randomized trials to asses specific models for CHW support; to aid with implementation of such model, 
including identification of effective strategies for recruitment, training, monitoring and retention of lay 
personnel; and to successfully integrate these personnel within the PCMH. 
 
The goal of this proposal study is to develop and test a model of CHW health coaching, designed to prevent the 
onset of Type 2 DM in a large population of underserved patients at risk. CHWs will be recruited from the 
target populations and trained in core competencies to serve as peer health coaches. Our central premise is that 
CHWs are uniquely suited to engage fellow patients by encouraging lifestyle change through shared 
experiences and social support to extend the reach of primary care (PC) beyond the clinic visit. This study will 
test a scalable model of peer health coaching to address the millions of patients at risk for DM, using low cost, 
culturally congruent personnel to promote prevention of DM in PCMH practice. 
 
Background 
Type 2 DM is a preventable chronic disease that affects 11% of US adults. An additional 35% (79 million) have 
pre-DM and thus at risk of developing DM and cardiovascular disease. DM is a leading cause of death in the 
US and a major cause of heart disease and stroke. It is essential that the US leverage prevention strategies to 
mitigate the health and economic impact of DM in the population. Up to 20% of adult PC patients at BH and 
25% of veterans at NY Harbor have DM, 2x and 3x the rate in the general population, respectively, and this rate 
has been steadily increasing. There is also a substantial population with undiagnosed pre-DM, half of who are 
expected to develop DM in the next decade. Our preliminary analysis of VA NY Harbor data from 2010-2012 
showed that 9,610 (62%) of 15,500 veterans <75 years old, without DM, had a glycosylated hemoglobin 
(HbA1c) test, and 1,730 (18%) of them had pre-DM. 
 
Study Design 
We will conduct a cluster-randomized trial to test the impact of peer health coaches on prediabetic patients 
cared for by PCMH teams at BHC and VA to: 
1. Reduce the incidence of type 2 DM in pre-diabetic, PCMH patients; 
2. Promote weight loss among pre-diabetic patients; 
3. Increase patient activation levels, a measureable construct of engagement, efficacy, skills, and confidence in 
managing one’s health, among pre-DM patients, resulting in: 
a. Improved secondary clinical outcomes: better glycemic and blood pressure control, and lower 
Framingham risk scores; 

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b. Increased utilization of preventive services (e.g. MOVE!, TeleMOVE!, Healthy Lifestyles, etc.); 
c. Improved health behaviors (e.g. making dietary and exercise changes); and 
4. Develop, implement and assess strategies to recruit, train, and integrate peer CHW health coaches within the 
PCMH model. 
 
The 36-month intervention will be conducted using a staggered entry design across four, overlapping, 12-
month waves to account for CHW caseload limits. This study will test a scalable model of peer health coaching 
to address the millions of patients at risk for DM, using low cost, culturally congruent personnel to promote 
prevention of DM in PCMH practice. If successful, our study team will work with VA’s Central Office and NY 
City’s Health and Hospital Corporation to translate the model for larger scale implementation. 
 
Characteristics of the Research Population 
 
Number of Subjects 
All 12 PC teams at VA NY Harbor and all 4 PCMH teams at BH will be eligible to participate. In our VA PROVE 
study, 51/52 PCPs participated in the intervention, and we expect similar rates in this project. Eligible patients 
will be identified through the study’s pre-DM registry, which will be based on the EMR and Corporate Data 
Warehouse (CDW) at each site. This methodology builds on our ongoing national, retrospective cohort study of 
predictors of DM among veterans with pre-DM back to 2008. Based on preliminary analysis of VA NYHHS 
data from 2010-2012, 62% of veterans enrolled in PC without DM, have had an HbA1c test in the previous two 
years.  
 
In the intervention group, we anticipate contacting 2,100 randomly selected patients (1,050 at the VA* and 
1,050 at BH) to ultimately enroll about 1,100 patients (550 at the VA and 550 at BH). This outreach sample 
reflects our assumption that 20% of patients will be unreachable and that 60% of those reached will enroll in 
the study. Another 1,100 patients attributed to control group providers will be randomly selected as the control 
group, in accordance with the waiver of HIPAA authorization. As detailed below, the control group will not 
participate in the CHW intervention. The total sample, including the intervention and control groups, will be 
about 2,200 patients. This amounts to approximately 265 patients (across intervention and control groups) per 
wave and per clinical site. 
 
*We will work closely with the staff of another research study being conducted at the VA that has 
similar eligibility criteria, resulting in dual-eligible patients. In order to avoid patients being enrolled in 
both studies, which could result in patient burden, both studies will work with a statistician to identify 
these dual-eligible patients and randomly assign them to one study only prior to patient outreach and 
recruitment. 75% of these dual-eligible patients will be allocated to our study and 25% will be allocated 
to the other study in accordance with both programs’ statistical power needs. Since both studies are 
similar in scope (e.g., weight loss, increasing exercise), we do not anticipate patients enrolled in one 
study will receive greater health benefits than patients enrolled in the other study. 
 
Gender of Subjects 
Subjects of both genders are included in the study. 
 
Age of Subjects 
The minimum age of the subjects is 18 and the maximum age is 75.  
 
Racial and Ethnic Origin 
There are no enrollment restrictions based upon race or ethnic origin. 
 
Inclusion Criteria 
Inclusion criterion: Having at least one HbA1c result in the prediabetic range (5.7-6.5%) in the 2 years prior to 
the start date of the study wave. In order to communicate with CHWs, patients must also speak either English 
or Spanish. 
 

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Exclusion Criteria 
A diagnosis of DM, based on ICD-9 and ICD-10 codes applied during ambulatory encounters in the 2 years 
prior to the study wave; treatment with DM medication other than metformin (e.g. insulin or oral agents); age 
greater than 75 years; or exclusion by patient’s PCP due to contraindication for lifestyle intervention or CHW 
outreach. 
 
Vulnerable Subjects 
The protocol includes collecting data from BH and VA clinical providers whose participation is vital to the 
success of the study. There is no coercion to enroll these clinic staff subjects. All such subjects can opt out by 
notifying the study staff that they would no longer like to participate in the study.  Alternatively, subjects can 
decide not to complete surveys. 
 
As we will be surveying a large random sample of pre-diabetic patients, it is possible that some of the survey 
respondents will be pregnant, mentally disabled, economically or educationally disadvantaged. Their exclusion 
from possible participation would prevent us from accurately sampling the population at random. 
 
Such vulnerable patient populations may be excluded from CHW outreach as instructed by primary care 
physicians. (i.e. patient will not receive a letter about services or CHW coaching intervention). 
 
Methods & Procedures 
 
Control Group  
The control group will not have access to CHWs. They will experience usual care in their primary care clinics. 
PCPs in the control group will receive reminders from the study team to order A1C tests for their patients in 
their study, as this pragmatically collected data is necessary to evaluate the study’s main outcome. 
 
Intervention Group: (CHW Health Coaching Integrated into Team) 
CHWs will provide the diabetes prevention intervention, described below, to a randomly selected subset of 
eligible patients per wave in the intervention teams at each hospital. CHWs and the researchers will provide 
regular updates to the primary care providers in the intervention group on these activities. As with PCPs in the 
control group, intervention group providers will receive reminders to order follow-up A1C tests for their 
patients enrolled in the study. 
 
Choice of intervention strategies for each patient: We will have patients across the entire spectrum of 
motivation. Since we target the full population at risk, it will include highly motivated patients, highly resistant 
patients and a large group in between with varying degrees of motivation and activation. Our toolkit driven 
approach, which includes a wide range of strategies aligned with patient activation levels, will be based on the 
same framework used when Dr. Sherman helped revise the VA-DOD smoking cessation guidelines from a 
referral-based approach to a population-based one. In the revised guidelines, the underlying principle guiding 
all treatment decisions – which applies equally well in this proposed study – was all patients should be offered 
treatment in the most intensive setting they are willing to attend. Similarly, all patients with pre-DM will be 
encouraged to use the most intensive DM prevention intervention that they are willing to attend. 
CHW Reach:  We anticipate that up to 40% of pre-DM subjects will participate in hospital-based programs 
(MOVE! at VA and Healthy Lifestyles at BH) and another 10-20% will participate in the community based 
Diabetes Prevention Program (e.g. at local YMCAs). 
 
Community Health Worker (CHW) Coaches - Recruitment and Training 
CHW Recruitment: We will hire and train 6 CHWs (3@VA, 3@BH), from local patient support organizations 
(Veteran Service Organizations and BH volunteer office, as we have done in prior CHW studies) to implement 
the toolkit strategies. CHW employment opportunities announcements will be created. Requirements will 
include: 1) evidence of a leadership role in the patient community through social support or advocacy 
organizations; 2) strong communication and interpersonal skills; and 3) a high school education or GED. CHW 
candidates will not be required to have a background in health. Personal experience with DM will not be 
required. 

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CHW Training: We will train the CHWs in key DM concepts, motivational interviewing, brief action planning, 
and stages of behavior change. CHWs will participate in a 105- hour core competency training developed 
collaboratively developed by Dr. Islam and her team and the Community Health Worker Network of New York. 
CHWs will conduct mock telephone counseling calls with trained standardized patients to enhance skills, gain 
feedback, and develop confidence in these techniques. In addition to these training experiences, CHWs will 
have letter templates, motivational interviewing scripts, and protocols available for patient outreach to 
standardize and guide patient outreach 
 
CHW Intervention 
 
At each wave’s outset, ~ 250 patients at each study site will be randomly selected for outreach and paired with 
one of five CHWs (2 at BH, 2 at VA, 1 at both clinics). Researchers will provide each intervention group PC 
provider their selected list of prediabetic patients. PCPs will be asked to review the list to identify anyone they 
think should be excluded from the intervention. Patients are matched to a CHW according to the patient’s 
language and neighborhood of residence, as the study aims to cluster CHWs’ patients to facilitate CHW travel 
and expertise in local resources. We mail selected patients a letter on behalf of their PCP alerting them of their 
DM risk status, available prevention resources, and introducing them to their assigned CHW. CHWs will then 
call patients to describe the program and seek verbal informed consent to enroll in the study. Patients who 
decline participation will be asked if they are willing to be invited again in subsequent waves of the study. 
CHWs will continue outreach until they have met their caseload for the wave. 
 
We developed a toolkit of strategies for pre-DM coaching outreach to standardize the intervention across 
CHWs and to focus on evidence-based strategies for preventing DM. The toolkit was adapted from the version 
we developed and used in the PROVE study aiming to improve outcomes in HTN and smoking. The toolkit 
interventions reflect standards of care and can be selected and tailored for the broad population of pre-DM 
patients. We will enhance uptake and effectiveness of services by employing CHWs to regularly contact, 
counsel, remind, and follow-up with patients. Outreach strategies will be tailored to patients’ health care needs 
and their stage of activation. CHWs will deliver outreach based on patient preferences and activation level, as 
there is evidence that the fit between an intervention and a patient’s motivations, beliefs and perceptions 
encourages activation, goal setting and ultimately behavior change. During their first contact with patients, 
CHWs will use a standardized, 6-item questionnaire (PAM-6) to quickly assess patients’ activation level. Thus, 
CHWs will offer toolkit strategies that best fit the patients’ level of activation, matching patients with the most 
intensive intervention they are ready to accept. Standardized protocols will also be used to ensure that CHWs 
dedicate sufficient time to engaging patients with lower levels of activation.  
 
Within the 3-year intervention period, each patient’s 12-month CHW intervention will consist of a 6-month 
intensive phase followed by a 6-month maintenance phase, as described below.  
 
 
Phone Call: CHWs will call eligible pre-DM patients and ask to obtain informed consent (in accordance 
with our waiver of documentation of consent) to participate in the study, fully describing the study and 
reviewing all elements of consent. If the patient consents, CHWs will conduct the intake process, which 
includes a survey, the PAM, and a conversation about health goals. CHWs encourage the patient to engage 
in the most intensive strategy that is matched to their activation level and health goals (Health Action 
Plan).  
 
 
Telephone-Based Coaching: CHWs will offer a minimum of 6 monthly, 30-minute phone counseling 
sessions to all patients using motivational interviewing (MINT) and brief action planning (BAP). However, 
patients will be offered more frequent coaching, up to once per week. BAP is a counseling approach 
emphasizing goal setting and MINT principles that can be completed in short telephone counseling 
sessions.  
Telephone coaching will be timed to occur just before or after PC visits to optimize the value of the visit for DM 
prevention. For patients with lower activation scores (Stages 1 and 2), who are less engaged in their own care, 
CHWs will prepare patients for PC visits, empowering them to ask questions, seek information and participate 
in decision-making. This approach can increase PAM scores and help patients to have more effective 

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encounters with their health care teams and to improve health outcomes such as HbA1c among patients with 
chronic illnesses. 
o CHWs will re-call patients, who are not yet ready to engage in behavior change during the initial 
phone call, every 6 months unless they ask to be taken off the re-call list. 
 
Referral to VA’s MOVE! Program or BH’s Healthy Lifestyles Program: These programs offer a series of 
weekly workshops (BH 8 weeks, VA 12 weeks) focused on healthy eating and exercise. Patients “graduate” 
after 6 months but then continue with maintenance activities and ongoing peer support. CHWs will also 
encourage VA patients to participate in Tele-MOVE!, which provides daily interaction with in-home 
messaging technologies, and clinician contact as needed. 
 
Referral to the DM Prevention Program (DPP): The DPP is a 16-session, weekly lifestyle intervention with 
certified DPP coaches, which is effective in preventing DM onset in pre-diabetics. The intensive program is 
then followed by monthly maintenance phone workshops with the DPP coach. This program will be 
provided by the study to all patients who wish to participate. These programs are offered by the NYC YMCA 
and by other community-based organizations.  
 
Metformin: Although not commonly used for DM prevention, metformin has been shown to prevent DM 
among patients with pre-DM, particularly those struggling with making lifestyle changes or with a BMI>30. 
CHWs will suggest that such patients with normal renal function (GFR>50%) discuss this option with their 
PCP and will provide a list of these patients to the team. 
 
Maintenance: After 6 months of intensive coaching, CHWs will transition to making monthly phone check-
ins with patients for another 6 months to reinforce the knowledge and behaviors taught earlier.  
 
Data Collection 
 
Patient Data 
 
As a pragmatic, population-based trial, we aim to understand the impact of our interventions on panels of 
patients in a real clinic environment and therefore will not collect any clinical data directly from patients. 
Instead we will rely on measurements taken during regular clinic visits and recorded in the EMR. We will 
access this clinical and administrative data for VA patients through the VA Informatics and Computing 
Infrastructure (VINCI), a secure, high performance interface with VA’s Corporate Data Warehouse (CDW), and 
for BH patients from the NYC Health and Hospitals CDW. Relying on routinely collected clinical data does 
have its challenges. Patients in our cohort at baseline may not return to the clinic at appropriate intervals, and 
there may be incorrect information within the EMR limiting our ability to assess the impact of the 
interventions on all patients. Learning from our previous work, we will mitigate these challenges by updating 
the study registry regularly, and validating our data during Phase I of the study as we construct the pre-DM 
registries. 
 
We will have the CHWs administer a survey (in person or by phone) of all intervention patients to assess 
patient activation and self-reported behaviors (diet and exercise habits). We will survey each wave’s cohort of 
intervention patients twice: at baseline and at the end of their 1-year intervention phase. Surveys will include 
an MTA MetroCard worth $11 to incentivize response. Non-responders will be mailed up to two reminders. A 
statement will be included with the survey outlining the number of times the survey will be conducted (two), 
the timeframe for the surveys (now, and one year from now).  
 
Implementation Research 
 
Survey of providers: We will conduct a survey of primary care providers to assess the impact of the 
intervention on staff with measures described below to understand implementation issues. The survey will be 
conducted at baseline and following the 3-year intervention, using a mixed approach, including hard copies, in 
person or in office mailboxes, and email. In our previous study, we had a 65% response rate from providers and 
nurses, and we anticipate a similar response rate in the proposed study. A statement will be included with the 
survey outlining the number of times the survey will be conducted (2) and the timeframe for the surveys.  
 

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Semi-structured interviews: To further understand the clinic staff’s lived experience of the CHW intervention, 
we will conduct brief, semi-structured interviews of the providers at baseline and semi-annually, for a total of 6 
times (baseline, and after years 1, 1.5, 2, 2.5, and 3) with a subset of participating PCPs identified as key 
informants based on their experience and institutional knowledge. To understand any changes in how teams 
collectively integrate CHWs into their practices, we will also conduct brief, semi-structured interviews with 
primary care team members other than providers at the same intervals. Through these surveys and interviews, 
we will assess key aspects of the implementation of the CHW intervention as experienced and perceived by 
clinic staff. To additionally understand factors that impede or facilitate the implementation of the intervention, 
we will conduct semi-structured interviews annually (after years 1, 2, and 3) with practice administrators at 
each health care organization; key informants knowledgeable about population health and health policy at city 
level as relevant to DM prevention; and staff at the nutrition and exercise programs, whose involvement in the 
program can enable implementation success. Interviews will continue until emerging themes are saturated, 
anticipating up to 25 subjects at each site (approximately 20 involved in primary care delivery, 2 in managerial 
or administrative roles, and up to 3 staff at nutrition and exercise programs) and up to 5 informants outside the 
two sites who can speak to macro-level factors. These interviews will be audio-recorded and transcribed for 
analysis. 
 
Process indicators: In this pragmatic trial, we will systematically track and examine the process of 
implementation and the contextual factors that influence implementation of the CHW intervention. To do so, 
we will draw on available study data in REDCap, the secure program used to record CHW-patient encounters 
for the study. At the end of the study we expect to have data on approximately 1,000 enrolled intervention 
patients, with each patient followed for one year, with CHW-patient contacts limited to the intensity that 
patients are willing to attend. From REDCap, we will collect data semi-annually on four indicators of 
implementation fidelity, namely (1) the content of CHW activities. (2) the coverage (number of patients 
reached), (3) duration (how long each patient is followed up), and (4) frequency (how often patients are 
contacted) of CHW-patient contacts. Content of CHW activities will be assessed through assessing CHW case 
notes on a random selection of 15 enrolled patients and interviews with CHWs. Case notes will be assessed to 
examine how CHWs handle patients’ behavioral barriers and social needs, including the referrals they make to 
various services (e.g., mental health, social work, exercise programs). To understand barriers that CHWs 
confront in the course of implementation, we will conduct semi-structured interviews with the CHWs and 
identify major themes (questions, concerns) related to behavioral counseling and referrals that may be 
discussed during the study team’s meetings and case conferences. Similar to the semi-structured interviews 
with providers and other primary care team members, interviews will be conducted at end of year 1, 1.5, 2, 2.5, 
and 3. Findings resulting from analysis of patient case notes and other CHW materials will be reported 
anonymously.  
 
Influence of neighborhood factors: To examine the influence of contextual factors on implementation and 
intervention effectiveness, we will conduct population-level analysis of variation in implementation and health 
outcomes across NYC neighborhoods. We will conduct this analysis with patient data available at the start of 
the study and data on enrolled patients post-intervention. To obtain information on neighborhood-level 
factors, we will use publically available data on social and environmental aspects of NYC neighborhoods in the 
FACETS database (data accessible at https://github.com/mcantor2/FACETS). We will map patient addresses 
to census tracts, aggregate census tracts to neighborhoods, and statistically examine the association of 
neighborhood-level contextual factors on prediabetes prevalence across NYC. Patients’ location information 
will be used at an aggregate neighborhood level, and it will not be possible to identify their precise location in 
the city. Individual patients and their PHI will not be identifiable. 
 
 
Data Analysis and Data Monitoring 
 
The analytic methods described below are designed to test the primary hypotheses that prediabetic patients 
cared for by PCMH teams randomly allocated to the CHW Coaching group, will have lower annual hazard rate 
of incident cases of DM overtime more weight loss, and higher PAM scores by the end of the intervention 

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period than similar patients cared for by PCMH teams allocated to the Control group, adjusting for baseline 
rates. The unit of analysis is patients, aggregated to the provider level. 
 
Analysis: Patient Clinical Outcomes and Health Behaviors 
 
Descriptive analysis techniques (measures of central tendency and variability, frequencies and proportions) 
will be used to present baseline characteristics of participants (patients and their PC staff) in the control and 
intervention arms. Chi-square tests and t-tests will be used to check if these baseline characteristics are 
balanced between the two study groups. For continuous outcomes, normal assumptions will be checked, and 
non-parametric alternatives and transformations will be considered as needed. 
 
To assess the overall effectiveness of the CHW intervention we will compare cumulative DM incidence rates 
and time to DM incidence (in addition to other outcomes: weight loss, obesity rate, and health care utilization) 
between the two study groups, using intention-to-treat and per protocol analyses. Time to DM incidence at 12-
month follow-up of the intervention and control arms, aggregated across the 4 study waves, will be compared 
using Cox proportional hazard regression models. Chi-square analyses will be conducted to compare outcomes 
between the two groups for categorical variables (e.g. obesity rate, PAM stage) and t-tests will be conducted for 
continuous outcomes (e.g. weight change, PAM score). We will then conduct (generalized) linear mixed-effects 
modeling, which will (1) take into account the intra-cluster correlation coefficient (ICC) of patients within 
providers and teams, (2) analyze repeated measures at several time-points (baseline, midpoint, and post-
intervention) simultaneously, (3) include team or patient level baseline covariates easily, if they are found to be 
unbalanced between two arms, and (4) deal with attrition problems and other missing data automatically. For 
categorical outcomes, such analyses will be implemented using SAS Proc GLIMMIX, while using SAS Proc 
MIXED for continuous outcomes. 
 
We will use multilevel survival analysis to determine the effect of the intervention on time to DM, as patients 
are enrolled in waves and the time to DM incidence may be censored by the end of study. Specifically, we will 
fit Cox proportional hazard regression models with mixed effects to examine the hazard ratio between two 
groups, adjusting for important covariates and taking into account the correlation among patients within 
teams. 
 
We will use a similar generalized linear mixed-effects modeling for the secondary outcomes, to explore the 
relationship of the intervention’s effectiveness to specific patient and provider or team characteristics. We will 
investigate interactions between the intervention and the patients’ level of activation, co-morbidities (HTN, 
depression, and smoking), and health care utilization. We will also test the correlation (Pearson’s r) of provider 
self-efficacy and team collective-efficacy on patient outcomes. We will conduct secondary analyses to better 
understand the impacts of the individual components of this complex set of interventions. While designed to 
test the effectiveness of an overall strategy, we will seek to determine which of the intervention elements and 
dose of intervention (e.g. number of phone contacts, number of mailings, successful referral to MOVE!, 
Healthy Lifestyles, DPP or other programs) were most strongly associated with any improved outcomes. We 
will also conduct subgroup analyses to see which subgroups may benefit more from the intervention than the 
others. Such group analyses are data dredging; they should be considered as exploratory analyses and any 
resulting findings should be confirmed by independent studies. 
 
Because control patients are not surveyed, follow-up survey data for a given wave will serve will serve as the 
control group for the following wave’s baseline survey data. For example, wave 1 follow-up data will be 
compared against wave 2 baseline data. The data collected in the survey are secondary outcomes. 
 
Attrition/missing data: Although the retention of patients with specific provider panels is relatively stable at 
the VA and BH, there are a number of reasons for changes including moving, entering a nursing home or rehab 
facility, not being seen in PC for >2 years, or requiring specialty-based PC. Patients seldom switch among 
teams or providers within teams, limiting the potential for contamination between study groups. In our VA 
study of panel management (PROVE), only 7% of 9,841 hypertensive patients switched teams over 12 months 
of follow-up. In the event that a provider changes teams and moves from one study arm to the other, patients of 
theirs already enrolled in the study will remain in the study arm in which they were enrolled. In waves after a 

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provider has switched teams, newly enrolled patients attributed to this provider will enter the study in their 
provider’s current study arm. For the intervention group, CHWs will contact patients when they are due for PC 
visits to ensure that they complete regular screenings as one of the toolkit strategies. Loss to follow-up of 
patients assigned to control teams is a concern, however we will address it through data reports provided to the 
control teams, which will include patients due for an HbA1c screening. 
 
To limit bias due to contamination and missing values, we will assess the baseline characteristics of patients 
who switch teams or are removed from the panel or have incomplete repeated outcomes, and compare them 
with that of the other participants. The (generalized) linear mixed-effect models discussed earlier can deal with 
attribution problem and other missing data automatically, under the missing-at-random assumption. This 
model assumes that the missing information only depends on the observed information, which allows us to 
utilize all the observed information. To better understand the nature of our missing data and its mechanism; 
we will summarize the outcome variables by discontinuation status/reason in each arm. If the trajectories of 
the primary outcome variables from those with incomplete data are similar to those with complete information, 
the data may be missing at random; otherwise, it may be missing not at random. We will then conduct 
sensitivity analysis to assess the impact of missing not at random data on our analysis. The sensitivity analysis 
will test whether our primary statistical analysis remains credible if we investigate cases where those patients 
with incomplete data have outcomes that are unfavorable to the intervention arm of the study (eg. those with 
incomplete outcome data in the control arm are less likely to develop DM, lose weight or have improved 
glycemic control or that those with incomplete outcome data in the intervention group are less likely to have 
lost weight or improved glycemic control but more likely to have developed DM). The sensitivity analysis will 
be conducted via multiple imputation using sequential modeling, applying a SAS macro. 
 
 
Analysis: Intervention Implementation 
 
Staff survey data will be used to assess the self-efficacy and collective-efficacy as a team in preventing 
DM and in working with a CHW coach. We will compare baseline and post-intervention scores on each of the 
measures. To test the hypothesis that staff assigned to the intervention teams who work closely with a CHW 
will improve their self and collective efficacy of DM prevention and CHW coaching, we will compare post-
intervention scores for these measures across the study arms using linear regression and controlling for 
baseline scores and adjusting for staff roles, length of time in their role and site. Survey data will also be used to 
assess PCPs’ readiness to work with CHWs for DM prevention. Baseline and post-intervention scores will be 
compared using Wilcoxon signed-rank tests.  
 
All interviews transcripts (from PCMH and other staff, practice administrators, CHWs, and key informants) 
and observations of study team meetings and case conferences will be analyzed for common themes by two 
independent researchers for qualitative analysis. First, two researchers will read the transcripts to identify key 
domains. Second, the researchers will independently code two of each set of transcripts. They will then meet to 
develop initial codebooks with code names and meanings. Third, each coder will apply the codebook to the 
remaining transcripts. Fourth, coders will meet to compare codes and identify patterns and common themes 
throughout the transcripts. Baseline interviews will be used to guide toolkit refinement and to explore 
anticipated facilitators and barriers to incorporating CHWs into the PCMH workflow. Mid- and post-
intervention interview data will help us to determine key barriers, facilitators and lessons learned from staff, 
CHWs, and key informants regarding the implementation of CHWs in PC practice. 
 
To assess implementation fidelity, baseline and 6-monthly scores on the coverage, duration, and frequency of 
CHW-patient contact for BH and VA patients will be compared using ANCOVA. Content of delivery will also be 
assessed qualitatively based on a sample of CHW-patient contacts. Implementation fidelity will be compared 
across BH and the VA to examine if differences in organizational setting shape the implementation process.  
 
Data from the FACETS neighborhood database of social determinants will be conjoined with study data to 
describe whether contextual factors pertaining to NYC neighborhoods are associated with prediabetes 
prevalence across neighborhoods. We will use a multilevel statistical model, with patients nested within 
neighborhoods, to conduct this analysis.  

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Process Evaluation: To ensure that the intervention was delivered completely and standardized across the sites, 
CHWs and clinical teams, there will be continuous monitoring of process outcomes and fidelity to the protocol 
during the CHW intervention. We will maintain standardized protocols for each toolkit strategy and 
documentation of peer coaching. The CHW Coordinator will conduct quarterly assessments of the 
interventions, proportion of patients reached and engaged by site and CHW, fidelity to counseling protocols, 
and the preferred toolkit and contact strategies.  
 
Statistical Power and Sample Size 
The primary study outcome for power calculations is the annual hazard rate of incident DM.  
 
To determine sample size, we begin with the total accessible population of about 46,000 primary care patients 
served at the two sites (BH and VA). Of these we exclude patients with diagnosed DM (25% at VA and 15% at 
BH) and those over 75 years of age (who are ineligible for this intervention). Of these eligible subjects, we 
estimated that about 70% will have had the HbA1c test in the last 2 years and that about 40% of these will have 
had a test result in the prediabetes range. 
 
While the above inclusion and exclusion criteria return about 9,300 eligible patients, 8,200 at BH and 1,100 at 
the VA, CHW caseload limitations preclude us from reaching all these eligible patients during the 3-year 
intervention. Assuming a caseload of 72 patients per fulltime CHW per wave (with 3.5 fulltime equivalent 
CHWs across both sites and 4 waves), the intervention is projected to enroll a minimum of 1,008 subjects into 
the intervention group. An equivalent number of subjects will be randomly selected from the Control teams for 
a total of at least 2,016 study subjects overall. The intervention and control subjects will be split across the two 
study sites. After assuming that we will not be able to reach about 20% (due to missing or incorrect contact 
information) unreachable rate, and that about 60% will consent to enroll in the intervention, we will randomly 
select about double the 1,008 subjects (about 2,100) for potential enrollment into the intervention in order to 
enroll the minimum of 1008 intervention subjects needed to have adequate statistical power.  
 
Power: In the pre-DM population we estimate the 3-year DM incidence to be 15% (based on preliminary 
analysis of a similar VA cohort from 2010-2012). Based on our analyses, with 1,008 patients allocated to each 
of the intervention and control groups, we anticipate having 80% power (alpha = 0.05) to detect a difference in 
time-to-event (DM incidence) between the intervention and control group. 
 
To assess measures of implementation fidelity, specifically coverage, duration, and frequency of CHW-patient 
contact, we will base calculations on all patients enrolled. Since we will use all available study data from the 
electronic medical records, power and sample size considerations do not apply. We will assess content of CHW-
patient contact using qualitative methods, hence power and sample size considerations do not apply. 
 
To examine the variation in prediabetes prevalence across NYC neighborhoods, we will use available data from 
BH at the start of the study, in approximately 19,000 patients. These patients meet the study’s previously 
stated eligibility criteria, with two modifications: patients must have (1) any HbA1c result in the past 5 years 
and (2) an address available in the EHR. Data on all enrolled BH patients at the end of the study, an estimated 
1,000 patients, will also be used. Since we will use all available study data, power and sample size 
considerations do not apply. 
 
 
Data Storage and Confidentiality 
Many steps will be taken to ensure the security and integrity of all study data. Information obtained for this 
study will be stored on password-protected research drives. Data obtained from surveys, the BH and VA CDW, 
and the local EMR will be coded and stored separately from their code key files on a secured, password-
protected, HIPAA compliant network drive. Only the Research Director, Project Manager and Evaluator will 
have access to the subjects’ codes. Once coded, the de-identified data will be securely transferred to a 
password-protected, shared research drive for analysis. Hard copies of surveys returned from patients will be 
locked in a secure cabinet or drawer located in the team’s research space. A waiver of authorization for both 
recruitment/identification purposes and for study procedures has been sought. 

IRB Protocol 2019-03-21| email irb-info@nyumc.org | phone 212.263.4110 | page 10 of 12 
 
Audio recordings of the in-person interviews with an anticipated 60 subjects will be taped using approved 
recording devices, which will be stored in a locked cabinet or drawer. Interview recordings will be transcribed 
without identifiers. We will present informed consent forms and audio/visual consent forms (VA form 3203 
“Consent for Use of Picture and/or Audio” and NYU Research Subject Audio/Video/Photo Use Consent Form) 
to all staff participants involved in qualitative research interviews who verbally consent to participate in the 
protocol.  
 
Risk/Benefit Assessment 
 
Risk 
The main risk to patients, primary care and other staff, practice administrators, CHWs, and key informants, 
though unlikely, is a loss of confidentiality. 
 
Protection Against Risks 
Provider /staff participants will be asked to participate in the different parts of the study (CHW intervention, 
surveys) but not required to do so. Patient survey respondents will be offered a modest incentive 
($11 MetroCard) to compensate them for their time. Questionnaires and interviews will be delivered by a 
neutral party not in the employee’s supervisory chain. Participation is completely voluntary and participants 
may drop out of the study at any time. 
 
For the neighborhood effects analysis, patients’ location information will be maintained at the level of the 
neighborhood, which is an aggregate of census tracts. NYC has over 2,100 census tracts. The NYC Department 
of City Planning constructs approximately 210 Neighborhood Tabulation Areas (NTA) out of the 2,100+ census 
tracts by aggregating whole census tracts. Although individual patient data is initially mapped to census tract 
level, it is used and analyzed only at the NTA level. Each NTA includes an average of about 50,000 residents. 
Patients’ precise geographic location therefore will not be identifiable. Seeking consent from patients for their 
data to be used for this study would increase the likelihood of loss of confidentiality.  
 
Potential Benefits to the Subjects 
Staff subjects may improve their clinical practice if they are randomized to the intervention, which provides a 
CHW to the PC provider that assists in accessing and interpreting the large VA and Bellevue electronic datasets 
in attempt to enhance patient care. Patients may receive improved care as a result of their providers receiving 
the information in an organized, usable fashion and having support to encourage patients to enroll in and 
complete programs that reduce the risk of developing type 2 DM. Potential risks are minimal and primarily 
include loss of confidentiality, while the potential benefit to individual and scientific knowledge is sizeable. 
CHWs will not be making any management decisions for patients’ care but rather will be acting under the 
direction of each patient’s primary care physician. CHWs who participate in interviews will gain opportunities 
to reflect upon the challenges and successes of their work and subsequently incorporate this understanding 
into their work, thus providing improved counseling and support to patients. 
 
Investigator’s Qualifications & Experience 
 
See attached biosketches for qualifications and experience. 
 
Subject Identification, Recruitment and Consent/Assent 
 
Method of Subject Identification and Recruitment, and Consent 
All primary care staff will be given information about the proposed research during regular staff meetings, 
email announcements and a study flyer and then asked to participate. Staff providing verbal consent to 
participate will be randomized (as part of their PACT team) to either work with a CHW or serve as controls. 
Staff who opt-out will not be randomized, although might still work on a team that is included in the study. For 
example, if one primary care provider in a team declines participation, the other providers and team members 
consent, the team will be randomized to a study arm. If that team is randomized to an intervention arm, the 

IRB Protocol 2019-03-21| email irb-info@nyumc.org | phone 212.263.4110 | page 11 of 12 
CHW would only work with the patients of the consenting providers. We anticipate that we will be able to 
obtain sufficient numbers of staff consenting to participate, as in our previous panel management study only 
one PCP out of fifty-one declined, and a majority of staff reported that the interventions and CHW support 
were helpful. Lastly, as CHWs will be extending services and interventions that are a part of regular, evidence-
based practice on behalf of patients’ primary care physician, patients will not individually consent to receiving 
phone calls, mailings, or any other contact with the CHW. For surveys, which are research procedures specific 
to this study, consenting elements will be presented at the top of the survey . Primary care teams will pre-
approve all lists of patients receiving interventions as well as approving the content of the CHW’s intervention. 
Patients will have the right to opt out of receiving outreach at any time. All mail materials will include 
instructions on how to stop receiving mail from the CHW. 
 
A waiver of authorization for both recruitment/identification purposes and for study procedures has been 
sought. We use the electronic medical record to generate a list of eligible participants, in order to approach 
them to screen for eligibility. Without the requested Waiver, screening could not be practically carried out and 
would adversely affect the scientific rigor of the study.  
 
A waiver of consent has been requested. Informed consent is given when a provider chooses to participate in 
the intervention. He or she can opt out of the study at any point. With regard to surveys, completion of the 
survey will serve as implied consent. The survey cover sheet includes all elements of consent. Informed consent 
is implied by patients completing and returning a mail-based survey. Similar to the staff survey, all patient 
surveys will state that the survey is voluntary, all data will be reported in the aggregate, and completion of the 
survey serves as consent for participation. The survey will also specify that completion of the survey will not 
impact their health care in any way and that their individual responses will not be shared with members of 
their health care team.  
 
Further, patients will be considered to have given informed consent by choosing to continue to interact with 
CHWs. Patients can request to not be contacted by a team’s CHW at any point. This will be clearly stated on all 
materials given to staff and patients. Interventions will consist of educating patients of existing services at the 
institution or outside of the institution that they can access to improve their health, ensuring coordination and 
follow-up on referrals already made by their health care team. Patients interested in attending a institution-
provided service (such as MOVE, smoking cessation classes, or Telehealth) will be referred as a part of usual 
care from their team. Programs such as YMCA DPP are available to anyone that meets pre-diabetes criteria, not 
just our subjects. Anyone is able to join these programs without the referral of a physician. The study team will 
only offer existing evidence-based services already available to pre-diabetics. Patients interested in attending 
the community based DPP will be provided contact information or a warm transfer by telephone, but will need 
to register themselves and consent to the outside program. PHI will not be sent to either organization by the 
study team. Patients will be making an informed decision to join such groups and will be explicitly explained 
this via phone or letter. This same implied consent applies to patients who register for VA’s Telehealth or 
MOVE services and BH’s Healthy Lifestyle services.   
 
CHWs will be interviewed in groups and/or individually, as they prefer. Their participation in interviews is 
voluntary. Identifying information on CHWs or on our study team members will not be collected or recorded in 
these interviews and observations. 
 
Costs to the Subject 
Subjects or their health insurance may be billed for the costs of medical care during this study if these expenses 
would have happened even if they were not in the study, or if your insurance agrees in advance to pay .   
 
Payment for Participation 
Patient survey respondents will be offered a modest incentive ($11 MetroCard) to compensate them for their 
time. 
 
Documentation of Consent 

IRB Protocol 2019-03-21| email irb-info@nyumc.org | phone 212.263.4110 | page 12 of 12 
We will present informed consent forms and audio/visual consent forms (VA form 3203 “Consent for Use of 
Picture and/or Audio” and NYU Research Subject Audio/Video/Photo Use Consent Form) to all staff 
participants involved in qualitative research interviews who verbally consent to participate in the protocol. We 
will not be obtaining informed consent from those who will not be audiotaped. The consent will be obtained 
immediately prior to starting the interview.