Enhanced Quality in Primary Care for Elders With Diabetes and Dementia
Phase: NA
Conditions: Diabetes, Dementia, Alzheimer Disease
Sponsor: NYU Langone Health

 
 
Official Title: 
Enhanced Quality in Primary Care for Elders With Diabetes and 
Dementia   
NCT Number: 
NCT03723707 
Study Number: 
18-01166 
Document Type:  
Study Protocol and Statistical Analysis Plan 
Date of the 
Document: 
• 
January 20, 2021 
 
 

 
 
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Enhanced Quality in Primary Care for Elders with Diabetes and Dementia 
(EQUIPED-ADRD)  
– R33 Trial 
 
 
 
Principal Investigator 
(mPI): 
 
 
Caroline S. Blaum, MD, MS 
Diane and Arthur Belfer Professor of Geriatrics 
Director Division of Geriatric Medicine and Palliative Care  
NYU School of Medicine 
550 First Ave, BCD612 New York, NY, 10016  
646-501-2323 
Caroline.Blaum@nyulangone.org 
 
 
Co-Investigator 
(mPI):  
 
Joshua Chodosh, MD, MSHS, FACP 
Michael L. Freedman Professor of Geriatric Research in Medicine 
Director, Freedman Research Program on Aging and Cognition 
Co-Director, NYU Aging Incubator 
Professor of Medicine and Population Health 
Division of Geriatric Medicine and Palliative Care 
NYU School of Medicine 
550 1st Ave BCD 616, New York, NY 10016 
212-263-6768 
Joshua.Chodosh@nyulangone.org 
 
 
Additional Investigators: 
 
 
Sondra Zabar, MD 
Simon Jones, PhD 
Leora Horwitz, MD 
Ira Goldberg, MD 
Victoria Vaughan Dickson, PhD 
Andrea Troxel, Sc.D. 
 
 
NYULH Study Number: 
 
s18-01166 
 
Funding Sponsor:  
 
National Institute on Aging (NIA) 
7201 Wisconsin Avenue  
Bethesda MD 20892-9205 
 
 
ClinicalTrials.gov Number 
 
 
 
 
 
 
 

 
 
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Statement of Compliance 
This study will be conducted in accordance with the Code of Federal Regulations on the Protection 
of Human Subjects (45 CFR Part 46), any other applicable US government research regulations, 
and institutional research policies and procedures. The Principal Investigator will assure that no 
deviation from, or changes to the protocol will take place without prior agreement from the sponsor 
and documented approval from the Institutional Review Board (IRB), except where necessary to 
eliminate an immediate hazard(s) to the trial participants. All personnel involved in the conduct of 
this study have completed Human Subjects Protection Training. 
 
 

 
 
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List of Abbreviations 
AE 
Adverse Event/Adverse Experience 
DSMB 
Data and Safety Monitoring Board 
HIPAA 
Health Insurance Portability and Accountability Act 
ICF 
Informed Consent Form 
IRB 
Institutional Review Board 
MOP 
Manual of Procedures 
N 
Number (typically refers to participants) 
NIH 
National Institutes of Health 
PI 
Principal Investigator 
SAE 
Serious Adverse Event/Serious Adverse Experience 
SOP 
Standard Operating Procedure 
US 
United States 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
 
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1. Purpose of Study and Background 
 
1.1 Purpose 
 
The purpose of EQUIPED is to test and evaluate a care quality improvement intervention featuring 
use of consensus decisional guidance for the medical management of diabetes (DM) patients 
with Alzheimer’s and other forms of dementia (ADRD) in primary care at NYU Langone Health. 
This quality improvement program will include provider (PCP) workflow enhancements supported 
by a panel manager (PM) for workflow support, electronic health record (EHR) decision support 
and feedback, and PCP collaborative learning.  
 
It will test hypotheses about whether care based on explicit standards for DM medical 
management for people with ADRD will: H1) Improve patient symptoms and quality of life while 
maintaining expected clinical outcomes; H2) decrease patient and caregiver management burden 
and improve care quality based on patient/caregiver preferences;H3) (secondary) decrease 
specialty, ED and hospital utilization.  
 
In order to test and evaluate this program, we will conduct a pragmatic randomized controlled trial 
(RCT) and evaluate it using mixed methods (surveys and interviews) in 20 NYU Langone Health 
clinics with the enrollment goal of 500 patients with diagnosed DM and ADRD in the intervention 
(INT) and control (CON) group (1,000 total). 
 
If EQUIPED demonstrates that patients and family caregivers who receive this quality 
improvement program achieve established goals for diabetic care in addition to fewer dementia-
related symptoms, less caregiver burden and stress, and fewer DM-related adverse events, 
potentially avoidable and costly utilization may also decrease. This best practice approach could 
then be widely disseminated to other clinical practices. 
 
1.2 Specific Aims 
 
Specific Aims of the R33 Enhanced Quality In Primary Care for Elders with Diabetes-ADRD 
(EQUIPED-ADRD) are:  
1) Implement and evaluate a pragmatic trial in a large healthcare system using cluster 
randomization, and the practice change framework, that will: manage people with co-
occurring DM and ADRD according to the guidelines developed to test our hypotheses 
and identify additional patients with cognitive impairment and inappropriate DM 
management.  
2) Test whether EQUIPED-ADRD will increase the proportion of intervention patients who 
are in desirable glycemic and blood pressure ranges compared to control patients. 
3) Test whether the EQUIPED-ADRD intervention will improve dyad perception of care 
quality and reduce treatment burden.  
4) Test whether dementia symptoms will deteriorate less in intervention subjects compared 
to controls.  
 

 
 
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Exploratory Aim. Test whether intervention subjects will use fewer health care services than 
controls and will have less cognitive decline associated with desired changes in glycemic and 
blood pressure control. 
 
1.3 Background 
Over 11 million Americans ≥65 years have Diabetes (DM)1, a prototypic chronic disease requiring 
self- management.2 While the linear increase in prevalence of Alzheimer’s disease and related 
dementia (ADRD) associated with increasing age is well known, diabetic patients of similar ages 
may have as much as a two-fold risk of developing cognitive impairment and ADRD.3–6 Emerging 
evidence suggests pathophysiological links between DM and both AD and microvascular 
dementia.7,8 DM management is complex and includes management of co-existing risks, 
complications and related diseases (hypertension, cardiovascular and microvascular disease). 
Cognitive impairment likely challenges diabetic self-management placing responsibility and 
additional stress on family caregivers. Management complexity requires logistical skills, complex 
decision- making and understanding of risks and disease trajectories so caregivers must be 
deeply involved in managing DM in dementia patients. Some patients with DM and ADRD are not 
diagnosed and/or recognized as cognitively impaired9 and their caregivers may be insufficiently 
involved, unrecognized or unsupported, further challenging DM management.  
 
Over and under treatment of DM and its medical complications in some ADRD patients,10 
increased hypoglycemia risk,6,11 and caregiver burden are well documented.4,12 Adding to the 
complexity of the co-occurrence of DM and ADRD is the heterogeneity of patients in age, ADRD 
and DM severity, race/ethnicity, health status, and life expectancy.13 This heterogeneity argues 
strongly for a pragmatic trial14 within a healthcare system representing patient and clinical system 
diversity. ACCORD,15 ADVANCE,16 and related studies provide substantial trial and observational 
evidence about DM management in elders and DM’s relationship to dementia, but clinical 
uncertainty exists. This suggests that health priorities and preferences of DM-ADRD patients and 
caregivers should help direct DM management.  But the push towards value-based payment and 
the focus by healthcare systems and payers on diabetes quality metrics that may not apply can 
lead to particular confusion about management of DM in ADRD patients. 
 
The relationship between diabetes and dementia: Underlying the co-occurrence of DM and 
ADRD is a 1.5-2.5 times increased risk DM patients have for ADRD.9,35,36 Pathophysiological links 
underlie this increased risk and substantial research is directed to find new treatment targets for 
both conditions.7 A 2012 meta- analysis found that DM increased risk for AD, vascular and other 
dementia, and mild cognitive impairment.37 Vascular dementia may mediate the relationship 
between DM and AD, making AD clinically apparent.8 To capture clinically detectable risks, a 
recent international collaboration developed an empirically validated risk score to predict 10-year 
dementia risk in DM with reasonable predictive validity.38 Regardless of causal links, the co-
occurrence of DM and ADRD presents a significant challenge for clinicians, patients and CGs 
because these co-occurring diseases increase clinical uncertainty, complicate management of 
both conditions, and too often lead to care burden and poor outcomes for patients and CGs, and 
confusion and frustration for providers. 
 
Cognitive impairment may be undetected in DM: Cognitive impairment and dementia are 
frequently undetected in DM, leading to poor quality of care for both conditions.21,35 DM patients 
with unrecognized cognitive impairment may have trouble with self-management, which could 

 
 
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lead to under- or over- treatment of hyperglycemia, hypertension9 and poor adherence to diet and 
exercise.3 The American Diabetes Association (ADA) and the American Geriatrics Association 
(AGS) Guidelines advocate screening for ADRD in DM.39–41 A European intervention to screen 
DM patients for cognitive impairment is underway42 and the VA has developed an administrative 
screen for veterans at risk for hypoglycemia.10 Multiple screening tools exist for detecting ADRD.43 
One of the most studied and practical is the Mini-CogTM,44 a brief dementia-screening test created 
and validated by Dr. Soo Borson (a member of our study team). This has been cited in numerous 
studies comparing the feasibility and accuracy of several tests.45 
 
Patients with DM-ADRD experience DM over-treatment and under-treatment: Diabetes care 
includes management of hyperglycemia, blood pressure, hyperlipidemia, and monitoring for 
microvascular and macro- vascular complications, using pharmacologic and non-pharmacologic 
(diet and exercise) management.39,46  DM-ADRD patients experience worse DM monitoring,21 poor 
non-pharmacologic treatment,3 and have worse metabolic outcomes than patients with DM 
alone.28,35 Under-treatment can potentially lead to symptomatic hyperglycemia such as polyuria, 
increased infections, weight loss and fatigue. Over-treatment can potentially lead to 
hypoglycemia, acute confusion, and health care utilization. VA research has shown potential over- 
treatment of hyperglycemia in veterans with ADRD and DM, ranging from over 50-63% of high 
risk veterans having HbA1c<7%.10 Hypertension in DM can be over- or under-treated; ACCORD 
and ADVANCE provide evidence for moderate management of hypertension in DM.15,16,47 Under-
treatment of hypertension in DM has been well studied but there is VA evidence for hypertension 
over-treatment in routine clinical practice.48 Cholesterol management by statins in older DM 
patients was not specifically readdressed in ACCORD or ADVANCE. In Enhanced Quality In 
Primary Care for Elders with Diabetes-ADRD (EQUIPED-ADRD) we aim to target glycemic and 
blood pressure (BP) management based on ACCORD and ADVANCE evidence to decrease both 
over and under treatment. During the R21 phase of this study we developed consensus decisional 
guidance related to glycemia (measured as “HbA1c”) and BP targets that also address monitoring 
for risks of complications, any new cholesterol recommendations, and non-pharmacological DM 
management with a goal of identifying safe, high quality management guidelines for DM-ADRD 
patients to be implemented in the R33 phase. These guidelines address 1) screening for cognitive 
impairment in older DM patients with out-of-desired range of HbA1c or BP but no ADRD 
diagnosis, 2) CG support, and 3) treatment based on CG preferences. 
 
Hyperglycemia, hypoglycemia and cognition – a complex story: The relationship between 
cognition and hyperglycemia or hypoglycemia is complex. People with hyperglycemia perform 
more poorly on tests of cognition,49,50 but ACCORD provided no evidence that intensive glycemic 
control improves cognition or prevents cognitive decline.51,52 Although intensive glucose control in 
ACCORD was associated with more hypoglycemia,53 lower baseline cognition was also 
associated with increased risk of severe hypoglycemic episodes in ACCORD-MIND25. Evidence 
that hypoglycemic episodes increase the risk of future cognitive worsening is less clear. In 
ACCORD-MIND/MRI, more hypoglycemic episodes occurred with intensive treatment but there 
was no difference in rates of cognitive decline between the groups25 or MRI differences related to 
hypoglycemic episodes.52 Observational studies suggest hypoglycemia may increase risk of 
dementia23,24,54,55 but risks may be biased because hypoglycemia may occur in people with 
unrecognized ADRD which is subsequently recognized.26 Although dementia severity is related 
to hypoglycemia, the role of glycemic control in causing or preventing hypoglycemia is less clear; 
thus, hypoglycemia is not an outcome in our study. However, utilization is a study outcome, so 

 
 
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we will observe and analyze hypoglycemia leading to clinic, ED or hospital use, adding to 
evidence about hypoglycemia’s relationship to DM management in ADRD. 
 
Family and friends provide 75% of daily care needs for patients with ADRD living in the 
community:56 We refer to these individuals as CGs. When included with the person with dementia, 
we refer to these as dyads. CGs of patients with DM and CGs of patients with dementia report 
substantial CG burden.27,57 A recent European study of CGs of DM-ADRD patients demonstrated 
increased supervision time.12 CG burden is known to be linked to patients’ behavioral problems, 
poor cognition, and increased dependency; a recent study demonstrates increased burden 
related to medications and medical care supervision.58 CG stress is associated with poor 
outcomes for dementia CGs themselves, such as depressive symptoms often meeting diagnostic 
criteria for major depressive disorder59 and ED visits or hospitalizations.60 Decreasing CG stress 
improves outcomes for patients with AD61,62;CG burden and stress are important outcomes for 
our study. 
 
ADRD’s increase healthcare utilization and costs for DM patients: A comprehensive analysis of 
1999 Medicare claims data showed that all types of utilization and costs (hospitals, hospital 
outpatient, physicians, nursing homes and home health), were increased for dementia patients.30 
For Medicare beneficiaries with a dementia diagnosis, DM was present in 21% versus 16% of 
non-dementia patients. The same analysis showed significantly different crude rates of 
hospitalization/1000 beneficiaries (OR 3.36 [2.44-4.44]) for DM- ADRD vs. DM without ADRD. 
Data from 2007-08, focusing on potentially avoidable hospitalizations for ADRD patients, showed 
that Medicare costs and utilization are higher and the main driver of increased costs is increased 
hospitalizations.31 ADRD patient admissions for short-term and long-term DM complications were 
higher compared to non-ADRD DM patients (OR: 1.43 [1.31-1.57] and 1.08 [1.02-1.14], 
respectively). 
 
DM management in ADRD patients – summary of current evidence and gaps: Consensus on best 
management of DM in ADRD patients is lacking. High quality DM care in people ≥75 in general 
is undefined,13 although there is consensus that DM management must be individualized in such 
patients.39,40 Life expectancy for DM-ADRD is highly heterogeneous and substantially 
complicates DM management decisions. These issues add to clinical uncertainty and suggest 
that dyad care preferences and outcomes that matter to them, like decreased symptoms, 
decreased care burden, and decreased healthcare use, are important to consider in DM-ADRD 
guidelines.63  Despite these challenges, research discussed above (mostly observational, some 
from trials) concerning DM-ADRD informs management approaches: moderate control of 
hyperglycemia and BP is appropriate, DM quality improvement is safe, feasible and may improve 
survival in older DM patients,64 hypoglycemia is a major risk, “self”-management must be handled 
by CGs, and CGs need support. However, available evidence has not led to consensus decisional 
management guidance for patients/CGs and providers (international efforts are beginning),35,42 or 
to practical, clinical quality improvement programs to address this. New value-based 
management makes evidence-based treatment guidance and meaningful outcomes important to 
define for DM-ADRD patients: The evidence reviewed above points to meaningful outcomes for 
the patient/CG dyad that high quality DM-ADRD care must achieve – CG support, decreased 
burden and attention to preferences; improved quality of life based on decreased symptoms and 
stable function for patients; and decreased healthcare utilization. Too often DM-ADRD patients 
are not represented in studies used for DM quality metrics and payers may not be aware of ADA 
and AGS positions. Our project will define high quality management and meaningful outcomes 
for this vulnerable, rapidly growing patient group. 

 
 
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2. Study Design 
 
The design is a mixed methods evaluation of a pragmatic randomized controlled trial (RCT) of a 
clinical quality improvement program for patients with diabetes (DM) and Alzheimer ’s disease 
and Related Dementias (DM-ADRD).  The RCT will occur at NYU Langone Health and affiliated 
hospitals and clinics. We are using mixed methods (surveys and qualitative interviews) to better 
understand patient, caregiver (CG) and provider experiences and outcomes.  
 
3. Subject Population 
 
3.1 Total Number of Subjects and Sites 
 
We will randomize the 20 largest NYU Langone Health primary care practices, 9 Intervention 
(INT) clinics and 9 control (CON) clinics. We will enroll 1,000 patients (and their caregivers) ≥65 
with diabetes (DM) and Alzheimers disease and other forms of dementia (ADRD) from these 
practices based on the Inclusion and Exclusion criteria below. As stated in inclusion and 
exclusion criteria, patients must have a caregiver who will also be enrolled. The patient and 
caregiver are referred to as a “dyad.” 
 
3.2 Inclusion Criteria  
 
Patient: 
1) Patient must receive care at one of the INT or CON clinics. 
2) Patient must be 65 years and older. 
3) Patient must have DM diagnosis. 
4) Patient must have documented cognitive impairment or an ADRD diagnosis (ICD-10 
diagnosis in Epic). 
5) Patient must have someone who is identified as a family or friend who provides 
caregiving assistance. 
 
Caregiver: 
1) Caregiver must have adequate knowledge of identified patient and/or participate in 
that member’s healthcare decisions. 
2) Caregiver must be English or Spanish speaking. 
3) Caregiver must demonstrate capacity to consent to research participation. 
4) Caregiver must be at least 21 years old. 
 
3.2 Exclusion Criteria 
Patient: 
1) Patient does not receive care at one of the clinics. 
2) Patient is not 65 years and older. 
3) Patient does not have DM diagnosis. 
4) Patient does not have documented Cognitive impairment or an ADRD diagnosis. 
5) Patient has end stage dementia, other terminal illness with <6 months to live, and/or 
is hospice eligible. 

 
 
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6) Patient does not have a caregiver. 
7) Hearing too poor to use telephone. 
 
Caregiver: 
1) Caregiver does not have adequate knowledge of identified patient and/or does not 
participate in that member’s healthcare decisions. 
2) Caregiver is not English or Spanish speaking. 
3) Caregiver lacks capacity to consent to research. 
4) Caregiver is under 21 years old. 
5) Hearing too poor to use telephone. 
 
3.3 Vulnerable Subjects  
 
Patients with cognitive impairment and their caregivers are a vulnerable group; however, the 
procedures employed in this clinical trial are low risk and have been successfully employed 
without incident in a number of other studies by this research team as well as by other 
investigative teams. The patient has the right to decline participation for any potential caregiver 
who assists them or direct the caregiver to withdraw participation at any time. See Section 5.2 
for consent procedures that include a Capacity to Consent screen, to ensure subject 
comprehension.  
3.4 Duration of Subject Participation  
 
Participant dyads (patient and caregiver) will be in the study for a maximum of 24 months 
(surveyed at baseline, 6, 12 and 24 months). Only caregivers will complete surveys and 
interviews. 
 
4. Quality Improvement Program – Description of the QI interventionIn this 
quality improvement program, INT and CON clinics will be provided with quality improvement 
activities for patients with diabetes and ADRD.  
For both the INT and CON clinics: 
We will provide decisional guidance (the guideline); materials about community and NYU 
Langone Health resources for managing patients with DM-ADRD, particularly caregiver support 
services; advice on referrals for both DM and cognitive specialty care; provider education, and 
basic feedback. We will try to identify a clinical champion in all INT and CON clinics.   
We will receive some workflow support for the quality improvement program. This will include 
Epic-based EHR enhancements such as guidance for MiniCogTM cognitive screening; provider 
scripts for decisional guidance discussions, especially for care de-escalation and cognitive 
screening results. Basic feedback and education will occur in both INT and CON clinics 
including yearly meetings with PCPs for education and feedback on DM and ADRD 
management. 
Preparation for the PCPs will occur either before or very soon after the quality improvement 
program begins. The research team will meet with clinic providers and staff at a monthly 
meeting. PCPs will receive a 30-60 minutes in person training including introduction to the 

 
 
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decisional guidance, introduction to clinical resources and possibly other educational materials, 
such as templates and scripts.  
Based on the guideline, providers will be encouraged to develop individualized management 
targets, particularly for HbA1c and BP, for each patient, and re-evaluate these targets over time. 
Providers will also be trained in cognitive screening with the MiniCogTM .  Clinic staff will be 
trained in minor workflow changes related to the intervention.  
INT Clinics: 
In the INT clinics we will introduce the panel manager (PM) to all clinic staff and develop 
processes for interaction.  The PM will work with INT clinic providers to individualize 
communication methods between the PCP and PM.  Each month INT clinic providers will get a 
list of eligible patients who have appointments with them in the coming month - those with 
diagnoses of DM-ADRD and those 75 and older with DM who are out of range for HbA1c or BP. 
This process gives providers monthly reminders about the ongoing quality improvement study 
and is a more intensive form of QI intervention than provided to CON clinics. 
Because this is a pragmatic trial, the clinical team and a project-funded PM will deliver the 
intervention, fitting it as closely as possible into usual clinical workflow. The clinical team 
includes PCPs, occasional APNs and PAs (who function as PCPs), RN’s, MA’s, office staff, and 
clinic onsite administration. The PM will be part of the team; PMs providing chronic disease self-
management support (usually telephonic) are clinic team members in many healthcare systems.  
We will assign two PMs to 9 randomly selected INT clinics. Each PM will have 4.5 INT clinics 
and will engage and focus on their first clinics in a randomly ordered step-wise fashion working 
within 1-2 clinics over a focused 3-month period before moving on to the next 1-2 clinics for 3 
months, then the last 1-2 clinics for 3 months. Our preliminary data suggests 20-50 patients per 
INT clinic with DM-ADRD ≥65 years; and about an equal number with DM without ADRD who 
will screen positive for cognitive impairment, most of whom are ≥75 years and identified by 
HbA1c/BP over or under treatment, or identified by provider referral, which we will allow. With 9 
INT clinics, given our preliminary data about patient numbers, each PM will have an anticipated 
300 dyads. PMs can engage about 33 patients/month, making initial 300 patient/CG contact in 9 
months.  
The PM will clinically decide how/which patients to engage in what order. We think that 
engaging DM-ADRD patients/caregivers around their PCP visit makes the most sense for the 
dyad, the PCP and the PM and we have established that process.  However, as a clinician, the 
PM may identify other patients with significant needs and may engage them as soon as patient 
is identified (i.e. patient over 75 with poor BP control, social needs, and PCP suspects cognitive 
problem). For the INT clinics we think this approach will ensure 1) adequate time to engage all 
dyads with thorough evaluation for those who meet criteria for care quality improvement; 2) 
focused presence to engage and be known to the PCPs in that clinic; and 3) time needed to 
ensure initial follow-up of recommended actions to ensure that recommended care processes 
are completed. Supporting activities will continue for each previously engaged clinic when 
moving onto the next clinic. We anticipate patient/caregiver loss over the 3 years of the study 
and the sample will be refreshed with patients with new diagnoses and who are new to the 
clinic. Although these patient/caregiver dyads will be followed for shorter durations, they will be 
enrolled as discussed in 4.2 and they will contribute information until the end of the study.  

 
 
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PM Qualifications and Training: The PM will be a licensed healthcare professional, either an RN 
or pharmacist.  She/he will meet all criteria needed for hiring and credentialing within the NYU 
Langone Health clinical enterprise.  Required qualifications:  RN or clinical pharmacist; 2 years’ 
experience in licensed role.  Preferred characteristics: Certified diabetes educator (CDE); 
geriatrics experience, Spanish fluency.  
Because we plan to hire two PMs, a combination CDE who is also an RN, and a clinical 
pharmacist would provide complementary expertise, although a second RN would also be 
acceptable. As noted below, we plan that the PM will work mainly with particular clinics to 
develop relationships with providers and clinic staff, but we also anticipate that they will work on 
relevant cases in any clinic where complementary expertise may be useful.  For example, if only 
one PM speaks Spanish, regardless of INT clinic, that PM would handle Spanish speaking 
dyads.   
We will train intervention PMs in DM and ADRD management for INT clinics. Training will 
include one-on-one sessions with the mPI’s and co-I’s, suggested reading, shadowing relevant 
clinicians, such as social workers in the Alzheimer’s Disease Center and geriatrics clinic, and 
other relevant activities. We expect training will require one month’s duration with subsequent 
continuous learning activities that include continuing meetings with mPIs and co-I’s and travel to 
national conferences. 
PM Activities. The PM will reach out to eligible patients with diagnosed DM-ADRD (see section 
4.3) and ≥75 year-old patients with over- and under-treatment of HbA1c/BP for cognitive 
screening using IQ-CODE as defined in the Guideline. For those with a positive screen, in 
coordination with the PCP, the PM will facilitate further cognitive evaluation.  These patients will 
become part of the quality improvement intervention. The PM will begin telephonic assessment 
and DM management education of DM-ADRD patients around the time of the scheduled visit 
(either just before or just after). The PM will conduct a detailed psychosocial and needs 
assessment with each willing CG and assess the patient based on both a standardized 
assessment and clinical judgement. The PM will also engage those CGs who live far from the 
patient and who manage the patient remotely through paid home heath aids (HHA). The CG 
psychosocial assessment will focus on diabetic management support and family dementia CG 
support providing referrals as needed to well established New York City programs. The PM will 
provide PCPs with evaluation data, DM-relevant care suggestions and facilitate PCP visits for 
care reassessment as clinically appropriate. The PM will assist the PCP and the dyad with 
developing individualized DM management targets and re-evaluating these targets over time. 
The PM will maintain dyad follow-ups and monitor patient-level data using EHR follow-up data 
as per usual clinical care, and an Epic-generated report for relevant issues.  The PM will also 
address dyad goals and treatment preferences and assist with communicating these with the 
PCP. A key part of PM activity will be determining with each PCP their preferred method of 
communication (e.g., Epic messaging, order pending, periodic phone calls, etc).  
At primary care visits of DM patients with known ADRD or a positive cognitive screen, PCPs, 
coordinating with PMs, will proceed with DM management according to EQUIPED-ADRD 
Guidelines. PCPs will have PM information about CG stress, treatment preferences, and need 
for CG support referrals through the PM notes or Epic “in-basket” communications.  PCPs will 
reassess as needed and encourage referrals. In patients with a positive cognitive screen, PCPs 
will follow guidelines for further cognitive evaluation per dyad preference. PCPs will have scripts 
to facilitate discussions, knowing that the PM will follow-up with the dyad after the visit. Clinic 

 
 
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workflow redesign is expected to be minimal. Providers will be alerted to the visit of relevant 
patients as described in the enrollment section and dyads will have an explanation of the 
EQUIPED-ADRD program through IRB approved brochures. 
Over the 3 years of the study, the PM will continue to assist the dyad telephonically with DM-
ADRD management support as clinically appropriate to meet management targets, 
communicating as needed with the PCP. EHR-generated reports on DM management will 
support intervention PCPs and PMs.  
Provider Feedback. In the INT clinics, bi-annual reports will be given to providers and these will 
be discussed at bi-annual meetings which will be either by webinar or in person; in-person 
meetings will be held at least once a year. The provider–specific reports will detail DM-ADRD 
patients’ medical management metrics such as numbers of caregiver referrals to community 
support, any changes in proportions of patients in range for HbA1c and BP, and the number of 
older adults with DM screened for cognitive impairment.  Monthly patients lists will serve as 
periodic reminders of the quality improvement program. Other feedback and collaborative 
learning opportunities for INT clinic providers include quarterly “office hour” webinars with the 
mPI’s and co-I’s to review the reports and brainstorm opportunities for improvement.  
CON Clinics: 
Providers will get a list of eligible patients DM-ADRD initially, giving them the opportunity to 
follow the decisional guidance. In addition, the guideline will specify cognitive screening in DM 
patients, ≥75 years with high or low HbA1cs or BP’s because we suspect that these values may 
represent self-management red flags due to cognitive (especially memory and executive) 
impairment. During training the CON providers will be encouraged to do cognitive screening as 
well as follow the guidelines in general. Clinics can decide who does the cognitive screen, such 
as a RN or MA, using the MiniCogTM we will address this issue in the guideline and during 
provider training. Per guidelines, any patient with a MiniCogTM score < 3 of 5 should have 
further cognitive assessment per the guideline and preferences of the patient/caregiver dyad. 
These patients will also become eligible for the evaluation and can be identified by periodic 
research staff EHR identification of patients with DM-ADRD diagnoses in the CON clinics. When 
identified we will enroll them for the evaluation (4.2). As with INT clinic patients, we anticipate 
patient/caregiver loss over the 3 years of the study and the sample will be refreshed with 
patients with new diagnoses and who are new to the clinic. The investigators will visit CON 
clinics yearly to discuss care of patients with DM-ADRD. These meetings will serve to answer 
questions, get feedback from PCPs and provide general feedback on the progress of the quality 
improvement program. 
 
5.  Methods and Procedures (Evaluation) 
 
5.1 Screening and Identification 
 
We will use NYU Langone Health Epic to identify patients in the INT and CON clinics who meet 
inclusion and exclusion criteria listed in Section 3.2. 
 
There will be three levels of screening: 

 
 
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• 
Level 1: Initial screening will be automated by settings in the EHR that generate a report 
based on inclusion criteria (above). 
 
• 
Level 2: The initial list of patients generated by the EHR will be screened by the RA first 
through chart review for eligibility based on exclusion criteria (see Section 3.2). Should the 
patient not meet inclusion criteria, for example they don’t actually have a diagnosis of 
diabetes, or speak English or Spanish; the patient will be removed from the list of 
potentially eligible patients.  
 
• 
Level 3: Those patients who remain eligible following chart review to their PCP’s in the 
INT clinics to notify them about their patients with DM-ADRD. The PCP’s will be 
encouraged to review their list and decide if a patient is misclassified or inappropriate; 
some will review the lists and some will not. Any patient a PCP indicates as inappropriate 
or misclassified will be ineligible and will be screen failures. The amended list of eligible 
patients with both DM and ADRD for both the INT and CON clinics will go back to the RM 
who will send a letter to the patients informing the patients/caregiver of the quality 
improvement program and of a potential telephonic survey.  
 
While eligible patients are easily identified by Epic, their caregivers (the respondents to the 
surveys and interviews to evaluate the quality improvement program) are not always listed in the 
patient chart. To identify an appropriate caregiver, a letter from the primary care physician will ask 
the patient to read the letter and then give it to their caregiver. The letter will explain the quality 
program briefly and state that a research assistant will call the patient’s home unless they do not 
want to be called.  
 
If the dyad, for whatever reason, does not want to participate in a call, they will be asked to opt 
out using the Standard Operating Procedure (SOP) of NYU Langone Health as outlined in SOP 
#HSR-312, Version Number 2.0. This SOP states that patients are able to opt-out of the Direct 
Recruitment process either by phone (1-855-777-7858) or email (research-contact-
optout@nyumc.org). Patients who wish to opt out must provide at least three of the following 
identifiers:  
 
1. Full name 
2. Date of birth 
3. Address 
4. Medical record number 
 
The opt-out phone line and email account are managed by Office of Science and Research (OSR) 
personnel. Authorized OSR personnel and the Senior Director of Compliance and Privacy are the 
only individuals authorized to add patients to the opt out list. Should we receive a patient opt out 
request we will instruct the patient to follow this process. OSR will process this request upon 
receipt of all required information, and update the patient status in a tracking sheet and in Epic to 
“Do Not Contact.” 
 
5.2 
Consent Procedures and Documentation  
 
5.2.1 Process of Consent 
 
The patient and caregiver (dyad) is enrolled in the study (the evaluation of the RCT of a quality 

 
 
Study #: s18-01166 
 
 
 
 
Page 14 
Version date: 6/03/2020 
 
 
 
 
improvement program) when verbal consent (or assent, see E3) is obtained from the patient and 
caregiver.  
 
Verbal Consent 
We are requesting a HIPPA waiver of authorization and documentation of consent in order for 
caregivers and patients to give verbal consent for the survey, qualitative interview and use of 
patient  data (EHR and claims).  
 
We request the use of verbal consent and a waiver for documentation of consent because: 
 
1) This study presents no more than minimal risks to privacy for subjects. All survey data 
obtained will be stored in HIPPA compliant REDCap library accessible only to the IRB 
approved study team. All data exported from REDCap will be fully de-identified, and 
contain no subject identifiers. 
 
2) It would not be possible to conduct this study without the use and analysis of subject 
PHI to evaluate the improvement in care for patients, and burden for caregivers. 
Investigators will take all precautions, outlined in Section 6.2 Protection Against Risks, 
to protect the privacy and maintain confidentiality of subjects.  
 
3) Surveys and qualitative interviews will occur by telephone making written consent 
infeasible given enrollment of 1,000 patients and caregiver dyads.  
 
4) Verbal consent provides opportunity to fully explain study procedures, risks and benefits 
and assess for capacity to consent, an important and necessary procedure in this 
population both for patients and caregivers. 
 
5) It Requiring an elderly person to recall, interpret, and understand requested instructions 
for consent purposes through mail will result in many unreturned documents and an 
unfair prevention of participation for those persons who want to participate but are 
otherwise “unable” to.  
 
6) Finally, in the clinical space, where HIPPA rules are equally enforced, we conduct 
verbal consents for release of information when written consents are not feasible and 
complete that authorization by documentation from a legally authorized representative 
(in this case, a physician). 
 
Step by step process of consent:  
1. INT: RA mails letter (see Patient Letter) to patients in INT clinic signed by the clinic director, 
lead physician, or primary provider (depending on clinic preference) informing them about 
EQUIPED quality improvement program and evaluation. 
 
2. INT and CON: RA calls eligible patient and/or caregiver using contact information from 
patient chart in EHR. If caregiver information is not available in the chart, the RA will ask the 
patient for caregiver contact information. 
 
3. INT and CON: RA screen Patient and/or Caregiver for Capacity to Consent (See section E3) 
a. If the patient demonstrates capacity, the patient is deemed able to provide verbal 
consent to have the study team talk to the caregiver to obtain their verbal consent 

 
 
Study #: s18-01166 
 
 
 
 
Page 15 
Version date: 6/03/2020 
 
 
 
 
and to have the study personal obtain and analyze health data (medical records and 
claims). 
b. If the patient does not have capacity and assents to the study, the RA is able to speak 
to the caregiver who provides verbal consent for the caregiver survey , and the Health 
Care Proxy (HCP) (who may or may not be the caregiver) provides verbal consent 
for study personnel to obtain and analyze the patients’ health data (medical records 
and claims).  
c. If the patient does not have capacity, and refuses (no assent), the dyad will not be 
enrolled although the clinical team (Panel Manager) can re-contact that dyad over 
time to offer improved care quality.  
 
4. INT and CON: If the caregiver demonstrates capacity (screened using Capacity to Consent, 
at the discretion of the RA) verbal consent will be documented by the RA in REDCap and 
the caregiver will be consented to participate in the study. Caregiver consent covers 
participation in 4 telephone surveys.   
 
A healthcare proxy is an individual who is designated as a representative/agent through a health 
care proxy signed by both the subject and the appointed representative/agent. For a health care 
proxy to be effective, it must have been signed at a time when the subject had decision-making 
capacity. In addition, the health care proxy must not specifically prohibit research. Determination 
of the legal authority of a surrogate will be obtained through Epic, or verbally by the patient 
and/or caregiver.  
 
Potential subjects will be told that their involvement in the study is completely voluntary and that 
they can withdraw from the study at any point. Caregivers may themselves be elderly and might 
have cognitive impairment such that it impacts their capacity to consent to research. For all 
potential participants, we will assess the individual’s ability to provide informed consent using 
IRB approved interview procedures to assess capacity to consent for research. Some subjects 
may be too hearing impaired to communicate by telephone and the telephone interview is 
designed to assess for this potential problem and mitigate this issue when possible but this might 
impair one’s capacity to consent. Although we have conducted numerous studies with elderly 
subjects, this has been a rare occurrence. Nonetheless we will not enroll any caregiver 
participant who cannot communicate by telephone. 
 
If the patient demonstrates capacity (See E3. Subject Capacity), the patient is deemed able to 
provide verbal consent to have the RA talk to the caregiver and to have the study personal obtain 
and analyze health data. If the patient does not have capacity and assents the caregiver will 
provide verbal consent for the caregiver survey, and the HCP (who may or may not be the 
caregiver) provides verbal consent for the health data (medical records and claims). If the patient 
refuses (with or without capacity), the dyad will not be enrolled although the clinical team can re-
contact that dyad over time to offer improved quality care.  
 
If the caregiver, after following our standard consent procedures, demonstrates capacity using 
the below questions, verbal consent will be documented and the caregiver will be consented to 
the study. Caregiver consent covers participation in 4 telephone surveys.  Patient (with capacity) 
or HCP (if patient assents but does not have capacity) will provide verbal consent for health data 
(EHR and claims information). The research assistant will document this agreement to 
participate using a standardized form kept for documentation purposes.  
 

 
 
St u d y #: s 1 8 -0 1 1 6 6  
 
 
 
 
P a g e 1 6 
V er si o n d at e: 6/ 0 3/ 2 0 2 0 
 
 
 
 
C o n s e nt f or Q u alit ati v e I nt er vi e w s  
 
C ar e gi v er:  
 
C o n s e nt pr o c e d ur e s a s pr e vi o u sl y d e s cri b e d will b e f oll o w e d  f or t h o s e c o m pl eti n g q u alit ati v e 
i nt er vi e w s. All w h o p arti ci p at e will pr o vi d e v er b al c o n s e nt t o b e a u di ot a p e d ( s e e 6. 2 Pr ot e cti o n 
A g ai n st Ri s k s ), w hi c h will b e d o c u m e nt e d b y t h e r e s e ar c h a s si st a nt u si n g a st a n d ar di z e d f or m 
k e pt f or d o c u m e nt ati o n p ur p o s e s. T h e q u alit ati v e r e s e ar c h er s will n ot b e bli n d e d d u e t o t h e 
p ur p o s e s of t h e q u alit ati v e st u d y a n d t h e t y p e of d at a t h e y ar e c oll e cti n g.  
 
Pr o vi d er s a n d St aff:  
P C P s  a n d  st aff  m e m b er s  will  b e  i d e ntifi e d  b y  cli ni c  c o nt a ct s  f or  p arti ci p ati o n  i n  q u ali t ati v e 
i nt er vi e w s ( o n e i nt er vi e w f or e a c h i n di vi d u al). T h e q u alit ati v e st u d y R A will n ot i nt er vi e w m or e 
t h a n o n e p arti ci p a nt t y p e fr o m e a c h cli ni c a n d s a m pli n g will b e b y c o n v e ni e n c e f or t hi s st u d y 
c o m p o n e nt. P ot e nti al p arti ci p a nt s will b e i nf or m e d t h at a d e cli n e i n p arti ci p ati o n will i n n o w a y 
i m p a ct e m pl o y m e nt a n d t h eir e m pl o y er s will n ot k n o w of t h eir a gr e e m e nt or r ef u s al t o p arti ci p at e. 
T h o s e w h o a gr e e t o p arti ci p at e will pr o vi d e writt e n c o n s e nt, i n cl u di n g c o n s e nt t o b e a u di ot a p e d, 
w hi c h  will  b e  d o c u m e n t e d  b y  t h e  r e s e ar c h  a s si st a nt  u si n g  a  st a n d ar di z e d  f or m  k e pt  f or  
d o c u m e nt ati o n p ur p o s e s  (6. 2 Pr ot e cti o n A g ai n st Ri s k s).  
 
E 3. S u bj e ct C a p a cit y  
If t h e c ar e gi v er, aft er f oll o wi n g o ur st a n d ar d c o n s e nt pr o c e d ur e s, d e m o n str at e s c a p a cit y u si n g 
t h e b el o w q u e sti o n s, v er b al c o n s e nt will b e d o c u m e nt e d a n d t h e c ar e gi v er will b e c o n s e nt e d t o 
t h e st u d y. A s f ar a s p ati e nt c o n s e nt i s c o n c er n e d, s h o ul d t h e p ati e nt n ot d e m o n str at e c a p a cit y t o 
c o n s e nt, b ut n ot r ef u s e t o p arti ci p at e, t h e R A/ R C will f oll o w t h e a s s e nt pr o c e s s a n d c o n s e nt t h e 
c ar e gi v er.  C o n s e nt  c o v er s  p arti ci p ati o n  i n  o n e  s ur v e y  a n d  a  q u alit ati v e  i nt er vi e w.  O n c e  t h e  
c o n s e nt pr o c e s s i s c o m pl et e d, t h e R A will eit h er c o m pl et e t h e b a s eli n e i nt er vi e w or s c h e d ul e a 
ti m e f or a f oll o w-u p p h o n e c all.  
 
W h e n o bt ai ni n g c o n s e nt w e will u s e t h e st a n d ar d pr o c e d ur e s f or a d dr e s si n g c a p a cit y t h at w e 
h a v e b e e n u s e d i n m a n y pri or st u di e s, b ut m a y m o dif y t hi s pr o c e s s t o b e i n c o m pli a n c e wit h t h e 
I R B i n v ol v e d i n t hi s st u d y a s p er t h eir r e q u e st. T h e f oll o wi n g q u e sti o n s will b e us e d:  
 
W e h a v e j u st r e vi e w e d w h at it m e a n s t o p arti ci p at e i n t hi s st u d y. I a m g oi n g t o a s k y o u a f e w 
q u e sti o n s j u st t o m a k e s ur e y o u u n d er st a n d w h at w e will b e d oi n g o n c e w e b e gi n.  
 
1.  W h at w o ul d y o u b e d oi n g if y o u a gr e e t o t a k e p art i n t hi s st u d y ? ( E x a m pl e s of 
a c c e pt a bl e a n s w er s: “ T a k e p art i n a n i nt er vi e w/ s ur v e y,” or “ A n s w er q u e sti o n s a b o ut m y 
fri e n d or r el ati v e.”) 
 P er s o n i s a bl e t o a n s w er t hi s  
P er s o n i s n ot a bl e t o a n s w er t hi s  
 
2.  W h at c a n y o u d o or a s k m e t o d o if y o u ar e u n c o mf ort a bl e wit h a p arti c ul ar q u e sti o n i n 
t h e s ur v e y ? ( E x a m pl e s of a c c e pt a bl e a n s w er s: “ A s k t o s ki p t h e q u e sti o n.” “ A s k y o u t o 
r e a d a n ot h er q u e sti o n.”) 
 
 P er s o n i s a bl e t o a n s w er t hi s  
P er s o n i s n ot a bl e t o a n s w er t hi s  
 

 
 
St u d y #: s 1 8 -0 1 1 6 6  
 
 
 
 
P a g e 1 7 
V er si o n d at e: 6/ 0 3/ 2 0 2 0 
 
 
 
 
3.  W h at c a n y o u d o if y o u d e ci d e aft er w e st art t h at y o u d o n ot w a nt t o p a rti ci p at e i n t h e 
st u d y ? ( E x a m pl e s of a c c e pt a bl e a n s w er s: “ T ell y o u t h at I d o n ot w a nt t o a n s w er a n y 
m or e q u e sti o n s.”)  
 
 P er s o n i s a bl e t o a n s w er t hi s  
P er s o n i s n ot a bl e t o a n s w er t hi s  
 
E 4. S u bj e ct/ R e pr e s e nt ati v e C o m pr e h e n si o n  
P ot e nti al s u bj e ct s will b e t ol d t h at t h eir i n v ol v e m e nt i n t h e st u d y i s c o m pl et el y v ol u nt ar y a n d t h at 
t h e y c a n wit h dr a w fr o m t h e st u d y at a n y p oi nt. C ar e gi v er s m a y t h e m s el v e s b e el d erl y a n d mi g ht 
h a v e c o g niti v e i m p air m e nt s u c h t h at it i m p a ct s t h eir c a p a cit y t o c o n s e nt t o r e s e ar c h. F or a ll 
p ot e nti al p arti ci p a nt s, w e will a s s e s s t h e i n di vi d u al’ s a bilit y t o pr o vi d e i nf or m e d c o n s e nt u si n g 
I R B a p pr o v e d i nt er vi e w pr o c e d ur e s t o a s s e s s c a p a cit y t o c o n s e nt f or r e s e ar c h. S o m e s u bj e ct s 
m a y b e t o o h e ari n g i m p air e d t o c o m m u ni c at e b y t el e p h o n e a n d t h e  t el e p h o n e i nt er vi e w i s 
d e si g n e d t o a s s e s s f or t hi s p ot e nti al pr o bl e m a n d miti g at e t hi s i s s u e w h e n p o s si bl e b ut t hi s 
mi g ht i m p air o n e s c a p a cit y t o c o n s e nt. Alt h o u g h w e h a v e c o n d u ct e d n u m er o u s st u di e s wit h 
el d erl y s u bj e ct s, t hi s h a s b e e n a r ar e o c c urr e n c e. N o n et h el e s s w e will n ot e nr oll a n y c ar e gi v er 
p arti ci p a nt w h o c a n n ot c o m m u ni c at e b y t el e p h o n e.  
 
E 5. D o c u m e nt ati o n of C o n s e nt  
T h o s e w h o a gr e e t o p arti ci p at e will pr o vi d e v er b al c o n s e nt, i n cl u di n g c o n s e nt t o b e a u di ot a p e d, 
w hi c h will b e d o c u m e nt e d b y t h e r e s e ar c h a s si st a nt i n t h e R E D C a p li br ar y f or cl e ar 
d o c u m e nt ati o n p ur p o s e s. T h e pr o vi d er s t h at p arti ci p at e i n t h e q u alit ati v e i nt er vi e w s will si g n 
writt e n i nf or m e d c o n s e nt s a n d a u di o c o n s e nt f or m s.  T h e s e d o c u m e nt s will b e l o g g e d a n d k e pt 
i n t h e st u d y bi n d er i n a l o c k e d c a bi n et t h at i s a c c e s si bl e o nl y t o t h e PI a n d t h e st u d y 
c o or di n at or.  
 
5 . 3 St u d y S p e cifi c Pr o c e d ur e s   
 
St u d y pr o c e d ur e s i n cl u d e c ar e gi v er s ur v e y s a n d i nt er vi e w s t o e v al u at e t h e q u alit y i m pr o v e m e nt 
pr o gr a m d e s cri b e d i n S e cti o n 4.  
 
5 . 4 D at a C oll e cti o n O v er vi e w  ( E v al u ati o n) 
 
W e  will  c oll e ct d at a  fr o m fi v e s o ur c e s:  
1)  C ar e gi v er s ur v e y s  
2)  C ar e gi v er  q u alit ati v e i nt er vi e w s   
3)  Pr o vi d er/ St aff q u alit ati v e i nt er vi e w s  
4)  P ati e nt d at a fr o m E pi c    
5)  P ati e nt d at a fr o m R e s D A C  ( R e s e ar c h D at a  A s si st a n c e C e nt er)  cl ai m s  d at a  
 
1.  C ar e gi v er s ur v e y s.  T h e s ur v e y will b e a d mi ni st er e d  o v er t h e t el e p h o n e a n d p arti ci p a nt 
r e s p o n s e s will  b e  e nt er e d  i n  R E D C a p  s ur v e y  d at a b a s e . A  bli n d e d  r e s e ar c h  a s si st a nt  
i nt er vi e w er will c oll e ct c o m pl et e t el e p h o n e s ur v e y d at a fr o m C G s at b a s eli n e, 6 mo nt h s, 
1 2 m o nt h s a n d 2 4  m o nt h s u si n g a 3 0 -mi n ut e s ur v e y ( s e e S ur v e y i n str u m e nt ). T h e R A will 
e nt er d e -i d e ntifi e d s ur v e y d at a fr o m e a c h s ur v e y w a v e i nt o a HI P A A-c o m pli a nt R E D C a p 
el e ctr o ni c d at a b a s e h o st e d at N Y U L H .  
2.  Q u alit ati v e i nt er vi e w s  will b e c o n d u ct e d wit h  40 d y a d s ( or u ntil t h e m ati c s at ur ati o n i s 
r e a c h e d f or k e y c o nt e nt ar e a s) e a c h fr o m t h e I N T a n d C O N cli ni c s. C ar e gi v er C o g niti v e 
I nt er vi e w s will al s o b e c o n d u ct e d wit h a n a d diti o n al 2 0 c ar e gi v er s t o e v al u at e t h e u s e of 

 
 
Study #: s18-01166 
 
 
 
 
Page 18 
Version date: 6/03/2020 
 
 
 
 
the Treatment Burden Questionnaire (TBQ) for Caregivers and identify any potential 
problems that may compromise the quality of data collected using the TBQ with 
caregivers. The purpose of these interviews is to validate this tool for future studies to 
measure treatment burden of caregivers. These 60 interviews will be audio recorded 
(included in verbal consent) and transcribed. Audio tapes will be destroyed once 
transcriptions are complete, which will be stored in a HIPAA-compliant NYU secure 
server.  
 
 
3. Provider/Staff Qualitative Interviews will be conducted using purposive sampling 
framework with members from each category: internal medicine physician; specialty 
physician; care managements and nursing. Written informed consent will be obtained.  
Interviews will be conducting via phone. These interviews will be audio recorded  and 
transcribed. Audio tapes will be destroyed once transcriptions are complete, which will 
be stored in a HIPAA-compliant NYU secure server.   
 
4. Patient data from Epic. An trained member of the research team (Research Coordinator) 
who will be blinded to participant INT or CON group affiliation will be responsible for 
collecting and entering EHR data into REDCap for enrolled patients. The dyad will have 
consented verbally to review of their medical record in Epic. In order to evaluate this quality 
improvement intervention, the study team will pull and review administrative data from 
Epic on patients in the intervention and control clinics. These data will be de-identified and 
used to monitor safety and evaluate effectiveness of the intervention.  
 
5. ResDAC (Research Data Assistance Center) claims data will be applied for in the 2nd or 
3rd year of this study. An IRB modification will be submitted to obtain this data.  
 
 
Measures 
Survey 
Table 1 
 
 
 
 
 
 
 
Measure 
Source 
of Data 
How measured 
Subj
ect 
Baselin
e 
6 Months 
12 
months 
24 
months 
Age 
EHR/ 
Survey* 
Years 
CG, 
Pt 
X 
 
 
 
Gender 
EHR/ 
Survey 
Categorical: Male/Female 
CG, 
Pt 
X 
 
 
 
Race/Ethni
city 
EHR/ 
Survey 
Categorical: White, Black, 
Hispanic, other 
CG, 
Pt 
 
X 
 
 
 

 
 
Study #: s18-01166 
 
 
 
 
Page 19 
Version date: 6/03/2020 
 
 
 
 
Education 
Survey 
Categorical: < H.S., H.S., 
Some College, College 
graduate+ 
CG 
 
X 
 
 
X 
Clinical co-
morbid 
conditions 
EHR 
Charlson comorbidity index8 
Pt 
X 
X 
X 
X 
Medication 
Complexity 
EHR 
Unique medications (n) + 
unique multiple 
administrations/day (n) 
Pt 
X 
X 
X 
X 
Prior (1-
year) non-
acute use 
ResDAC 
Counts: physician 
ambulatory visits 
Pt 
X 
X 
X 
X 
Prior (1-
year) 
acute use 
ResDAC 
Counts: ED, hospital visits / 
bed days 
Pt 
X 
X 
X 
X 
Social 
Support 
Survey 
MOS Abbreviated Social 
Support (4-item; 5-point 
Likert scale)79,80 
CG 
X 
X 
X 
X 
COVID-19  
Survey 
Exposure and symptoms, 
testing status, impact, 
changes in burden, access 
to resources 
CG, 
Pt 
X 
 
 
 
Follow-up 
COVID-19  
Survey 
Exposure and symptoms, 
testing status, impact, 
changes in burden, access 
to resources 
CG, 
Pt 
 
X 
X 
X 
DM-
ADRD-
Specific 
 
 
 
 
 
 
 
Dementia 
Diagnosis 
/Type 
EMR 
Categorical: Yes/No and if 
yes, AD, Lewy Body 
disease, Parkinson’s 
Disease, Vascular, 
Frontotemporal, and mixed 
Pt 
X 
 
 
X 
Dementia 
Severity 
Survey 
Dementia Severity Rating 
Scale87 
Pt 
X 
 
 
X 
Caregiver 
relationshi
p to CR 
Survey 
Categorical: Spouse, child, 
other relative, friend/other 
CG,  
Pt 
X 
 
 
 

 
 
Study #: s18-01166 
 
 
 
 
Page 20 
Version date: 6/03/2020 
 
 
 
 
Functional 
State 
Survey 
14 items: ADL/ IADL for CG; 
within DSS  for Pt 
CG,  
Pt  
X 
X 
X 
X 
Marital 
Status 
Survey 
Categorical: Single/never 
married, married, divorced, 
widowed 
CG,  
Pt 
X 
 
 
 
X 
Substance 
use history 
Survey 
Current: Yes/No; Past 
history: Yes/No  
CG,  
Pt 
X 
X 
X 
X 
Mental 
illness 
history 
Survey 
Yes/No: Depression, 
schizophrenia, PTSD, other  
CG,  
Pt 
X 
 
 
 
Diabetes 
care 
questions  
Survey 
diet, blood sugar testing, 
exercise 
Pt 
x 
x 
x 
x 
Hypoglyce
mia 
Survey 
Number, number 
documented,  treatment, 
number seek medical 
attention 
Pt 
 
 
 
 
Neuropathi
c pain 
Survey 
Yes/no 
Pt  
X 
X 
X 
X 
Urinary 
symptoms 
 
Survey 
Counts: frequency, dysuria, 
incontinence, urgency 
Pt 
X 
X 
X 
X 
Falls 
Survey 
Number, number injurious in 
last year and then since last 
survey, number ED or other 
falls requiring medical 
attention 
Pt 
X 
X 
X 
X 
Syncope 
EHR 
Number, number ED 
diagnoses or other events 
requiring medical attention 
Pt 
X 
X 
X 
X 
Structural 
Measures 
 
 
 
 
 
 
 
General 
 
 
 
 
 
 
 
Change in 
PCP–past 
6 mo./last 
survey 
EHR 
Yes/No 
Pt 
X 
X 
X 
X 
Consistent 
PCP care 
EHR 
% Visits by PCP versus 
other ambulatory providers 
Pt 
X 
X 
X 
X 

 
 
Study #: s18-01166 
 
 
 
 
Page 21 
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New home 
health aide 
or 
increased 
hours 
Survey 
Yes/no;  HHA resource 
changes 
Pt 
X 
X 
X 
X 
New home 
health care 
services 
Survey 
Yes/no 
Pt 
x 
x 
x 
x 
Insurance 
EHR 
Categorical: Yes/No, 
Medicare, Medicaid, HMO 
Pt 
X 
X 
X 
X 
DM-
ADRD-
Specific 
 
 
 
 
 
 
 
Has a 
caregiver 
(Defined: 
Sec. B5) 
EHR 
Yes/No  
Pt 
 
X 
 
X 
 
X 
X 
Caregiver 
living 
arrangeme
nt 
Survey 
Categorical: Live with 
subject, close proximity 
(miles), other 
CG 
X 
X 
X 
X 
Clinic-
Specific 
 
 
 
 
 
 
 
Clinic Size 
Admin 
Number primary care 
providers / number of 
patients 
Clini
c 
X 
 
 
X 
Clinic 
Support 
Admin 
Number of clinic support 
staff / provider 
Clini
c 
X 
 
 
X 
Proportion 
Medicare/
Medicaid 
Admin 
Insurance data specific to 
Medicare/Medicaid 
categories 
Clini
c 
X 
 
 
X 
EQUIPED 
Process 
of Care 
Measures 
 
 
 
 
 
 
 
Provider 
use of 
structured 
template 
EHR 
Counts: visit note/templates; 
proportion of visits with 
templates 
PCP  
 
X 
X 
X 

 
 
Study #: s18-01166 
 
 
 
 
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Provider 
educationa
l 
attendance  
Admin 
Proportion (n, %) of 
educational sessions 
attended 
PCP 
 
X 
 
 
PM – PCP 
Communic
ation 
EHR 
Counts: emails, forwarded 
notes between PM and PCP 
PM/
PCP 
 
X 
X 
X 
Change in 
diabetic 
medication 
EHR 
Counts: change (add, 
delete); dosing (increase, 
decrease) 
Pt 
X 
X 
X 
X 
Change in 
antihyperte
nsive 
medication 
EHR 
Counts: change (add, 
delete); dosing (increase, 
decrease) 
Pt 
X 
X 
X 
X 
Medication 
complexity 
EHR 
Sum of unique medications, 
daily dosing 
frequency/differences 
Pt 
X 
X 
X 
X 
Anticholine
rgic 
medication 
burden 
EHR 
Anticholinergic medication 
burden scale 
Pt 
X 
X 
X 
X 
PM – CG 
contact 
frequency 
EHR 
Counts: CG visits with PM 
(by type: email, phone, in-
person) 
CG 
 
X 
X 
X 
Referrals 
for CG-
support 
services 
EHR 
Proportion (n, %) of CGs 
referred to programs / 
receipt of service 
CG 
 
X 
X 
X 
Cognitive 
screening 
of eligible 
patients 
EHR 
Proportion (n, %) of DM-
eligible patients screened w/ 
MiniCogTM39 
Pt 
 
X 
X 
X 
Outcome 
Measures 
 
 
 
 
 
 
 
General 
 
 
 
 
 
 
 
Hemoglobi
n A1C 
Change 
EHR 
Proportional change: 
patients with in-range values 
versus not 
Pt 
X 
X 
X 
X 

 
 
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Blood 
pressure 
change 
EHR 
Proportional change: 
patients with in-range values 
versus not 
Pt 
 
X 
X 
X 
X 
Treatment 
Burden 
Questionn
aire 
Survey 
15-item survey modified for 
CG administration (0-10 
likert)85 
Pt 
X 
X 
X 
X 
Non-acute 
care use 
ResDAC 
Counts: provider ambulatory 
visits / all health system 
contacts 
Pt 
X 
 
X 
X 
X 
Acute care 
use** 
 
ResDAC 
Counts: ED, hospital / #bed 
days 
Pt 
X 
X 
X 
X 
Sub-acute 
care use 
 
ResDAC 
Counts: # bed days 
Pt 
X 
X 
X 
X 
LTC use 
 
ResDAC 
Counts: # bed days 
Pt 
 
 
 
 
LTAC or 
Hospice 
use 
 
ResDAC 
Counts: # bed days 
Pt 
 
 
 
 
DM-
ADRD-
Specific 
 
 
 
 
 
 
 
Dementia 
symptoms 
Survey 
DSS  
Pt 
/CG 
X 
X 
X 
X 
Diabetes 
caregiver 
distress 
 
Survey 
 
Diabetes Caregiver Distress 
Scale 
CG 
X 
X 
X 
X 
 
LEGEND: CG=Caregiver; Pt=Patient; EHR=Electronic Health Record; ResDAC=Research Data 
Assistance Center; DM=Diabetes mellitus; ADRD=Alzheimer’s disease and related dementias; 
ADL=Activities of Daily Living; IADL=Instrumental Activities of Daily Living; HABC-M=Health Aging Brain 
Care-Monitor; PTSD=Post-traumatic Stress Disorder; ED=Emergency Department; PCP=Primary Care 
Provider; PM=Panel Manager; MYLOH=Managing Your Loved One’s Health; MOS=Medical Outcomes 
Study TBQ= Treatment Burden Questionnaire;* Note – the survey is always given to the caregiver (CG) 

 
 
Study #: s18-01166 
 
 
 
 
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and includes questions about the CG and about the patient; ** Baseline utilization variables will have 20 
month look-back through claims and EHR 
As shown in Table 1, many variables for the evaluation will be collected from the EHR or from 
claims. However, many caregiver-reported variables will also be collected using scales that have 
been validated for patients, but usually not for caregivers noting that some have been widely used 
to investigate how a caregiver perceives the patient’s conditions. Below we discuss instruments 
used for caregiver reported variables, as well as the use of EHR and claims to measure patient-
related variables. (Table 1 does not reflect the qualitative evaluation. The qualitative study as 
discussed in Section 3 and elsewhere above, will investigate the experiences of caregivers, 
patients and providers.)  
 
Variables describing the patients, caregivers and clinics include: a) characteristics of patients and 
of caregivers, including demographics, marital status, living arrangements, and general health 
and function; b) patient medical and utilization characteristics, including comorbid conditions, 
medication complexity, patient symptoms potentially related to diabetes or to medication use and 
changes, depression and history of substance uses and healthcare utilization in the prior year.  
Dementia specific characteristics of the patients include type of dementia, its severity, and 
function. The survey respondent is always the caregiver, although the questions may measure 
patient or caregiver status.  
 
We will also measure structure of care variables. These include patient use of consistent PCP 
care, home health services, and patient insurance. Clinic characteristics are size, support staff 
number, proportion of Medicare and Medicaid patients.  Several baseline variables relate to 
diabetes but because they are also outcome variables they will be described later.  As shown in 
table 1, many of these baseline and control variables are measured in the EHR and Epic 
administrative reports, or by claims. Some are measured by validated survey instruments, which 
are discussed briefly below.  
 
We will collect many process of care measures at baseline and at follow-up.  These include: a) 
provider use of Epic templates and tools; b) provider attendance at educational sessions; c) PM-
PCP communication; d) PM-caregiver contact frequency; e) referral for caregiver-support 
services; f) cognitive screening of diabetes patients over 75; g) change in diabetes medications; 
h) change in hypertensive medications; i) change in anticholinergic burden; j) change in 
medication complexity.  These variables are measured by EHR review and Epic administrative 
systems.   
 
Outcome variables include HbA1c level and blood pressure.  These variables will be measured 
at 0, 6, 12 and 24 months when available. Our main outcome is the proportion of patients 
achieving consensus HbA1c targets. BP will be measured by proportion of patients achieving 
consensus BP targets per our guideline.  Theses variables will be measured by the EHR.   
 
Utilization outcome variables are ED, hospital, SNF and ambulatory clinic utilization measured by 
EHR and by claims (for non-New York Langone Health utilization).  SNF days must be measured 
by claims; Epic reports have discharge destination but do not have SNF days. Utilization variables 
will be measured at 6, 12, 24 months; the baseline measures include a 20 month look back at 
utilization.  
 
Multiple caregiver reported outcomes about the caregiver and about the patients will also be 

 
 
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collected at 0, 6, 12, 24 months. General outcomes include: a) caregiver perception of care quality 
(our main caregiver-reported outcome), dyad care goals, preferences, and satisfaction; b) 
treatment burden; c) caregiver global health.  Dementia and diabetes specific outcomes include: 
a) patient dementia symptoms; b) caregiver diabetes stress.  
 
Below is a brief description of the instruments we will use, all of which have been studied and 
validated, although not always with caregivers.  
 
• 
Social Support MOS-5.  This survey instrument has been used to investigate social 
support for caregivers of dementia patients and is well studied.79, 80 It has 5 questions. 
 
• 
Global Health (Promis Scale v1.2):  This commonly used instrument from the Promis 
series of instruments83 assesses the general health of the caregiver and is reported 
by the caregivers. It has 10 questions. 
 
• 
Diabetes Caregiver Distress Scale:  This scale is adapted from the diabetes distress 
scale.84 We were unable to find a diabetes care distress or care burden scale that is 
directed at caregivers, even when checking literature for type 1 diabetes and children 
with diabetes.  We therefore will use this instrument for caregivers although it is usually 
given to patients.  It has 7 questions.  
 
• 
Mental Health and Substance Use: These 5 questions ask about caregiver history 
of mental health, including stress and depression, alcohol and illicit drug use. 
 
 
• 
Treatment Burden Questionnaire (TBQ): This instrument has been used in studies 
with patients but not with caregivers who are supervising or providing care for care-
patients (patients).  The form has 15 questions. In order to publish our findings, we are 
working with experts to conduct psychometric evaluation to validate the TBQ for use 
with caregivers.  
 
• 
Dementia Severity Rating Scale (DSRS): This is a caregiver questionnaire that asks 
about the patient’s dementia characteristics.87 It has been used in many studies, 
including studies by our group, and is well validated.  This scale includes questions 
related to the patient’s functional ability. 
 
• 
COVID Questionnaire: This instrument assesses the impact of COVID-19 pandemic 
and its associated mitigation efforts on study subjects. Specifically, it includes 
COVID-19 status, related symptoms, and the social, medical and functional impact of 
the pandemic on caregivers and care recipients. We will attempt to complete this 
instrument at least once (baseline or follow-up) with every caregiver/care recipient 
dyad.  
 
• 
Follow-up COVID Questionnaire: This survey will capture any changes that may 
have occurred since the first COVID survey and will be administered to any 
participant that has already completed an initial survey. 
 

 
 
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Most variables measured by EHR and claims are self-explanatory.  However, two other 
instruments will be used with EHR and claims.  
 
• 
Patient: Charlson Comorbidity Index:  This well-known modified index will be 
calculated from the EHR and/or claims.88 
 
• 
Patient: Anticholinergic Cognitive Burden Scale:  This is also a commonly used 
scale derived from chart review that has been used in the past by our group.89 
 
6. Risk and Benefit Assessment  
 
6.1 Risks 
 
No pharmacological intervention or medical procedures will be used in this study. Rather this 
study aims to develop and test the use of consensus decisional guidance for the medical 
management of DM in patients with ADRD. 
 
No survey or qualitative interview data will be gathered without patient and caregiver consent (or 
in some cases, patient assent). However, some questions may cause anxiety, embarrassment or 
be emotionally upsetting. The RA/RC will receive training in minimizing emotional impact or 
discomfort and remind subjects that they may discontinue participation at any time. Dr. Dickson 
is experienced in qualitative interviews and will also minimize emotional impact or discomfort. In 
the event of significant emotional upset, the mPIs will be notified and will intervene to address any 
concerns.  
 
Subject loss of confidentiality is another risk of clinical trials like the one proposed here and with 
this type of data collection. However, the computerized assisted telephone interview (CATI) and 
in some cases, in person, data collection method using a REDCap survey tool that we utilize is 
specifically designed to mitigate such loss as no data is collected with personal identifiers and 
contact names, addresses and telephone numbers, which are maintained in separate databases.  
 
 
6.2 Protection Against Risks 
 
All study personnel have completed training in Human Subjects Research and HIPPA standards 
and we have a strong record of quality assurance and maintained confidentiality from prior 
projects. NYU MCIT and DataCore, the data management experts who will manage the 
administrative data and the combined database have multiple data security elements in place 
(see below) and all personnel are trained in Human Subjects Research HIPPA standards, and 
data security. 
 
To further protect against risk to loss of subject confidentiality, all records will be coded with 
anonymous identifiers. Only de-identified data will be shared with the research team without a 
need to know identifying information. Documentation of consent will be encrypted and will not be 
known by the PM and clinical team. We will keep one separate and password protected and 
encrypted computer file that contains identifiable data that is necessary to contact subjects (phone 
numbers and U.S. mailing addresses). This file will be the only file that can link subject names, 

 
 
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addresses, and/or telephone numbers to the study unique codes, and is only accessible by the 
study Principal Investigators and Research Coordinator.  
 
Qualitative interviews with caregivers and providers/staff will be audio recorded should patients 
verbally consent. Audio recording is necessary for transcription and qualitative analysis of 
interviews. Audio tapes of subject interviews will be labeled with subject anonymous identifier 
(described above), only linked in a secure file accessed only by IRB approved study team. Audio 
tapes will be destroyed once transcriptions are complete, which will be stored in a HIPAA-
compliant NYU secure server.   
All other computer files containing data from this study (survey and interview files and files 
containing medical record and claims data) will be stripped of identifiable data, and subjects will 
only be differentiated by unique study codes. Data will be compiled from all of the subjects in the 
study and aggregated for analysis and publication. All identifying data will be eliminated from files 
before the statistician analyzes the data. All electronic data will be kept in password-protected 
databases and program files.  
 
Procedures for maintaining confidentiality will be reviewed quarterly with the research team to 
assure compliance. Audiotaped intervention sessions that will be used to ensure the quality of the 
intervention and judge treatment fidelity will be reviewed by Dr. Dickson and subsequently 
destroyed. A separate consent for audiotaping will be obtained. All study personnel will be trained 
in data confidentiality, Human Subjects Research and HIPPA compliance, as will the panel 
managers. Even though the panel managers are part of the clinical team and not the research 
team, they will interact with the research team and the patient/caregiver dyad and need to 
understand the context and relationship of the quality improvement program and the research 
evaluation. 
 
 
6.3 Potential Benefit to Subjects 
 
We anticipate that participants may receive benefit either from enhanced panel management or 
usual care and for all we anticipate some immediate benefit regardless of the arm into which they 
are randomized. All subjects will be recipients of care in clinics that have received guidelines for 
enhanced care and will be offered referral information for caregiver support services and other 
informational materials. Contact from an RA may be a break from what for some will be the 
loneliness of caregiving. We expect some improved caregiver knowledge, decreased sense of 
burden and improvement in mood for at least intervention subjects. Care recipients may benefit 
through improved health outcomes. They may also receive increased medical care quality through 
attention to previously unattended medical issues. Finally, both caregivers and care recipients 
may receive increased levels of community support through mobilized informal supports and 
through community agency assistance. This study poses minimal risk to subjects, since the study 
does not involve tests or treatments beyond that which they would normally receive as part of 
their normal care. Therefore, the potential benefits outlined above exceed the risks of participation 
in the study. 
 
For PCPs and staff, participation in interviews poses minimal risk. The opportunity to contribute 
to better understanding about health service delivery may provide some personal satisfaction and 
benefit. Information gathered from these interviews may lead to an improved work environment 
providing direct benefit to participants and colleagues. The interview may also be a place where 

 
 
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PCPs and staff feel free to voice concerns or objections to clinical approaches and this may 
present a safe space in which to do this. 
 
7. 
Data Analysis  
 
We will begin all analyses with descriptive summary statistics and graphical displays of all 
variables.  Continuous variables will be summarized with means, medians, standard deviation 
and interquartile range; categorical variables will be summarized with frequencies. We will assess 
the balance by treatment assignment of patients in the INT and CON clinics with respect to 
demographic and clinical characteristics (e.g., age, gender, Charlson Index, socioeconomic 
status, baseline TBQ, etc.) using standard tests (t-tests, Wilcoxon rank-sum tests, and χ2 tests 
as appropriate).  Any factors that appear to be unbalanced by treatment assignment will be 
considered as adjustment factors in the primary analyses.  All hypothesis testing will be two-sided 
and conducted using a significance level of 0.05. 
 
The primary outcome of ‘on target’ HbA1C values will be measured for each patient as a binary 
indicator.  The primary analysis will use a generalized linear mixed model approach, with a logit 
link, for the probability of being ‘on target.’ The treatment group (CON vs INT) will be the primary 
fixed effect of interest; we will also include the practice as a random effect to accommodate 
clustering of patients within clinics.  We will also explore non-parametric methods such as quantile 
regression or other rank-based approaches.  As noted above, randomization should obviate the 
need for any additional covariate adjustment, but we will explore whether adjustment for clinic-
level characteristics (e.g., clinic size) and provider-level characteristics (e.g., provider 
demographics and panel size) is necessary.  We will use standard assessments of goodness-of-
fit, including residual plots, to evaluate the models. Finally, in addition to reporting the treatment 
difference in terms of the odds ratio from the logistic regression, we will report absolute risk 
difference as well.  
 
The secondary outcome of TBQ score, transformed into a binary outcome using an appropriate 
threshold (e.g., the median) will also be assessed using generalized logistic mixed models as 
described above; the treatment group (CON vs INT) will be the primary fixed effect of interest, 
with practice included as a random effect. As with the primary outcome, we will assess the need 
for adjustment using demographic or clinical characteristics, and will evaluate goodness-of-fit 
using standard approaches. We will also evaluate the TBQ as a continuous score using a linear 
mixed model. We will assess the validity of the linearity assumption, and seek a suitable 
transformation of the TBQ score if it appears to be violated.  The statistical power for this analysis 
will be greater than that for the binary version of the outcome because of the additional information 
provided when using the scale in its original form. 
Health care utilization outcomes will be analyzed using similar generalized linear mixed models; 
indicators of use will employ the logistic link function, and counts of days in various facility types 
will employ Poisson regression with the log link function. Treatment burden (using the Treatment 
Burden Scale) and dementia symptoms/cognitive function (using the DSRS) will also be evaluated 
as important secondary outcomes.  We will have repeated assessments of these items at 6, 12, 
and 24 months, and will apply longitudinal mixed effects models to evaluate the trajectories and 
assess whether they differ by treatment group.  Specifically, we will model time using indicator 
variables, and include interaction terms between time indicators and treatment group (CON vs 
INT); the statistical significance of the coefficients of the interaction terms will indicate whether 

 
 
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the trajectories in the outcomes over time differ by treatment group.  We will also explore more 
parsimonious ways of modeling time, for example as a linear or polynomial effect.  We will choose 
link functions that address ordinal outcomes, such as the log link for ordered categorical 
outcomes, in the context of proportional odds or multinomial logistic regression. 
All clinical trials are at risk for missing data.  Although we will attempt to retain as high a fraction 
of participants as possible, we acknowledge that some attrition is likely, leading to missing 
outcome values. The generalized linear mixed models proposed for the primary and secondary 
analyses incorporate an assumption of data that are missing at random (MAR), meaning that the 
likelihood of a value being missing depends on observable characteristics (e.g., sex, age, baseline 
clinical status, etc).  In sensitivity analyses, we will assess the impact of different assumptions 
about the missing data mechanism, and will determine the robustness of trial results to these 
different assumptions. These sensitivity analyses will take the several forms. The first extreme 
value imputation, in which we assume that all members of one intervention group experience 
either a success or a failure (e.g., HbA1 on or off target) while the opposite occurs in the other 
intervention group.  We will also apply a more formalized assessment using the Index of 
Sensitivity to Nonignorability, developed by Dr. Troxel and colleagues, which provides an 
objective assessment of the robustness of trial results to different assumptions about the missing 
data mechanism. 
 
8. 
Data and Safety Monitoring 
 
This study will be monitored by 1) the multiple Principle Investigators (mPIs) and 2) the Data 
Safety Monitoring Board (DSMB). 
 
8.1 
mPI responsibilities: 
• 
Provide oversight of daily operations and on-site monitoring of data accuracy and 
quality, adherence to the research design, methods and procedures outlined in the 
protocol 
• 
Monitor AE and SAE and follow-protocols for those events outlined in Section 10, 
including reporting these events to the IRB and DSMB. 
 
8.2 
DSMB responsibilities:  
• 
Review the research protocol, informed consent documents and plans for data safety 
and monitoring;  
• 
Advise the NIA on the readiness of the study staff to initiate recruitment; 
• 
Evaluate the progress of the trial, including periodic assessments of data quality and 
timeliness, recruitment, accrual and retention, participant risk versus benefit, 
performance of the trial sites, and other factors that can affect study outcome; 
• 
Consider factors external to the study when relevant information becomes available, 
such as scientific or therapeutic developments that may have an impact on the safety 
of the participants, and outcomes or ethics of the trial; 
• 
Review study performance, make recommendations and assist in the resolution of 
problems reported by the mPrincipal Investigators; 
• 
Protect the safety of the study participants; 
• 
Report to NIA on the safety and progress of the trial;  

 
 
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• 
Make recommendations to the NIA and to the Multiple Principal Investigators 
concerning continuation, termination or other modifications of the trial based on the 
observed beneficial or adverse effects of the treatment under study; 
• 
Review interim analyses to assess study recruitment and outcome milestones which 
are clearly defined in advance of data analysis and have the approval of the DSMB; 
• 
Ensure the confidentiality of the study data and the results of monitoring; and,  
• 
Assist the NIA by commenting on any problems with study conduct, enrollment, 
sample size and/or data collection. 
 
There will also be a data monitoring committee consisting of the statistician, Dr. Troxel, a 
DataCore representative, and Co-I Dr. Horwitz.  This committee will meet twice yearly during the 
first three years of the trial to review the survey data and any data to be presented to the DSMB.  
In the last year, when utilization information from the EHR and claims are becoming available, 
this group will meet every two months. 
 
 
9. 
Ethics/Protection of Human Subjects 
 
9.1 
Ethical Standards 
 
The investigator will ensure that this study is conducted in full conformity with Regulations for the 
Protection of Human Subjects of Research codified in 45 CFR Part 46. 
9.2 
Institutional Review Board 
 
The protocol, informed consent form(s), recruitment materials, and all participant materials will be 
submitted to the IRB for review and approval. Approval of both the protocol and the consent form 
must be obtained before any participant is enrolled. Any amendment to the protocol will require 
review and approval by the IRB before the changes are implemented to the study. All changes to 
the consent form will be IRB approved; a determination will be made regarding whether previously 
consented participants need to be re-consented. 
 
10.  
Data Handling and Record Keeping  
 
10.1 
Data Storage and Management Responsibilities    
 
All study personnel will be trained in data confidentiality, Human Subjects Research and HIPPA 
compliance. Data will be stored using HIPAA-compliant REDCap electronic database hosted at 
NYU Langone Health. To protect against risk to loss of subject confidentiality, all records exported 
from REDCap will be coded with anonymous identifiers. Only de-identified data will be shared 
with the research team without a need to know identifying information. Documentation of consent 
will be encrypted and will not be known by the PM and clinical team. Data will be compiled from 
all of the subjects in the study and aggregated for analysis and publication. All identifying data will 
be eliminated from files before the statistician analyzes the data. All electronic data will be kept in 
password-protected databases and program files. Procedures for maintaining confidentiality will 
be reviewed quarterly with the research team to assure compliance. Audiotaped intervention 
sessions that will be used to ensure the quality of the intervention and judge treatment fidelity will 
be reviewed by Dr. Dickson and subsequently destroyed.  

 
 
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NYULH has privacy provisions that are strictly adhered to, including mandatory Security 
Awareness and HIPAA training of all employees from custodial staff to Administration; mandatory 
training for all clinical trials staff, which includes Protection of Human Subjects training. All staff 
must sign a confidentiality agreement upon employment, and NYULH meets or exceeds all HIPAA 
requirements. These requirements pertain both to our study personnel and to any MCIT or data 
management personnel who come into contact with our databases, which are stored on NYULH 
IT secure servers. 
 
All resources, including web, database, and file servers, are protected from outside intrusion by 
a firewall that blocks unauthorized access to the LAN by any unauthorized user originating from 
the Internet by using a sophisticated combination of secure application proxies and packet 
filtering. Internal network security is maintained through Active Directory authentication. Intrusion 
detection software is employed to scan for attempted break-ins. User IDs and passwords are 
assigned and controlled as per SOP “SD004: Study Security”, and users are required by the 
system to change their passwords regularly. Access to clinical trials or other sensitive data is 
strictly limited and is granted only by the Director of the Technical Support Unit. 
 
10.2 Study Record Retention 
 
In compliance with NIH policy, study records will be retained for a minimum of 3 years after 
study completion. 
 
10.3 Publication and Data Sharing Policy 
 
This study will comply with the NIH Public Access Policy, which ensures that the public has access 
to the published results of NIH funded research. It requires scientists to submit final peer-reviewed 
journal manuscripts that arise from NIH funds to the digital archive PubMed Central upon 
acceptance for publication. 
11. Investigator’s Qualifications and Experience 
 
Our multidisciplinary team is expert in health system design science. Dr. Blaum, mPI, an expert in 
multiple chronic conditions (MCC), DM in older adults, and practice change, has led both VA and 
Medicare practice change projects. Dr. Chodosh, mPI, an expert in cognitive assessment, CG 
research, and care delivery model implementation for cognitively impaired patients, is the 
Outreach and Recruitment Core Leader for the NYU Alzheimer’s Center, is co-PI on a large NY 
State grant to provide supportive services for dementia CGs. His ADRD research experience is 
invaluable as we navigate systems and human subject issues. Dr. Zabar, Division Director of 
General Internal Medicine and an expert on physician training and interdisciplinary practice, will 
assist with practice change and provider interface with panel managers (PMs). Dr. Horowitz is 
Director of the Healthcare Delivery Science Division in the Department of Population Health. A 
former Beeson Scholar, she is PI of the NYU CMMI Primary Care Transformation Project and has 
worked on practice change interventions, and electronic health records (EHR) and claims data 
related to the NYU healthcare centers. She has expertise in behavioral economics and practice 
change. Dr. Dickson, an expert on qualitative research methodology, has conducted self-
management interventions in ethnically diverse patients, including those with low health literacy. 

 
 
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Ira Goldberg, a prominent lipid researcher, is Division Director of Endocrinology. Although a basic 
scientist, he has a particular interest in diabetes management in complex populations. Dr. Simon 
Jones is a prominent statistician with substantial experience in public health, delivery system 
redesign, and implementation research. Our consultants have critical expertise. Dr. Borson is well 
known for her research in dementia screening and CG burden, Dr. Boustani is known for his work 
in dementia care and screening, and Dr. Williamson from Wake Forest was Co-PI of ACCORD-
MIND. 
 
12. 
Study Finances  
 
12.1 
Funding Source 
 
This study is financed through a grant from the National Institute on Aging (NIA).  
 
12.2 
Costs to Subjects 
 
There are no costs for participation. 
 
12.3 
Payment for Participation 
 
Caregivers will be provided a $20 gift card upon completion of each of the 4 surveys (baseline, 6 
months, 12 months and 24 months) and an additional $20 gift card should they complete a 
qualitative interview.  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Page 33 
 
 
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13. 
References 
 
1. 
CDC. 2014 National Diabetes Statistics Report. Centers for Disease Control 
https://www.cdc.gov/diabetes/data/statistics/2014statisticsreport.html. Accessed January 4, 2017. 
2. 
Bodenheimer T, Lorig K, Holman H, Grumbach K. Patient self-management of chronic disease in primary 
care. JAMA. 2002;288(19):2469-2475. 
3. 
Feil DG, Zhu CW, Sultzer DL. The relationship between cognitive impairment and diabetes self- 
management in a population-based community sample of older adults with Type 2 diabetes. Journal of 
Behavioral Medicine. 2012;35(2):190-199. doi:10.1007/s10865-011-9344-6. 
4. 
Feil DG, Pearman A, Victor T, et al. The role of cognitive impairment and caregiver support in diabetes 
management of older outpatients. Int J Psychiatry Med. 2009;39(2):199-214. 
5. 
Feil DG, Rajan M, Soroka O, Tseng C-L, Miller DR, Pogach LM. Risk of hypoglycemia in older veterans 
with dementia and cognitive impairment: implications for practice and policy. J Am Geriatr Soc. 
2011;59(12):2263-2272. doi:10.1111/j.1532-5415.2011.03726.x. 
6. 
Feil DG, Pogach LM. Cognitive impairment is a major risk factor for serious hypoglycaemia; public health 
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