Family Health History in Diverse Care Settings
Phase: NA
Conditions: Diabetes, Heart Disease, Cancer
Sponsor: Duke University

Title:  Coordinating Center for Implementation, Adoption, and Utility of 
Family History in Diverse Care Settings   
PI:  Geoffrey Ginsburg, MD, PhD        IRB # Pro00043372     NCT01956773
Research 
Summary 
Protocol ID Pro00043372 
1/20/2017 
1
The Clinical Genomic Studies Unit (CGSU) at the Institute for Genome Sciences and 
Policy (IGSP) will serve as the Clinical Coordinating Center and Data Coordinating 
Center for this study. 
The Coordinating Center (CC) responsibilities include study design, project 
management, data acquisition and storage, QA, statistical analysis, site coordination 
and training, as well as thought leadership. The policies and procedures of Duke Office 
of Clinical Research (DOCR) and the CGSU serve to assure appropriate standards are 
met, including federal regulations of privacy and security and also to assure that 
analyses are validated prior to publication. 
The main responsibilities of the Coordinating Center will be: 1) Protocol development; 2) 
Dissemination of  DUHS IRB approved protocol and all related documents (e. g. 
consent form templates, recruitment materials, surveys)  to participating sites; 3) 
Conducting site visits for site assessment and personnel training; 4) Providing a central 
study coordinator to facilitate subject enrollment (creating subjects accounts for the 
online study access); 5) Data management and analysis; 6) Overall study monitoring to 
ensure sites compliance with regulatory requirements.  
Each site is responsible for the selection of their research subjects recruitment. There 
are two populations of subjects – providers and patients.  Consenting providers is the 
responsibility of the enrolling sites. Coordination of patients online consenting is the 
responsibility of the Coordinating Center.  The Coordinating Center will confirm that all 
enrolled subjects provided informed consent. The CC does not have a role in assessing 
subject’s capacity to give legally informed consent. The protocol does not allow the 
inclusion of subjects unable to provide informed consent. 
Purpose of the Study – The purpose of this study is to address the key question of 
whether and how family health history (FHH) is adopted as a tool to more efficiently 
manage patients at risk for breast, colon, ovarian, and hereditary cancer syndromes as 
well as thrombophilia and coronary heart disease (CHD) and to provide evidence 
supporting clinical utility -- improved health behaviors in patients and physician 
screening recommendations.  Five health care delivery organizations will participate in 
this demonstration project: Duke University, the Medical College of Wisconsin, the Air 
Force, Essentia Health, and the University of North Texas Health Science Center. The 
study will take place in ‘real world’ clinical, socio-cultural, and demographically diverse 
(rural, underserved, academic, family medicine) clinics (n=34) in 5 states (CA, MN, NC, 
WI, TX) that include genomic medicine ‘early adopter’ and ‘naïve’ sites, as well as those 
that are EMR-enabled and others that are not, and will use a cluster randomized 
controlled pragmatic hybrid type III implementation-effectiveness observational study 
design. We anticipate enrolling 7000 English or Spanish speaking adult participants 
(at a minimum) over a 3-year period; to reach this goal we need to enroll ~300 
participants from each intervention clinic (assuming 10 of the 34 clinics will be dedicated 
controls). Specifically we will use Healthcare Effectiveness Data and Information Set 
(HEDIS) measures as intermediate clinical effectiveness measures for CHD and the 
selected cancers as well as survey/formative data and electronic medical record (EMR) 

Title:  Coordinating Center for Implementation, Adoption, 
and Utility of Family History in Diverse Care Settings  
PI:  Geoffrey Ginsburg, MD, PhD        IRB # Pro00043372  
Research 
Summary 
Protocol ID Pro00043372 
1/20/2017 
2
data as outcomes measures. The research model is purposely designed to mimic 
clinical delivery as an important step toward widespread implementation and 
sustainability. In addition we will use a cost-effectiveness analysis to compare usual 
care to the FHH guided preventive health model. The completion of this project will 
result in an optimal strategy for integration of FHH data collection and clinical 
decision support (CDS) tools into an EMR and demonstrate the utility of the FHH 
intervention among diverse primary care patients, their settings, their providers, 
and the health systems that deliver their care. 
Specific Aim 1:  To optimize the collection of patient entered FHH in diverse clinical 
environments for coronary heart disease, thrombosis, and selected cancers 
Specific Aim 2: To export FHH data to an open clinical decision support (open CDS) 
platform and return CDS results to providers and patients (and to EMRs where 
relevant).  To explore the integration of genetic risk and FHH data at selected sites. 
Specific Aim 3: To assess the clinical and personal utility of FHH using a pragmatic 
observational study design to assess reach, adoption, integrity, exposure, and 
sustainability, and to capture, analyze, and report effectiveness outcomes at each 
stakeholder level: patient, provider, and clinic/system.  
Specific Aim 4:  To take a leadership role in the dissemination of guidelines for a FHH 
intervention across in diverse practice settings. 
Background & Significance – In 2002 the CDC launched the Family History Public 
Health Initiative, founded upon the principle that family history is an underutilized but 
effective tool for risk stratification. Among the stated goals were to develop tools to 
enhance family health history (FHH) collection and to evaluate whether FHH-based 
strategies work in practice. Because primary care providers account for the majority of 
care encounters in the US they are a natural choice as partners to study the 
implementation of FHH into care delivery and medical decision-making. 
FHH assessments have clearly been shown to identify persons at higher risk for 
common chronic disease, enabling preemptive and preventive steps, including lifestyle 
changes, health screenings, testing, and early treatment as appropriate(1).  More 
recently Qureshi has shown prospectively the potential to identify presymptomatic 
individuals at elevated risk for common, chronic diseases and activate them to modify 
their risks(2) - an enormous opportunity to improve public health by implementing risk-
based screening and prevention strategies. Yet, although FHH is a standard component 
of the medical interview and professional guidelines recommend screening strategies 
based upon FHH, its widespread adoption is hindered by three major barriers: (1) 
standard collection methods; (2) health care provider access to FHH information; and 
(3) clinical guidance for interpretation and use of FHH.

Title:  Coordinating Center for Implementation, Adoption, 
and Utility of Family History in Diverse Care Settings  
PI:  Geoffrey Ginsburg, MD, PhD        IRB # Pro00043372  
Research 
Summary 
 
Protocol ID Pro00043372 
1/20/2017 
3
The Rationale for Using FHH Tools.  FHH is underutilized by practitioners and therefore 
represents a significant missed opportunity for risk stratification(3): a systematic review 
found a 46-78% improvement in data recording by FHH tools as compared with the use 
of standard practice(4). FHH tools show excellent concordance with structured pedigree 
interviews and the gold standard three-generation pedigree(5).  In a study of 1124 
primary care patients not only was medical record documentation insufficient in two-
thirds of charts for FHH assessment of six common diseases, but also 23% had no 
evidence of risk in their medical record yet had a moderate or strong risk for at least one 
disease as assessed by the Family Healthware™ tool(6).  
FHH collection, analysis, and risk stratification can be performed efficiently and 
effectively using a variety of software platforms that have the potential to overcome the 
barriers created by a reliance on physicians to gather, record, and analyze FHH. 
Implementation of automated FHH linked to clinical decision support (CDS) is feasible in 
the community setting as shown by use of HughesRiskApps in over 25,000 individuals, 
leading to referral of 3.6% of patients for breast and ovarian cancer genetic counseling 
and consideration of genetic testing(7).  In our own experience using the MeTree™ FHH 
tool, the mean completion time by 1320 primary care patients was 23 minutes, and 35% 
were classified as having strong or moderate risk for at least one of five common 
diseases. It is absolutely clear that to elicit information for a comprehensive FHH is a 
significant time commitment making it clear that patients, not physicians, need to serve 
as the main locus for data input.  
 
Electronic Medical Records and FHH. The American Health Information Community 
(AHIC) Personalized Health Care (PHC) Workgroup, part of the U.S. Department of 
Health and Human Services (HHS) Personalized Health Care Initiative, has put 
significant effort into developing standards for incorporating FHH into the electronic 
medical record (EMR). However, there are important roadblocks to realizing the full 
potential of FHH: for example, for the ~150 EMR vendors, FHH information is primarily 
recorded as free text and no EMRs have graphical pedigree drawing functions. In 
addition, among the few structured data sets, none are compliant with the AHIC core 
data set standard(8).  Highlighting the fact that EMRs do not provide a solution to FHH 
capture, in query of data from the EPIC EMR at Medical College of Wisconsin in ~ 
721,000 patient encounters 85% lacked a FHH, and only 1% of records had recorded 
three generation data (Dimmock D, personal communication). Stand alone software 
packages may provide the needed functionalities such as pedigree-drawing, and 
algorithms but none of these are interoperable with EMRs and EMR vendors avoid 
linking one-off programs to their own packages. A key point is that CDS (see below) 
capabilities remain limited in most EMRs and are virtually non-existent for FHH.  In the 
current proposal we will use a modular approach whereby FHH collection is centralized, 
key data elements are exported to a program that applies specific algorithms, and the 
data are then returned to the EMR where CDS strategies can be applied(8).  
Clinical Decision Support. CDS is a critical prerequisite to realizing the full potential of 
the EMR to facilitate evidence-based medicine(9). HHS, the CDC, and the Secretary’s 
Advisory Committee on Genetics, Health, and Society have designated Health 
Information Technology and CDS as priorities for achieving the goals of personalized 

Title:  Coordinating Center for Implementation, Adoption, 
and Utility of Family History in Diverse Care Settings  
PI:  Geoffrey Ginsburg, MD, PhD        IRB # Pro00043372  
Research 
Summary 
 
Protocol ID Pro00043372 
1/20/2017 
4
medicine(10-12).  The goal of CDS is “to provide the right information, to the right person, 
in the right format, through the right channel, at the right point in workflow to improve 
health and health care decisions and outcomes” and a roadmap has been developed to 
achieve this goal(11). A systematic review found that adoption of CDS significantly 
improved clinical practice with a 94% success rate when CDS provided computer-
generated recommendations at the point of decision-making and was integrated into the 
clinical workflow(13).   This proposal will develop an open source risk-stratified CDS 
system that can be accessed by diverse EMRs.  We will adopt the standards for FHH to 
exchange, integrate, manage, and share key data elements that were developed and 
approved by HL-7 (Health Level 7)(14).   
 
Clinical utility of FHH. Qureshi et al.,(2) recently implemented systematic collection of 
FHH for cardiovascular risk assessment in 24 family practices in the UK using a 
pragmatic cluster randomized controlled trial design, and demonstrated a highly 
significant (40%) increase in identification of individuals at high risk. Surprisingly, given 
that the study was not powered to detect a difference in health behaviors, there was 
also a highly significant increase in successful smoking reduction or cessation in the 
intervention group compared to controls. This was the first rigorously designed 
prospective study to show that systematic collection and use of FHH in a primary care 
setting can improve risk stratification and health behaviors for CHD and provides an 
important proof of concept for the work in this proposal. However, in general, the gold 
standard of a randomized clinical trial (RCT) has not been achieved for FHH. 
Challenges faced by RCTs including feasibility, expense, and applicability to ‘real world’ 
situations, 
make 
comparative 
effectiveness 
research 
(CER) 
and 
pragmatic 
implementation trials an appealing solution. CER broadens the scope of methodologies 
to include not only RCTs but also decision analysis and observational studies(15).   
Clinical utility of an FHH intervention can be established using measurable outcomes 
that include clinician and patient behaviors, as well as mechanisms that facilitate these 
behaviors(16). Provider behaviors include the use of optimal decision-making, counseling 
the patient, and direct the use of medical services. Mechanisms that promote these 
behaviors include perceived value of FHH and risk, competencies to collect and discuss 
FHH, and education. Patient behaviors include increased or reduced screening and use 
of preventative services, and improved lifestyle behaviors (e.g., diet, exercise, and 
smoking cessation). Mechanisms such as patients’ perceived value of FHH, their ability 
to obtain the information, family communication, and especially patients’ risk perception 
affect patient behaviors. This approach was highlighted in two studies at the NIH State-
of-the-Science Conference - one showed improvement in mammography screening, 
breast self-examination and clinical breast examination with systematic collection of 
FHH in a primary care/general population setting(17).  The other, the Family History 
Impact Trial(18) coupled one-time tailored messages to computerized FHH in 3786 
healthy primary care patients and assessed self-reported behavior change at 6 months. 
Those in the intervention group showed increased fruit and vegetable consumption and 
improved physical activity(19).  Use of a touch-screen kiosk in a comprehensive cancer 
clinic was associated with increases in cancer screening and prevention behaviors and 
communication with family members(20).  

Title:  Coordinating Center for Implementation, Adoption, 
and Utility of Family History in Diverse Care Settings  
PI:  Geoffrey Ginsburg, MD, PhD        IRB # Pro00043372  
Research 
Summary 
 
Protocol ID Pro00043372 
1/20/2017 
5
 
Design & Procedures – This study will: 1) utilize a software platform entitled MeTree, 
which electronically captures participant-entered FHH and links to a web-based risk 
stratification and CDS system for prevention of CHD, breast cancer, colon cancer, and 
hereditary cancer syndromes.  The risk stratification and CDS system pull together 
established, standard of care guidelines and validated risk calculators in one place to 
facilitate provider decision making.  The output (pedigrees and reports with evidence-
based risk stratified prevention recommendations) will be integrated into the EMR, and 
capture patient behaviors and attitude changes through a series of web-based computer 
surveys; and 2) provide just-in time education embedded within the CDS output to 
activate patients and providers and improve awareness of and adherence to FHH risk-
stratification and risk-stratified prevention plans. 
Multiple clinics at each participating institution will be recruited to participate, but 
providers will individually be able to participate at their own discretion.  One comparator 
clinic will be randomly assigned as a “control” to be used to assess any changes in the 
standard clinical care between the participating clinics and the control. 
 
This study will also include the administration of an Organizational Readiness to 
Change (ORCA) survey to identified personnel at each participating clinic, and followed 
by qualitative interviews for key personnel (Key informant interviews) identified at each 
participating clinic. . 
 
ORCA survey design:  an Organizational Readiness to Change Assessment (ORCA) 
will be administered as a survey by the Duke coordinating center personnel through a 
web-based electronic data capture program, with personnel in identified roles (provider, 
nurse, administrator) within participating clinics from each of the five health systems.  
Survey completion will occur prior to the implementation of the MeTree family health 
history tool, and will provide information about the organization’s climate and culture 
about integrating and implementing change.   
 
Key informant interview design:  Individual semi-structured qualitative interviews will be 
conducted over the telephone with key informants from each of the five health systems. 
Interviews will occur prior to and post-implementation. Pre-implementation interviews 
will provide information about barriers to implementation of MeTree, which will allow us 
to develop a tailored implementation plan at each site. Post-implementation interviews 
will provide information about the success and outcomes of the implementation of 
MeTree. Interviews will be conducted by telephone by Drs. Voils and Sperber of Duke 
University Medical Center, who are experienced interviewers with qualitative research 
expertise. The conversations will be audiorecorded and transcribed, and data will be 
analyzed using content analysis. 
 
Providers will be consented in person by local staff at each participating Institution 
during the pre-implementation phase (first six months of the study) and will receive FHH 
and education about the Genomic Medicine Model. After providers are consented, they 
will undergo formative evaluation to assess the needs of their clinic for optimal 

Title:  Coordinating Center for Implementation, Adoption, 
and Utility of Family History in Diverse Care Settings  
PI:  Geoffrey Ginsburg, MD, PhD        IRB # Pro00043372  
Research 
Summary 
 
Protocol ID Pro00043372 
1/20/2017 
6
integration of the system and complete a web-based survey at 6 months to assess their 
response to the intervention and to inform adaptations to improve efficiency and 
efficacy.    
 
ORCA survey participants will be invited based on their role of provider, nurse, and 
administrator in participating clinics within the five health systems. The number of 
survey respondents will depend on clinic composition and degree of heterogeneity in 
clinic organization.  We anticipate inviting 365 providers and roughly an equal number of 
nurses and administrators – for approximately 450 respondents. 
 
Key informants will be selected based on their role at each clinic. To obtain necessary 
information, we will sample physicians, nurses, and schedulers. The number of key 
informants to be interviewed will depend on clinic composition and degree of 
heterogeneity in clinic organization. For example, if two clinics within a health system 
are highly similar in organization and planned implementation procedures, then we may 
interview only one scheduler to represent those two clinics. The number of key 
informants should be sufficiently large to capture varying organizational structures, 
viewpoints and experiences with MeTree implementation, yet small enough so as to be 
feasible. We anticipate interviewing 40-80 key informants. 
 
Participants will be enrolled 
through a central Duke 
research 
coordinator. 
Electronic consent, survey 
administration, 
FHH 
education and MeTree™ 
access will be web-based.  
They will have access to 
assistance for questions,  
but will view all educational 
resources 
electronically 
and collect and enter their 
own FHH from a computer, 
mobile 
device, 
or 
a 
dedicated clinic kiosk. After 
receipt 
of 
CDS 
output 
(pedigree, 
tabular 
FHH, 
and 
provider 
report 
for 
providers and pedigree and 
patient report for patients), 
the 
clinical 
encounter 
proceeds 
as 
usual. 
Participants may receive 
reports through a personal 
health 
record, 
patient 

Title:  Coordinating Center for Implementation, Adoption, 
and Utility of Family History in Diverse Care Settings  
PI:  Geoffrey Ginsburg, MD, PhD        IRB # Pro00043372  
Research 
Summary 
 
Protocol ID Pro00043372 
1/20/2017 
7
portal, email, or clinic printer, depending on the optimized process for each individual 
clinic setting.  
 
Once enrolled, each participant will be provided an account to the electronic data 
capture system, through which the participant will first sign the electronic consent form 
As of 04/08/2016 the study team has implemented and will continue to follow 
“Procedure for Updating Consent Documents.IT.SOP” located in the Full Protocol of the 
eIRB. , and then access the computer survey program and the MeTree family health 
history collection tool.  For this process, they will electronically be provided education 
about how and what to collect for FHH; along with materials including brochures and a 
worksheet. In addition, they will be educated about the electronic surveys, electronic 
consent process, benefits and risks of study participation, how to use MeTree (the FHH 
collection tool), how to receive their CDS output, and who to talk to about questions. 
Each consented participant will then complete the baseline survey prior to the 
scheduled primary care provider visit.  The baseline survey is re-administered with a 
request to the participant via email at 3 and 12 months to capture changes in health 
related activities, activation and risk perceptions. Patients or providers can 
communicate their desire to discontinue participation at any time to the study 
coordinator or the PI (figure 1). 
 
Standard health behavior surveys (SF12 and PAM) will be used to collect data covering 
diet, exercise, knowledge, screening practices, activation, attitudes and perception of 
risk for cardiovascular disease and the study cancers, and family health history. Each 
subject will be assigned a Unique Study ID and only trained research staff will have 
access to the list of IDs and patient names, for the purpose of tracking surveys and 
collecting medical record data. 
 
Resulting outcomes data, including all referrals, diagnoses, laboratory and genetic test 
results, medical procedures, office and ER visits, hospitalizations and medications that 
occur will be abstracted from patient medical record files prior to patient enrollment and 
throughout the study period  by the participating clinics after patient participation has 
been concluded at each site and provided to the Duke statistical analysis team with only 
the patient’s unique ID number. 
 
Selection of Subjects –  
Population:  Study subjects will be comprised of providers and patients at the diverse 
clinics within in each of the 5 organizations (Duke University, Medical College of 
Wisconsin, Essentia Health, University of North Texas Health Science Center, and the 
Air Force).  
 
Providers: all providers in the participating clinics will be selected to be included in the 
study. We anticipate 100% participation, for an expected enrollment of 365 providers. 
 
ORCA survey participants will be providers, nurses, and administrators at participating 
clinics at each institution which are involved in MeTree implementation. 

Title:  Coordinating Center for Implementation, Adoption, 
and Utility of Family History in Diverse Care Settings  
PI:  Geoffrey Ginsburg, MD, PhD        IRB # Pro00043372  
Research 
Summary 
 
Protocol ID Pro00043372 
1/20/2017 
8
 
Key informants will be providers, nurses, and schedulers at each participating clinic 
which is involved in MeTree implementation.   
 
Patients: All adult English or Spanish speaking patients scheduled for non-acute visits 
within 2 weeks will be invited to enroll when they schedule an appointment with their 
physician. Since this proposal focuses upon prevention and not disease management 
strategies, those with a study disease (breast, or colon cancer, hereditary cancer 
syndromes, or CHD) will not be excluded from enrollment but will be excluded from 
analyses relevant to their disease. We anticipate enrolling 7000 participants at a 
minimum (to achieve significance for effectiveness measures), but as an observational 
study will continue to enroll as many as are interested in order to maximize our ability to 
assess differences across settings, populations, and sociodemographic factors. To 
reach this goal we need to enroll ~300 participants from each intervention clinic 
(assumes 10 of the 34 clinics will be dedicated controls). Assuming 20% enrollment 
(from MeTree™ pilot -see preliminary data), we anticipate being able to enroll at least 
9,100 participants.  
 
All documents (consent forms, educational brochures, surveys, etc) will be translated as 
appropriate to Spanish-language version.  The MeTree software program user interface 
will also be translated into Spanish with a choice for the participant to have it displayed 
in English or Spanish. 
 
Subject Recruitment and Compensation –  
Provider recruitment will involve invitations to providers through telephone, letter and 
email communication from the study PI and/or his designee to invite participation in 
qualitative research regarding the integration of family health history, risk stratification 
and clinical decision support for their patients. 
 
ORCA Survey participant recruitment will involve the collection of appropriate personnel 
at each participating clinic from each institution. Potential survey respondents will 
receive a recruitment email (see attached recruitment email) describing the study, 
purpose of the survey, risks and benefits and other elements of informed consent, and a 
link to the web-based electronic data capture program that hosts the ORCA survey.  
 
Key informant recruitment will involve the collection of appropriate key informants from 
each site champion. Potential key informants will receive by e-mail a recruitment letter 
(see attached recruitment letter) describing the study and purpose of the interviews. 
When key informants respond to the invitation letter and state that they want to 
participate, the Duke scheduling coordinator will schedule a time for the interview and 
email the informed consent document (see attached email consent document) with the 
time/date for the interview. 
 
Recruitment flow for ORCA survey participants and Key informants will be as follows: 
Week one: Initial invitations to potential ORCA survey participants are sent 

Title:  Coordinating Center for Implementation, Adoption, 
and Utility of Family History in Diverse Care Settings  
PI:  Geoffrey Ginsburg, MD, PhD        IRB # Pro00043372  
Research 
Summary 
 
Protocol ID Pro00043372 
1/20/2017 
9
Week two: Reminding invitations to potential ORCA survey participants are sent  
Week three: Initial invitations for qualitative interviews to potential Key informants are 
sent 
Week four: Reminding invitations or follow up phone calls for qualitative interviews to 
potential Key informants are initiated to those who have not responded.  
 
Patient recruitment will be initiated with requests to participate mailed when a well visit 
appointment is made or a reminder sent from the scheduling service at each 
intervention study site. Each invitation will include all the elements of informed consent, 
including a description of the study, its risks and benefits, further information about the 
surveys and description of the electronic consent process. Those who are interested will 
contact the central Duke study coordinator who may briefly review the study again.  If 
the patient is interested, the Duke study coordinator will provide the participant with a 
web-based computer survey program account where they will complete the enrollment 
and consent process.  
 
If the invited patients do not respond within the expected time window prior to their 
scheduled appointment the local site coordinators may follow up with a phone call to 
provide additional information about the study and to encourage their participation. If 
during this phone call patients express interest in enrolling the site coordinator will 
advise them to call Duke central office directly or will offer to contact Duke on their 
behalf. If latter, local site coordinators will collect/verify the following information and will 
submit in a secure email to support.familyhistory@duke.edu: 
 
a. name (first, middle if any, last) 
b. email address (this will be the participants login, and to which all emails 
will be sent) 
c. did they set up this email specifically to participate in this study? 
d. institution 
e. verification that the participant is 18 years of age or older 
f. phone number 
g. gender 
h. date of birth 
i. clinic name 
j. provider name 
k. appointment date 
l. preferred language (English / Spanish) 
m. Medical record number or local unique identifier 
 
Upon receipt of this information Duke study coordinator will complete the registration 
and notify participant via email. The local site coordinator will monitor this process in the 
site specific census. 
 
There will be no compensation to provider, other clinic personnel, or patient participants. 
 

Title:  Coordinating Center for Implementation, Adoption, 
and Utility of Family History in Diverse Care Settings  
PI:  Geoffrey Ginsburg, MD, PhD        IRB # Pro00043372  
Research 
Summary 
 
Protocol ID Pro00043372 
1/20/2017 
10 
Consent Process: 
Providers will be consented in person by local study staff at each participating Institution 
after they have been provided with onsite education (by the local study staff) about the 
study and as to why they would want to participate.  Should they agree, they will sign 
the consent form and receive an electronic survey link via email. 
 
ORCA survey participants will have an implied consent process.  The potential survey 
respondent will receive a recruitment email with all the elements of informed consent 
and it is expected that participants who access the survey are actively consenting to the 
study through the action of accessing the survey and completing it. 
 
Key Informants will be contacted and consented separately for pre-implementation and 
post-implementation interviews. At the beginning of the conversation, the study 
interviewer will confirm that the participant received the written information about the 
study and consent process. If the key informant states that s/he has received the 
information, then the interviewer will reiterate key parts of the consent information that 
was emailed, including the purpose of the study, the key informant’s rights as a study 
participant, and the confidentiality of the interview (see attached verbal informed 
consent document). If the key informant states that s/he has not received or reviewed 
the consent information, then the interviewer will read the informed consent document 
verbatim and email another copy of the informed consent document. All key informants 
will be asked if they agree to participate in the study and have the interview audio 
recorded. For participants who agree to audio recording, the interviews will be recorded 
using an approved digital recording device. For participants who do not agree to audio 
recording, the interviewer will take copious notes on a memo template and will not 
record the interview. Study interviewers enter will keep an electronic verbal consent log 
(e.g., in an Excel spreadsheet).  
 
Interviewers will use an interview guide, which contains open-ended questions 
that direct the interview in a natural topical flow and suggested probes for more in-depth 
information, as is standard with semi-structured interviewing. The interview guides for 
this study were created based on theoretical constructs from Weiner’s Theory of 
Organizational Readiness for Change and specify questions relevant for each type of 
key informant (physician, nurse, scheduler). The pre-implementation guide contains 
questions relevant to understanding policies and barriers that may affect 
implementation; the goal is to inform a tailored implementation plan for each site. The 
post-implementation guide contains questions relevant to understanding experiences 
and outcomes of MeTree implementation. 
 
Patients will be consented via an electronic consent process: each is provided via email 
a web-based computer survey program account in which a full version of the consent 
form is initially presented and electronically signed and dated by the participant to 
complete the consent process. Once signed, the participant is provided access to the 
baseline survey, the MeTree program for completion of family health history, and 
education about collection of FHH.     Access to these online tools will be available from 

Title:  Coordinating Center for Implementation, Adoption, 
and Utility of Family History in Diverse Care Settings  
PI:  Geoffrey Ginsburg, MD, PhD        IRB # Pro00043372  
Research 
Summary 
 
Protocol ID Pro00043372 
1/20/2017 
11 
computer or mobile device via the web or the clinic via a kiosk. In addition, a local study 
coordinator will be available for assistance. 
 
Subjects' Capacity to Give Legally Effective Consent – Subjects who cannot give 
legally effective consent will not be included in the study since they would not be able to 
adequately perform the risk assessment or survey evaluations.  
 
Study Interventions – see Design and Procedures section 
 
Risk/Benefit Assessment –  
Risks:  Potential risks to the subjects include anxiety related to family health history 
results and breach of confidentiality of their study data.  FHH data collection is already 
considered standard of care for medical practice and the risk associated with this 
information or risk-based prevention strategies is considered to be no more than that 
associated with routine clinical care. Patients and providers will discuss CDS output 
during their appointment and study and clinical staff are available if needed.   
 
Provider participants do not have any anticipated risks. 
 
The alternative for potential participants is not participating in the study. 
 
Benefits:  Two aspects of the study will provide information that will improve patient 
care in primary care: 1) Enhancing primary care physician decision making by the 
application of individualized evidence-based algorithms based on patient characteristics 
and 2) Enhancing patient decision making by using active patient facing tools to 
promote patient engagement and activation. Overall we anticipate greater patient and 
provider satisfaction and the potential for streamlined workflows with improved 
information exchange.  Risk stratification with decision support can assist in decision 
making for both patients and providers by 1) increasing knowledge, 2) lowering 
uncertainty, 3) reducing the likelihood of indecision, and 4) increasing the match 
between decisions and values. These effects have both cognitive and emotional 
components that can influence “decisions” by shifting perceptions of: disease, disease 
risk, treatment, and treatment benefits. Patients are also given a copy of their pedigree 
which can be shared with and distributed among family members as well as retained by 
the patient as documentation of their effort to collect the family history and to share with 
other clinical providers involved in their care. 
 
Costs to the Subject – There will be no costs to patients or providers for their 
participation, though it does requirement a small time commitment.   
 
Data Analysis & Statistical Considerations – Effectiveness data will be summarized 
with descriptive statistics and plots. Generalized linear ordinal regression models 
(GLO)(the function ordglm from the R statistics package) will fit ordinal survey outcomes 
to the continuous outcome variables. Associations will be considered significant when 
the regression coefficient is not zero; a false discovery rate of 5% will be used to correct 

Title:  Coordinating Center for Implementation, Adoption, 
and Utility of Family History in Diverse Care Settings  
PI:  Geoffrey Ginsburg, MD, PhD        IRB # Pro00043372  
Research 
Summary 
 
Protocol ID Pro00043372 
1/20/2017 
12 
for multiple comparisons. Multivariate analysis will control for clinic and provider. A p-
value of <0.1 in stepwise regression will identify significant factors such as 
demographics, intent to change, and their interactions. The analyses for the multiple 
outcomes will follow the same procedure as the survey outcomes but using a logistic 
regression model that includes the 7 covariate factors (see sample size section). 
Although the study is implemented at the level of the clinical practice, the likelihood of 
clustering is low given that all participants undergo the intervention and the intervention 
is aimed at both the patient and the provider; however, to address the possibility of 
clustering, we will calculate a design effect; if it is 1 we will use standard tests and 
generalized linear mixed models with clinic and state as random effects, if not we will 
adjust the confidence intervals using a conditional logistic regression. Effect size bias is 
extremely unlikely in this study as all individuals within the clinics are offered  the 
intervention, preventing the imbalance in treatment assignment that can lead to 
inaccurate point estimates. 
 
ORCA survey data will be analyzed using this validated survey’s scoring method. The 
results will be used to categorize institutions and/or the individual clinics according to 
their flexibility for adapting to new ideas/technologies, which will then be included as an 
explanatory variable in the analysis of the effectiveness data captured during the trial as 
well as to help understand barriers encountered during the implementation process. 
 
Key Informant Interview data analysis will proceed with an initial review of the 
transcripts conducted independently by study investigators. Each coder will identify 
major thematic categories included in the a priori theoretical model and emergent 
categories. The coders will work together to develop a revised schema for content 
coding. Once the schema has been finalized, the coders will code the transcripts for 
relevant categories and have discussions that may lead to further revision and 
refinement of the code book. Findings from the pre-implementation interviews will be 
used to create a tailored implementation plan at each site. 
 
As of 01/20/2017Corrine Voils is no longer on key personnel for this protocol, however 
she has been added to outside key personnel and will assist with writing study 
publications. She will see data summaries only, and  not individual data.   
 
 
Data & Safety Monitoring – Dr. Ginsburg, the study PI, Dr. Orlando, the Co-I, and Dr. 
Ginsburg’s designees will be responsible for monitoring adverse events that occur as a 
result of participation in this study. They will also oversee that all appropriate measures 
are taken to ensure data security.  
 
Privacy, Data Storage & Confidentiality – Each subject will be assigned a Unique 
Study ID and only trained research staff will have access to the list of IDs and patient 
names for the purposes of scheduling follow-up surveys tracking subject participation.  
All survey and family health history data will be entered through a web-accessibly 
software program (each subject will have a unique login and password) and saved on a 

Title:  Coordinating Center for Implementation, Adoption, 
and Utility of Family History in Diverse Care Settings  
PI:  Geoffrey Ginsburg, MD, PhD        IRB # Pro00043372  
Research 
Summary 
 
Protocol ID Pro00043372 
1/20/2017 
13 
Duke University Health system server that is HIPAA compliant and where applicable, 
GINA compliant.    All data will be gathered and stored using protocols and privacy & 
security standards that comply with HIPAA and, where applicable, GINA. All patient 
family health history data will be gathered from patient portal applications and 
transmitted to and from the algorithm and clinical decision support databases using 
industry standard encryption protocols, including HTTPS and TLS. The healthcare 
systems employ additional protections for the data, including detailed audit logs, 
insulation from direct SQL queries, and detailed version control. All data gathered for 
the proposed studies will be treated with the same degree of confidentiality as a medical 
record. Only group information without personal identifiers will be included when sharing 
process implementation data and outcomes with approved collaborators. 
 
ORCA survey data will be stored on a secure server in the same manner as the data 
collected from patients.  Datasets will be downloaded and de-identified for analyses.  
These datasets will be kept on a shared departmental server. 
 
Key informant interviews:  The audio recordings will be stored on a pass-word protected 
folder on the Duke server accessible only to study staff. The recordings will be reviewed 
by the study team and transcribed by a transcription service contractor. The de-
identified transcripts will be analyzed with approved qualitative coding software.  
 
 
In compliance with NIH Genomic Data Sharing (GDP) Policy collected MeTree data will 
be deposited in the database of Genotypes and Phenotypes (dbGaP). The data 
elements to be released are listed in Appendix A. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Title:  Coordinating Center for Implementation, Adoption, 
and Utility of Family History in Diverse Care Settings  
PI:  Geoffrey Ginsburg, MD, PhD        IRB # Pro00043372  
Research 
Summary 
 
Protocol ID Pro00043372 
1/20/2017 
14 
 
 
 
 
 
 
 
BIBLIOGRAPHY & REFERENCES CITED  
 
1. 
Heald B, Edelman E, Eng C. Prospective comparison of family medical history with personal genome screening 
for risk assessment of common cancers. Eur J Hum Genet. 2012;20(5):547-51. PubMed Central PMCID: 
PMC3330209. 
2. 
Qureshi N, Armstrong S, Dhiman P, Saukko P, Middlemass J, Evans PH, Kai J. Effect of adding systematic family 
history enquiry to cardiovascular disease risk assessment in primary care: a matched-pair, cluster randomized 
trial. Ann Intern Med. 2012;156(4):253-62. PubMed Central PMCID: PMC22351711. 
3. 
Rubenstein WS. Family History and Health Risk Assessment Tools. In: Willard H, Ginsburg G, editors. Genomic 
and Personalized Medicine, 2nd Edition (In Press): Elsevier; 2012. 
4. 
Qureshi N, Carroll JC, Wilson B, Santaguida P, Allanson J, Brouwers M, Raina P. The current state of cancer 
family history collection tools in primary care: a systematic review. Genet Med. 2009;11(7):495-506. PubMed 
Central PMCID: PMCJournal--In Process. 
5. 
Reid GT, Walter FM, Brisbane JM, Emery JD. Family history questionnaires designed for clinical use: a 
systematic review. Public Health Genomics. 2009;12(2):73-83. PubMed Central PMCID: PMCJournal--In 
Process. 
6. 
O'Neill SM, Starzyk EJ, Kattezham RA, Rubenstein WS. Comparison of Family Healthware and Physicians' 
Family History Documentation  among 1124 patients. (Abstract #180) American Society of Human Genetics. 
2008. 
7. 
Ozanne EM, Loberg A, Hughes S, Lawrence C, Drohan B, Semine A, Jellinek M, Cronin C, Milham F, Dowd D, 
Block C, Lockhart D, Sharko J, Grinstein G, Hughes KS. Identification and management of women at high risk 
for hereditary breast/ovarian cancer syndrome. Breast J. 2009;15(2):155-62. PubMed Central PMCID: 
PMCJournal--In Process. 
8. 
Feero WG, Bigley MB, Brinner KM. New standards and enhanced utility for family health history information in 
the electronic health record: an update from the American Health Information Community's Family Health 
History Multi-Stakeholder Workgroup. 2008. PubMed Central PMCID: PMC2585527. 
9. 
Osheroff JA, Teich JM, Middleton B, Steen EB, Wright A, Detmer DE. A roadmap for national action on clinical 
decision support. J Am Med Inform Assoc. 2007;14(2):141-5. PubMed Central PMCID: PMC2213467. 
10. Ginsburg G, Willard H. Genomic and personalized medicine: foundations and applications. Transl Res. 
2009(154):277-87. PubMed Central PMCID: PMCJournal--In Process. 
11. Downing GJ, Boyle SN, Brinner KM, Osheroff JA. Information management to enable personalized medicine: 
stakeholder roles in building clinical decision support. BMC Med Inform Decis Mak. 2009;9:44. PubMed 
Central PMCID: PMC2763860  
12. Khoury MJ, Bowen S, Bradley LA, Coates R, Dowling NF, Gwinn M, Kolor K, Moore CA, St Pierre J, Valdez R, 
Yoon PW. A decade of public health genomics in the United States: centers for disease control and prevention 
1997-2007. Public Health Genomics. 2009;12(1):20-9. PubMed Central PMCID: PMCJournal--In Process. 
13. Kawamoto K, Houlihan CA, Balas EA, Lobach DF. Improving clinical practice using clinical decision support 
systems: a systematic review of trials to identify features critical to success. Bmj. 2005;330(7494):14. PubMed 
Central PMCID: PMC555881. 
14. Dolin RH, Alschuler L, Boyer S, Beebe C, Behlen FM, Biron PV, Shabo Shvo A. HL7 Clinical Document 
Architecture, Release 2. J Am Med Inform Assoc. 2006;13(1):30-9. PubMed Central PMCID: PMC1380194. 
15. Kuderer N, GS G. Comparative Effectiveness Research, Personalized Medicince and Rapid Learning Healthcare: 
A Common Bond. J Clin Oncol (In Press). 2012. 

Title:  Coordinating Center for Implementation, Adoption, 
and Utility of Family History in Diverse Care Settings  
PI:  Geoffrey Ginsburg, MD, PhD        IRB # Pro00043372  
Research 
Summary 
 
Protocol ID Pro00043372 
1/20/2017 
15 
16. . Family History and Improving Health:  Research Challenge in Affecting Behavior Change and Family History 
Information: Patients and Providers. NIH State-of-the-Science Conference; 2009. 
17. NIH State of the Science: Family History and Improving Health 2009. Available from: 
http://consensus.nih.gov/2009/familyhistorystatement.htm. 
18. O'Neill SM, Rubinstein WS, Wang C, Yoon PW, Acheson LS, Rothrock N, Starzyk EJ, Beaumont JL, Galliher JM, 
Ruffin MTt. Familial risk for common diseases in primary care: the Family Healthware Impact Trial. Am J Prev 
Med. 2009;36(6):506-14. PubMed Central PMCID: PMCJournal--In Process. 
19. Ruffin MTt, Nease DE, Jr., Sen A, Pace WD, Wang C, Acheson LS, Rubinstein WS, O'Neill S, Gramling R. Effect of 
preventive messages tailored to family history on health behaviors: the Family Healthware Impact Trial. Ann 
Fam Med. 2011;9(1):3-11. PubMed Central PMCID: PMC3022039. 
20. Westman J, Hampel H, Bradley T. Efficacy of a touchscreen computer based family cancer history 
questionnaire and subsequent cancer risk assessment. J Med Genet. 2000;37(5):354-60. PubMed Central 
PMCID: PMC1734575  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Title:  Coordinating Center for Implementation, Adoption, 
and Utility of Family History in Diverse Care Settings  
PI:  Geoffrey Ginsburg, MD, PhD        IRB # Pro00043372  
Research 
Summary 
 
Protocol ID Pro00043372 
1/20/2017 
16 
 
 
 
 
 
 
 
 
 
APPENDIX A. 
 
 
MeTree data elements for release to dbGaP 
 
Demographics: 
Gender: 
Male 
Female 
Age 
Race: 
American indian or alaska native 
Asian 
Asian indian 
Chinese 
Filipino 
Japanese 
Korean 
Vietnamese 
Other asian 
Unknown 
Black or african-american 
Native hawiian or other pacific islander 
Chamorro 
Guamanian 
Native hawaiian 
Samoan 
Unknown 
White 
  
Ethnicity: 
Hispanic or latino 
Central american 
Cuban 
Dominican 
Mexican 
Other hispanic 
Puerto rican 
South american 
Ashkenazi jewish 

Title:  Coordinating Center for Implementation, Adoption, 
and Utility of Family History in Diverse Care Settings  
PI:  Geoffrey Ginsburg, MD, PhD        IRB # Pro00043372  
Research 
Summary 
 
Protocol ID Pro00043372 
1/20/2017 
17 
Not hispanic or latino 
 
 
Vital signs: 
Blood pressure 
Weight 
Height 
Waist circumfrence 
 
 
Labs: 
LDL 
HDL 
Total cholesterol 
Hs-CRP 
CA-IMT 
Calcium CT score 
HgbA1c 
 
Diseases and age of onset: 
These are collected about the individual and about their family members so assume they would need 
to be identified using different mechanisms.  
 
Abdominal aortic aneurysm 
DVT 
Factor V Leiden Mutation 
Prothrombin mutation 
Antithrombin III deficiency 
Protein S deficiency 
Protein C deficiency 
Cancer 
Cancer that isn't one of specific ones below 
Bone cancer 
Brain cancer 
Colon cancer 
Esophageal cancer 
Renal cell carcinoma 
Leukemia 
Hepatocellular carcinoma 
Lung cancer 
Sarcoma 
Ovarian cancer 
Pancreatic cancer 
Prostate cancer 
Rectal cancer 
Skin cancer (any type) 
Small bowel cancer 

Title:  Coordinating Center for Implementation, Adoption, 
and Utility of Family History in Diverse Care Settings  
PI:  Geoffrey Ginsburg, MD, PhD        IRB # Pro00043372  
Research 
Summary 
 
Protocol ID Pro00043372 
1/20/2017 
18 
Stomach cancer 
Thyroid cancer 
Uterine cancer 
Hereditary cancer syndrome 
Syndrome that isn't one specified below 
Cowden or listed PTEN gene mutation 
Familial adenomatous polyposis or listed APC gene mutation 
Hereditary Breast and Ovarian or listed BRCA mutation 
Li-fraumeni syndrome or listed TP53 gene mutation 
Lynch or listed MLH1, MSH2, MSH6 gene mutation 
Carotid stenosis 
Dementia 
Diabetes type 1 
Diabetes type 2 
Gestational diabetes 
Colon polyp 
Crohn's disease 
Irritable bowel  
Ulcerative colitis 
GI disorder (other than the 5 listed above) 
Atrial fibrillation 
Heart attack/CAD 
Heart disease not listed above 2 
Hereditary cardiovascular syndromes 
Syndrome that isn't one specified below 
Long qt 
Brugada 
Catecholaminergic polymorphic ventricular tachycardia 
Hypertrophic cardiomyopathy 
Left ventricular non-compaction syndrome 
Arrhythmogenic right ventricular dysplasia 
Any cardiomyopathy 
Ehlers danlos 
Marfan 
Familial hypercholesterolemia 
Hyperlipidemia 
Hypertension 
Poly Cystic kidney disease 
Diabetic nephropathy 
Nephrosis 
Nephritis 
Nephrotic syndrome 
Kidney disease (other than the 5 listed above) 
Alpha 1 antitrypsinase deficiency 
Auto immune hepatitis 
Hemochromatosis 
Primary biliary cirrhosis 

Title:  Coordinating Center for Implementation, Adoption, 
and Utility of Family History in Diverse Care Settings  
PI:  Geoffrey Ginsburg, MD, PhD        IRB # Pro00043372  
Research 
Summary 
 
Protocol ID Pro00043372 
1/20/2017 
19 
Sclerosing cholangitis 
Wilson's disease 
Asthma  
Copd 
Chronic bronchitis 
Emphysema 
Lung disease (oter than 4 listed above) 
Systemic lupus 
Multiple sclerosis 
Osteoporosis 
Peripheral arterial disease 
Alcohol abuse 
Drug abuse 
Anxiety 
Add/adhd 
Autism 
Bipolar disorder 
Depression 
Eating disorder/bulemia/anorexia 
Obsessive compulsive disorder 
Panic disorder 
Personality disorder 
Ptsd 
Schizophrenia 
Social phobia 
Rheumatoid arthritis 
Ischemic stroke 
Hemorrhagic stroke 
Thyroid disease (any type) 
  
  
  
Medically related 
• 
Menopause  
• 
Age at Menopause 
• 
Taken hormone replacement therapy in the past 
• 
Currently taking hormone replacement therapy 
• 
Pregnant, breastfeeding, or taking the medication tamoxifen or raloxifen 
• 
Had pre-eclampsia, pre-term birth, or birth of infant small for gestational age 
• 
Hysterectomy 
• 
Uterine hyperplasia 
• 
Radiation therapy to the chest between the ages of 10 and 30 
• 
Breast biopsy 
• 
More than 1 breast biopsies 
• 
Breast biopsy with hyperplasia 
• 
Breast biopsy with atypical hyperplasia 
• 
Breast biopsy with lobular carcinoma in situ 
• 
Unknown breast biopsy result 

Title:  Coordinating Center for Implementation, Adoption, 
and Utility of Family History in Diverse Care Settings  
PI:  Geoffrey Ginsburg, MD, PhD        IRB # Pro00043372  
Research 
Summary 
 
Protocol ID Pro00043372 
1/20/2017 
20 
• 
Age first menstrual cycle 
• 
Age of first live birth 
  
  
Family related 
• 
Were you born a twin (for you and family members) 
• 
If twin are you identical or fraternal (for you and family members) 
• 
Were you adopted (for you and family members) 
• 
Are your parents consanginous (only you) 
• 
Still alive (only family members) 
o 
-- if yes age 
o 
--if no cause of death (accident, cancer, diabetes, heart disease, infection, lung disease, natural 
causes, SIDS, stroke, unknown, other) 
o 
--if no, age of death 
  
  
Diet/Exercise 
• 
Average cups of fruit you eat per day 
• 
Average cups of vegetables you eat per day 
• 
Do you eat more whole grain products than refined flour products 
• 
Average times per day you eat salty or sugary foods 
• 
Do you eat more monosaturated fat than trans- or saturated fats 
• 
Average days per week performing moderate exercise for 30 min 
• 
Average days per week performing vigorous exercise for 20 min 
• 
Average days per week performing strength training 
  
 
Tobacco 
• 
Tobacco packs per day 
• 
Tobacco number of years 
• 
Tobacco year that you quite