Models of Primary Osteoporosis Screening in Male Veterans
Phase: NA
Conditions: Osteoporosis, Osteopenia, Osteoporotic Fracture
Sponsor: VA Office of Research and Development

PROTOCOL TITLE: Models of Primary Osteoporosis Screening in Male Veterans 
 
PRINCIPAL INVESTIGATOR:  Cathleen Colon-Emeric, M.D. 
 
VERSION NUMBER AND DATE: Version 4, October 21, 2020 
 
SPONSOR/FUNDING SOURCE: VA Health Services Research and Development 
 
Purpose 
     The purpose of this study is to test new models of osteoporosis screening and treatment adherence on 
fracture risk in older men using a group randomized trial compared to no additional screening support 
(control).  Randomization and intervention will occur at the Patient Aligned Care Team (PACT) level; 
therefore, the PACT providers will complete the informed consent process, agreeing that their team will 
utilize the randomly assigned care model.  Because many PACT teams are located off site, we request a 
waiver of documentation of informed consent. 
 
All care models deliver VA guideline-recommended osteoporosis screening and treatment to high-risk 
Veterans by DVAHS credentialed clinical staff, which represents usual clinical care.  Patient-level 
measures are all routine clinical ultilization and outcomes collected soley from the electronic medical 
record.  Therefore, a waiver of informed consent and HIPAA authorization for the patient-level data 
collection procedures is requested as the study presents minimal risk beyond routine clinical care to 
Veterans. 
 
Specific aims: 
 
 
1. Compare the impact of BHS primary osteoporosis screening models on patient level 
outcomes strongly associated with fractures as measured by the EHR at 2 years; 1) eligible 
proportion screened; 2) medication adherence (initiation; implementation, and 
discontinuation); 3) bone mineral density at the femoral neck in a random sample of high risk 
patients. Fracture rates (fractures/patient years) are exploratory. 
H1a: PACT teams randomized to BHS will have better patient level outcomes compared 
to usual care at pre-specified clinically important levels, adjusting for baseline levels. 
 
2. Determine the impact of BHS primary osteoporosis screening models on provider  
and facility level outcomes including change in DXA volume, change in metabolic bone 
disease clinic volume (assessed by EHR), and PACT provider time and satisfaction 
(assessed by Nominal Group Technique). 
 
H2a: DXA and metabolic bone disease clinic volumes will increase during the intervention, 
with a higher proportion of referrals coming from PACTs randomized to BHS. 
H2b: Provider satisfaction with osteoporosis screening systems will be higher for PACTs 
randomized to BHS management compared to usual care. 
3. Determine the impact of BHS primary osteoporosis screening programs on health system 
and policy level outcomes using Markov models of screening program cost per quality 
adjusted life year. Model inputs are based on VA national fracture data from our prior work, 
results from aims 1 and 2, and published quality of life estimates. 
 
Background and Significance 
   Osteoporosis is under-recognized in older men.  At age 50 years, 1 in 5 men can expect to suffer a 
major osteoporotic fracture in their remaining lifetime, comparable to the risk of prostate cancer.1  Men 
are more than twice as likely as women to experience complications after a fracture,2 and have greater 
excess mortality after hip fracture.3  Because risk factors are common in Veterans, osteoporosis is 

particularly prevalent in the Veterans Health Administration (VA) system.  More than half of male Veterans 
over age 50 years have osteopenia or osteoporosis, a rate nearly double the non-Veteran population.4   
     Fractures resulting from osteoporosis have negative consequences on  functional status, mortality, 
and quality of life, with high rates of pain, depression, and loss of independence.2  After a hip fracture, 
nearly 75% of patients spend time in a nursing facility, and only 20% regain their prior level of ambulation.  
Many fractures are associated with substantial excess mortality; men with a hip fracture have excess 
annual mortality of 20% that persists up to 10 years.3  Osteoporotic fractures also have an important 
economic impact.  It is estimated that hip fractures result in 43 million dollars of excess cost to the VHA 
annually.5 
     Fortunately, osteoporotic fractures are preventable.  The generic bisphosphonate alendronate (annual 
VA cost VA $20) reduces the risk of vertebral, hip and other non-vertebral fractures by 45%, 40%, and 
16% respectively.6  Although fewer studies in men are available, fracture risk reduction has been similar.7-
9 Importantly, our work shows that bisphosphonates also reduce mortality in men and women.10,11  
Medication adherence is critical, but has been documented to be poor within VA and community 
settings.14-16   
     Osteoporosis screening is simple and inexpensive.  Patients without a prior fracture are selected for 
treatment based on the results of a non-invasive Dual Energy X-ray Absoptiometry (DXA) measurement 
of bone mineral density (BMD).  Current U.S. guidelines suggest that it is cost-effective to treat patients 
with BMD T-score of < -2.5 (osteoporosis), and those with T score between -1.5 and -2.5 (osteopenia) 
who have additional risk factors resulting in a 10 year fracture risk of over 3% for hip fracture, or 20% for 
major osteoporotic fracture.18-20  
     Despite the high burden and preventability of osteoporotic fractures, men are rarely diagnosed or 
treated for osteoporosis before a fracture has occurred. Economic models based on large cohort studies 
have suggested that screening is likely to be highly cost-effective.27-30 Furthermore, our national VA cohort 
study (see preliminary studies) demonstrates screening effectiveness in high risk subgroups.  
Professional groups including the American College of Physicians, Endocrine Society, National 
Osteoporosis Foundation, the Canadian Medical Association, the U.K. Health System, and the VA 
Undersecretary for Health all advocate for primary osteoporosis screening in men.   
Osteoporosis screening and treatment services within VA are ineffective overall.  Our national study of 
primary osteoporosis screening in male Veterans (preliminary studies) showed wide variation in patient 
selection.  Overall, screening rates were 8% for men over age 65; far lower than expected based on the 
prevalence of osteoporosis risk factors in the population. Moreover, even among men in whom screening 
was completed, it was not associated with lower overall fracture rates because osteoporosis treatment 
and adherence following screening were extremely low. The result is an ineffective and wasteful 
primary osteoporosis screening program across VA that does not identify appropriate men for 
screening, nor facilitate treatment adherence for those found to be at high fracture risk.  Notably, we 
found that screening was associated with clinically important reductions in fractures for high-risk men in 
pre-specified subgroup analyses. 
     Attempts to improve osteoporosis screening using traditional quality improvement programs have been 
minimally effective.34-36  EHR alerts alone do not improve osteoporosis screening rates37 and do nothing 
to address adherence.  However, two distinct osteoporosis screening paradigms have been suggested, 
and form the scientific premise for the models proposed in this application.  A practice manager approach 
in which a non-physician staff member is responsible for organizing osteoporosis screening led to a 
doubling in osteoporosis screening in a single academic medical center, but its impact on medication 
adherence is unknown.37  In this paradigm, responsibility remains at the individual practice level (or in VA, 
PACT).  In contrast, a Fracture Liaison Service (referred to here as “Bone Health Service”, BHS) 
represents a centralized model that has been successful in improving secondary osteoporosis screening 
and treatment adherence after a fracture has already occurred.38,39  In this model, a team of nurses led by 
a bone specialist identify patients with fracture within the entire health system, and arrange for evaluation 
and treatment.  Such models have reduced 2-year fracture rates by 56%40 and are cost saving or highly 
cost-effective.41,42   The National Bone Health Alliance and others recommend expansion of BHS models 
to address primary fracture prevention, however its impact on osteoporosis screening and treatment rates 
in this context are unknown.    

     Based on this body of evidence, we conclude that the VA urgently needs data on the impact of primary 
osteoporosis screening and adherence models to inform the adoption of rational clinical programs.  
Design 
 
Pragmatic group randomized trial of PACT teams (n=39 teams recruited, estimated 24 at DVAHS and 15 
at Richmond VAMC) will be randomized into 2 groups: a control group (no additional support, and a 
centralized Bone Health Service (BHS) model. Outcomes for all patients eligible for osteoporosis 
screening within the randomized PACTs will be assessed by investigators masked to group assignment 
via EHR at baseline and 2 years.  Outcomes for PACT providers will be assessed using qualitative 
methods (nominal group technique).   
 
Outcome measures are listed in the table 1 below. 
Table 1.  Outcome measures by Aim.  RDW=Regional Data Warehouse; MPR=Medication Possession Ratio; 
FRAX=Fracture Risk Assessment Tool. 
Outcome 
Definition/Measure 
Data Source/Timing 
Important Difference  
Patient (Panel) Level (Aim 1) 
Screening Rates  Proportion of eligible men screened in 
last 12 months 
RDW at baseline, year 1 and 
year 2 
25% increase from 
6% Control 
Medication 
Initiation 
Proportion of screened men meeting 
treatment threshold (T score <-2.5 or 
FRAX score high-risk) who receive at 
least 1 prescription  
RDW, intervention period 
year 1 and year 2, non-VA 
medication lists by chart 
abstraction.  
30% increase from 
55% Control 
Medication 
Implementation 
Days of medication dispensed divided 
by follow-up days  
Pharmacy dispensing 
records, for patients started 
within prior year at baseline, 
year 1 and 2. Non-VA 
medication lists by chart 
abstraction.  
 
20% increase in 
MPR>80%14 from 
30% Control 
Medication 
Discontinuation 
Time between first prescription 
dispensing date and the date of first 
medication possession gap of >3 
months 
20% difference 
Bone Mineral 
Density 
BMD g/cm2 at femoral neck and lumbar 
spine in random sample of men eligible 
for screening 
Random sample of 712 men 
(356 UC, 178 each of the 
other 2 models) eligible for 
screening in panel at least 1 
year, measured 2 years after 
start date   
Post-intervention 
between group 
difference of 3% 
femoral neck, 5% 
lumbar spine99 
Harms 
Proportion of men started on oral 
medication for new GI distress in 3 
months  
Subtrochanteric fractures or 
Osteonecrosis of the jaw 
RDW ICD10 codes, new 
prescription for proton pump 
inhibitor or H2 blocker. 
RDW ICD10 codes 
15% increase from 
30% Control  
>expected 1/50,000 
patient years 
treatment 
Fractures 
(exploratory) 
All clinical fractures excluding facial, 
digital 
RDW, confirmed by chart 
abstraction 
10% decrease from 
2.5/100 person years 
Control 
Provider/Facility Level (Aim 2) 
DXA volume 
DXA orders/ 1000 patients/year, by 
EMR data, calculated at 2 
 

 
Provider-level Covariates will be collected from the PACT providers at the time of randomization, 
including medical provider type (Advanced Practice Provider vs. MD), medical provider and RN years in 
practice, years in VA, and practice site (rural CBOC, urban CBOC, VAMC).   
Patient-level Covariates will be extracted from the Regional Data Warehouse and CPRS.  
Demographics include age, self-reported race, body mass index, and rural zip code as classified by 
Rural-Urban Commuting Area.  Because medication co-pays may be a barrier to adherence, co-pay 
status will be collected. Co-morbidities related to fracture risk include chronic lung disease, diabetes, 
endocrine disorder (hyperthyroidism, hyperparathyroidism, Cushing’s, hypogonadism), prostate cancer, 
rheumatoid arthritis, Parkinson’s disease, stroke, gastrectomy/malabsorption, smoking, alcohol abuse, 
chronic kidney disease, chronic liver disease, dementia.  Medications include calcium, vitamin D, 
glucocorticoids, androgen deprivation therapy, traditional anti-epileptic drugs, proton pump inhibitors, 
selective serotonin reuptake inhibitors, and psychoactive medications. 
Risk/Benefit Assessment 
 
Protection against Risk:   
1) Disclosure of protected health information.  All human subjects’ data will be stored in a restricted 
access folder behind the VA firewall on a server meeting Federal Research Data Security 
requirements.  Only study stuff listed on the IRB staff listing will have access to the folder, and all 
computer access requires a PIV card and password.  Data will not be transferred outside of this 
environment.   
2) Nominal Group Technique.  An experienced qualitative researcher will conduct the nominal group 
sessions with PACT providers.  Participation in the sessions is voluntary, and steps will be taken to 
reduce social desirability and psychological discomfort during the session including using anonymous 
responses on index cards and anonymous ranking sheets. 
 
Potential Benefits of the Proposed Research to Human Subjects and Others:   
1) Benefits to PACT providers.  All PACT providers will be provided with educational materials to 
improve their knowledge of osteoporosis screening guidelines. . 
2) Benefits to Veterans.  If the new screening models are effective, Veterans will benefit from improved 
fracture prevention services, with fewer expected to suffer painful and debilitating low-trauma 
fractures.   
 
Selection of Subjects 
PACT Providers (n=78, estimated 48 at DVAHS and 30 at RVAMC) include the medical provider (MD or 
advanced practice provider, APP) and registered nurse (RN) who provide primary care to a panel of 60 or 
more eligible male Veterans for osteoporosis screening. If the PACT does not have an RN assigned to 
the team, the PACT provider may participate alone. Providers will be identified by the ACOS and ACNS 
for Ambulatory Care at each site.  Eligible PACT medical and RN providers must be: 
• 
Completed training (i.e., PACT teams led by residents and fellows are excluded, unless 
supervised by faculty physicians)  
intervention group 
years 
Bone Disease 
clinic volume 
Consults/ 1000 patients/year, by 
intervention group 
EMR data, calculated at 2 
years 
 
PACT 
satisfaction, time 
Nominal Group Technique at Routine 
Staff meeting 
Measured at 2 years 
 
Health System/Policy Level (Aim 3) 
Program Cost 
Effectiveness 
Cost/quality adjusted life years (QALY) 
of the screening models compared to 
control 
Markov model with above 
outcomes, fracture rates, 
cost and quality of life from 
VA and medical literature 
Probability of 
cost/QALY >80% at 
thresholds of 
$50,000, $100,000, 
$200,00071 

• 
Care for male Veterans >65 years (i.e., Women’s Health PACTs are excluded)   
Patients (estimated n at both sites = 2376; 1462 at DVAHS) include men aged 65-85 years eligible for 
primary osteoporosis screening within enrolled PACT teams.  Patients will be identified using Corporate 
Data Warehouse queries.  Inclusion criteria:  
• 
No prior fracture or osteoporosis diagnosis 
• 
At least 1 VA Undersecretary Guideline risk factor (weight loss >20% in 5 years; BMI <25  kg/m2; 
diabetes; pernicious anemia; gastrectomy; anticonvulsants; glucocorticoids; androgen deprivation 
therapy; hyperthyroidism; hyperparathyroidism; rheumatoid arthritis; alcohol dependence; chronic 
lung disease; chronic liver disease; stroke; Parkinsonism; prostate cancer; and current smoking).63  
 
Exclusion criteria: 
• Active non-skin cancer diagnosis 
• Enrollment in hospice or palliative care 
 
Patients (year 4/5 sub-sample) (estimated n at both sites =900) include men aged 65-85 years, enrolled 
in eligible PACT team for at least 2 years, who met 1 or more criteria for osteoporosis screening as the 
protocol at PACT enrollment. 
 
Exclusion criteria:  
• 
Dual Energy X-ray Absorptiometry measurement <18 months prior to outcome measurement 
period (minimum time required to detect a difference in BMD) 
• 
Active non-skin cancer diagnosis 
• 
Receiving hospice or palliative care 
• 
Lacks capacity to provide informed consent (missing two items on the Evaluation to Consent 
Measure)101 
• 
Inability to transfer independently to DXA table (over scanner weight limit, spinal cord injury, 
bilateral lower extremity amputation) 
 
 
Subject Recruitment 
     The intervention is focused on the PACT medical and RN providers; therefore, both will be 
asked to provide verbal informed consent for participation in all training and data collection 
activities.  Study procedures will be described to PACT providers during a monthly Ambulatory 
Care meeting, with written study informational materials distributed via VA Outlook email. During 
the meeting participant may be given low-valued promotional items Study personnel will follow-
up individually with each provider to answer questions and complete the informed consent 
process.  Both the PACT provider and RN must agree to participate.  As PACT providers turn-
over in our health system, patient panels are left intact and a new provider assigned; study team 
members will therefore approach the new provider to request continued participation in the group 
randomized.   
     In year 3, a sub-sample of medical providers and RNs whose PACTs have participated in the 
care models will be recruited for a 1-hour Nominal Group session to collect qualitative data about 
their experience with the care model.  Study stuff will send out an informational Outlook email to 
the work address of all participating PACT providers.  Those expressing interest will be 
contacted individually to provide more information and schedule their participation in the session.  
Written informed consent will be complete at the beginning of the session, as described below. 
     In year 4, an additional sub-sample of patients will be recruited to complete a DXA scan. 
Subjects will be contacted for participation in this outcome measurement regardless of whether 
or not they were screened during the study period; however, those screened <18 months prior to 
the outcome assessment will be excluded since the minimum recommended time between DXA 
scans is 18 months. Study staff will schedule DXA at their closest VA facility. Subjects will be 
provided $50 compensation for their time and travel. All subjects and their PACT providers will 
be provided with their DXA results for clinical decision 
making.  
      

Figure 2. Main model components and outcomes by 
PROSPR model step and screening model. 
Consent Process 
     If a PACT provider expresses interest in participation, a study staff member will arrange a 
time for them to meet to further describe study procedures, risks, and benefits.  When possible, 
this meeting will occur in-person in the PACT staff workroom or other quiet workplace location; 
however, providers in Community Based Outpatient Clinics may choose to have VA Skype for 
Business or telephone meetings to accommodate their schedules.  Study staff will distribute 
copies of the Participant Consent Handout to each provider prior to the meeting so they are 
available for review during the meeting.   
     Once the informational meeting has been completed and PACT team members have had a 
chance to ask any questions, the study staff will encourage them to discuss privately whether or 
not they wish to participate.  This may occur immediately after the meeting, or they may choose 
to take several days to consider.  If providers choose to participate, they will be asked to provide 
verbal informed consent to 2 study staff members; a waiver of documentation of informed 
consent is requested for this process. As a way to thank subject and to promote the project, 
participants will be given promotional items such pens, badge holders and Bluetooth speakers 
with study logos.  
       In year 3, a subset of PACT medical providers and RNs will be recruited for the Nominal 
Group sessions as above.  Each will be sent an electronic copy of the informed consent 
document via VA Outlook email prior to the session to review individually.  As each staff member 
arrives, a study staff member will review the procedures, risks, and benefits with each individual 
or small group.  They will have the opportunity to ask any questions and will be informed that 
they can leave now or at any time during the session.  If they wish to participate, they will be 
asked to sign 2 copies of the informed consent, HIPAA authorization, and notice of privacy 
practices, keeping 1 set for 
themselves and giving the other set 
to 
the study staff. 
In year 4, a subset of Veterans 
receiving a DXA scan will be 
contacted, screened and consented. 
After 
which, study staff will schedule a 
DXA 
scan at closest VA facility to the 
Veteran. For completing the DXA 
scan, participants will be 
compensated $50 for their time 
according to VA compensation 
policies. 
     A waiver of patient informed 
consent and HIPAA authorization is 
requested for patient outcomes 
assessment via the EMR because 
this 
is a low risk study implementing 
routine clinical care as currently 
recommended by the VA 
Undersecretary.  
  
 
 
Study Interventions 
 
Randomization.  At the beginning of the project stratified, block randomization was used to 
randomize all providers.  Randomization will occurred at the level of PACT team.  PACT teams 

were stratified by medical provider type and blocked by site (e.g., specific CBOC/VAMC). A 
statistician unaware of team identity randomized PACTs in blocks of 3 within strata to ensure 
similar distributions.  If insufficient numbers of PACTs were recruited within small CBOCs, they 
were combined with other similar CBOCs (rural vs. urban) for randomization. In light of the VA’s 
response to COVID-19 efforts and demand on PACT providers, PACT teams participating in the 
PACT practice management arm will be re-randomized to either the Bone Health Service or 
Control arms to decrease burden and continue participation in the project. 
 For the sub-sample of participants recruited starting in year 4, Veterans will be randomized 
using a random number generator. Each eligible Veteran will be contacted in order until the 
target number in each PACT have provided informed consent for BMD measurement (total 
n=900). 
 
Interventions.  Initially two  screening models will be compared to control. Each includes 2 main 
categories; 1) osteoporosis screening promotion, and 2) medication adherence promotion.  
Figure 6 depicts the main intervention components and outcome measures as they relate to the 
PROSPR conceptual model.48   
Note that Veterans in all enrolled PACTs receive guideline-recommended “usual clinical 
care” for osteoporosis screening delivered by a VA clinical provider and endorsed by 
their primary care provider.  In this situation, the “intervention” is how the model 
organizes responsibility and support for this care.  Table 2 describes how the steps differ 
between the screening models and which providers are responsible for them.  
Control– PACT providers in the control group will be given the VA Undersecretary Guidelines for 
primary osteoporosis screening and standard patient education materials for adherence support 
without additional support.  This arm represents a “no practice management support” control 
group.  
PACT Practice Management Model.  This model represents a robust practice management 
support model, with multiple tools and processes to facilitate osteoporosis care.  In addition, it 
adds an adherence support component. All components are implemented by PACT providers, 
who will receive 1 hour of individualized instruction by study staff in their clinics at the beginning 
of the study period. The VA’s COVID-19 response has increased demand on PACT providers. 
With input from stakeholders including PI’s, statisticians and providers and the ACOS, to 
decrease the time burden on PACT providers assigned to this arm, the study team will re-
randomize and re-consent PACT team, therefore, eliminating PACT practice management 
activities and analysis. 
 
Bone Health Service Model – Patients in PACTs randomized to the BHS model will have 
osteoporosis screening, education, and follow-up handled centrally by the bone health team.  
PACT providers can opt out of the service for patients in whom they believe it is not appropriate, 
and approve all orders, but are not responsible for most activities.   
BHS Screening Promotion 
1. The Bone Health Nurse (BHS RN) will identify eligible patients quarterly as described 
previously.  Patients will be contacted via letter and telephone, and if they agree will be 
scheduled for DXA.  
2. The BHS RN obtains DXA results, calculates Fracture Risk Assessment Tool (FRAX) score33, 
and those meeting treatment thresholds are referred to the Bone Health MD for e-consult.  
3. The Bone Health MD reviews additional clinical information in the EHR and generates an e-
consult containing recommendations for additional laboratory evaluation (if needed) and 
treatment; this note is co-signed by the PACT provider. The BHS RN then contacts the 
patient to provide education and shared decision making, and places orders for PACT 
provider co-signature.   
BHS Adherence Promotion 
1. All patients initiating bisphosphonates will be called by the BHS RN at 1, 6, and 12 months to 
identify adherence barriers using a validated tool modified for osteoporosis therapy.47  

Algorithms for overcoming patient and health-care system adherence barriers to osteoporosis 
medications will be used in these calls (appendix 1).51,52,66  For example, patients reporting 
gastrointestinal distress will be offered annual intravenous therapy; patients with difficulty 
ordering refills will be assisted to enroll in myhealthevet. The 12-month call will ensure that 
the medication has been re-ordered.  Subsequently, patients not refilling medications will be 
identified from RDW every 6 months, with telephone follow-up as indicated.  
2. Patients with medication nonadherence identified during these calls will be offered an 
additional educational visit, based on the content of a prior successful osteoporosis 
adherence promotion program.45  The educational program will be delivered by the BHS RN 
during a group visit, Virtual Medical Room visit, or telephone visit at the Veteran’s choice.  
 
 
 
Adverse Events 
 
Potential risks to PACT providers include disclosure of confidential demographic information, 
disruption or change of usual workflow, and emotional discomfort sharing information in a 
Table 2. Model components by step in the Screen and Treat Process. All steps represent usual clinical care for the 
Veteran. 
Step in Process 
Control 
PACT Practice Management  
(removed from study 
activities) 
Bone Health Service (BHS) 
Screening Promotion 
Selection for screening 
Discretion of provider 
List of eligible patients 
provided to PACT RN 
biannually 
BHS RN queries RDW 
quarterly 
Scheduling screening 
Provider orders; MSA 
or Veteran phone call 
to radiology  
PACT RN orders; MSA or 
Veteran phone call to radiology 
BHS RN orders and 
coordinates scheduling with 
Veteran 
Quantify risk from DXA 
results, determine if 
they meet treatment 
threshold 
Discretion of provider 
Provider accesses FRAX link 
on Osteoporosis order set 
BHS RN and BHS MD based 
on FRAX risk  
Shared decision-
making with Veteran 
Provider by phone or 
at next primary care 
visit 
Provider by telephone or at 
next primary care visit, patient 
education materials available 
E-consult to provider, BHS 
phone call with Veteran, 
decision- tool sent to patient 
Adherence Promotion 
Ordering treatment 
Provider 
Provider on Osteoporosis 
Order Set 
BHS RN with provider co-
signature 
Adherence monitoring 
Discretion of provider 
List of non-adhering patients 
provided to PACT Pharmacist 
quarterly 
BHS RN telephone follow-up 
and personalized barrier 
assessment 
Intervening when non-
adherence detected 
Discretion of provider 
PACT Pharmacist phone call 
or visit 
BHS RN uses adherence 
algorithm, educational visit  

nominal group technique session.  Potential risks to the Veterans include disclosure of protected 
health information.  
All adverse events will be reported per Durham VAMC requirements. All Serious, Unanticipated 
and Related adverse events will be reported to IRB within 5 business days of hearing of the 
event. All other adverse events will be reported at continuing review. 
 
Costs and/or Payments to Subjects 
There are no costs to subjects. Beginning in year 4, a subset of patients will be given a repeat 
DEXA scan. For their time, patients will be compensated $50. A total of 900 patients will be 
compensated using standard VA compensation policies.   
 
Data and Safety Monitoring 
 
Although this is a low-risk study that is promoting guideline-recommended care, a data safety 
monitoring board will be recruited to include at least 1 ambulatory care clinician and 2 additional 
members from the Durham HSR&D COIN.  The DSMB will meet biannually to review subject 
recruitment, data collection and management procedures, and safety outcomes.  Screening rates 
at the PACT level will be measured at baseline and 2 years after implementation.  Adverse drug 
effects related to osteoporosis medications will be evaluated by the DSMB every 6 months.  
Inadvertent data disclosures will be reported to the DSMB, IRB and VA ORD as soon as 
discovered, and immediate steps to minimize sharing will be taken. 
 
Withdrawal of Participants 
   PACT Providers may choose to withdraw their team at any time with no consequence to them 
or their patients.  No further data collection will be completed on their PACT team, and there will 
be no end-of-study visit.  Study staff will request an in-person or phone meeting with the provider 
to assess reasons for withdrawal. 
     If a Veteran wishes to withdraw, he/she can do so by contacting our study team in writing or 
verbally. There are no anticipated circumstances under which subjects will be withdrawn without 
their consent. 
 
Data Collection, Flow and Management 
     Provider-level data is limited to demographic information and is collected on a paper form at 
the time of informed consent and entered into the study database.  Paper forms are stored in the 
Durham GRECC as above. 
     Patient-level data from both Durham and Richmond VAMCs is downloaded directly from the 
Regional Data Warehouse on an excel spreadsheet, and uploaded into the study database 
behind the VA firewall.  Additional data fields are abstracted by study staff from CPRS directly 
into the study database.  The study database is maintained in a secure HSR&D drive folder 
\\vhadurhsmcifs01.v06.med.va.gov\DURHAM_HSRD_P\MOPS.  Data will not be transferred to outside 
entities. 
 

Figure 6.  Markov model for Aim 3 analyses of economic impact of 3 screening models. 
 
Data Analysis and Statistical Considerations 
     Data for Aims 1 and 2 will be analyzed by the study statisticians (Mr. Sloane, Dr. Pieper) on 
the HSR&D server using the most currently available version of SAS.  Nominal Group Technique 
data will be analyzed using qualitative methods by the PI (Colón-Emeric) and other relevant 
study staff on the HSR&D server.  Aggregated, population-level data for aim 3 economic 
analyses will be provided to the study economist (Dr. Nelson) at the Salt Lake City VAMC using 
TreeAGE software. 
Aims 1 and 2.  
     Mixed-model ANOVA/ANCOVA will be employed. This extension of the ANOVA/ANCOVA 
based on the General Linear Model is preferred for group randomized trials with 1 or 2 follow-up 
time points.85 We will use the General Linear Mixed Model or the Generalized Linear Mixed 
Model to account for clustering of patients within providers; this approach accommodates 
regression adjustment for covariates and has the advantage of both allowing for correlation 
between subjects within cluster, and within subjects over time. Simulations have shown these 
methods have the nominal Type I error rate across a wide range of conditions common in group 
randomized trials.86 Our general strategy is to follow an “analyze as you randomize” strategy, 
comparing PACT level parameters between randomization groups. PACTs and individuals will be 
entered into the model as random effects, while group and time will be tested as fixed effects. 
We note, however, that if there are minimal differences between PACTs, we will be able to 
merely control for PACT in the analysis. Further, unlike a longitudinal panel study, subjects will 
enter and leave the PACT over time. For events that should occur only once (e.g. screening), we 
will censor the subject at the point of the event. Further, entry into some analyses are conditional 
on prior events (e.g. medication adherence will occur only among those who are screened and 
who have a low DXA value and are subsequently prescribed). And, these conditional 
probabilities may differ by group. In order to get into a groups (example, the osteoporosis 
treatment group, you must have been diagnosed as having osteoporosis, and, for medication 
treatment adherence, you must be on treatment. Thus, each group is determined, conditional on 
having the factor or event that gets them into the group. We will assess if the groups differ on 
either the rates or demographic/clinical characteristics, and, if necessary, we will employ ‘causal 
models’(1,2) to derive estimates of effect. If differential dissolution of PACTs is observed we will 
consider the negative binomial model in addition to the Poisson for the generalized linear and 
generalized linear mixed models analyses. We will be careful to control (by covariate control, 
weighting or 
propensity score 
matching) to make 
the groups 
conditionally equal. 
The parameter of 
interest will be the 
Group mean (and 
standard error) over 
time, and measured 
by the ‘average’ 
PACT value at each 
time point. Finally, 
we note that the 
estimation models 
above can be 
adapted to 
outcomes distributed other than normal, including Poisson (for number of events/time) and binary 
(for binary events). This is a 2 group by 3 

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yearly time point design. To control the overall Type-I error level, we will use the 
baseline time point as a baseline covariate, and assess group differences at the 
following time points controlling for baseline. Level of statistical significance will be set 
at 0.05 (two-tailed) for all tests. In this work, we proposed a GroupxTime interaction, 
using the time effects as classes/factors. Depending on the significance of this omnibus 
test, we can assess tests of individual differences (say, group differences at a specific 
point) by gate-keeping strategy. In the case where the omnibus group by time 
interaction is significant, then, these will be done without a Type-I error penalty. Initially, 
we will assess a Time by Group interaction (on 1 degree of freedom). If that effect is 
declared statistically significant, we will perform follow-up tests to determine where the 
group differences exist at each follow-up time point, using the gate-keeping strategy 
listed above. If the Group by Time interaction is not significant, then the main effects of 
Group and Time will be tested. 
Aim 3.  Prior Markov models 
of osteoporosis screening 
have been adapted for this 
study (Figure 6).28,29,87,88  A 
Markov cost-utility model 
with 6 health states will be 
constructed comparing 3 
different strategies of DXA 
screening, followed by 5 
years of treatment with 
alendronate (the most 
commonly prescribed 
medication) for those with a 
femoral neck T-score of 
<−2.5 or FRAX 10 year 
fracture risk above current 
treatment thresholds (3% 
hip, 20% major osteoporotic 
fracture). For the base-case 
analyses, the model will be 
run for five different starting 
ages (65, 70, 75, 80, and 
85) using Monte Carlo 
simulations with 40,000 trials 
each. Running the models 
for 5-year increments allows 
us to adjust the transition 
probabilities for observed 
differences over time (e.g., 
higher fracture rates or 
different adherence rates 
with older age). The health 
states in the model are no 
fracture, post distal forearm fracture, post clinical vertebral fracture, post hip fracture, 
post other fractures (humerus, scapula, ribs, pelvis, distal femur, pelvis, patella, tibia, or 
proximal fibula), and death. Following the recommendations of the 2nd Panel on Cost-
Table 5.  Data Sources for Aim 3 (see also Health Systems Policy 
Outcomes Section) 
Data Category 
Source(s) 
Proportion 
screened and 
treated 
Aggregated aim 1 results 
Medication 
adherence, 
persistence 
Aggregated aim 1 results 
Bone Mineral 
Density 
Random sample of 712 men (356 UC, 178 
each of the other 2 models) eligible for 
screening in panel at least 1 year, measured 2 
years after start date 
Treatment efficacy 
Published efficacy for bisphosphonates by 
medication adherence and persistence rates 
Fracture rates 
National VA data (preliminary results) 
Fracture costs 
National VA and CMS data including Fee 
Basis and CHOICE costs (preliminary results) 
Screening and 
Treatment costs 
Aim 2 results, current VA/CMS DXA cost, rare 
serious harm estimates from population data 
Fracture disutility 
Systematic review of disutility by fracture type 

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Effectiveness in Health and Medicine,89 we will analyze our model from both the VA and 
societal perspectives and present our results as an impact inventory.   
 
The direct and indirect costs of that fracture will be assigned as a transition cost. The 
disutility associated with these fractures will be modeled as a QALY decrement 
associated with that fracture state based on a published systematic review of fracture 
disutility rates90 and is assigned for 6 months upon which they return to baseline state, 
except for hip and vertebral fractures for which permanent disutility is the norm. If an 
individual suffers an additional fracture, the costs of that fracture are assigned, but the 
person remains in the post vertebral or post hip fracture state because the long-term 
disutility associated with prior vertebral and hip fractures is greater. Long-term care 
costs beyond the first year after hip fracture are assigned as a cost per year. Individuals 
in the model will be eligible (at risk) of transition to a different state once every 3 
months, and a maximum of 2 fracture types is assumed. We will parameterize our 
model using inputs derived from Aims 1 and 2 of the current grant and from the 
published literature. A discount rate of 3% will be assumed for costs and health benefits.    
 
      Treeage software will be used for analyses.  One-way sensitivity analyses will be 
performed varying discount rates, fracture rates, fracture costs, fracture disutility, costs 
of DXA, the onset  
and offset of fracture reduction benefit following initiation and cessation of drug therapy, 
medication adherence, the relative risks of fractures attributable to osteoporosis or prior 
clinical fracture, cost of screening and yearly bisphosphonate. Because of uncertainty 
regarding the nonvertebral fracture reduction efficacy of oral bisphosphonates for men, 
2-way sensitivity analyses will be performed assuming reduced fracture efficacy. 
Probabilistic sensitivity analyses will be performed using 2nd order Monte Carlo 
simulations in which each parameter value will be drawn from a distribution with 
characteristics specific to that parameter. For example, log-normal distributions of 
fracture direct costs and normal distributions of fracture rates and long-term care costs 
following hip fracture. The distributions of the relative risks of incident fractures 
associated with osteoporosis, prior fracture, and oral bisphosphonate therapy are 
assumed to be log-normal. Uniform distributions will be used to model variability in 
fracture disutility and indirect fracture costs. Results from the PSA will be presented as 
scatterplots on the cost-effectiveness plane and as cost effectiveness acceptability 
curves. 
Nominal Group Analysis.  During structured group discussion and voting, each nominal 
group generates a list of statements in response to each question, and rank orders 
them on order of importance.  To analyze the resulting data, we will first generate a 
spreadsheet for each question listing the group-generated statements, scores, and 
average score (total score/number of group members) by group.  The statements from 
each group will be entered into Atlas.ti, and content analysis used to generate themes 
recurring across groups. Themes will be generated independently by the PI who has 
extensive experience in qualitative analysis72-74,91-94 and the Project Director who will 
engage in additional qualitative training for this project (see budget justification).  A code 
book will be developed in an iterative manner, and confirmatory content analysis 
completed independently by co-investigator Lee to enhance reliability.  All statements 
will then be coded by at least 2 independent investigators.  Once the data is coded, final 
analysis will proceed in 2 steps. 1) Generation of top 7 themes for each question.  
Although each group responds to the same questions, because they work 

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Table 6. Power calculation assumptions for Aim 1 
independently the number, wording and order of the statements will be different.  Larger 
groups also have a wider score range than smaller groups. To address this issue we will 
use procedures described by van Breda95 to analyze data across groups. Using the 
coded data described above, we will calculate average scores for each theme by 
summing the total of statement scores for the theme divided by the number of 
statements in the theme. The top 7 themes will be listed for each question, along with 
exemplar statements. 2) Assessment of Implementation Variation.  We will examine 
variation in implementation by site and provider type in order to better inform 
dissemination.  Co-occurrence tables and matrices of the themes identified through 
content analysis as described above will be generated by site characteristics 
(urban/rural, academic/community) and provider type (medical/RN).  We will identify 
similarities and differences in the frequency of the themes, the ordering of the 
statements, and the discussion around the 
statements.   
Power. We estimate power using aim 1 
(patient level) outcomes. The power-limiting 
endpoint of interest is BMD. We can feasibly 
invite 100 patients for primary screening in 
each BHS team given DXA capacity and staff 
limitations. To achieve 90% power for our 
minimally clinically significant change in BMD, 
we will randomly select 25 (25%) from these 
patients and the top 100 highest risk patients 
in the Usual Care teams.  
Recruitment of 712 patients (19/team) will still 
provide 80% power to detect this difference. 
Power for the feasibility and acceptability 
endpoints exceeds 85% with this sample size. 
We expect a low ICC for patients within PACTs 
as patients are randomly assigned PACT 
provider, and based on prior studies of patient 
behavior change within primary care providers 
ICC<0.1.96 Our enrolled PACT teams all have 
>100 patients/panel eligible for osteoporosis 
screening, and we will select the 100 with 
highest risk based on the Osteoporosis 
Screening Tool calculation. We do not expect 
attrition as new patients are added as others leave with relatively constant panel size. 
Finally, we determine power for the single degree of freedom contrast of import – Usual 
Care vs. BHS groups across the follow-up time points. For each of the individual 
outcomes, assumptions and power requirements are listed in the Table. A sample size 
of 39 PACTs (19 BHS vs. 20 Usual Care) with an average 100 patients / PACT provides 
over 85% power for all our primary patient-level outcomes, except fracture rates - an 
exploratory analysis. 
 
Outcome 
Assumptions, 
Minimal Clinically 
Significant 
Difference 
Power for 39 
PACTS and 
3900 
patients 
Screening Rates 
(PACT level) 
6% Usual Care, 
40% new models 
>0.99 
Osteoporosis 
Treatment 
Assume 25% of 
screened meet 
treatment 
thresholds. 30% 
increase from 55% 
Usual Care 
>0.99 
Medication 
Adherence 
Usual Care MPR 
0.60 (SD 0.35). 
20% increase 
0.85 
Bone Mineral 
Density (BMD) 
Femoral Neck 
in random 
sample of 
high-risk 
patients 
0.939 g/cm2 in 
BHS group vs. 
0.967 Usual Care 
with 
SDpooled=0.133 
0.90 for 
random 
sample of 
952 patients 
(25/team); 
0.80 for 712 
(19/team) 

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Missing data Strategies.   As is standard in administrative databases, the absence of a 
diagnosis code (e.g., fracture) will be assumed to indicate that the event did not occur, 
and coded by default as ‘not present’.  For continuous measures where zero is illogical, 
we will impute a value, simulate and use bootstrapping to derive estimates of effect with 
appropriate standard errors. To implement the multiple imputation techniques for 
primary analyses, we will use preliminary analyses of such associations, including 
graphical displays, to investigate the plausibility of the assumptions underlying the 
imputation model employed.97  Further, we will use 25 or more imputed data sets, with 
FU bootstrapped estimates in order to  reduce the impact of the random sampling.  

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Privacy, Confidentiality, and Information Security 
1. Lists of Data Reviewed and/or Collected for Screening/Recruitment and 
Conduction of Study:  
The Personal Health Information that will be obtained, used, and/or shared for this study 
includes:   
Identifier(s) 
Source(s) of Health Information 
 Names 
 Medical history & physical exam 
information 
 All geographic subdivisions smaller than 
a State, including street address, city, 
county, precinct, and zip code.  Describe: 
VAMC/CBOC location 
 Photographs, videotapes, audiotapes, 
or digital or other images 
 All elements of dates (except year) for 
dates directly related to an individual, 
including birth date, admission date, 
discharge date, visit or treatment dates, etc.; 
and all ages over 89,  Describe: fracture date, 
prescription fill dates, birth date,  DXA testing 
date, death date 
 Biologic specimens (e.g., blood, 
tissue, urine, saliva). Describe: 
 Telephone numbers 
 Progress notes 
 Fax numbers 
 Diagnostic / Laboratory test results 
 Electronic mail addresses (staff only) 
 Operative reports 
 Social Security Numbers 
 Imaging (x-ray, CT, MRI, etc.) 
 Medical record numbers 
 Discharge summaries 
 Health plan beneficiary numbers 
 Survey / Questionnaire responses 
 Account numbers 
 Billing records 
 Certificate and/or license numbers  
 HIV testing or infection records 
 Vehicle identifiers and serial numbers, 
including license plate numbers  
 Sickle cell anemia information 
 Device identifiers and serial numbers 
 Alcoholism or alcohol use information 
 Web Universal Resource Locators 
(URLs) 
 Drug abuse information 
 Internet Protocol (IP) address numbers 
 Mental health (not psychotherapy) 
notes 
 Biometric identifiers, including finger & 
voice prints 
 Psychological test results 
 Full-face photographic images and any 
comparable images 
 Genetic testing 
 Any other unique identifying number, 
 Other, describe:        

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Identifier(s) 
Source(s) of Health Information 
linked study ID, characteristic, or code, 
describe:  A unique study ID to link patient 
direct identifiers, maintained in a separate file, 
to the other study data. 
 
2. Data and/or Specimen Acquisition:   
Data for this study will be collected through: 
  Prospective data and/or specimen collection obtained from participants.  Provide 
description of processes:   
Prospective data collection is for consented staff only.  The Nominal Group 
Technique combines quantitative and qualitative data collected from small groups of 8–
20 people to rapidly generate a prioritized list of responses to specific questions during 
a 45–60 minute facilitated meeting. Purposive sampling will be used to include at least 2 
representatives from different PACTs assigned to each of the 3 interventions for an 
estimated 10 sessions including at least 1 provider from all 36 PACTs.  The nominal 
group technique will include four steps: (1) each participant writes responses to specific 
questions posed by the facilitator; (2) responses are anonymously recorded in a round-
robin fashion, with brief discussion for clarification if needed; (3) similar responses are 
grouped into themes through group discussion; (4) each person records the 5 most 
important themes identified in step 3, in order of importance to that individual. Questions 
will elicit providers’ perceived barriers and facilitators to osteoporosis care, experience 
with their assigned model, and estimated time spent per month. See grant Appendix 2 
for the nominal group protocol. 
Beginning in year 4, Veterans will be randomly selected to complete a bone density 
scan. Study staff will collect information from the medical record and scan results. 
  Retrospective data collection and/or specimens obtained from medical chart 
review/data access.  Describe how data will be obtained (e.g., fileman, CDW, etc.):  For 
Veterans within enrolled PACT teams only.  Data is obtained through CDW queries 
(SQL) and manual abstraction from CPRS.  At the completion of data collection, a 
limited dataset with direct identifiers removed will be created, and a cross-walk file 
maintained in a separate location.  Data will not be fully de-identified. 
  Retrospective data collection and/or specimens obtained from an IRB-approved 
data and/or specimen repository.  Indicate the repository source including name, VA 
location, and IRB number:       . 
3. Level of Data:   
The following level(s) of data will be acquired/maintained for this study (check all that 
apply): 

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  Identified (e.g., names, addresses or other identifiers included)  
  Coded (direct and/or all identifiers removed, but study code/ID included)  
  De-Identified (all HIPAA 18 and study ID/code removed): 
  Verified Statistically  
 
OR 
  Verified by Absence or Removal of HIPAA 18 and study ID  
  Limited Data Set 
  Other: Describe:        
 
4. Location of Data and/or Specimens, and Data Retention Plan:   
A. Data and/or Specimen Location:  
Data will be stored electronically in 
\\vhadurhsmcifs01.v06.med.va.gov\DURHAM_HSRD_P\MOPS.  Data that will be stored 
electronically are listed in the “Outcome Measures” and “Covariates” sections, and 
summary results from provider nominal group techniques.    
Paper records of data include staff demographic surveys.  They will be stored in a 
locked cabinet in the DVAHS Geriatrics Research Education and Clinical Center 
(GRECC) room N3006, Durham VA Hospital. 
There are no biological specimens.  
  Data will be also be placed at the VA Informatics and Computing Interface (VINCI; 
http://vaww.vinci.med.va.gov/vincicentral/VINCIWorkspace.aspx). The VA Informatics 
and Computing Infrastructure is a partnership between the VA Office of Information 
Technology and the Veterans’ Health Administration Office of Research and 
Development.  Researchers and operations staff can use VINCI to access data and 
statistical analysis tools in a virtual working environment through a certified VHA 
network computer using the VA Intranet or Virtual Private Network (VPN).  
B. Data Retention Plan 
 Research records will be maintained and destroyed according to the National 
Archives and Records Administration, Records Schedule Number:  DAA-0015-2015-
0004.  Records destruction, when authorized, will be accomplished using the then 
current requirements for the secure disposal of paper and electronic records.  Currently, 
destruction of research records (see DAA-0015-2015-0004, section 7.6 “Research 
Investigator Files” for materials included in research records) is scheduled for 6 years 
after the cut-off (the cut-off is the completion of the research project) and may be 

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retained longer if required by other federal agencies.  Records will not be destroyed 
without pre-notification to the facility records manager.    
  Other data retention plan, describe:        
5. Data Access and Data Recipients:   
Only members of our DVAMC research team will have access to identifiers and coded 
data.   
 
All VA research personnel who have access to VHA records are instructed, in 
accordance with VA policy, on the requirements of Federal privacy and information laws 
and regulations, VA regulations and policies, and VHA policy. All study personnel who 
are VA employees working within the VA system have fulfilled all required HIPAA and 
other VA security and privacy policy training requirements and have agreed to follow 
guidelines pertaining to the protection of patient data. All research staff sign VA Rules of 
Behavior, and all study staff are up-to-date with VHA Privacy Policy Training and the VA 
Office of Cyber and Information Security Awareness Training Course. The data security 
and privacy procedures summarized in that course include logging off or locking the 
computer when walking away from it; no sharing of access codes, verify codes or 
passwords; not allowing anyone else to use the computer under one’s password; and 
disposing of sensitive information using VA-approved methods (e.g., shredder bins). 
Access to study data will be removed for all study personnel when they are no longer 
part of the research team.  
 
6. Data and/or Specimen Transportation and/or Transmission for all data and/or 
specimens involved in the study:   
 
I. 
  Data and/or specimens will not be transported or transmitted outside of 
Durham VAMC environment. 
II. 
  Data and/or specimens will be transported BETWEEN sites that are under 
the auspices of the Durham VA Medical Center.  Study staff may transport paper 
staff demographic information forms back to the DVAMC GRECC from 
Community Based Outpatient Clinics.  Forms will be kept in an envelope in the 
staff’s briefcase at all times during transport.  Forms may also be sent via VA 
intra-office mail in sealed envelopes marked “confidential”. 
III. 
   Data and/or specimens will be transmitted to other VA sites using the 
following method(s): 

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A. Data 
  Data are de-identified and thus will be sent via unencrypted e-mail or 
unencrypted disk (encryption is optional). 
  Data are coded or contain identifiers and thus will be sent  
  Other, describe:        
B. Specimens 
  Specimens are de-identified and thus will be sent via standard carrier 
(tracking is optional). 
  Specimens are coded or contain identifiers and thus will be sent via VA-
authorized carrier with tracking.   
  Other, describe:        
IV. 
  Data and/or specimens will be transported to non-VA/VHA sites (e.g., 
academic affiliates, laboratories, etc.) using the following method(s): 
A. Data 
  Data are de-identified and thus will be sent via unencrypted e-mail or 
unencrypted CD. 
  Data are coded or contain identifiers and thus will be sent via using VA—
approved carrier with tracking.   
  Data are coded or identified and will be sent via the Safe Access File 
Exchange (SAFE) at https://safe.amrdec.army.mil/safe/.  SAFE is a secure 
method of exchanging files <2GB to and from individuals with a valid .gov, 
.mil, .com, or .edu email address.  
  Data are coded or identified and will be uploaded to sponsor website 
using electronic case report form (eCRF) 
 Other, describe:       
B. Specimens 
  Specimens are de-identified and thus will be sent via standard carrier 
(tracking is optional) or will be hand-delivered by research study personnel.  
Specify method of delivery:        
  Specimens are coded and thus will be sent via VA-approved carrier with 
tracking or will be hand-delivered by research study personnel.  Specify 
method of delivery:        

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In accordance with the HIPAA and the Privacy Act, for any coded or identifiable data or 
specimens released from the Durham VAMC (with the exception of Limited Data Sets), 
an Accounting of Disclosure (AOD) will be maintained (e.g., in a database or 
spreadsheet) that includes the participant’s name, date of the disclosure, description of 
the nature of the Individually Identifiable Information (III) disclosed, purpose of each 
disclosure, and the name and address of the person/agency to whom the disclosure 
was made. 
C.      
 Local DVAMC memorandum “Authorization to Use, Process, Store, or 
Transmit VA Sensitive Information Outside VA Owned or Managed Facilities” has 
been pre-filled out for each study team member who may transport the data 
and/or specimens off-site.  This (these) forms are included with the IRB 
materials.   
D. 
  Containers (e.g., briefcase, bin) are labeled with the following notice (label 
placed on the outside of container) in accordance with VHA Directive 6609: 
NOTICE!!! 
Access to these records is limited to: AUTHORIZED PERSONS ONLY. 
Information may not be disclosed from this file unless permitted by all applicable 
legal authorities, which may include the Privacy Act; 38 U.S.C. §§ 5701, 5705, 
7332; the Health Insurance Portability and Accountability Act; and regulations 
implementing those provisions, at 38 C.F.R. §§ 1.460 – 1.599 and 45 C.F.R. 
Parts 160 and 164. Anyone who discloses information in violation of the above 
provisions may subject to civil and criminal penalties. 
 
V. 
  We will communicate with veterans enrolled as participants in this research 
study through MyHealtheVet.    
 
7. Risk Mitigation Strategies:   
The PI, statisticians, and study coordinator bear primary responsibility for overseeing 
privacy and security of research data.  Risk mitigation strategies include: 1) developing 
a limited dataset with direct identifiers maintained separately in a cross-walk file as soon 
as data collection is completed; 2) restricting access to folders containing research data 
to approved Durham VA personnel only; 3) individual research data will be used only by 
VA entities for analyses to complete study aims; 4) not transmitting individual data 
outside VA protected environment; 5) never storing research data on a computer hard 
drive or mobile device. 

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  Data are fully de-identified (stripped of HIPAA 18 and study ID/code) before being 
shared outside of Durham VAMC. 
  Specimens are fully de-identified (stripped of HIPAA 18 and study ID/code before 
being shared outside of Durham VAMC. 
  Direct identifiers will be maintained separately from data and or specimens by using 
a code to “identify” subjects.  In a separate database (i.e., a “linking” or “cross-walk” 
database) this code will be linked to identifying subject information.   
  Other, specify:        
8. Suspected Loss of VA Information: 
Should any incident such as theft or loss of data, unauthorized access of sensitive data 
or non-compliance with security controls occur it will be immediately reported according 
to VA policy. All incidents regarding information security/privacy incidents will be 
reported to the ISO and PO within 1 hour of acknowledgement of issue and done so 
using the VHADUR Research Events Report e-mail group 
(VHADURResearchEventReport@va.gov). 
9. Reporting of Results:   
  Reporting of results, such as in scientific papers and presentations, will never 
identify individual subjects.  Data will be presented in aggregate and individual-level 
data will not be published. 
  Other results reporting plan, describe:       
10. Future Use of Data: 
  Data will be retained for future use.  This is described elsewhere in the protocol and 
is noted in the HIPAA authorization. 
 
  Future Use of data is optional (i.e., not required by the research subject). 
  Future Use of data is required for participation in the study. 
  No future use of data is currently planned. 
11. Use of Mail Merge Technology 
  Mail merge programs will be used to generate letters and/or address labels for 
mailings to potential or already enrolled research subjects.  The study team is aware 
that to reduce risk of mail merge related privacy incidents, use of mail merge programs 
requires a 25% accuracy check to verify that (potential) research subject name and 

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mailing address are properly “matched”.  If discrepancies are found, a 100% accuracy 
check is required before letters may be mailed.   
12. Use of Non-Standard Software 
 I do NOT intend to use any new specialized software (i.e. Software that’s not already 
approved OR installed) in this study. 
 
 I intend to use specialized software that has not already been installed and it has 
been approved for use by the VA Technical Reference Model (TRM) Group.  
(Note: All new software must be approved by TRM before it can be installed on VA 
systems.) 
 
 I intend to use previously installed software on my VA computer.  
 
13. Use of Cloud Computing Services 
 Cloud computing services will NOT be used in this study. 
 
 Cloud computing services WILL be used in this study as described below and have 
been approved nationally by the VA Chief Information Officer (CIO).  (Note: ONLY cloud 
computing services that have been approved nationally may be used.) 
 
References 
1. 
Cummings SR, Melton LJ. Epidemiology and outcomes of osteoporotic fractures. 
Lancet. 2002;359(9319):1761-1767. 
2. 
Fox K, Hawkes W, Hebel J, et al. Mobility after hip fracture predicts health outcomes. J 
Am Geriatr Soc. 1998;46(2):169-173. 
3. 
Haentjens P, Magaziner J, Colon-Emeric CS, et al. Meta-analysis: excess mortality after 
hip fracture among older women and men. Ann Intern Med. 2010;152(6):380-390. 
4. 
Krall E, Miller D, Watkins B, Rourke A. Prevalence of osteoporosis and osteopenia in 
male veterans. 128th Annual Meeting of APHA 2000; Boston, MA. 
5. 
Ohldin A, Floyd J, Ohldin A, Floyd J. Unrecognized risks among Veterans with hip 
fractures: opportunities for improvements. J South Orthop Assoc. 2003;12(1):18-22. 
6. 
Wells GA, Cranney A, Peterson J, et al. Alendronate for the primary and secondary 
prevention of osteoporotic fractures in postmenopausal women. Cochrane Database 
Syst Rev. 2008(1). 
7. 
Zhong ZM, Chen JT, Zhong Z-M, Chen J-T. Anti-fracture efficacy of risedronic acid in 
men: A meta-analysis of randomized controlled trials. Clin Drug Investig. 
2009;29(5):349-357. 
8. 
Orwoll  E, Ettinger  M, Weiss  S, et al. Alendronate for the Treatment of Osteoporosis in 
Men. N Engl J Med. 2000;343(9):604-610. 
9. 
Orwoll ES, Miller PD, Adachi JD, et al. Efficacy and safety of a once-yearly i.v. Infusion 
of zoledronic acid 5 mg versus a once-weekly 70-mg oral alendronate in the treatment of 
male osteoporosis: A randomized, multicenter, double-blind, active-controlled study. J 
Bone Miner Res. 2010;25(10):2239-2250. 

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10. 
Bolland MJ, Grey AB, Gamble GD, Reid IR. Effect of osteoporosis treatment on 
mortality: a meta-analysis. J Clin Endocrinol Metab. 2010;95(3):1174-1181. 
11. 
Lyles K, Colón-Emeric C, Magaziner J, et al. Zoledronic acid and clinical fracture and 
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