Shared Decision Making to Improve Palliative Care in the Nursing Home
Phase: NA
Conditions: Pain
Sponsor: Washington University School of Medicine

 
 
2015.11.16 
Version 1 
Debra Parker Oliver, MSW, PhD 
IRB 2003012 Title Shared Decision Making to Improve Palliative Care in the Nursing Home 
Protocol 
 
Purpose 
Our team is using web-conferencing technology to facilitate shared decision making (SDM) between families of 
hospice patients and hospice staff (1R01NR011472). Family members of hospice patients living in nursing 
homes in our current study suggested we translate this intervention to the nursing home.10,20 Based on this 
family-identified need, this proposal facilitates SDM among family members, residents with serious illnesses 
(not enrolled in hospice), and the nursing home care team. Our overall research question (RQ) is: What are 
the effects of a SDM process in care conferences via web-conferencing on family members and 
nursing home residents with serious illnesses? Our overall hypothesis (H) is: SDM among family 
members, residents (when possible), and skilled nursing home staff via web-conferencing will improve 
outcomes for family members and residents with serious illnesses. 
 
 
Objectives 
 
1. To explore the experience of SDM for family, residents, and nursing home staff. 
RQ 1. What are the facilitators and barriers to SDM in the nursing home? 
RQ 2. What shared decisions will be made with family/residents during care conference meetings? 
RQ 3. What concerns are communicated by families/residents to nursing home staff? 
RQ 4. How will participation in web-conferencing impact the family/resident satisfaction with care? 
 
2: To assess the outcomes of SDM using web-conferencing on families/residents. 
H1: Family depression (Patient Health Questionnaire-9) will be lower in the intervention group than in the 
control group. 
H2: Family burden (Zarit Burden Interview) will be lower in the intervention group than in the control group. 
H3: Resident pain (Minimum Data Set 3.0) will be lower in the intervention group than in the control group. 
H4: Family members’ satisfaction will be higher in the intervention group than in the control group. 
H5: The number of web conferences attended will be positively associated with improvements in outcomes. 
H6: SDM instruments will demonstrate adequate reliability and validity within a nursing home setting. 
 
 
Research Design and Method: We propose a P-RCT for this pilot study. Nursing home residents and their 
identified family member in one nursing home (The Bluffs) will be randomized into either an enhanced usual 
care group or an intervention group. Our purpose is to look at the intervention in a real-world context to allow 
evaluation of feasibility in the actual setting. This trial meets the definition of pragmatic because its inclusion 
criteria are broad, staff receive training in the intervention but are not required to strictly comply with every 
element of SDM in every conference, the intervention is applied by the entire nursing home team, the 
enhanced care training will be given to all clinical staff without restriction, the primary outcome is a clinically 
meaningful one, and the analysis will include all participants in an intention-to-treat fashion.63,64 Enhanced 
usual care as a comparator is appropriate when the goals of a trial are pragmatic rather than explanatory.65 
Family in the enhanced usual care group will not participate in a SDM process but staff will be trained.  
 
We will collect measures with families of both groups upon consent and every thirty days for a minimum of 
90 days and a maximum of 240 days, depending upon the length of time they are enrolled in the study before 
data collection is concluded. Resident measures will be recorded following each MDS assessment. We will 
recruit 23 residents and their family members in each group for a total sample of 46 residents and 46 family 
members (See Section D.7.2.1). If more than one family member enrolls then we will need fewer residents, as 
our total of 46 family members will be reached more quickly. Inclusion/exclusion criteria are summarized in 

Table 2 and explained fully in Section E. Family members will be identified by either the residents or the 
nursing home staff; a resident may have more than one family member enrolled. Based on intervention trials in 
the nursing home,19 we will assume a 15% attrition rate (Section D.7.2.1). Nursing home staff will also be 
research subjects and will assist in the evaluation of the intervention through qualitative interviews. The 
analysis of care conferences will include video-recording staff interactions, and a final interview to assess staff 
satisfaction with the project. We will interview 5 staff in each year of the project for a total of 10 interviews. 
 
Intervention: The purpose of our intervention is to enable and facilitate family member involvement in care 
planning conferences with a SDM process. Web-conferencing technology will enable remote participation. 
Based on experience from our preliminary work (publication in review), a SDM process will be incorporated into 
the care plan meeting to facilitate meaningful involvement. We will use VSee as the web-conferencing 
software. VSee uses open industry standard, FIPS 140-2 compliant 256-bit AES encryption on all control and 
media traffic. Only the people participating in a conversation can decrypt data passed through VSee 
conversations.66 VSee is often referred to as “telemedicine” videoconferencing tool and has been endorsed by 
numerous health care systems and organizations throughout the country (including Stanford Hospitals and 
Clinics, Trinity Health, Intermountain Healthcare etc). (http:vsee.com). See Section E. 
 
Intervention Group: Per regulation, residents will continue to be encouraged to attend their care 
conferences on-site, as is the current standard of practice. At least one member of the research team will be 
on-site for each care conference to facilitate the technological aspects of the intervention. Family members in 
the intervention group will use a web-enabled device (computer, smartphone or tablet) to virtually participate in 
the care conference. To prepare family members for the intervention, we will produce a short video that will 
train family members on the use of VSee, provide an overview of care planning conferences, offer 
recommendations to enhance web-based communication, and discuss the process of shared decision-making. 
A member of the research team will contact each participating family member at least 24 hours prior to the 
scheduled care conference to confirm their participation, answer questions, and provide an approximate time 
the nursing home team will be contacting them to initiate the web-conference. Time zone differences will be 
considered in the scheduling when possible. In addition, the research staff member will have a cell phone on-
site during the care conference to allow the team to contact the family member via phone if necessary to 
provide just-in-time instruction on the use of the web-conferencing technology, as needed. Our team’s five 
years of experience facilitating web-conferencing between families and health care teams in non-nursing home 
settings have allowed us to develop these procedures, which have been successful. After successful contact 
with the family member, research staff will take on the role of observer, completing detailed field notes during 
each care conference. In addition, research staff will video-record a sample of 4 conferences per month (76 
total) to allow for detailed analysis of the conferences. All clinical staff will attend a quarterly SDM training 
session, will be given reference cards outlining the SDM process, and a poster with the elements will be placed 
in the conference room for reference. Staff will be trained to use the SDM process when interacting with family 
or residents, however, given the pragmatic nature of this study, staff will be encouraged and supported to use 
the SDM process but not required to do so.  
 
Enhanced Usual Care: Usual care will be enhanced with the training provided to all clinical staff in 
SDM. Family members assigned to the enhanced usual care group will not be involved in the web-
conferencing and are by definition of the inclusion criteria unable to attend the care conference. They will not 
be offered web-conferencing access to the care conference. Interactions among the family member, resident, 
and staff will not be scheduled, initiated, or facilitated by the research staff. Research staff will observe care 
conferences for enhanced usual care participants to compare staff behaviors and attitudes.  
 
Data Collection: Research staff will contact family members in both the intervention and enhanced usual care 
groups every 30 days to collect data using the same measures (Table 3) for both groups. Additionally, for both 
groups, research staff will extract selected elements (Table 3) from all MDS assessments completed during a 
resident’s participation in the study. Finally, family members and residents (when able) in both groups will be 
interviewed following study completion using a semi-structured interview guide. A sample of facility staff will be 
interviewed each year of the study. See Appendix. 
 
Consent/enrollment: The study will be presented to nursing home staff in a staff meeting. A special effort will 
be made to promote attendance at a resident/family council meeting to explain the study, obtain resident 
feedback and promote enrollment. Brochures will be developed to encourage participation and referral. Similar 
to our prior work, nursing home staff members will identify residents who meet the study inclusion criteria and 

request verbal permission from residents or their family members to provide their contact information to the 
research team.46,67  
 
Protection of Human Subjects 
Human subjects will include nursing home residents, their designated family member(s), and nursing home 
staff. The total participants for this trial will be 102; 46 residents and 46 family members (23 residents and 23 
family in each group) and approximately 10 nursing home staff. The participants must meet inclusion criteria to 
ensure the effectiveness of the intervention and reduce any potential risks or burdens to them. 
 
Family Members 
Family members will be the primary focus of the research and primary pool of research subjects. The first 
criterion is that they be identified by the nursing home resident or nursing home staff as a family member or 
significant other of a resident at The Bluffs. A second criterion is that the family member must be over the 
age of 18 to formally consent to participate in the study. Although 18 is considered a child by NIH, it is the 
minimum age for proxy decision-making in the state of Missouri. Thirdly, the designated family member must 
not have a cognitive impairment that interferes with their ability for shared decision-making on behalf of the 
resident. This will be determined by the nursing home staff. The fourth criterion is that the family member has 
access to a computer, tablet, or smartphone device that supports web-conferencing. The pilot nature of this 
project and the budget limitations prevent us from providing this technology to family members. While research 
in technology continues to show the increased access to these technology resources,37 we appreciate that not 
all families may have access. One of the secondary outcomes from this pilot will be determining the degree to 
which Internet and technology access is an issue. If access to technology is an issue in this pilot, a plan will be 
created and budget will be available in the follow-up trial for affordable solutions permitting access and 
participation. The fifth criterion is that the family member is otherwise unable to attend the care conference 
onsite at the nursing home due to travel distance, employment restrictions, etc. The intervention is focused on 
allowing those who would otherwise be unable to participate in care conferences the opportunity to do so. 
Should a family member’s situation change and they become able to routinely attend conferences in person, 
they will be dis-enrolled from the study as they no longer would meet this criterion.  
 
Residents 
The first criterion requires that a nursing home resident live at The Bluffs nursing home. The second 
criterion requires residents be at least 65 years of age. Currently, the majority of nursing home residents are 
over 80 years of age. Seniors are the focus of the NIH Program Announcement (PA 13-355) for this proposal 
to improve geriatric palliative care. A third criterion is that the resident has at least one family member or 
significant other who will participate in the shared decision-making process. The fourth criterion requires that 
the resident, as determined by the nursing home staff, has a serious illness, making them appropriate for 
palliative care. 
 
In addition to these four inclusion criteria, there are two criteria that will exclude residents from the 
study. The first exclusion criterion involves residents who are admitted to the skilled nursing facility for short-
term post-hospital care with the goal of returning home. These residents do not represent the long-stay nursing 
home population, and their length of stay in the nursing home will not allow for evaluation of the research 
questions or testing of the hypothesis. The second exclusion criterion involves residents enrolled in 
hospice care at the time of study enrollment. The Program Announcement (PA 13-355) supporting this 
proposal specifically excludes hospice patients from the available funding. If a study resident enrolls in hospice 
while already enrolled in our study, they will not remain in our study. 
 
Residents with cognitive impairment may participate in the study. We will use a reasonable person 
approach to determine a resident’s understanding of the research. As a low risk study, this approach allows us 
to determine if the resident seems to grasp the concepts of the study and determine if their responses are 
appropriate and make sense. Dr. Popejoy has used this approach previously. If the research specialist in 
consultation with the nursing home staff evaluate the resident and determine they understand the concepts of 
the study, they will be asked to sign a consent form. If however the research specialist and nursing home staff 
to not believe the resident can understand the study, then their surrogate decision maker or designated family 
member will be asked to consent on their behalf.  
 
 Nursing Home Staff 
 
Finally, nursing home staff will also be study subjects. As residents and family members become more 

active in the decision-making process, staff may need to change their behaviors to support the process 
changes. 42,43 Thus, the comprehensive evaluation of the SDM intervention we propose will examine outcomes 
not only for residents and family members, but also for the nursing home staff involved in the project. The first 
criterion will be that they are employees at The Bluffs nursing facility. We will observe and video-record the 
staff during their interactions with residents and families during the care conferences. All nursing home staff 
involved in the project will be asked to sign a consent form to participate. While involvement in the care 
conference and addressing family issues is a part of the nursing home residents’ bill of rights and the staff 
members’ job descriptions, they are not required to be video-recorded or interviewed. We have successfully 
addressed this issue in our preliminary work38 and have outlined this process in the consent section below. 
The second criterion requires staff to be over the age of 18, the youngest age that a staff person may be 
employed in a nursing home. Finally, staff must hold a position which makes them a part of the care team and 
a participant in the care conference or direct care of a resident (aide, nurse, social service, dietary, etc.) 
 
Protection against risk 
Resident and family confidentiality and comfort with the technology are protected, for they must agree before a 
web-conference connection is made. We have chosen the videoconferencing solution called VSee (Vsee Inc, 
Sunnyvale, CA) which is free to download and use for both personal and commercial use (similar to Skype). 
While both Skype and VSee are free videoconferencing systems, VSee is considered more secure. VSee uses 
open industry standard, FIPS 140-2 compliant 256-bit AES encryption on all control and media traffic. Unlike 
Skype, VSee uses RSA public/private key to exchange the AES session key such that the VSee servers do not 
have access to the AES session key. For this reason, VSee is often referred to as “telemedicine” 
videoconferencing tool and has been endorsed by numerous health care systems and organizations as a 
videoconferencing tool throughout the country (including Stanford Hospitals and Clinics, Trinity Health, 
Intermountain Healthcare etc.) (http:vsee.com). VSee uses open industry standard, FIPS 140-2 compliant 256-
bit AES encryption on all control and media traffic. Unlike Skype, VSee uses RSA public/private key to 
exchange the AES session key such that the VSee servers do not have access to the AES session key. This 
means only the people participating in a conversation can decrypt data passed through VSee conversations 
(whereas Skype has the ability to monitor individual conversations).66 In a study by the Office of High 
Performance Computing and Communications at the NIH National Library of Medicine, investigators concluded 
that “VSee provided secure encrypted video that looked superior to other low-bandwidth products.” 66 
 
A leadership resource at MU provides us with an additional layer of protection. Our Senior Associate Dean for 
Information Technology has a background in information security, and assurance of data security is part of her 
role. Finally, all resident/family information taken from the nursing home will be “de-identified” with a coding 
schema rather than names. All research data that leave the nursing home will be maintained in a locked file 
cabinet in the PI’s office. No transcription shall contain the name of a resident, family member or staff member. 
 
Consent and Enrollment 
Upon referral from the nursing home staff, research staff will contact the resident or his/her family member 
surrogate decision-maker, explain the study, enroll the resident, and identify appropriate family member(s) to 
participate. Residents will be randomized and family members will receive the same group assignment as their 
resident. Family member(s) will be referred by the resident, nursing home staff, or other family members. More 
than one family member may participate, and all members of the same family will be assigned to the same 
group. Participating residents who are able to sign a written consent form will do so (see Section E.1.2 for 
protocol with impaired residents), and baseline measures for residents will be obtained from the most recent 
MDS. Enrollment will not be considered final until we obtain the written consent of both resident (or his/her 
surrogate decision-maker) and family member. Following consent of the resident/surrogate, research staff will 
contact the family member(s) identified as potential study participants (if different than the surrogate), explain 
the study, and obtain oral consent for their participation. Family members will be asked to go to a secure 
website to electronically sign a consent form as approved by MU HSIRB. Nursing home staff consent will be 
obtained for anyone involved in care plan meetings. Nursing home staff will sign a consent form that will permit 
video-recording of their participation in care conferences and audio-recording of their follow-up interviews. In 
our previous work we have had no staff members opt out of any aspect of the study. Draft consent forms are in 
the Appendix. 
We anticipate that 10 nursing home staff will be involved in the study. We will observe and randomly video-
record staff as they interact with families during team meetings. As in our preliminary study, all staff members 

will be asked to sign a consent form with three levels of consent (see appendix). We recognize that coercion is 
a potential issue and have developed a plan to address the concern. The consent process is designed so staff 
members have time decide whether and how much to participate. Our Research Specialists will meet 
individually and privately with each staff member during the consent process or during their orientation to the 
nursing home. Research Specialists will explain the study and consent without making the administration or 
other staff aware of who has and has not consented.  
 
Because staff must participate in care plan meetings as part of their job, study consent involves (1) 
being video-recorded in care plan meetings, (2) having their image appear on the Internet and, (3) participating 
in a post-study interview. During our preliminary trial, all of the 115 hospice staff approached consented to all 
three options. Staff members do not need to consent to participate in the study to participate in care plan 
meetings. In recognition of staff members’ right not to participate in the study, we have developed a multi-level 
consent process, allowing them to specify their involvement. The staff consent form will designate each option 
separately and will be kept confidential. Should a staff member refuse to be recorded during care plan 
meetings and communications with family, then those family will not be among the cases we record (we will 
video record a 25% subsample of family in both groups per quarter). Should a staff member refuse to have 
their image displayed on the Internet, they can choose not to sit in sight of the camera and thus prevent the 
image from being sent to the family. They also can decline to be interviewed post-study. Research staff will 
know the individual conditions of staff consent but other nursing home staff and administration will not. In 
appreciation for the staff time and commitment, we will issue tickets for an annual lottery drawing held in each 
agency. The winners will receive $100 cash. 
 
Potential Benefits of the Proposed Research to the Subjects and Others 
The proposed project can improve nursing home services by empowering family members to be more actively 
involved in the care of their loved one. The web-conferencing technology allows family to participate in the 
nursing home care discussions and express their concerns, goals, and values as the plan of care is developed 
and modified. 
 
Importance of the knowledge to be gained 
This project will evaluate the value of family members formally participating in the development and delivery of 
care to their resident in a nursing home, and sharing in decisions related to that care. The underlying concept 
is that, with the help of the web-conferencing to bridge geographic distances, family can enter into discussions 
related to resident needs and ensure that the care and decisions made align with the resident 
values/beliefs/goals. The knowledge gained from this project will allow the research team to develop a future 
study that utilizes the intervention in more homes and potentially across various long-term care settings. 
 
Data Monitoring Plan  
Data will be collected using standardized paper forms and will only be identified with the study’s arbitrary ID 
number for the participant. Codes that link the name of the participant and the study ID will be kept confidential 
in a secured cabinet. Collected forms will be transported to the PI’s office once per week for permanent 
storage in a locked office. The research staff will enter data from the forms into the electronic database. The 
data manager, based on source documents, will report apparent data discrepancies and seek staff input for 
correction. Data and protocol concerns will be addressed through the research team. Larger concerns with the 
protocols may be forwarded on to institutional committees depending on the severity of the issues. Fidelity of 
the intervention will be monitored through quarterly observations by the PI or her designee and through 
ongoing qualitative analysis of video recordings. Data quality will be monitored by random inspection of the 
completed forms by the data manager, and any problems detected will be discussed with the PI and research 
team. 
Safety Monitoring Plan  
During screening, study applicants will be assessed to determine their eligibility and safety of their participation 
in this study. Research staff will collaborate with the nursing home nurse to assess the appropriateness of the 
resident and their alignment with the inclusion/exclusion criteria. We will use the HSIRB definition of serious 
adverse events (SAEs). The IRB understands that this definition is unusual in nursing homes and with 
residents with serious illness, where deaths are not considered an SAE because death is not unexpected. Any 
SAE related to the study intervention will be reported to the IRB. The initial SAE report will be followed by 
submission of a completed SAE report to the MU HSIRB. Outcomes of SAEs will be reported periodically to 

NIH. A summary of the SAEs that occurred during the previous year will be included in the annual progress 
report to NIH. 
 
 
 
 Measures 
 
 
Qualitative analysis: Qualitative analysis will proceed simultaneously and continuously with data collection, 
allowing for pertinent revisions to be made to the observation protocol and interview guide as the study 
proceeds.77 Researchers will begin analysis by applying codes to segments of data that address the study 
research questions (Table 4). Early coding will be guided by the initial coding framework detailed in Table 4; 
however, the framework will be refined and expanded as needed during the process of data analysis. 
Researchers will use NVivo 10 software, which permits direct coding of audio and video files, eliminating the 
need for transcription. After agreement has been reached on the final coding framework and corresponding 
definitions, two investigators will code the same data files (which will comprise 10% of the full data set) and use 
NVivo 10 to calculate a Kappa statistic for inter-coder reliability. If inter-coder reliability is 80% or greater, they 
will divide the remaining files and independently code the remaining data. If inter-coder reliability is less than 
80%, they will repeat co-coding with an additional 10% of the data files, repeating this process until satisfactory 
reliability is achieved. A coding matrix summarizing data for each research question will be generated. 
 
 
 
 
 
 
 
 
 
Table 3: Summary of outcomes (reference), instruments, measure frequency 
Outcome Variable 
Instrument and Description 
Family member 
depression 13,47  
Collected every 30 days  
Patient Health Questionnaire (PHQ-9).68 Family members indicate the frequency of 
symptoms of depression; higher scores reflect higher depression severity (9 items). 
Internal reliability Cronbach’s alpha = 0.89.  
Family member burden13 
Collected every 30 days 
Zarit Burden Interview.69 Family members indicate the frequency with which their 
responsibilities to their resident are perceived as burdensome; higher scores reflect 
higher burden (22 items). Internal reliability Cronbach’s alpha = 0.86.  
Family satisfaction with 
nursing facility 37 
Collected every 30 days 
Nursing Facility Family Satisfaction (NF-FSQ).70 Family members indicate their level of 
satisfaction with various domains of the nursing facility (23 items). Cronbach’s alpha for 
all domains > 0.70. 
Resident pain 47  
Collected with new MDS 
Minimum Data Set 3.0 Pain (Section J).71,72 Standardized tool used quarterly (or more 
often for a significant status change) to assess every resident in the nursing home. 
Shared Decision Making 
PICS collected after each 
care conference;  
LACTonII collected for 
staff annually 
PICS (Patients Perceived Involvement with Care Scale).73 20 items to assess the 
perceived involvement with care. 4 subscales: Provider information, family information, 
family decision-making, and provider facilitation. Reliability= .79-.89  
LACTon II74 (Leeds Attitude Concordance). 20 items to identify attitudes of health care 
providers towards patient partnership. Reliability .82 
Qualitative and Co-Variate Data 
SDM during care 
conferences 
Video-recorded care conferences will be analyzed to explore family involvement in 
shared decision-making. Four sessions per month will be video-recorded (total of 76).  
Family, resident, and 
staff satisfaction with 
the intervention 
Individual interviews will be conducted with family members, residents, and nursing 
home staff. Interview data will be analyzed to examine participants’ satisfaction with the 
intervention. 
Technical quality 
A structured field note will provide a summary of each web-conference encounter and 
an assessment of technical quality.75  
Demographic variables 
Demographic data include the date of admission to the nursing home, family distance 
from nursing home, number of care conferences previously attended (as reported by 
family), frequency of resident/family contact (as reported by the family), resident and 
family member age, resident diagnoses, and relationship to the resident.  

 
Sample Size/Power Analysis: Staff-family relationship quality, specifically conflict, has been found to be 
significantly associated with family caregiver depression.78 We will therefore power the proposed 
intervention from the PHQ-9, which measures family member depression. While the aim of this pilot study 
is to test the outcomes of the intervention in preparation for a larger trial, we rely on the literature and our 
preliminary data to determine a sample size for this study. The PHQ-9 is measured on an integer scale with a 
range of 0 to 27, with higher scores indicating greater depression.68 The null hypothesis is that the mean PHQ-
9 score will not differ between the Enhanced Usual Care and Intervention groups. Although we anticipate that 
the mean PHQ-9 will be higher for caregivers in the Enhanced Usual Care group than in the Intervention 
group, indicating that the intervention lowers caregiver depression, we will power the study using a two-tailed 
test of significance, allowing the detection of a significant difference in either direction. The sample size 
calculation is based on a two-tailed test of significance and the following assumptions: (1) the expected 
difference in PHQ-9 means between enhanced usual care and intervention groups is 5 points, the documented 
clinically significant effect;78 (2) based on our preliminary work with hospice caregivers the variance of scores is 
5.33; (3) error protection: α =.10, β = .20 (given this is a preliminary trial) 79 and, (4) anticipated attrition of 15% 
as indicated in similar end-of-life intervention studies in the nursing home setting. 19 A sample of 23 residents 
and 23 family members per group (46 total family and residents, total of 92 participants) will provide 
80% power to detect the 5-point difference in the PHQ-9 scores. 
 
Statistical Analysis: Basic descriptive statistics including the range, mean, median, and appropriate 
measures of precision will summarize demographic and baseline data. We will test whether randomization 
created balanced groups by comparing baseline measures and demographic characteristics using chi-square 
or t-test analysis for categorical or continuous variables, respectively. If any variables differ significantly 
between groups, they will be included in regression models as potential confounders. For H1-4 we will 
compare outcomes using a mixed model for repeated measures of each outcome variable that includes TIME 
(baseline, 30 days, 60 days etc.), GROUP (intervention, enhanced usual care), and a TIME x GROUP 
interaction term, along with potential confounding variables as covariates. We will use SAS PROC MIXED 
because it is known to be robust for missing values. The MIXED procedure will allow us to model the 
correlation between the repeated measures over time in a variety of ways, the simplest being autocorrelation 
or order 1 (AR1). In this analysis, the main effect of GROUP will be treated as the average effect; the main 
effect of TIME will be treated as a trend; and the interaction indicates whether the trends differ between 
groups. Least Squares Means will be used to compare groups. Residuals from this model will be examined for 
normality. If residuals show non-normality, we will explore log-transforming the outcome variables or using 
nonparametric methods such as the Wilcoxon Rank Sum test or the Cochran-Mantel-Haenszel test. To test H 
5, we will use a regression model from the Poisson family that will account for varying rates of exposure with a 
clustered sandwich estimator to account for the dependency in the data. For example, we will use a negative 
binomial regression if there is overdispersion in the variation of the Poisson distribution. We will use zero-
truncated negative binomial regression if there is overdispersion and zero truncation for the outcome, the 
number of web conferences attended. For these models we will use SAS PROC NLMIXED, will check model 
specification using regression diagnostics, and compare the various models with AIC and BIC values to ensure 
correct model choice.  Analyses will be conducted under the intention-to-treat principle – all participants 
randomized to a group will be included in the analysis regardless of their level of participation. SAS 9.4 (SAS 
Institute, Cary, NC) will be used for all data analyses. H 6 data analysis will be guided by the NIH patient-
reported outcomes measurement system analysis plan80 including: (1) Item and scale analyses to include an 
inspection of response frequency, mean, standard deviation, range, median, interquartile range, inter-item 
correlation matrix, item-scale correlations, and coefficient alpha; (2) Descriptive statistics to characterize the 
Table 4: Initial coding framework by research question 
Research Questions 
Initial Codes 
1. What are the facilitators and barriers to 
SDM in the nursing home? 
Facilitators/barriers will be identified for each of the 9 steps of SDM.41 
2. What shared decisions will be made with 
family/residents during care conference 
meetings?  
Decisions regarding: 1) nutrition, 2) infections, 3) pain, 4) shortness 
of breath, 5) behavioral issues, 6) hospitalization, 7) other (specify 
and memo for potential modifications to framework).76 
3 What concerns are communicated by 
families/residents to nursing home staff? 
Family/resident expresses concerns related to 1) communication 
problems, 2) resident care concerns, and 3) pain management.9  
4. How will participation in web-conferencing 
impact satisfaction with care? 
Content analysis of interviews will inform the coding process as 
codes emerge from the data. 

sample demographics for item and questionnaire nonresponses. Depending on the prevalence of item 
nonresponse, missing data may be handled by excluding items, imputing responses using mean substitution, a 
mixed-model approach, or multiple imputation prior to factor analysis; (3) Evaluation of statistical assumptions 
of classical test and item response models to include the unidimensionality, local independence, and 
monotonicity assumptions; (4) Estimate CFA and IRT model parameters; and (5) Use of the Cochran-Mantel-
Haenszel test to identify potential differential item functioning between socio-demographic groups.  
 
 
 
 
References 
 
1. 
Amella EJ, Strumpf NE, Teno JM, Mitchell SL. The influence of nursing home culture on the use of 
feeding tubes. Arch. Intern. Med. 2010;170(1):83-88. 
2. 
Covinsky KE, Fuller JD, Yaffe K, et al. Communication and decision-making in seriously ill patients: 
Findings of the SUPPORT project. J. Am. Geriatr. Soc. May 2000;48(5):S187-S193. 
3. 
Towle A, Godolphin W. Framework for teaching and learning informed shared decision making. BMJ. 
1999;319(7212):766-771. 
4. 
Legare F, Ratte S, Stacey D, et al. Interventions for improving the adoption of shared decision making 
by healthcare professionals (Review). The Cochrane Library. 2010(5). 
5. 
National Center for Health Statistics. Health, United States, 2010: With Special Feature on Death and 
Dying. Hyattsville, MD: National Center for Health Statistics 2011.2010. 
6. 
Ersek M, Carpenter JG. Geriatric Palliative Care in Long-Term Care Settings with a Focus on Nursing 
Homes. J Pall Med. 2013;16(10):1180-1187. 
7. 
Miller CL, Intrator O, Gozalo P, Roy J, Barber J, Mor V. Government expenditures at the end of life for 
short- and long-stay nursing home residents: Differences by hospice enrollment status. JAGS. 
2004;52(8):1284-1292. 
8. 
Oliver DP, Porock D, Zweig S. End-of-life care in U.S. nursing homes: a review of the evidence. J Am 
Med Dir Assoc. May-Jun 2005;6(3 Suppl):S21-30. 
9. 
Parker Oliver D, Washington K, Kruse R, Albright D, Lewis A, Demiris G. Hospice family members' 
perceptions and experiences with end-of-life care in the nursing home. J Am Med Dir Assoc. 
2014;15(10):744-750. PMCID: PMC4177958 
10. 
Gage L, Parker Oliver D, Washington K, Kruse R, Lewis A, Demiris G. Family members experience 
with hospice in the nursing home. Am J of Hosp and Palliat Med. In Press. Published online ahead of 
print, November 23, 2014 as doi:10.1177/1049909114560213. PMCID: PMC4177958 
11. 
Kiely DK, Carey K, Mitchell SL. Healthcare proxies of nursing home residents with advanced dementia: 
decisions they confront and their satisfaction with decision-making. J. Am. Geriatr. Soc. 
2009;57(7):1149-1155. 
12. 
Gaugler JE. Family involvement in residential long-term care: A synthesis and critical review. Aging and 
Mental Health. 2005;9(105-118). 
13. 
Chen CK, Sabir M, Zimmeran S, Suitor J, Pillemer K. The importance of family relationships with 
nursing facility staff for family caregiver burden and depression. J. Gerontol. B. Psychol. Sci. Soc. Sci. 
2007;62B(5):P253-P260. 
14. 
Drysdale AE, Nelson CF, Wineman NM. Families need help too: group treatment for families of nursing 
home residents. Clin. Nurse Spec. 1993;7(3):130-134. 
15. 
Kellett UM. Transition in care: family carers' experience of nursing home placement. J. Adv. Nurs. 
1999;29(6):1474-1481. 
16. 
Rodgers BL. Family members' experiences with the nursing home placement of an older adult. Appl. 
Nurs. Res. 1997;10(2):57-63. 
17. 
Whitlatch CJ, Schur D, Noelker LS, Ejaz FK, Looman WJ. The stress process of family caregiving in 
institutional settings. Gerontologist. 2001;41(4):462-473. 
18. 
Hertzberg A, Ekman S, Axelsson K. Staff activities and behaviour are the source of many feelings: 
relatives' interactions and relationships with staff in nursing homes. J. Clin. Nurs. 2001;10(3):380-388. 
19. 
Hanson L, Carey T, Caprio A, et al. Improving decision making for feeding options in advanced 
dementia: A randomized, controlled trial. J. Am. Geriatr. Soc. 2011;59(11):2009-2016. 

20. 
Parker Oliver D, Albright D, Wittenberg-Lyles E, Kruse R, Demiris G. Caregiver evaluation of the 
ACTIVE intervention: " It was like we were sitting at the table with everyone". Am J Hosp Palliat Med. 
2014;31(4):444-453. PMCID: PMC3770818 
21. 
Tabachnick BG, Fidell LS. Using Multivariate Statistics. 3 ed. Northridge: Harper Collins; 1996. 
22. 
Parker Oliver D, Porock D, Zweig S. End of life care in U.S. nursing homes: A review of the evidence. J 
Am Med Dir Assoc. 2004;5:147-155. 
23. 
Hanson L, Eckert J, Dobbs D. Symptom exerience of dying long term care residents. J. Am. Geriatr. 
Soc. 2008;56:91-98. 
24. 
Reynolds K, Henderson M, Shulman A, Hanson L. Needs of the dying in nursing homes. J Palliat Med. 
2002;5:895-901. 
25. 
Hall P, Schroder C, Weaver L. The last 48 hours of life in long-term care: A focused chart audit. J. Am. 
Geriatr. Soc. 2002;50(3):501-506. 
26. 
Teno JM, Weitzen S, Wetle T, Mor V. Persistent pain in nursing home residents. JAMA. Apr 
2001;285(16):2081. 
27. 
Fish R, Levy C, Kutner J. Factors influencing models of end of life care in nursing homes:Results of a 
survey of nurisng home administrators. J Palliat  Med. 2004;7:668-675. 
28. 
Tarzian AJ, Hoffmann DE, Tarzian AJ, Hoffmann DE. Barriers to managing pain in the nursing home: 
findings from a statewide survey. J Am Med Dir Assoc. May-Jun 2005;6(3 Suppl):S13-19. 
29. 
Hodgson N, Landsberg L, Lehning A, Kleban M. Palliative Care Services in Pennsylvania nursing 
homes. J Palliat  Med. 2006;9:1054-1058. 
30. 
Centers for Medicare and Medicaid Services. Code of Federal Regulations. Vol 42CFR418. 
Washington, DC: Government Printing Office via GPO; 2008. 
31. 
National Quality Forum. A National Framework and Preferred Practices for Palliative and Hospice Care 
Quality: A Consensus Report. 2006. 
32. 
Alexander GL, Alwan M, Batshon L, et al. Building on a national health information technology strategic 
plan for long-term and post-acute care: comments by the Long Term Post Acute Care Health 
Information Technology Collaborative. J. Gerontol. Nurs. Jul 2011;37(7):23-25. 
33. 
Gaugler JE, Pearlin LI, Leitsch SA, Davey A. Relinquishing in-home dementia care: difficulties and 
perceived helpfulness during the nursing home transition. Am J Alzheimers Dis Other Demen. Jan-Feb 
2001;16(1):32-42. 
34. 
Davies E. Self-perceived roles of family caregivers of older people living in care homes: A qualitative 
study. Int. J. Nurs. Stud. 2006;43(3):281-291. 
35. 
Ryan AA, Scullion HF. Family and staff perceptions of the role of families in nursing homes. J. Adv. 
Nurs. 2000;32(3):626-634. 
36. 
Train GH, Nurock SA, Manela M, Kitchen G, Livingston GA. A qualitative study of the experiences of 
long-term care for residents with dementia, their relatives and staff. Aging Ment Health. Mar 
2005;9(2):119-128. 
37. 
Taunton RL, Swagerty DL, Smith B, Lasseter JA, Lee RH. Care Planning: for Nursing Home Residents: 
Incorporating the Minimum Data Set Requirements Into Practice. J. Gerontol. Nurs. 2004;30(12):40-49. 
38. 
Bott MJ, Gajewski B, Lee R, Piamjariyakul U, Taunton RL. Care Planning Efficiency for Nursing 
Facilities. Nurs. Econ. 2007;25(2):85-94. 
39. 
Saltz C. Promoting skills in evaluating interdisciplinary geriatric teams. Gerontol. Geriatr. Educ. 
1996;16(4):79-90. 
40. 
Siminoff LA, Step MM. A communication model of shared decision making: Accounting for cancer 
treatment decisions. Health Psychol. 2005;24(4):S99-S105. 
41. 
Makoul G, Clayman M. An integrative model of shared decision making in medical encounters. Patient 
Educ. Couns. 2006;60(3):301-312. 
42. 
Saltz CC, Schaefer T. Interdisciplinary teams in health care: integration of family caregivers. Soc. Work 
Health Care. 1996;22(3):59-69. 
43. 
Parker Oliver D, Demiris G, Wittenberg-Lyles E, Porock D. The use of videophones for patient and 
family participation in hospice interdisciplinary team meetings: A promising approach. Eur. J. Cancer 
Care (Engl). Nov 2010;19(6):729-735. PMCID: PMC2891692 
44. 
Jones J. Using SKYPE to support palliative care surveillance. Nursing Older People. 2014;26(1):16-19. 
45. 
Family Caregivers Online. 2012. http://pewinternet.org/Reports/2012/Caregoivers-online.aspx. 
46. 
Kruse R, Parker Oliver D, Wittenberg-Lyles E, Demiris G. Conducting the ACTIVE randomized trial in 
hospice care: Keys to success. Clin Trials. 2012;10:160-169. PMCID: PMC3554844 

47. 
Joosten E, DeFuentes-Merrillas L, de Weert G, Sensky T, van der Staak C, de Jong C. Systematic 
review of the effects of shared decision-making on patient satisfaction, treatment adherance and health 
status. Psychother. Psychosom. 2008;77(4):219-226. 
48. 
Kaplan S, Greenfield J, Ware J. Assessing the effects of physician-patient interactions on the outcomes 
of chronic disease. Med. Care. 1989:S110-S127. 
49. 
Godin G, Belanger-Gravel A, Eccles M, Grimshaw J. Healthcare professionals' intentions and 
behaviours: A systematic review of studies based on social cognitive theories. Implement Sci. 
2008;3(36). 
50. 
Mitchie S, Fixsen D, Grimshaw J, Eccles M. Specifying and reporting complex behaviour change 
interventions:The need for a scientific method. Implement Sci. 2009;4(40). 
51. 
Demiris G, Oliver DRP, Hensel B, Dickey G, Rantz M, Skubic M. Use of videophones for distant 
caregiving: an enriching experience for families and residents in long-term care. J. Gerontol. Nurs. 
2008;34(7):50-55. 
52. 
Hensel BK, Parker-Oliver D, Demiris G. Videophone communication between residents and family: a 
case study. J Am Med Dir Assoc. 2007;8(2):123-127. 
53. 
Hensel BK, Parker-Oliver D, Demiris G, Rantz M. A comparison of video-based resident-family 
communication in a nursing home and a congregate living facility. J Am Med Dir Assoc. Jun 
2009;10(5):342-347. 
54. 
Parker Oliver D, Demiris G, Wittenberg-Lyles E. The use of video conferencing to imvolve caregivers in 
hospice care planning: Preliminary results from a randomized trial. International Palliative Care Network 
Lecture Series; 2012; Online. 
55. 
Parker Oliver D, Demiris G, Wittenberg-Lyles E, Kruse R. Preliminary results Year 1: ACTIVE 
intervention. National Institute of Nursing Research State of the Science in End of Life Care; 2012; 
Bethesda, Maryland. 
56. 
Parker Oliver D, Demiris G, Wittenberg-Lyles E, Porock D, Collier J, Arthur A. Caregiver participation in 
hospice interdisciplinary team meetings via videophone technology: A pilot study to improve pain 
management. Am. J. Hosp. Palliat. Care. Nov 2010;27(7):465-473. PMCID: PMC2890035 
57. 
Parker Oliver D, Porock D, Demiris G, Courtney K. Patient and family involvement in hospice 
interdisciplinary teams. J. Palliat. Care. Winter 2005;21(4):270-276. 
58. 
Parker Oliver D, Washington K, Wittenberg-Lyles E, Demiris G, Porock D. “They’re part of the team”: 
Participant evaluation of the ACTIVE intervention. Palliat. Med. 2009;23:549-555. PMCID: 
PMC2721906 
59. 
Wittenberg-Lyles E, Oliver DP, Demiris G, Petty B, Day M. Caregiver involvement in hospice 
interdisciplinary team meetings: a case study. J. Palliat. Care. 2008;24(4):277-279. PMCID: 
PMC2675180. 
60. 
Wittenberg-Lyles E, Parker Oliver D, Demiris G, Baldwin P. The ACTive intervention in hospice 
interdisciplinary team meetings:Exploring family caregiver and hospice team communication. J Comput 
Mediat Commun. 2010;15(3):465-481. PMCID: PMC20543889 
61. 
Wittenberg-Lyles E, Parker Oliver D, Demiris G, Regehr K. Interdisciplinary collaboration in hospice 
team meetings. J Interprof Care. 2010;24(3):264-273. PMCID: PMC2854854 
62. 
Wittenberg-Lyles E, Parker Oliver D, Demiris G, Washington K, Regehr K. Question asking by family 
caregivers in hospice interdisciplinary team meetings. Res Gerontol Nurs. 2010;3(2):82-88. PMCID: 
PMC2860630 
63. 
Patsopoulos N. A pragmatic view on pragmatic trials. Dialogues Clin Neurosci. 2011;13(2):217-224. 
64. 
Thorpe K, Zwarenstein M, Oxman A, et al. A pragnatic-explanatory continuum indicator summary 
(PRECIS): a tool to help trial designers. CMAJ. 2009;180(10):E47-E57. 
65. 
Freedland K. Demanding attention: Reconsidering the role of attention control groups in behavioral 
intervention research Psychosom Med. 2013;75(2):100-102. 
66. 
T. G. How Secure is Skype, Really? . PC World. 2008. 
67. 
Popejoy L, Marek KD, Scott-Cawiezell J. Patterns and problems associated with transitions after him 
fracture in older adults. J. Gerontol. Nurs. 2013;39(9):43-52. 
68. 
Kroenke K, Spitzer RL, Williams J. The PHQ-9: Validity of a brief depression severity measure. J. Gen. 
Intern. Med. 2001;16:606-613. 
69. 
Bachner Y, O'Rourke N. Reliability generalization of responses by care providers to the Zarit Burden 
Interview. Aging & Mental Health. 2007;11(6):678-685. 
70. 
Castle N. Family satisfaction with nursing facility care. Int. J. Qual. Health Care. 2004;16(6):483-489. 

71. 
Hawes C, Phillips C, Mor V, Fries BE, Morris J. MDS data set should be used for research. 
Gerontologist. 1992;32:563-564. 
72. 
Hawes C. Reliability estimates for MDS for Nursing Home Assessment and care screening. 
Gerontologist. 1995;35:172-178. 
73. 
Smith M, Winkel G, Egert J, Diaz-Wionczek M, DuHamel K. Patient-Physician communication in the 
context of persistent pain: Validation of a modified version of the Patients Perceived Involvement in 
Care Scale`. J. Pain Symptom Manage. 2006;32(1):71-81. 
74. 
Knapp P, Raynor D, Thistlethwaite J, Jones ML. A questionnaire to measure health practitioners' 
attitudes to partnership in medicine taking: LATCon II. Health Expectations. 2009;12:175-186. 
75. 
Demiris G, Parker Oliver D, Kruse R, Wittenberg-Lyles E. Telehealth group interactions in the hospice 
setting: Assessing technical quality across platforms. Telemed J E Health. 2013;19(4):235-240. 
PMCID: PMC3621258 
76. 
Givens J, Kiely DK, Carey B, Mitchell S. Healthcare proxies of nursing home residents with advanced 
dementia: Decisions they confront and their satisfaction with decision-making. J. Am. Geriatr. Soc. 
2009;57(7):1149-1155. 
77. 
Gubrium JF, Sankar A. Qualitative Methods in Aging Research. Thousand Oaks,CA: Sage; 1994. 
78. 
McMillan D, Gilbody S, Richards D. Defining successful treatment outcome in depression using the 
PHQ-9: A comparison of methods. J. Affect. Disord. 2010;127:122-129. 
79. 
Meinert C. Clinical trials: Design, conduct and analysis. 2nd ed: Oxford University Press; 2012. 
80. 
Reeve BB, Hays RD, Bjorner JB, et al. Psychometric evaluation and calibration of health-related quality 
of life items banks: plans for the patient-reported outcome measurement information system (PROMIS). 
Med. Care. 2007;45(5 Supp 1):S22–S31. 
81. 
Steinbrook R. Public Access to NIH-Funded Research. The New England Journal of Medicine. 
2005;352(17):1739-1741.