Running head: ADVANCE CARE PLANNING

Advance Care Planning in a Primary Care Setting
Arseña Smith
Arizona State University

1

2
ADVANCE CARE PLANNING
Abstract
Purpose: Advance care planning (ACP) allows an individual to discuss and document their
personal preferences at end-of-life. ACP has been shown to improve communication and reduce
discomfort for patients and their families. The literature supports utilizing formalized,
multimodality training programs for healthcare providers in order to increase their confidence in
initiating ACP discussions. These findings led to the initiation of an evidence-based practice
project in a primary care setting with the purpose of increasing advance care planning
discussions between providers and patients with the use of a standardized education tool.
Background and Significance: National regulations mandate that patients are provided
information about advance directives in the healthcare setting, but completion rates are not
monitored and continue to be low. ACP is now a billable service for healthcare providers, but it
has not provided enough incentive to increase completion rates. Barriers for healthcare providers
in the outpatient setting include lack of time, protocols, and lack of education on how to initiate
and foster advance care planning discussions.
Methods: Healthcare providers in a primary care office attended a 15-minute structured
educational session with and a toolkit was provided on the importance of ACP, how to initiate
conversations with patients, and bill for the service. Participants completed a portion of the
Knowledge, Attitudinal, and Experiential Survey on Advance Directives (KAESAD) survey
assessing their confidence in ACP before and three months post intervention. Participant
confidence (N = 6) in ACP was analyzed using the Wilcoxin test and descriptive statistics. The
number of billed ACP services for the office was collected for four months post intervention and
compared to the previous four months.
Outcomes: A significant increase in provider confidence after participating in a multimodality

3
ADVANCE CARE PLANNING
education program was found in the results (Z = -2.21, p = .03). There was a 42.1% increase in
the number of billed ACP discussions for the office in the four months post intervention.
Conclusion: The future desired state is that ACP discussions become standard practice in
primary care leading to the completion of advance directives. This can be accomplished through
formalized education sessions and resources for providers in order to increase their confidence in
initiating ACP discussions with patients. The ultimate goal is to decrease unnecessary spending
at end-of-life while improving patient and family satisfaction with the quality of care received at
end-of-life.
Keywords: Advance directive, advance directives, advance care planning, primary care,
intervention, education, communication

4
ADVANCE CARE PLANNING
Advance Care Planning in a Primary Care Setting
Death is inevitable for all, but the discussions surrounding this topic continue to be
difficult and are often postponed until it is too late. An advance directive is a written statement
by a competent person that indicates their wishes regarding medical decisions at end-of-life if
they are unable to communicate due to mental infirmity or unconsciousness (Congressional
Research Services (CRS) & Library of Congress (LC), 2016). The two parts of an advance
directive are the living will and the health care power of attorney. A living will is utilized when
an individual is unable to communicate their wishes and inform health care provider about the
type of medical care they wish to receive at the end-of-life (CRS & LC, 2016). The health care
power of attorney identifies a health care proxy or decision maker in the event that the patient is
unable to make decisions for themselves (CRS & LC, 2016). Advance directives promote patient
autonomy, dignity, reassurance, and empowerment (Wissow et al., 2004).
Problem Statement
In the United States (U.S.), advance care planning rates are less than 15%, and healthcare
providers have not made progress in improving these rates (Ramsaroop, Reid, & Adelman, 2007;
Tung et al., 2014). It is estimated that 40% to 70% of medical inpatients are not capable of
making medical decisions at end-of-life (Sullivan & Dickerson, 2016). If a patient has not
previously documented their end of life wishes and is unable to do so, it is left up to the patient’s
family to make those difficult decisions. This can cause stress and uncertainty for those involved.
Advance care planning (ACP) has been shown to improve communication, increase knowledge
and respect for a patient’s wishes at end-of-life, and improve patient and family satisfaction with
care (Detering et al., 2014; Sullivan & Dickerson, 2016).
Laws regarding advance directives are individualized by state, but there have been a few

5
ADVANCE CARE PLANNING
regulations passed by Congress regarding advance care planning (CRS & LC, 2016). In 1991,
Congress approved the Patient Self-Determination Act (PSDA) which requires that all Medicareparticipating healthcare facilities provide information to patients on advance directives to give
patients autonomy over their care (Ramsaroop, Reid, & Adelman, 2007; Tung et al., 2014).
These facilities are also required to provide community education on advance directives, provide
information about health care decision making rights, ask all patients if they have an advance
directive, educate staff and community on advance directives, and not discriminate against
patients based on their advance directive state (Ramsaroop, Reid, & Adelman, 2007). The PSDA
mandates that providers distribute advance directives at time of admission to the hospital and on
initial receipt of care or plan of enrollment (CRS & LC, 2016). If advance directives are not
distributed and documented per the PSDA, the Secretary of Health and Human Services can
withhold payment of services to Medicare-certified providers (CRS & LC, 2016).
Additional laws include The National Defense Authorization Act which established a
federal advance directive for military personnel and the Medicare Improvements for Patients and
Providers Act (MIPPA) (CRS & LC, 2016). The MIPPA added end-of-life planning to the initial
preventive physical exam for new Medicare patients (CRS & LC, 2016). The Centers for
Medicare and Medicaid Services (CMS) rely on state agencies and internal contract review to
monitor advance directive requirements (CRS & LC, 2016). The Institute of Medicine prioritized
advance care planning in 2014. Healthcare providers can now bill Medicare for ACP discussions,
but this incentive has not provided enough motivation to overcome the barriers (Sullivan &
Dickerson, 2016). How advance directive information is addressed can vary, but there are
common challenges such as the providers discomfort in talking about end-of-life issues as well

6
ADVANCE CARE PLANNING
as the lack of time for discussion (Detering et al., 2014; Lund, Richardson, & May, 2015;
Spoelhof & Elliott, 2012).
Purpose and Rationale
Advance care planning is an ongoing process that requires multiple conversations with
family members and healthcare professionals (Lum et al., 2016). Primary care clinics have the
ability to implement an intervention to engage patients in advance care planning (Lum et al.,
2016). However, many providers find advance care planning conversations difficult and feel that
they have inadequate training to assist in the process of end-of-life care communication (Clayton
et al, 2012; Detering et al., 2014; Tung et al., 2014).
Advance directives are associated with lower levels of Medicare spending, decreased
likelihood of in-hospital deaths, and increased hospice use in areas that have high levels of endof-life spending (Rao, Anderson, Lin, & Laux, 2014). An advance directive allows a patient to
have high quality care at end-of-life without unwanted or invasive treatments (Oczkowski,
Chung, Hanvey, Mbuagbaw, & You, 2016). The purpose of this evidence-based practice project
was to utilize a multimodality educational intervention for healthcare providers in a primary care
practice to improve their confidence in their ability to have advance care planning discussions
with patients and bill for the service.
Background and Significance
Many barriers that have been identified that may account for the low completion rates of
advance directives. Prior to the 17th century, death was accepted as an inevitable part of life and
people were prepared, however, life-prolonging technology in the 19th and 20th centuries
improved the lives of humankind and attitudes changed (Sullivan & Dickerson, 2016). Death and
dying became something to be ashamed of and was hidden to imply the possibility of

7
ADVANCE CARE PLANNING
immortality (Sullivan & Dickerson, 2016). Federal funding for research is often focused on
finding a cure instead of determining ways in which to manage chronic conditions (Sullivan &
Dickerson, 2016). Living wills were initially developed by advocates of euthanasia, and advance
care planning may be looked at by some as murder (Sullivan & Dickerson, 2016). Religious or
spiritual beliefs may increase the rate of life-prolonging care along with the fee-for-service
medical paradigm in the United States (Sullivan & Dickerson, 2016).
Effective communication is a major barrier to end-of-life discussion and can be attributed
to a healthcare provider’s lack of time and communication skills, lack of education on how to
initiate discussions, lack of protocols, and inadequate mutual understanding regarding values and
goals (Houben, Spruit, Groenen, Wouters, & Janssen, 2014; Spoelhof & Elliot, 2012). Historical,
political, economic, and social beliefs all contribute to the low rates of advance care planning in
the United States, and it is important to train healthcare providers on the ways in which to initiate
these discussions in the primary care setting (Sullivan & Dickerson, 2016). Factors that may
increase the likelihood of having an advance directive include presence of a chronic illness or
condition, being 65 years or older, being Caucasian, being female, and having a higher income
and education level (Rao et al., 2014). In addition to demographic barriers to completion of ACP,
there are legal barriers to consider. Barriers include poor health literacy, health care agent
restrictions, execution requirements, inadequate reciprocity, and religious, cultural, and social
inadequacies (Hinders, 2012).
A systematic review and meta-analysis compared communication tools such as decision
aids, structured meeting plans, and educational interventions to determine the impact on end-oflife decisions of adult patients in the ambulatory care setting (Oczkowski et al., 2016). Low
quality evidence was found that supported structured communication tools to assist with end-of-

8
ADVANCE CARE PLANNING
life discussions in the outpatient setting (Oczkowski et al., 2016). The lack of supporting
evidence was thought to be related to the need for a large sample size over a prolonged period of
time with follow-up (Oczkowski et al., 2016). A standardized approach to measuring outcomes
and knowledge of advance care planning after implementing an intervention was found to be
lacking and made it difficult to objectively compare the interventions (Oczkowski et al., 2016).
In another systematic review, it was determined that a combined written, verbal, and video
education was significantly more effective than a single written intervention (Durbin, Fish,
Bachman, & Smith, 2010).
In a study of community-dwelling adults, lack of awareness was the most frequently
reported reason for not having an advance directive but 67.8% reported having concerns about
end-of-life care (Rao et al., 2014). The data suggested that most people prefer receiving this
information from healthcare providers but their attitude and comfort levels could be a barrier
(Rao et al., 2014). Patients have indicated that they would prefer to discuss this topic with a
healthcare provider who has known them for some time and for the provider to initiate the
advance care planning when they are in good health (Ramsaroop, Reid, & Adelman, 2007;
Wissow et al., 2004). In an evaluation of a multimodality education program for healthcare
providers it was determined that providers were significantly more confident in their abilities to
discuss advance care planning after reading a training manual, viewing a DVD, and participating
in an interactive e-simulation (Detering et al., 2014). In a study of internal medicine resident
physicians, 70% of the residents reported a lack of confidence in discussing advance directives
and avoided the conversation (Tung et al., 2014). Enhanced training for providers, workshops for
all members of the health care team, non-physician ACP champions, and standardized
documentation were proposed interventions (Tung et al., 2014).

9
ADVANCE CARE PLANNING
Interactive interventions in which patients can ask questions have also been shown to be
more effective than didactic interventions (Spoelhof & Elliott, 2012). Group visits to discuss
advance care planning are an alternative option which allow patients to interact with one another
and discuss end-of-life decisions in a safe and supportive environment (Lum et al., 2016). An
intervention to improve advance directive completion rates in a primary care setting will need to
first focus on provider education and comfort levels with the material. Overcoming barriers to
starting these difficult conversations can be done through interactive education and standardized
workflows. An example of a comprehensive resource is The Conversation Project (Bisognano &
Goodman, 2013). When implemented within several health systems in La Crosse, Wisconsin,
patients and families were routinely engaged in conversations regarding their wishes (Bisognano
& Goodman, 2013). In a study of 540 adults who died from April 1995 to March 1996 in La
Crosse, 85% of them had written advance directives (Bisognano & Goodman, 2013). Impacting
advance directive rates will require increased education for providers to initiate the conversation
and patient-friendly materials to further the discussion.
Internal Evidence
In a primary care setting within an Accountable Care Organization in Phoenix, Arizona,
there were new efforts to increase advance care planning discussions during annual physical
exams. The plan was to empower providers to not only initiate these conversations, but also
properly document and bill for the service. The goal was that these conversations would meet
quality measures, increase revenue, decrease end-of-life care costs, and improve quality of care
for their patients at end-of-life. Within the Accountable Care Organization, there were 16,415
patients on Medicare, but only 1,590 advance care planning discussions were billed in 2016 (L.
Donkerbrook, personal communication, April, 18, 2017). Only 9.68% of eligible patients

10
ADVANCE CARE PLANNING
participated in advance care planning discussions, and there is a need for further evaluation and
change in current practice (L. Donkerbrook, personal communication, April, 18, 2017). After
review of the background and clinical significance of advance care planning along with effective
interventions, the clinically relevant PICOT question was developed, “In patients in a primary
care setting, does a multimodality training program for providers in comparison to current
practice impact the completion rates of advanced directives after the completion of the
program?”.
Search Strategy
Electronic database searches were completed to obtain relevant studies to answer the
clinical PICOT question. The databases searched for this literature review included CINAHL
(Appendix A), PubMed (Appendix B), Web of Science (Appendix C) and Cochrane Library
(Appendix D). Keywords included; advance directive, advance directives, advance care
planning, primary care, evidence-based interventions, intervention, education, communication,
conversation project, respecting choices, next steps, and prepared. The initial search of the
keywords (‘advance directive’ or ‘advance care planning’) yielded 6,463 results in CINAHL
(Appendix A), 953 in PubMed (Appendix B), 9,204 in Web of Science (Appendix C) and 752 in
Cochrane Library (Appendix D). Keywords were searched independently and then combined
using “AND” with additional keywords to obtain a manageable yield in each database.
The initial yield in CINAHL was narrowed by searching the original terms with AND
‘education’ AND ‘primary care’. Limitations included published dates before 2012 and studies
outside of the U.S. The final yield was 25 articles that were then reviewed for inclusion in the
literature review (Appendix A).

11
ADVANCE CARE PLANNING
The initial PubMed search was limited by searching the original terms with AND
‘primary care’ AND (‘provider education’ OR ‘evidence-based interventions’) with a yield of
17 articles (Appendix B). An additional search was conducted within PubMed using the original
key terms AND (‘conversation project’ OR ‘respecting choices’ OR ‘next steps’ OR ‘prepared’)
with the limitation of being published in the last 5 years. This resulted in a yield of 85 articles.
The Web of Science database search was limited by using the original key terms AND
(‘intervention’ AND ‘communication’) and a timespan from 2012 to 2017 yielding 182 results
(Appendix C). Article titles and abstracts were reviewed for inclusion in literature review. A
search of the Cochrane Library initially yielded 25 results (Appendix D). Exclusions included
published dates prior to 2012 and study protocols with a yield of 18. The only article that was
relevant to the PICOT was excluded because it focused solely on hemodialysis patients.
Exclusion criteria in each database included published dates before 2012 apart from one
landmark systematic review. Additional exclusion criteria were studies written in a language
other than English, study protocols, doctoral dissertations, studies focused on patients under 18
years of age, or studies focused on specific patient populations (i.e. congestive heart failure,
dialysis). A hand ancestry search was also completed and yielded one study. The majority were
found to be irrelevant or outside of the published date guidelines. The ten studies chosen for
inclusion were relevant to the PICOT question. They were independently reviewed for validity,
reliability, and applicability (Appendix E).
Critical Appraisal and Synthesis
Ten studies were selected in this literature review. Each study was evaluated using
Melnyk and Fineout-Overholt’s (2015) rapid critical appraisal tool and was presented in
evidence tables for analysis of data (Appendix E). The strength of the studies varied from level

12
ADVANCE CARE PLANNING
one through level six evidence. There were three systematic reviews (SR) with two of them also
being a meta-analysis (MA), three quasi-experimental studies (QE), one retrospective chart
review (RCR), one qualitative systematic review, and two mixed-method research studies
(MMR). There was minimal bias reported amongst the studies with only one study reporting that
an author received royalties from the educational tool (Appendix E). Additional biases to
consider were that several of the study’s participants were volunteers and may have already had
positive beliefs about advance care planning or wanted to provide socially desirable answers on
surveys. There was moderate heterogeneity in the measurable outcomes for each study but
homogeneity in the fact that they each assessed the effect of a structured tool to address advance
care planning (Appendix F).
The sample size for each study was adequate and patient demographics were consistent in
focusing on patients over 21 years of age and excluding studies or interventions that were
disease-specific or involved psychiatric care planning (Appendix E). Interventions across all
studies had at least two components, but there was a wide variety of measurement tools utilized.
Eight of the studies did not report the specificities or sensitivities of their measuring tools
(Appendix E). Seven studies assessed patient or provider satisfaction and confidence through pre
and post questionnaires or phone interviews. Two studies focused on advance directive
completion rates, and two studies measured both outcomes (Appendix F). Transferability may be
impacted by the fact that only four of the studies were completed in the United States. Other
countries may have different views on end of life, but the patient population and clinical settings
are similar. There were significant results or positive outcomes in each study to support the use
of multimodality education tools for advance care planning.
There is currently not a standardized approach for discussing or completing advance

13
ADVANCE CARE PLANNING
directives. Healthcare providers are encouraged to initiate advance care planning conversations
with their patients, but studies have indicated that lack of provider comfort and time are barriers.
Healthcare providers currently do not receive additional training or tools to help them facilitate
these important discussions. The evidence indicates that standardized, multimodality education
tools can improve provider confidence in having advance care planning discussions.
Additionally, standardized education tools for patients are shown to improve patient satisfaction
and can positively impact the number of advance directives completed.
Conceptual Framework and Evidence-Based Practice Model
The self-efficacy theory was the conceptual framework that guided this evidence-based
project (Appendix G). Self-efficacy is an individual’s beliefs in their ability to complete an
action (Resnick, 2014). Behavior is believed to be influenced by environment, person, and
informational sources as well as self-efficacy and outcome expectations (Resnick, 2014). This
theory was appropriate for this project design because the project was focused on increasing
healthcare provider’s confidence in having advance care planning discussions with patients. The
project was designed to promote self-efficacy for healthcare providers while addressing current
behavior and potential barriers.
The Model for Evidence-Based Practice Change facilitated this proposed practice change
(Appendix H). The model guides healthcare professionals through a systematic process for
change and supports a combination of quantitative and qualitative data, clinical expertise, and
contextual evidence (Rosswurm & Larrabee, 1999). This model provides a six-step approach for
implementing an evidence-based practice (EBP) that starts with identifying a need for change
and ends with implementing and evaluating that change (Melnyk & Fineout-Overholt, 2015).
The model provided a solid framework to guide this project through the steps of evaluating,

14
ADVANCE CARE PLANNING
analyzing, and synthesizing the evidence for the purpose of designing a practice change (Melnyk
& Fineout-Overholt, 2015). A need for increasing advance care planning discussions was
identified within the Accountable Care Organization and the goal was to implement an
intervention that would assist providers in having advance care planning discussions with
patients and evaluate the outcomes.
Methods
Ethical Considerations
An approval letter from the Vice President of Case Management of the Accountable Care
Organization was obtained (Appendix G). Arizona State University Institutional Review Board
approved the project as an Initial Study (Appendix H). The practice was selected by the Case
Management team at the Accountable Care Organization and the practice verbally consented to
host the project. Informed consent was obtained from participants prior to their engagement in
project (Appendix I).
Practice Setting and Participants
The project site was a primary care clinic in a metropolitan area in the southwestern
United States. The office had two physicians, one nurse practitioner, two physician assistants,
one registered nurse, one office manager, and several front and back office staff members. The
educational session time was planned with the office manager and all members of the staff were
invited to participate in the educational session over a lunch break.
The participants donated their time and did not receive any direct compensation for
participating in this educational program. Inclusion criteria included providers and clinical staff
who were English speaking and at least 18 years of age. Exclusion criteria were minors, adults
unable to consent, and were non-English speaking. There were six participants.

15
ADVANCE CARE PLANNING
Intervention
This project consisted of a pre-post design with an educational component and follow up
data collection on billable advance care planning rates in an accountable care organization. Staff
in an internal medicine office voluntarily attended a 15-minute structured educational session
about Advance Care Planning. that included verbal and written material. The written materials
included the Five Wishes Physician Toolkit and an additional information about the laws and
regulations surrounding ACP, barriers, and a list of additional resources. Participants completed
a Level of Confidence subscale of the Knowledge, Attitudinal, and Experiential Survey on
Advance Directives (KAESAD) survey to assess their confidence in Advance Care Planning
before the intervention and three months post intervention (Jezewski et al., 2005). The total time
required to complete the survey before and after the completion of the project was approximately
five minutes each.
The educational session provided participants with information about the background and
importance of ACP, how to initiate conversations with patients, implement into practice, and bill
for the service. The proposed program educated participants through verbal instruction and
written materials. There was additional time allowed to answer questions about the education
material and surveys.
Outcome Measures
The primary outcome of this project was to assess the change in participant confidence in
advance care planning after the educational session. The secondary outcome was tracking the
number of billed Advance Care Planning services for each provider. This data was collected
from quality data reported to the organization from Medicare for four months post intervention
and compared to the data four months before the intervention.

16
ADVANCE CARE PLANNING
Instruments
A demographic questionnaire was developed to collect information on participant’s
demographics, role, and years of experience (Appendix J).
Staff completed a Level of Confidence subscale of the Knowledge, Attitudinal, and
Experiential Survey on Advance Directives (KAESAD) originally developed by Mary Ann
Jezewski, RN, PhD, FAAN to assess their confidence in Advance Care Planning (Jezewski et al.,
2005). Permission was given by Dr. Jezewski to reproduce the instrument for the project with the
understanding that it would not be published or attached to this final report. The portion of the
survey utilized consisted of 10 questions on a five-point Likert scale designed to measure
confidence in Advance Care Planning. The reliability and validity of the entire survey was
established for use by registered nurses and not the general public.
Data Collection and Analysis
Post surveys were administered, and data collected from subjects before the intervention
and three months post intervention. The rate of advance care planning codes billed by the
providers was tracked through quality data reported to the organization’s chief financial officer
each month. All data analysis was performed using IBM SPSS® Statistics Version 24. Data was
analyzed using the Wilcoxin test with intent to treat. Descriptive statistics and cross-tabulation
were used to describe the sample and outcome variables. Non-parametric statistics were used to
analyze the data using a two-tailed test and the critical value was set at p > .05.
Budget
Total costs for the project were estimated to be $1365.00 USD (Appendix K). In-kind
support in the amount of $1215.00 USD was provided by the project site and Accountable Care

17
ADVANCE CARE PLANNING
Organization. Education materials were $5.00 per person. Lunch was provided by the DNP
student during the education session and was $10.00 per person.
Results
Demographic data
The respondents were clinic personnel at a primary care practice in Arizona (N = 6). The
respondents were 2 (33.3%) males, 4 (66.7%) females and all Caucasian (100%). The average
years of age of the respondents was 42.5 (SD = 19.25) and ranged from 25 to 68 years. The
respondents were 1 (16.7%) Nurse Practitioner (NP), 2 (33.3%) Physician Assistants (PA), 1
(16.7%) Medical Doctor/Doctor of Osteopathic Medicine (MD/DO), 1 (16.7%) Office Manager,
and 1 (16.7%) Medical Student. The level of education of the respondents were 2 (33.3%)
Bachelor’s degrees, 3 (50%) Master’s degrees and 1 (16.7%) Doctorate degree. The average
years of experience and the years in current role were both 13 (SD = 17.05) years with the same
range of 1 to 35 years.
Outcomes
Confidence. A Wilcoxon test examined the results of the pre and post survey conducted
to measure the provider’s level of confidence related to advance care planning (Appendix L). A
significant increase in provider confidence was found in the results (Z = -2.21, p = .03). Provider
confidence in advance care planning improved after participating in a multimodality education
program. The NP had a high initial score of 88% and the same score post intervention. The PAs
and MD/DO all had improved scores post intervention. The PAs had initial scores of 62% and
86% which increased to 72% and 100% confidence respectively. The MD/DO had an initial
score of 80% that increased to 84%. Years of experience or time in current role did not have any
clinical significance.

18
ADVANCE CARE PLANNING
Billed ACP codes. The billed ACP codes were measured from quality data reported to
the organization from Medicare for four months post-intervention and compared to the data four
months pre-intervention. The practice had billed for 19 ACP codes between June 2017 to
September 2017 and 27 ACP codes between October 2017 to January 2018. Providers within the
Accountable Care Organization (ACO) averaged 4.48 billed ACP codes during the four months
pre-intervention. The selected practice had billed for 19 ACP codes accounting for 4.49% of the
total codes billed within the organization. During the four months post intervention, providers
within the ACO averaged 4.22 billed codes and the selected practice billed for 27 accounting for
6.63% of the total billed codes. There was a 42.1% increase in the number of billed ACP
discussions for the selected practice in the four months post intervention.
Discussion
The evidence indicated that a formalized, multimodality training program would increase
provider confidence in advance care planning. This evidence-based practice project was
successful in significantly increasing provider confidence regarding advance care planning after
a formalized education session. The rate of billed advance care planning rates within the practice
increased post intervention. ACP is a billable service but was underutilized within the entire
organization and can be attributed to lack of time, provider confidence, and patient resistance.
This project was successful in addressing provider confidence surrounding advance care
planning. The educational session provided them with the resources to help them quickly discuss
the topic and ways in which to address a patient’s resistance or concerns.
The goal of the organization was to meet quality measures, increase revenue, and
decrease end-of-life care costs while improving quality of care at end-of-life. This project
suggests that if providers receive education on advance care planning their confidence in

19
ADVANCE CARE PLANNING
initiating conversations with patients improves and more patients will receive this important
information. The developed education session is sustainable and could be easily implemented at
other practices within the organization as the materials are both cost effective and time efficient.
This project directly impacted the organization and providers and indirectly impacted patients
and their families.
Limitations and Implications
One of the limitations of this project was a small sample size. The practice that was
selected by the ACO to participate in the intervention was a small practice and each of the
providers on site the day of the presentation participated. The initial aim was that a well
performing practice would be selected and this project would be conducted as a pilot project for
a larger roll-out within the organization. The educational session was short but the time with the
participants was rushed because coordinating schedules over a lunch hour on a Friday afternoon
was difficult. However, this time was selected by the practice as they felt it would be the best
time.
The ACP billed rates were also only tracked by the organization for Medicare patients.
ACP discussions may have occurred with patients who had a different insurance and there was
not a way to track this information at this time. A limitation of the project was that there was a
significant delay in how the data is reported back to the organization from Medicare so that only
four months post data could be collected with the timeline of the project. A better measure of the
impact of the project would have been to examine at data six months pre and six months post
intervention. Also, implementing the project at the beginning of a calendar year and monitoring
for a longer period of time would have allowed the data to be collected for a full year of annual
Medicare physicals and compared to the previous year.

20
ADVANCE CARE PLANNING
There is also the possibility that ACP discussions were initiated with patients but that the
providers did not remember to bill for the service. While provider confidence increased in ACP it
is difficult to assess if this directly impacted their practice. Future practice sites may benefit from
weekly check-ins with providers and staff to answer questions, audit charts, and assess
facilitators or barriers to ACP conversations with patients.
Material cost were minimal but may be a limiting factor for the organization or future
practices. The educational packets were $5 each and the organization would have to pay staff to
participate in the educational session and block appointment times. The materials could be
redesigned and reproduced at a lower cost but there would be initial costs associated with
developing the material. It is important for the organization and providers to recognize billing for
ACP has the potential to both increase revenue for the practice as well as improve quality of care
for their patients at end-of-life.
Conclusion
Advance care planning has been shown to decrease unnecessary spending while
improving patient and family satisfaction with the quality of care received at end-of-life. The
future desired state is that advance care planning will become a standard practice in primary care.
Death is both inevitable and unpredictable. Advance care planning discussions need to be
initiated in the primary care setting long before a patient’s health declines or they have an
unexpected event. American society is focused on planning for the future but fails to plan for the
end. Healthcare providers have a unique opportunity to encourage their patients to make
decisions surrounding end-of-life. This will ensure that the care that each patient receives is
within their wishes and can decrease the amount of stress and burden on friends and family. The
literature and this project indicate that all healthcare providers can benefit from additional

21
ADVANCE CARE PLANNING
education and training about advance care planning on how to initiate and have these critical
conversations with patients.

22
ADVANCE CARE PLANNING
References
Blackford, J., & Street, A. F. (2013). Facilitating advance care planning in community palliative
care: Conversation starters across the client journey. International Journal of Palliative
Nursing, 19(3), 132-139. doi:10.12968/ijpn.2013.19.3.132
Bisognano, M., & Goodman, E. (2013). Engaging patients and their loved ones in the ultimate
conversation. Health Affairs (Project Hope), 32(2), 203.
Butler, M., Ratner, E., McCreedy, E., Shippee, N., & Kane, R. L. (2014). Decision aids for
advance care planning: An overview of the state of the science. Annals of Internal
Medicine, 161(6), 408-418. doi:10.7326/M14-0644
Clayton, J. M., Butow, P. N., Waters, A., Laidsaar-Powell, R. C., O’Brien, A., Boyle, F., . . .
Tattersall, M. H. (2013). Evaluation of a novel individualised communication-skills
training intervention to improve doctors’ confidence and skills in end-of-life
communication. Palliative Medicine, 27(3), 236-243. doi:10.1177/0269216312449683
Congressional Research Service (CRS) & Library of Congress (LC). (2016). Federal laws
concerning advance directives: CRS in focus. Retrieved from
http://congressional.proquest.com.ezproxy1.lib.asu.edu/congressional/result/pqpresultpag
e.gispdfhitspanel.pdflink/$2fapp-bin$2fgis-congresearch$2f4$2f6$2f8$2fe$2fcrs-2016dsp-0010_from_1_to_2.pdf/entitlementkeys=1234%7Capp-gis%7Ccongresearch%7Ccrs2016-dsp-0010
Detering, K., Silvester, W., Corke, C., Milnes, S., Fullam, R., Lewis, V., & Renton, J. (2014).
Teaching general practitioners and doctors-in-training to discuss advance care planning:
Evaluation of a brief multimodality education programme. BMJ Supportive & Palliative
Care, 4(3), 313-321. doi:10.1136/bmjspcare-2013-000450

23
ADVANCE CARE PLANNING
Durbin, C. R., Fish, A. F., Bachman, J. A., & Smith, K. V. (2010). Systematic review of
educational interventions for improving advance directive completion. Journal of
Nursing Scholarship, 42(3), 234-241. doi:10.1111/j.1547-5069.2010.01357.
Hinders, D. (2012). Advance directives: Limitations to completion. American Journal of
Hospice and Palliative Medicine, 29(4), 286-289. doi:10.1177/1049909111419293
Houben, C. H. M., Spruit, M. A., Groenen, M. T. J., Wouters, E. F. M., & Janssen, D. J. A.
(2014). Efficacy of advance care planning: A systematic review and meta-analysis.
Journal of the American Medical Directors Association, 15(7), 477-489.
doi:10.1016/j.jamda.2014.01.008
Jezewski, Brown, Wu, Meeker, Feng, & Bu. (2005). Oncology nurses' knowledge, attitudes, and
experiences regarding advance directives. Oncology Nursing Forum, 32(2), 319-27.
Lum, H. D., Jones, J., Matlock, D. D., Glasgow, R. E., Lobo, I., Levy, C. R., . . . Kutner, J. S.
(2016). Advance care planning meets group medical visits: The feasibility of promoting
conversations. Annals of Family Medicine, 14(2), 125.
Lund, S., Richardson, A., & May, C. (2015). Barriers to advance care planning at the end of life:
An explanatory systematic review of implementation studies: E0116629. PLoS
One, 10(2) doi:10.1371/journal.pone.0116629
Pecanac, K. E., Repenshek, M. F., Tennenbaum, D., & Hammes, B. J. (2014). Respecting
choices® and advance directives in a diverse community. Journal of Palliative
Medicine, 17(3), 282-287. doi:10.1089/jpm.2013.0047
Melnyk, B. M., Fineout-Overholt, E. (2015). Evidence-based practice in nursing and healthcare:
A guide to best practice. (3rd ed.). Philadelphia: Wolters Kluwer Health.

24
ADVANCE CARE PLANNING
Oczkowski, S. J., Chung, H., Hanvey, L., Mbuagbaw, L., & You, J. J. (2016). Communication
tools for end-of-life decision-making in ambulatory care settings: A systematic review
and meta-analysis. PLoS One, 11(4), e0150671. doi:10.1371/journal.pone.0150671
Ramsaroop, S., Reid, M., & Adelman, R. (2007). Completing an advance directive in the
primary care setting: What do we need for success? J Am Geriatr Soc, 55(2), 277.
doi:10.1111/j.1532-5415.2007.01065.x
Rao, J. K., Anderson, L. A., Lin, F., & Laux, J. P. (2014). Completion of advance directives
among U.S. consumers. American Journal of Preventive Medicine, 46(1), 65-70.
doi:10.1016/j.amepre.2013.09.008
Resnick, B. (2014). Theory of self-efficacy. In M. Smith & P. Liehr (Eds.), Middle range theory
for nursing (3rd ed., pp. 197-223). New York, NY: Springer Publishing Company, LLC.
Rosswurm, M. A., & Larrabee, J. (1999). A model for change to evidence-based practice.
Journal of Nursing Scholarship, 31(4), 317-322.
Spoelhof, G. D., & Elliott, B. (2012). Implementing advance directives in office
practice. American Family Physician, 85(5), 461.
Sullivan, S. S., & Dickerson, S. S. (2016). Facing death: A critical analysis of advance care
planning in the united states. Advances in Nursing Science, 39(4), 320-332.
doi:10.1097/ANS.0000000000000138
Tung, E. E., Wieland, M. L., Verdoorn, B. P., Mauck, K. F., Post, J. A., Thomas, M. R., . . .
Thomas, K. G. (2014). Improved resident physician confidence with advance care
planning after an ambulatory clinic intervention. American Journal of Hospice and
Palliative Medicine, 31(3), 275-280. doi:10.1177/1049909113485636

25
ADVANCE CARE PLANNING
Vleminck, A. D., Pardon, K., Beernaert, K., Houttekier, D., Stichele, R. V., & Deliens, L (2016).
How do general practitioners conceptualize advance care planning in their practice? A
qualitative study. PLoS One, 11(4), e0153747. doi:10.1371/journal.pone.0153747
Wissow, L. S., Belote, A., Kramer, W., Compton-Phillips, A., Kritzler, R., & Weiner, J. P.
(2004). Promoting advance directives among elderly primary care patients. Journal of
General Internal Medicine, 19(9), 944-951. doi:10.1111/j.1525-1497.2004.30117.x

26
ADVANCE CARE PLANNING
Appendix A
Search Strategy 1
CINAHL

27
ADVANCE CARE PLANNING
Appendix B
Search Strategy 2
PubMed 1

PubMed 2

28
ADVANCE CARE PLANNING
Appendix C
Search Strategy 3
Web of Science

29
ADVANCE CARE PLANNING
Appendix D
Search Strategy 4
Cochrane

30
ADVANCE CARE PLANNING
Appendix E
Evaluation Table
Citation

Conceptual
Framework

Design/
Method

Sample/
Setting

Butler et al.,
(2014).

CLT

Design:
MMR

N= 16 studies
n= 9 RCT
n=7 case
series

Decision Aids for
advance care
planning: An
overview of the
state of science
Funded by MN
EPC under
contract HHSA to
AHRQ
Bias: Author
affiliations at
acponline.org/auth
ors but unable to
be viewed
U.S.

Method:
Review of
both gray and
published
literature
along with
semistructured
interviews
for technical
brief
Purpose:
Overview of
advance care
planning
decision aids
for adults

Demographi
c: Adult PTs
with and
without
serious or
advance
illness.
Setting: OP
(15), IP (1)
Exclusion:
Studies with
children,
psychiatric
care
planning, or
current EOL
decisions,
interventions
without

Major
Variables &
Definitions
IV:
MyDirectives
IV1: Five
Wishes
IV2:
Consumer’s
Toolkit for
ACP
IV3: EOL
Decisions
IV4: Caring
Conversations
IV5: ACP
Conversation
Guide
IV6: The
Conversation
Project
IV7: The One
Slide Project
IV8:
CRITICAL
IV9:
Preferred
Priorities of
Care

Measurement

Analysis

Finding

Decision for
Use

Semistructured
telephone
interviews

NA

DV1: PF to
support
decisions aids
(12)

LoE: VI

Standardized
data extraction
form by
IPDAS to
collect
information
about
population,
decision aids,
and outcomes
Technical
brief methods
used

DV2: PF to
support clarity
(5- all video
interventions)
DV3:
Knowledge of
AD or disease
process (9)
DV4: Medium
effect
PREPARE and
Making Your
Wishes Known

Strength:
Evaluated
multiple ACP
tools
Weakness:
Technical brief
methods used
and outcomes
not
synthesized,
risk of bias not
assessed or
strength of
evidence.
Individual
studies
measured
satisfaction
rather than
IPDAS
effectiveness
measures.

Key: ASA - agreed or strongly agreed; ACP - advance care planning; AD - advance directive; AHRQ - Agency for Healthcare Research and Quality; AR - attrition rate; AU - Australia; CLT cognitive learning theory; CI – confidence interval; CST - Conversation Starter Tool; DN - authors declared none; EB – evidence based; ED - emergency department; EOL - end of life; EMR –
electronic medical record; EPC - evidence-based practice center; ERA - Elder Risk Assessment; ES – effect size; FRNR - funders report no role in study design, data collection or analysis; GHS Gundersen Health System; GRADE - grading recommendations, assessment, development, and evaluation; HC - healthcare; HCP - health care provider; HCP - healthcare providers; IM - internal
medicine; IP - inpatient; IPDAS - international patient decision aids standards; LQE - low quality evidence; LoE - level of evidence; LS - Likert Scale; MA - meta-analysis; MBI - Maslach Burnout
Scale; MMR - mixed methods research; MN - Minnesota; MNT – McNemar Test; N/A - not applicable; ND - not disclosed; NIHR CLAHRC - National Institute for Health Research Collaboration for
Leadership in Applied Health Research and Care; NP - nurse practitioner; NPT – Normalization process theory; NR - narrative review; NRT - nonrandomized trials; OP - outpatient; OR – odds ratio;
PASW - Predictive Analytics Software; PC - palliative care; PEDRo – Physiotherapy evidence based database; PGY - post-graduate year; PF – positive findings; PT - patient; QE - quasi-experimental;
QOE - quality of evidence; RC - Respecting Choices; RCR - retrospective chart review; RCT - randomized controlled trials; RN - nurse; SE – standard error; SR - systematic review; U.S. - United
States; UTD - unable to determine; WSRT – Wilcoxon Signed Ranks Test

31
ADVANCE CARE PLANNING
educational
component

IV10:
PREPARE

Inclusion:
English
studies that
assessed
effect of
decision aid
from 19902014

DV1:
Satisfaction
with decision
aid
DV2: Clarity
of patient
preferences
DV3:
Knowledge of
AD and
disease
process
DV4:
Effectiveness
of decision
aids.
Major
Variables &
Definitions
IV:CST-ACP

AR: n/a

Citation

Conceptual
Framework

Design/
Method

Sample/
Setting

Blackford et al.,
(2013).

PC practice
framework

Design:
MMR

N=7 service
locations

Method:
Multi-site
action
research with
observation,
semistructured
interviews,
medical
record audits,

n= 390
medical
record audits

Facilitating
advance care
planning in
community
palliative care:
Conversation
starters across the
client journey

n=27 semistructured
interviews
n=35 focus
group

DV: PC team
initiating
ACP
discussions in
practice

Feasibility:
Tools assessed
were publically
available and
appropriate in
ambulatory
setting

Measurement

Analysis

Finding

Decision for
Use

60 hours of
participant
observations

Directed content
analysis

The tool was
helpful
reminder for
PC team to
initiate ACP.
Experienced
staff relied
more on
clinical
judgment and
lessexperienced
PC staff

LoE: VI

Medical
record audits
to identify
potential cues
for ACP
Semistructured
interview with

NVivo Ver 8
(QSR
International)

Strength:
Useful
reminder and
educational
tool for HCP to
initiate ACP
Weakness:
May not be
applicable to
other

Key: ASA - agreed or strongly agreed; ACP - advance care planning; AD - advance directive; AHRQ - Agency for Healthcare Research and Quality; AR - attrition rate; AU - Australia; CLT cognitive learning theory; CI – confidence interval; CST - Conversation Starter Tool; DN - authors declared none; EB – evidence based; ED - emergency department; EOL - end of life; EMR –
electronic medical record; EPC - evidence-based practice center; ERA - Elder Risk Assessment; ES – effect size; FRNR - funders report no role in study design, data collection or analysis; GHS Gundersen Health System; GRADE - grading recommendations, assessment, development, and evaluation; HC - healthcare; HCP - health care provider; HCP - healthcare providers; IM - internal
medicine; IP - inpatient; IPDAS - international patient decision aids standards; LQE - low quality evidence; LoE - level of evidence; LS - Likert Scale; MA - meta-analysis; MBI - Maslach Burnout
Scale; MMR - mixed methods research; MN - Minnesota; MNT – McNemar Test; N/A - not applicable; ND - not disclosed; NIHR CLAHRC - National Institute for Health Research Collaboration for
Leadership in Applied Health Research and Care; NP - nurse practitioner; NPT – Normalization process theory; NR - narrative review; NRT - nonrandomized trials; OP - outpatient; OR – odds ratio;
PASW - Predictive Analytics Software; PC - palliative care; PEDRo – Physiotherapy evidence based database; PGY - post-graduate year; PF – positive findings; PT - patient; QE - quasi-experimental;
QOE - quality of evidence; RC - Respecting Choices; RCR - retrospective chart review; RCT - randomized controlled trials; RN - nurse; SE – standard error; SR - systematic review; U.S. - United
States; UTD - unable to determine; WSRT – Wilcoxon Signed Ranks Test

32
ADVANCE CARE PLANNING
Funding:
Department of
Health and
Ageing,
Commonwealth of
AU
Bias: DN
AU

and focus
group
interviews
Purpose:
Development
and
implementati
on of a tool
to facilitate
ACP in
community
palliative
care practices

interviews
with PC staff
Demographi
c:
Majority of
care was
provided by
PC RNs. RN
managers (6),
NP (6), PC
RN
specialists
(45), RN
(33), and
enrolled RN
(14)
Setting:
Community
PC locations:
eastern states
(5), urban (3),
regional sites
(2); northern
AU (2) with
service to
regional and
remote areas

key
informants
comprising
medical staff,
RN managers,
NPs, and
educators
Focus group
interviews
with PC staff

required more
ACP education
to develop
skills and
confidence.
Tool is a
starting point
for staff.
Participative
natures of
action research
the CST was a
practicerelevant tool
rather than a
validated
research tool
and would
require more
formal testing.

cultures/setting
s
Practice
relevant tool
but not
validated
research tool
Feasibility:
CST-ACP tool
can assist HCP
in developing
relationship
with PTs to
facilitate ACP
discussions

Exclusion:
ND
Inclusion:
ND
Key: ASA - agreed or strongly agreed; ACP - advance care planning; AD - advance directive; AHRQ - Agency for Healthcare Research and Quality; AR - attrition rate; AU - Australia; CLT cognitive learning theory; CI – confidence interval; CST - Conversation Starter Tool; DN - authors declared none; EB – evidence based; ED - emergency department; EOL - end of life; EMR –
electronic medical record; EPC - evidence-based practice center; ERA - Elder Risk Assessment; ES – effect size; FRNR - funders report no role in study design, data collection or analysis; GHS Gundersen Health System; GRADE - grading recommendations, assessment, development, and evaluation; HC - healthcare; HCP - health care provider; HCP - healthcare providers; IM - internal
medicine; IP - inpatient; IPDAS - international patient decision aids standards; LQE - low quality evidence; LoE - level of evidence; LS - Likert Scale; MA - meta-analysis; MBI - Maslach Burnout
Scale; MMR - mixed methods research; MN - Minnesota; MNT – McNemar Test; N/A - not applicable; ND - not disclosed; NIHR CLAHRC - National Institute for Health Research Collaboration for
Leadership in Applied Health Research and Care; NP - nurse practitioner; NPT – Normalization process theory; NR - narrative review; NRT - nonrandomized trials; OP - outpatient; OR – odds ratio;
PASW - Predictive Analytics Software; PC - palliative care; PEDRo – Physiotherapy evidence based database; PGY - post-graduate year; PF – positive findings; PT - patient; QE - quasi-experimental;
QOE - quality of evidence; RC - Respecting Choices; RCR - retrospective chart review; RCT - randomized controlled trials; RN - nurse; SE – standard error; SR - systematic review; U.S. - United
States; UTD - unable to determine; WSRT – Wilcoxon Signed Ranks Test

33
ADVANCE CARE PLANNING
AR: ND
Citation

Conceptual
Framework

Design/
Method

Sample/
Setting

Clayton et al.,
(2012).

CLT

Design: QE

N=21

Purpose:
Determine if
an
individualize
d training
program to
discuss EOL
issues will
improve
MDs
confidence,
communicati
on skills, and
attitudes

Demographi
c: Juniordoctors

Evaluation of a
novel
individualized
communicationskills training
intervention to
improve doctors’
confidence and
skills in end-oflife
communication
Funding: Cancer
Institute NSW
Clinical Research
Fellowship for
author.

Setting:
Teaching
hospital in
AU
Exclusion:
MDs with
competing
commitments

Bias: ND

Inclusion:
MDs who
volunteered
to internal
advertisement
s about study

AU

AR: 9%

Major
Variables &
Definitions
IV: Brief
training
program (3
teaching
sessions, 2
individual
sessions with
expert
facilitator and
simulation)
DV1: MD
communicatio
n skills
DV2: MD
confidence in
EOL
discussion
DV3: Attitude
towards
psychosocial
care
DV4: MD
sense of
accomplishm
ent

Measurement

Analysis

Finding

Decision for
Use

Pre and post
video
recorded
consultation
and deidentified
questionnaires
pre/post
training
measuring
self-assessed
confidence,
attitudes to
psychosocial
care, and MBI

PASW

DV1:
Communicatio
n significantly
improved

LoE:III

Communicatio
n- 21 specific
skills rates on
four-point
scale and
recoded using
Cohen’s
Kappa with
Landis and
Koch’s
standard for
interpretation

DS to summarize
demographics
NPT to analyze
pre and post selfreports (WSRT)
and
behavior/skills
WSRT –ordinal
items
MNTdichotomous
items

Clarity of
information
(p<0.001),
pacing of
information
(p=0.002),
empathy and
support
(p=0.022)
DV2:
Confidence
significantly
increased (Z= 3.923,
p<0.001)
DV3: Attitude
significantly
improved (Z= 2.155,
p=0.031)
DV4: Personal
accomplishme

Strength:
Short total
teaching time
in comparison
to other
workshops
with one-onone and faceto-face
interaction
Weakness:
Small, nonrandomized
sample,
involvement of
only one
institution and
lack of longer
follow-up,
participants
were
volunteers
Feasibility:
One-to-one
training
intervention (1

Key: ASA - agreed or strongly agreed; ACP - advance care planning; AD - advance directive; AHRQ - Agency for Healthcare Research and Quality; AR - attrition rate; AU - Australia; CLT cognitive learning theory; CI – confidence interval; CST - Conversation Starter Tool; DN - authors declared none; EB – evidence based; ED - emergency department; EOL - end of life; EMR –
electronic medical record; EPC - evidence-based practice center; ERA - Elder Risk Assessment; ES – effect size; FRNR - funders report no role in study design, data collection or analysis; GHS Gundersen Health System; GRADE - grading recommendations, assessment, development, and evaluation; HC - healthcare; HCP - health care provider; HCP - healthcare providers; IM - internal
medicine; IP - inpatient; IPDAS - international patient decision aids standards; LQE - low quality evidence; LoE - level of evidence; LS - Likert Scale; MA - meta-analysis; MBI - Maslach Burnout
Scale; MMR - mixed methods research; MN - Minnesota; MNT – McNemar Test; N/A - not applicable; ND - not disclosed; NIHR CLAHRC - National Institute for Health Research Collaboration for
Leadership in Applied Health Research and Care; NP - nurse practitioner; NPT – Normalization process theory; NR - narrative review; NRT - nonrandomized trials; OP - outpatient; OR – odds ratio;
PASW - Predictive Analytics Software; PC - palliative care; PEDRo – Physiotherapy evidence based database; PGY - post-graduate year; PF – positive findings; PT - patient; QE - quasi-experimental;
QOE - quality of evidence; RC - Respecting Choices; RCR - retrospective chart review; RCT - randomized controlled trials; RN - nurse; SE – standard error; SR - systematic review; U.S. - United
States; UTD - unable to determine; WSRT – Wilcoxon Signed Ranks Test

34
ADVANCE CARE PLANNING
Satisfaction:
Four-point LS

nt significantly
improved
(p=0.043); no
significant
differenced in
emotional
exhaustion
(p=0.115) or
depersonalizati
on (p=0.48)

hr) total
teaching (3 hrs
face-to-face
and 2 hrs
reviewing
material);
difficult to
schedule times

Analysis

Finding

Decision for
Use

X2 testsdemographics

DV1:
Improved
confidence in
six of eight
area surveyed
(p<0.001)

LoE: III

DV2:
Significant
improvement
of knowledge
of ACP
(p=0.001)

Weakness:
Amount of
missing data
from surveys,
participants
volunteered,

Self-assessed
confidence:
15-item, fivepoint LS
(Cronbach’s
alpha 0.934)
Attitude: 20item
questionnaire
using fivepoint LS

Citation

Conceptual
Framework

Design/
Method

Sample/
Setting

Detering, et al.,
(2014).

CLT

Design: QE

N=148

Sampling:
Convenience

n=69 HCP
who
participated
in training
and
completed
pre and post
workshop
evaluations

Teaching general
practitioners and
doctors-in-training
to discuss advance
care planning:
Evaluation of a
brief
multimodality
education
programme

Purpose:
Develop and
evaluate an
interactive
ACP
educational
program for
HCP

Major
Variables &
Definitions
IV1:
Completion
of the
multimodality
education
ACP program
(DVD,
interactive esimulation, 2
hr workshop
and training
manual)

Stress and
burnout: 22item MBI
Measurement

Pre-education
and posteducation
questionnaires
E-simulation
scores

Paired sample t
test- comparing
knowledge
MNT- general
knowledge and
attitudes/confide
nce

Strength:
Significant
results with
strong design

Key: ASA - agreed or strongly agreed; ACP - advance care planning; AD - advance directive; AHRQ - Agency for Healthcare Research and Quality; AR - attrition rate; AU - Australia; CLT cognitive learning theory; CI – confidence interval; CST - Conversation Starter Tool; DN - authors declared none; EB – evidence based; ED - emergency department; EOL - end of life; EMR –
electronic medical record; EPC - evidence-based practice center; ERA - Elder Risk Assessment; ES – effect size; FRNR - funders report no role in study design, data collection or analysis; GHS Gundersen Health System; GRADE - grading recommendations, assessment, development, and evaluation; HC - healthcare; HCP - health care provider; HCP - healthcare providers; IM - internal
medicine; IP - inpatient; IPDAS - international patient decision aids standards; LQE - low quality evidence; LoE - level of evidence; LS - Likert Scale; MA - meta-analysis; MBI - Maslach Burnout
Scale; MMR - mixed methods research; MN - Minnesota; MNT – McNemar Test; N/A - not applicable; ND - not disclosed; NIHR CLAHRC - National Institute for Health Research Collaboration for
Leadership in Applied Health Research and Care; NP - nurse practitioner; NPT – Normalization process theory; NR - narrative review; NRT - nonrandomized trials; OP - outpatient; OR – odds ratio;
PASW - Predictive Analytics Software; PC - palliative care; PEDRo – Physiotherapy evidence based database; PGY - post-graduate year; PF – positive findings; PT - patient; QE - quasi-experimental;
QOE - quality of evidence; RC - Respecting Choices; RCR - retrospective chart review; RCT - randomized controlled trials; RN - nurse; SE – standard error; SR - systematic review; U.S. - United
States; UTD - unable to determine; WSRT – Wilcoxon Signed Ranks Test

35
ADVANCE CARE PLANNING

Funding:
Development and
evaluation of Next
Step programme
by Victorian
Quality Council,
Department of
Health Victoria
Bias: ND
AU

Demographi
cs: Majority
40 years in
age with
more than 10
years of
experience.
63% not
trained in
AU.

DV1: HCP
confidence in
having ACP
conversations

Setting: 8
workshops:
Metropolian
(4)
Rural (4)

DV4:
Satisfaction
with program

Inclusions:
HCP and
doctors-intraining
Exclusion:
Not
completing
both pre and
post survey
AR: n/a

DV2: Change
in ACP
knowledge
DV3: Attitude

DV5: Esimulation
performance

Wilcoxonassessed esimulation scores
Bonferroni
correction to
adjust for
multiple
statistical
comparisons
α ≤ 0.05

DV3: No
significant
changes in
attitude
(p>0.05)
DV4: 90% of
participants
ASA the
workshop was
well presented,
88% pace was
appropriate,
85% group
discussion
helpful

unsure if less
experienced
facilitators
would produce
similar results
Feasibility:
Practical,
relatively
short, need
facilitators

65% ASA that
reading
material was
useful, 85%
DVD was
valuable, 69%
that esimulation was
helpful
DV5: (n=64)
completed esimulation at
least once,
(n=46)
completed esimulation

Key: ASA - agreed or strongly agreed; ACP - advance care planning; AD - advance directive; AHRQ - Agency for Healthcare Research and Quality; AR - attrition rate; AU - Australia; CLT cognitive learning theory; CI – confidence interval; CST - Conversation Starter Tool; DN - authors declared none; EB – evidence based; ED - emergency department; EOL - end of life; EMR –
electronic medical record; EPC - evidence-based practice center; ERA - Elder Risk Assessment; ES – effect size; FRNR - funders report no role in study design, data collection or analysis; GHS Gundersen Health System; GRADE - grading recommendations, assessment, development, and evaluation; HC - healthcare; HCP - health care provider; HCP - healthcare providers; IM - internal
medicine; IP - inpatient; IPDAS - international patient decision aids standards; LQE - low quality evidence; LoE - level of evidence; LS - Likert Scale; MA - meta-analysis; MBI - Maslach Burnout
Scale; MMR - mixed methods research; MN - Minnesota; MNT – McNemar Test; N/A - not applicable; ND - not disclosed; NIHR CLAHRC - National Institute for Health Research Collaboration for
Leadership in Applied Health Research and Care; NP - nurse practitioner; NPT – Normalization process theory; NR - narrative review; NRT - nonrandomized trials; OP - outpatient; OR – odds ratio;
PASW - Predictive Analytics Software; PC - palliative care; PEDRo – Physiotherapy evidence based database; PGY - post-graduate year; PF – positive findings; PT - patient; QE - quasi-experimental;
QOE - quality of evidence; RC - Respecting Choices; RCR - retrospective chart review; RCT - randomized controlled trials; RN - nurse; SE – standard error; SR - systematic review; U.S. - United
States; UTD - unable to determine; WSRT – Wilcoxon Signed Ranks Test

36
ADVANCE CARE PLANNING
more than once
Score preeducation (7)
and posteducation (60)
(max
score=85)
(p<0.001)
Citation

Conceptual
Framework

Design/
Method

Sample/
Setting

Durbin et al.,
(2010).

Clinical
decisionmaking
theory

Design:
Systematic
review

N=12 studies

Systematic review
of educational
interventions for
improving
advance directive
completion
Funding: ND
Bias: ND
U.S.

Purpose:
Analyze
effectiveness
of
educational
interventions
for
improving
advance
directive
completion

n= 8 RCT
n= 4 NRT
Demographi
c: Ages 26 to
93. Eight of
12 samples
predominantl
y women.
Three studies
Caucasian
only, 2
majority
African
American,
and 4
included both
races.

Major
Variables &
Definitions
IV:
Educational
interventions
IV1: written
IV2: verbal
discussions
IV3: videos
DV: AD
completion

Measurement

Analysis

Finding

Decision for
Use

Systematic
review based
on Cochrane
review and
grading
criteria

ND for
individual
studies

In 3 RCTs
combined
written and
verbal
interventions
were more
effective than
single written
interventions
in completion
of AD
(p<0.05)

LoE: I

Effectiveness
of types of
educational
interventions

α < 0.05

Strength:
High quality
evidence
Weakness:
Low number of
studies for
types of
educational
interventions
Feasibility:
Findings can
be generalized
to adult clinic
outpatients and
hospitalized
elderly

Setting: Two
studies IP, 9
Key: ASA - agreed or strongly agreed; ACP - advance care planning; AD - advance directive; AHRQ - Agency for Healthcare Research and Quality; AR - attrition rate; AU - Australia; CLT cognitive learning theory; CI – confidence interval; CST - Conversation Starter Tool; DN - authors declared none; EB – evidence based; ED - emergency department; EOL - end of life; EMR –
electronic medical record; EPC - evidence-based practice center; ERA - Elder Risk Assessment; ES – effect size; FRNR - funders report no role in study design, data collection or analysis; GHS Gundersen Health System; GRADE - grading recommendations, assessment, development, and evaluation; HC - healthcare; HCP - health care provider; HCP - healthcare providers; IM - internal
medicine; IP - inpatient; IPDAS - international patient decision aids standards; LQE - low quality evidence; LoE - level of evidence; LS - Likert Scale; MA - meta-analysis; MBI - Maslach Burnout
Scale; MMR - mixed methods research; MN - Minnesota; MNT – McNemar Test; N/A - not applicable; ND - not disclosed; NIHR CLAHRC - National Institute for Health Research Collaboration for
Leadership in Applied Health Research and Care; NP - nurse practitioner; NPT – Normalization process theory; NR - narrative review; NRT - nonrandomized trials; OP - outpatient; OR – odds ratio;
PASW - Predictive Analytics Software; PC - palliative care; PEDRo – Physiotherapy evidence based database; PGY - post-graduate year; PF – positive findings; PT - patient; QE - quasi-experimental;
QOE - quality of evidence; RC - Respecting Choices; RCR - retrospective chart review; RCT - randomized controlled trials; RN - nurse; SE – standard error; SR - systematic review; U.S. - United
States; UTD - unable to determine; WSRT – Wilcoxon Signed Ranks Test

37
ADVANCE CARE PLANNING
OP, 1
community
based.
Exclusion:
Only dates
1991 -2009.
Specific PT
populations
(i.e. HIV).
RCTs that
lacked
sufficient
data.
Inclusion:
Studies in
nursing,
medicine, and
social work
written in
English,
educational
intervention,
AD
completion as
outcome, and
AD for
general
population

Citation

Conceptual
Framework

Design/
Method

AR: n/a
Sample/
Setting

Major
Variables &
Definitions

Measurement

Analysis

Finding

Decision for
Use

Key: ASA - agreed or strongly agreed; ACP - advance care planning; AD - advance directive; AHRQ - Agency for Healthcare Research and Quality; AR - attrition rate; AU - Australia; CLT cognitive learning theory; CI – confidence interval; CST - Conversation Starter Tool; DN - authors declared none; EB – evidence based; ED - emergency department; EOL - end of life; EMR –
electronic medical record; EPC - evidence-based practice center; ERA - Elder Risk Assessment; ES – effect size; FRNR - funders report no role in study design, data collection or analysis; GHS Gundersen Health System; GRADE - grading recommendations, assessment, development, and evaluation; HC - healthcare; HCP - health care provider; HCP - healthcare providers; IM - internal
medicine; IP - inpatient; IPDAS - international patient decision aids standards; LQE - low quality evidence; LoE - level of evidence; LS - Likert Scale; MA - meta-analysis; MBI - Maslach Burnout
Scale; MMR - mixed methods research; MN - Minnesota; MNT – McNemar Test; N/A - not applicable; ND - not disclosed; NIHR CLAHRC - National Institute for Health Research Collaboration for
Leadership in Applied Health Research and Care; NP - nurse practitioner; NPT – Normalization process theory; NR - narrative review; NRT - nonrandomized trials; OP - outpatient; OR – odds ratio;
PASW - Predictive Analytics Software; PC - palliative care; PEDRo – Physiotherapy evidence based database; PGY - post-graduate year; PF – positive findings; PT - patient; QE - quasi-experimental;
QOE - quality of evidence; RC - Respecting Choices; RCR - retrospective chart review; RCT - randomized controlled trials; RN - nurse; SE – standard error; SR - systematic review; U.S. - United
States; UTD - unable to determine; WSRT – Wilcoxon Signed Ranks Test

38
ADVANCE CARE PLANNING
Houben, et al.,
(2014).
Efficacy of
advance care
planning: A
systematic review
and meta-analysis
Funding: Grant of
Lung Foundation
Netherlands,
Leusden. FRNR.
Bias: DN
Netherlands

CLT

Design: SR
and MA
Purpose:
Systematicall
y review the
efficacy of
ACP
interventions
in various
adult patient
populations

N=56 RCT
Demographi
c: Cancer (3),
Cardiac
diseases (4),
COPD (1),
CRF (4),
Dementia (1),
HIV (2),
Comorbiditie
s (24),
nursing home
residents (4),
elderly &
healthy (8),
HCP (4), and
unknown (1)
Setting: IP
(15), OP (37),
both (4)

Inclusion:
Described
original data,
RCT, and
written in
English.

Exclusion:
Pts <21 years
and studies

IV1:
Structured
intervention
tools focused
on AD
completion

Study details
recorded using
predefined
data
abstraction
form

IV2:
Structured
tools to
initiate
conversations
about EOL
planning

QualityPEDro scale

DV1:
Completion
of AD and
EOL
discussions
DV2:
Concordance
of pt
preferences
and delivered
care,
knowledge of
ACP, EOL
preferences,
quality of
communicatio
n, satisfaction
with HC,
decisional

X2 testrelationship
between
interventions
IBM SPSS
statistics 21.0
Meta-analytic
technique used
random effects
model in
RevMan 5.
Pooled OR with
95% CI
α ≤ 0.05

Agreement
between 2
reviewers=0.8
9
95% CI=0.860.93; p <0.001

LoE: I

DV1: OR 3.26;
95% CI 2.005.32;
p<0.00001

Weakness:
Multiple
instruments
available to
assess quality
of RCTs,
nature of
interventions
makes it
difficult to
blind patients,

DV2: OR 4.66;
95% CI 1.2018.08; P=0.03
DV3: OR 2.82;
95% CI 2.093.79; p<0.0001

Strength: SR
and MA of
RCTs; Good
validity

Feasibility:
Applicable to
practice

Key: ASA - agreed or strongly agreed; ACP - advance care planning; AD - advance directive; AHRQ - Agency for Healthcare Research and Quality; AR - attrition rate; AU - Australia; CLT cognitive learning theory; CI – confidence interval; CST - Conversation Starter Tool; DN - authors declared none; EB – evidence based; ED - emergency department; EOL - end of life; EMR –
electronic medical record; EPC - evidence-based practice center; ERA - Elder Risk Assessment; ES – effect size; FRNR - funders report no role in study design, data collection or analysis; GHS Gundersen Health System; GRADE - grading recommendations, assessment, development, and evaluation; HC - healthcare; HCP - health care provider; HCP - healthcare providers; IM - internal
medicine; IP - inpatient; IPDAS - international patient decision aids standards; LQE - low quality evidence; LoE - level of evidence; LS - Likert Scale; MA - meta-analysis; MBI - Maslach Burnout
Scale; MMR - mixed methods research; MN - Minnesota; MNT – McNemar Test; N/A - not applicable; ND - not disclosed; NIHR CLAHRC - National Institute for Health Research Collaboration for
Leadership in Applied Health Research and Care; NP - nurse practitioner; NPT – Normalization process theory; NR - narrative review; NRT - nonrandomized trials; OP - outpatient; OR – odds ratio;
PASW - Predictive Analytics Software; PC - palliative care; PEDRo – Physiotherapy evidence based database; PGY - post-graduate year; PF – positive findings; PT - patient; QE - quasi-experimental;
QOE - quality of evidence; RC - Respecting Choices; RCR - retrospective chart review; RCT - randomized controlled trials; RN - nurse; SE – standard error; SR - systematic review; U.S. - United
States; UTD - unable to determine; WSRT – Wilcoxon Signed Ranks Test

39
ADVANCE CARE PLANNING
about
psychiatric
AD

conflict, use
of HC
services and
symptoms

AR: n/a

Citation

Conceptual
Framework

Design/
Method

Sample/
Setting

Lund et al.,
(2015).

Normalizati
on Process
Theory

Design:
Explanatory
SR of
qualitative
implementati
on studies

N=13 studies

Barriers to
advance care
planning at the
end of life: An
explanatory
systematic review
of implementation
studies
Funding: Author
(Lund) is a post
doctoral research
fellow supported
by South Central
Strategic Health
Authority.
(Richardson &
May) partly
supported by
NIHR CLAHRC

Purpose:
Investigate
barriers and
facilitators to
implementin
g ACPs in
clinical
practice

Demographi
c: Adults in
healthcare
setting
without
mental health
problems
Setting: HC:
OP (8), IP (5)
Exclusion:
Interventions
aimed at
children and
those with
mental health
problems
Inclusion:
Implementati

DV3:
Occurrence of
EOL
discussions
Major
Variables &
Definitions
IV: Trained
staff utilizing
a structured
approach to
ACP
DV: Effective
ACP
discussions

Measurement

Analysis

Finding

Decision for
Use

Variable per
study:
individual
measurement
tools not listed
but reported
that they were
highly
structured

Data extraction
developed by
NPT

Data from
individual
articles was
not disclosed.

LoE: V

Coding frame
and taxonomy
items related to
intervention
types, clinical
contexts, and HC
systems

Interventions
most likely to
facilitate ACP
are those that
provide a
simple,
structured tool
for HCP to
take action.

Strength: SR
Weakness:
Information is
lacking about
the process of
implementing
and delivering
ACPs,
inadequate
reporting of
intervention
design and
methods of
evaluation
Feasibility:
Requires time
and trained
staff

Key: ASA - agreed or strongly agreed; ACP - advance care planning; AD - advance directive; AHRQ - Agency for Healthcare Research and Quality; AR - attrition rate; AU - Australia; CLT cognitive learning theory; CI – confidence interval; CST - Conversation Starter Tool; DN - authors declared none; EB – evidence based; ED - emergency department; EOL - end of life; EMR –
electronic medical record; EPC - evidence-based practice center; ERA - Elder Risk Assessment; ES – effect size; FRNR - funders report no role in study design, data collection or analysis; GHS Gundersen Health System; GRADE - grading recommendations, assessment, development, and evaluation; HC - healthcare; HCP - health care provider; HCP - healthcare providers; IM - internal
medicine; IP - inpatient; IPDAS - international patient decision aids standards; LQE - low quality evidence; LoE - level of evidence; LS - Likert Scale; MA - meta-analysis; MBI - Maslach Burnout
Scale; MMR - mixed methods research; MN - Minnesota; MNT – McNemar Test; N/A - not applicable; ND - not disclosed; NIHR CLAHRC - National Institute for Health Research Collaboration for
Leadership in Applied Health Research and Care; NP - nurse practitioner; NPT – Normalization process theory; NR - narrative review; NRT - nonrandomized trials; OP - outpatient; OR – odds ratio;
PASW - Predictive Analytics Software; PC - palliative care; PEDRo – Physiotherapy evidence based database; PGY - post-graduate year; PF – positive findings; PT - patient; QE - quasi-experimental;
QOE - quality of evidence; RC - Respecting Choices; RCR - retrospective chart review; RCT - randomized controlled trials; RN - nurse; SE – standard error; SR - systematic review; U.S. - United
States; UTD - unable to determine; WSRT – Wilcoxon Signed Ranks Test

40
ADVANCE CARE PLANNING
with a partnership
between Wessex
and NHS
organizations and
partners of
University of
Southhampton.
FRNR.

on of
intervention
intended to
support ACP
AR: n/a

Bias: DN
United Kingdom
(6) Canada (2),
AU (4)
U.S. (1)
Citation

Oczkowski et al.,
(2016).
Communication
tools of end-of-life
decision making in
ambulatory care
settings: A
systemic review
and meta-analysis
Funding: Grant
from Technology
Evaluation in the
Elderly Network.
FRNR.

Conceptual
Framework

Design/
Method

Sample/
Setting

CLT

Design: SR
and MA

N=76 studies
n= 46 RCTs

Purpose:
Determine
effects of
structured
communicati
on tools for
end of life
decision
making on
completion
of ACP

Demographi
c: Patients
age >50 with
no specific
medical
conditions.
Many
specifically
evaluated
populations
with cancer,
lung, heart,
neurologic, or
renal disease.

Major
Variables &
Definitions
IV: Structured
communicatio
n tools for
EOL decision
making and
ACP
IV1: Verbal
discussions
IV2: Paper
tools
IV3: Verbal
discussion
with paper
tools
IV4: Videos

Measurement

Analysis

Finding

Decision for
Use

SR using
GRADE with
GradePRO
software

Revman 5.3
software

LoE: I

OttawaNewcastle
Scale for
Cohort studies

Clinical
heterogeneity
reported using I2
calculations

Structured
communicatio
n tools
increased
DV1: ACP
(RR 2.31, 95%
CI 1.25-4.26,
p=0.007, LQE)
Completion of
AD (RR 1.92,
95% CI 1.432.59, p<0.001,
LQE)

Weakness:
Lack of
consistent
terminology
for
interventions
which may
have led to

95% CI

DV2: AD care
desired and

Strength:
Rigorous
search strategy
with GRADE,
wide variety of
interventions

Key: ASA - agreed or strongly agreed; ACP - advance care planning; AD - advance directive; AHRQ - Agency for Healthcare Research and Quality; AR - attrition rate; AU - Australia; CLT cognitive learning theory; CI – confidence interval; CST - Conversation Starter Tool; DN - authors declared none; EB – evidence based; ED - emergency department; EOL - end of life; EMR –
electronic medical record; EPC - evidence-based practice center; ERA - Elder Risk Assessment; ES – effect size; FRNR - funders report no role in study design, data collection or analysis; GHS Gundersen Health System; GRADE - grading recommendations, assessment, development, and evaluation; HC - healthcare; HCP - health care provider; HCP - healthcare providers; IM - internal
medicine; IP - inpatient; IPDAS - international patient decision aids standards; LQE - low quality evidence; LoE - level of evidence; LS - Likert Scale; MA - meta-analysis; MBI - Maslach Burnout
Scale; MMR - mixed methods research; MN - Minnesota; MNT – McNemar Test; N/A - not applicable; ND - not disclosed; NIHR CLAHRC - National Institute for Health Research Collaboration for
Leadership in Applied Health Research and Care; NP - nurse practitioner; NPT – Normalization process theory; NR - narrative review; NRT - nonrandomized trials; OP - outpatient; OR – odds ratio;
PASW - Predictive Analytics Software; PC - palliative care; PEDRo – Physiotherapy evidence based database; PGY - post-graduate year; PF – positive findings; PT - patient; QE - quasi-experimental;
QOE - quality of evidence; RC - Respecting Choices; RCR - retrospective chart review; RCT - randomized controlled trials; RN - nurse; SE – standard error; SR - systematic review; U.S. - United
States; UTD - unable to determine; WSRT – Wilcoxon Signed Ranks Test

41
ADVANCE CARE PLANNING
Bias: DN
U.S.

Setting:
Ambulatory
care
Inclusion:
RCT or
prospective
observational
studies with
control group
published in
peerreviewed
journals in
English. PTs
> 18 years
and evaluated
a
communicati
on tool to
assist patients
in EOL
decision
making
compared to
a control
group.
Exclusion:
Duplicate
references,
conference
abstracts,
study

IV5:
Computer
programs
IV6:
multimodal
interventions
IV7:
interventions
directed at
HCP vs PTs
DV1:
Completion
of ACP
DV2: Quality
of
communicatio
n between PT,
family, and
HCP; PT and
family
knowledge
about EOL
care and
available
resources; HC
resource
utilization; PT
and family
satisfaction
with EOL
care;
acceptability

care received
(RR 1.17, 95%
CI 1.05-1.30,
p=0.004, LQE,
2 RCTs)

relevant
articles being
missed; review
limited by
highly
heterogenous
nature of the
populations
and
interventions
Feasibility:
Structured
communication
tools should be
considered for
ACP
discussions in
practice

Key: ASA - agreed or strongly agreed; ACP - advance care planning; AD - advance directive; AHRQ - Agency for Healthcare Research and Quality; AR - attrition rate; AU - Australia; CLT cognitive learning theory; CI – confidence interval; CST - Conversation Starter Tool; DN - authors declared none; EB – evidence based; ED - emergency department; EOL - end of life; EMR –
electronic medical record; EPC - evidence-based practice center; ERA - Elder Risk Assessment; ES – effect size; FRNR - funders report no role in study design, data collection or analysis; GHS Gundersen Health System; GRADE - grading recommendations, assessment, development, and evaluation; HC - healthcare; HCP - health care provider; HCP - healthcare providers; IM - internal
medicine; IP - inpatient; IPDAS - international patient decision aids standards; LQE - low quality evidence; LoE - level of evidence; LS - Likert Scale; MA - meta-analysis; MBI - Maslach Burnout
Scale; MMR - mixed methods research; MN - Minnesota; MNT – McNemar Test; N/A - not applicable; ND - not disclosed; NIHR CLAHRC - National Institute for Health Research Collaboration for
Leadership in Applied Health Research and Care; NP - nurse practitioner; NPT – Normalization process theory; NR - narrative review; NRT - nonrandomized trials; OP - outpatient; OR – odds ratio;
PASW - Predictive Analytics Software; PC - palliative care; PEDRo – Physiotherapy evidence based database; PGY - post-graduate year; PF – positive findings; PT - patient; QE - quasi-experimental;
QOE - quality of evidence; RC - Respecting Choices; RCR - retrospective chart review; RCT - randomized controlled trials; RN - nurse; SE – standard error; SR - systematic review; U.S. - United
States; UTD - unable to determine; WSRT – Wilcoxon Signed Ranks Test

42
ADVANCE CARE PLANNING
protocols,
outcomes of
interest not
specifically
stated,
pediatric
studies, no
comparison
arm,
qualitative, or
not based in
ambulatory
settings

of
intervention

AR: n/a
Citation

Conceptual
Framework

Design/
Method

Sample/
Setting

Pecanac, K.
(2014).

CLT

Design: RCR

N= 732

Purpose:
Determine if
RC would
improve AD
in a racially
and
ethnically
diverse
community

Demographi
c: Decedents
from 20052010

Respecting
Choices and
advance directives
in a diverse
community
Funding: ND
Bias:
Author BJS is an
employee of GHS
who owns the
copyright to RC.

Setting: 300bed
Midwestern
metropolitan
hospital
Exclusion:
Decedents

Major
Variables &
Definitions
IV- RC in
community
DV1- AD
completion
rates for
whites
DV2- AD
completion
rates for
racial/ethnic
minority
DV3: DV1
and DV2

Measurement

Analysis

Finding

Decision for
Use

Data collected
from manual
chart review
about
prevalence
and utilization
of ADs

Stata’s
TEFFECTS
program

DV1:
β= 0.026
SE= 0.06
TS= 0.46
p= 0.648
95% CI= 0.09-0.14

LoE: III

Data included
date of
admission and
discharge, age
at discharge,
gender, length
of hospital
stay,

Regression
analysis and
matching to
analyze RC on
AD prevalence
Proportional
difference tests
to compare
consistency of
wishes by
race/ethnicity

DV2:
β=0.136
SE= 0.05
TS=2.53
p= 0.011
95% CI= 0.030.24

Strength: RC
is culturally
sensitive and
respects
individual and
spiritual needs,
EB ACP
Weakness:
RCR and
difficult to
know if
decedents were
personally

Key: ASA - agreed or strongly agreed; ACP - advance care planning; AD - advance directive; AHRQ - Agency for Healthcare Research and Quality; AR - attrition rate; AU - Australia; CLT cognitive learning theory; CI – confidence interval; CST - Conversation Starter Tool; DN - authors declared none; EB – evidence based; ED - emergency department; EOL - end of life; EMR –
electronic medical record; EPC - evidence-based practice center; ERA - Elder Risk Assessment; ES – effect size; FRNR - funders report no role in study design, data collection or analysis; GHS Gundersen Health System; GRADE - grading recommendations, assessment, development, and evaluation; HC - healthcare; HCP - health care provider; HCP - healthcare providers; IM - internal
medicine; IP - inpatient; IPDAS - international patient decision aids standards; LQE - low quality evidence; LoE - level of evidence; LS - Likert Scale; MA - meta-analysis; MBI - Maslach Burnout
Scale; MMR - mixed methods research; MN - Minnesota; MNT – McNemar Test; N/A - not applicable; ND - not disclosed; NIHR CLAHRC - National Institute for Health Research Collaboration for
Leadership in Applied Health Research and Care; NP - nurse practitioner; NPT – Normalization process theory; NR - narrative review; NRT - nonrandomized trials; OP - outpatient; OR – odds ratio;
PASW - Predictive Analytics Software; PC - palliative care; PEDRo – Physiotherapy evidence based database; PGY - post-graduate year; PF – positive findings; PT - patient; QE - quasi-experimental;
QOE - quality of evidence; RC - Respecting Choices; RCR - retrospective chart review; RCT - randomized controlled trials; RN - nurse; SE – standard error; SR - systematic review; U.S. - United
States; UTD - unable to determine; WSRT – Wilcoxon Signed Ranks Test

43
ADVANCE CARE PLANNING
He also a coauthor
of RC and is
entitled to a small
royalty if a profit
is made on the
materials.

who died in
ED

diagnosis, unit
where care
was provided
and
race/ethnicity

Inclusion:
Decedent >
18 years who
died during
hospitalizatio
n 2005-2010

U.S.

α = 0.05

DV3:
β= 0.071
SE= 0.04
TS= 1.82
p= 0.069
95% CI= 0.01-0.15

AR: n/a

Citation

Conceptual
Framework

Design/
Method

Sample/
Setting

Tung et al.,
(2014).

CLT

Design: QE

N= 144

Purpose:
Assess
internal
medicine
residents’
ACP
practices and

Demographi
c: IM
residents:
PGY-1 (35),
PGY-2 (39),
PGY-3 (32).

Improved resident
physician
confidence with
advance care
planning after an

Major
Variables &
Definitions
IV: Quality
improvement
workshop
(interactive
presentation
& chart audit)

Measurement

Analysis

Finding

Pre- and post
intervention
surveys to
assess ACP
practices in
clinic, barriers
to effective
ACP,
confidence

Descriptive
summary
statistics for
survey results
and chart audits
Pearson chisquare test and 2sample t test

Residents
reported
significant
improvement
in confidence
in finding AD
in EMR
(Scores 4.8 vs
6.46 on 7-point

impacted by
RC program,
only included
legal
documents as
AD, data only
collected in
one hospital
and did not
include
patients
discharged
from hospital
Feasibility:
Applicable to
diverse
community,
cost of
program that
includes
multiple
components
Decision for
Use
LoE: III
Strength:
Significant
results and
applicable to
other settings,
mandatory
participation

Key: ASA - agreed or strongly agreed; ACP - advance care planning; AD - advance directive; AHRQ - Agency for Healthcare Research and Quality; AR - attrition rate; AU - Australia; CLT cognitive learning theory; CI – confidence interval; CST - Conversation Starter Tool; DN - authors declared none; EB – evidence based; ED - emergency department; EOL - end of life; EMR –
electronic medical record; EPC - evidence-based practice center; ERA - Elder Risk Assessment; ES – effect size; FRNR - funders report no role in study design, data collection or analysis; GHS Gundersen Health System; GRADE - grading recommendations, assessment, development, and evaluation; HC - healthcare; HCP - health care provider; HCP - healthcare providers; IM - internal
medicine; IP - inpatient; IPDAS - international patient decision aids standards; LQE - low quality evidence; LoE - level of evidence; LS - Likert Scale; MA - meta-analysis; MBI - Maslach Burnout
Scale; MMR - mixed methods research; MN - Minnesota; MNT – McNemar Test; N/A - not applicable; ND - not disclosed; NIHR CLAHRC - National Institute for Health Research Collaboration for
Leadership in Applied Health Research and Care; NP - nurse practitioner; NPT – Normalization process theory; NR - narrative review; NRT - nonrandomized trials; OP - outpatient; OR – odds ratio;
PASW - Predictive Analytics Software; PC - palliative care; PEDRo – Physiotherapy evidence based database; PGY - post-graduate year; PF – positive findings; PT - patient; QE - quasi-experimental;
QOE - quality of evidence; RC - Respecting Choices; RCR - retrospective chart review; RCT - randomized controlled trials; RN - nurse; SE – standard error; SR - systematic review; U.S. - United
States; UTD - unable to determine; WSRT – Wilcoxon Signed Ranks Test

44
ADVANCE CARE PLANNING
ambulatory clinic
intervention
Funding: Mayo
Clinic
Bias: DN
U.S.

improve their
confidence in
discussing
ACP

Avg age 28.4;
47% female.
Setting:
Mayo
Clinical
ambulatory
clinic in
Rochester,
MN
Exclusion:
IM residents
who were
away from
Mayo campus
during
scheduled
sessions were
excused
Inclusion:
Required for
all IM
residents
AR: 8%

DV: IM
resident’s
confidence
with ACP
discussions

with ACP
tasks (8 items
on 7-point
Likert scale)
Patient’s
classified
using ERA
score

Multivariate
logistic
regression
models to
determine
association
between ACP
completion and
PT and HCP
variables
SAS version 9.3
α < 0.05

Likert scale)
p<0.001
Improved
confidence in 7
of 8 ACP
related
practices
following
interventions
(p value range
0.028 to
<0.002)

Weakness:
HCP at single
institution,
recall bias and
respondents’
tendency to
provide
socially
desirable
answers, did
no measure
impact of
intervention on
the quality of
ACP
Feasibility:
Multidimensio
nal educational
intervention is
feasible way to
improve HCP
ACP
confidence.
Generalizable
to other OP
clinics.

Key: ASA - agreed or strongly agreed; ACP - advance care planning; AD - advance directive; AHRQ - Agency for Healthcare Research and Quality; AR - attrition rate; AU - Australia; CLT cognitive learning theory; CI – confidence interval; CST - Conversation Starter Tool; DN - authors declared none; EB – evidence based; ED - emergency department; EOL - end of life; EMR –
electronic medical record; EPC - evidence-based practice center; ERA - Elder Risk Assessment; ES – effect size; FRNR - funders report no role in study design, data collection or analysis; GHS Gundersen Health System; GRADE - grading recommendations, assessment, development, and evaluation; HC - healthcare; HCP - health care provider; HCP - healthcare providers; IM - internal
medicine; IP - inpatient; IPDAS - international patient decision aids standards; LQE - low quality evidence; LoE - level of evidence; LS - Likert Scale; MA - meta-analysis; MBI - Maslach Burnout
Scale; MMR - mixed methods research; MN - Minnesota; MNT – McNemar Test; N/A - not applicable; ND - not disclosed; NIHR CLAHRC - National Institute for Health Research Collaboration for
Leadership in Applied Health Research and Care; NP - nurse practitioner; NPT – Normalization process theory; NR - narrative review; NRT - nonrandomized trials; OP - outpatient; OR – odds ratio;
PASW - Predictive Analytics Software; PC - palliative care; PEDRo – Physiotherapy evidence based database; PGY - post-graduate year; PF – positive findings; PT - patient; QE - quasi-experimental;
QOE - quality of evidence; RC - Respecting Choices; RCR - retrospective chart review; RCT - randomized controlled trials; RN - nurse; SE – standard error; SR - systematic review; U.S. - United
States; UTD - unable to determine; WSRT – Wilcoxon Signed Ranks Test

45
ADVANCE CARE PLANNING
Appendix F
Synthesis Table
Author
Year
Level of Evidence
Design
Country

Butler
2014

Blackford

Clayton

Detering

Durbin

Houben

Lund

Oczkowski

Pecnac

Tung

2013

2012

2014

2010

2014

2015

2016

2014

2014

VI

VI

III

III

I

I

V

I

III

III

MMR

MMR

QE

QE

SR

SR and MA

SR Qualitative

SR & MA

RCR

QE

AU

AU

AU

AU

US

Netherlands

UK, CA, AU, US

US

US

US

X (2)

X (15)

X (9)

X (37)

X (8)

X

X (1)

X (4)

X (5)

Setting
Inpatient

X (15)

Outpatient

X (1)

X
X

X

Community or Mixed
X

X
X

X

X

X

E-Simulation

X

X

X

Lecture

X

X

X

Reading

X

X

X

HCP focused education

Observation

X

Individual training

X

Video

X
X

Structured tools
Discussion

X

X

X

X

X

X (3)

X

X

X
X (5)

Computer Program

X (6)

Multiple interventions

X (2)

X

X

X

X

X

Written
Video

X
X (9)
X (4)

X

X

X

X

X

X

X (21)

Key: AU – Australia; CA – Canada, MA - meta-analysis; MMR - mixed methods research; RCR - retrospective chart review; QE - quasi-experimental; SR systematic review; U.S. - United States; X- applicable to study; ↑ - positive finding; * - significant; ≠ - no significance

46
ADVANCE CARE PLANNING

Outcomes Evaluated
Patient satisfaction
AD Completion rates
Rate of ACP Discussions

↑*

↑*

Provider Pre/post survey
Communication skills
Confidence
Attitude

↑*

↑

↑

↑*
↑*

↑*
↑*

↑*

↑*

↑*

X

X

↑*

↑*

↑*

↑*

↑*

↑*

≠

↑*

Key: AU – Australia; CA – Canada, MA - meta-analysis; MMR - mixed methods research; RCR - retrospective chart review; QE - quasi-experimental; SR systematic review; U.S. - United States; X- applicable to study; ↑ - positive finding; * - significant; ≠ - no significance

47
ADVANCE CARE PLANNING
Appendix G
Self-Efficacy Model

The Theory of Self-Efficacy (Resnick, 2014)

48
ADVANCE CARE PLANNING
Appendix F
Model for Evidence-Based Practice Change

The Model for Evidence-Based Practice Change (Melnyk & Fineout-Overholt, 2015)

49
ADVANCE CARE PLANNING
Appendix G
Letter of Support

50
ADVANCE CARE PLANNING

51
ADVANCE CARE PLANNING
Appendix H
Institutional Review Board Approval Letter

52
ADVANCE CARE PLANNING

53
ADVANCE CARE PLANNING
Appendix I
Participant Informed Consent

54
ADVANCE CARE PLANNING
Appendix J
Demographic Questionnaire

55
ADVANCE CARE PLANNING
Appendix K
Budget
Table 1
Projected cost
Expense Items
Personnel
Project director (DNP Student)
20 hrs @ $40/hr
ACO Chief Operating Officer
1 hrs/month x 2 months @
$35/hr
Primary Care Providers (1)
Initial training 1 hr @ $75/hr
Advance practice providers (3)
Initial training 1 hr @ $45/hr
Office Manager
Initial training and organization
of event 3 hr @ $20/hr
Equipment/Materials
Provider resource materials
$5/each x 10
Office/Operations
Utilizing physician’s office for
implementation of project
Lunch at initial meeting &
training 10 people at $10 pp
Total Expenses

Expenses

In-Kind Support

$800.00

$70.00
$75.00
$135.00

$60.00

$50.00

$75.00
$100.00
$150.00

$1215.00

56
ADVANCE CARE PLANNING
Appendix L
Statistical Analysis
Table 2
Demographics
Age
Gender:
Female
Male
Race/Ethnicity
Caucasian
Hispanic/Latino
Black/African
American
Asian
Native American
Other
Highest Level of
Education
High School degree
Associate’s degree
Bachelor’s degree
Master’s degree
Doctorate degree
Other
Role
Office Manager
Registered Nurse
Nurse Practitioner
Physician Assistant
MD/DO
Medical Student
Other
Years of Experience
Years in Current Role

Percent (%)

Frequencies

66.7
33.3

4
2

100
0
0

6
0
0

0
0
0

0
0
0

0
0
33.3
50
16.7

0
0
2
3
1

1
0
1
2
1
1
0

16.7
0
16.7
33.3
16.7
16.7
0

Mean (SD)
42.5 (19.25)

13 (17.05)
13 (17.05)

57
ADVANCE CARE PLANNING
Table 3
Pre and Post Intervention Confidence Score Resultsa
POSTTS-PRETS
Z
-2.207a
Asymp. Sig (2-tailed) .027
a. Wilcoxin Signed Ranks Test
b. Based on negative ranks