Editorial Open AccessBruning and Baghurst, Bus Eco J 2013,

Editorial Open Access
Bruning and Baghurst, Bus Eco J 2013, 4:2
DOI: 10.4172/2151-6219.1000e101
Volume 4 • Issue 2 • 1000e101
Bus Eco J
ISSN: 2151-6219 BEJ, an open access journal
A major concern for health care leadership is the increasingly
tenuous relationship between the primary stakeholders within
the
system that include patients, providers, and payers. Decreased
trust
between stakeholders changes the very culture of interactions
and
communication which in turn leads to a relationship breakdown
between the stakeholders [1-3]. Movement toward patient-
centered
care allows physicians to act as a “fact provider” in the
physician-patient
relationship which permits patient autonomy and self-
determinism [3].
Consumer-driven health care requires increased participation
from
patients regarding care decisions; this requires access to
understandable
information that directly compares options [4]. Unfortunately,
patients
do not always have adequate and transparent information on
costs or
quality of care to make ethical and appropriate decisions

regarding
health care [5,6]. Thus, they must rely on others to ethically
select the
best options with respect to care and cost.
Health care leaders perform an essential role in the success or
failure of relationships between the various stakeholders. Ethics
integrates features required to promote positive relationships.
Voges [7]
described five principles involved with health care leadership
decision-
making. Beneficence is the first principle, and can be
considered as the
obligation of benefiting staff, patients, organization, and
community.
Health care leaders’ decisions must advance stakeholders’
various
positions and promote population health. Decisions must meet
the
second principle of non-maleficence, the responsibility to bring
no
harm to patients, staff, organization, or community. Poor
economic
decisions lead to potential loss for health care organizations
including
service lines or even failure of the organization. These
decisions require
obligation to stakeholders of the particular organization. Either
patients
of the organization, providers, or other community members
suffer
when poor economic decisions are made and organizations fail.
Respect for individuals and their autonomy is the third principle
of
ethical decision-making for leaders. Ethical dilemmas occur

between
providers, payers, and patients. As a result, tension occurs as
conflicting
priorities transpire around individual decisions regarding
patient
care and autonomy. This challenge occurs as patients expect
certain
treatment options that payers do not want to provide payment
for or
providers do not feel are warranted.
The fourth principle of justice requires that leaders provide fair
and
unbiased concern when making decisions. One of the primary
roles of
health care leaders is to promote the organization and improve
function
and margin. Decisions that negatively influence the
organization
decrease the organization’s ability to continue meeting its
mission.
Development of sustainable relationships among the
stakeholders
improves the probability of success.
The previous four principles are combined into providing for
a maximal competence in decision-making or the fifth principle
of
utility. Health care leaders have a responsibility to the
community in
which the organization functions. A poor relationship between
the
various stakeholders threatens the organization’s ability to
remain
functional. Organizations that fail negatively influence and

harm the
community to which the organization means to serve. Leaders
that
understand and work to improve the three primary relationships
improve the community.
This article reviews the three stakeholder relationships that
occur
in health care, and discusses some of the ethical issues that
strain those
relationships. Payers are the organizations which provide
payment
for services rendered. These payers may include government,
primary
*Corresponding author: Paul Bruning, Summit Orthopedics,
United States,
E-mail: [email protected]
Received August 25, 2013; Accepted August 27, 2013;
Published September
02, 2013
Citation: Bruning P, Baghurst T (2013) Improving Ethical
Decision Making in
Health Care Leadership. Bus Eco J 4: e101. doi: 10.4172/2151-
6219.1000e101
Copyright: © 2013 Bruning P, et al. This is an open-access
article distributed under
the terms of the Creative Commons Attribution License, which
permits unrestricted
use, distribution, and reproduction in any medium, provided the
original author and
source are credited.
Abstract

Purpose: The purpose of this article discussion is to describe the
application of ethical decision-making and the
three primary relationships within health care leadership.
Healthcare change occurs rapidly and increases tension
and mistrust between payers, providers, and patients.
Application of ethical standards to decision-making and change
decreases healthcare cost and improves trust in change
processes.
Approach: Health care challenges occur among three primary
relationships. These relationships include the patient
and provider, patient and payer, and provider and payer. A
plethora of leadership models exist with regard to leading
change; however, these models do not consider that leaders are
not always concerned with the ethical decision-making
process. Evaluation of the ethical principles, healthcare
relationships, and recent healthcare changes found in the
Patient Protection and Affordable Care Act guide the article's
discussion.
Findings: Application of ethical principles to transformational
leadership improves healthcare relationships
and alleviates stress and tension produced by change.
Healthcare leaders have an expectation to provide ethical
considerations during change management and the decision-
making process which influences the various relationships
found in healthcare.
Value: Healthcare leaders are in the unique position to improve
healthcare using ethical principles. Because health
care reform requires ethical decision-making from leaders, the
application of ethical principles to the various relationships
health care leader's influence creates fundamental and
successful change in health care.

Improving Ethical Decision Making in Health Care Leadership
Paul Bruning1* and Timothy Baghurst2
1Summit Orthopedics, United States
2Oklahoma State University
Business and Economics
JournalBu
si
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ss
an
d E conomics
Journal
ISSN: 2151-6219
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Decision Making in Health Care Leadership. Bus Eco J 4: e101.
doi: 10.4172/2151-
6219.1000e101
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insurance, and work compensation payer organizations.
Providers are
the individuals or organizations that provide various
components of
care or work to improve individual health. Patients are the
individuals
seeking care for various illness, injuries, or detriments to
wellbeing.
Leaders who identify and understand these ethical dilemmas are
empowered to positively influence the relationships among
these
primary stakeholders and improve the healthcare system.
Northouse

[8] explained that promotion of a collaborative climate requires
expected standards of excellence; these standards of excellence
require
ethical decision-making.
Leadership Role in the Health Care Relationship Triad
Leaders must understand the three primary relationships in
health care to determine what changes can be made to improve
the
effectiveness of these relationships. The following sections
contain
a guide to the leadership role in the various relationships. The
three
relationships considered within the model are patient–provider,
patient–payer, and provider–payer. Leadership influences these
various
roles and participates in helping direct the challenge of
introducing and
leading change.
Patient Physician Relationship
As patient and physician relationships become increasingly
strained, patients grow increasingly suspicious of providers [1-
3].
Leadership in health care must work to engage ethical decision-
making in the patient and physician relationship. The
application of
ethical decision-making improves working relationship and trust
for
both the patient and physician. Physicians provide facts in
patient-
centered care permitting shared decision-making between
patient and
provider [3]. Patients must trust providers to offer the best

options for
care without influence of economic benefit for the provider.
However,
without trust patients are less-confident that decisions made are
in
their best interest. Balint and Wayne [9] identified six
principles that
influence patient and physician relationships that include the
“Basic
Fault…Apostolic Function…Mutual Investment
Company…Drug
Doctor and Therapeutic Agents…Deeper Diagnosis…and
Conspiracy
of Anonymity”. These principles explain how patients react to
life
experiences and how these experiences define individuals.
Because
communication influences understanding and cooperation
increases
trust between both parties, physicians must monitor their
interaction
with patients to avoid a false sense of security. This false sense
may
cause potential harm to patients because alternative treatments
are not
offered. Thus, to alleviate this concern the provider must
understand
and listen to the patient’s life circumstances. A failure to do so
may
limit how much the patient’s concerns are considered in the
decision
making process.
Leadership influences and improves relationships when a
mutual
relationship of the provider and patient occurs. Portman [2]

indicates
that patient physician interactions are consensual and not
obligatory.
Both parties have a responsibility to the relationship and must
be
willing to negotiate during conflict. The patient and physician
may
both benefit from improving their interaction and relationship.
Managing this relationship requires ethical decision-making
based on
core competencies and characteristics of the leader.
Payer Patient Relationship
Challenges to the prayer and patient relationship occur because
insurance companies profit from collecting premiums and not
paying
health care costs. Patients who obtain insurance desire benefit
from
premiums through access to effective health care. Although
premiums
decrease the sense of health care cost, they also create a culture
of
entitlement to health care [10]. Several processes and problems
occur
that increase the challenges of health care leadership with
respect to
payers and patients. Two of those challenges include moral
hazard and
insurance companies creaming or skimming patient populations.
First,
moral hazard results when insurance insulates a patient from
health
care costs. This process of moral hazard increases the volume of
services

sought. Refusing treatment or insurance coverage of patients
with illness
potentially increases costs above premium or contracted
payment and
introduces the concept of dumping. Removing the pre-existence
or
denial of health care insurance coverage within the Affordable
Care Act
of 2010 has proved popular within the United States. This
provision
eliminates payer ability to deny coverage or for dumping to
occur.
Another challenge for leadership in the patient and payer
relationship comes from the payers creaming or skimping on
coverage.
Creaming occurs as payers seek healthy patients who demand
fewer
services than premium cost paid. Providing less quality of care
for a
condition during a specified length of time is skimping. These
actions
increase tensions between payers and patients, but occur
commonly,
and aid in increasing the profit-margin within the insurance
industry.
Leadership within health care can improve this patient – payer
relationship by providing patients with adequate and transparent
information on costs or quality [2,3]. Challenges occur when
costs
vary based on health care provider. Currentl y prices are
negotiated
between providers and payers and are based on market leverage
rather
than outcomes or true value of service provided [11]. However,

ethical
decision-making applied to leadership characteristics can
improve the
relationship of patient and payer when appropriately addressed.
Payer Provider Relationship
Health care leaders function on both sides of the provider and
payer process creating an opportunity to reduce health care
costs and
more efficiently control resources. The decisions of a physician
can
shape the quality, quantity, and costs associated with the health
care
system [12]. Unfortunately a physician’s decisions in this
regard are
often based on market trends while the decisions and practices
of the
provider generally adopt a “follow the pack” mentality [12].
Thus, peers
play a vital role in influencing practice which contradicts the
evidence-
based practice preferred by payers.
Many factors influence the health care industry’s reimbursement
of
healthcare providers. For example, reimbursement rates for
physicians
are calculated using complex formulas including elements such
as
physician time, skill required, and intensity of work [2].
Various payer
calculations are used to determine payments to providers.
Diagnosis-
related groups provide payment levels based on diagnosis,
surgery,

patient age, discharge destination, and patient sex. Other
payment
schemes include ambulatory payment categories, resource-based
relative value scale, and resource utilization groups. Fee-for-
service
payments provide conflict to the provider and payer
relationship.
Franzini et al. [13] suggested that the current system of
reimbursement
creates a culture of money where some providers overuse more
profitable services. This system of various payments occurs
through
numerous agreements including per diem rates, capitation, and
fee-
for-service adding complexity and conflicting incentives to
provider
[4,11].
The Massachusetts attorney general conducted a study on price
differences paid by insurers to providers and found that,
compared
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to the lowest-paid physician group, the highest paid physician
group
received 145% more for the same procedure [11]. This
imperfect free
market increases the complexity of the health care system and
provides
avenues for unethical behavior and practices. Multiple payers
create
different requirements for reimbursement [14] and it is
therefore
unsurprising that administrative costs in health care contribute
significantly to the United States health care spending [15].
Aggregate
costs for administration in health care that include
documentation,
coding, billing, and dealing with multiple insurance payers
exceeded
31% of total health care costs in the United States [15,16].
Blanchfield
et al. [15] estimated that a typical 10 physician practice accrues
administrative costs exceeding $250,000 per year.
Challenges to health care leadership come from reducing the
variation in payments and payers. Health care leadership is
challenged
through contracting payment plans through multiple payers
nullifying
any chance for clear and transparent cost of care comparisons.

Individual payers are able to pay different rates for the same
services
depending on contracts arranged with providers. This pricing
variance
interferes with the three relationships defined within this
article.
Further challenges come from helping providers accept
evidence-
based medicine that potentially decreases reimbursement but
also
cost to the system. Health care market forces stray considerably
from
ethical free market economics. Price transparency does not
exist,
individuals often do not have the ability to choose when seeking
care
or treatment, and individuals most often do not bear the full
cost of
accessing the health care system. Vladeck and Rice [6] stated
that health
care reimbursement and economics does not provide an ethical
market
as providers, even those with virtuous intentions, may guide
patients
in the wrong direction caused by incentives within a fee-for-
service
payment structure. The creation of a model constructed to
address this
issue by fostering ethical decision-making based on solid
leadership
characteristics has the potential to improve the health care
system.
Ethical Decisions
Health care leaders encounter ethical situations concerning

resource limitations, quality of care, cost-effectiveness,
efficiencies, and
organizational need to produce profit margins [17,18]. Further
ethical
dilemmas in health care occur when leadership must balance
employee
and patient rights [18]. The present health care dilemma
increases
ethical challenges for leadership [18,19], yet it is evident that
leadership
within health care requires guidance on ethical decision-
making.
Ethical Reasoning within the Patient Protection and
Affordable Care Act (PPACA)
According to Lachman [19], several issues are addressed
through
ethical justifications in the Patient Protection and Affordable
Care Act
of 2010.The lack of distributive justice is a primary validator of
the need
for change in the relationship of the patient and payer [19]. The
U.S.
Census Bureau identified over 46.3 million uninsured
individuals in the
United States. Thus, the decision to require insurance coverage
proves
challenging ethically, as the expense could cause significant
harm to
financially struggling individuals. Individuals invariably require
health
care services, and the Emergency Treatment and Labor Act of
1986
prohibit hospitals from denying care based on inability to pay or
lack

of insurance. This uninsured care costs approximately $100
billion
annually [19], and hospitals face challenges from
uncompensated care
and the need to generate revenue to provide care for other
individuals.
Unfortunately, this dilemma causes cost shifting and increased
charges for those individuals with health insurance which
results in
an approximate $1,000 annual premium increase for individuals
with
insurance [19]. Requiring affordable health insurance, as
described
in the PPACA, promotes the ethical concepts of beneficence and
non-maleficence whereby individuals are required to obtain
health
insurance to reduce cost shifting [19]. This coverage proves
affordable
when purchased through health care exchanges.
A growing ethical dilemma in health care results from a high
resource demand system with an increasingly aging population.
Hosseini [17] raised the ethical dilemma of age-based rationing
of
health care services. Individuals over the age of 65 consume
four times
the per capita cost of health care as those under the age of 65.
Lachman
[19] described that 30 percent of Medicare dollars are spent
during the
last year of life and half of those funds are spent in the last 60
days of life.
Younger individuals are cheaper to insure and require limited
resources
from the health care system. The elderly use a

disproportionately larger
apportion of health care resources. These resources tend to
include
more complicated and expensive technolo gies and treatments
[17].
This places an ethical burden on health care leaders to make
decisions
that support, promote, and transform change.
National policy and reform within health care are driven by
ethics.
Senator Kennedy, in his last letter to President Obama regarding
health care reform stated that “what we face is above all a moral
issue:
at stake are not just the details of policy, but the fundamental
principles
of social justice and the character of our country” [20]. The
challenge
for leadership is because ethics overlaps with regulations, law,
and
compliance but these are not the same or equal.
Ethical Decision Making in Health Care Economics
Health care market forces stray considerably from ethical free
market economics. Vladeck and Rice [6] suggest that health
care
reimbursement and economics does not provide an ethical
market as
providers, even those with virtuous intentions, may guide
patients in
the wrong direction due to incentives within a fee-for-service
payment
structure. This system of various payment schemes through
numerous
agreements including per diem rates, capitation, and fee-for-

service
adds complexity and conflicting incentives to providers [4,11].
For
example, Franzini et al. [13] reported that Medicare spendi ng in
McAllen, Texas was 86% higher than in El Paso, Texas. At the
same time
Blue Cross patients in McAllen, Texas cost 7% less to cover
than patients
in El Paso, Texas. Franzini et al. [13] indicated that the current
system
of reimbursement creates a culture of money where some
providers
overuse more profitable services. According to Kaufman, the
system
of incentives causes potential challenges to the behavior of
providers.
The Massachusetts attorney general’s study noted that, “instead
prices
reflect the relative market leverage of health insurers and
healthcare
providers”.
Health care leaders must apply the concepts of ethical decision-
making when confronted with the questions of economic
influences.
The complexity of reimbursement and the various revenue
streams
create distrust in relationships. Further complicating the
relationships
are the reality that the combinations of moral hazard and
entitlement
insulate individuals from costs of health care. This causes
individuals
to have difficulty appreciating the value and price of health care
until
needed.

Practical Steps to Improve Ethical Decision Making in
Health Care
Health care change continues to move forward at an exponential
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rate with no indication of slowing. The new road to success in
an environment of instantaneous access to information requires
organizational ability to adapt [21]. Former models of
organizational
administration, gathered from the manufacturing system, do not
apply
neatly to the complex atmosphere of individual patients.
Humans are
much more complex than automobiles or stereo systems.
Individual
patients have comorbidities, experiences, and complex emotions

that influence the interactions. Providers and payers have
different
visions, goals, and experiences that further complicate the very
nature
of the relationships. One only needs to look at various health
care
policies, which are put in place to improve the system, that
result in
downstream problems and potential crisis. Leaders must
understand
these complex relationships and provide ethical principles to
decisions
made regarding the relationships within health care.
Trusting Relationships
Dye and Garman [22] argued that “developing trust is vital for
highly effective leadership; in many ways, it is the glue that
holds work
groups and organizations together”. Earning trust requires
remaining
accessible, continuing authenticity, and modeling of behaviors
expected
[21,22]. These characteristics help develop trust from staff and
other
stakeholders. Building trust in the relationships provides
framework for
change. This trust advances the ability to provide visions and
goals each
of the three relationships can believe.
Trust also builds with focus on similarities, shared principles,
common vision and goals, and clear benefits from collaboration
[20]. Physicians desire autonomy in decisions and take pride in
their
offerings of patient care. Patients want to improve their health

status
and have some level of decision-making within their own care
process.
Payers desire to decrease the cost of care while providing the
insured
with access to evidence-based medicine. While on the surface
there
is a common goal of improving the individual’s health there is a
great
deal of mistrust between the stakeholders. Health care leaders
have the
ability to improve this trust with the use of evidence-based and
ethical
decision-making.
Common Vision
While a common vision seems implied within health care the
various
stakeholders’ goals create differences in perceptions of how to
reach the
common vision. Physician’s desire for autonomy regarding
treatment
decisions may be at odds with a payers desire to reduce the cost
of care.
Payer’s rationale to deny coverage of a controversial medication
may
be at odds with a patient’s desire to use the medication to fight
their
ailment. Patient’s emotional state or asymmetric information
creates
conflict within the relationship of patient and provider.
Health care leaders must provide the common vision of these
relationships and define these shared visions based on ethical
standards

and principles. Without appropriate modeling of ethical
behaviors
vision and values are lost. Providers, patients, and payers that
do not
display behaviors consistent with the common vision threaten
the
relationships. The challenge for stakeholders comes from
forgetting the
past and failures of ethical behaviors and moving forward to
build and
model the common vision.
Cooperation
Health care leaders must identify, describe, and reinforce the
benefits of collaboration between the various health care
relationships.
This includes clarification of the ethical standards around
decisions.
Decisions based on ethical principles increase collaboration and
help
develop understanding of the consequences of failure to
collaborate.
When providers collaborate with patients on care decisions the
similarities and differences of opinion are able to be discussed
and
understood from each perspective. Focusing on the similarities
helps
develop shared decisions and mutual respect. These processes
improve
the outcomes of care.
Conclusion
Health care leaders must have the courage to act and act
ethically.

Decisions are complex and influence the various relationships
in
health care. Atchison and Bujak [21] wrote, "Healthcare leaders
today
understand that the complexity of change issues demands
courage to
stay on the right course. Any systematic change process will
offend at
least one constituency. Courage in its simplest form is the
capacity to
act. Talking, analyzing, and processing are all good only if they
lead to
action".
Basing decisions on ethical process helps progress the three
most
common relationships in health care. Leaders using ethical
decision-
making are able to defend and hold strong to how these
decisions
influence the relationships of patient, physician, and payer.
Ethical
decision-making encourages leader’s ability to act and improve
health
care decisions and relationships.
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executive+partnership.&dq=Leading+transformational+change,+

the+physician-
executive+partnership.&hl=en&sa=X&ei=8XIdUp6eL4jBrAeBs
4D4CQ&ved=0CC0Q6AEwAA
http://books.google.co.in/books?id=iPRFAAAAYAAJ&q=Leadi
ng+transformational+change,+the+physician-
executive+partnership.&dq=Leading+transformational+change,+
the+physician-
executive+partnership.&hl=en&sa=X&ei=8XIdUp6eL4jBrAeBs
4D4CQ&ved=0CC0Q6AEwAA
http://books.google.co.in/books?id=ITTXPAAACAAJ&dq =Exce
ptional+Leadership,+16+critical+competencies+for+healthcare+
executives.&hl=en&sa=X&ei=gHYdUs_UIcvNrQf69oGoCQ&ve
d=0CC8Q6AEwAA
http://books.google.co.in/books?id=ITTXPAAACAAJ&dq=Exce
ptional+Leadership,+16+critical+competencies+for+healthcare+
executives.&hl=en&sa=X&ei=gHYdUs_UIcvNrQf69oGoCQ&ve
d=0CC8Q6AEwAA
http://www.emeraldinsight.com/journals.htm?articleid=1959247
http://www.emeraldinsight.com/journals.htm?articleid=1959247
http://www.ncbi.nlm.nih.gov/pubmed/20444780TitleCorrespond
ing authorAbstractLeadership Role in the Health Care
Relationship Triad Patient Physician Relationship Payer Patient
Relationship Payer Provider Relationship Ethical Decisions
Ethical Reasoning within the Patient Protection and Affordable
Care Act (PPACA) Ethical Decision Making in Health Care
Economics Practical Steps to Improve Ethical Decision Making
in Health Care Trusting Relationships Common Vision
CooperationConclusionReferences

Research and Applications
Opportunities for addressing gaps in primary care shared
decision-making with technology: a mixed-methods
needs assessment
Anjali J. Misra,
1,2
Shawn Y. Ong,
3
Arjun Gokhale,
3
Sameer Khan,
3
and
Edward R. Melnick4
1Department of Brain and Cognitive Sciences, Massachusetts
Institute of Technology, Cambridge, Massachusetts, USA,
2School
of Public Health, University College Cork, Cork, Ireland,
3Department of Internal Medicine, Yale School of Medicine,
New Haven,
Connecticut, USA and 4Department of Emergency Medicine,
Yale School of Medicine, New Haven, Connecticut, USA

Corresponding Author: Edward R. Melnick, MD, MHS, Yale
School of Medicine, 464 Congress Ave, Suite 260, New Haven,
CT 06519, USA; [email protected]
Received 1 March 2019; Revised 13 June 2019; Editorial
Decision 27 June 2019; Accepted 9 July 2019
ABSTRACT
Objectives: To analyze current practices in shared decision-
making (SDM) in primary care and perform a needs
assessment for the role of information technology (IT)
interventions.
Materials and Methods: A mixed-methods study was conducted
in three phases: (1) ethnographic observation
of clinical encounters, (2) patient interviews, and (3) physician
interviews. SDM was measured using the vali-
dated OPTION scale. Semistructured interviews followed an
interview guide (developed by our multidiscipli-
nary team) informed by the Traditional Decision Conflict Scale
and Shared Decision Making Questionnaire.
Field notes were independently coded and analyzed by two
reviewers in Dedoose.
Results: Twenty-four patient encounters were observed in 3
diverse practices with an average OPTION score of
57.2 (0–100 scale; 95% confidence interval [CI], 51.8–62.6).
Twenty-two patient and 8 physician interviews were

conducted until thematic saturation was achieved. Cohen’s
kappa, measuring coder agreement, was 0.42. Pa-
tient domains were: establishing trust, influence of others,
flexibility, frustrations, values, and preferences. Phy-
sician domains included frustrations, technology (concerns,
existing use, and desires), and decision making
(current methods used, challenges, and patients’ understanding).
Discussion: Given low SDM observed, multiple opportunities
for technology to enhance SDM exist based on
specific OPTION items that received lower scores, including:
(1) checking the patient’s preferred information for-
mat, (2) asking the patient’s preferred level of involvement in
decision making, and (3) providing an opportunity
for deferring a decision. Based on data from interviews, patients
and physicians value information exchange
and are open to technologies that enhance communication of
care options.
Conclusion: Future primary care IT platforms should prioritize
the 3 quantitative gaps identified to improve
physician–patient communication and relationships.
Additionally, SDM tools should seek to standardize com-
mon workflow steps across decisions and focus on barriers to
increasing adoption of effective SDM tools into

routine primary care.
Key words: primary health care, decision making, medical
informatics, physician–patient relations, needs assessment
VC The Author(s) 2018. Published by Oxford University Press
on behalf of the American Medical Informatics Association.
This is an Open Access article distributed under the terms of the
Creative Commons Attribution Non-Commercial License
(http://creativecommons.org/licenses/by-nc/4.0/),
which permits non-commercial re-use, distribution, and
reproduction in any medium, provided the original work is
properly cited. For commercial re-use, please contact
[email protected] 447
JAMIA Open, 2(4), 2019, 447–455
doi: 10.1093/jamiaopen/ooz027
Advance Access Publication Date: 31 July 2019
Research and Applications
https://academic.oup.com/
https://academic.oup.com/
INTRODUCTION
National policy such as the Health Information Technology for
Eco-
nomic and Clinical Health (HITECH) Act, has promoted

technology
to become a larger part of healthcare delivery.1 This has driven
clini-
cians to adopt electronic health record (EHR) systems in both
inpa-
tient and outpatient settings with 96% of nonfederal acute care
hospitals and over 86% of office-based physicians reporting
adopt-
ing some type of EHR in their practices by 2015 and 2017,
respec-
tively.2,3 There is evidence that technology has improved
patient
safety, organizational efficiency, and patient satisfaction in
health-
care.4–6 In the decades that have passed since, there has been a
sig-
nificant effort to utilize technology to improve all aspects of
health
care.7,8
Recent studies have shown that patients demonstrate a willi ng-
ness to utilize technology to engage with their health care such
as
with mobile applications or internet resources.9,10 In a 2017

study
surveying 121 patients in the Chicago metropolitan area,
interest in
a mobile health app for patient education was 63.7% and
increased
to 68.4% when physicians referred the app.11 In addition, there
is
emerging evidence that increased patient engagement leads to
better
outcomes and increased patient satisfaction.12 Technology is
in-
creasingly becoming an accepted medium through which to
provide
access to information and may represent an opportunity to reach
historically difficult to access populations including
adolescents,
young adults, low-income populations, less educated adults, and
those with unstable home addresses as these populations have
the
highest rates of mobile phone usage.13–15
One major challenge with current technological solutions is that
they often focus predominantly on either the provider or the
patient

without considering both parties together to make a joint
informed
or shared decision. However, research and technology is
starting to
focus on these joint decisions with benefits to both the patients
and
providers. An example of this can be seen with a patient-
centered
clinical decision support app created by one of the authors that
was
used in the emergency department for minor head injury and
resulted in an increased awareness of the utility of CT imaging
after
head injury for patients with a high degree of clinician
acceptabil-
ity.16 Decision aids are a particularly appealing tool because
they
can be individualized to treatment options and patient
conditions,
contributing to a more patient-centered approach to primary
care as
has been well documented with diabetes.17,18 However,
barriers re-

main to the widespread adoption of such tools. These include
per-
ceptions among clinicians that such tools may reduce
professional
autonomy, incur additional medico-legal responsibilities, and
im-
pose new technical and usability problems.19
Over the last several decades, clinical practice has evolved to
place greater value on patient involvement in making personal
health care decisions.20 Patient-centered care is reflected in
SDM
practices, which emphasize information exchange between the
pa-
tient and physician, as well as their joint involvement in
deciding on
a treatment plan.21,22 Prior work has noted the difficulty of
imple-
menting SDM due to limited time, training, and available
decision
aids.23 To date, analyses have mostly focused on paper-based
deci-
sion aids and have suggested improvements in patient
engagement

with decision making. The attitudes of clinicians and patients
to-
ward incorporating technological solutions into this process
have
remained unexamined. Therefore, in this study, we aimed to
assess
the current level of the quality of SDM in primary care clinical
encounters and to perform a needs assessment for opportunities
for
SDM that could benefit from health information technology (IT)
interventions. This information can be used to inform
development
of applications or platforms that foster communication and SDM
between the clinician and patient for decisions such as chronic
dis-
ease medications, contraception, or screening test options. Our
long-term goal is to inform the development of IT solutions that
im-
prove SDM in primary care.
OBJECTIVES
Though the use of technology in health care delivery has
expanded

in recent years, few health (IT) tools exist that can be used
jointly by
patients and physicians during a clinical encounter.16 In this
study,
the current extent of shared decision-making (SDM) in primary
care
was measured and a needs assessment for health IT
interventions
was conducted to identify key gaps for future IT development to
im-
prove clinical experiences for both patients and physicians.
MATERIALS AND METHODS
Study design
This was a mixed-methods study conducted in three phases: (1)
ethno-
graphic observation of clinical encounters, (2) patient
interviews, and
(3) physician interviews. Patients and clinicians were
interviewed and
observed at three separate outpatient clinic sites. Verbal consent
was
obtained from all study participants prior to clinical encounter
observa-
tions and interviews. Neither patient nor physician study

participants
were compensated for their involvement in the study.
The study protocol (ID #2000022272) was reviewed by our
institu-
tion’s IRB and deemed exempt under (Category 2) 45 CFR
46.101(b)(2) for research involving use of interview procedures
or ob-
servation not recorded in a manner that leaves subjects
identifiable.
Study setting and population
The practices were purposively selected based on their
representative-
ness of academic and private locations, lower and higher
socioeconomic
patient populations, and urban and suburban settings. Study
partici-
pants were drawn from three practice settings in southern
Connecticut
known to the authors between January 19, 2018 and January 31,
2018:
(1) an adult primary care resident clinic in an urban, community
hospi-
tal; (2) an HIV/AIDS clinic in an urban, academic hospital; and
(3) a

primary care office in a suburban community. Observations and
inter-
views continued until the multidisciplinary team determined
that the-
matic saturation had been achieved.
At site (1), approximately 288 patients are seen per week, 87%
are covered by Medicare/Medicaid, and on average 20 health
care
providers including attendings, residents, APRNs, PAs work on
a
given day. At site (2), 35–40 patients are seen per week,
approxi-
mately 80% are covered by Medicare/Medicaid, and 3–9 health
care
providers work on a given day. At site (3), 380–400 patients are
seen per week, approximately 60% are covered by
Medicare/Medic-
aid, and on average 5–7 healthcare providers work on a given
day.
Patients whose primary language of communication during the
clinical encounter was not English were excluded from the
study.

Physician participants were recruited by email outreach for sites
(1) and (2), and by phone call for site (3).
448 JAMIA Open, 2019, Vol. 2, No. 4
Study protocol
Patient encounter observations
Trained observers, A.M. and S.O., observed clinical encounters
and
recorded field notes. The observers identified problems
undergoing
a decision-making process by the patient and physician. During
a
single encounter, multiple problems requiring a decision were
some-
times identified. The observers scored separate decisions from
the
same encounter independently of another using the OPTION
scale
(Supplementary Appendix S1) for each, a validated 12-item
inven-
tory developed for use by external observers to assess overall
SDM.24 Each OPTION item is evaluated with a Likert scale
ranging

from 0 (strongly disagree) to 4 (strongly agree), summing to a
raw
total score between 0 and 48. The raw total score is then scaled
to
range from 0 to 100. Higher scores indicate stronger SDM
practices
were observed. Each OPTION item assesses a separate aspect of
SDM meaning that scores can be used to identify specific
aspects of
SDM that are strong or weak.
Patient interview guide development and interviews
Our multidisciplinary research team included a pre-med student
with clinical research experience, 3 primary care residents with
pre-
vious work experience in the health IT industry, and a clinical
infor-
matics researcher with extensive qualitative research
experience.
The multidisciplinary team developed a preliminary
semistructured
patient interview guide (Supplementary Appendix S2) to
determine

patients’ perceived level of involvement in clinical decision
making
and their ideas for resources that could increase their comfort
with
decision making. The interview guide was developed with
reference
to the validated Traditional Decisional Conflict Scale25 and
under-
went iterative revision throughout data collection in response to
the
quality and relevance of data gathered. Trained interviewers,
A.M.
and S.O., conducted one-on-one interviews with patients after
their
clinical encounters. Field notes were recorded on paper and
later
transcribed for qualitative analysis. An anonymous key was
assigned
to each patient and data was recorded on the major decision
made
during the encounter.
Physician interview guide development and interviews
The multidisciplinary team developed a preliminary
semistructured

physician interview guide (Supplementary Appendix S3) to
assess
physicians’ current use of IT during clinical encounters and the
ca-
pacity of IT to improve SDM practices. The interview guide was
de-
veloped with reference to the validated Shared Decision Making
Questionnaire (physician version)26 and underwent iterative
revision
throughout data collection in response to the quality and
relevance
of data gathered. Trained interviewer A.M. conducted one-on-
one
interviews with physicians. An anonymous key was assigned to
each
physician and data were collected in a word processor during
the
interviews.
Data analysis
OPTION data from the observed encounters were analyzed
using
descriptive statistics to describe overall SDM performance. For
each

of the 12 items within the OPTION scale, the average score and
standard deviation across encounters were computed.
Data collected from patient and physician interviews were for -
matted and uploaded by S.O. into Dedoose (version 8.0.42;
Socio-
Cultural Research Consultants, LLC; Los Angeles, CA, USA), a
web-based application for qualitative data analysis. S.O. and
S.K.
independently identified relevant excerpts from the data and
coded
them within Dedoose. Notes were analyzed using the constant
com-
parative method of grounded theory, an iterative coding process
to
establish a hierarchy of domains and themes.27 To test inter -
rater re-
liability, Cohen’s kappa was calculated using the Dedoose
Training
Center. A third reviewer, A.G., was blinded to the themes
assigned
by S.O. and S.K., and independently assigned themes to the data
excerpts. The data excerpts were then jointly reviewed by A.G.
and

S.O. to reconcile discrepancies and refine the original themes.
A cod-
ing manual was then created describing each theme and
organizing
them into a hierarchy under larger domains. This manual was
then
analyzed by the other members of the research team for final
ap-
proval.
RESULTS
Between January 19, 2018 and January 31, 2018, 24 encounters
were observed and scored using the OPTION scale, and 22
patient
interviews with patients and 8 physician interviews were
conducted
until thematic saturation was achieved.
Demographic characteristics of the study subjects are reported
in
Table 1. The patients interviewed and observed were
representative
of the patient populations in sites (1), (2), and (3): 58.3% male,
33.3% Black or African American, 12.5% Hispanic or Latino,

and
87.5% covered by Medicaid or Medicare. The physicians inter-
viewed were: 62.5% male, 25% Hispanic or Latino, and had an
av-
erage 5.4 years of experience practicing primary care.
A.M. and S.O. conducted ethnographic observations of 24
encounters (A.M. 22 of 24 and S.O. 2 of 24) that encompassed
26
medical decisions (Supplementary Appendix S4). The OPTION
scale
data from encounter observations were analyzed to identify
addi-
tional areas for improvement in SDM. On a scale of 0 to 48, the
mean of total scores was 27.5 (95% confidence interval [CI],
24.9–
30.0). Adjusted to a scale from 0 to 100, the mean was 57.2
(95%
CI, 51.8–62.6). Average raw scores per item in the OPTION
scale
are reported in Table 2, on a scale of 0 to 4.
During the 24 observed encounters, the highest average scores
on the OPTION scale were in items 1, 2, and 3 (the clinician

identi-
fies a problem needing a decision-making process, the clinician
states that there is more than one way to deal with an identified
problem [“equipoise”], the clinician lists “options” including
the
choice of “no action” if feasible). The lowest average scores
were in
items 5, 10, and 11 (the clinician checks the patient’s preferred
in-
formation format [words/numbers/visual display], the clinician
asks
for the patient’s preferred level of involvement in decision
making,
an opportunity for deferring a decision is provided).
Cohen’s kappa, measuring agreement between coders in the
qualitative side of this study, was 0.42. The revised coding
manual
was used to produce the domains and themes from patient and
phy-
sician interviews presented in Table 3.
From the patient interviews, we identified 5 domains (establish-
ing trust, influence of others, patient flexibility, patient

frustrations,
and patient values and preferences) with 21 key themes that
reflect
patients’ priorities and experiences with health-related decision
making. From the physician interviews, we identified 8 domains
(concerns with technology, current methods used in decision
mak-
ing, education and information gathering, existing decision
chal-
lenges, existing use of technology, frustration, patient
understanding
of decision, and technology wish list/desires) with 30 key
themes
that reflect physicians’ current use of IT and needs for further
use in
SDM. These domains and themes were reviewed and approved
by
all members of the research team and are reported in Table 3.
JAMIA Open, 2019, Vol. 2, No. 4 449
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lookup/doi/10.1093/jamiaopen/ooz027#supplementary-data

Patients frequently mentioned that trust and relationships,
whether with physicians or their family and friends, were
important
factors in their decision making. Patients wanted to feel
informed
and involved in the decision-making process in order to
personalize
their medical care to their preferences. When patients felt these
needs were met, it resulted in increased patient engagement in
deci-
sion making. When patients felt ignored or uninvolved, they felt
frustration with their physicians and dissatisfied with the
decision
overall.
Physicians valued being able to accurately convey information
about clinical options to patients and were interested in the
potential
of IT interventions to facilitate patient-centered decision
making.

Awareness of the potential negative, or distracting, impacts of
IT in
a clinical encounter made some physicians cautious about its
incor-
poration into their workflow.
Representative quotes from patients and physicians that illus-
trate many of the key themes are reported in Table 3.
DISCUSSION
From ethnographic observation of 24 clinical encounters and
subse-
quent scoring using the OPTION scale, we found that within the
context of a shared medical decision, physicians regularly
identify a
problem that needs a decision-making process, state there are
multi-
ple options (equipoise), and list available options. We also
found
that physicians did not reliably check a patient’s preferred
informa-
tion format, preferred level of decision-making involvement, or
pro-
vide opportunities to defer a decision until a later date.
Additionally,

we identified items from the OPTION scale that physicians only
sometimes performed, such as exploring patients’ expectations
or
ideals on how a problem can be managed, exploring a patient’s
fears
or concerns, verifying patient understanding, allowing
opportunities
for patients to ask questions, and setting a follow -up date to
review
the decision. These data reflect the practice variation between
physi-
cians and the difficulty in performing a complete set of steps to
en-
compass a decision, which can be influenced by a variety of
factors such as background, training, patient volume, and level
of
autonomy.28
During interviews, we found that patients repeatedly mentioned
the effect of trust and relationships on decision making and a
desire
to feel informed and engaged in the process in order to
personalize

their ultimate decision to their preferences, values, and goals.
We
found recurring themes (“Trust in the doctor,” “History of good
communication,” “Decision based on information from
friends/fam-
ily”) that reflected the importance patients placed on close
relation-
ships in decision making. On the other hand, themes such as
“Patient is frustrated with the doctor,” “Patient is frustrated
with
the outcome,” and “Not actively involved in decision making”
dem-
onstrated the resulting dissatisfaction when this process went
poorly. When patients did mention the impact of technology, it
was
in regards to how it would fit into this framework, as noted by
the
themes, “Values having information to take away” and “Values
tracking health using technology.” Overall, we found that
patients
were most concerned with the provider–patient relationship and
considered technology an underutilized resource for
strengthening

the relationship. Providers should be mindful that patients might
evaluate technology by different criteria than themselves and
that
the impact on the patient–provider relationship should be
consid-
ered prior to adopting new technologies in their practice.
We found that physicians valued being able to accurately
convey
information about clinical options to patients (“Desires to
convey
full list of medical options”), even if it were currently difficult
in
practice (“Challenging to present accurate cost information”,
“Balancing the amount of information presented”). Clinicians
expressed a complicated relationship with technology,
conveying
optimism that it may improve their ability to communicate with
patients (“Values simplified patient-facing tools” and “Values
visual
presentation of data”) yet also skepticism about how this would
happen in practice (“Concerns about technology taking doctor’s
at-

tention away from the patient,” “Cost burden of technology,”
and
“Challenging to incorporate existing technology”).
The mixed-methods nature of this study allowed for quantitative
identification of specific areas for improvement in SDM, as
well as
qualitative exploration of themes, factors, issues, and ideas
patients
and physicians consider important. The quantitative analysis of
the
OPTION scale data complemented our qualitative approach to
in-
terview analysis and helped us identify areas for improvement
that
may have otherwise been overlooked. Multiple coding by two
inde-
pendent reviewers, as well as revision of codes in collaboration
with
a third independent reviewer, increased the rigor of our
qualitative
analysis.
Our study had several limitations. In general, a qualitative
needs

assessment focuses on a small, targeted sample to establish
initial
needs. The generalizability of our findings is limited as a result.
The
sample sizes of patients and physicians were relatively small.
Addi-
tionally, while the authors had pre-existing relationships with
each
Table 1. Baseline characteristics of the study subjects (patients
and
physicians)
Characteristic Patients Physicians
Number of participants 24 8
Age (years), mean (range) 50.5 (32–77) 32.9 (28–51)
Sex
Male 14 (58.3) 5 (62.5)
Female 10 (41.6) 3 (37.5)
Race
Black or African American 8 (33.3) 0 (0)
White 14 (58.3) 8 (100)

Asian 1 (4.2) 0 (0)
Other 1 (4.2) 0 (0)
Ethnicity
Hispanic or Latino origin 3 (12.5) 2 (25)
Not of Hispanic or Latino origin 21 (87.5) 6 (75)
Hospital type
Academic 19 (79.2) 6 (75)
Community 5 (20.8) 2 (25)
Education
Some vocational training 2 (8.3)
Some school 4 (16.7)
Some high school 2 (8.3)
High school 6 (25)
Some college 5 (20.8)
College graduate or higher 5 (20.8)
MD N/A 8 (100)
Insurance
Private/HMO 2 (8.3)

Medicaid 12 (50)
Medicare 9 (37.5)
Uninsured 1 (4.2)
Experience (years), mean (range) N/A 5.4 (1–25)
HMO: health maintenance organization; MD: doctor of
medicine.
Note: Data are reported as n (%) unless otherwise noted.
of the practices selected, sufficient data were gathered to allow
for
thematic saturation and subsequent qualitative analysis.29 The
sites
were intentionally selected to reflect demographic diversity.
The
physician sample was less representative of the general
population
of physicians and was weighted disproportionately towards
young,
white physicians compared to national level demographic data
on
physicians, which indicate 72.5% of primary care physicians are

white30 and the average American physician age is 52.04.31
Given
increasing interest in SDM in recent years, the physicians
involved in
our study may be biased towards performing SDM and its
practice
among the older general population of physicians may be rarer
than
observed here. Notably, when observers noted an opportunity
for a
clinical decision, the physician was often responsible for
guiding the
decision-making process. This may have led to some missed
decision-making opportunities that clinicians did not explicitly
iden-
tify. However, this is a natural limitation of all time-limited
encoun-
ters, where clinicians must ensure important topics are
addressed.
We used the OPTION scale to identify aspects of SDM that
were
deficient and, therefore, potentially amenable to high quality IT
sol-

utions. However, these deficient areas may benefit from non-IT
re-
lated solutions as well. Because data collection was conducted
during a single 2-week period, we were unable to assess
temporal
trends. We used a single OPTION scorer per clinical encounter
to
establish internal consistency in the quantitative data collection.
However, a more rigorous methodology would utilize 2
reviewers
with high inter-rater reliability scoring encounters
simultaneously,
while blinded to one another’s scores. Future researchers may
con-
sider collecting data over a longer period of time, deliberately
select-
ing a more representative physician sample, and involving an
additional independent OPTION scorer in encounter
observations.
The Cohen’s kappa of 0.42 indicated moderate agreement be-
tween coders in the qualitative analysis. We attribute this to the
in-
clusion of some overlapping and redundant codes in the original

coding manual. This was addressed by the coders
collaboratively re-
vising the coding manual after calculating Cohen’s kappa to
elimi-
nate unnecessary codes and refining the definition of each key
theme. To mitigate coding discrepancies, the updated coding
manual
and final codes were reviewed and approved by all members of
the
team.
Compared to other studies, we chose to focus on the overall
medical decision-making process in adult primary care clinics
and
interviewed both patients and providers instead of focusing on a
sin-
gle party,32 decision or medical condition. While this increased
the
ability to draw generalized themes from the SDM process, it did
limit the ability to analyze SDM using specific decision aids
such as
with statin initiation33 or for specific medical conditions such
as

cancer care34 and osteoarthritis of the knee.35 Past studies
report
overall scaled OPTION scale scores between 14.3 and
49.7.36,37 We
found a higher overall scaled OPTION score of 57.2 in our
study
population, which is likely due to multiple factors including
subjec-
tive scoring assessment, the sample of physicians observed
(mainly
recently trained in a program emphasizing shared decision
making),
and clinical practice changes compared to years prior, when
past
studies were conducted.
Unlike previous studies on physician-implemented SDM tools
during the clinical encounter, our findings suggest a
reconsideration
of how best to engage patients and physicians in SDM.
Physicians
hesitate to incorporate SDM tools into clinical encounters
because
of concerns about the quality of their content and disruption to
the

regular workflow,38,39 and our results illustrate their
reluctance may
extend to SDM practices in general. Using SDM tools solely
during
the clinical encounter may be inadequate in meeting patient and
physician needs, as patients value making “decisions based on
infor-
mation from friends/family” and over longer time periods.
Instead,
our findings suggest a more successful approach may be a
patient-
facing SDM aid that is accessible to patients before and during
the
clinical encounter which they can engage with at their
convenience
and their preferred desired level of involvement. Compared to
cur-
rent SDM tools, such a design has the potential to combat
asymmet-
ric information exchange between patient and physician during
the
clinical encounter, and provide patients with the information
they

need to make the best possible decision.
An analysis of the needs assessment for SDM demonstrates sev-
eral key findings based on positive and negative experiences de -
scribed by patients and physicians. Patients mainly value trust
in
their physician, which is encompassed in understanding the
decision
to be made along with the manner in which it is communicated.
While one theme showed that patients placed trust in
relationships
such as friends and family for help with medical decisions,
more
themes were expressed relating to trust in their doctor. Patient
inter-
views also highlighted the need to encompass patient-specific
values,
preferences, and goals, which is an area that can be improved as
noted previously.22 Our interviews revealed a way to address
patient
frustrations by actively involving them in decision making.
Current
technology often impedes physician–patient communication.
How-

ever, technology has the potential to improve communication
and
decision making,40 and the needs assessment presented here
demon-
strates a path forward to do so.
Table 2. OPTION scores from encounter observations by
inventory item
OPTION scale item Average score (0–4) Standard deviation
(1) The clinician identifies a problem(s) needing a decision-
making process 4.0 0.0
(2) The clinician states that there is more than one way to deal
with an identified problem (“equipoise”) 3.6 1.1
(3) The clinician lists “options” including the choice of “no
action” if feasible 3.5 1.1
(4) The clinician explains the pros and cons of options to the
patient (taking “no action” is an option) 2.9 1.2
(5) The clinician checks the patient’s preferred information
format (words/numbers/visual display) 0.0 0.2
(6) The clinician explores the patient’s expectations (or ideas)
about how the problem(s) are to be managed 2.7 1.3
(7) The clinician explores the patient’s concerns (fears) about
how problem(s) are to be managed 2.3 1.4
(8) The clinician checks that the patient has understood the

information 2.5 1.1
(9) The clinician provides opportunities for the patient to ask
questions 2.5 1.1
(10) The clinician asks for the patient’s preferred level of
involvement in decision making 0.0 0.0
(11) An opportunity for deferring a decision is provided 1.0 1.7
(12) Arrangements are made to review the decision (or the
deferment) 2.4 1.8
Table 3. Domains, key themes, and representative quotes from
patient and physician interviews
Domain Theme Quote
Patients
Establishing
trust
Patient understands the scope of options that exist and
feels able to make an informed decision
“[I know] the facts and what should be expected.”
Trust in the doctor “I trust the doctors here. . . I trust you guys.
This has been my primary care

for years. My wife, my son, everybody comes here.”
Having a plan “[I am] totally relieved to have a plan to help me
feel better.”
History of good communication
Patient seeks doctor’s approval
Patient has an understanding of their medical condition
Influence of
others
Decision based on information from friends/family
Patient flexibil-
ity
Patient willingness to explore available options
Patient frustra-
tions
Patient is frustrated with the doctor “Everybody knows their
body” [but I was] “shot down” [by the doctor].
Patient is frustrated with the outcome “[I] didn’t come out with
any more information than I came in with.”
Lack of information

Technology too complicated
Not actively involved in decision making
Patient values
and preferences
Personal ownership of choice “The choice was mine at the end.”
Importance of cost “I don’t want this to be used as somebody’s
money.”
Avoiding negative side effects “I will tell you right now, if I
start to take the medication and I get those
side effects, I’ll stop taking it. Right now, I have no problems
with my
legs.”
Values having information to take away
Active involvement in decision making “[I value] how much I
am involved, decision-wise.”
Importance of preserving quality of life
Value of visuals
Values tracking health using technology “[I use the online
chart] a lot. . . it’s great because everything is there, even
the test results.”
Physicians

Concerns with
technology
Concerns about technology taking doctor’s attention
away from the patient
Aversion for technological assistance for easy/quick
decisions
“I feel like I remember enough to not need it. I turn to
technology when it
is something out of my experience, something I don’t recall, or
when it
will be helpful to show the patient something.”
Role of technology in improving current workflow “In the
setting of actually seeing a patient, it [technology use] has to be
efficient.”
Frustration with technology limitations “Our current technology
is not very good at tracking the status of things. . .
When I place a referral, it is hard to know whether it is acted on
or not,
and why or why not.”
Challenging to incorporate existing technology “There’s a lot
[of technology] out there, but it’s [important] knowing how

to use it and then having shared decision making with the
patient.”
Cost burden of technology “[I don’t] get reimbursed for what I
am doing at a higher quality.”
Current meth-
ods used in de-
cision making
Customizes options presented to patient “Very commonly the
comorbidities are giving me a preselection [of
options, such as]. . . if someone has to do P.T. but they have
bad knees
and cannot go.”
Values clinical decision support “I think one nice thing is
sometimes now we prescribe a medication and it
will remind you to check that certain labs have been checked
and fol-
low-ups are in place.”
Avoids using technology during encounter “There could be the
latest and best application that is life-saving and I
wouldn’t use it during the [initial] encounter.”
Education and

information
gathering
Consulting experts or reference guidelines or evidence-
based tools
“[I consult an] expert pharmacist who is a master of these
medications [or
use reference guidelines as a] framework for decision making.”
Values established evidence-based tools “I would only go to
websites like the Mayo or Cleveland Clinic or medical
journals; the source that I choose is a source that I trust.”
Expanding knowledge through continuing education
Existing deci-
sion challenges
Prioritization of patient values “We decide together. I give them
a couple of options and we discuss the
pros and cons of each option. I tell them the best options and if
the pa-
tient doesn’t agree, then we can discuss it further until we are
able to get
to a resolution together.”
Balancing the amount of information presented “It is always a

delicate balance between the amount of information you
present and how much is needed for a shared decision. The
biggest thing
(continued)
From the healthcare provider perspective, the needs were more
varied as evidenced by the increased number of domains and
themes
identified. Ruiz Morilla et al.41 found that “The ease-of-use of
the
electronic devices was of particular concern as was the need for
incentives to use the technology,” which was also consistent
with
the concerns about technology and the desires/wish-list domains
raised by physicians in our study. Physicians also differed
widely in
their use of technology currently from preferring to avoid it
during
some situations but relying on it during others. This highlights
the
need for technology to meet physicians’ and patients’ actual

needs
(as reported here) and to fulfill specific use-cases rather than as
a
generalized solution. Other domains and themes revealed a
focus on
education or communication needs, which is appropriate given
that
the use of technology during encounters has been described as a
bar-
rier to effective communication.42
The role of new technologies in health care is increasingly ac-
cepted. The findings of this study provide a guide to SDM tool
developers to address the lingering gap between existing
technolo-
gies and the user experience for both patients and physicians.
For
patients, physicians, researchers, entrepreneurs, policy makers,
and
software designers seeking to increase communication and SDM
in
primary care practice, we recommend the following
considerations
based on our study.

1. Patients’ preferences for technological platforms can vary
widely
and are often individualized. It is important that multiple tools
are available for patients and providers to draw from in an en-
counter. Furthermore, physicians should actively elicit patient
preference for a given platform.
2. The utility of an SDM tool is incumbent upon the patient and
provider sharing a mutual interest in making a decision
together.
As such, it is important to evaluate the patient’s preferred level
of involvement prior to using a given tool.
3. Often, patients may prefer to defer decisions for which SDM
is
indicated for a variety of reasons. As such, SDM tools should
provide an opportunity to defer a decision.
CONCLUSION
These findings are valuable for clinicians, patients, researchers,
entrepreneurs, policy makers, and software designers seeking to
in-
crease communication and SDM in primary care practice. For

those
interested in pursuing IT interventions to address this common,
yet
complex, healthcare topic, an analysis of OPTION scale data
identi-
fied three key areas to prioritize: (1) checking the patient’s
preferred
information format, (2) asking the patient’s preferred level of
in-
volvement in decision making, and (3) providing an opportunity
for
Table 3. continued
Domain Theme Quote
Patients
with our clinic is an asymmetry of information. . . when one
party has a
huge amount of information and one doesn’t. Typically I’ll
present all
of the options that I think are beneficial to their health, with
always the
option of not doing them, but preferring we do it.”
Reliance on memory or prior experience

Existing use of
technology
Comfort with using technology during an encounter “I’ve
definitely pulled up UpToDate during the encounter as well. . .
even if
they come in with something basic. I feel pretty comfortable
with using
it in the room. And most patients are pretty good about it too.”
Values patients using existing technologies
Extensive use of technology tools
Frustration Challenging to present accurate cost information
“Cost is a little tricky because the cost to the patient will be
very variable
depending on what insurance they have, copays, etc.”
Patient under-
standing of
decision
Using teach-back method for patient understanding “[I] ask
them to repeat [the decision] back to me in their own words so I
can assess if they understood.”
Values resources to send home with patients

Enable patient autonomy “I usually try to use shared decision-
making principles which include let-
ting the patient decide what option they would like.”
Technology
desires/wish
list
Simplify workflow where possible “I’d like to get the
information with far fewer clicks. The other thing that
would be useful is some sort of pop-up. If I order a test, has the
status of
anything changed since I last updated the patient’s chart?”
Values electronic validation tools
Desires easier access/use of technology tools “I think we have
[calculators] for the common things. . . but if you could
just plug those things in to see what medication. . . that would
be
amazing. . . If we had easier access, definitely in this clinic we
would all
be using it.”
Physician desires increased patient engagement with
technology

“In the perfect world, maybe there would be an interactive game
or some-
thing to direct them to afterwards.”
Values technology to enhance knowledge or tasks “I turn to
technology when it is something out of my experience, some-
thing I don’t recall, or when it will be helpful to show the
patient some-
thing.”
Values visual presentation of data “[I] would want something
more visual and more accessible, both.”
Values simplified patient-facing tools
Desires to convey full list of medical options “I tend to use a
full spectrum of options available.”
deferring a decision. These priorities all reflect a desire for
increased
engagement with decision making and should be incorporated
into
provider workflows. In its best use, IT can be a powerful tool to
standardize and simplify these workflows and is particularly
well

suited to addressing these priorities. However, IT interventions
may
not be as desirable for the more personal aspects of medicine
such as
trust building, as patients feel that a provider is paying undue
atten-
tion to the technology and not the patient. During interviews,
patients expressed views on IT use in relation to potential
effects on
the patient–provider relationship. Further research is needed to
as-
sess the impact of adoption of technology on patient satisfaction
with their provider. Physician interviews revealed that
physicians de-
sired new technologies to improve communication with patients
or
simplify their workflow, but they expressed hesitancy to
incorporate
new technologies. Our results are novel in that they suggest a
change
in approach for the development of SDM tools to begin placing
a
heightened emphasis on addressing barriers to their successful
imple-

mentation into routine primary care. Additionally, this
highlights
the need for tools to standardize common parts of SDM across
deci-
sions and demographics to capture patient preferences that are
criti-
cal to a successful shared decision. Entrepreneurs and software
developers should consider these priorities and needs when
design-
ing products to maximize their adoption. We believe that when
new
technologies are implemented that consider these factors, they
can
positively address current deficiencies in SDM.
FUNDING
ERM was partially supported by Agency for Healthcare
Research and Quality
grant number K08HS021271 during the data collection period.
The content
is solely the responsibility of the authors and does not
necessarily represent
the official views of the Agency for Healthcare Research and
Quality.

AUTHOR CONTRIBUTIONS
All authors contributed to the study design. A.M. and S.O. were
re-
sponsible for data collection. Qualitative analysis was
conducted by
S.O., A.G., and S.K. Quantitative analysis was conducted by
A.M.
All authors participated in drafting and revising the manuscript,
and
approved the final version of the manuscript.
SUPPLEMENTARY MATERIAL
Supplementary material is available at Journal of the American
Medical Informatics Association online.
ACKNOWLEDGMENTS
We thank the patients, administrators, and clinical staff at our
interview and
observation sites for their willingness to participate in this
study.
CONFLICT OF INTEREST STATEMENT
None declared.
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