JE- 3

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

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 willing-

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

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.

450 JAMIA Open, 2019, Vol. 2, No. 4

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

JAMIA Open, 2019, Vol. 2, No. 4 451

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)

452 JAMIA Open, 2019, Vol. 2, No. 4

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.”

JAMIA Open, 2019, Vol. 2, No. 4 453

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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