Clinical Trial Details
— Status: Completed
Administrative data
| NCT number |
NCT04099485 |
| Other study ID # |
CV185-764 |
| Secondary ID |
|
| Status |
Completed |
| Phase |
N/A
|
| First received |
|
| Last updated |
|
| Start date |
November 18, 2020 |
| Est. completion date |
February 28, 2023 |
Study information
| Verified date |
May 2023 |
| Source |
University of Cincinnati |
| Contact |
n/a |
| Is FDA regulated |
No |
| Health authority |
|
| Study type |
Interventional
|
Clinical Trial Summary
Background and Significance - Atrial fibrillation (AF) is the most common significant cardiac
rhythm disorder and is a powerful common risk factor for stroke. Randomized trials have
demonstrated that anticoagulation can reduce the risk of stroke in patients with AF. Yet,
there continues to be widespread underutilization of this therapy. To address this practice
gap locally and improve stroke prevention for patients with AF in the UC Health system, the
investigators have assembled an interprofessional team, the Cincinnati Atrial Fibrillation
Initiative (CAFI).
Objectives - The objective of this project, "EHR-Embedded Decision Support to Prevent Stroke
in Patients with AF", is to improve thromboprophylaxis treatment decisions for patients with
non-valvular AF and to increase awareness of the underutilization of appropriate
thromboprophylaxis in the University of Cincinnati Health system, including vulnerable
populations with health disparities. To achieve this objective, the investigators will
implement and evaluate the effectiveness of an Atrial Fibrillation Decision Support Tool
(AFDST), embedded within the UC Health electronic health record (EHR) that will: (a) identify
at the point of care, patients who might benefit substantially from a change in their current
thromboprophylaxis; (b) provide patient-tailored guidance to support decision-making; and (c)
provide an opportunity to refer the patient to a pharmacist-staffed AF Thromboprophylaxis
Shared Decision-Making consultation service.
Overview of Study Design - The overarching goal is to improve the rate of "appropriate
thromboprophylaxis" by eliminating system barriers through provision of appropriate decision
support in the right place and at the right time, that improves provider and patient
knowledge about AF-related stroke risks, bleeding risks, practice gaps in prevention, and how
to think about balancing risks and benefits of anticoagulation therapy, and by improving
patient engagement in decision-making. The investigators have designed interventions based on
a conceptual model that attributes the gap between evidence and practice to the following
issues: 1) provider knowledge, 2) patient understanding and engagement, 3) sociodemographic
factors that create barriers to care and treatment, and 4) systems barriers such as time
constraints for busy clinicians and inadequate electronic health record-integrated decision
support.
The investigators will achieve the overarching goal through two aims. The first aim will be
addressed by a randomized controlled trial that examines two strategies - 1) AFDST without
best practice advisory [BPA] (current state), or 2) AFDST with BPA and semi-automated order
set to refer patients to an AF Thromboprophylaxis Shared Decision-Making Service. The
investigators will use the RE-AIM framework for the evaluation of implementation studies to
assess outcomes of effectiveness, reach, and adoption.
The second aim is to evaluate the impact of shared decision-making tools and services. The
investigators believe that a shared decision-making specialty service that utilizes an
EHR-embedded Atrial Fibrillation Shared Decision Making Tool (AFSDM) tool will improve a
number of metrics for quality care. These include, among others, decrease decisional
conflict, improve patient satisfaction with decision-making, improve patient knowledge, and
improve adherence with final shared treatment decisions.
Methods - The first aim will be accomplished through a clinical study in which AF patients in
the UC Health primary care network will be randomized into one of two study arms. Briefly,
these arms are: 1) Atrial Fibrillation Decision-Support Tool (AFDST); 2) AFDST with addition
of best practice advisory (BPA) and option to refer to shared decision-making consultation
services. Patients will enter the study as their clinicians receive BPAs, or in the case of
the first study arm, when BPAs would have been generated as clinicians open medical records
of patients for whom current thromboprophylaxis is not optimal.
The second aim will be accomplished through a pre/post study design evaluating the impact of
shared decision-making tools and services. Patients will be consented and enrolled following
their referral to the pharmacist-staffed AF shared decision-making service. Patients
consenting to participation in this aspect of the study, will have a shared decision-making
visit with one of the anticoagulation pharmacists. Information to be collected will include a
number of validated measures of decision quality, patient engagement and confidence, and
connection with the clinical team gathered prior to and at the conclusion of the shared
decision-making visit.
Description:
C.2.1 Specific Aim 1 - Randomized Comparative Effectiveness Study to Evaluate Atrial
Fibrillation Decision-Support Tool (AFDST) vs. AFDST with addition of best practice advisory
(BPA) and semi-automated order set to refer patients to AF Thromboprophylaxis Shared
Decision-Making Service.
The investigators will improve the rate of "appropriate thromboprophylaxis" by eliminating
system barriers through provision of appropriate decision support in the right place and at
the right time, that improves provider and patient knowledge about AF-related stroke risks,
bleeding risks, practice gaps in prevention, and how to think about balancing risks and
benefits of anticoagulation therapy, and by improving patient engagement in decision-making.
H1 - Addition of BPA (including semi-automated order set to generate referral to an AF
Thromboprophylaxis Shared Decision-Making Service) to an EHR-embedded AFDST will improve
rates of "appropriate thromboprophylaxis" compared with the current state of an EHR-embedded
AFDST without BPA or Shared Decision-Making Service.
The investigators will examine this hypothesis by conducting a randomized controlled trial
that implements the respective bundles at ambulatory sites, using the RE-AIM framework for
evaluation of implementation studies.(36-41) Outcomes will include - effectiveness, reach,
and adoption.
Triggers for BPAs - New AF - Develop a BPA that will fire automatically whenever a patient
without a prior history of AF receives a diagnosis of AF (either newly incident AF, or new
patient to the system with prior diagnosis of AF). The BPA would provide a direct link to the
AFDST, providing real-time decision support for initial treatment.
Change in Clinical Risk Factors - Implement automated process to identify situations where
AFDST recommendation has changed due to changes in risk factors such that current treatment
is not "optimal." Persistent AF and non-optimal thromboprophylaxis - Implement automated
process to review AFDST recommendations when clinician is in patient chart. Generate BPA if
current therapy is not "optimal." To minimize alerts, the investigators will generate
advisories only for patients who would gain significant benefit from a change in treatment
(e.g., > 0.5 QALYs). Based on prior studies, this is likely to be the most commonly triggered
BPA. Clinicians will indicate whether they would like the BPA to fire again, or suppress
future alerts for that patient.
C.2.2 Specific Aim 2 - Evaluate the impact of shared decision-making tools and services.
H2 - A shared decision-making specialty service that utilizes an EHR-embedded Atrial
Fibrillation Shared Decision Making Tool (AFSDM) tool will improve a number of metrics for
quality care. These include, among others, decrease decisional conflict, improve patient
satisfaction with decision-making, improve patient knowledge, and improve adherence with
final shared treatment decisions.
The investigators will evaluate this hypothesis using a pre/post study design of patients
referred to the AF shared decision-making service. Outcomes will include validated measures
of decision quality, patient engagement, and connection with the clinical team completed
prior to, and at the conclusion of, the visit.
Develop application software - The AFSDM application will provide patient education about
AF-related stroke risk, treatment options, and their risks and benefits in an inclusive
manner that considers barriers to treatment that may inordinately affect vulnerable
populations. The AFSDM will use individual patient preferences and values for health states,
and patient-specific EHR data to generate recommendations.
Provide Shared Decision-Making Services - Develop AF Thromboprophylaxis Shared
Decision-Making services for clinicians who are not comfortable making thromboprophylaxis
decisions themselves. These services will be located in the UC Health anticoagulation clinic.
Facilitate Access to this Service - Use the AFDST to identify patients who might benefit from
a change in treatment (see above, Triggers for BPAs) and embed electronic support to simplify
referral process.
BPA will provide options for clinicians to directly address the thromboprophylaxis decision
themselves, or easily refer patients to the appropriate AF Thromboprophylaxis Shared
Decision-Making service.
Clinicians can indicate whether they want the Shared Decision-Making service to make the
treatment decision and prescribe therapy, or only generate a recommendation to the referring
clinician.
C.3. Target Population: Practices, Clinicians, and Patients - The UC Health primary care
network (PCN) consists of 20 primary care practices and 144 clinicians located in the Greater
Cincinnati and Tri-state area, serving more than 69,000 patients. Practices include 2 urban
residency-training sites (Internal Medicine and Medicine-Pediatrics), the UCMC Internal
Medicine Faculty Practice, and the Burnet Family Medicine Practice, all of which serve
vulnerable patient populations. All practices and the inpatient facility use Epic® as a
common EHR. A centralized data warehouse containing clinical information for the health
system is housed in the university's Center for Health Informatics (CHI). UCMC is a
tertiary/quaternary medical center, safety-net institution with 630 beds (283 of these are
adult medical/surgical beds) serving vulnerable patient populations in the Cincinnati
metropolitan area, which includes northern Kentucky and South-Eastern Indiana. Thus, the
investigators estimate a total of 144 ambulatory clinicians, eligible to be randomized into
this study. The investigators serve a diverse ethnic and sociodemographic patient base that
includes both urban residents and rural Appalachians. While the overall proportion of Black
patients in the UC Health AF cohort is 32%, 4 of the primary care practices (3 UCMC
hospital-based sites and 1 community site), caring for 711 AF patients, serve a
disproportionately large proportion (47% - 58%) of Black patients. Forty percent of patients
are insured by Medicaid or managed Medicaid and 30% by Medicare or managed Medicare; 2% are
uninsured.
C.3.1. Ambulatory Study Sites - Ambulatory visits will take place in the primary care
practices and pharmacist-staffed Anticoagulation Clinic at UC Medical Center Hospital. As
described above, the BPA only will fire for patients for whom the AFDST suggests an optimal
treatment different from current therapy who would gain a benefit of more than 0.5 QALYs by
changing current treatment. If an advisory has already fired at a previous ambulatory visit,
the investigators will prevent the BPA from firing again, unless their primary clinician has
requested the alert be allowed to fire again.
C.3.2. Estimated Patient Numbers - A recent data pull from the UC Health EHR identified
roughly 4,700 active patients fitting these criteria in the UC Health system. Based on
earlier studies, in the UC Health AF cohort, 41% of patients were receiving "non-optimal"
thromboprophylaxis (1,927), and 49% of those (944) could gain 0.5 QALYs or more if they were
to receive "optimal therapy." Conservatively, the investigators estimate enrollment of 800
patients (400 in each of 2 study arms) during the 18-month planned enrollment period. In
addition, roughly 1,460 patients with new diagnoses of AF were seen during the most recent
calendar year. Of these roughly 80% were new patients entering the system with prior
diagnoses of AF and roughly 20% were established patients with newly incident AF. Thus, the
investigators anticipate influx of roughly 1,215 patients with prior diagnoses of AF into the
system annually. Of these, roughly 245 (1,215 x .41 x .49) might benefit substantially from a
change in their current thromboprophylaxis, resulting in the potential accrual of another 122
patients in each study arm if needed. If the investigators still find they are not making
patient enrollment milestones, they will lower the BPA triggering threshold for anticipated
gain in QALYs from 0.5 to a reasonable but smaller gain.
C.4. Study Design and Methods C.4.1. Design of the AFDST - The current version of the AFDST
is an external web application that is launched by clicking on an activity button while in
the patient's EHR record. An AF data mart consisting of a set of Clarity® data tables is
maintained and refreshed every 24 hours. All UC Health patients fitting inclusion and
exclusion criteria are in the data mart. Information needed to calculate stroke risk
(CHA2DS2VASc(18)), major hemorrhage (HASBLED(19)), and intracerebral hemorrhage(29) are
contained in the data mart after being extracted using the active problem list and a
combination of laboratory values and clinical measurements. These data prepopulate the AFDST
when the tool is launched. The investigators ask clinicians to verify this information by
adding or removing risk factors they believe are incorrect. They may also alter risk factors
to use the tool to explore alternate clinical scenarios. Stroke risk and bleeding risk
(extracranial and intracranial) are modified by appropriate measures of efficacy and relative
hazards for each treatment. Time in therapeutic range, needed to calculate the HASBLED score,
is determined by interpolating international normalized ratio values through time over the
past 1 year, similar to the method by Rosendaal et al.(42) Current antithrombotic therapy
(oral anticoagulant or antiplatelet therapy) is retrieved from the active medication list.
Efficacy of treatment and relative risk of complications including major bleeding and
intracranial hemorrhage are informed by the most up-to-date literature including
meta-analyses(43, 44) and network meta-analyses(45) of the new agents in general populations
and in the elderly(46, 47) along with systematic reviews of the literature, given the absence
of head-to-head trials comparing the DOACs to one another.(10, 48) Logic is included to avoid
recommendations for specific DOACs based on renal function, along with decision support to
provide specific alternate dosing recommendations as appropriate (e.g., based on age and
weight).
C.4.2. Study Design Details for Aim 1 - At the beginning of the study, the investigators will
take a snapshot of current thromboprophylaxis practice in the UC Health Primary Care network
by accessing all primary care patients in the AF data store. The investigators estimate this
will entail roughly 4,700 patients. The investigators will run the AFDST on all of these
patients and compare current antithrombotic therapy with treatment recommended by the AFDST
to ascertain the proportion of this cohort that is receiving recommended antithrombotic
therapy. This will give us an updated estimate of the care gap, and the potential for
improving outcomes through this intervention.
When a clinician is in the chart of an AF patient, the AFDST will run in the background and
determine whether the patient would gain more than 0.5 QALYs were their current
thromboprophylaxis changed. Depending upon whether the patient is in the usual care or active
intervention study arm, either a hidden best practice advisory or an actual best practice
advisory will be triggered. This will automatically enroll the patient into the study, and
this visit will be noted as their index visit.
If for any reason, we are not able to implement full functionality of the plan described
above, we will proceed with the following more manual alternative plan. At the end of each
week, we will generate a report of all patients in our AF data mart who have had either a
primary care visit with one of our GIM attendings or UC Health primary care physicians. We
will run the AFDST for each of these patients to see if they would gain an estimated benefit
greater than 0.5 QALYs were their current thromboprophylaxis changed. Those patients will be
enrolled in the study, and this visit will be noted as their index visit. In addition, the
PI, project manager, and study nurses will receive an Epic alert whenever any enrolled
patient has an Emergency Department visit or is hospitalized at UCMC. We will use this alert
as a trigger to review those patients' charts to assess for the occurrence of any adverse
events (AE). This information will be captured on the case report forms. Outcomes for
specific aim 2 will be determined at the end of the study.
C.4.4. Sample Size Calculations for Primary Outcome - All sample size estimates assume 90%
power in a two-tailed, alpha = .05 significance test. For the AFDST group (current state) we
assume, based on similar past assessments, that no more than 4% of patients with
"non-optimal" treatment will be switched to "appropriate thromboprophylaxis" as determined by
the AFDST. Given that 4% rate, detecting a 10% rate of change to "appropriate
thromboprophylaxis" in the group also receiving BPAs would require 397 independently sampled
patients in each group. Note also that we believe that the 4% estimate for the AFDST group is
optimistic in that we are likely to observe a lower rate, thus lowering the rate detectable
in the other group.
C.4.5. Clinical Significance of Estimated Changes in "Appropriate Thromboprophylaxis" - Given
the current 2.2 million patients in the United States with AF, if the investigators are
successful in demonstrating a 10% improvement in appropriate thromboprophylaxis, the broad
implementation of AF decision support with BPAs could result in improved treatment for more
than 44,000 patients, and a population gain of more than 22,000 QALYs. Similarly, an 18%
improvement through the addition of AF Shared Decision-Making services, could improve
treatment for almost 80,000 patients, with a population gain of almost 40,000 QALYs.
C.4.6. Study Design Details for Aim 2 - Aim 2 is focused on the development and evaluation of
an Atrial Fibrillation Shared Decision Making tool (AFSDM) and an AF Thromboprophylaxis
Shared Decision-Making service that will use this tool to engage referred patients in a
shared decision-making conversation about AF thromboprophylaxis treatment options. To
accomplish these goals, the investigators propose the following specific steps:
Develop the AFSDM - In the previously described pilot/feasibility study of the AFSDM, the
investigators used a software application written in Visual Basic®, the Gambler® (developed
by the PI and a past fellow in 1992) to assess patient values and preferences using the
Standard Gamble technique.(35) This needs to be re-programmed and integrated into the AFSDM
using a contemporary web-based language. The AFSDM integrates processes of - 1) utility
assessment for health states (major gastrointestinal bleed, as an exemplar for major
extracranial bleeding events, stroke with minor and with major long-term neurological
sequelae, and taking a medication [warfarin] that requires monthly or bimonthly medical
visits to check INRs and dosing adjustments); 2) patient and family education regarding the
risks and benefits of treatment; 3) performance of patient-specific decision analyses; and 4)
real-time communication of results. The investigators will perform utility assessments for
relevant health states using the standard gamble technique.(35) This is a validated method
commonly used to assess patients' values and preferences for health outcomes in decision
analyses. It is particularly appropriate for choices that entail risk, as risk attitude is
incorporated holistically in utility assessments using this technique. The investigators will
develop software to computerize these assessments and seamlessly integrate them with the
decision support tool. The investigators will include educational materials for use by the
shared decision-making service to inform patients better about AF-related stroke risk,
available treatments and the risks and benefits of those treatments. In addition, the
investigators anticipate that, for many patients, the decision analytic results will not
favor a clear best treatment recommendation among the various DOACs, as they have similar
efficacies and risks. As shown in the report for a hypothetical patient in Figure 1,
quality-adjusted life expectancy for apixaban dabigatran, rivaroxaban, and edoxaban fall
within 0.1 QALYs of each other. From a decision analytic perspective, they are all reasonable
choices. Therefore, the best choice for this patient will also need to account for more
nuanced considerations. Based on previous work by the investigative team assessing factors
that patients feel are important in decision-making beyond treatment efficacy and side
effects, these include - out of pocket cost, frequency of administration (e.g., daily or
twice daily), availability of reversal agents, need to take with food, complexity of
food-drug or drug-drug interactions, and need to have blood work done on a recurring basis
(e.g., once or twice-monthly visits for INR). Figure 2 shows the type of customized
information that will be provided to support discussion of these more nuanced issues.
Although relative costs are shown in the placards above, the investigators plan to get
specific information for each patient's out of pocket cost for these agents depending upon
their insurance plan, coverage, and pharmacy.
Educational Materials for Patients Embedded in the AFSDM - Utilizing the overall structure
and internal logic of the earlier computerized utility assessment tool, the "Gambler," the
investigators will develop a new generation tool that makes use of current web-based
client-server programming advances and multi-media technology.(49) In shared decision-making
visits, using the AFSDM, utility assessments will be done for four health states/clinical
outcomes: life while receiving anticoagulant therapy with warfarin, mild stroke, severe
stroke, and major gastrointestinal bleed. The investigators will provide health state
descriptions through a variety of user-selected formats, including text and multimedia. The
investigators will film media clips for each of these health states, using professional
patients or actual patients who have agreed to be filmed. Standard scenario descriptions will
include the impact of the health state on their physical performance, life style and role
functioning. In prior patient focus groups, patients have told us they prefer receiving
information from patients of similar ethnicity, gender, and relative age to themselves. Thus,
the investigators will develop a library of multimedia clips so that a patient will
automatically receive health state scenario descriptions and clinical information from a
patient of the same gender, race, and age range (within limits). The investigators will also
provide the opportunity for additional, self-directed patient education, providing web-links
to an array of sites they can access from home, or their local library, including the AHA's
AFib Town, among others.
Develop and implement the AF Thromboprophylaxis Shared Decision-Making services - Across the
nation, Anticoagulation Clinics (so-called "coumadin clinics") are searching for new business
models, as patients transition away from warfarin to treatment with DOACs. These
pharmacist-staffed clinics are ideal for engaging patients in shared decision-making. Their
expertise will also address increasing concerns about inappropriate usage and dosing of
DOACs. Implementation will require the development of sustainable business models; education
of Anticoagulation Clinic professional staff in use of the AFSDM; and outreach to clinicians
about the availability of these services.
C.4.7. Health Disparities - To address health disparities for Black patients and other
vulnerable populations that result in lower rates of anticoagulation therapy, the proposal
intervenes at multiple points along the continuum of prevention and care. First, the
investigators will implement interventions at multiple practice sites that provide care for
vulnerable populations in the health care system. The next major gap relates to
patient-specific factors. The investigators will be inclusive and mindful of economic,
educational, access and other barriers to treatment among Black patients and other
underrepresented minorities. For example, the investigators will provide descriptions of
health states for which they are obtaining patient values and preferences using a bank of
audio/video clips they create using professional patients matched to patient's race, gender
and age. Shared decision-making discussions also will focus on issues such as how often lab
testing must be done with each medication. The need to travel to clinic once or twice a
month, as is the case when warfarin is prescribed, may not be feasible for someone who has a
3-hour bus ride to see the doctor. Another topic of discussion is dietary restrictions. Due
to their high vitamin K content, green, leafy vegetables, such as kale and collards, may
interfere with the effectiveness of warfarin, but not the DOACs. Out-of-pocket cost and
availability of adequate health insurance may also drive decisions towards or away from
specific treatments. Attention to these details will enhance the effectiveness of
interventions for all patient populations.
C.4.9. Sample Size Calculations for Impact of Shared Decision-Making Consultation on
Decisional Conflict - The investigators will offer enrollment to patients referred to these
services in a study evaluating their experience with the shared decision-making visit. The
following numbers are based upon a conservative enrollment rate of 30%, (120 of 400 patients
in that group) and shows the minimal point change in decisional conflict the investigators
would be able to detect, using paired t-tests for pre vs post, a two-tailed alpha = .05, and
90% power. In preliminary studies, the average score for decisional conflict prior to the
visit was 31 (100-point scale), post-visit mean was 9. Mean change was 22.3 (95% CI, 17.2 -
27.3) with a standard deviation of the change of 20. With those parameters the investigators
could detect a mean improvement in decisional conflict as small as 6.0 points, slightly more
than a minimally important change (33), but much smaller than the mean change of 22.3 seen in
preliminary work. The stated numbers do not account for the effects of covariates, which
would increase power slightly, or of clustering, which would reduce power slightly.
C.4.10. Data Analysis Plans - Data will be stored in the UC Secure Data Center using
Microsoft SQL™ and managed by the Center for Health Informatics. The investigators will
create SAS data files as necessary for statistical analyses using unique coded patient
identifiers. The major outcome of interest is "appropriate thromboprophylaxis". The
investigators will assess overall rates of "appropriate thromboprophylaxis" in each study
arm, along with change rates following advisories and shared decision-making consultations
for "non-optimal" thromboprophylaxis following each intervention. The investigators realize
that the active intervention consists of a bundle that includes both a BPA and the option to
refer the patient to a Shared Decision-Making service. The investigators first will analyze
differences in "appropriate thromboprophylaxis" between the two study arms, regardless of
whether physicians ordered a consultation or not. The investigators will perform exploratory
analyses comparing "appropriate thromboprophylaxis" between study arm one (AFDST alone) and
those in study arm two who did or did not get referred for a Shared Decision-Making
consultation, to better understand the incremental benefit of the consult service over and
above the BPA added to the decision support tool. The investigators realize there may not be
sufficient power for these exploratory analyses to provide definitive results.
All hypotheses will be addressed by modeling continuous measures (such as the decisional
conflict scale) or rates (such as appropriate thromboprophylaxis), to compare groups, and the
effects of groups and/or covariates. In the simplest cases, these can be t-tests, chi-square
tests of independent proportions, or McNemar tests. The addition of patient-level covariates
(e.g., gender, age, race, health literacy, numeracy, CHA2DS2VASc and HASBLED scores) or
physician/practice-level covariates (e.g., ambulatory or inpatient site of care, faculty
physician, staff clinician, medical specialty) will be accomplished using generalized linear
models. When possible the investigators will account for provider and/or clinic effects by
treating them as random effects or as clusters, using a GEE approach. All such models can be
estimated using SAS procedures GLM, GENMOD, MIXED, and GLIMMIX. Sample sizes permitting, the
investigators will conduct secondary analyses on subgroups based on physician/practice
factors and patient factors, similar to those described above as covariates. Alpha for each
test will be a two-tailed 0.05, unadjusted for multiple tests. The investigators will perform
simple descriptive analyses of clinical outcomes, such as stroke or bleeding. However, the
investigators do not expect that differences in event rates following sequential
interventions will be large enough to demonstrate statistically significant differences in
clinical outcomes.
The investigators recognize that the behavior of the clinicians is critical to assessing the
outcome of this project. Each clinical practice has its own culture through which
interventions will be filtered prior to any changes in practice. Drs. Kues, Arduser, and
Costanzo will assess the implementation of practice changes and physicians' experiences using
the AFDST through the various EHR interventions via semi-structured interviews with key
practice personnel and observations. Interviews will be audio recorded, coded and analyzed
using Nvivo®, a qualitative software analysis program. Research questions the investigators
will address through qualitative analyses include clinicians' perceptions regarding: 1) ease
of AFDST use and workflow integration, 2) usefulness of AFDST in patient care, 3) how or
whether they used the AFDST to involve the patient in a shared decision-making discussion, 4)
reasons for ignoring or bypassing BPAs for some of their patients, and 5) suggestions for
improving either the tool or its integration into the EHR and workflow.
