Overview: Using key stakeholder engagement, this study will refine clinician- and
patient-directed nudges designed to change the status quo bias that too often is relied
upon within the complexity of medical care and decision-making, which reduces the
likelihood that genetic testing will be used in situations where it will change medical
management. The investigatorswill define algorithms to identify patients eligible for
genetic testing (Aim 1); conduct a hybrid type 3 cluster-randomized implementation trial
to evaluate optimized patient- and/or clinician-directed nudges for increasing the use of
genetic testing to inform medical management (Aim 2); and engage in dissemination
activities to increase the capacity of other medical settings to adopt both our EHR-based
infrastructure and the implementation strategies designed and evaluated in this trial
(Aim 3).
For Aim 1, our Stakeholder Advisory Council will design the nudges to "de-risk" and
optimize implementation strategies by ensuring that the perspectives of end-users are
included initially. In Aim 2, the investigators will test our optimized nudges in a
six-arm hybrid type 3 pragmatic cluster randomized controlled trial (RCT) to evaluate the
effectiveness of nudges to clinicians (referral vs.#46; ordering), nudges to patients, or
nudges to both for increasing genetic testing, vs.#46; generic clinician Best Practice Alert
and no nudge. The trial will include 230 clinicians, who will be the unit of
randomization, with randomization performed on "clusters" of clinicians to control for
the potential of contamination that can arise when clinicians who work closely together
are randomized to different arms of the trial. Once the clusters are randomized by
specialty, the trial will follow at least 16,500 patients over 3 years, monitoring
fidelity of nudge delivery, use of genetic testing, and secondary implementation
outcomes. Patient, clinician, and system factors will be assessed as moderators and an
effectiveness outcome will be examined.
In Aim 3, Both EHR-based algorithms already established through the PennChart Genomics
Initiative, for which the investigators have received multiple requests, and those
developed through this application, will be shared through PheKB, ANVIL, and Epic
Community Library.
Aim 1: To develop clinician- and patient-directed nudges, informed by behavioral economic
theory, within the EHR that will address the barriers to specialist clinician genetic
testing of patients in whom it will change medical management, develop clinician- and
patient-directed informational websites, and refine EHR algorithms to identify patients
who are good candidates for genetic testing. Procedures for refining systems to identify
patients for genetic testing: Although there is a growing number of conditions for which
genetic testing is indicated where the results will change medical management for
patients, between 0-90% of patients have genetic testing. Changing this first depends on
the use of electronic phenotyping algorithms to identify eligible patients. Development
of electronic phenotype algorithms involves the integration of ICD-10 diagnosis codes,
clinical lab measurements, vital signs, medications, procedures, and clinical notes into
rule-based algorithms to identify individuals who can be classified with a diagnosis for
a given disease phenotype. The phenotype knowledgebase (PheKB) is a collaborative
environment to build, validate, and share these electronic phenotype algorithms. To
perform our RCT, the investigators first need to identify patients who would benefit from
genetic testing. The investigators will work closely with the clinical experts in
neurogenetics, cardiac, and medical genetics to identify the clinical features from the
EHR for defining disease diagnosis for each condition, including two prior encounters for
the diagnosis with first within a year. The investigators will deploy the algorithm and
then perform manual review of 100 charts to estimate the positive predictive value (PPV)
of the algorithm; this is the proportion of patients defined as cases by the algorithm
who have the condition. The investigators will also perform manual review of 100 charts
for individuals who have a diagnosis code in the EHR from two different encounters for
one of the study conditions but are not identified as cases based on the electronic
phenotyping algorithm. This review will give us an estimate of how much specificity the
investigators gain with the electronic phenotype algorithm above and beyond the diagnosis
codes alone. As the patients identified by the algorithm will be enrolled in the clinical
trial, the investigators will aim for 100% PPV. Each patient identified by the phenotype
algorithms will be added to the Diagnosis-specific Epic Registry and the SQL database.
The algorithms will be disseminated through Aim 3.
Procedures for nudge design: To develop a sustainable EHR-based infrastructure,
supporting the provision of genomic medicine and inclusion of specialty clinicians,
equally valuable for other groups nationally, the investigators must consider multiple
perspectives on how our nudges
- - content, design, and mode of delivery - will impact
institutions, payors, clinicians, and patients.
Thus, the investigators have formed a
Stakeholder Advisory Council with diverse representation from genetics and non-genetics
clinicians, informaticians, payors, testing companies, legal experts and ethicists, and
patient groups and community representation, with expertise regarding health disparities
and equity. The group will support the development of and wording in the nudges, genetics
and disease-specific website education for patients and clinicians, and ease of use of
the EHR-based infrastructure for genetic test ordering, results, and referral.
To ensure that our nudge design and delivery consider issues relevant to health
disparities and equity, the investigators have engaged Dr. Rachel Shelton as a
consultant. She is an expert in understanding and addressing existing health inequities
and identifying interventions and strategies to promote greater health equity. She has
worked with members of the research team to develop nudges that improve the quality of
cancer care delivery and consider existing health disparities and evaluate indicators of
health disparities as moderators of nudge effectiveness. The Stakeholder Advisory Council
will meet three times in the first year and then every six months in subsequent years;
discussions will be audio-recorded, and survey questions assessing usability of nudge
designs will be administered.
Patient informational video: The video will be employed as part of the patient-directed
nudge. Patients in patient nudge arms will be provided with a link to the video via text
message. The video will provide general information about genetic testing and patients
will be able to view it multiple times.
Clinician informational website: An informational website, maintained on the Penn
Medicine intranet, for clinicians will be developed; it will be available through the
clinician nudges and when results are returned. The website will include information
about genetics and genetic testing, details about ordering genetic testing through the
EHR (with tipsheets), referral to Penn Medicine genetic clinics and how the results of
genetic testing would influence the patient's medical management for each diagnosis.
Aim 2: To conduct a type 3 hybrid implementation cluster randomized clinical trial to
evaluate the effect of behavioral economic theory clinician nudges and patient nudges
delivered within the EHR on the rate of genetic testing by non-geneticist specialist
clinicians across a diverse health system, compared to generic messages and no
default.Overall design. The investigators will test optimized implementation strategies
in a six-arm factorial hybrid type 3 cluster implementation RCT, testing the
effectiveness of nudges to clinicians (referral vs.#46; order), nudges to patients, or nudges
to both for increasing genetic testing among patients for whom testing would influence
medical management vs.#46; a generic Best Practice Alert/no patient or clinician nudge. The
investigators include two forms of physician nudges
- - referral and ordering - to consider
and test the effects of a local adaptation to this implementation strategy, which can be
an important factor that influences the effectiveness of implementation strategies.
Primary and secondary implementation outcomes, and contextual factors that shape
implementation effectiveness and clinician census. Our trial adopts a health equity lens,
as done in our ongoing trials. To this end, our preliminary data focused on identifying
medical conditions for which genetic testing may affect outcomes and for which there
exists disparities in testing across races. Second, the investigators have considered
important health disparities in the design and delivery of our nudges. In particular, the
investigators examined the rate of access to our patient portal and, found that there are
lower rates of access for racial minority groups, including delivery of patient nudges
via text message as well. Third, the analytic plan includes an assessment of the impact
of our nudges across equity groups. All patient-facing materials will be available in
Spanish.
Participants and randomization. Clinicians within each site will be randomized to six
arms using variable permuted blocks. The researchers will form clusters of clinicians and
randomize clusters using raw data from clinic administrators to identify networks of
interconnected colleagues. A waiver of informed consent will allow for collection of
general census data to characterize the sample of clinicians, EHR data to characterize
the sample of patients, and ascertain data to assess as study moderators. Our clinician
sample, drawn from practicing clinicians within all sites, will 1) be currently in
practice at a Penn Medicine site; 2) have prescribing authority in Pennsylvania (i.e.,
physician or APP); and 3) have cared for at least five patients in 30 days prior to
recruitment.
Diagnosis-specific Epic Registry: Based on the electronic phenotype algorithms developed
in Aim 1, eligible patients will be filtered into diagnosis-specific Epic Registries.
This step is necessary to identify the patients eligible for observation in the trial.
Once identified and entered into this registry, and when these patients have an
appointment with a clinician within our clinician sample, they are entered into the
trial's system within one of the randomized arms. The registry drives the downstream
nudges, e.g. for clinic referral, genetic test selection, and clinician information.
Nudge to clinicians: The investigators will use the Best Practice Alert (BPA)
functionality within the EHR as our conduit to the point of decision-making about genetic
testing with clinicians. Epic BPA deployment is modifiable to accommodate the inclusion
of nudges. When a patient is scheduled to be seen by a clinician randomized to one of our
study arms and matching the patient eligibility (registry), at the subsequent visit with
this clinician, the clinician BPA will fire. The BPA can be triggered with over 50
multiple potential actions within the chart, such as entering patient diagnosis or
problem, or opening or entering orders. Resolution of the BPA will be required before the
chart is closed. The clinician nudge will have two forms to account for the need to
assess for local adaptation of the implementation strategy: refer or order. In either
case, refer or order are defaulted; the clinician must toggle to "do not order" or "do
not open (Order Set)" and, if so, an explanation is required. Prior to the launch of the
trial, clinicians receive standardized information about the trial through service line
disease team monthly meetings, led by the study MPIs. These sessions give basic
information about the study without disclosing the hypotheses.
Refer Clinician Nudge: For the refer clinician nudge, if accepted, an order is
automatically placed for a genetic consult with the appropriate genetics program, based
on the diagnosis-specific Epic Registry, either medical/cancer, cardiac or
neuro-genetics. The order will go to the scheduling pool for each program, which will
contact the patient for an appointment (warm hand off). For patients with pheo/pgl seen
in medical or cancer genetics, they will be seen locally, as all hospitals have cancer
genetics providers. For patients referred to cardiac or neurogenetics, patients will be
contacted and offered an in-person visit at either HUP or PAH or a telemedicine visit,
based on preference.
Order Clinician Nudge: For the order clinician nudge, the Epic SmartSet function will be
used since it is common and easily transferrable. The SmartSet will include 1) genetic
testing order with a default set of diagnosis-specific genes and a testing lab selected
(the BPAs and resulting Smart Sets will be sensitive to the patient's insurance, so if
the patient is capitated to a certain commercial testing lab or if sponsored testing is
available, the testing will go to that lab); 2) default order to have the genetic testing
kit (saliva or buccal swab) sent to the patient's house; 3) smartphrase to populate the
clinician's note; and 4) an option to send the clinical letter to the testing company.
Once the order is placed through the SmartSet, a linked second BPA will come up that
contains a one-page acknowledgment of genetic testing e-form for patient's signature
(every exam room has a signature pad for e-signature) for the clinician to review with
the patient. The after-visit summary (AVS) that each patient receives at the end of their
visit will be automatically populated with the signed acknowledgment e-form and link to
the patient educational website.
Nudge to patients: The patient nudge will be designed to "prime" the patient to discuss
the potential benefits of genetic testing with their clinician ahead of their next
appointment. The patient nudge will be delivered via text message directly to the
patient's cell phone. The patient nudge will be delivered within 72 hours prior to their
medical appointment and will include normalizing language about the potential benefits of
genetic testing for their condition and a clear message of endorsement: The patient nudge
will contain a link to the informational video discussed above.
Generic clinician nudge: To standardize the experience of all clinicians randomized to
this arm (and the patients they see), we will use a generic clinician BPA. The content of
the BPA will indicate that their patient may be a candidate for genetic testing and a
link to the clinician website. No choice architecture will be embedded to facilitate
genetic testing ordering or referring; no patient nudge is provided.
Support for clinicians when genetic testing results are returned: Across all study arms,
discrete results of genetic tests will be returned into the EHR, with an accompanying PDF
with the full results. Along with the results will be a static option with the hyperlink
to the clinician informational website and when they open the results, they will get a
BPA with options to: 1) order a consult to genetics, which will automatically go to the
disease appropriate clinic; or 2) e-Consult genetics, meaning that they can send a
question to genetics (again triaged based on disease type [Epic registry]) without a
formal referral.
Insurance coverage for genetic testing: A key point of concern for both clinicians and
patients is insurance coverage for genetic testing. Clinicians will not deal with
insurance coverage directly. The patient's insurance information goes via HL7 with the
testing order to the commercial lab, which deals with the insurance company.
Testing and validation of EHR nudges: To launch the nudges, investigators will use a
two-phase approach from past and ongoing studies. In the first phase, the alert will fire
invisibly in the background without prompting patients or clinicians, followed by an
evaluation of the results to verify accuracy. The algorithm will be refined until it
achieves perfect accuracy. In the second phase, clinician nudges will fire live for
several weeks among a few clinicians. Investigators will then compare the patients for
whom it should have fired to the ones for whom it did and the acceptability of the alert
to clinical staff. Nudge delivery will be monitored in all arms throughout the trial.
