Clinical Trial Details
— Status: Completed
Administrative data
NCT number |
NCT06292130 |
Other study ID # |
156588-01 |
Secondary ID |
|
Status |
Completed |
Phase |
N/A
|
First received |
|
Last updated |
|
Start date |
March 21, 2022 |
Est. completion date |
September 21, 2023 |
Study information
Verified date |
March 2024 |
Source |
Pro-Change Behavior Systems |
Contact |
n/a |
Is FDA regulated |
No |
Health authority |
|
Study type |
Interventional
|
Clinical Trial Summary
Tobacco use remains the leading preventable cause of death in the US, contributing to more
than 480,000 premature deaths each year. The Tobacco Treatment Guidelines underscore the need
to offer patients who use tobacco products brief interventions that include prescriptions for
proven pharmacological smoking cessation aids and proactive connections to evidence-based
behavioral support. The rapid expansion of smart phone capabilities enhances the potential
for tobacco cessation apps to personalize behavior change guidance and to send contextually
relevant tailored behavior change nudges based on readiness to quit and electronic heath
record (EHR) data. Rich data from EHRs are now available to third-party apps from the Health
app (iOS) via Fast Healthcare Interoperability Resources standard Application Programming
Interface (API).
This Phase I SBIR will explore the acceptability and effects of one such innovative health IT
solution. Refresh is a highly individualized tobacco cessation HealthKit enabled app that
will 1) implement a full range of best practices in tailored health behavior change
communications based on readiness to change; 2) individualize behavior change guidance based
on Health app data; and 3) concisely provide data and documentation of key actionable
insights in the EHR on the patient's smoking status, app usage, and brief micro-message
clinicians can deliver to reinforce and accelerate a patient's behavior change progress. This
interoperability will provide value to both patients and clinicians; empower and support
successful and lasting behavior change; and enable the implementation and evaluation of a
best-in-class approach to tobacco and nicotine treatment.
Extensive end user and stakeholder input will ensure refresh is designed for rapid
dissemination. Patients of an integrated delivery system with an upcoming appointment (n=100)
will be recruited to participate in a 30-day pilot test. Pilot participants will provide
quantitative and qualitative data, and utilization and acceptability data will be examined.
Pre-post comparisons of PROMIS measure for tobacco (psychosocial expectancies) will provide
preliminary data on the effects of the program. Acceptability data from participating
clinicians (n=10) who receive and deliver EHR prompts will also be gathered. The hypothesis
is that the patients who utilize refresh will have significantly higher psychosocial
expectancies regarding tobacco at follow-up. Secondary outcomes will be examined.
Description:
For the pilot, the health system will run a workbench report in Epic to identify
English-speaking tobacco users aged 18 or older with an upcoming appointment with any of the
5 participating clinicians from primary care/internal medicine. Invitations for patients with
an upcoming appointment in the next 42 days will be sent via an alert in MyHealth, the
patient portal. These proactive communications will be sent on behalf of the clinician whom
the patient is scheduled to see and will invite the patient to visit the study landing page.
The landing page will provide an overview of the study, include frequently asked questions,
and will include a link to a brief screener. Potentially interested patients will be asked
whether they currently use any tobacco products; own an iPhone 6s or newer (available since
9/2015); and are able and willing to download a tobacco cessation app. Patients will be
excluded if they do not use tobacco, do not own a compatible iPhone, or are unwilling/unable
to download the app. Eligible patients will be provided with an informed consent document to
review and a link to a specific section of the app store to download FHIR-ed Up. Recruitment
will continue until each clinician has recruited 20 patients. Once the participant completes
the informed consent and screener (i.e., baseline assessment of patient's smoking history,
current rate of tobacco use, psychosocial expectancies, and readiness to quit smoking,
tobacco products, and electronic nicotine delivery systems (ENDs), they will be asked to
download the app. As part of the app onboarding process, users will be invited to enable the
app to access their health records via their Health app. Users will be invited to interact
with the app as often as they like over the following 30 days. Each user's experience will be
tailored to their responses. All new data elements that become available from user
assessments or the Health app will be used to further tailor the user's feedback, nudges, and
prompts. Data on the patient's readiness to quit, current smoking status, number of
interactions with the app, and the evidence-based behavior change message that would be most
helpful for the patient will be transmitted to a research assistant at the health system who
will manually enter it into the patient's chart in the pre-visit encounter note to simulate
an automated transmission and ensure it is available for the upcoming visit. At that visit,
the data elements will thus be in a chart note at the clinician's fingertips in the patient
visit view of Epic. Within one week of the visit, participants will receive an email or text
message inviting them to complete a follow-up survey, including readiness to change,
psychosocial expectancies, acceptability measures, and open-ended questions regarding what
they liked most and least about each intervention component and how the app could be
improved. Patients who don't complete it within one week will be called and asked to complete
by phone. In addition to the specified outcomes of feasibility, acceptability, and
preliminary effects, the app will provide an array of utilization and engagement data at the
participant level. Key utilization metrics will include app opens and activities accessed by
user.
Upon the completion of the pilot test, the 5 participating clinicians will be asked to
complete an online survey. They will be asked what they liked most and least about the EHR
prompts, major facilitators and barriers to implementation, and how the prompts could be
improved. Their feedback on what went well and ideas for addressing any challenges will be
used to revise procedures to help ensure successful implementation in Phase II. They will
also be asked to complete a modified version of Weiner's 3-dimensional measure
(acceptability, appropriateness, feasibility) of implementation outcome. Data with regard to
the number of patients for whom each clinician delivered the behavior change message will be
captured.
This pilot involves a single-group, pre-post design. Simple descriptive statistics will be
calculated to describe the study sample and to evaluate app utilization and acceptability.
Data analysis for the final outcome, psychosocial expectancies, will be analyzed using
general linear mixed models (GLMM). Residuals will be examined to make a final determination
regarding type of distribution - discrete count, ordinal, or continuous. Count and ordinal
outcomes will be analyzed with Statistical Analysis System (SAS) Proc GLIMMIX; continuous
outcomes will be analyzed using General Linear Models (a subclass of GLMM) with SAS Proc
Mixed. The primary model will assess whether psychosocial expectancies increased over time.
Based on accumulated data from Pro-Change intervention trials and pilot tests, we estimate an
effect size d=.30 for psychosocial expectancies. Assuming study retention rate of 75%, we
will recruit 100 patients so that N=75 remain at follow-up to provide a power estimate that
will exceed β= .80 in a one-tailed test at α= .05. Secondary analyses will be conducted using
GLMM to examine the impact of the intervention on patient's readiness to quit tobacco;
confidence for quitting, and tobacco use behavior. Intervention dose-response effects based
on level of engagement/utilization of FHIR-ed Up and clinician interaction will also be
conducted.