Clinical Trial Details
— Status: Enrolling by invitation
Administrative data
NCT number |
NCT05198765 |
Other study ID # |
20-107 |
Secondary ID |
R01DK128281 |
Status |
Enrolling by invitation |
Phase |
N/A
|
First received |
|
Last updated |
|
Start date |
April 19, 2023 |
Est. completion date |
April 2026 |
Study information
Verified date |
January 2024 |
Source |
HealthPartners Institute |
Contact |
n/a |
Is FDA regulated |
No |
Health authority |
|
Study type |
Interventional
|
Clinical Trial Summary
Despite steady increases in obesity prevalence, the more than 12 million obese U.S. adults
with type 2 diabetes (T2DM) and severe obesity encounter a number of barriers to adopting
effective surgical and pharmaceutical treatments, including: (a) both patients and primary
care clinicians frequently underestimate the effectiveness and potential benefits of obesity
treatments; and (b) both patients and clinicians typically lack access to evidence-based
estimates of the patient-specific potential benefits and risks of appropriate obesity
treatment options. This project addresses these important obstacles to evidence-based obesity
care by providing accurate, patient-specific estimates of benefits and risks of various
obesity treatment options to inform shared decision making about obesity treatment.
In this project the study team will implement a scalable, web-based point-of-care
decision-support intervention in primary care that provides patient-specific estimates of
obesity treatment benefits and risks in a randomized trial in 40 primary care clinics with
15,810 eligible patients, and assess intervention impact on (i) appropriate active management
of obesity in eligible patients, (ii) weight trajectories, and (iii) patient and clinician
satisfaction with the decision support intervention.
Description:
Obesity has been steadily increasing in prevalence and now affects more than 4 in 10 U.S.
adults, leading to many adverse health outcomes including myocardial infarction, stroke, type
2 diabetes (T2DM), hypertension, sleep apnea, arthritis, and others. Effective surgical,
pharmaceutical, and behavioral treatments for obesity are available, and the evidence to
support the broad use of these treatments for obesity is very well established. However,
active management of obesity defined as prescribing or referring adults with obesity for
lifestyle, pharmaceutical, or surgical treatment of obesity, is greatly underused. Major
underlying reasons for underutilization of effective obesity treatments include: (a) both
patients and primary care clinicians (PCCs) frequently underestimate the effectiveness and
potential benefits of obesity treatments; and (b) both patients and clinicians typically lack
access to evidence-based, patient-specific estimates of the potential benefits and risks of
appropriate patient-specific obesity treatment options.
To address this problem, the study team will integrate externally validated prediction
equations that estimate benefits and risk of various obesity treatment options in adults with
T2DM into a widely-used and successful clinical decision support system in order to deliver
appropriate patient-specific obesity treatment suggestions at the point of care. The team
will implement a scalable, web-based point-of-care decision-support intervention in a
randomized trial in 40 primary care clinics with 15,810 eligible patients, and assess
intervention impact on the following primary outcomes: (a) appropriate referral of eligible
patients for evaluation for metabolic bariatric surgery (MBS); (b) appropriate initiation of
FDA-approved medications for weight loss; (c) weight trajectories; and (d) patient-reported
conversations with their PCC about weight loss and intentions to engage in weight loss. In
addition, the study team collect and analyze clinician-reported and patient-reported data to
identify factors that may impede or facilitate broad dissemination of this intervention
strategy to other care delivery settings.
This innovative project will (a) provide state-of-the-art scientific evidence on obesity
treatment to large numbers of obese American adults with T2DM and their PCCs at the point of
care; (b) help PCCs identify appropriate patient-specific obesity treatment options; (c)
implement in primary care a web-based electronic health record (EHR)-linked obesity treatment
clinical decision support model that uses state-of-the-art Health Information Technology
(HIT) standards, is broadly scalable, easy to update as evidence changes, and optimized for
clear communication of information to patients and PCCs; and (d) improve the clinical return
on ongoing massive private and public investments in outpatient health information systems.