Clinical trial NCT04993807: Data-driven SDM to Reduce Symptom Burden in AF
Official title: Data-driven Shared Decision-Making (SDM) to Reduce Symptom Burden in Atrial Fibrillation (AF)
Study type: INTERVENTIONAL
Overall status: ACTIVE_NOT_RECRUITING
Phase: NA
Conditions: Atrial Fibrillation
Patient Engagement
Keywords: Shared Decision-Making (SDM)
Symptom Burden
Decisional Conflict
Decision Regret
Decision Satisfaction
Lead sponsor: Columbia University
Sponsor class: OTHER
Collaborators: name: National Institute of Nursing Research (NINR)
First posted: 2021-08-06
Enrollment: 75
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: NA
Intervention model: SINGLE_GROUP
Intervention model description: This is a single arm feasibility study.
Primary purpose: OTHER

Brief summary: This study is a single-group feasibility study evaluating decision aid visualizations which display common post-ablation symptom patterns as a tool for shared decision-making. The specific aim of the clinical trial is to evaluate the feasibility of putting the visualizations into clinical practice (n=75). The hypothesis is that patients will report low decisional conflict and decision regret and high satisfaction with their decision about whether to undergo an ablation or not.

Detailed description: Atrial fibrillation (AF) is the most common heart rhythm disorder, and nearly 90% of patients experience symptoms such as shortness of breath that directly impair their health-related quality of life (HRQoL). Catheter ablation is a minimally invasive, surgical procedure that is routinely performed to treat AF and associated symptoms with the goal of improving HRQOL, but also carries potentially serious risks. Shared decision-making (SDM), in which treatment decisions are aligned based on high quality evidence and patient values and goals of care, is a widely encouraged practice for navigating complex healthcare decisions such as these. However, SDM around rhythm and symptom management does not routinely occur due to a lack of detailed evidence about symptom improvement post-ablation, and a lack of decision aids to communicate evidence to patients. The overarching goal of this award is to create an interactive patient decision aid composed of established evidence from clinical trials together with novel "real world" evidence about symptom improvement post ablation mined from electronic health records (EHRs).

The investigators propose to use "real-world evidence" drawn from electronic health records (EHRs) to characterize post-ablation symptom patterns, and display them in decision-aid visualizations to support shared decision-making (SDM). In this project, the investigators will first use natural language processing (NLP) and machine learning (ML) to extract and analyze symptom data from narrative notes in EHRs. The investigators will also employ a rigorous, user-centered design protocol created during the Principal Investigator's post-doctoral work to develop decision-aid visualizations. In the clinical trial, the investigators will evaluate the feasibility of implementing these interactive decision-aid visualizations in clinical practice.

Eligibility criteria: Inclusion Criteria:

* Diagnosis of paroxysmal AF according to International Classification of Diseases, Tenth Revision (ICD-10)
* Scheduled consultation at NewYork-Presbyterian Hospital (NYP) to discuss catheter ablation
* Symptomatic AF at baseline
* Age 18 years and older
* Able to read and speak English
* Willing/able to provide informed consent

Exclusion Criteria:

* Asymptomatic AF
* Severe cognitive impairment
* Major psychiatric illness
* Concomitant terminal illness that would preclude participation

Primary outcomes:
measure: Decisional conflict assessed using the Decisional Conflict Scale
timeFrame: Baseline
measure: Decision regret assessed using the Decisional Regret Scale
timeFrame: 12 weeks
measure: Decision satisfaction assessed using the Satisfaction with Decision Scale
timeFrame: 12 weeks
Secondary outcomes:
measure: Post-ablation symptom burden assessed using the Atrial Fibrillation severity Scale (AFSS)
timeFrame: 12 weeks
measure: Post-ablation health-related quality of life assessed using the Atrial Fibrillation Effect on QualiTy-of-Life (AFEQT) questionnaire
timeFrame: 12 weeks
Other outcomes:
Locations:
city: New York
country: United States
facility: Weill Cornell Medicine
state: New York
city: New York
country: United States
facility: Columbia University Irving Medical Center
state: New York
Study officials:
affiliation: Columbia University
name: Meghan Reading Turchioe, PhD, MPH, RN
role: PRINCIPAL_INVESTIGATOR
References: