Purpose of Review
With the rising cost of cardiovascular clinical trials, there is interest in determining whether new technologies can increase cost effectiveness. This review focuses on current and potential uses of voice-based technologies, including virtual assistants, in cardiovascular clinical trials.
Recent Findings
Numerous potential uses for voice-based technologies have begun to emerge within cardiovascular medicine. Voice biomarkers, subtle changes in speech parameters, have emerged as a potential tool to diagnose and monitor many cardiovascular conditions, including heart failure, coronary artery disease, and pulmonary hypertension. With the increasing use of virtual assistants, numerous pilot studies have examined whether these devices can supplement initiatives to promote transitional care, physical activity, smoking cessation, and medication adherence with promising initial results. Additionally, these devices have demonstrated the ability to streamline data collection by administering questionnaires accurately and reliably. With the use of these technologies, there are several challenges that must be addressed before wider implementation including respecting patient privacy, maintaining regulatory standards, acceptance by patients and healthcare providers, determining the validity of voice-based biomarkers and endpoints, and increased accessibility.
Summary
Voice technology represents a novel and promising tool for cardiovascular clinical trials; however, research is still required to understand how it can be best harnessed.
Background
The COVID-19 pandemic has disrupted the health care system, limiting health care resources such as the availability of health care professionals, patient monitoring, contact tracing, and continuous surveillance. As a result of this significant burden, digital tools have become an important asset in increasing the efficiency of patient care delivery. Digital tools can help support health care institutions by tracking transmission of the virus, aiding in the screening process, and providing telemedicine support. However, digital health tools face challenges associated with barriers to accessibility, efficiency, and privacy-related ethical issues.
Objective
This paper describes the study design of an open-label, noninterventional, crossover, randomized controlled trial aimed at assessing whether interactive voice response systems can screen for SARS-CoV-2 in patients as accurately as standard screening done by people. The study aims to assess the concordance and interrater reliability of symptom screening done by Amazon Alexa compared to manual screening done by research coordinators. The perceived level of comfort of patients when interacting with voice response systems and their personal experience will also be evaluated.
Methods
A total of 52 patients visiting the heart failure clinic at the Royal Victoria Hospital of the McGill University Health Center, in Montreal, Quebec, will be recruited. Patients will be randomly assigned to first be screened for symptoms of SARS-CoV-2 either digitally, by Amazon Alexa, or manually, by the research coordinator. Participants will subsequently be crossed over and screened either digitally or manually. The clinical setup includes an Amazon Echo Show, a tablet, and an uninterrupted power supply mounted on a mobile cart. The primary end point will be the interrater reliability on the accuracy of randomized screening data performed by Amazon Alexa versus research coordinators. The secondary end point will be the perceived level of comfort and app engagement of patients as assessed using 5-point Likert scales and binary mode responses.
Results
Data collection started in May 2021 and is expected to be completed in fall 2022. Data analysis is expected to be completed in early 2023.
Conclusions
The use of voice-based assistants could improve the provision of health services and reduce the burden on health care personnel. Demonstrating a high interrater reliability between Amazon Alexa and health care coordinators may serve future digital tools to streamline the screening and delivery of care in the context of other conditions and clinical settings. The COVID-19 pandemic occurs during the first digital era using digital tools such as Amazon Alexa for disease screening, and it represents an opportunity to implement such technology in health care institutions in the long term.
Trial Registration
ClinicalTrials.gov NCT04508972; https://clinicaltrials.gov/ct2/show/NCT04508972
International Registered Report Identifier (IRRID)
DERR1-10.2196/41209
The acceptability of artificially intelligent interactive voice response (AI-IVR) systems in cardiovascular research settings is unclear. As a result, we evaluated peoples’ attitudes regarding the Amazon Echo Show 8 device when used for electronic data capture in cardiovascular clinics. Participants were recruited following the Voice-Based Screening for SARS-CoV-2 Exposure in Cardiovascular clinics study. Overall, 215 people enrolled and underwent screening (mean age 46.1; 55% females) in the VOICE-COVID study and 58 people consented to participate in a post-screening survey. Following thematic analysis, four key themes affecting AI-IVR acceptability were identified. These were difficulties with communication (44.8%), limitations with available interaction modalities (41.4%), barriers with the development of therapeutic relationships (25.9%), and concerns with universality and accessibility (8.6%). While there are potential concerns with the use of AI-IVR technologies, these systems appeared to be well accepted in cardiovascular clinics. Increased development of these technologies could significantly improve healthcare access and efficiency.
Supplementary Information
The online version contains supplementary material available at 10.1007/s12265-022-10289-y.
Background and Aims: Objective monitoring and effective early treatment using a treat-to-target approach are key to improving therapeutic outcomes in IBD patients. This study aimed to assess adherence to objective monitoring (clinical, biomarkers, and endoscopy) and its impact on clinical outcomes.
Methods: A prospective, multicenter study included consecutive IBD patients starting on adalimumab therapy between January 2019 and December 2020. Disease activity, assessed by the Harvey-Bradshaw index (HBI), partial Mayo, C-reactive protein (CRP), fecal calprotectin (FCAL), and endoscopy were evaluated at adalimumab initiation and 3, 6, 9 and 12 months. Therapeutic drug monitoring, changes in treatment, drug sustainability, and clinical outcomes were assessed.
Results: 104 IBD patients were enrolled (78.8% CD, median age 34.3 years, disease duration 9 years). During the 12 months follow-up, high adherence to clinical activity assessment was observed in both CD (81.3%- 87.7%) and UC patients (76.5-90.9%). CRP measurement decreased over time in both CD (37.3%-54.9%) and UC (29.4%-50.0%). The adherence to serial FCAL monitoring was low in CD (22.7-31.3%) and UC patients (17.6-56.0%). UC patients had higher adherence to early endoscopic assessment (<6 months) compared to CD patients (40.9% vs. 21.5%). Adherence to early combined clinical and biomarkers resulted in earlier dose optimization in CD and UC (log-rank<0.001), but drug sustainability was not different. The patients with early combined adherence had a significantly higher clinical remission rate at 1 year compared to non-adherence (70.2% vs. 29.8%, p=0.007) but no significant difference in UC patients.
Conclusions: The adherence to early objective monitoring with combined clinical and biomarkers assessment in IBD patients starting adalimumab therapy led to dose optimization and improved 1-year clinical remission in CD but did not change drug sustainability and clinical remission in UC.
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