Pediatrician Attitudes toward Digital Voice Assistant Technology Use in Clinical Practice

Vanderbilt Electronic Health Record Voice Assistant Supports Clinicians

BACKGROUND

 Electronic health records (EHRs) present navigation challenges due to time-consuming searches across segmented data. Voice assistants can improve clinical workflows by allowing natural language queries and contextually aware navigation of the EHR.

OBJECTIVES

 To develop a voice-mediated EHR assistant and interview providers to inform its future refinement.

METHODS

 The Vanderbilt EHR Voice Assistant (VEVA) was developed as a responsive web application and designed to accept voice inputs and execute the appropriate EHR commands. Fourteen providers from Vanderbilt Medical Center were recruited to participate in interactions with VEVA and to share their experience with the technology. The purpose was to evaluate VEVA's overall usability, gather qualitative feedback, and detail suggestions for enhancing its performance.

RESULTS

 VEVA's mean system usability scale score was 81 based on the 14 providers' evaluations, which was above the standard 50th percentile score of 68. For all five summaries evaluated (overview summary, A1C results, blood pressure, weight, and health maintenance), most providers offered a positive review of VEVA. Several providers suggested modifications to make the technology more useful in their practice, ranging from summarizing current medications to changing VEVA's speech rate. Eight of the providers (64%) reported they would be willing to use VEVA in its current form.

CONCLUSION

 Our EHR voice assistant technology was deemed usable by most providers. With further improvements, voice assistant tools such as VEVA have the potential to improve workflows and serve as a useful adjunct tool in health care.

Survey of Referral Patterns in Southwestern Mainland China: How Do Pediatricians Manage Children with Dysphonia

OBJECTIVE

Voice disorders are common in children and have a negative impact on their quality of life. However, presently, voice assessment and therapy are inaccessible in most pediatric departments of Mainland China. Thus, referring pediatric patients with voice disorders to otolaryngology is warranted for prompt and appropriate treatment. The purpose of this study is to investigate referral patterns and their influencing factors for pediatricians' managing children with dysphonia in Southwestern Mainland China.

STUDY DESIGN

Observational study.

METHODS

A 28-item questionnaire was designed by multidisciplinary experts, and an anonymous survey was performed online via Wenjuanxing between September 8, 2021 and October 8, 2021. The statistical analyses were performed using the independent sample median test, the linear/logistic regression model, the Kruskal-Wallis test, and Spearman's correlation test to determine any statistically significant relationships between the variables of interest.

RESULTS

Predominantly recruited from institutions in Southwestern China, 368 pediatricians were surveyed. (1) The majority of the pediatricians reported that ≤10% of children sought medical help for voice disorders; (2) only 22.1% of the pediatricians' hospitals had equipment for evaluating voice disorders; (3) 74.6% of the pediatricians would refer children with dysphonia to otolaryngology, and the older pediatricians were more likely to refer their patients than were the younger pediatricians (P = 0.022); (4) in the group that would make a referral (n = 250), the pediatricians who had worked longer (P = 0.037) and practised in the Grade-A tertiary hospitals (P = 0.044) were more likely to trust their experience as a reason for making a referral. For each year worked the probability of referring children with dysphonia depending on the pediatrician's experience increased by 3.4%.

CONCLUSION

Although the pediatricians encountered some barriers to diagnosing voice disorders, their attitude towards making referrals was positive. The age and work duration of the pediatricians and the hospital grade were the influencing factors in the referral patterns. Further publicity of vocal hygiene, ongoing education among Chinese pediatricians and the improvement of referral systems may be most useful for better managing children with dysphonia.

An Empirical Study of Older Adult’s Voice Assistant Use for Health Information Seeking

Although voice assistants are increasingly being adopted by older adults, we lack empirical research on how they interact with these devices for health information seeking. Also, prior work shows how voice assistant responses can provide misleading or inaccurate information and be harmful particularly in health contexts. Because of increased health needs while aging, this paper studies older adult’s (ages 65+) health-related voice assistant interactions. Motivated by a lack of empirical evidence for how older adults approach information seeking with emerging technologies, we first conducted a survey of n = 201 older adults to understand how they engage voice assistants compared to a range of offline and digital sources for health information seeking. Findings show how voice assistants were used for confirmatory health queries, with users showing signs of distrust. As much prior work focuses on perceptions of voice assistant use, we conducted scenario-based interviews with n = 35 older adults to study health-related voice assistant behavior. In interviews, participants engaged with different health topics (flu, migraine, high blood pressure) and scenario types (symptom-driven, behavior-driven) using a voice assistant. Findings show how conversational and human-like expectations with voice assistants lead to information breakdowns between the older adult and voice assistant. This paper contributes a nuanced query-level analysis of older adults’ voice-based health information seeking behaviors. Further, data provide evidence for how query reformulation happens with complex topics in voice-based information seeking. We use our findings to discuss how voice interfaces can better support older adults’ health information seeking behaviors and expectations.

The Children's Hospital of the Future: A Vision That Meets All Needs

OBJECTIVES

The objective of this article is twofold. First, to present a comprehensive internal assessment of the hospital by different groups of stakeholders and, second, to determine whether there are common needs and wishes that, if incorporated in the hospital vision, will enable future development.

BACKGROUND

The Children's Memorial Health Center is the largest children's hospital in Poland. The hospital began operations in 1977 with a vision to be a modern healthcare facility that provides comprehensive care for children. That vision has not changed over time but everything else did.

METHODS

Six design thinking sessions were conducted with 83 employees and 40 respondents who used health services in the hospital in the past, along with in-depth interviews with 25 representatives of management to gather data for the hospital assessment.

RESULTS

Sixty-three features influencing future development were identified. Seven groups of features were classified to be either transformation drivers (four groups) or enablers (three groups). We focused on features that were indicated by all groups of respondents to define a common vision for future development.

CONCLUSIONS

Depending on the respondent's role in the healthcare ecosystem, the list of variables within each of seven groups defining the "hospital of the future" was different while evaluating the healthcare services. Therefore, all stakeholders must be engaged in the ideation process to create a strategy for a future care model driven by innovation.

AI-based language models powering drug discovery and development

The discovery and development of new medicines is expensive, time-consuming, and often inefficient, with many failures along the way. Powered by artificial intelligence (AI), language models (LMs) have changed the landscape of natural language processing (NLP), offering possibilities to transform treatment development more effectively. Here, we summarize advances in AI-powered LMs and their potential to aid drug discovery and development. We highlight opportunities for AI-powered LMs in target identification, clinical design, regulatory decision-making, and pharmacovigilance. We specifically emphasize the potential role of AI-powered LMs for developing new treatments for Coronavirus 2019 (COVID-19) strategies, including drug repurposing, which can be extrapolated to other infectious diseases that have the potential to cause pandemics. Finally, we set out the remaining challenges and propose possible solutions for improvement.

A Practical Experience on the Amazon Alexa Integration in Smart Offices

Smart offices are dynamically evolving spaces meant to enhance employees' efficiency, but also to create a healthy and proactive working environment. In a competitive business world, the challenge of providing a balance between the efficiency and wellbeing of employees may be supported with new technologies. This paper presents the work undertaken to build the architecture needed to integrate voice assistants into smart offices in order to support employees in their daily activities, like ambient control, attendance system and reporting, but also interacting with project management services used for planning, issue tracking, and reporting. Our research tries to understand what are the most accepted tasks to be performed with the help of voice assistants in a smart office environment, by analyzing the system based on task completion and sentiment analysis. For the experimental setup, different test cases were developed in order to interact with the office environment formed by specific devices, as well as with the project management tool tasks. The obtained results demonstrated that the interaction with the voice assistant is reasonable, especially for easy and moderate utterances.