IVACS: Intelligent Voice Assistant for Coronavirus Disease (COVID-19) Self-Assessment

At the time of writing this paper, the world has around eleven million cases of COVID-19, scientifically known as severe acute respiratory syndrome corona-virus 2 (SARS-COV-2). One of the popular critical steps various health organizations are advocating to prevent the spread of this contagious disease is self-assessment of symptoms. Multiple organizations have already pioneered mobile and web-based applications for self-assessment of COVID-19 to reduce this global pandemic's spread. We propose an intelligent voice-based assistant for COVID-19 self-assessment (IVACS). This interactive assistant has been built to diagnose the symptoms related to COVID-19 using the guidelines provided by the Centers for Disease Control and Prevention (CDC) and the World Health Organization (WHO). The empirical testing of the application has been performed with 22 human subjects, all volunteers, using the NASA Task Load Index (TLX), and subjects performance accuracy has been measured. The results indicate that the IVACS is beneficial to users. However, it still needs additional research and development to promote its widespread application

Talk2Care: Facilitating Asynchronous Patient-Provider Communication with Large-Language-Model

Despite the plethora of telehealth applications to assist home-based older adults and healthcare providers, basic messaging and phone calls are still the most common communication methods, which suffer from limited availability, information loss, and process inefficiencies. One promising solution to facilitate patient-provider communication is to leverage large language models (LLMs) with their powerful natural conversation and summarization capability. However, there is a limited understanding of LLMs' role during the communication. We first conducted two interview studies with both older adults (N=10) and healthcare providers (N=9) to understand their needs and opportunities for LLMs in patient-provider asynchronous communication. Based on the insights, we built an LLM-powered communication system, Talk2Care, and designed interactive components for both groups: (1) For older adults, we leveraged the convenience and accessibility of voice assistants (VAs) and built an LLM-powered VA interface for effective information collection. (2) For health providers, we built an LLM-based dashboard to summarize and present important health information based on older adults' conversations with the VA. We further conducted two user studies with older adults and providers to evaluate the usability of the system. The results showed that Talk2Care could facilitate the communication process, enrich the health information collected from older adults, and considerably save providers' efforts and time. We envision our work as an initial exploration of LLMs' capability in the intersection of healthcare and interpersonal communication.Comment: Under submission to CHI202

Notable Bills of the 2012 General Assembly

House and Senate Bills during the 2012 General Assembl

Notable Bills of the 2012 General Assembly

House and Senate Bills during the 2012 General Assembl

Vol. 43, No. 2: Summer 2018

https://commons.und.edu/ndm-archive/1006/thumbnail.jp

The Veterans Affairs Patient Aligned Care Team (VA PACT), a New Benchmark for Patient-Centered Medical Home Models: A Review and Discussion

Objective: Conduct a literature review on existing patient-centered medical home (PCMH) models and outline the differences and contributions

House Bills

Listing of House bills from the 2013 General Assembl

Integrating Ethics and the Opioid Crisis via Simulation: An Ethical Debriefing for Nursing Students

Over the past three decades, opioid medication misuse and abuse has skyrocketed. The increase in improper use has created the need for more frequent exercise of ethical reasoning skills in practice. This study was designed to determine the effect of an ethics-centered debriefing exercise following a standardized simulation scenario concerning opioid misuse/abuse on nursing students’ value of and perceived confidence in ethical reasoning skills. 18 senior level BSN students at James Madison University in Harrisonburg, VA, participated in an ethics- focused debriefing exercise following the simulated scenario. The debriefing was constructed using the ANA Code of Ethics and James Madison University Eight Key Question framework. Students’ outlooks on ethical reasoning, both perceived confidence and value of, were captured before and after the experience via the CARS Survey of Ethical Reasoning. This study found that overall confidence, knowledge, and perceived value of ethical reasoning were increased following the simulation and debriefing experience and concluded that a structured debriefing exercise following exposure to an opioid-involved patient scenario was beneficial to students’ ethical reasoning skills, and better prepared them for these scenarios in practice