Smart Digital Assistants as Customizable Patients
Motivation:
Healthcare educators rely on standardized patients to simulate patients and practice scenarios, especially for tasks that require communication with the patient. Simulation provides a safe space to practice and learn before interacting with real patient. Healthcare
students (e.g., nursing students, medical students) need to be able to practice any time anywhere, especially when their study schedule is very tight. Standardized patients are very expensive and not always available, especially outside the classroom or dedicated simulation times. Additionally, during the Covid19 pandemic, lockdown and social distancing made the opportunity for in person simulation harder which pushed educators and researchers to seek virtual solutions. One possibility to make training widely available to healthcare educators and students is to use digital assistants such as Amazon Alexa, Apple Siri, Microsoft Cortana, and Google. Voice-based digital assistants have significantly evolved in the past few years. While they are used in different domains, their use in healthcare has been limited to applications such as reminding patients to take medication, or to walk every hour, or as an assistant in searching for symptoms and providing answers upon the patient’s request. Digital Assistants have not been used to simulate patients’ responses that allow healthcare trainees to practice communication and critical thinking in eliciting information from the patient, such as in the case of a review of systems.
Innovation Description:
Allowing healthcare educators to custom the responses of the digital assistant and providing the customized modules for their students to practice anytime anywhere can be a game changer in healthcare education. We propose to create an Alexa Skill software that is connected to a Google sheet. The Alexa Skill simulates being the patient and reads the customized content from the Google sheets. Healthcare providers (the super users) can create their own content and feedback by modifying the Google sheet. Healthcare students (the end users) can practice anytime anywhere by asking questions to Alexa (the simulated patient). Alexa will retrieve the relevant content (e.g., patient’s responses) from the Google sheet and will respond back to the end user. At the end of the practice the students receive an after-action review informing them what they did right and what they missed.
Impact:
We are in the process of designing multiple studies to evaluate the usability, technology acceptance, and efficacy in terms of short-term and long-term learning. We expect that allowing educators to easily custom create content for different healthcare scenarios simulating patients combined with the availability of the software to any student to practice anytime anywhere will improve learning and patient outcomes. This technology is low cost and can be used by nursing and medical students, especially when practice is needed, and standardized patients are not available.
Videos:
Publications:
2022
Sarah Jane Mee, Salam Daher
Alexa, M.D. Journal Article
In: IEEE Internet of Things Magazine, vol. 55, iss. 2, pp. 85-89, 2022, ISSN: 1558-0814.
@article{mee2022alexa,
title = {Alexa, M.D.},
author = {Sarah Jane Mee and Salam Daher},
editor = {Joanna F. Defranca},
url = {https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9714086undefined},
doi = {10.1109/MC.2021.3126528},
issn = {1558-0814},
year = {2022},
date = {2022-02-14},
urldate = {2022-02-14},
journal = {IEEE Internet of Things Magazine},
volume = {55},
issue = {2},
pages = {85-89},
abstract = {In the health-care field, intelligent personal assistants (IPAs) are commonly used as diagnostic guides for health-care professionals or support for patients. This article expands the use of IPAs in health care by demonstrating using Alexa to train health-care personnel.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
2020
Vivian Sanchez, Salam Daher
Automating Virtual Patients Responses for Medical Simulation Conference
Great Minds in STEM, 2020.
@conference{sanchez2020automating,
title = {Automating Virtual Patients Responses for Medical Simulation},
author = {Vivian Sanchez and Salam Daher},
url = {https://drive.google.com/file/d/1wE61kpo1ljqZksb6jb4r4xfILhb7J0AA/view?usp=sharing},
year = {2020},
date = {2020-10-01},
urldate = {2020-10-01},
booktitle = {Great Minds in STEM},
abstract = {Voice assistants are not being used enough in healthcare. Health students train on simulators that requires members of faculty to control patient responses. This takes up resources and limits the students to certain training times. We created an Alexa skill for a stroke patient scenario, connected it to a 3D character, and explored the capabilities and limitations of the Amazon Alexa. Healthcare students can then interact with the Alexa patient without the faculty feeding the answers to the patient. By supplementing existing simulations with an automated way to respond while still providing controlled answers can allow more doctors and nurses to practice without waiting for an available instructor.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}