BEGIN:VCALENDAR
VERSION:2.0
PRODID:Linklings LLC
BEGIN:VTIMEZONE
TZID:America/Phoenix
X-LIC-LOCATION:America/Phoenix
BEGIN:STANDARD
TZOFFSETFROM:-0700
TZOFFSETTO:-0700
TZNAME:MST
DTSTART:19700101T000000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTAMP:20241014T203101Z
LOCATION:Grand Ballroom
DTSTART;TZID=America/Phoenix:20240911T111500
DTEND;TZID=America/Phoenix:20240911T113500
UID:HFESAM_ASPIRE - Presented by HFES_sess196_LECT197@linklings.com
SUMMARY:AI Scribes and the Future of Healthcare: A New Paradigm for Inform
 ed Consent
DESCRIPTION:Lecture\n\nIman Basha (University of Waterloo), Puneet Seth (M
 cMaster University), and Catherine Burns (University of Waterloo)\n\nIn th
 e evolving healthcare technology landscape, Ambient Scribe Technology - al
 so called Ambient Artificial Intelligence (AI) Scribe Technology (herein A
 I scribe) represents a significant innovation that can revolutionize prima
 ry care. AI scribes are designed to semi-automate physician paperwork by o
 perating unobtrusively in the background from electronic devices such as l
 aptops or smartphones. Their operation entails recording patient-physician
  conversations, transcribing the interactions into text, and subsequently 
 generating summaries in a standard format based on medically relevant info
 rmation extracted from the dialogue. Some AI scribes can also pre-populate
  prescriptions, requisitions, and billing codes, further assisting physici
 ans in their daily tasks.\n\nThe primary objective of an AI scribe is to a
 lleviate the documentation burden on physicians, a significant factor cont
 ributing to physician burnout [1], [2]. However, introducing such technolo
 gy also brings forth complex challenges related to privacy, consent, and d
 ata security [3]. These challenges are particularly pronounced in ambient 
 scribe technology due to its ability to record all information in patient-
 physician encounters, which may include sensitive and personal details. Mo
 reover, the lack of a comprehensive regulatory framework complicates these
  issues further [4], [5]. Currently, terms of service agreements between A
 I scribe providers and physicians govern data collection, retention, and u
 sage [6], [7], [8], [9], [10], [11]. Accordingly, clinicians are tasked wi
 th obtaining consent from their patients for the collection, use, and disc
 losure of personal information. There is ambiguity around service provider
 s' data processing methods, including whether and when de-identification i
 s completed. \n\nAt the surface level, the practice aligns with relevant r
 egulatory policies such as the Health Insurance Portability and Accountabi
 lity Act (HIPAA), the General Data Protection Regulation (GDPR), and the P
 ersonal Information Protection and Electronic Documents Act (PIPEDA), base
 d on the premise that users (physicians and patients) provided consent. Ho
 wever, the process undermines the need for informed consent (applicable un
 der GDPR and PIPEDA), the requirement for transparency on data use and pro
 cessing, and the right to access, amend, or remove data.\n\nThis study cri
 tically examines and addresses the nuanced issues of privacy and consent a
 rising from deploying AI scribes in clinical settings. Here, we present th
 e evaluation of a Multi-Tiered Granular Informed Consent (MTGIC) designed 
 for AI scribes. The MTGIC design incorporates tiered consent options [12] 
 and granular specificity clearly and concisely. Tiers categorize consent o
 ptions based on functionalities, such as basic use, data storage, and seco
 ndary data use and sharing, whereas granular options provide specific choi
 ces within the tiers for data type, duration and types of secondary uses. 
 The framework design draws upon existing literature on ambient intelligent
  systems and is informed by principles of Value-Sensitive Design [13] and 
 Privacy by Design [14]. \n\nThe study is guided by key questions aimed at 
 exploring the effectiveness of the MTGIC framework in addressing privacy a
 nd consent concerns among patients and physicians, its potential to enhanc
 e user adoption and trust, its perceived usability, and the integration of
  the multi-consent process into clinical workflows.\n\nTrack: Health Care\
 n\nSession Chair: Tosin Akintunde (University of Toronto)
END:VEVENT
END:VCALENDAR