Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Dec 31, 2021
Open Peer Review Period: Dec 30, 2021 - Feb 24, 2022
Date Accepted: Oct 19, 2022
(closed for review but you can still tweet)
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
The Computer Will See You Now: A Scoping Review of Digital Tools Designed to Obtain the History of Present Illness from Patients
ABSTRACT
Background:
Many medical conditions—perhaps 80% of them—can be diagnosed by taking a thorough history of present illness (HPI). In the clinical setting, however, situational factors such as interruptions and time pressure may cause interactions with patients to be brief and/or fragmented. One solution for improving clinicians’ ability to collect a thorough HPI and maximize efficiency and quality of care could be to use a digital tool to obtain the HPI prior to face-to-face evaluation by a clinician.
Objective:
Our objective was to identify and characterize digital tools that have been designed to (1) obtain the history of present illness (HPI) directly from patients or caregivers and (2) present this information to clinicians before a face-to-face encounter. We also sought to describe outcomes reported in testing of these tools, especially those related to usability, efficiency, and quality of care.
Methods:
We conducted a scoping review using pre-defined search terms in the following databases: MEDLINE, CINAHL, PsychInfo, Web of Science, Embase, IEEE Digital Library, ACM Digital Library, and ProQuest Dissertations. Two reviewers screened titles and abstracts for relevance, performed full-text reviews of articles meeting inclusion criteria, and used a pile sorting procedure to identify distinguishing characteristics of the tools. Information describing the tools was primarily obtained from identified peer-reviewed sources; supplementary information was also obtained from tool websites and through direct communications with tool creators.
Results:
We identified 18 tools meeting inclusion criteria. Among them, 14 tools used primarily close-ended and/or multi-choice questions, 1 tool used free-text input, and 3 used conversational (chatbot) style. In total, 10 tools were tailored to specific patient subpopulations, and 8 did not specify a target subpopulation. Seven tools included multilingual support, and 12 had the capability to transfer data directly into the electronic health record. Studies of the tools reported on various outcome measures related to usability, efficiency, and/or quality of care.
Conclusions:
The 18 HPI tools we identified varied greatly in their purpose and functionality. There was no consensus on how patient-generated information should be collected or presented to clinicians. Existing tools have undergone inconsistent levels of testing with a wide variety of different outcome measures used in evaluation, including some related to usability, efficiency, and quality of care. There is substantial interest in using digital tools to obtain the HPI from patients, but the outcomes measured have been inconsistent. Future research should focus on whether using HPI tools can lead to improved patient experience and health outcomes. Clinical Trial: N/A
Citation
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Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.