Maintenance Notice

Due to necessary scheduled maintenance, the JMIR Publications website will be unavailable from Wednesday, July 01, 2020 at 8:00 PM to 10:00 PM EST. We apologize in advance for any inconvenience this may cause you.

Who will be affected?

Previously submitted to: JMIR Cancer (no longer under consideration since Sep 15, 2021)

Date Submitted: Aug 17, 2021
Open Peer Review Period: Aug 17, 2021 - Sep 15, 2021
(closed for review but you can still tweet)

NOTE: This is an unreviewed Preprint

Warning: This is a unreviewed preprint (What is a preprint?). Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn (a note "no longer under consideration" will appear above).

Peer-review me: Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period (in this case, a "Peer-Review Me" button to sign up as reviewer is displayed above). All preprints currently open for review are listed here. Outside of the formal open peer-review period we encourage you to tweet about the preprint.

Citation: Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author).

Final version: If our system detects a final peer-reviewed "version of record" (VoR) published in any journal, a link to that VoR will appear below. Readers are then encourage to cite the VoR instead of this preprint.

Settings: If you are the author, you can login and change the preprint display settings, but the preprint URL/DOI is supposed to be stable and citable, so it should not be removed once posted.

Submit: To post your own preprint, simply submit to any JMIR journal, and choose the appropriate settings to expose your submitted version as preprint.

Warning: This is an author submission that is not peer-reviewed or edited.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.

Using a chatbot to reduce emergency department visits and unscheduled hospitalizations among patients with gynecologic malignancies during chemotherapy: a pilot study

  • Ming-Yuan Huang; 
  • Chia-Sui Weng; 
  • Hsiao-Li Kuo; 
  • Yung-Cheng Su

ABSTRACT

Background:

A chatbot is an automatic text-messaging tool that creates a dynamic interaction and simulates a human conversation through text or voice via smartphones or computers. A chatbot could be an effective solution for cancer patients’ follow-up during treatment, and could save time for healthcare providers.

Objective:

We conducted a retrospective cohort pilot study to evaluate whether a chatbot-based collection of patient-reported symptoms during chemotherapy, with automated alerts to clinicians, could decrease emergency department (ED) visits and hospitalizations. A control group received usual care.

Methods:

Self-reporting symptoms were communicated via the chatbot, a Facebook Messenger-based interface for patients with gynecologic malignancies. The chatbot included questions about common symptoms experienced during chemotherapy. Patients could also use the text-messaging feature to speak directly to the chatbot, and all reported outcomes were monitored by a cancer manager. The primary and secondary outcomes of the study were emergency department visits and unscheduled hospitalizations after initiation of chemotherapy after diagnosis of gynecologic malignancies. Multivariate Poisson regression models were applied to assess the adjusted incidence rate ratios (aIRRs) for chatbot use for ED visits and unscheduled hospitalizations after controlling for age, cancer stage, type of malignancy, diabetes, hypertension, chronic renal insufficiency, and coronary heart disease.

Results:

Twenty patients were included in the chatbot group, and 43 in the usual-care group. Significantly lower aIRRs for chatbot use for ED visits (0.27; 95% CI 0.11–0.65; p=0.003) and unscheduled hospitalizations (0.31; 95% CI 0.11–0.88; p=0.028) were noted. Patients using the chatbot approach had lower aIRRs of ED visits and unscheduled hospitalizations compared to usual-care patients.

Conclusions:

The chatbot was helpful for reducing ED visits and unscheduled hospitalizations in patients with gynecologic malignancies who were receiving chemotherapy. These findings are valuable for inspiring the future design of digital health interventions for cancer patients.


 Citation

Please cite as:

Huang MY, Weng CS, Kuo HL, Su YC

Using a chatbot to reduce emergency department visits and unscheduled hospitalizations among patients with gynecologic malignancies during chemotherapy: a pilot study

JMIR Preprints. 17/08/2021:32984

DOI: 10.2196/preprints.32984

URL: https://preprints.jmir.org/preprint/32984

Download PDF


Request queued. Please wait while the file is being generated. It may take some time.

© 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.

Advertisement