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

被引:2
|
作者
Huang, Ming -Yuan [1 ,2 ]
Weng, Chia-Sui [3 ]
Kuo, Hsiao-Li [3 ,4 ]
Su, Yung-Cheng [5 ]
机构
[1] Mackay Mem Hosp, Dept Emergency, Taipei, Taiwan
[2] MacKay Med Coll, Dept Med, New Taipei, Taiwan
[3] MacKay Mem Hosp, Dept Obstet & Gynecol, Taipei, Taiwan
[4] Chang Gung Univ, Sch Nursing, New Taipei, Taiwan
[5] Chia Yi Christian Hosp, Ditmanson Med Fdn, Dept Emergency Med, Chiayi, Taiwan
关键词
Chatbot; Patient -reported symptoms; Gynecologic malignancies; REPORTED OUTCOMES; CANCER; CARE; PAIN;
D O I
10.1016/j.heliyon.2023.e15798
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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 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 Messengerbased interface for patients with gynecologic malignancies. The chatbot included questions about common symptoms experienced during chemotherapy. Patients could also use the textmessaging 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.Result: 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.
引用
收藏
页数:7
相关论文
共 50 条
  • [1] RETROSPECTIVE COHORT STUDY OF RATES OF RETURN EMERGENCY DEPARTMENT VISITS AMONG PATIENTS TRANSPORTED HOME BY AMBULANCE
    Munjal, Kevin G.
    Shastry, Siri
    Chapin, Hugh
    Tan, Nadir
    Misra, Anjali
    Greenberg, Eric
    Traisman, Benjamin
    Kleiman, Rose
    Loo, George
    Grudzen, Corita
    Chason, Kevin
    Richardson, Lynne D.
    [J]. JOURNAL OF EMERGENCY MEDICINE, 2020, 59 (01): : 147 - 152
  • [2] Predicting Unscheduled Emergency Department Return Visits Among Older Adults: Population-Based Retrospective Study
    Chen, Rai-Fu
    Cheng, Kuei-Chen
    Lin, Yu-Yin
    Chang, I-Chiu
    Tsai, Cheng-Han
    [J]. JMIR MEDICAL INFORMATICS, 2021, 9 (07)
  • [3] Association of skeletal muscle relaxers and antihistamines on mortality, hospitalizations, and emergency department visits in elderly patients: a nationwide retrospective cohort study
    Carlos A Alvarez
    Eric M Mortensen
    Una E Makris
    Dan R Berlowitz
    Laurel A Copeland
    Chester B Good
    Megan E Amuan
    Mary Jo V Pugh
    [J]. BMC Geriatrics, 15
  • [4] Association of skeletal muscle relaxers and antihistamines on mortality, hospitalizations, and emergency department visits in elderly patients: a nationwide retrospective cohort study
    Alvarez, Carlos A.
    Mortensen, Eric M.
    Makris, Una E.
    Berlowitz, Dan R.
    Copeland, Laurel A.
    Good, Chester B.
    Amuan, Megan E.
    Pugh, Mary Jo V.
    [J]. BMC GERIATRICS, 2015, 15
  • [5] Emergency department visits during outpatient parenteral antimicrobial therapy: a retrospective cohort study
    Shrestha, Nabin K.
    Kim, So Lim
    Rehm, Susan J.
    Everette, Angela
    Gordon, Steven M.
    [J]. JOURNAL OF ANTIMICROBIAL CHEMOTHERAPY, 2018, 73 (07) : 1972 - 1977
  • [6] Machine learning models for predicting unscheduled return visits of patients with abdominal pain at emergency department and validation during COVID-19 pandemic: A retrospective cohort study
    Hsu, Chun-Chuan
    Chu, Cheng-C. J.
    Ng, Chip-Jin
    Lin, Ching-Heng
    Lo, Hsiang-Yun
    Chen, Shou-Yen
    [J]. MEDICINE, 2024, 103 (08) : E37220
  • [7] Return visits to the pediatric emergency department: A multicentre retrospective cohort study
    Meyer-Macaulay, Colin B.
    Truong, Mimi
    Meckler, Garth D.
    Doan, Quynh H.
    [J]. CANADIAN JOURNAL OF EMERGENCY MEDICINE, 2018, 20 (04) : 578 - 585
  • [8] THE IMPACT OF ROUTINE ESAS USE ON EMERGENCY DEPARTMENT VISITS AND HOSPITALIZATIONS: A POPULATION-BASED RETROSPECTIVE MATCHED COHORT STUDY
    Barbera, Lisa
    Sutradhar, Rinku
    Earle, Craig
    Mittman, Nicole
    Seow, Hsien Yeang
    Howell, Doris
    Li, Qing
    Thiruchelvam, Deva
    [J]. RADIOTHERAPY AND ONCOLOGY, 2019, 139 : S90 - S91
  • [9] A LARGE-SCALE RETROSPECTIVE STUDY OF EMERGENCY DEPARTMENT VISITS OR HOSPITALIZATIONS FOR ANAPHYLAXIS AMONG PATIENTS WITH EMPLOYER-SPONSORED HEALTH INSURANCE
    Landsman-Blumberg, P.
    Wei, W.
    Douglas, D.
    Smith, D. M.
    Camargo, C. A.
    [J]. VALUE IN HEALTH, 2012, 15 (04) : A60 - A60
  • [10] Factors Affecting Unscheduled Return Visits to the Emergency Department among Minor Head Injury Patients
    Wang, Kuo-Cheng
    Chaou, Chung-Hsien
    Liu, Peng-Huei
    Chien, Cheng-Yu
    Lee, Ching-Hsing
    [J]. BIOMED RESEARCH INTERNATIONAL, 2017, 2017