Outcome After Self-Triage App Referral in Urgent Direct-to-Consumer Telemedicine Encounter.
Tarso Augusto Duenhas AccorsiFlavio Tocci MoreiraAnderson Aires EduardoRenata Albaladejo MorbeckKaren Francine KöhlerKarine De Amicis LimaCarlos Henrique Sartorato PedrottiPublished in: Telemedicine journal and e-health : the official journal of the American Telemedicine Association (2024)
Background: The quantification of self-triage effectiveness, guided by mobile applications, in urgent direct-to-consumer telemedicine (TM) encounters requires further investigation. The objective of this study was to evaluate the outcomes of referral guidance provided by a symptom-based self-management mobile application decision algorithm in the context of remote urgent care assessments. Methods: An observational retrospective single-center study was conducted from May 2022 to December 2023. The inclusion criteria encompassed individuals aged >18 years old, and those spontaneously seeking virtual emergency care through the EINSTEIN CONECTA application. Patients experiencing connectivity issues, preventing completion of the encounter, were excluded. The primary outcomes included the rate of patient concurrence with the algorithm's recommendation for seeking in-person emergency care and the referral rate to face-to-face assessment among cases evaluated through TM. The application's algorithm employs scientific evidence based on symptoms to recommend referrals to emergency departments (EDs). Results: Out of 88,834 patients connected to the TM Center, self-triage obviated the need for virtual physician assessment in 53,302 (60%) encounters. A total of 35,532 patients were remotely evaluated by 316 on-duty physicians, resulting in 1,125 ICD-coded diagnoses. Among these, 21,722 (61.1%) were initially advised by self-triage to visit the ED, with subsequent medical assessment leading to in-person referrals in 6,354 (29.3%) of the evaluations. Of the 13,810 patients recommended to continue with virtual care post-self-triage, 157 (1.1%) were referred for in-person assessment. Conclusions: Self-triage effectively reduced the need for physician encounters in approximately three-fifths of TM consultations. Despite being based on scientific evidence, symptom-based referral algorithms demonstrated high sensitivity but poor correlation with physician decision-making.
Keyphrases
- emergency department
- primary care
- healthcare
- end stage renal disease
- ejection fraction
- newly diagnosed
- machine learning
- palliative care
- deep learning
- prognostic factors
- randomized controlled trial
- systematic review
- multiple sclerosis
- decision making
- chronic pain
- physical activity
- insulin resistance
- skeletal muscle
- sleep quality
- resting state
- cross sectional