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Updated: May 24, 2026

E-Patient Counseling Trial (E-PACO): Computer Based Education versus Nurse Counseling for Patients to Prepare for Colonoscopy
Published on: August 1, 2019
An analysis of computer-assisted pre-screening prior to elective surgery
C Grant1, G L Ludbrook, E J O'Loughlin
1Department of Acute Care Medicine, University of Adelaide, South Australia, Australia. cliff.grant@adelaide.edu.au
Guided patient self-assessment via telephone offers a reliable preoperative triage tool. This method effectively identifies patients suitable for same-day surgery assessment, potentially streamlining care.
Area of Science:
- Anesthesiology
- Health Informatics
- Patient Triage
Background:
- Preoperative assessment is crucial for surgical safety and resource allocation.
- Traditional outpatient preoperative clinics can be resource-intensive.
- Exploring efficient triage tools is essential for modern healthcare.
Purpose of the Study:
- To evaluate guided patient self-assessment via telephone as an early preoperative triage tool.
- To compare telephone assessment with traditional face-to-face anaesthetist evaluation.
- To determine the feasibility of streaming patients directly to day of surgery assessment.
Main Methods:
- A computer-assisted telephone questionnaire was administered by non-clinicians to 514 elective surgery patients.
- Assessments were compared to face-to-face interviews and examinations by anaesthetists.
- Specialist anaesthetists reviewed data to identify patients suitable for bypassing outpatient assessment.
Main Results:
- Telephone assessment quality was comparable to face-to-face interviews for most patients.
- 60% of patients (398/514) were deemed suitable for day of surgery assessment.
- Telephone triage demonstrated high sensitivity (98%) and specificity (97%) for patient classification.
Conclusions:
- Remote computer-assisted assessment effectively gathers quality patient health information.
- This approach enables efficient early patient work-up and triage.
- Utilizing telephone self-assessment can potentially reduce healthcare costs through resource optimization.
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