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PreAnaesThesia computerized health (PATCH) assessment: development and validation.

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  • 1Centre for Population Health Sciences, Lee Kong Chian School of Medicine, Nanyang Technological University (Singapore), Singapore, Singapore.

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A new digital preanesthesia health assessment tool is reliable and acceptable for patients, improving medical history collection. This technology enhances healthcare efficiency and patient self-efficacy in preoperative evaluations.

Keywords:
Computer-assisted history-taking systemDigital healthPreanaesthesia assessment

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Area of Science:

  • Health Informatics
  • Digital Health
  • Preoperative Assessment

Background:

  • Technological advancements facilitate patient digital self-assessment, improving healthcare efficiency and self-efficacy.
  • A patient-administered digital application was developed for preanesthesia health assessment to gather crucial medical history.
  • Effective preoperative evaluation optimizes patient conditions and minimizes same-day surgery cancellations.

Purpose of the Study:

  • To develop and validate a digitized preanesthesia health assessment questionnaire.
  • To assess the face and criterion validity of the digital tool.
  • To evaluate patient perception and reliability of the digital health assessment.

Main Methods:

  • An iterative mixed-methods approach including literature review, surveys, and panel consensus.
  • Enrollment of 228 patients at a tertiary women's hospital's preoperative evaluation clinic.
  • Evaluation of patient perception using the QQ10 questionnaire and reliability via comparison with nurse assessments.

Main Results:

  • The digital questionnaire demonstrated moderate to good criterion validity (83.8%).
  • High concordance (93.4%) between patient and nurse assessments for the digital tool.
  • High patient acceptability with a QQ10 score of 76 and a burden score of 30%.

Conclusions:

  • Patient self-administration of the digital preanesthesia health assessment is acceptable and reliable.
  • The digital tool effectively elicits necessary medical history for preoperative evaluations.
  • Future iterations should enhance reliability, support multilingual use, and integrate clinical decision tools.