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PreAnaesThesia computerized health (PATCH) assessment: development and validation

BACKGROUND: Technological advances in healthcare have enabled patients to participate in digital self-assessment, with reported benefits of enhanced healthcare efficiency and self-efficacy. This report describes the design and validation of a patient-administered preanaesthesia health assessment dig...

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Autores principales: Osman, Tarig, Lew, Eileen, Lum, Elaine Pooi-Ming, van Galen, Louise, Dabas, Rajive, Sng, Ban Leong, Car, Josip
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7666442/
https://www.ncbi.nlm.nih.gov/pubmed/33189131
http://dx.doi.org/10.1186/s12871-020-01202-8
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author Osman, Tarig
Lew, Eileen
Lum, Elaine Pooi-Ming
van Galen, Louise
Dabas, Rajive
Sng, Ban Leong
Car, Josip
author_facet Osman, Tarig
Lew, Eileen
Lum, Elaine Pooi-Ming
van Galen, Louise
Dabas, Rajive
Sng, Ban Leong
Car, Josip
author_sort Osman, Tarig
collection PubMed
description BACKGROUND: Technological advances in healthcare have enabled patients to participate in digital self-assessment, with reported benefits of enhanced healthcare efficiency and self-efficacy. This report describes the design and validation of a patient-administered preanaesthesia health assessment digital application for gathering medical history relevant to preanaesthesia assessment. Effective preoperative evaluation allows for timely optimization of medical conditions and reduces case cancellations on day of surgery. METHODS: Using an iterative mixed-methods approach of literature review, surveys and panel consensus, the study sought to develop and validate a digitized preanaesthesia health assessment questionnaire in terms of face and criterion validity. A total of 228 patients were enrolled at the preoperative evaluation clinic of a tertiary women’s hospital. Inclusion criteria include: age  ≥ 21 years, scheduled for same-day-admission surgery, literacy in English and willingness to use a digital device. Patient perception of the digitized application was also evaluated using the QQ10 questionnaire. Reliability of health assessment questionnaire was evaluated by comparing the percentage agreement of patient responses with nurse assessment. RESULTS: Moderate to good criterion validity was obtained in 81.1 and 83.8% of questions for the paper and digital questionnaires respectively. Of total 3626 response-pairs obtained, there were 3405 (93.4%) concordant and 221 (6.1%) discrepant response-pairs for the digital questionnaire. Discrepant response-pairs, such as ““no/yes” and “unsure/yes”, constitute only 3.7% of total response-pairs. Patient acceptability of the digitized assessment was high, with QQ10 value and burden scores of 76 and 30%, respectively. CONCLUSIONS: Self-administration of digitized preanaesthesia health assessment is acceptable to patients and reliable in eliciting medical history. Further iteration should focus on improving reliability of the digital tool, adapting it for use in other languages and incorporating clinical decision tools. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12871-020-01202-8.
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spelling pubmed-76664422020-11-16 PreAnaesThesia computerized health (PATCH) assessment: development and validation Osman, Tarig Lew, Eileen Lum, Elaine Pooi-Ming van Galen, Louise Dabas, Rajive Sng, Ban Leong Car, Josip BMC Anesthesiol Research Article BACKGROUND: Technological advances in healthcare have enabled patients to participate in digital self-assessment, with reported benefits of enhanced healthcare efficiency and self-efficacy. This report describes the design and validation of a patient-administered preanaesthesia health assessment digital application for gathering medical history relevant to preanaesthesia assessment. Effective preoperative evaluation allows for timely optimization of medical conditions and reduces case cancellations on day of surgery. METHODS: Using an iterative mixed-methods approach of literature review, surveys and panel consensus, the study sought to develop and validate a digitized preanaesthesia health assessment questionnaire in terms of face and criterion validity. A total of 228 patients were enrolled at the preoperative evaluation clinic of a tertiary women’s hospital. Inclusion criteria include: age  ≥ 21 years, scheduled for same-day-admission surgery, literacy in English and willingness to use a digital device. Patient perception of the digitized application was also evaluated using the QQ10 questionnaire. Reliability of health assessment questionnaire was evaluated by comparing the percentage agreement of patient responses with nurse assessment. RESULTS: Moderate to good criterion validity was obtained in 81.1 and 83.8% of questions for the paper and digital questionnaires respectively. Of total 3626 response-pairs obtained, there were 3405 (93.4%) concordant and 221 (6.1%) discrepant response-pairs for the digital questionnaire. Discrepant response-pairs, such as ““no/yes” and “unsure/yes”, constitute only 3.7% of total response-pairs. Patient acceptability of the digitized assessment was high, with QQ10 value and burden scores of 76 and 30%, respectively. CONCLUSIONS: Self-administration of digitized preanaesthesia health assessment is acceptable to patients and reliable in eliciting medical history. Further iteration should focus on improving reliability of the digital tool, adapting it for use in other languages and incorporating clinical decision tools. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12871-020-01202-8. BioMed Central 2020-11-14 /pmc/articles/PMC7666442/ /pubmed/33189131 http://dx.doi.org/10.1186/s12871-020-01202-8 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Osman, Tarig
Lew, Eileen
Lum, Elaine Pooi-Ming
van Galen, Louise
Dabas, Rajive
Sng, Ban Leong
Car, Josip
PreAnaesThesia computerized health (PATCH) assessment: development and validation
title PreAnaesThesia computerized health (PATCH) assessment: development and validation
title_full PreAnaesThesia computerized health (PATCH) assessment: development and validation
title_fullStr PreAnaesThesia computerized health (PATCH) assessment: development and validation
title_full_unstemmed PreAnaesThesia computerized health (PATCH) assessment: development and validation
title_short PreAnaesThesia computerized health (PATCH) assessment: development and validation
title_sort preanaesthesia computerized health (patch) assessment: development and validation
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7666442/
https://www.ncbi.nlm.nih.gov/pubmed/33189131
http://dx.doi.org/10.1186/s12871-020-01202-8
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