Literature DB >> 29728246

Quality and accuracy of electronic pre-anesthesia evaluation forms.

Meshari Almeshari1, Mohamed Khalifa2, Ashraf El-Metwally3, Mowafa Househ4, Abdullah Alanazi5.   

Abstract

BACKGROUND AND
OBJECTIVE: Paper-based forms have been widely used to document patient health information for anesthesia; however, hospitals are now switching to electronic patient file documentation for anesthesia. The aim of this study is to compare the quality of paper-based and electronic pre-anesthesia assessment forms.
METHODS: The research conducted in this study was quasi-experimental using a pretest-posttest design without a control group. The study was conducted at King Abdulaziz Medical City, Riyadh (KAMC-RD) during November 2015. Paper-based forms were converted into electronic forms, and the paper-based pre-anesthesia forms were used during the first two weeks of the data collection period while electronic forms were completed in the last two weeks. The quality of each (electronic vs. paper) was evaluated with respect to missing items, errors, and unreadable items. The sample size included all 15 anesthetists working in the pre-anesthesia clinic at KAMC-RD. The anesthetists completed 25 pre-anesthesia forms daily during a five-day week schedule. A total of 500 patient forms were completed during the study (250 paper-based and 250 electronic forms). Anesthetists' satisfaction with the electronic pre-anesthesia form was also measured using a questionnaire.
RESULTS: The electronic form shows significantly higher quality in all assessment categories (missing items, errors, and unreadable items; X² (2, N = 500) = 171.64, p < 0.001). The satisfaction survey found 81.65% of the anesthetists were satisfied with the electronic pre-anesthesia form for all questions.
CONCLUSION: Our study demonstrates that the electronic pre-anesthesia form has better data quality, meets the expectations of anesthetists and aids to decrease missing key preoperative information. This type of approach is imperative for the safety of perioperative patients.
Copyright © 2018. Published by Elsevier B.V.

Entities:  

Keywords:  Anesthesia; Electronic medical record; Informatics; Quality improvement

Mesh:

Year:  2018        PMID: 29728246     DOI: 10.1016/j.cmpb.2018.03.006

Source DB:  PubMed          Journal:  Comput Methods Programs Biomed        ISSN: 0169-2607            Impact factor:   5.428


  4 in total

1.  Reducing defects in the datasets of clinical research studies: conformance with data quality metrics.

Authors:  Naila A Shaheen; Bipin Manezhi; Abin Thomas; Mohammed AlKelya
Journal:  BMC Med Res Methodol       Date:  2019-05-10       Impact factor: 4.615

2.  Staff preferences towards electronic data collection from a national take-home naloxone program: a cross-sectional study.

Authors:  Øystein Bruun Ericson; Desiree Eide; Philipp Lobmaier; Thomas Clausen
Journal:  Subst Abuse Treat Prev Policy       Date:  2022-02-16

3.  Implementation of a Personalized Digital App for Pediatric Preanesthesia Evaluation and Education: Ongoing Usability Analysis and Dynamic Improvement Scheme.

Authors:  Yaron Connelly; Roni Lotan; Yitzhak Brzezinski Sinai; Dan Rolls; Amir Beker; Eilone Abensour; Orit Neudorfer; Daniel Stocki
Journal:  JMIR Form Res       Date:  2022-05-05

4.  Pre-anesthetic clinic internship: new teaching method of pre-anesthesia evaluation for undergraduates.

Authors:  Shao-Hua Zheng; Xiao-Peng Mei
Journal:  J Dent Anesth Pain Med       Date:  2021-06-01
  4 in total

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