Literature DB >> 12455744

Real-time pulse oximetry artifact annotation on computerized anaesthetic records.

Richard Karl Gostt1, Graeme Dennis Rathbone, Adam Paul Tucker.   

Abstract

OBJECTIVES: Adoption of computerised anaesthesia record keeping systems has been limited by the concern that they record artifactual data and accurate data indiscriminately. Data resulting from artifacts does not reflect the patient's true condition and presents a problem in later analysis of the record, with associated medico-legal implications. This study developed an algorithm to automatically annotate pulse oximetry artifacts and sought to evaluate the algorithm's accuracy in routine surgical procedures.
METHODS: MacAnaesthetist is a semi-automatic anaesthetic record keeping system developed for the Apple Macintosh computer, which incorporated an algorithm designed to automatically detect pulse oximetry artifacts. The algorithm labeled artifactual oxygen saturation values < 90%. This was done in real-time by analyzing physiological data captured from a Datex AS/3 Anaesthesia Monitor. An observational study was conducted to evaluate the accuracy of the algorithm during routine surgical procedures (n = 20). An anaesthetic record was made by an anaesthetist using the Datex AS/3 record keeper, while a second anaesthetic record was produced in parallel using MacAnaesthetist. A copy of the Datex AS/3 record was kept for later review by a group of anaesthetists (n = 20), who judged oxygen saturation values < 90% to be either genuine or artifact.
RESULTS: MacAnaesthetist correctly labeled 12 out of 13 oxygen saturations < 90% (92.3% accuracy). A post-operative review of the Datex AS/3 anaesthetic records (n = 8) by twenty anaesthetists resulted in 127 correct responses out of total of 200 (63.5% accuracy). The remaining Datex AS/3 records (n = 12) were not reviewed, as they did not contain any oxygen saturations <90%.
CONCLUSIONS: The real-time artifact detection algorithm developed in this study was more accurate than anaesthetists who post-operatively reviewed records produced by an existing computerised anaesthesia record keeping system. Algorithms have the potential to more accurately identify and annotate artifacts on computerised anaesthetic records, assisting clinicians to more correctly interpret abnormal data.

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Year:  2002        PMID: 12455744     DOI: 10.1023/a:1020785323889

Source DB:  PubMed          Journal:  J Clin Monit Comput        ISSN: 1387-1307            Impact factor:   2.502


  8 in total

1.  Automatic artifact identification in anaesthesia patient record keeping: a comparison of techniques.

Authors:  S W Hoare; P C Beatty
Journal:  Med Eng Phys       Date:  2000-10       Impact factor: 2.242

2.  Integrating computerized anesthesia charting into a hospital information system.

Authors:  X Wang; R M Gardner; P R Seager
Journal:  Int J Clin Monit Comput       Date:  1995-05

3.  The present and future medicolegal importance of record keeping in anesthesia and intensive care: the case for automation.

Authors:  R F Gibbs
Journal:  J Clin Monit       Date:  1989-10

4.  Automated charting of physiological variables in anesthesia: a quantitative comparison of automated versus handwritten anesthesia records.

Authors:  J G Lerou; R Dirksen; M van Daele; G M Nijhuis; J F Crul
Journal:  J Clin Monit       Date:  1988-01

5.  The Australian Incident Monitoring Study. Which monitor? An analysis of 2000 incident reports.

Authors:  R K Webb; J H van der Walt; W B Runciman; J A Williamson; J Cockings; W J Russell; S Helps
Journal:  Anaesth Intensive Care       Date:  1993-10       Impact factor: 1.669

6.  The Australian Incident Monitoring Study. The pulse oximeter: applications and limitations--an analysis of 2000 incident reports.

Authors:  W B Runciman; R K Webb; L Barker; M Currie
Journal:  Anaesth Intensive Care       Date:  1993-10       Impact factor: 1.669

7.  Anesthesia record keeping.

Authors:  J H Eichhorn
Journal:  Int J Clin Monit Comput       Date:  1993-05

8.  Computerized patient anesthesia records: less time and better quality than manually produced anesthesia records.

Authors:  D W Edsall; P Deshane; C Giles; D Dick; B Sloan; J Farrow
Journal:  J Clin Anesth       Date:  1993 Jul-Aug       Impact factor: 9.452

  8 in total
  2 in total

1.  Automated anesthesia artifact analysis: can machines be trained to take out the garbage?

Authors:  Allan F Simpao; Olivia Nelson; Luis M Ahumada
Journal:  J Clin Monit Comput       Date:  2020-09-12       Impact factor: 2.502

2.  Artifacts in research data obtained from an anesthesia information and management system.

Authors:  Nathalie P Kool; Judith A R van Waes; Jilles B Bijker; Linda M Peelen; Leo van Wolfswinkel; Jurgen C de Graaff; Wilton A van Klei
Journal:  Can J Anaesth       Date:  2012-07-18       Impact factor: 5.063

  2 in total

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