Paperless anesthesia: uses and abuses of these data
Corresponding Author
Brian J. Anderson
Department of Anaesthesiology, University of Auckland, Auckland, New Zealand
Correspondence
Brian J. Anderson, Department of Anaesthesiology, University of Auckland School of Medicine, Auckland, New Zealand
Email: [email protected]
Search for more papers by this authorAlan F. Merry
Department of Anaesthesiology, University of Auckland, Auckland, New Zealand
Search for more papers by this authorCorresponding Author
Brian J. Anderson
Department of Anaesthesiology, University of Auckland, Auckland, New Zealand
Correspondence
Brian J. Anderson, Department of Anaesthesiology, University of Auckland School of Medicine, Auckland, New Zealand
Email: [email protected]
Search for more papers by this authorAlan F. Merry
Department of Anaesthesiology, University of Auckland, Auckland, New Zealand
Search for more papers by this authorSummary
Demonstrably accurate records facilitate clinical decision making, improve patient safety, provide better defense against frivolous lawsuits, and enable better medical policy decisions. Anesthesia Information Management Systems (AIMS) have the potential to improve on the accuracy and reliability of handwritten records. Interfaces with electronic recording systems within the hospital or wider community allow correlation of anesthesia relevant data with biochemistry laboratory results, billing sections, radiological units, pharmacy, earlier patient records, and other systems. Electronic storage of large and accurate datasets has lent itself to quality assurance, enhancement of patient safety, research, cost containment, scheduling, anesthesia training initiatives, and has even stimulated organizational change. The time for record making may be increased by AIMS, but in some cases has been reduced. The question of impact on vigilance is not entirely settled, but substantial negative effects seem to be unlikely. The usefulness of these large databases depends on the accuracy of data and they may be incorrect or incomplete. Consequent biases are threats to the validity of research results. Data mining of biomedical databases makes it easier for individuals with political, social, or economic agendas to generate misleading research findings for the purpose of manipulating public opinion and swaying policymakers. There remains a fear that accessibility of data may have undesirable regulatory or legal consequences. Increasing regulation of treatment options during the perioperative period through regulated policies could reduce autonomy for clinicians. These fears are as yet unsubstantiated.
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