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Reporting of Observational Research in ANESTHESIOLOGY: The Importance of Data Quality: Trust but Verify.

A N O N I N VA S I V E blood pressure cuff is applied proximally to a pulse oximetry probe, causing the value of oxygen saturation measured by pulse oximetry to drop transiently with every cuff inflation cycle. Electrocautery causes the heart rate monitor to double with every buzzing zap. Anesthesia providers observe—and lament—vital sign artifacts such as these, whereas the anesthesia information management system (AIMS) dutifully stores the vital sign values that might later be used for research or quality improvement purposes. For these initiatives to be valid, they must be based on data of high quality— that is, data that are accurate, reliable, consistent, and meticulously collected and recorded.1 However, physiologic monitors routinely send artefactual data to AIMS.2 Failure to recognize or minimize these artifacts can negatively impact data quality and secondary uses of the data and potentially lead to inaccurate observations (“garbage in, garbage out”).3 Thus, verification of data quality is crucial and must be considered before proceeding with data analysis.4,5 In this issue of ANESTHESIOLOGY, Hoorweg et al.6 present a novel prospective observational cohort study of the artefactual physiologic data in their locally developed AIMS. They collected their data in a pediatric population undergoing procedures with general anesthesia at a tertiary pediatric hospital. The authors should be applauded for prospectively measuring the occurrence of data artifacts in their AIMS, because there exists a paucity of research on this phenomenon. This study was thoughtfully designed and well conducted and builds on some of the authors’ previous work in an adult population.7 The study reported in this issue defined artefactual measurements by concurrent observations by a single investigator and the attending anesthesiologist. The major finding was that artifacts were present in a substantial number of recordings and that they were associated with deviating status of the measurement, phase of anesthesia, and anesthetic technique. For example, end-tidal carbon dioxide artifacts were more common during an inhalation induction when compared to an intravenous induction, and human errors were responsible for a remarkable number of artifacts. The study informs other pediatric hospitals of areas of potential concern for artefactual AIMS data, as well as methods by which those institutions can prospectively scrutinize their own generation of AIMS artifacts. The authors state their limitations clearly. They used an institution-specific AIMS with one set of monitoring equipment that uses filtering methods that differ from those of other pediatric hospitals. For example, the heart rate was derived from values obtained by either electrocardiogram or pulse plethysmograph, depending on the quality of the signal for either monitor. Thus, the authors’ conclusions are not Reporting of Observational Research in Anesthesiology