Anesth Analg 2006;103:251-252
© 2006 International Anesthesia Research Society
doi: 10.1213/01.ANE.0000215122.69686.B8
LETTER TO THE EDITOR
What Good are Large Databases of Intraoperative Data?
Virginie Luce, MD,
Yves Auroy, MD, and
Dan Benhamou, MD
Department of Anesthesiology; Hôpital Antoine Béclère; Department of Anesthesiology; Hôpital Percy; Clamart, France; dan.benhamou{at}bct.ap-hop-paris.fr
To the Editor:
We read with great interest the article by Reich et al. (1), who described using a large database to predict hypotension after induction of general anesthesia. In 2001 we (2) extracted from our own database (n = 2691) all episodes of intraoperative hypotension that occurred during general anesthesia for general or orthopedic surgery during a 1-yr period and studied the associated factors. The incidence of hypotension was 16.8%. Anesthetic induction with neither etomidate nor propofol modified the occurrence of intraoperative hypotension.
This result is at variance with results obtained by Reich et al. Our own conclusion from this analysis was that retrospective analysis of large databases did not offer us any real opportunity to improve anesthetic practice. We therefore question the efficiency of such databases because factors that were significantly associated with hypotension (i.e., duration of surgery, age, and ASA physical status) are not under the control of the anesthesiologist. Moreover, these intuitively identified factors have already been described in previous studies (3).
Our database was built from data collected using a preformatted sheet describing anesthetic techniques and incidents. The sheet was completed manually for every patient by the attending anesthesiologist, then recorded in the electronic database. We were impressed by the link between the medical database and the administrative records described by Reich et al., a link which unfortunately could not be built in our institution. This certainly would have simplified data collection, reduced the risks of errors, and allowed for more in-depth analysis (4).
Running such databases is likely a valuable tool for teaching, may automate evaluation of outcomes, and may be useful for local quality assurance programs (5). It is, however, difficult to ensure and maintain an exhaustive collection. Maintaining such databases is also time-consuming and expensive, and this raises the issues of patient data confidentiality. Given the investment required, we would hope that analysis of large automated databases would produce novel insights, leading to a real improvement of our anesthetic practice. We admit disappointment that the identified risk factors for hypotension were easily predictable.
In conclusion, such databases have great potential. However, perhaps the data collection needs to be refined to capture those data most likely to produce novel insights to guide anesthetic practice.
REFERENCES
- Reich DL, Hossain S, Krol M, et al. Predictors of hypotension after induction of general anesthesia. Anesth Analg 2005;101:622–8.[Abstract/Free Full Text]
- Luce V, Auroy Y, Ausset S, et al. Intraoperative arterial hypotension recorded by an anaesthesia information management system. Ann Fr Anesth Reanim 2004;23: 788–93.[Web of Science][Medline]
- Sanborn KV, Castro J, Kuroda M, Thys DM. Detection of intraoperative incidents by electronic scanning of computerized anesthesia records: comparison with voluntary reporting. Anesthesiology 1996; 85: 977–87.[Web of Science][Medline]
- Tremper KK. Anesthesia information systems: developing the physiologic phenotype database. Anesth Analg 2005;101: 620–1.[Free Full Text]
- Fasting S, Gisvold SE. Data recording of problems during anaesthesia: presentation of a well-functioning and simple system. Acta Anaesthesiol Scand 1996;40: 1173–83.[Web of Science][Medline]
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D. L. Reich, S. Hossain, and C. A. Bodian
What Good are Large Databases of Intraoperative Data?
Anesth. Analg.,
July 1, 2006;
103(1):
252 - 252.
[Full Text]
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