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A1378
October 17, 2006 1:30 PM - 3:00 PM Room N426a |
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| Decision Support System Increases Data Quality on Preoperative Record | ||||||||||||||||||||||||||||
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Fabian O. Kooij, M.D., Toni Klok, M.D., Markus W. Hollmann, M.D., Ph.D., Jasper E. Kal, M.D., Ph.D. Anesthesiology, Onze Lieve Vrouwe Gasthuis/Academical Medical Center, Amsterdam, Netherlands |
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Introduction Data quality on pre-operative records can be improved. Especially negative findings have a tendency to be left out. In order to identify high risk patients, one should document the risk factors involved. With the implementation of Anesthesia Information Management Systems (AIMS), quality of preoperative screening data and documentation of risk factors may supposedly be improved by using mandatory fields on the preoperative screening form. Materials and Methods Medical information of all patients scheduled for elective surgery in our 12 OR regional teaching hospital, is routinely entered in our AIMS (Metavision, iMDsoft, Tel Aviv, Israel). For this study, we used the departmental guideline for prevention of postoperative nausea and vomiting (PONV). According to our PONV prevention guideline, patients are at high risk for PONV if at least three of the following risk factors are present: female gender, previous history of PONV or motion sickness, non-smoker status, and anticipated use of postoperative opioids. [1, 2] In order to be able to identify these high risk patients, all four risk factors should be documented. Therefore, we changed these risk factors on the pre-operative screening form from optional to mandatory. To study the effect on data quality, we studied the percentage of patients with these risk factors documented from eight weeks before to ten weeks after this change (for each seperate risk factor). Results Between November 6th 2005 and March 14th 2006, 4058 patients visited our preoperative clinic. Of these, 1785 patients (44 %) visited before the mandatory fields were installed and 2273 visited thereafter. Data quality as measured by the percentage of patients with the actual risk factor specified, improved for three out of four risk factors. This resulted in a significant improvement in identification of patients entitled to PONV prophylaxis. (Table 1) Conclusions Anesthesia information management systems allow for direct data quality control by making fields mandatory. In our study, this improved the quality of data that was entered and allowed for more accurate identification of patients entitled to PONV prophylaxis. References 1. Apfel CC, Kranke P, Eberhart LHJ, Roos A, Roewer N; Comparison of predictive models for postoperative nausea and vomiting; BJA 2002(88-2):234-40 2. v/d Bosch JE, Kalkman CK, et al; Assessing the applicability of scoring systems for predicting postoperative nausea and vomiting; Anaesthesia 2005(60):323-331.[table1] Anesthesiology 2006; 105: A1378 |
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