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Interactive decision support in hepatic surgery.

Dugas M, Schauer R, Volk A, Rau H - BMC Med Inform Decis Mak (2002)

Bottom Line: Hepatic surgery is characterized by complicated operations with a significant peri- and postoperative risk for the patient.The results of the risk estimation are consistent with the observed survival data, but must be interpreted with caution because of the limited number of matching reference cases.Critical issues for the decision support system are clinical integration, a transparent and reliable knowledge base and user feedback.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Medical Informatics, Biometrics and Epidemiology, University of Munich, D-81377 Munich, Germany. dug@ibe.med.uni-muenchen.de

ABSTRACT

Background: Hepatic surgery is characterized by complicated operations with a significant peri- and postoperative risk for the patient. We developed a web-based, high-granular research database for comprehensive documentation of all relevant variables to evaluate new surgical techniques.

Methods: To integrate this research system into the clinical setting, we designed an interactive decision support component. The objective is to provide relevant information for the surgeon and the patient to assess preoperatively the risk of a specific surgical procedure. Based on five established predictors of patient outcomes, the risk assessment tool searches for similar cases in the database and aggregates the information to estimate the risk for an individual patient.

Results: The physician can verify the analysis and exclude manually non-matching cases according to his expertise. The analysis is visualized by means of a Kaplan-Meier plot. To evaluate the decision support component we analyzed data on 165 patients diagnosed with hepatocellular carcinoma (period 1996-2000). The similarity search provides a two-peak distribution indicating there are groups of similar patients and singular cases which are quite different to the average. The results of the risk estimation are consistent with the observed survival data, but must be interpreted with caution because of the limited number of matching reference cases.

Conclusion: Critical issues for the decision support system are clinical integration, a transparent and reliable knowledge base and user feedback.

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Related in: MedlinePlus

Example of a similarity search (section): Selected clinically important characteristics for patients matching Fig. 2. By clicking on the case number all information concering a specific patient can be displayed. Individual patients can be excluded from the analysis and the Kaplan-Meier-Plot (Fig. 3) can be recalculated.
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Figure 4: Example of a similarity search (section): Selected clinically important characteristics for patients matching Fig. 2. By clicking on the case number all information concering a specific patient can be displayed. Individual patients can be excluded from the analysis and the Kaplan-Meier-Plot (Fig. 3) can be recalculated.

Mentions: After submitting the form to the system it connects to the database to retrieve the appropriate results based on the specified parameters and their ranges. The system then computes the data necessary for the Kaplan-Meier plot and generates a web page containing the plot and the underlying data (Fig. 3, Fig. 4).


Interactive decision support in hepatic surgery.

Dugas M, Schauer R, Volk A, Rau H - BMC Med Inform Decis Mak (2002)

Example of a similarity search (section): Selected clinically important characteristics for patients matching Fig. 2. By clicking on the case number all information concering a specific patient can be displayed. Individual patients can be excluded from the analysis and the Kaplan-Meier-Plot (Fig. 3) can be recalculated.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC113749&req=5

Figure 4: Example of a similarity search (section): Selected clinically important characteristics for patients matching Fig. 2. By clicking on the case number all information concering a specific patient can be displayed. Individual patients can be excluded from the analysis and the Kaplan-Meier-Plot (Fig. 3) can be recalculated.
Mentions: After submitting the form to the system it connects to the database to retrieve the appropriate results based on the specified parameters and their ranges. The system then computes the data necessary for the Kaplan-Meier plot and generates a web page containing the plot and the underlying data (Fig. 3, Fig. 4).

Bottom Line: Hepatic surgery is characterized by complicated operations with a significant peri- and postoperative risk for the patient.The results of the risk estimation are consistent with the observed survival data, but must be interpreted with caution because of the limited number of matching reference cases.Critical issues for the decision support system are clinical integration, a transparent and reliable knowledge base and user feedback.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Medical Informatics, Biometrics and Epidemiology, University of Munich, D-81377 Munich, Germany. dug@ibe.med.uni-muenchen.de

ABSTRACT

Background: Hepatic surgery is characterized by complicated operations with a significant peri- and postoperative risk for the patient. We developed a web-based, high-granular research database for comprehensive documentation of all relevant variables to evaluate new surgical techniques.

Methods: To integrate this research system into the clinical setting, we designed an interactive decision support component. The objective is to provide relevant information for the surgeon and the patient to assess preoperatively the risk of a specific surgical procedure. Based on five established predictors of patient outcomes, the risk assessment tool searches for similar cases in the database and aggregates the information to estimate the risk for an individual patient.

Results: The physician can verify the analysis and exclude manually non-matching cases according to his expertise. The analysis is visualized by means of a Kaplan-Meier plot. To evaluate the decision support component we analyzed data on 165 patients diagnosed with hepatocellular carcinoma (period 1996-2000). The similarity search provides a two-peak distribution indicating there are groups of similar patients and singular cases which are quite different to the average. The results of the risk estimation are consistent with the observed survival data, but must be interpreted with caution because of the limited number of matching reference cases.

Conclusion: Critical issues for the decision support system are clinical integration, a transparent and reliable knowledge base and user feedback.

Show MeSH
Related in: MedlinePlus