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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

Histogram describing the distribution of similar cases per patient. For 165 patients with HCC (hepatocellular carcinoma) we calculated the number of cases which are rated as similar to the individual case by the risk assessment tool. The similarity search provides a two-peak distribution indicating there are groups of similar patients and singular cases which are quite different from the average. This may be caused by the small number of reference cases in the database, another explanation might be that there are patients with exclusive features which are very different from "the average patient".
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Figure 5: Histogram describing the distribution of similar cases per patient. For 165 patients with HCC (hepatocellular carcinoma) we calculated the number of cases which are rated as similar to the individual case by the risk assessment tool. The similarity search provides a two-peak distribution indicating there are groups of similar patients and singular cases which are quite different from the average. This may be caused by the small number of reference cases in the database, another explanation might be that there are patients with exclusive features which are very different from "the average patient".

Mentions: We used a batch version of our decision support system to calculate the Kaplan-Meier estimation for all 165 patients from the CIS diagnosed with HCC. Fig. 5 shows the distribution of the number of cases rated to be similar to a given patient. It has two peaks indicating there are groups of similar patients and singular cases which are quite different from the average. This may be influenced by the small number of reference cases in the database (range: 1 to 25 matched cases), but can also be interpreted that there are patients with exclusive features which are very different from "the average patient".


Interactive decision support in hepatic surgery.

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

Histogram describing the distribution of similar cases per patient. For 165 patients with HCC (hepatocellular carcinoma) we calculated the number of cases which are rated as similar to the individual case by the risk assessment tool. The similarity search provides a two-peak distribution indicating there are groups of similar patients and singular cases which are quite different from the average. This may be caused by the small number of reference cases in the database, another explanation might be that there are patients with exclusive features which are very different from "the average patient".
© Copyright Policy
Related In: Results  -  Collection

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

Figure 5: Histogram describing the distribution of similar cases per patient. For 165 patients with HCC (hepatocellular carcinoma) we calculated the number of cases which are rated as similar to the individual case by the risk assessment tool. The similarity search provides a two-peak distribution indicating there are groups of similar patients and singular cases which are quite different from the average. This may be caused by the small number of reference cases in the database, another explanation might be that there are patients with exclusive features which are very different from "the average patient".
Mentions: We used a batch version of our decision support system to calculate the Kaplan-Meier estimation for all 165 patients from the CIS diagnosed with HCC. Fig. 5 shows the distribution of the number of cases rated to be similar to a given patient. It has two peaks indicating there are groups of similar patients and singular cases which are quite different from the average. This may be influenced by the small number of reference cases in the database (range: 1 to 25 matched cases), but can also be interpreted that there are patients with exclusive features which are very different from "the average patient".

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